Current World Environemnt Journal Volume 8, Number 1 by Nilofar Iqbal

Current World Environment

Vol. 8(1), 01-12 (2013)

Agricultural Vulnerability and Adaptation to Climatic Changes in Malaysia: Review on Paddy Sector MD. MAHMUDUL ALAM1*, CHAMHURI SIWAR1, ABDUL HAMID JAAFAR2, BASRI TALIB2 and KHAIRULMAINI BIN OSMAN SALLEH3 *Institute for Environment and Development (LESTARI), National University of Malaysia (UKM), Malaysia 2 Faculty of Economics and Management, National University of Malaysia (UKM), Malaysia. 3 Department of Geography, University of Malaya, Malaysia. DOI : http://dx.doi.org/10.12944/CWE.8.1.01 (Received: December 30, 2012; Accepted: February 14, 2013) ABSTRACT Climate change has mixed impacts on agriculture and the impacts are different in terms of areas, periods and crops. The changing factors of climate have been exerting strong negative impacts on Malaysian agriculture, which is apprehended to result in shortages of water and other resources for long term, worsening soil condition, disease and pest outbreaks on crops and livestock, sea-level rise, and so on. Due to climate change, agricultural productivity and profitability is declining. Despite continuous increases of government subsidy, area of paddy plantation is decreasing and the adaption practices are ineffective. As climate change is universal and its existence is indefinite, the farmers need to adapt to and find ways to mitigate the damages of climatic variation in order to sustain agricultural productivity and attain food security for them.

Key words: Climate Change, Agriculture, Food Security, Sustainability, Adaptation, Mitigation, Vulnerability, Malaysia.

INTRODUCTION The changing patterns of climate factors adversely affect the social, economic and environmental agents all over the world. The agriculture is fully dependent on the factors of climate and consequences of climate change are of adverse impacts on agriculture and agriculture relevant stakeholders. Among all the stakeholders, farmer community is the most affected and risk group due to their full dependency on agriculture. The climatic factors as expressed by the amount of rainfall, sunshine hours, temperature, relative humidity and length of the drought period result in year-to-year and area-to-area variability of crop production. Variability of production unit causes indirect impacts on the social and economic status of the livelihood of farming community along with

several direct impacts- e.g. health hazards, frequent sickness etc. The impacts of climate change are not limited to any geographical boundary or timeframe. Some of the aspects are long term and related to national or international security such as, soil erosion, chemical poisoning or nuclear waste (Daly and Cobb, 1990), and some issues are related to daily quality of life such as, water pollution, shortage of food or resources (Homer-Dixon, 1992; Alam et al., 2011d). The combined effects of these issues are difficult to predict such as, natural and environmental catastrophes in recent times- floods, landslides, long periods of drought etc (United Nations, 1997), and these cause vulnerability in terms of yield, farm profitability, regional economy and hunger (Reilly, 1999; Schimmelpfenning et al., 1996; Siwer et al., 2009).

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Several impacts of climate change affect various sectors, regions and factors in different ways (Klein et al., 2005). Agricultural sector dominates the economies of 25% of the world’s countries, where half of the world’s workforce is currently employed. Due to the climate change the agricultural sector is vulnerable in terms of productivity and economic benefits. This paper provides a brief review on the global and Malaysian perspective of climate change, and its impacts on Malaysian agriculture and relevant adaptation practices, and policy recommendations for better coping with the changing nature of climatic factors. Global scenario of climate change Due to increasing atmospheric concentration of carbon dioxide and other trace gases, since the beginning of the 1980s, many climatologists predicted significant global warming in the coming decades. The Intergovernmental Panel on Climate Change (IPCC) was established in 1988 by the United Nations Environmental Programme (UNEP) and the World Meteorological Organization (WMO) to assess the scientific, technical and socioeconomic information relevant for the understanding of human induced climate change, its potential impacts and options for mitigation and adaptation. National Academy of Science (2001) found trends of increasing average temperature and more volatile rainfall patterns. IPCC report 2007 shows further scientific evidence that the world’s climate systems are changing faster than predicted, raising the likelihood of more rapid and damaging changes. It also motions 90-95% likelihood that changes in modern climate have been caused by human actions (Figure 1). According to the Third Assessment Report of IPCC (2001), if the levels of emissions are not reduced, the global average temperature will increase by 1.4°C to 5.8°C between 1990 and 2100. Another projection pointed to an increase in the average global temperature of 2.4ºC between 1990 and 2100, with 95% chance that the change will be between 1.0ºC and 4.9ºC (Webster et al., 2002). Other studies have estimated that the average global temperature is likely to rise by between 0.3ºC and 1.3ºC during the next 30 years (Zwiers, 2002).

The warming to a great extent, during the next 30 years, will be due to emissions that have already occurred. Over the longer term, the degree and pace of warming depends mainly on current and near future emissions. There is more than 50% chance that in the longer term the temperature rise would exceed 5 oC. Due to the climate change impacts, the amount of 5% of the global GDP, which is regionally going up to even 20%, is expected to amount at annual loss in future (Stern, 2007: iv). Different behaviors of climate factors were found by different studies based on place and time differences. Average precipitation is expected to increase globally (IPCC, 2001), but the magnitude of regional precipitation changes as well as varies among models: with the range 0-50% where the direction of change is strongly indicated, and around -30 to +30% where it is not. For some areas, it shows a positive trend in the daily intensity and a tendency toward higher frequencies of extreme rainfall in the last few decades (Houghton et al., 1996). Among them, the main areas where significant positive trends have been observed are USA (Karl et al., 1995; Trenberth, 1998; Kunkel et al., 1999), eastern and north-eastern Australia (Suppiah and Hennessey, 1998; Plummer et al., 1999), South Africa (Mason et al., 1999), UK (Osborn et al., 2000), and northern and central Italy (Brunetti et al., 2000, 2001). Fuhrer et al., (2006) reviewed on Europe that both rain-day frequency and intensity during winter increases to the north (about 45°N), while the rain-day frequency decreases to the south. This is also consistent with increases of mean winter precipitation by 10 to 30% over most of the central and northern Europe, and decreases over the Mediterranean. In summer, the most notable change is strong decreases in the frequency of wet days, for instance to about half in the Mediterranean, along with a 20 to 50% decrease of mean summer precipitation. In the tropics, models show an increase in Africa, a small increase in South America, but no change in Southeast Asia. Summer precipitation is expected to decrease in the Mediterranean-basin and in regions of Central America and north-western Europe. Bonaccorso et al., (2005) analyzed the trends of annual maximum rainfall series of Mediterranean areas and found different behavior

ALAM et al., Curr. World Environ., Vol. 8(1), 01-12 (2013) patterns based on the different time scales, particularly shorter duration series shows increasing trends and longer duration series shows decreasing trends. In most cases when there is a positive trend in rainfall intensity, an increase in total precipitation has also been observed (Groisman et al., 1999). However this relationship is not universal. Observation shows that there is an increase in heavy precipitation in some areas (i. e. Italy) with a tendency toward a decrease in total precipitation (Brunetti et al., 2001). The costs costs due to impacts of climate change have already been tried to point out by different institutions (WBGU 2003: 17; Stern 2007: iv). The joint research centre PESETA of the EC has calculated the costs in 1995 arising from sea level rise with and without adaptation measures by 2020 and 2080 (Commission of the European Communities, 2007: 10). Oxfam estimates that adaptation in developing countries will cost at least USD $50–$80 billion each year, based on the estimation from the World Bank, Stern and IPCC (Raworth, 2007). The costs of adapting existing urban water infrastructure in Africa alone have been estimated at USD $1.05–$2.65 billion annually, excluding the cost of rehabilitating deficient infrastructure. In Africa, the costs of climate-proofing new development are also likely to rise by USD $1–$2.55 billion a year (Muller, 2007). The IPCC mentioned Africa as one of the most continents vulnerable to climate change (Boko et al., 2007). Very few parts of Africa will be benefited from a rising temperature, unlike some parts of the northern hemisphere (Canada, Japan, Russia). The UN Framework Convention on Climate Change (UNFCCC) identifies a list of 49 Least Developed Countries (LDCs), which are at high risk from climate change, and out of these countries at stake, 33 are located in Africa. A study analyzed that due to climate change, Southern Africa will lose more than 30% of its main crop, maize, by 2030, and Asia, especially South Asia and South East Asia will lose top 10% of many regional staples, such as rice, millet and maize (Lobell et al., 2008) All of the projections of the future climate change are based on the extrapolation of current trends with logical assumptions about future

emissions of greenhouse gases, prospective economic and industrial growth, population growth, technological progress etc., which are not phenomenon for any particular country , rather they are global concern. Climate change in malaysia According to the United Nations Development Report, carbon dioxide emissions in Malaysia increased by 221% during the period of 1990 to 2004, and the country is included in the list of 30 biggest greenhouse gas emitters. Curb Global Warming (2007) quoted from the Associated Press (AP) that rapid growth in emissions has occurred even though Malaysia ratified the Kyoto Protocol and has taken several initiatives to use renewable energy as well as ways to cut emissions. Currently Malaysia ranks as the 26th largest greenhouse gas emitter in the world with a population of about 27 million, and it appears likely to move up the list quickly due to the growth rate of emissions. Due to high greenhouse gas emissions, the temperature is projected to rise by 0.3oC to 4.5oC. Warmer temperature will cause a rise in sea level about 95cm over hundred periods. The changes in rainfall may fluctuate from about -30% to +30%. This change will reduce crop yield and and will cause drought in many areas with a consequence that cultivation of some crops such as rubber, oil palm and cocoa will not be possible (MOSTE, 2001). Table 1 shows the projection of positive rainfall changes by 2050 in few areas of Malaysia. The projection shows maximum monthly precipitation will increase up to 51% in Pahang, Kelantan and Terengganu, while minimum precipitation decreases between 32% to 61% for all over Peninsular Malaysia. Consequently, annual rainfall will increase up to 10% in Kelantan, Terengganu, Pahang and North West Coast, and decrease up to 5% in Selangor and Johor (NAHRIM, 2006). This variation of climate factors will make the agricultural system vulnerable in Malaysia. Climate change and malaysian agriculture The global effect of climate change on agricultural production is minimum to moderate, where regional impacts are significant for many areas. Regional variations in gains and losses result

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in a slight overall changes in world cereal grain productivity. Some studies addressed climate change impacts on rice yields, which vary greatly, in South and Southeast Asia (Matthews et al., 1994a, 1994b). Climatic impacts on agriculture span a wide range depending on the climate scenario, geographical scope, and study. While large changes were predicted for China, to a certain extent warming would be beneficial with yield increasing due to diversification of cropping systems. In case of Japan, the positive effects of CO2 on rice yields would be generally more than offset any negative climatic effects (MOSTE, 2001). Under current climate change scenario, temperature above 25oC may decline grain mass of 4.4% per 1oC rise (Tashiro and Wardlaw, 1989), and grain yield may decline as much as 9.6%10.0% per 1oC rise (Baker and Allen, 1993), where average temperature in rice growing areas in Malaysia is about 26 oC. Singh et al., (1996) mentioned that the actual farm yields of rice in Malaysia vary from 3-5 tons per hectare, where potential yield is 7.2 tons. It also mentioned that a decline of rice yield between 4.6%-6.1% per 1oC temperature increases under the present CO2 level, but a doubling of CO2 concentration (from present level 340ppm to 680ppm) may offset the detrimental effect of 4 o C temperature increase on rice production in Malaysia. In a recent study it is found that a 1% increase in temperature leads to a 3.44% decrease in current paddy yield and 0.03% decrease in paddy yield in next season; and a 1% increase in rainfall leads to 0.12% decrease in current paddy yield and 0.21% decrease of paddy yield in next season (Alam et al., 2010a). Tisdell (1996) mentioned that rainfall variability increases the level of environmental stress that affects the capability of the system to maintain productivity. The projection of paddy yield in the country shows that any positive or negative variation of above 0.4% in both rainfall and temperature will decrease the yield of paddy production by 2020 (Table 2). When considering a positive or negative variation of above 0.7% in both rainfall and temperature by 2040, paddy yield tends to decline further and this negative trend of paddy

yield is expected to continue by the year 2060, considering the variation (Âą) of above 1%. These clearly indicate a very high level of vulnerability of paddy productivity due to the climatic variation in the next couple of decades. This indicates that climate change has an adverse impact on agriculture in Malaysia. Alam et al., (2011a) indicate that the yearly total rainfall is increasing and its monthly variation is too high. The adverse effects of lower rainfall can be reduced or averted by introducing proper irrigation system. But the effect of the opposite phenomenon of over rainfall especially at the end of the crop cycle or at the maturity period is absolutely uncontrollable. The climatic change causes change in several agriculture relevant factors that determine the sustainability of agricultural production. Farmers believe that vulnerability of some of the factors like injurious insects (supported by 42.9% of the farmers), temperature (supports by 58.6% of the farmers), soil fertility loss (supports by 49.5% of the farmers), cost of inputs (supports by 61.1% of the farmers), shortage of rainfall (supports by 45.5% of the farmers), excessive rainfall (supports by 35.9% farmers) increased over the last 5 years (Alam et al., 2011b). Due to the climate change impacts on agriculture, the projections of NAHRIM of paddy yield in terms of climate change, in a given level of temperature and CO2 level, shows more than 0.4% variation of rainfall by 2020 and will cause a fall in paddy yield in Malaysia (NAHRIM 2006). Therefore the agricultural sustainability in the future in Malaysia is projected to be vulnerable due to climatic changes. Agricultural adaptation Farmersâ&#x20AC;&#x2122; adaptation practices to cope with the agricultural vulnerability due to climatic change are not found adequate and satisfactory (Alam et al., 2011c, 2012a,c). Their adaptation methods are based only on their ideas or reactions. As a result, only 30.3% farmers believe that they have been able to properly cope with climatic vulnerabilities (Alam et al., 2012d). On the issue of availability of external supports, most of the farmers were not found aware

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Table 1: Future Rainfall and Temperature Change Projections in Peninsular Malaysia by 2050 Area

Projected Change* in Maximum Monthly Value Temperature (0C) Rainfall (%)

Regions/Sub-regions/states North East Region -Terengganu, Kelantan, Northeast- coast North West Region-Perlis (west coast), Perak, Kedah Central Region-Klang, Selangor, Pahang Southern Region-Johor, Southern Peninsula

+1.88 +1.80 +1.38 +1.74

+ 32.8 + 6.2 + 8.0 + 2.9

* Difference = Average 2025-2034 & 2041-2050 minus Average 1984-1993 Source: NAHRIM, 2006

Table 2: Projection of Paddy Yield (Kg/Ha) with Different Variations of Temperature and Rainfall at Certain Level of CO2

Variation in Rainfall

14% 7% 0.4% 0% 0.4% -7% -14%

Year 2020* Variation in Temperature ( 0C) 0.3

0.85

6,156 6,646 7,202 7,202 7,202 6,698 6,194

5,806 6,306 6,862 6,862 6,862 6,382 5,901

Year 2040^ Year 2060~ Variation Variation in Variation Variation in in Temperature ( 0C) in Temperature ( 0C) Rainfall Rainfall 1.4 0.4 1.4 2.4 0.6 2 3.4

5,586 23% 7,342 6,942 6,086 11% 8,200 7,800 6,642 0.7% 9,042 8,642 6,642 0% 9,042 8,642 6,642 -0.7% 9,042 8,642 6,177 -11% 8,047 7,691 5,712 -23% 6,962 6,654

6,542 32% 7,400 15% 8,242 1% 8,242 0% 8,242 -1% 7,335 -15% 6,346 -32%

8,619 9,834 10,962 10,962 10,962 9,318 7,454

8,059 9,274 10,402 10,402 10,402 8,842 7,073

7,499 8,714 9,842 9,642 9,642 8,366 6,693

*, ^, ~ indicates CO2(ppm) level at 400, 600, and 800 respectively

Table 3: Government Subsidy (in MYR) for Paddy Sector in Malaysia Items Subsidy For Paddy Price Paddy Fertilizers Paddy Production Incentive Yield Increase Incentive Paddy Seed Help Diesel Subsidy Scheme Petrol Total Subsidy and Incentive

2004

2005

2006

476,628,303 186,744,867 NA NA NA NA NA 663,373,170

443,218,042 178,072,073 NA NA NA NA NA 621,290,115

445,749,898 396,393,001 NA NA NA 989,727,418 45,413,959 1,877,284,276

Note: NA means data were not found available.

2007 444,000,000 261,677,743 67,563,904 85,434,620 17,000,000 1,099,000,723 69,461,384 2,044,138,374

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of the current supports provided by external parties to adapt to climate change. But, in order to support the farmers to increase productivity and increase income, government’s subsidy for agricultural sector is increasing each year (Table 3). Worth noting to mention that government of Malaysia currently provides huge amount of subsidy to the paddy producers to encourage paddy cultivation and to ensure more production for increasing the country’s self-sufficiency level. The types and contents of these subsidies have been summarized below: Input subsidy 12 beg (20 kg each) compound fertilizer and 4 beg (20kg each) urea fertilizer per hectare – worth MYR 400 and pesticide incentive MYR 200 per hectare. Price Subsidy Provided at the selling price – MYR 248.1 per ton. Rice Production Incentive Land preparation/plowing incentive – MYR 100 per hectare and organic fertilizer 100kg per hectare – worth MYR 140. Yield Increase Incentive Provided if producers (farmers) are able to produce 10 tons or more per hectare – MYR 650 per ton.

Free Supports Free supports for irrigation, infrastructure, and water supply. Source Agriculture Statistical Handbook, 2008 The subsidies for urea and compound fertilizer have been continuing since 1979. The incentive for land preparation and using organic fertilizer has been continuing since 2007. Providing urea and compound fertilizer and pesticide incentive was introduced in 2008 and these supports are still continuing. Still farmers expect several types of external supports to cope properly with the changes in climatic factors. Among several types of expected new supports, farmers significantly believe moisture deficiency related innovations, crop development, cash incentive, infrastructural supports, and adjustment in wage, and leasing system are required to adapt to climate change (Alam et al., 2012a). Policy recommendation and conclusions As climate change is a continuous and long term process, its effects and solutions are similarly time and effort consuming process. Most of the warming during the next 30 years will be due to emissions that have already occurred. Over the longer term, the degree and pace of warming mainly depend on current and near future emissions

Fig. 1: Regional and Global Climate change from 1990 to 2000

ALAM et al., Curr. World Environ., Vol. 8(1), 01-12 (2013) (Stern, 2007). To adapt with climate change, conventionally, mitigation has received more attention than adaptation, both from a scientific and policy perspectives. Mitigation is the main way to prevent future impacts of climate change, and it will reduce the cost of adaptation. So, any delay in mitigation strategy to reduce emissions will increase the need and cost of adaptation, and increase the risk of being victim of global climate change. On the other hand, though adaptation is not a substitute of mitigation, there are arguments for adaptation to consider as a response measure. Mitigation actions never stop a certain degree of climate change due to historical emissions and the inertia of the climate system (IPCC, 2001). Moreover, mitigation effects may take several decades to manifest, where most adaptation activities take immediate effects. Adaptation reduces risks associated with current climate variability as well as addressing the risks associated with future climate changes, where mitigation only focuses on future risks. The measures of adaptation can be applied to a local scale or root level with the involvement of large number of stakeholders, where mitigation works in the decision making level. In the current world, climate factors are exogenous variables that are immitigable in a quick manner and as a consequence adaptation is the most appropriate way to cope with the system properly. It is therefore important to strike a balance between measures against the causes of climate change and measures to cope with its adverse effects (Stern, 2007; Pielke et al., 2007). In recent years, adaptation has gained prominence as an essential response measure, especially for vulnerable countries due to the fact that some impacts are now unavoidable in the short to medium term. Mitigation is necessary but adapting to future risk is more important. Immediate and long term actions are essential for various factors including government, development partners, research organizations, and community organizations. In fact, adaptation is too broad to attribute its costs clearly, because it needs to be undertaken at many levels, including at the household and community level, and many of these initiatives are self-funded (Stern, 2007). Options for agricultural adaptation can be grouped as technological developments, government

programs, farm production practices, and farm financial management (Smith, 2002). So, it has been suggested to prepare a planned and proactive adaptation strategy to secure sound functioning of the economic, social and environmental system. Government as the policy and law making authority has to play the most influential role to ensure climatic mitigation and adaptation at all levels (Alam et al., 2010b, 2012b). It is the main responsibility of government to give enough supports in order to enable farmers to adapt to different climatic situations and to make them selfsufficient rather than subsidy dependent. Appropriate authorities also need to carefully define governmentâ&#x20AC;&#x2122;s subsidy supports and incentive programmes to influence farm-level production, practices, and financial management. Hence, agricultural policies and investments need to be more strategic. But the government needs to define and ensure the compensation, minimum income protection, and insurance facility for the affected groups â&#x20AC;&#x201C; individual farmer or farm. In the planning processes, policy makers need to account the barriers of adaptation including ecological, financial, institutional, and technological barriers, as well as information and cognitive hurdles. Other few important issues need to be focused, such as stakeholders may not sufficiently inform about the needs and possible strategies of climate change (Eisenack et al., 2006, 2007), farm level faces uncertain future and hinders the development process, causes obstacle for implementation of adaptations policy (Behringer et al., 2000; Brown et al., 2007), and the policy deals with different conflicting interest groups. To avoid the negative impacts of climate changes on agriculture and to control pollutions and emissions in the sector, however, proper mitigation policies are urgently required for Malaysia. Further, Malaysian agriculture sector also needs to include mitigation policies due to the emission of commercial farming. The issues of mitigation and adaptation to climate change concern all sectors as well as all levels of political, administrative, economic and everyday life. To better cope up, cooperation is necessary across countries, sectors and administrative levels. Relevant agencies need to be aware of the benefits of cooperation to gain long-

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term benefits instead of focusing only on short-term and individual interest. The production practices of farm and the knowledge of individual farmer also need to be updated with the changes of climate factors. The agricultural farmers should understand the crop rotation, crop portfolio, and crop substitutions. They should also take all precautions and be aware about the uncertainty of low rainfall and heavy rainfall. The financial management of agricultural farms must be efficient and the farmers must secure minimum two cropping seasons so that if crops damage in one season they will have the seeds for next season. This will help them bear the cost of another crop production and survive financially up to the time when new crops are collected. But this will make the farmers take initiative for crop sharing, forward rating, hedging, and insurance etc. Different new groups of stakeholders also need to be engaged to ensure necessary facilities for the farmers. Financial institutions also need to be engaged more inclusively in order to provide supports of loan, insurance, saving schemes, hedging or future option, and so on to the agricultural farmers. Technological adaptation to climate change is also important to deal with the climatic problems in the long run. It is apparent that development of technology is a boundless area, but it is possible in several ways. The highest efficient method of technological advancement is expected to be able to solve the problem. Until gaining such level of technological advancement, there should be some alternative options which are expected to help the agricultural farmers in their effort to adapt to climate changes in the following ways: To solve the problem controlling the pattern of rainfall, sunshine, and moisture level. To improve shielding resources protecting crops from excessive rainfall or sunshine and solving water logging problems. To develop defensive approach development of varieties of crops, development of rainfall and temperature tolerant

plants, and finding alternative crops and hybrids. To find alternative approach changing crop cycle and reducing the timing of crop cycle. To provide information providing weather forecast and early warning system and ensuring delivery of proper information at the farm level. The impacts of climate change on agricultural sustainability vary from country to country, region to region and time to time. The yield and productivity of agricultural crops in Malaysia are proven to have been heavily influenced by climatic variations. Malaysia is the 26 th largest greenhouse gas emitter which causes the expected rise of temperature by 0.3oC to 4.5oC, and rise in sea level is expected to be about 95cm over the time span of one hundred years. The changes in the countryâ&#x20AC;&#x2122;s rainfall fluctuate heavily from -30% to +30%. This change reduces crop yield and is prone to drought in many areas so that cultivation of some crops such as rubber, oil palm and cocoa becomes unfeasible. Current crop productivity is also affected by the climatic variations throughout the country as the actual farm yields of rice in Malaysia vary from 3-5 tons per hectare while the potential yield is 7.2 tons per hectare. The projection of climate change and its impacts on productivity and farmersâ&#x20AC;&#x2122; profitability are thus considered very alarming. ACKNOWLEDGEMENTS We are thankful to Ministry of Science, Technology and Environment of the Government of Malaysia for generously funding the research, under the Research University Grants (UKM-APPLW-04-2010, LRGS-TD-2011-UPM-UKM-KM-04 and UKM-GUP-PI-08-34-081). We would also like to thank Dr. Basri Talib, Dr. Mohd Ekhwan bin Toriman, Prof Dr. Abdul Hamid Jaafar (National University of Malaysia), Md. Wahid Murad (University of Adelaide, Australia), and Prof. Dr. Rafiqul Islam Molla (Multimedia University, Malaysia) for their advices and supports at various stages of the study.

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Current World Environment

Vol. 8(1), 13-21 (2013)

Odour Pollution Measurement from Refuse Derive Fuel Operations Using Odour Concentration Meter (OCM) XP-329 ZAINI SAKAWI1*, LUKMAN ISMAIL2, MOHD ROZAIMI ARIFFIN2 and NOOR KHAFAZILAH ABDULLAH2 1 Earth Observation Centre, Universiti Kebangsaan Malaysia. School of Social, Development & Environmental Studies, Universiti Kebangsaan Malaysia.

DOI : http://dx.doi.org/10.12944/CWE.8.1.02 (Received: February 17, 2013; Accepted: February 28, 2013) ABSTRACT Odour perception is subjective and difficult to be accurately measured between individuals. Hence many studies on odour issues are more commonly pertain to its intensity, concentration, types, standards, measurement methods, law and impacts on physical and human environments. Nevertheless, odour analysis can be conducted empirically or based on human sensorial. Among major sources of odour pollution are animal rearing, oil palm and rubber mills, dumpsites, industries and sewage treatments. This study attempted to measure odour pollution generated by Refuse Derived Fuel (RDF) operation. The analysis was conducted at different times of day (morning, evening and night) and weather conditions (normal days and after rains). 10 sampling stations were selected for observations using the Odour Concentration Meter Siri XP-329 III.The results indicated that there existed different level of odour concentrations on normal days and after rains due to the influence of meteorological environment. Distance factors also influenced the odour concentrations, whereby gradually, the stations further from RDF operation recorded higher odour concentrations.

Key words: Odour pollution, Odour concentration, RDF, Meteorological factors.

INTRODUCTION There has been a dearth on studies of odour pollution in Malaysia due constraints such as lack of measurement equipments, guidelines and legal act for such operational endeavour. Despite the media publication on odour pollution, actions and enforcement were ineffective due to limitations in regulations and operationals standards.In particular, scientific studies on odour concentrations and intensity were difficult to be implemented due to lack of equipments for measuring the phenomenon. Comparatively, researchers in Japan, European Union, Australia and New Zealand have paid serious attention on odour pollutions1. Their studies not only conducted to measure the odour concentrations, intensity, components, impact on health and people well-being but also involved in

determining the accuracy in the usage of various equipments for such measurements. There were various measument methods to measure odour concentrations and intensity in terms of effectiveness in applications, comparative outcomes and systemacity. Studies conducted by212 were those focusing on applications of various methods to measure odour pollutions. There were not many studies on odour pollution conducted in Malaysia. A study on odour concentrations emanated from an open dumpsite was conducted by13. Other than that, a study on a population sensory perception was conducted to identify the odour impact, intensity and meteorological factors1,14. This study is therefore aimed to measure the odour intensity from the RDF operation to further highlight issues of odour concentrations measurement in Malaysia. The

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measurement was conducted at various times in the morning, evening and night. The differences in odour concentrations were measured according to the prevailing situations of either normal days or after rains. The measurementswere conducted at sampling stations per distances from the RDF operation, and also recorded were the meteorological data to identify the other factors involved in influencing the odour concentrations. MATERIALS AND METHODS Refuse Derived Fuel (RDF) is a method of power generation involving a process of combustion of solid wastes to produce electricity. The amount of electricity generated depends on the capacity and quantity of wastes being used. The RDF operation in this study was capable to generate electricity at a maximum of 9 megawatt (MW) through utilization of 700 tonnes of solid wastes per day. Parts of the power were used to run its own operation (3.5 MW) and the rest (5.5 MW) was sold to the Tenaga Nasional Berhad. The RDF is located at N 03°00’3.1’’ and longitude E 101°52’56.6’’ at 70m above sea level. Figure 1 shows the RDF location and sampling stations per the RDF. Method for Measuring the Odour Concentration: The equipment for measuring the odour concentration is Odour Concentration Meter (OCM) XP-329 III. The equipment is also used to measure odour threshold and the measuring unit is stated in odour concentration per cubic meter or ou/m3. The OCM has the capacity to measure odour concentration from a minimum concentration of 0 to a maximum of 2000 ou/m3. Malaysian Standards on Odour Pollution and Gas There have not been specific standards established for regulatory and enforcement guidelines on odour pollution and of gas components. Existing Malaysian guidelines such as the Recommended Malaysian Air Quality Guidelines (RMAQG) have been limited to those pertaining to several gas types: O3, CO, NO2 and SO 2 (Table 1). Based on the table, there is no indication of the H2S, CH4 and NH3 being emitted from the RDF.

RESULTS AND DISCUSSION The results can be divided into three major components i.e. the average of odour concentration on normal days; concentration after rains and comparative concentrations on normal days and after rains. Average Concentrations on Normal Days Concentrations of odour in the morning, evening and night times are shown in Tables 3, 4 and 5. The highest concentration in the morning was detected at station 5 at 43.0 ou/m 3. Hot temperatures at 32.7°C and comparative humidity of 79.6 per cent (Table 3) have influenced the odour concentration at that station. The second highest concentration was at station 1 with 38.6 ou/m3. Meanwhile, values of average odour concentration recorded was (53.0 ou/m3) at Station 7 (Table 4), and maximum values was obtained up to 76.2 ou/m 3 at Station 1. The low average concentrations occurred due to the influence of strong winds at the station, at 3.5 m/s. Furthermore, the average concentrations at night time on normal days indicated a sequence of higher readings from various directions. The highest odour concentration was from the north east of the RDF location, with 68.0 ou/m3 (Station 8); followed by the south west direction with 60.6 ou/ m3 (Station 7); and from the western side of the location (56.2 ou/m3) at Station 3 (Table 5). The average of lowest concentrations on the day was at station 1 with concentration values of 27.8ou/m3. Average of Odour Concentration after Rains: Meteorological elements, gas and odour concentrations, measured in the morning after rains are indicated in Table 6. Station 7 recorded highest odour concentration at 77.2 ou/m3, in addition to Station 6 at 70.8 ou/m3. Accordingly, the NO2, H2S and SO2 gas concentrations measured were at 0.16 ppm, 0.020 ppm dan 20.50 ppm respectively. The three gases recorded highest readings at station 7 compared to that of other stations. This phenomenon occured due to the influence of high temperatures and humidity; which directly stabilised the athmosphere and thus increased the concentrations of gases and odour.

SAKAWI et al., Curr. World Environ., Vol. 8(1), 13-21 (2013) Table 7 shows concentrations of gas and odour in the evening after rains. Highest odour concentration was measured at station 9 (104 ou/ m3), the furthest from the RDF. The combination of temperatures, high humidity, and stable athmosphere of the recorded evenings affected the odour concentration at the station.

Meanwhile, night time after rain concentrations of gas and odour did indicate an uneven pattern (Table 8). The measurement for the night time after rains concentrations indicated high odour concentrations at all stations, with the highest being at station 5 with 42 ou/m3. For gas, night time data indicated the scarce presence of H2S. Based

Table 1: Gas Standards linked to Air Quality in Malaysia Air Pollutant

Average Time

Standardppm

Malaysian(ug/m3)

Ozone Carbon Monoxide Nitrogen Dioxide Sulphur Dioxide

1 hour8 hour 1 hour8 hours 1 hour24 hours 1 hour24 hours

0.100.06 30.09.00 0.170.04 0.130.04

200120 3510 320 350105

Table 2: Gas Standards linked to Odour Pollution Gas

Standard (ppm)

Description

SO2 NO2 H2S

0.19 0.17 0.00014 0.13 10 17

Allowed Allowed Harmful Allowed

NH 3

maximum values 1 maximum values 1 to adults and children2Odour threshold2 maximum values OSHA2

Odour Threshold2

Note: 1 Recommended Malaysian Air Quality Guidelines 2 EPA standard

Table 3: Meteorological elements, odour concentrations and gas on normal days (morning) Station

1 2 3 4 5 6 7 8 9 10

Meteorological elements Temp.(째C) Rh(%) Wind Speed (m/s) 30.0 28.9 29.7 30.8 32.7 31.6 33.7 28.7 31.2 30.6

80.3 83.4 82.6 80.4 79.6 81.5 79.0 83.9 80.1 79.8

1.0 0.1 0.0 0.0 0.0 0.1 0.0 0.8 0.1 0.0

Gas Concentration(ppm) NO2 H 2S SO2

0.16 0.10 0.08 0.06 0.08 0.10 0.10 0.08 0.02 0.04

0.014 0.026 0.024 0.012 0.018 0.010 0.004 0.016 0.004 0.014

0.24 3.60 2.98 2.82 0.00 3.14 0.00 2.26 0.00 0.00

Odour Concentrations (ou/m3) 38.6 27.2 4.20 12.4 43.0 5.30 30.8 22.2 24.7 25.5

SAKAWI et al., Curr. World Environ., Vol. 8(1), 13-21 (2013)

Table 4: Meteorological elements, odour concentrations and gas on normal days (morning) Station

1 2 3 4 5 6 7 8 9 10

Meteorological elements Temp.(째C) Rh(%) Wind Speed (m/s) 37.6 36.1 38.0 32.3 32.0 34.6 36.0 32.3 34.4 33.1

42.6 46.0 44.0 57.1 59.5 49.3 54.2 57.3 53.5 55.2

1.2 0.4 1.5 1.6 1.0 1.1 3.4 1.5 1.1 1.2

Gas Concentration(ppm) NO2 H 2S SO2

0.24 0.12 0.14 0.16 0.14 0.10 0.10 0.12 0.22 0.16

0.024 0.030 0.026 0.016 0.026 0.024 0.000 0.022 0.048 0.016

5.84 0.00 10.34 7.24 7.64 6.18 0.00 3.26 24.34 15.76

Odour Concentrations (ou/m3) 76.2 62.4 73.2 36.8 68.6 59.7 53.0 75.6 72.8 64.6

Table 5: Meteorological elements, odour concentrations, and gas on normal days (night) Station

1 2 3 4 5 6 7 8 9 10

Meteorological elements Temp.(째C) Rh(%) Wind Speed (m/s) 24.2 24.6 26.3 25.0 26.1 25.5 25.6 25.9 26.4 27.1

85.1 84.0 83.4 83.0 84.2 87.0 92.3 83.0 82.0 81.7

0.3 0.2 0.1 0.1 0.1 0.1 0.1 0.4 0.2 0.2

Gas Concentration(ppm) NO2 H 2S SO2

0.10 0.18 0.10 0.10 0.12 0.12 0.14 0.06 0.08 0.00

0.020 0.012 0.006 0.014 0.000 0.000 0.024 0.002 0.012 0.018

9.06 10.44 0.00 9.18 0.38 0.14 18.36 0.56 4.68 5.94

Odour Concentrations (ou/m3) 27.8 28.4 56.2 30.8 49.4 46.6 60.6 68.0 58.0 52.0

Table 6: Meteorological elements, gas and odour concentrations after rains (morning) Station

1 2 3 4 5 6 7 8 9 10

Meteorological elements Temp.(째C) Rh(%) Wind Speed (m/s) 23.8 25.4 23.6 23.9 23.6 23.5 24.0 23.7 24.3 24.0

83.6 77.0 85.9 87.0 82.0 80.1 84.5 87.2 81.2 85.2

0.3 0.1 0.0 0.0 0.0 0.6 0.3 0.1 0.1 0.2

Gas Concentration(ppm) NO2 H 2S SO2

0.02 0.04 0.04 0.06 0.04 0.04 0.16 0.00 0.06 0.04

0.012 0.000 0.004 0.010 0.002 0.018 0.020 0.000 0.000 0.000

1.00 0.00 1.52 6.24 10.20 13.80 20.50 1.90 0.00 0.00

Odour Concentrations (ou/m3) 17.7 11.0 20.6 15.4 65.0 70.8 77.2 17.2 19.4 8.20

SAKAWI et al., Curr. World Environ., Vol. 8(1), 13-21 (2013) on Table 8, it shows that 2/3 of the observation stations could detect the presence of H2S during the period. Comparison Between the Averages of Odour Concentrations on Normal Days and after Rains: Figure 2 shows odour concentration recorded around the RDF. Based on the figure, it shows that concentrations vary per day and time variances, with indications of the concentrations exceeded the limit set by the [15]. According to the standards, the allowable concentration was set at 10 ou/m3. However, the analyses showed that the average concentration of the three sessions of

measurements on normal days and after rains exceeded the limit allowable under the standards Minimum and maximum concentrations recorded on normal days was at 23.39 ou/m 3 (morning) dan 64.29 ou/m3 (evening) respectively. After rains recording saw a maximum reading of 54.21 ou/m3 (evening); while minimum concentration was 31.26 ou/m3 at (night). The high concentration could adversely effect routine outdoor activities and wellbeing of the local population. Comparison of The Averages of H2S, SO2 and NO2 Gas Concentrations on Normal Days and After Rains:

Table 7: Meteorological elements,gas and odour concentrations after rains (evening) Station

1 2 3 4 5 6 7 8 9 10

Meteorological elements Temp.(째C) Rh(%) Wind Speed (m/s) 26.2 26.7 26.5 27.1 27.4 27.6 25.1 26.2 26.6 26.4

100 98.8 100 79.1 80.2 80.7 90.2 98.8 85.6 83.3

2.4 2.0 2.4 0.2 0.0 0.0 0.5 1.3 0.2 0.1

Gas Concentration(ppm) NO2 H 2S SO2

0.12 0.12 0.14 0.22 0.22 0.26 0.14 0.14 0.14 0.16

0.026 0.020 0.014 0.006 0.006 0.012 0.012 0.004 0.000 0.000

Odour Concentrations (ou/m3)

29.46 18.36 14.46 7.50 8.56 8.43 13.04 8.52 1.96 1.72

31.8 30.8 43.6 64.6 80.2 34.3 30.4 27.0 104.4 95.0

Table 8: Meteorological elements, gas and odour concentrations after rains (night) Station

1 2 3 4 5 6 7 8 9 10

Meteorological elements Temp.(째C) Rh(%) Wind Speed (m/s) 24.7 24.6 24.5 24.7 24.7 24.7 25.3 24.5 24.7 25.1

86.4 86.0 85.3 80.8 86.2 97.4 97.3 92.5 91.1 93.8

0.1 0.2 0.1 0.2 0.0 0.2 4.0 0.3 0.1 0.1

Gas Concentration(ppm) H 2S SO2 NO2

0.12 0.16 0.16 0.16 0.10 0.10 0.12 0.10 0.10 0.16

0.000 0.000 0.000 0.000 0.000 0.000 0.016 0.000 0.002 0.014

1.32 0.58 2.40 0.24 0.00 0.02 14.04 3.52 9.22 13.94

Odour Concentrations (ou/m3) 34.8 28.0 25.6 33.8 42.0 28.6 25.6 35.2 24.2 34.8

SAKAWI et al., Curr. World Environ., Vol. 8(1), 13-21 (2013)

Fig.1: Sampling stations from the RDF Operation

Fig. 2: Comparison of odour concentrations in the morning, evening and night on normal days and after rains

Fig. 3: Comparison of H2S concentrations in the morning, evening and night on normal days and after rains

SAKAWI et al., Curr. World Environ., Vol. 8(1), 13-21 (2013) Generally, based on figure 3, figure 4 and figure 5, the gas concentrations were the highest in the evening and after rains. For example, the concentration of SO 2 and NO 2 reached highest reading after rains, whilst the H2S registered highest concentration on normal days. Table 3 indicated that the presence of H2S around the studied area exceeded the standard limit set by the EPA. The exceeded presence could give an impact on the health of sensitive recepients. For example, the maximum presence of H2S at 0.0232 ppm on normal days and at 0.01 ppm after rains are extremely hazardous to the sorrounding population. Exposure to a concentration of 0.00014 ppm could give adverse effect on the health of the elderly and children (Table 2).

The analysis of SO2 (Table 4) indicated that the concentrations exceeded the limit set by JAS. The rate of maximum gas concentration on normal days (8.06 ppm) and after rains (11.201 ppm) exceeded the standard limit by 0.19 ppm (Table 2). These gases extended exposure to human beings could damage not only their health but also their properties16 . An indication is ruinous effect on human skins and deterioration of buildings walls and paintwork. Based on the RMAQG standards, the overal observations indicated that the NO 2 presence were below the standard limit allowable (Figure 5). The figure shows that the NO 2 concentration was at maximum on normal days and the lowest after rains at 0.15 ppm and 0.16 ppm respectively (Table 2).

Fig. 4: Comparison of SO2 concentrations in the morning, evening and night on normal days and after rains

Fig. 5: Comparison of NO2 concentrations in the morning, evening and night on normal days and after rains CONCLUSION This study has indicated that concentrations of odour produced from the RDF

operation could be influenced by meteorologicalfactors such as temperatures, relative humidity and wind speed. On normal days, the concentration of odour indicated high readings

SAKAWI et al., Curr. World Environ., Vol. 8(1), 13-21 (2013)

in the evening that was at 76.0 ou/m3 followed by night readings at 68.0 ou/m3 and mornings at 43.0 ou/m3. After rains, the concentrations in the evening also shown highest reading at 104 ou/m3. However , the second highest reading was recorded in the morning at 77.2 ou/m3. While for the night time, concentration was at the lowest at 42 ou/m3. In addition to that, this study also revealed the concentrations of odour generated by the RDF operation have exceeded the standard limit set by the DEC at10ou/m3, either on normal days or after rains. It was also revealed that odour pollution was also due to the release of H2S, SO2, and NO 2 concentrations. SO2 and NO2 were detected at high concentrations after rains; whilst the H2S attained high concentrations on normal days.

The exposure to odour concentrations and the gases for an extended period may be harmful to wellbeing and quality of the environment of sensitive receptors. Close monitoring and penalty enforcement by the authorities need to be enhanced to minimize the potential harms of odour and gas pollutions to human beings and the larger environment. ACKNOWLEDGEMENTS The researcher wish to gratefully acknowledgement financial support for this research by Institute of Climate Change, Universiti Kebangsaan Malaysia under grant code GGPM2012-018.

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Current World Environment

Vol. 8(1), 23-27 (2013)

Oryzalin Treatment ModifiedPlant Morphologyof Impatiens balsamina L M. RIA DEFIANI*, D.N.SUPRAPTA2, I.M. SUDANA3 and N.PUTU RISTIATI 1

Doctorate Program on Agricultural Science, School of Postgraduate, Udayana University, Denpasar Bali, Indonesia 2 Laboratory of Bio Pesticide, Faculty of Agriculture, Udayana University, Denpasar Bali Indonesia 3 Faculty of Agriculture, Udayana University,Denpasar Bali, Indonesia. 4 Department of Biology Education, Faculty of Natural and Basic Sciences, Ganesha Education University,Singaraja Bali, Indonesia. DOI : http://dx.doi.org/10.12944/CWE.8.1.03 (Received: February 25, 2013; Accepted: March 12, 2013) ABSTRACT Impatiens balsamina L. is well known as garden balsam that flowers are very usefull. The flowers can be arranged in coconut leaves for praying or as a decoration in pots. Garden balsam plants are tall. The flowers are easy to decay especially in rainy season. Vigorous plants with bigger flower for potted plant can be produced by using oryzalin throughseedlings treatment of garden balsam. Seedlings were treated in oryzalin at concentrations of 0, 0.01, 0.02 and 0.03% for 0, 12, 24, 36, and 48 hours, then grown in the field. As a result, for M1 generation, interaction between oryzalin concentration and incubation time was significant for plant height, number of branch and flower weight. Plants height decreased about 54% for treatmentof 0.01% oryzalin in 48 h incubation. Oryzalin application also increased the weight of flower. In the next generation (M3), mixoploid plants were obtained from treatment 0.02% oryzalin for 12 h incubation. Based on this study, oryzalin can be used for producing compact potted plants.

Key words: Impatiens balsamina, Oryzalin, Potted plant, Mixoploid.

INTRODUCTION

Impatiens balsaminaL. (garden balsam) is a flowering plant that belonged to Balsaminaceae family.The plant has many flower colour like red, purple, pink and white. The flowers can be used for gardening and potted plants, nail polished and natural colouring agent1, antibiotic activity against pathogenic bacteria and fungi 2 , offerings in Balinese ceremony3. Seed extract of garden balsam contained antimicrobial activity against the growth of E.coli and Bacillus anthrasis and antifungal against Aspergillus nigerand Fusarium sp.4Seeds also used for expectorant and treatment for cancer5. This plantis relatively tall with plant height6 can reach up to 65 cm or higher that depend on type and fertility of soil. In the field, tall plants are susceptible to be lodged by strong wind and heavy rain3.

Previously, colchicine is widely applied for plant modification such as Rhododendron to produce compact plants7,Impatiens balsamina L. to obtain tetraploid plants 8 , Phlox subulata 9 , ornamental ginger (Hedychium muluense)10, basil (Ocimum basilicum L.)11 and yellow passion fruit12, Portulaca grandiflora13 to increase flower size. In fact, colchicine in a certain concentration had negative effect to the plant cell14,environment15 and people who are exposed to this chemical16. In contrast, oryzalin is easier to be degradabled by light and had similar effect to colchicineas antimitotic agent in order to inhibit mitosis12. Oryzalin is a herbicide that can be used for inhibit root growth17. As herbicide, oryzalin was applied preemergence for control seedlings of grasses and annual broadleaves plants 17 . As

DEFIANI et al., Curr. World Environ., Vol. 8(1), 23-27 (2013)

mutagenic agent, oryzalin was used in some plants such as rose18 and Mecardonia tenella a native plant from South America19to produce shorter plant with bigger flower, Rhododendron to obtain thicker leaf and vigorous plant7, Hibiscus acetosellato have compact plant form20, banana cultivar to increase microshoot production 21. Oryzalin can replace colchicine application as antimitotic agent, that bind tubulin dimmer along division of cell and alter microtubules formation and spindle fibers22. Based on those previous study, oryzalin was applied to treat seedlings of Impatiens balsamina to modify plant form. Preliminary study showed that the growth of radicles of garden balsam seedlings was altered when treated with oryzalin because roots elongation was very poor3. After 7 days of germination, control and treatment with 0.01% oryzalin showed the growth of roots and hypocotyl. In contrast, treatment with oryzalin higher than 0.01 % only showed the growth of hypocotyl, while the roots was very slow and stunted. Effects of oryzalinin the field varied between plant species and oryzalin concentrations. In order to have shorter and compact plants, garden balsam seedlings were treated with oryzalin as a mutagenic agent with various time of soaking.Vigorous plant has advantage as border plant in a landscape or potted plants. In addition, lowered plants can enhance plant survival during heavy rain. MATERIALS AND METHODS Oryzalin treatment Seeds of garden balsam with red flower were pretreated by soaking in distilled water for 12 hand germinated on filter paper in Petri Dishes. Germinated seeds (4 days old) were treated with oryzalin in different concentrations (0, 0.01, 0.02, 0.03)% for (0,12, 24, 36 and 48) h. Treated seedlings were rinsed in water and planted in polybags and grown in the field.The randomized block design was applied to allocate the treatment. There are 20 of combination treatments and each treatment was repeated three times. Thus, there are 60 experimental units and each of experimental unit consisting of 5 plants. The plants were maintained

by watering every day and applying fertilizer (NPK 15:15:15) at 4 weeks and 8 weeks intervals after planted. Plant Morphology Morphology measurement includes plant height (from the stem base to the shoot tip), number of branch, weight of flower. Flowcytometry analysis (FCM) FCM analysis was sampled from M3 generation. Each treated plant that showed altered growth with bigger flower size was analysed to check its ploidy level. Sample of leaf tissue (0.5 cm2) was put in 55 mm plastic Petri Dishes (Partec code 04-2005) and was added with 500 µL extraction buffer (Partec Kit). Material was chooped using a sharp razor blade for 30 to 60 seconds, then incubated for 90 seconds before filtered through a Partec 50 µm Cell Trics disposable filter (code 04-0042-2317). Staining solution (PI) and RNAse of 2 mL each were added to the test tube, then incubated and protected from light at least 30 min. Sample was then analysed with flow cytometer in the red channel (Partec GmbH Flow Cytometry, Germany). Statistical analysis All data were subjected to the analysis of variance (ANOVA) followed by Duncan’s Multiple Range Test (DMRT) at 5% level(CoStat Co.). RESULTS AND DISCUSSION Plant height Twelve weeks after planted, plant height was measured to know the effect of oryzalin and time of incubation for plant performance. M1 generation showed significance of different for interaction of the treatment between oryzalin concentration and time of incubation on plant height (Table 1). Concentration of oryzalin 0.01% for 48 hand oryzalin 0.03% for 48 h reduced plant height significantly by 53.6 % and 53.9 %, respectively when compared to control. Plant height of Hibiscus acetosella treated with colchicine and oryzalin were reduced and internode were shorter in octoploid plants when compared with diploid20. Reduction of plant size

DEFIANI et al., Curr. World Environ., Vol. 8(1), 23-27 (2013) had reported for some polyploid plant. In arrow root (Maranta arundinacea) plant, oryzalin treatment at high concentration (e”30 µM) inhibited plant growth. In contrast, at concentration of 10 µM enhanced growth of plant23. Mecardonia tenella treated with colchicine 0.01% for 48 h incubation produced tetraploid plant in the field and showed shorter and more compact plant than diploid19. Number of branch Plant response to oryzalin treatment was varied in number of branch. The plants treated with 0.01% oryzalin for 48 h incubation did not produce any branch, eventhough higher concentration of oryzalin 0.02% for 48 h incubation produced 6 branches (Table 1), and significantly different to control. Oryzalin treatment altered the growth of vegetative plants. Treated plant with 0.01 % for 48

h showed the shortest plant without any branch, the lowest weight and diameters of flower. In addition, in M1 generation, the treatment did not produce polyploid plant, but plant morphology showed a dwarf plant that suitable for potted plant or border plant in landscape garden. Inhibition of vegetative growth due to limited root growth after treated with oryzalin. Radicle was very slow to develop longer roots and even fail to produce root hairs. Seedlings stage is very critical. Limitation on root growth can alter further growth of shoots because the absorption of nutrients were very low. Flower weight Weight of flower was not statistically different between all treatments including control in M1 generation (Table 1). Oryzalin 0.02% for 48 h incubation and 0.03% for 36 h incubation tended to produced more weight of flower (32.9 % and 48.8%, respectively). The flower weight did not

Table 1:Oryzalin concentration and duration of treatment modified plant morphology of garden balsam at 12 weeks after planted Oryzalin concentration (%) 0 (Control)

0.01

0.02

0.03

Duration of soaking (hours)

Plant heigh t (cm)

Number of of branch

Flower weight (g)

0 12 24 36 48 0 12 24 36 48 0 12 24 36 48 0 12 24 36 48

51.66bcdef 67.89a 47.22 def 48.22 cdef 66.56 ab 48.44 cdef 57.33 abcde 38.67 fg 36.06 fgh 22.5 h 60.67 abcd 43.39 efg 37.75 fgh 64 abc 36.44 fgh 66.56 ab 46.22 defg 49.78 cdef 37.84 fgh 30.67 gh

3.17bc 2.22 bcd 2.5 bcd 2.67 bcd 2.44 bcd 2 cd 2.33 bcd 4.25 ab 1.25 cde 0e 2.89 bc 2.55 bcd 0.67 de 4.25 ab 6a 2.55 bcd 2.39 bcd 2.84 bcd 2.33 bcd 2.67 bcd

0.79 bcd 0.99 abc 0.63 cd 0.83 bcd 0.82 bcd 0.86 bcd 0.73 cd 0.83 bcd 0.74 bcd 0.55 d 0.82 bcd 0.86 bcd 0.65 cd 0.79 bcd 1.09 ab 0.86 bcd 0.79 bcd 0.90 bcd 1.28 a 0.66 cd

Note: Numbers in the same group followed by same letter in a column are not significantly different at the 5% level of DMRT

DEFIANI et al., Curr. World Environ., Vol. 8(1), 23-27 (2013)

(a) Flower

(b) Plant 12 weeks

Fig. 1: Mixoploid (2x + 4x) plant

(a) Flower

(b) Plant 12 weeks

Fig. 2: Diploid (2x) plant

influenced by flower diameter. Increased in flower weight did not followed by enhanced of flower diameter (data not shown). Visually, flower with higher in weight obtained more petals even though in small size of petals. In Rose, tetraploid plants showed double the number of petals flower18. Tetraploid plants due to colchicine treatment of Portulaca grandiflora had a large number of petals than diploid plants 13 (Mishiba and Mii, 2000).Mecardonia tenella treated with colchicine 0.01% for 48 h then cultured in vitro,obtained bigger flowers compared to control plants19. In the field, compact shaped were shown by selected tetraploid plants of M. Tenella. Ploidy analysis by FCM Ploidy level of garden balsam was

analysed by flowcytometry for further generation (M3). Concentration oryzalin 0.02% for 12 and 24 h incubation and oryzalin 0.03 % for 12 h, 36 h, 48 h showed mixoploid plants (2x+4x) (Fig. 1). Based on FCM analysis, oryzalin treatment to seedlings of garden balsam was unsuccesfull in inducing tetraploid plants on M3 generation, however mixoploid plants were obtained in the present study. Mixoploid plant (2x+4x) had shorter plant morphology and higher number of petal flower than diploid plants (Fig. 2). ACKNOWLEDGEMENTS The authors thanks to Mr Fajarudin Ahmad from Indonesian Institute of Science for his assisstant in flowcytometry analysis.

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Polunin O. and Stainton A.,Flowers of the Himalayas.Oxford Universtiy Press (1984). Chopra R. N., Nayar S.L. and Chopra

I.J., Glossary of Indian Medicinal Plants (Including the Supplement). Council of Scientific and Industrial Research, New Delhi

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(1986). Defiani M.R., Procceeding International Conference on Biological Science. Gajah Mada University, Indonesia, (2011). Jain B., Curr. World Enviro. J., 6: 299 (2011). Duke J.A. and Ayensu E.S., Medicinal Plants of China. Reference Publications, Inc. (1985). Anurita D. and Girjesh K., Caryologia, 60: 199 (2007). Vainola A., Euphytica, 112: 239 (2000). Wiendra N.M.S.,Undergraduate Thesis, Universitas Udayana, Denpasar Bali Indonesia (2008). Zhang Z., Dai and Xiao M. Euphytica, 159: 59 (2008). Sakhanokho H.F., Rajasekaran K., Kelley R.Y. andIslam-Faridi N., Hort Sci., 44: 1809 (2009). Omidbaiqi R., Mirzaee M., Hassani M.E.and Moghadam M.S., Intl. J. of Plant Prod., 4: 87 (2010). RegoM.M., Rego E.R., BrucknerC.H., Finger F.L. and Otoni W.C., Plant Cell Tiss. Organ Cult. 107: 451 (2011). Mishiba K. and Mii M., Plant Sci., 156: 213 (2000). Jaap M., Van Tuyl B., Meijer and van Dien

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M.P., Acta Hort., 325: 625 (1992). Hanumante M.M., Vaidya D.P. and Nagabhushanam R., Bull. Environ, Contam and Toxic, 24: 37 (1980). Finkelstein Y.S.E.Aks., Hutson J.R., Juurlink D.N., Nguyen P., Dubnov-Raz U.,Pollak G.Koren and Bentur T., Clin. Toxicol, 48: 407 (2010). Ross M.A. and Childs D.J., Herbicide Mode of Action Summary. Department of Botany and Plant Pathology, Purdue University (1994). Kermani M.J., Sarasan V., Roberts A.V., Yokoya K., Wentworth J. and Sieber V.K., Theo. and Appl. Gen., 107: 1195 (2003). Escandon A.S., Alderete L.M. and Hagiwara J.C., Sci. Hort., 115: 56 (2007). Contreras R.N., Ruter J.M. and Hanna W.W., J. Amer. Soc. Hort. Sci., 134: 553 (2009). Ganga M.and Chezhiyan N., J. Hort. Sci. Biotech., 77: 572 (2009). Petersen K.K., Hagberg P. and Kristiansen K., Plant Cell, Tiss. Organ Cult., 73: 137 (2003). Sukamto L.A., Ahmad F. and Wawo A.H., Bul. Littro, 21: 93 (2010).

Current World Environment

Vol. 8(1), 29-36 (2013)

Comparison of Noise Sensitivity and Annoyance Among the Residents of Birjand Old and New Urban Districts VAHIDEH ABOLHASANNEJAD1 , MOHAMMAD REZA MONAZZAM2* and NARJES MOASHERI3 1

School of Public Health, Social Determinant of Health Research Center, Birjand University of Medical Sciences, Birjand, Iran. 2 Department of occupational Hygiene, School of Public Health and Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran. 3 MSc of Community Health, Birjand University of Medical Sciences, Birjand, Iran. DOI : http://dx.doi.org/10.12944/CWE.8.1.04 (Received: December 02, 2012; Accepted: January 21, 2013) ABSTRACT Noise is a stressor of today man’s working and living place. Therefore, the present study was conducted aiming to compare the noise sensitivity and annoyance among the residents of Birjand old and new districts. In this analytical – descriptive study, using Weinstein noise sensitivity scale and the seven point scale of noise annoyance based on ISO 15666 standards we measured the rate of noise sensitivity as one of the attitudinal factors as well as that of noise annoyance among individuals exposed to environmental noise. The result showed that the mean total score of sensitivity was 63.5±16.1. The highest and lowest scores in noise sensitivity subscales associated with “sensitive to noise” and “attitude towards noise in residence” respectively. No significant difference was seen between total score of noise sensitivity in old and new district among both sexes. Between “attitude towards noise control” at illiterate and university education levels significant difference was observed. Also, a significant difference was seen between noise annoyance in the old district and job. The one way analysis of variance showed a significant difference between annoyance degrees and noise sensitivity subscales. This research clearly showed that Most of the heavy traffic areas are located in the old district. Lack of urbanization measures has caused noise pollution and dissatisfaction among the residents. Regarding higher degrees of annoyance in the old district, probably caused by heavier traffic, particularly by motorcycles and narrower streets, we can reduce noise pollution and its subsequent physical and mental disorders by eliminating old and noisy vehicles and expanding urban green spaces.

Key words: annoyance; noise sensitivity; urban district; Birjand. INTRODUCTION Noise is defined as an unpleasant sound that can affect people’s health and efficiency. Noise pollution not only produces effects such as damage to hearing system and disturbance in acoustic activities, reduce in concentration and efficiency, sleep disorder, physiological disorders, but also in long term creates annoyance that in the most common complication caused by noise among people. Noise sensitivity is a personality characteristic that can be regarded as a measure of individuals’ annoyance cause by the noise

around them and it is a strong marker associated with noise annoyance1-5 . The formal and accepted definition of annoyance maybe as such: annoyance is an unpleasant feeling about a factor or condition that is believed to have adverse effects on man or community6,7. Where ever these exists bothering or unpleasant noise around, it may cause anger and irritability. For this purpose, the noise doesn’t need to be loud but even a clock tic-tac in a waiting hall can influence on a sensational and ready ground and produce anger and aggression in individuals. In addition, studies have shown that noise influences on one’s mood and increases his or her

ABOLHASANNEJAD et al., Curr. World Environ., Vol. 8(1), 29-36 (2013)

aggressiveness and vulnerability. Although humans become accustomed to noise and acquire adaptation with it, however the fact is that noise is a boring factor and reduces one’s working capacity both in mental jobs needing precision and carefulness and in physical and simple jobs .Moreover, noise affects on one’s mental status and disturbs his or her adaptation with working environment and even with family and society. Several studies in this fields have shown that the rate of noise annoyance among different individuals living in a similar condition have undergone relatively significant changes because of individual differences8. Investigating in Muscut, Oman, showed that noise and its causative problems is not limited to industrial communities and has had a very sharp increase in developing countries. Environmental noise that interferes with individuals’ communicative behaviors, rigorous and intensive activities or sleeping, is considered an important environmental stressor. Effects of environmental noise will depend on acoustic factors and conditions such as noise loudness and the time of occurrence and exposure. In fact, the annoyance caused by noise is a sensitive marker of the effects of harmful noise and is indicative of people’s quality of life under such conditions9. Zannin Paulo and et al in a study conducted on the residents of one of Brazilian cities showed that the individuals’ main reaction to noise included 58% annoyance, 42% disorder in concentration , 20% sleep disorder and 20% headache10. Sayed Abbas Ali, Egypt, in a study on dose-response relationship for the noise cause by road traffic showed that 71.9% of the studied subjects revealed high noise annoyance and 37.2% showed high noise sensitivity and a direct relationship was found between noise level of road traffic and the percent of respondents who reported high noise annoyance 11. Klaeboe and Amundsen studied noise exposure and noise annoyance in Norway. The results of their study showed that the rate of noise annoyance was greater inside buildings with low quality glass windows 12 .When noise was considered a serious environmental pollution factor for the first time, a great number of social evaluations have been performed to measure the extent of this problem. The aim of the present study is to assess the noise sensitivity and annoyance among the residents of old and new districts of Birjand.

MATERIALS AND METHODS In this descriptive - analytical (cross – sectional) study with the aim to assess the rate of noise sensitivity and annoyance among the residents of Birjand’s old and new districts in the summer, the studied population included the residents of 8 divisions including the residents close to stations of Taleghani st., Motahari st., Montazeri st., and Shohada st. in old district, and the stations of Jamaran st., Mahallati st., Avini st., and Ghaffari st. in new district (figure 1). Noise measurements were performed with the “CEL” Noise Level Analyzer. Equivalent noise levels (Leq) were measured in four daily periods (7:30h- 9:30h, 11:30h- 13:30h, 15:30h17:30h, 19:30h-21:30h ) and in two periods in night (0.00h-2h, 4h-6h), according to the procedures recommended by BS 7445-1-2003 æBS 7445-31991 standard11. A total of 364 individuals were selected by simple random sampling according to the mean prevalence of 60% noise sensitivity and annoyance from previous studies (n=pqz2/d2)10,11. 400 questionnaires were presently distributed among the subjects out of whom 355 individuals were interviewed at eight selected districts. Due to heavier traffic and higher noise pollution level (higher than permissible) in the main streets, 181 questionnaires were completed in the main streets of new district and 174 one in the main streets of old district. (Table1) The inclusion criteria were: age more than 18, at least one year residence, and willingness to voluntarily participate in the project. Data collecting tool was a questionnaire consisting of three parts that was completed by the subjects. The first part contained demographic characteristics, the second related to Weinstein noise sensitivity scale (WNSS) with 21 questions about noise sensitivity13, and the third part associated with noise annoyance rating scale (based on 15666 standard)14. Using this tool we measured the rate of noise sensitivity that is an attitudinal factor of the subjects’ irritation caused by noise. In addition, we measured the noise annoyance caused by exposure to environmental noise. Moreover, the rate of noise response was measured by this tool which is a kind of social surrey. Cronbach’s alpha in the first and second half and

ABOLHASANNEJAD et al., Curr. World Environ., Vol. 8(1), 29-36 (2013) the whole test in Ali Mohammadi and coworkers’ study on the reliability and validity of the Persian translation of Weinstein noise sensitivity scale was calculated 0.62 , 0.68 , 0.78 , respectively. Regarding this result, Weinstein noise sensitivity test has relevant reliability and validity to be applied in field studies15. Weinstein noise sensitivity scale contains 21 items. Each item has six options ranging from ‘agree strongly’ (0) to ‘disagree strongly’ 5 and the highest total score of the test was 105. (The higher score the higher sensitivity). The 21 item Weinstein noise sensitivity is categorized in to four subscales of “becoming sensitive to noise” (ten items), “disturbance in concentration” (6 item) “attitude to noise in where they live” (5 items), and “attitude to noise control” (6 items). (Some of the items are repeated within the subscales). Noise annoyance is measured on a 7-point verbal scale (1: not / 7: very annoyed / disturbed) in response to the question: what is you’re feeling about the environmental noise of you residence? Which score best represents your feeling? (16) All calculations were done using SPSS (version 11.5). Chi-square test, t-tests and one-way ANOVA were used for the statistical assessments. A significance level of alpha =0.05 was used for all tests.

RESULTS The finding of the study showed that 47% of the subjects were fewer than 30, 40.8% Between 30 to 50 and 12.2% more than 50. In the present study it was observed that 69% were married, 9.9% were illiterate, 40.8% were high school graduates, and 49.3% had university education.32.7% of the subjects had government jobs, and 51% resided in the old district. In this study, the mean score of noise sensitivity was 63.5±16.1. The highest score in the subscale of “becoming sensitive to noise” was 30.6±9.5, and the subscale of “attitude to noise in where they live” revealed the lowest score of 13.8±4.6. (Table2). The results of environmental noise measurement in the studied stations showed that the highest Day–Night Noise Level (Ldn) belongs to Motahary st., (72.2 dB), whereas the highest total score of noise sensitivity is observed in this station (69.7±15.1) too. Also, the lowest score of sensitivity belongs to Shohada st. (59.4±13.7). (The lowest noise level compared to Motahary st.)(Table3). The one way analysis of variance showed significant difference in “attitude to noise control” (Factor IV) between illiterate and university education levels (P=0.02). (Table 4) In the present

Table1. Frequency distribution of residents of old and new part Old Parts

New Parts

Districts

Frequency

Districts

Frequency

Taleghani st1. Motahari st. Montazeri st. Shohada st. Total

23 63 32 56 174

Jamaran st. Mahallati st. Avini st. Ghaffari st. Total

43 48 57 33 181

Table 2. Mean and standard deviation of noise sensitivity and its subscales score Scales

Mean

becoming sensitive to noise (Factor I) disturbance in concentration (Factor II) attitude to noise in where they live (Factor III) attitude to noise control (Factor IV) Total score of noise sensitivity

30.6 17.4 13.8 19.5 63.5

9.5 5.4 4.6 4.9 16.1

ABOLHASANNEJAD et al., Curr. World Environ., Vol. 8(1), 29-36 (2013) Table 3: Maximum & Minimum of noise sensitivity and its subscales score in the studied station Scales

Max (Studied station)

Min(Studied station)

(Factor I) (Factor II) (Factor III) (Factor IV) Total score

33.8 ± 8.7(Motahari .st)1 18.4 ± 5.4(Motahari .st) 14.8 ± 4.5(Motahari .st) 21.7 ± 4.6(Motahari .st) 63.5 ± 16.1(Motahari .st)

28.1 15.6 12.8 17.8 59.4

1- Old district

2- New district

± 10.2(Avini .st)2 ± 5(Taleghani .st)1 ± 5.2(Taleghani .st) ± 4.3(Shohada .st)1 ± 13.7(Shohada .st)

Table 4: Comparing the mean of noise sensitivity subscales based on level of education Noise sensitivity subscale

Education Level

Mean ± SD

Pvalue

attitude to noise control (Factor IV)

illiterate high school graduates university education

18.4 ± 5.6 18.9 ± 5.1 20.2 ± 4.6

3.8

0.02

study, 79.3% of the subjects in the old district and 77.3% in the new district desired to have peace and quiet in their residence and this desire revealed significant relationship with the urban district (P=0.05). Moreover, 81.8% of the unmarried and 72.7% of the married individuals stated the desire to have peace and quiet in their residence and this showed significant relationship with the marital status (P=0.04).T-test showed no significant difference between the total score of noise sensitivity between new (63.14±17.4) and the old districts (63.87±14.7) (P=0.6).The total score of noise sensitivity among men and women was calculated 63.6±15.6 and 63.1±17.5 respectively. However t-test showed no significant difference in the total score of noise sensitivity between the two sex groups (P=0.3). The one-way analysis of variance showed no significant difference between the total score of noise sensitivity and its subscales with age groups, job, income, and household population. In this study, 56.3% of the subjects preferred peace and quiet in their residence to the beauty of house and residence and 43.7% enjoyed the beauty of the residues more than peace and quiet. In the study of the annoyance caused by noise, 28.5% of the subjects stated point 2 (partly satisfied) and 7.3% stated the highest rate of annoyance (point 7: absolutely dissatisfied). Noise

Fig. 1: Distribution of the studied areas

ABOLHASANNEJAD et al., Curr. World Environ., Vol. 8(1), 29-36 (2013) annoyance rate in the old district (noise level =70.5 dB) was higher than that of the new district (noise level = 65.3 dB) (P=0.001). In addition, Chi-square test found significant relationship between noise annoyance and job (P=0.01).However, this relationship was not significant with the variables of marital status, sex, age, education level, income and household population. The one-way analysis of variance showed significant difference between the rates of noise annoyance and the subscales of noise sensitivity (P<0.001). The highest mean score of noise sensitivity subscales, “attitude to noise in where they live” and “attitude to noise control” and the total score of noise sensitivity were calculated in those who had selected “a little satisfied” option in relation with the noise annoyance in the relevant stations. The difference between the mean of total score of noise sensitivity and the score of “becoming sensitive to noise” subscale in those without noise annoyance compared to others with different rates of annoyance was observed to be significant (p<0.002), (p<0.001).Regarding the subscale of “disturbance in concentration” among the mentioned groups, we observed a significant difference too (p<0.001). The highest rate of “disturbance in concentration” relate to individuals with high rate of noise annoyance. The difference between the mean score of “attitude to noise in where they live” subscale among individuals without noise annoyance compared to those with annoyance rates of 2,3,5 and 6 was shown also significant(p<0.002). Also, The difference in the subscales of “attitude to noise control” in those with annoyance rates of 2, 3 and 6 was significant (p<0.009). DISCUSSION According to the results of the present study, the mean total score of noise sensitivity was 63.5+16.1 that is lower than the mean score calculated in Belojevic and Jakovljevic study performed in two noisy and quiet urban districts in Yugoslavia17. The mean scores of noise sensitivity subscales in our study is also lower than that of the above research that may be because of different environmental conditions existing in the studied districts (Lower difference between max and min noise level in our study rather than Belojevic and Jakovljevic study) as well as different cultural

variables and personal characteristics of the populations residing in those districts. . Raw and Griffiths in their study showed that people’s selfregulated noise sensitivity is the most important individual characteristic for predicting the rate of annoyance cussed by traffic noise18. The results showed no significant difference between the total score of noise sensitivity between new and the old districts that may be because of lower difference between max and min noise level in old and new districts. Meanwhile, the results of Sukowski and coworkers’ study showed that children who live in quiet places are more affected by noise and its subsequent annoyance than those living in noisy and crowded districts19.Concerning the results of our study, the highest noise level and the highest total score of sensitivity are found in Motahari st. station. This street, because of its business situation leads to shopping centers as well as long length and lack of main branches leading to it has been the cause of increased traffic density. In Shohada st, station, The lowest total score of noise sensitivity was measured seeming that is because the street is wider, has less traffic density, more green spaces that eventually leads to lower noise level than that of Motahari st. . The results of Raw and Griffith’s study revealed that noise sensitivity was associated with noise level18. In the present study, a significant difference was observed between “attitude to noise control” and the subject’s education level (illiterates and those with university education) (P=0.02). This indicates that those with higher education level (due to more mental work) have greater desire to control the noise. Pathak et al., in their study in India, suggested that people with higher education level and income have greater awareness of the effects of noise on one’s health20, however, other studies showed the difference between them non significant13,21-24. In our study, significant difference was observed between desire to have peace and quiet in their residence and the type of urban district so that the number of those agreeing with peace and quiet in the old district was greater than that of in the new district indicating higher rate of noise annoyance in the old district. In the present study, more than 80% of the subjects were under 50 year and no significant difference was seen between the total score of noise sensitivity and its subscales, and age that is consistent with the results of Belojevic Zimmer s’ study13,17 while several others

ABOLHASANNEJAD et al., Curr. World Environ., Vol. 8(1), 29-36 (2013)

studies found significant relationship between total score of sensitivity and age21-24. The results of the study performed by Thomas et al. indicated the probability of the effect of aging on noise sensitivity particularly among woman25. The present study showed no significant difference between the total score of sensitivity among both sex groups and similar results were found in other researchers’ studies21-24,26. The results of our study revealed no significant difference between the subscales of noise sensitivity and the urban district, job, education level, income, and the member of household. Based on the findings of the study, the rate of noise annoyance in the old district was higher than that of the new district which is justifiable noting higher noise level in the old district become of the narrow width of the streets, heavier motorcycle traffic (due to low- income residents) that produces traffic burden and consequently noise pollution and residents’ dissatisfaction. In Sayed Abbas Ali’s study on road traffic noise also a direct relationship was observed between noise level and the percent of respondents who felt annoyed by noise12. More ever, Klaeboe et al. in their study showed that noise annoyance is greater among those residing in buildings with low-quality glass windows (old district)12 The findings of the present study revealed significant relationship between the rate of noise annoyance and job. In the study performed by Taheri Nameghi also a significant relationship between noise annoyance and job was observed that is consistent with the results of the present study27. In our study, no significant relationship was seen between noise annoyance and sex which is similar with the results of other studies on noise annoyance28,29. In the study by Michaud et al. in Canada, The rate of noise annoyance was greater among woman and among those with high-income and better social status30. In addition, in a study by Ali Mohammadi et al, it is reported that the rate of noise annoyance was greater among men than women31; This finding is not consistent with that of our study. In this study no significant relationship

was observed between noise annoyance rate and age indicating consistency with the results of Kjellberg and Ouis studies32,33. However, in the study conducted by Ali Mohammadi et al, a significant relationship was seen and the suggested that the causes of greater annoyance among the middleaged (30 to 49 years of age) were their personal characteristics and more responsibility for their families31. In the present study, the variables of marital status, education level , income, and the member of household showed no significant relationship with noise annoyance indicating similarity with the results of the study performed by Vincent28. In this study, a significant difference was observed between noise sensitivity and noise annoyance mean score. Thus, the noise sensitivity score among individuals who were somehow affected by some degrees of noise annoyance was higher than that in those not affected. This means that noise annoyance can directly and indirectly cause increase in noise sensitivity rate among residents. Belojevic, Stansfeld and Moehler, in their study found the same results17,34,35. Regarding that noise pollution problem is evident for all citizens particularly in big cities and plays a substantial role in noise sensitivity and annoyance rate among resident, it is suggested that in developing small cities, municipalities move noisy jobs to city margins, modify urbanization patterns, design highways and beltways in order to reduce the adverse effects of noise. In addition, further qualitative and quantitative studies on the relation of personality factor and noise sensitivity rate can be performed. ACKNOWLEDGEMENTS The present study was conducted in the framework of plan No.368 with the financial support of research deputy of Birjand University of Medical Sciences. Authors wish to thank the officials and those dear ones who provided their best cooperation in our project.

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Current World Environment

Vol. 8(1), 37-53 (2013)

Environmental Prevalence of Pathogens in Different Drinking Water Resources in Makkah City (Kingdom of Saudi Arabia) ABDULLAH A. SAATI1 and HANI S. FAIDAH2 1

Deparment of Community Medicine and Pilgrims Healthcare, Faculty of Medicine, Umm Al-Qura University, Saudi Arabia. 2 Deparment of Medical Microbiology, Faculty of Medicine, Umm Al-Qura University, Saudi Arabia. DOI : http://dx.doi.org/10.12944/CWE.8.1.05 (Received: February 26, 2013; Accepted: March 24, 2013) ABSTRACT Water is the most important substance in our daily life. Without it, life would not have been possible. Potable water is essential to humans and other life forms, as water is important to the mechanics of biological metabolisms in the body. Drinking water should be pure and free of contaminants to ensure proper health and wellness. Drinking water from different water resources such as wells and tankers should be free from contamination with waterborne pathogens including bacteria, fungi, viruses and parasites.Treatment of water using many ways is generally done in order to purify it.However, some water treatment techniques may not properly handled. In addition, water transferring techniques may contaminate the drinking water. Therefore, this study was aim toinvestigate drinking water in wells and tankers to observe any microbial pathogen presence as a source of health hazard.One hundred and eightwater samples from different sources were examined for microbial pathogens using filtration method on solid and liquid selective media. Four sources include sea desalinated water(SDW) from governmental water desalination factories, drinkable wells water (DWW), non-drinkable wells water (NDWW) and commercial desalinated water(CDW)from small commercial water desalination factories.Seven DWW samples (58.3%) and five NDWW samples (41.7%) were contaminated with E. coli. Eleven DWW samples (91.7%) and all NDWW samples (100%) were contaminated with P. aeruginosa. One DWW sample (8.3%) and twoNDWW samples (16.7%) were contaminated with E. faecalis. Four DWW samples (33.3%) and one NDWW sample (8.3%) were found contaminated with aspergillus spp. Four SDW samples (100%) and four CDW samples (50%) were contaminated with Penicillium spp. Conclusion:CDWwas found to be the more suitable than other sources for drinking if a biological hazard is the main target. However, contamination at transferring process should be addressed. Yet, water tanker which is a common transferring technique in many areas in Saudi Arabia and should be tested for safety level from point of contamination hazard during the transferring process.

INTRODUCTION Water is unsafe for human consumption when it contains pathogenic or disease-causing microorganisms. Pathogenic microorganisms (and their associated disease(s)) may include bacteria, such as Salmonella typhi (typhoid fever), Vibrio cholerae (cholera), Shigella (dysenter y, shigellosis), and viruses, such as poliovirus or Hepatitis A virus and protozoa such as Giardia lamblia (giardiasis) or Cryptosporidium parvum (cryptosporidiosis).A major challenge for water suppliers is how to control and limit the risks from pathogens and disinfection by-products. It is

important to provide protection from pathogens while simultaneously minimizing health risks to the population from disinfection by-products (EPA, 2011). In addition to bacterial-related health risks, faecal contamination carries the increased risk of viral contamination of the water source. Although viruses cannot multiply in water, some may remain static. This health risk is elevated in treated water (i.e. chlorinated tanks) where the faecal indicators may be absent. Many viruses have been identified as key etiological agents in outbreaks of drinking water derived gastrointestinal illness in the United States and Netherlands (Leclerc et al., 2002).

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Some micro-fungi are known to be opportunistic human pathogens. Airborne spores are an important potential source of microfungi found in water storage reservoirs. It has also demonstrated conclusively that filamentous microfungi grow and sporulate on the inner surfaces of water pipe and in soft sediments within the water distribution system (Sammon et al.,., 2011). Worldwide, over one billion people lack access to an adequate water supply; more than twice as many lack basic sanitation (WHO/UNICEF, 2006). Unsafe water, inadequate sanitation, and insufficient hygiene account for an estimated 9.1 percent of the global burden of disease and 6.3 percent of all deaths, according to the World Health Organization (PrĂźss-Ă&#x153;stĂźn et al.,., 2008). This burden is disproportionately borne by children in developing countries, with water-related factors causing more than 20 percent of deaths of people under age 14. Nearly half of all people in developing countries have infections or diseases associated with inadequate water supply and sanitation (Bartram et al.,., 2005). The presence of E.coli in water is a strong indication of recent sewage or faecal contamination. Sewage may contain many types of diseasecausing organisms. E. coli comes from human and animal waste. During rainfalls, snow melts, or other types of precipitation, E.coli may be washed into creeks, rivers, streams, lakes, or groundwater. When these waters are used as sources of drinking water and the water is not treated or inadequately treated, E.coli may end up in the drinking water (Health Canada, 2008). Faecalcoliforms and E.coli are bacteria whose presence indicates that the water may be contaminated with human or animal wastes. Microbes in these waters can cause short-term effects, such as diarrhea, cramps, nausea, headaches, or other symptoms. They may pose a special health risk for infants, young children, some of the elderly, and people with severely compromised immune systems (CDC, 2009). Some bacteria are ubiquitous in soil, waterand on surfaces in contact with soil or watersuch as Pseudomonas aeruginosa which is

an opportunistic pathogen. P.aeruginosa is an opportunistic pathogen. It produces tissuedamaging toxins and causes urinary tract infections, respiratory system infections,central nervous system, endocarditis (P.aeruginosa infects heart valves establishes itself on the endocardium), dermatitis, soft tissue infections, bacteraemia, bone and joint infections, gastrointestinal infections and a variety of systemic infections, particularly in patients with severe burns and in cancer and AIDS patients who are immunosuppressed (EHA, 2012). Spread occurs from patient to patient on the hands of hospital personnel, by direct patient contact with contaminated reservoirs, and by the ingestion of contaminated foods and water (EHA, 2012). The presence of faecal coliform in aquatic environments may indicate that the water has been contaminated with the faecal material of humans or animals. Faecal coliform bacteria can enter water bodies through direct discharge of waste from mammals and birds, from storm and agricultural runoff, and from human waste(Doyle and Erickson, 2006). Pet wastes (cats,dogs) can contribute to faecal contamination of surface waters. Runoff from roads, parking lots, and yards can carry animal wastes to streams through storm sewers. Birds can be a significant source of faecal coliform bacteria. Birds (seagulls, geese, swans) can all elevate bacterial counts, especially in freshwater systems (wetland, rivers, lakes and ponds). Some waterborne pathogenic diseases that may coincide with faecal coliform contamination include ear infections, viral and bacterial gastroenteritis, dysentery, typhoid fever and hepatitis A. The presence of faecal coliform tends to affect humans more than it does aquatic creatures, though not exclusively (Walkerton, 2011). Fungi are ubiquitous organisms that are widely distributed in nature. Several fungal genera have been shown to be allergenic, such as Aspergillus, Alternaria and Cladosporium (Black et al.,., 2000; Bowyer et al.,., 2006; Hedayati et al.,., 2007; Simon-Nobbe et al.,., 2006). Several studies have suggested an important role for waterborne

SAATI & FAIDAH, Curr. World Environ., Vol. 8(1), 37-53 (2013) fungi to endanger human health (Anaissie et al.,., 2001; 2003; Warris et al.,., 2001). Some of these studies have linked a genetic relationship between waterborne fungi and fungi isolated from clinical samples (Anaissie et al.,., 2001; 2003). There are several species of Aspergillus which cause infection to the human especially Aspergillus fumigatus. Aspergillosis is opportunistic respiratory infection which causes about 40% of fatal nosocomial infections. Aspergillus spp infections are transmitted by water (Graybill, 2001). Drinking water quality is usually determined by its pathogenic bacterial content. However, the potential of water-borne spores as a source of nosocomial fungal infection is increasingly being recognized. Sammon et al.,. (2010) demonstrated that numerous microfungal genera, including those that contain species which are opportunistic human pathogens, populate a typical treated municipal water supply in sub-tropical Australia. Penicillium spp. contain more than 225 species confirming to certain morphological criteria (Pitt et al.,., 2000). They can be isolated from the well water (Siqueira et.al, 2011). Penicillium marneffi is diamorphic, forming yeast-like cells in infected tissues, often they can found intracellular (Jolanta, 2005; Rajendran et al.,., 2006). In immunocomprimised people, P. marneffi considered as a common opportunistic pathogens which can cause systemic penicillosis in acquired immunodeficiency syndrome (AIDS) patients. Rodents are usual reservoirs for P. marneffi and may be involved in its transmission to humans (Cheesbrough, 2007). Pathogenic bacteriacan occur in surface water in large numbers, either being excreted in faeces or occurring naturally in the environment. Bacteria typically range in size between 0.5 and 2 micrometres. Disease-causing bacteria that can be transmitted by water include Vibrio cholerae, Salmonella sp, Campylobacter sp, Shigella sp, and Staphylococcus aureus. (Health Canada, 2006a). Aimsof the present study was to investigate drinking water in wells and tankers, and discover any microbial pathogens in these water as a source of biological environmental health hazard.

MATERIALS AND METHODS Sources of water samples One hundred and eight water samples (36 samples in tripicate) were collected from different water sources within Makkah city and analysed for bacterial and fungal contamination. Each sample was collected in sterile container sealed with screw cap after disinfection of dispensing point with flame. Then, samples were kept on ice till analysis take place in the laboratory within three hours. There were four sources of water included in this study: governmental sea desalinated water(12 samples),drinkable wells water(36 samples), non-drinkable wells water (36 samples) and small commercial desalination water factories (24 samples). Sample analysis Each sample was diluted with sterile distilled water at ratio of 1:10 as final volume 300 ml. Then, each 100 ml from the diluted sample was filtered using filtration equipment system (LabTech, Korea) with fresh cellulose nitrate filter (Sartorius, Germany, with pore size 0.45 รฌm) for each partition of the diluted sample. The three partitions were poured through filter trap, then two cellulose nitrate filter was taken out carefully by sterile forceps and placed on the MacConkeyplate (Biolab, Hungary) and bile esculin plate (Himedia, India)for bacterial growth and the third filter was placed on SD media plate (Himedia, India) for fungal growth. MacConkey and bile esculin plates were incubated for 24 hrs ยบC, while SD plate at 25 ยบC for 72 hrs (Harley et al.,., 2002). Isolation of microorganisms in water samples Bacterial identification Colony counter was used for counting of bacterial colonies on cellulose nitrate filters. The used formula for calculating number of bacteria per 100 ml water sample is: No. of bacteria/100 ml = colony dilution x dilution factor. Cellulose nitrate filter was placed and cultured in MacConkey or bile esculine media.

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Table 1: The percentages of bacterial contamination in investigated water samples Bacteria

Drinkable well water (n=36)

E. coli P. aeruginosa E. faecalis

Non-drinkable well water (n=36)

Desalinated Private water desalinated water (n=12) (n=24)

No.

21 33 3

58.3 91.7 8.3

15 36 6

41.7 100 16.7

0 0 0

n = Means total number of investigated samples from each water source. No. = Means number of positively contaminated water samples

Table 2: The percentages of fungal contamination in investigated water samples Bacteria

Aspergillus spp. Penicillium spp

Drinkable well water (n=36)

Non-drinkable well water (n=36)

Desalinated Private water desalinated water (n=12) (n=24)

No.

12 0

33.3 0

3 0

8.3 0

0 12

0 100

0 12

0 50

n = Means total number of investigated samples from each water source. No. = Means number of positively contaminated water samples

Table 3: Isolated E. coli from water samples Type of water/location

Drinkable wells water

water

Well 46

Well 48

Non-drinkable wells water

Well 27 Well 47 Well 52

WS: water source, WT: Water Tanker

E. coli

Source of

WT 1 WT 2 WT 3 WS WT 1 WT 2 WT 3 WT 1 WT 3 WT 1 WT 2 WT 2

Mean Colony count n =3

No. of bacteria/ 100 ml

3 5 4 2 2 4 1 1 2 1 3 2

30 50 40 20 20 40 10 10 20 10 30 20

SAATI & FAIDAH, Curr. World Environ., Vol. 8(1), 37-53 (2013) Colonies in MacConkey media were pink or yellow color, small size, while colonies in bile esculine media were black in color. On MacConkey media, pink colonies indicate lactose fermented bacteria like E. coli while yellow colonies indicate non lactose fermented bacteria like P. aeroginosa. The nonlactose fermented bacteria were cultured on nutrient agar media to confirm P. aeroginosa that give greenish color colonies. The black colonies in bile esculine media indicate E. faecalis.

Gram stain One drop of saline was mixed with a single colony on slide and fixed with gentle heat. Crystal Violet Oxalate (Atlas, UK) was poured on slide for 2-3 minutes. Gramâ&#x20AC;&#x2122;s Iodine (mordant) was poured on slide for 2-3 minutes. Alcohol decolorized was poured on slide for 1 minute. Safranin counterstain was poured on slide for 2-3 minutes. In each step, the slide was washed with distilled water. The slide

Table 4: Isolated P. aeruginosa from water samples Type of

P. aeruginosa

Source of

water/location

water

Drinkable wells water

Well 46

Well 48

Well 233

Non-drinkable wells water

Well 27

Well 47

Well 52

WT 1 WT 2 WT 3 WS WT 1 WT 2 WT 3 WS WT 1 WT 2 WT 3 WS WT 1 WT 2 WT 3 WS WT 1 WT 2 WT 3 WS WT 1 WT 2 WT 3

Mean Colony count n =3

No. of bacteria/ 100 ml

37 30 12 103 74 47 22 6 26 11 17 2 22 15 8 3 117 23 4 5 106 5 7

370 300 120 1030 740 470 220 60 260 110 170 20 220 150 80 30 1170 230 40 50 1060 50 70

WS: water source, WT: Water Tanker

Table 5: Isolated E. faecalis from water samples Type of water/location Drinkable wells water Non-drinkable wells water

WS: water source, WT: Water Tanker

Source of

E. faecalis

water

Mean Colony count No. of bacteria/100 ml N=3 WT 2 10 100 WT 1 20 200 WT 2 50 500

Well 46 Well 47

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was examined microscopically according to Cheesbrough (2007). Gram positive bacteria were blue or violet while gram negative bacteria were pink or red (Momenah, 2004). Brilliant Green Lactose Bile (BGLB) tube test Every pink colony from MacConkey media was cultured on BGLB (Biolab, Hungary) tube containing inverted Durham’s tube. The tube was incubated for 48 hours at 44 C to detect E. coli. The formation of gas in Durham’s tube was recorded if the sample was positive (Collee et al.,., 1989). Indole test Used to identify E. coli (indole positive). Each pink colonies from MacConkey media was cultured into tube of tryptone water (HIMEDIA, India). The tube incubated at 44 C. A few drops of Kovak’s reagent (BioMerieux, France) added the tryptone water culture after the incubation. After gently mixing of tube, positive indole test was indicated by formation of red color in the surface layer within 10 minutes Cheesbrough (2007). Oxidase test Used to identify P. aeroginosa (oxidase positive). 2-3 drops of freshly prepared oxidase reagent (BDH Laboratories, UK) were added to a piece of filter paper, then the plastic loop was used to take out a colony of the organism that appeared in the culture and placed on the filter paper. In positive cases, blue-purple color appears in few seconds Cheesbrough (2007). Fungi identification Macroscopic examination On SD media, texture, surface color and pigment of the reverse (underside) appeared in positive fungal growth. Fungi can cover the whole surface of SD media. Microscopic examination A small portion of the fungal growth was mixed with drops of Lactophenol Cotton Blue (LPCB)(Bios Europe, UK) on slide. The mixture was tested by using a pair of bent dissecting needles and the slide placed with cover. The cover slip pressed softly by using eraser end of the pencil. The slide tested by low and high power for presence of macroconidia, microcondia, spores and hyphae.

RESULTS Seven drinkable well water samples (58.3%) and five non-drinkable well water samples (41.7%) were contaminated with E. coli (tables 1,3). Eleven drinkable well water samples (91.7%) and all non-drinkable well water samples (100%) were contaminated with P. aeruginosa(tables 1,4). One drinkable well water samples (8.3%) and 2 nondrinkable well water samples (16.7%) were contaminated with E. faecalis (tables 1,5). Four Table 6: Isolated Aspergillus spp from water samples Type of water/location

Source of water

Drinkable wells water

Well 46 Well 48 Well 233

Non-drinkable wells water

Well 52

WT 2 WT 3 WS WT 3 WT 3

Table 7: Isolated Penicillium spp. from water samples Type of water/location

Source of water

Drinkable wells water

Al-Abdiah

Non-drinkable wells water

Al-Shalal Al-Aziziah Al-Kadir Qatrat Al-Nadah

WS: water source

WT: Water Tanker

WS WT 1 WT 2 WT 3 Before filtration

drinkable water samples (33.3%) and one nondrinkable water sample (8.3%) were found contaminated with aspergillus spp (tables 2,6). Four desalinated water samples (100%) and four private desalinated water samples (50%) were contaminated with Penicillium spp (tables 2,7).

SAATI & FAIDAH, Curr. World Environ., Vol. 8(1), 37-53 (2013) DISCUSSION Waterborne pathogens can cause a problem to drinking water supplies, recreational waters, and source waters for agriculture, and aquaculture. Sources of pathogens include municipal wastewater effluents, urban runoff, agricultural wastes and wildlife. A drinking water killed 54 people and induced illness 400,000 in Milwaukee at 1993. Over 200 outbreaks of infectious diseases in Canada associated with drinking water occurred between 1974-1996. Pathogen contamination of irrigation water or shellfish beds can produce risks to human food supplies. In addition, declines in amphibian populations may be related to fungal or viral pathogens (The National Water Research Institute, Canada, 2001). The microbiological guidelines and standards for drinking water for E. coli, P. aerugnosa and E. faecalis are zero colony count/100 ml of water sample (The Natural Mineral Water, Spring Water and Bottled Drinking Water Regulations, 1999). Periodicity and intensity of rainfall have been shown to impact level of microbial contaminant entering tanks, and the more time between events, the more contaminants accumulate and are washed into the tank (Abbott et al.,., 2006). Outbreaks of disease attributable to drinking water in USA still occur and can lead to serious acute, chronic, or sometimes fatal health consequences, particularly in sensitive and immunocompromised populations. From 1971 to 2002, there were 764 waterborne outbreaks associated with drinking water, resulting in 575,457 cases of illness and 79 deaths (Blackburn et al.,. 2004). Contamination of water is affected by the number of pathogens in the source water, the age of the distribution system, the quality of the delivered water, and climatic conditions. Others have recently estimated waterborne illness rates of 12M cases/ year and 16 millioncases/yr. (Craun et al.,. 2006). Reynolds et al.,. (2008) found that 10.7 million infections and 5.4million illnesses/year occur in populations served by community groundwater systems; 2.2 million infections and 1.1 million illnesses/year occur in noncommunity groundwater

systems; and 26.0 million infections and 13.0 million illnesses/year occur in municipal surface water systems. The total estimated number of waterborne illnesses/yr. in the U.S. is therefore estimated to be 19.5 million/year. The safety of drinking water is evaluated by the results obtained from faecal indicators during the stipulated controls fixed by the legislation. However, drinking-water related illness outbreaks are still occurring worldwide (Figueras and Borrego, 2010). Drinking-water quality in both urban and rural areas of Pakistan is not being managed properly. Most of the drinking-water supplies are faecally contaminated. At places groundwater quality is deteriorating due to the naturally occurring subsoil contaminants or to anthropogenic activities. The poor bacteriological quality of drinking-water has frequently resulted in high incidence of waterborne diseases while subsoil contaminants have caused other ailments to consumers (Aziz, 2005). In the developing world, an estimated 10 million young children died there in 2006. Of these deaths, WHO estimates that 16.5 percent, or at least 1.65 million, were due to diarrheal diseases, many of which were caused by contaminated water (WHO, 2008). Deaths caused by nondiarrheal infections like typhoid fever are also related to contaminated water (Crump et al.,., 2040).

E.coli The obtained results revealed thatEscherichia Coli (E. coli) was found in water sources and tankers. Some water tankers were contaminated with E. coli either due to lack of proper treatment and cleaning of tankers or contamination of water well sources. However, the presence of E. coli indicates recent sewage or animal waste contamination (EPA, 2001). E. coli contamination in the present study was found to be higher than that recorded by Golas et al., . (2002) which represent 10.7%and Malakauskas et al., . (2007)found 16.7% of E. coli contamination in Lithuania different wells. Admassu et al., . (2004)found 28.6% of E. coli contamination in wells waterwhile was58.33% in 12 water samples (Oyetayo et al.,., 2007)which is higher than that reported in our study.

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The survival of enteric bacteria, like Salmonella spp. and E. coli, within the tank environment is influenced by temperature and the presence of nutrients (Leclerc et al.,., 2002). While leaves are a common source of organic matter, dust, especially during times of drought when particles of ground-based organic and inorganic matter can be carried for hundreds of kilometres during dust storms (Goudie, 2009), is another source. Evans et al.,. (2007) demonstrated that airborne pathogens from surrounding soils, including E. coli, are significant contributors to the microbial contamination of tanks. Therefore, in addition to the commonly attributed sources of microbial contaminants, birds, possums or rodents defecating or dying in tanks (Australian Government, 2004), rural participants who graze sheep and cattle, may be exposed to microbial contaminates from higher order-mammals. Exposure to microbial contaminants from higher-order mammals brings with it an increased health risk due to the greater zoonotic potential of such microorganisms. The Australian Government in its guidance on use of rainwater tanks (Australian Government, 2004) identifies livestock waste as a health hazard only for underground tanks and aerosol waste appears unconsidered. This partitioning of risk, between inground and above-ground tanks needs to be reconsidered in light of the work (Evans et al.,., 2007). Increasing outbreaks (Callaway et al.,., 2009; Goode et al.,., 2009) of gastrointestinal illness from livestock-derived E. coli indicates it is perhaps time to rethink the significance of the presence of E. coli in tanks, particularly in rural areas with livestock. In 2006, the most notorious strain of E. coli, STEC O157, was responsible for a waterborne-related outbreak that affected more than 100 people across America and caused at least one death when bacteria transferred from a contaminated water source to a spinach crop that was then packaged and widely distributed (Bettelheim 2007). The survival rate of E. coli in water is varies from 13-245 days (LeJeune et al.,., 2001). Because it can travel long distances underground, it is can be used as indicator for faecal contamination of ground water (Foppen and Schijven, 2006).In

Ireland, bacterial contamination of water is a national concern, with the EPA reporting that over 25% of groundwater samples were contaminated with E. coli in 2004 to 2006. E. coli is the most important indicator used in Ireland and its presence indicates water is unfit for human consumption. It has long been thought that E. coli can only survive for short periods of time in the environment, hence its almost universal use as an indicator of recent faecal contamination of waterways (APA Teagasc, 2010).

E. coli O157:H7 was isolated from many water wells in cattle farms. It may be found in water sources, such as private wells, that have been contaminated with feces from infected humans or animals. Waste can enter the water through: sewage overflows, sewage systems that are not working properly, polluted stor m water runoff, and agricultural runoff. Wells may be more vulnerable to such contamination after flooding, particularly if the wells are shallow, have been dug or bored, or have been submerged by floodwater for long periods of time (CDC, 2009). The Ministry of Health’s Annual Report on Drinking-Water in New Zealand showed unacceptable levels of E.Coli were found in the water of 72,000 or 2 percent of people accessing a registered water supply (Danya, 2011). Parts of the Danish capital Copenhagen were without clean drinking water after high levels of the E.coli bacteria were detected in the municipal tap water system (Berlingske daily’s Web site, 2011). Australia is particularly vulnerable to threats to both the quality and quantity of drinking water availability because most rainfall evaporates quickly, resulting in twenty percent of the population relying on ground water for drinking supplies which “is extremely difficult to clean up if it becomes polluted” (NHMRC 2004). More than half of the tank water sampled failed to meet the Australian Drinking Water Guidelines for safe drinking water. Levels of E. coli were up to 230x more than the acceptable levels proposed by the Australian Drinking Water Guidelines. Qualitative research found most consumers were unaware of the risks associated with drinking raw rainwater. Further, few took steps to minimize their risk through accepted

SAATI & FAIDAH, Curr. World Environ., Vol. 8(1), 37-53 (2013) water management practices (Andrea and Angela, 2010). Contamination of water samples with Pseudomonas. aeruginosa Our results showed that Pseudomonas aeruginosa(PA) was the most common microbial contamination in water sources and tankers. All water tankers and majority of water sources (wells) were contaminated due to lack of proper treatment and cleaning. High numbers of PA which represent 1030 bacteria/100 ml were detected in one water source of drinkable well water compared with its water tankers. Also there were high number of PA which represent 1170 bacteria/100 ml in one water tanker of non-drinkable well water. Bari et al.,. (2007) showed lower PA contamination (4%) from wells than that reported in our study. Geldreich (1996) found that PA was widely distributed in nature and most prevalent opportunistic pathogen isolated from the water samples.

P. aeruginosa is part of a large group of free-living bacteria that are ubiquitous in the environment. This organism is often found in natural waters such as lakes and rivers in concentrations of 10/100 mL to >1,000/100 mL. However, it is not often found in drinking water. Usually it is found in 2% of samples, or less, and at concentrations up to 2,300 mL(-1) or more often at 3-4 CFU/mL. Its occurrence in drinking water is probably related more to its ability to colonize biofilms in plumbing fixtures (i.e., faucets, showerheads, etc.) than its presence in the distribution system or treated drinking water (Mena and Gerba, 2009). Trautmann et al.,. (2005) in between 1998 and 2005 showed that 9.7% and 68.1% of randomly taken tap water samples on different types of ICUs were positive for PA, and between 14.2% and 50% of infection/colonization episodes in patients were due to genotypes found in ICU water. Although much has been written about biofilms in the drinking water industry, very little has been reported regarding the role of PA in biofilms. Tap water appears to be a significant route of transmission in hospitals, from colonization of plumbing fixtures (Mena and Gerba, 2009). Outbreaks have been reported from exposure to PA in swimming pools and water slides (Mena and Gerba, 2009).

The bacteriological content of water in large dispensers (coolers)and from the 20 liter supply bottles had P. aeruginosa in 25% of samples from the large supply bottles and also in 24% of water specimens from the actual coolers. A further 21.6% of 162 specimens from the coolers yielded P. aeruginosa (Baumgartner and Grand, 2006).

Enterococcus faecalis In the present study, enterococcus faecalis(E. faecalis) was isolated from drinkable and non-drinkable water samples (8.3% and 16.7%) respectively.Ahmed et al.,.(2005)examined of 12 water samples collected from different wells in Egypt and showed that bacterial contamination Staphylococcus aureus (22.22%), Staphylococcus epidermidis (11.11%), Enterococcus faecalis (11.11%), Bacillus Cereus (55.56%), Yersinia enterocolitica (37.5%), Klebsiella pneumoniae (18.75%), Pseudomonas aeruginosa (12.5%), Escherichia coli (6.25%), Enterobacter agglomerans (6.25%) and Citrobacter freundii (6.25%). These finding were similar to the current results in isolation of P. aeruginosa, E. coli and E. faecalis. The differences in results may be to several reasons including geographical differences, types of collection method, number of microorganisms which were isolated and type of water samples. Our results revealed that E. faecalis was found in tankers which was the lowest percentage of bacterial contamination. In contrast to our results, Malakauskas et al.,. (2007) found E. faecalis (23.4%) contamination in may wells. Adbelkarem and Hassan (2000) found that no E. faecalis was detected in wells. In the developing world, 90% of all wastewater still goes untreated into local rivers and streams.About 50 countries, with roughly a third of the worldâ&#x20AC;&#x2122;s population, suffer from medium or high water stress, and 17 of these extract more water annually than is recharged through their natural water cycles. Enterococcus faecalis not only affects surface freshwater sources (rivers and lakes), but it also degrades groundwater resources(UNEP International Environment, 2002). Failing home septic systems can allow coliforms in the effluent to flow into the water table,

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aquifers, drainage ditches and nearby surface waters. Sewage connections that are connected to storm drain pipes can also allow human sewage into surface waters. Some older industrial cities in USA use a combined sewer system to handle waste. A combined sewer carries both domestic sewage and storm water. During high rainfall periods, a combined sewer can become overloaded and overflow to a nearby stream or river, bypassing treatment(Walkerton, 2011). Poor quality of water is due to contamination by microorganisms of human or animal origin (Ratajczak et al.,., 2010).Total coliforms, faecal coliforms, E. coli and enterococci are commonly used microbial indicators of water quality (Davis et al.,., 2005). Several studies of both recreational and drinking water samples suggested that enterococci are more relevant indicators of faecal contamination than faecal coliforms and E. coli (Grammenou et al.,., 2006; Kinzelman et al.,., 2003). Approximately 13% of surface waters inUSA do not meet designated use criteria because of high densities of faecal indicator bacteria (â&#x20AC;&#x153;Microbial Source Tracking Guide Documentâ&#x20AC;? 2005). Despite the uncertainty of the effects of animal faecal contamination of ambient waters to human health, microbiological contamination of recreational waters from human faeces is regarded as a greater risk to human health as they are more likely to contain human-specific pathogens. E. coli and Enterococci are considered to have a higher correlation with outbreaks of swimming-associated gastroenteritis than total and faecal coliforms (Wikipedia, 2011). Twelve water sources (9 wells, 3 taps) and 15 latrines were identified and used by 444 inhabitants. Well and tap water showed heavy faecal contamination with more than 1000 CFU/100 ml. The contamination of drinking water in Bissau due to poor construction, maintenance and improper use ten years after the civil war, demonstrates the need to allocate resources after conflicts in the area of water and sanitation (Colombatti et al.,., 2009). A total of 300 water samples were collected from 20 different drinking water sources in Kamalapur, Dhaka city from August 2004 to January 2005. The

level of faecal contamination was estimated using measurements of faecal indicator bacteria (total coliforms, faecal coliforms and faecal streptococci). The unacceptable level of contamination of total coliforms (TC), faecal coliforms (FC) and faecal streptococci (FS) ranged from 23.8% to 95.2%, 28.6% to 95.2% and 33.3% to 90.0%, respectively (Sirajul Islam et al.,., 2007). Copeland et al.,. (2009) measured faecal contamination in 231 randomly primary drinking water samples from selected households. Risk for contamination was compared across source and storage types. A third of samples (30.3%) was contaminated; the source with the highest frequency of contamination was well water (23/24: 95.8%). For tap water, the type of storage had a significant effect on the susceptibility to contamination. The observed pattern of contamination demonstrated the relative potential contributions of both source and storage. Contamination of water samples with Aspergillus spp The recorded results here showed that Aspergillus spp. ontamination in water tankers and water well source. Warris et al.,. (2001) reported that 21% of drinking water samples have been contaminated with Aspergillus spp. which were higher than that in our obtained results. Aspergillus spp. were recorded by Anaissie et al.,. (2002) to be more as 70% of all drinking water samples examined. In comparing to this study, our findings were lower contamination. Aspergillus spp. are opportunistic and can cause health problems in immunocompromised patients (Graybill, 2001). In Brazil, 50 people died due to algal toxins in water used for haemodialysis in 1996. Toxins can attack the liver, the nervous system or irritate skin, yet very few of these toxins have been isolated and characterized. Taste and odour problems in potable water are increasing worldwide and are produced by microorganisms such as bacteria and fungi (TheNational Water Research Institute, Canada, 2001). A total of 197 hot and cold water samples were collected from the main water supply lines and from the taps at three different hospital sites of

SAATI & FAIDAH, Curr. World Environ., Vol. 8(1), 37-53 (2013) the University Hospital of LiĂ¨ge. Filamentous fungi were recovered from 55% and 50% of the main water distribution system and tap water samples, respectively, with a mean of 3.5 and 1.5 colony forming units per 500 ml water. Aspergillus spp. were recovered from 6% of the samples of the water distribution system and A. fumigatus was the most frequently recovered species (66.6%). Fusarium spp. was predominant at one site, where it was found in 28% of tap water samples (Hayette et al.,., 2010). Two hundred and forty water samples were collected from four university hospitals. 77.5% were positive for fungal growth. Aspergillus (29.7%), Cladosporium (26.7%) and Penicillium (23.9%) were the most common isolated. Among Aspergillus species, A. flavus had the highest frequency. Highest colony counts were found in autumn. Aspergillus predominated in autumn, Cladosporium in winter and spring and Penicillium in summer. This results showed that hospital water should be considered as a potential reservoir of fungi particularly Aspergillus (Hedayati et al.,., 2011). Waterborne fungi have been suspected as a source for allergic reaction in sensitive individuals and they may contribute to produce mycotoxins in water (Hageskal et al.,., 2009). Therefore, study on fungal contamination of water distribution system especially hospitals water has been an interesting subject for many investigators from different countries in the past decade (Hageskal et al.,., 2006; Kanzler et al.,., 2008; Pires-Goncalves et al.,., 2008; Hayette et al.,., 2010). Gottlich et al.,. (2002) reported a mean positivity of 26.6% in a Belgian university hospital and groundwater-derived drinking water from water supplies in Germany. Contamination of water samples with Penicillium spp Our results indicated that Penicillium spp. were found in desalinated water and private desalinated water samples with 100% and 50% respectively. Desalinated water tankers supplies water to private desalinated water stations, therefore, Penicillium spp. were detected in both sources. Kanzler et al.,. (2007) isolated fungi from 38 water wells samples asCladosporium spp.

(74.6%), basidiomycetes (56.4%) and Penicillium spp. (48.7%). This study suggested that drinking water can be a reservoir for opportunistic fungal pathogens. These pathogens are naturally found in the environment and are not usually regarding as pathogens. However, they can cause disease in human with impaired defence mechanisms like the elderly or young patients with burns, immunosuppressive therapy patient(Hussain et al.,., 2001). Surface water contamination occurs as a result of direct runoff from waste sites to streams, lakes and wetlands, and indirectly as contaminated groundwater discharges to surface waters. The contamination of groundwater is different from surface water contamination. Because we cannot observe groundwater, we typically discover that the groundwater is contaminated once a well or surface water body becomes contaminated. Surface water contamination occurs quickly and can be stopped at the source. However, groundwater contamination may commence years after the waste source is in place. The slow release rate causes it to take years to thousands of years to move through the groundwater flow regime, and groundwater can be difficult, if not impossible to remediate, and prohibitively costly to remediate. Ultimately all contaminated groundwater will discharge to surface water. Thus, should serious groundwater contamination occur, the destruction of drinking water supplies and aquatic ecosystems occurs for decades to hundreds of years (Coote and Gregorich, 2000). Effects on human civilization Water fit for human consumption is called drinking water or potable water. Water is made fit for drinking by filtration,distillation, or by a range of other methods. Poor water quality and bad sanitation are deadly; about five million deaths a year are caused by polluted drinking water. WHO (2010) estimates that safe water could prevent 1.4 million child deaths from diarrhoea each year. The contamination of drinking water sources with microbial pathogens in an on-going problem. More than three million people die every year from water-related disease and 43% of waterrelated deaths are due to diarrhoea (WHO, 2008).

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The majority of diseases are infectious in nature caused by bacteria, fungi, viruses and parasites, execrated in human faeces which may lead to contaminate water supplies (Tambekar and Hirulkar, 2007). Well water is one of the water sources which can be used for population purposes. In the current study, one (16.7%) out of all wells of drinkable well water is clean. Therefore, the remaining wells found to be contaminated with bacterial and fungal pathogens. In Ontario, there are an estimated 500,000 wells which about 10% - 34% of these wells were clean and there were no contamination (Goss et al.,., 1998). An investigation carried out in Nigeria found that all water samples collected from 15 wells were bacterial contaminated (Olabisi et al.,., 2008). Same study estimated 20 colony counts per 100 ml as a maximum value, while the present study found that the maximum value of colony counts was 117 per 100 ml. From the obtained results in our study we can conclude that: (1) Certain wells and certain water tankers were found to be contaminated with different microbial pathogens, bacteria and fungi. (2) Penicillium spp. was detected only in desalinated water and private desalinated water before filtration process. (3) The suitable water for drinking is the private desalinated water because they come under different treatment processes like filtration.

6 Recommendations Safe water and sanitation pose universal challenges for public healthas: 1 Periodical monitoring of water sources for pollutants (chemical & microbial). 2 Periodical testing of water tankers for their microbial contamination. The risk of microbial contamination in tanks can be reduced by

several well-known practices. These include the installation of first flush devices, cleaning gutters, both of which are designed to reduce the build-up of potential contaminants and the use of filtration to remove potential contaminants before use Enhanced funding is needed to validate newer molecular detection tools, understand the ecology of pathogens in aquatic ecosystems, better predict disease outbreaks, and improve emergency responses. A preventive approach to pathogen pollution should be taken by developing countries in the form of a source water protection program for all major freshwater sources. The identification and control of threats posed by waterborne pathogens will also require effective pathogen detection techniques. The need to develop, evaluate and validate newer molecular tools for pathogen detection such as PCR techniques and DNA microarrays. Rapid advances in fields such as genomics offer the potential to develop improved pathogen detection tools. Encourage infrastructure planning, including technological advances, to ensure that improved treatment and environmental protection measures are not diminished by development or population growth. Programs are needed to assess the effects of aerial emissions on drinking water quality. An improved understanding is needed of methods for assessment and risk analysis of the cumulative effects of agricultural, forestry and other land use activities (e.g., ore, oil and gas exploration) as well as pointsource inputs (e.g., municipal and industrial discharges) on surface and ground waters.

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Current World Environment

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Mercury Induced Biochemical Alterations as Oxidative Stress in Mugil cephalus in Short Term Toxicity Test J.S.I RAJKUMAR1* and SAMUEL TENNYSON2 *Department of Advanced Zoology and Biotechnology, LoyolaCollege, Chennai - 600 034, India. 2 Department of Zoology, Madras Christian College, Chennai - 600 059 India. DOI : http://dx.doi.org/10.12944/CWE.8.1.06 (Received: February 11, 2013; Accepted: March 21, 2013) ABSTRACT Mugil cephalus juveniles of size 2.5 Âą0.6cm were exposed to mercury in short term chronic toxicity test through static renewal bioassay to detect the possible biochemical agent as biomarkers in aquatic pollution and in estuarine contamination as specific. Lipid peroxidation levels, glutathione S-transferase, catalase, reduced glutathione and acetylcholinesterase were studied as biochemical parameters.Increased thio-barbituric acid reactive substances levels were observed under exposure to mercury, leading to the oxidative damage resulting in lipid peroxidation. Decreased activities of antioxidants, catalase and increased glutathione-S-transferase under short term chronic exposures to mercury were more prominent in metal stress suggesting activation of physiological mechanism to scavenge the ROS produced. Decreased values of reduced glutathione on prolonged exposures to mercury indicate utilization of this antioxidant, either to scavenge oxy-radical or act in combination with other enzymes. The acetylcholinesterase activity was found to be decreased during mercury exposure. The results also suggest that mercury alters the active oxygen metabolism by modulating antioxidant enzyme activities, which can be used as biomarker to detect sub-lethal effects in aquatic pollution.

Key words: Acetylcholinesterase; antioxidants; catalase; oxidative stress, reactive oxygen species, Mercury, lipid peroxidation. INTRODUCTION Estuarine pollution is an ongoing activity started long back however intensified during the last few decades, and currently the circumstances has become alarming, especially in India1. Metals are natural components; however become contaminants of the aquatic environment, due to anthropogenic activities 2 .Bioavailability and indestructible nature are the most fundamental property of heavy metal exerting toxic effects on living organisms when they exceed a certain concentration limit 3 . Heavy metals in metal accumulating organisms are linked to their ability to bind incoming metals, thereby controlling their intracellular availability leading to tolerance ability of test organisms. Oxidative stress induced by metals could be the best indicator and often interpreted as a failure of detoxification mechanisms in metal active sites such as mitochondria4. Cellular

measurements and its responses to chemical contaminants like heavy metals in test organisms are used as bio-indicators from aquatic environment allowing early detection of biological effects as well as assessment of the extent of contamination of pollutants5,6. Depletion of glutathione and sulfhydryl groupsof protein due to heavy metals results in increased Reactive oxygen species (ROS) production such as, hydrogen peroxide,superoxide anion and hydroxyl radicals7. Superoxide anion and hydrogen peroxide is generated from sequential reduction of oxygen8. Another reactive species peroxynitrite is produced when superoxide anion rapidly reacts with nitric oxide and has the potential to trigger cellular death9. ROS are measured as crucial intermediaries for the metal-triggered tissue injuries and apoptosis7. There must be effective antioxidation systems in the organisms to prevent

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oxidation induced damage. Some components of anti-oxidation systems involve reduced glutathione (GSH) and antioxidant enzymes including free radical scavenging enzymes, such as Superoxide dismutase (SOD), Catalase (CAT), Glutathione peroxidases (GPX) and Glutathione reductase (GR). Other related enzymes are Glyoxalase I (GI), Glyoxalase II (GII) and Glutathione S-Transferase (GST). GSH reduces ROS under oxidative stress, with the concomitant formation of theoxidized glutathione (GSSG) 10. Particularly in the aquatic environment, oxidative stress is one of the ecological significance, providing a sink for many pollutants that are capable of causing oxidative stress11. Alterations in the activity of enzymes and related biomarkers are the potential tools for aquatic toxicological research12. Fish being a source in nutrient cycling and maintaining community balances in aquatic ecosystem play an important role in energy flow and are regarded as high protein to man 13 . Hence convenience of fish for assessing environmental conditions in aquatic ecosystem as test organisms has gained eminence in recent years 14 .Fish are considered as suitable biomonitors for environmental pollution and they are exposed to the heavy metals in vitro and to study the effectsof heavy metals in aquatic ecosystems 15. The study related to antioxidant defense system is being increasingly reported due to its potential ability to provide biochemical biomarkers that can beused in environmental monitoring system such as aquatic pollution and estuarine contamination in specific 11 . Tools involving biomarkers in environmental monitoring confer significant advantages over traditional chemical measurements because measured biological effects can be meaningfully linked to environmental consequences so that environmental concernscan be directly addressed 16. Hence, in the present study the biochemical parameters such as lipid peroxidation levels, Glutathione S-transferase, catalase, reduced glutathione and acetylcholinesterase were measured by exposing juveniles of Mugil cephalus to mercury under short-term toxicity tests (static renewal).

MATERIALS AND METHODS Fingerlings of Mugil cephalus of mean 2.5 ±0.6cm in length and 0.13 ±0.02g in weight were selected for the study. Collected juveniles were immediately transported to the laboratory in air filled plastic bags and acclimatized in 200 L Fiberglass reinforced plastics (FRP) tanks with aerated natural filtered seawater. Stock solutions of mercury were freshly prepared by dissolving mercury (II) chloride in de-ionized (double distilled) water. Fresh stock solutions were prepared daily. These solutions were serially diluted to get the experimental concentration for the toxicity test. The experimental method includes static renewal (24hour renewal) test17. Five concentrations in a geometric series including control were prepared for the test for 14 days in short-term chronic toxicity test 18. Toxicant and seawater were replaced on daily basis. Test animals were fed three times during the test. Maximum-allowable control mortality was 20 per cent for short-term chronic toxicity test18. At the final stages of the toxicity test, the tissue samples of survived test animals were pooled and made in duplicates. For the analysis of lipid peroxidation marker and antioxidant enzyme activities, 1g tissue was homogenized in chilled pestle and mortar with 5ml homogenization buffer (0.25M sucrose, 10 mM Tris, 1 mM EDTA, and pH 7.4) and centrifuged at 5,000 rpm for 15 minutes at 4°C. The resulting supernatant was the homogenate which was used for the estimation of various biochemical assays. Lipid peroxidation (LPO) Lipid peroxidation level was assayed by measuring Malondialdehyde (MDA), a decomposed product of polyunsaturated fatty acids. Hydro peroxides were determined by the thiobarbituric acid reaction and was measured at 532 nm in the UV-Spectrophotometer19. The amount of Thio-barbituric acid reactive substance (TBARS) was calculated by using an extinction coefficient of 1.56 x 105/M/cm and expressed as nmol TBARS formed /mg protein. Glutathione s-transferase (GST) Activity of Glutathione S-transferase (GST) was assayed at 340 nm by measuring the increase in absorbance using 1-chloro-2, 4-dinitro benzene (CDNB) as the substrate 20 . The results were

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expressed as nM of GSH and CDNB conjugate formed /min/mg protein.

procedure) was used to compare the results with control using graphpad prism version 5.

Catalase (CAT) Catalase (CAT) activity was measured at 240 nm by determining the decay of hydrogen peroxide levels and was expressed as µmol of hydrogen peroxide consumed /min/mg/protein21.

RESULTS AND DISCUSSION

Reduced glutathione (GSH) The reduced glutathione (GSH) was measured at 412 nm using 5, 5-dithiobis-(2-nitro benzoic acid) (DTNB) reagent22. The values were expressed as µmol of GSH oxidized/mg protein. Acetylcholinesterase activity (AChE) Acetylcholinesterase activity (AChE) activity was determined using Ellman’s reagent, DTNB (5, 5’-dithio-bis (2- nitro benzoic acid); 0.5mM) and acetylthiocholine iodide (ACTI) as substrate23, 24, 25 . The rate of change of absorbance at 412nm was recorded over 1.5 minutes at 25°C. The protein concentration of each of the sample extract was determined measured at 750 nm in UVSpectrophotometer26. One-way ANOVA (Dunnetts

Scavenging enzymes at lower concentration in juvenile fish makes them vulnerable to oxidative damage when attacked by ROS 27 . M. cephalus exposed to exposure concentrations experienced rigorous Oxidative stress (OS) characterized by significant alterations in biomarkers,were also been observed in brain samples of the mullet28. Removal of H2O2 is an important strategy of marine organisms against oxidative stress29. Increased activities of CAT have been reported in several fish and invertebrate species30, 31. Concentration of LPO was significantly higher ( P < 0.001) in higher concentrations of mercury due to increased levels of exposure indicating the importance of antioxidant32.The level of total protein to mercury exposure significantly (P<0.001) decreased in 10 µg/l. Glutathione-Stransferase (GST) exhibited a significant (P<0.001) increase in the activity at 8 and 10 µg/l concentration of mercury. Reduced glutathione (GSH) level

Table 1: Biochemical alterations in M. cephalus exposed to mercury in short-term chronic toxicity test Concentration (µg/l)

Proteina

GSTb

GSHc

CATd

AchEe

16.92 ±0.09 15.82 ±0.00 ns 14.38 ±0.53** 14.59 ±0.59** 13.99 ±0.00** 12.57 ±0.71***

3.80 ±0.14 4.55 ±0.21ns 6.37 ±0.19*** 5.40 ±0.28** 6.52 ±0.03*** 7.95 ±0.35***

93.12 ±1.57 87.45±1.70*

213.28±17.03

4.50±0.71 9.94±0.41

1 2 4 8 10

MDAf

312.68±12.10*** 6.65±0.21* 18.71±1.20*

70.76±0.67*** 197.63 ±4.81 ns 66.93±1.36*** 179.60 ±0.90 ns 57.39±2.45*** 153.01±10.40**

2.50±0.71* 23.60±1.75**

1.85±0.07**40.57±0.64***

44.69±0.76*** 136.28±5.72***

1.00±0.14**52.68±3.84***

2.55±0.64* 30.07±0.59***

***values are significant at P<0.001, ** values are significant at P<0.01, * values are significant at P<0.05. One way ANOVA (Dunnetts multiple comparison test (á=0.05)); Values are the mean and standard deviation. a-mg protein /g tissue, b-(Glutathione-S-transferase) GST activity nM of CDNB /min/mg protein, c- (Reduced glutathione) µmol of GSH oxidized / mg protein , d- (Catalase) µmol of H2O2Consumed/min/mg protein, e- (Acetylcholinesterase) nM/min/ mg protein, f- (Lipid peroxidation) Nm of MDA/ mg protein;The concentration column (mg/l) contains ‘0’ indicating control in the test conducted in triplicate; ns-not significant

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significantly (P<0.001and 0.05) decreased in the 14 days of exposure compared to control in all the concentrations. CAT and LPO showed trend of significant decrease and increase in linear increase in the mercury concentration. The activity of AChE significantly ( P <0.01 and 0.05) decreased throughout the exposure concentration. M. cephalus exposed in short-term chronic toxicity test showed that all the biochemical components and antioxidative enzymes of the oxidative stress showed significant changes in the tissues exposed to mercury Table 1. Protein content in M. cephalusmight be due to the proteolysis process for energy production and utilization owing to the decreased food intake of test organisms under stress33.These data may indicate a faster rate of GSH utilization or degradation, which could be responsible for the observed lower GSH content. Moreover, increase of GSH content may be related to prevention of oxidative challenge34. Aquatic organisms maintain high content of GSH in tissues and increased content has the function of protection that could provide the first line of defense against the influence of toxic heavy metals35, 36. Esterases are considered as potential biomarkers to differentiate the levels of contaminants37. Maintenance of enzyme activities

in relation to oxidative stress may serve as important markers of the presence of hazardous substances38, 39 . Mullet (Mugil sp.) from contaminated Spanish areas revealed increased activities of antioxidant (catalase) and detoxifying GST enzymes 40,41. Channel catfish (Ictalurus punctatus) exposed to effluents resulted in a significant increase in catalase activity42. Changes in GST activity exhibit detoxification process in fish exposed to toxic compounds4,5. Decrease of GST was observed in fish exposed to mercury in the present study. This induction in GST activity could indicate a defense of fish against oxidative stress damage produced by adverse conditions such as heavy metal contamination. Increased levels of lipid peroxidation(LPO) have been observed in fish under experimental conditions, upon exposure to different xenobiotics43. There are evidences that heavy metals like those used in the studied, produced increased LPO levels in M. cephalus44. The concurrent use of several biomarkers is important to minimize misinterpretation in cases of complex situations of pollution45.The result indicates that fish actively generate oxidative stress and antioxidant responses which can be used as biomarkers of pollution.

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Current World Environment

Vol. 8(1), 61-76 (2013)

Cyanophyta Recorded in Erbil, Kurdistan Region of Iraq JANAN JABBAR TOMA¹ and BAHRAM K MAULOOD² ¹College of Science, University of Salahaddin, Hawler, Kurdistan Region of Iraq. ²HawlerBotanical Garden,Hawler, Kurdistan Region of Iraq. DOI : http://dx.doi.org/10.12944/CWE.8.1.07 (Received: March 22, 2013; Accepted: April 10, 2013) ABSTRACT Two hundred fourty four species of blue green algae have been listed and recorded in this investigation. The listed species belong to five main groups of cyanophyta, making up all together fourty six genus. It was found that blue green algae in Erbil represented (54%) of Iraqi blue green algae, and (11% ) of all known algae in Iraq so far.

Key words: Cyanophyta, Erbil,Kurdistan, Iraq. INTRODUCTION The1 may be regard as the first one who did a detail study on algae in Iraq as he studied phytoplankton in Razzah and Al-Habbaniyah. However (2 and 3)did published a periliminary study on algae arround Baghddad, mesopotamia and Kurdistan respectively. Concurrently with estabilshing different universities in different parts of Iraq during seventy last century attention were given to algal studies in parallel with other branches of sciences.Tens of papers and M.Sc thesis were furnishing the local and international journals with various aspects of algal studies.The university of Sulaimaniah team under the leadership of Prof B.K.Maulood and Bassarah university under leadership of prof AlSaadi and Haddi (4, 5 and 6). One of the important outcome of these investigation was the addition of new division of algae to Iraqi & Kurdistan flora, the red algae with more than 6 species have been described in details (7 and 8). Recently 3 sucesssive check list of algae in Iraq have been produced every decad since 1983.The fourth one is underway for publicationby the Maulood et al.

A series of keys for identification of different species of cyanophyta have been attempted by Maulood & Aziz but it have been realized that they are not so precise going to apply since quite many more species are continously been added to the flora of Kurdistan & Iraq throughout continous survies this is in one hand, the survey should extend to all other part of the country.On the other hand because of this such attempt should be terminated and not applied. The present study is dealing with the whole 244 known species of blue green algae within Erbil province and their distribution in variuos habitats such as pond, lake, river, stream, dutches ect—, and appeared in these figures (1, 2, 3, 4 and5) are represnted in different districts within Erbil province. Description of the area The Erbil province (Fig.1) is capital of Kurdistan and situated in the north east of Iraq. It is bounded to the north east and south east by the Greater and Lasser Zab rivers. Boundaries extend from longitudinal 430 15- E to 450 14- E and from latitude35027- N to37024-N(9). The climate of the area is characterized by a wide diurnal and annual range of temperature (9).The climate most closely related to IranoTuranian type. The average annual rainfall may exceed 1000mm.The annual average rainfall for

TOMA & MAULOOD, Curr. World Environ., Vol. 8(1), 61-76 (2013)

Fig. 1: Map of IraqshowErbilProvince

Fig. 2: Map of Erbil show Kalak and Al-Kuwayr districts

Fig. 3: Map of Erbil show Kasnazan, Shaqlawa and Koysinjaq districts

TOMA & MAULOOD, Curr. World Environ., Vol. 8(1), 61-76 (2013)

Fig. 4: Map of Erbil show Khalifan, Soran,Rawanduz and Harir districts

Fig. 5: Map of Erbil show Choman, and Haji Homaran

Erbil city estimated to be 440mm(10).. Details of geology, pedology and limnology of the area may given in11. In the present study the habitat and taxonomy of all species that was published in different journals and different peroids of time where gather together and documented in these papers(12, 13, 14, 15, 16, 17, 18, 19, 20and 21) as seen in theses figures (1, 2, 3, 4 and5), then after may start such study on other of algae such as green, yellow green, red ectâ&#x20AC;Śâ&#x20AC;Ś.. , in Erbil and other different provincve of Kurdistan of Iraq will be dealt with in coming in future.

algae in Arbil, it was found that out of 244 species, that have been recorded in Arbil province(Table.1) almost 52.9% are belonging to Oscillatoriales, whereas 30.4% of the genuses are belonging to chroococales. In contrast Oscillatoriales made up less than 22% of the genus, which was less than Nostocales which was more than of Chaemsiphonales & less than Chroococales as well.

RESULTS AND DISCUSSIONS

Number of species of Oscillatorialesin Arbil was found to be almost double of that of species number of Chroococales and fourfold higher than Nostocales, whereas the number of species of Chaemisphonales was almost ten folds less than that of Oscillatoriales.

Throughuot a review of all published scientific reliable information about blue green

The total number of blue green algae in Arbil province makeup almost ( 54% ) of total blue

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Table 1: Number of genus and species of blue green algae that recorded during this study Orders of Cyanophyta

Number of genus

Percent of genus

Number of species

Percent of species

15 2 5 10 14 46

32.6 4.3 10.9 21.7 30.4

60 4 7 129 44 244

24.6 1.6 2.9 52.9 18.0

Chroococales Chamaesiphonalis Pleurocapsales Oscillatoriales Nostocales

Type of Algae Division : CYANOPHYTA 1-Order: Chroococales 1-Aphanocapsadelicatissma West and West A. elachista West and West A. elachista var. planctonica G.M. Smith A. endophytica G.M. Smith A .montana Cramer 2-Aphanothececastagnei (Breb. ) Rabenhorst

A.nidularis var endophyticaWest & West

A. saxicola Naegeli 3-Chroococcusdispersus Lemmermann C. dispersus var minor G..M.Smith

C. giganteus West and West C. hansgirgi Schmidle

C. limneticus Lemmermann C.limneticus var elegans G.S.Smith

C. limneticus var subsalsus Lemmermann

C. minimus var careneus C. minor (Ktz.) Naegeli

Site

Kasnazan impoundment, Dlopa basin Degala stream Deygella Mountain stream Kasnazan impoundment , Dlopa basin Degala stream, Dermanawa spring Hamammok spring, Kany Gawra spring Dermanawa spring, Jale thermal spring, Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin, Wastewater( at Hawera subdistrict, at Gamsh Tapa village, Greater ZabRiver at Kunder area) Dermanawa spring, Kassnazan impoundment Dilope basin Kasnazan impoundment ,Dlopa basin Wastewater( at Tooraq village, at Arab-Kand village, at Tarijan village), Kassnazan impoundment , Dlopa basin Kasnazan impoundment, Dlopa basin Gali Ali-Bag area Kasnazan impoundment, Shekhi Balakan spring, Sarta spring, Chneran spring, Aqubani saru spring Wastewater(at Tooraq village, at Arab-Kand village) , Kasnazan impoundment , Dlopa basin Basstora stream, wastewater( at Jimakah& Binberz village, at Saadawa village, at Hawera subdistrict,at Gamesh Tapa village) Wastewater(at Tooraq village) Dlopa spring, Jale thermal spring,

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C. minutus (Ktz.) Naegeli

C. tenax (Kirchn.) Hieron C. turgidus (Ktz.) Naegeli

4-Coelosphaeriumdubium Grunow C. kuetzingiana Naegeli 5-Dactylococcopsisfascicularis Lemmermann 6-Eucapsisalpina Clem .and Schantz 7-Gloeocapsaaeruginousa (Garm) Keutzing

G. calcarea Tilden

G. compacta Kuetz

G. dermochroe Naegeli G. fusco-lutea Naegeli G. gelatinosaKuetz G. kuetzingiana Naegeli Hamammok spring, Dermanawa spring G. luteofusca Martens G. pluerocapsoids Novacek G. polydermatica Kutz G. punctate Naegeli G. quaternaria Kuetzing

wastewater(at Tooraq village, at Arab-Kand village, at Tarjan village) , Shekhi Balakan spring, Sarta spring, Chneran spring, Sheraswar spring, Haji Marg, Haji Agha, Haji Ahmad, Kasnazan impoundment, Kasnazan Kahreeze Dlopa spring, Bahrka spring, Hamammok spring, Basstora stream, Jazshnakan stream, Jazshnakan Kahreeze, Degala stream, Sardaw spring, wastewater( at Jimakah & Binberz village, at Saadawa village, at Hawera village, Greater Zab River at Kunar area), Kasnazan impoundment, Dlopa basin,Debaga spring Hamammok spring, Gomaspan darband, wastewater Bahrka spring, Basstora stream, Rubary Koya, Gomaspan darband, Sulauke stream, Geli Muzik stream, Shekhi Balakan spring, Azadi spring, zar gali thermal spring, Sheraswar spring, Kani Piawan, Haji marg, Qalasnji Khwaru, Seta spring, Kasnazan impoundment ,Dlopa basin, wastwater(at Jimkah & Binberz village, at Trjan village, at Saadawa village). Kasnazan impoundment, Dlopa basin Degala stream Kasnazan impoundment,Kasnazan Kahreeze Degala stream Kassnazan impoundment, Dlopa basin, wastewater(at Tarjan village, at Gamsh Tapa village) Gomasheen pond, Kassnazan impoundment, Dlopa basin, wastewater(at Tarjan village, at Saadawa village) Degala stream, wastewater(at Saadawa village, at Hawera subdistrict, at at Gamsh Tapa village, Greater Zab River at Kudar area) Gomasheen pond Gali Ali-Bag area Suse stream Kanya gawra( concret tank), Dlopa spring, Kasnazan Kahreeze, Jale thermal spring Bahrka spring Gali Ali-Bag area Bahrka spring, Dlopa spring, Kassnazan impoundment, Dermanawa spring Dermanawa spring

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G. rupestris Kutz 8-Gloeothecalinearis Naegeli 9-Gomphosphaeriaaponina Kuetzing G. mauloodianumKuetzing 10-Gleocystisgigas Kuetz

11-Merismopediaconvolute de Brebison district, at Gamesh Tapa village) M. elegans A.Braun

M. glauca (Ehr.) Naegeli

M. marsoniA.Braun M. minima Heck

M. punctata Heyen

M. tenussima Lemmermann

M. trolleri Bachmann

12-Microcystisaeruginosa Kuetzing M. elongata Nov M. elabens Breb

M. flos-aquae (Wittr.) Kirchner M. marginate (Menegh) Kuetzing

13-Rhabdodermairregulare Geitler 14-Synechococcusaeruginosus Naegeli S. elongatus Naegeli

Gali Ali-Bag area, Kasnazan impoundment, Dlopa basin Kehres Qoritan Degala stream Degala stream Wastewater( at Tooraq village, at Tarajan village, at Saadawa village, Gamesh Tapa village, at Greater Zab River at Kudar area) Degala stream, wastewater(at Hawera sub Basstora spring, Hamammok spring, wastewater( at Tooraq at village, Gamesh Tapa village) Deygella Mountain stream, Basstora spring, Hamammok spring, Dermanawa spring, Rubary Koya, Gomasheen pond, Jazshnekan stream, Kasnazan impoundment, Degala stream Gomaspan darband Basstora spring, Jazshnekan spring, Degala stream, Dlopa stream, Sheraswar spring, Piawan spring Bistana spring and stream, Deygella mountain stream, Basstora spring, Hamammok spring,Rubary Koya, Jazshnakan stream, Degala stream, Gomaspan stream, Kasnazan impoundment, Kani -Hunjir spring, wastewater(at Hawera sub district, Greater Zab River at Kudar area) Serta springs(Batas), Azadi spring, Zar gali thermal spring, Aqubani saru spring, Piawan spring, Kasnazan impoundment Bistana spring and stream, Gomaspan darband, Geli muzik stream, Degala stream, Sulauke stream Degala stream, wastewater(at Saadawa village, at Hawera sub district) Wastewater(at Saadawa village, at Hawera sub district) Bahrka spring, Dlopa spring, Dermanawa spring, wastewater(at Tooraq village, at Gamesh Tapa village, Greater Zab River at Kudar area) Basstora spring Bahrka spring, Basstora spring, Degala stream, wastewater(at Tooraq village, at Hawera sub district, Gamesh Tapa village) Dibaga spring, Jale thermal spring Jale thermal spring Dibaga spring, Mersaid thermal spring

TOMA & MAULOOD, Curr. World Environ., Vol. 8(1), 61-76 (2013) 15-Synechocystissaline Wisloush Spevalekii Erecegevic 2-Order : Chamaesiphonalis 1-Chamaesiphoncurvatus Nordst C. siderphilus Starmach C. siderphilus var. glabra C.B. Rao 2-Chlorogloeamicrocystoides Geitter 3-Order: Pleurocapsales 1-Hyellacaespitosa Born and Flah 2-Myxosarcinaburmensis Skuja M. amathystina Skuja M. spectabilis Printz 3-Pleurocapsaminor Hansginosa 4-Stichosiphon regularis Skuja 5- Xenococcuskerneri Hansgirg

4-Order: Oscillatoriales 1-Arthrospiramassarti Kuffareth 2-Borziatrilocularis Cohn 3-Lyngbyaaerugineo-coerulea (Ktz.) Gomont

L. allorgi Fermy L . bipunctata Lemmermann spring, Piawan spring,spigra spring, L. birgei G.M. Smith L. chaetomorphe Iynger and Deskachary L. circumerata G.M. Smith L. contorta Lemmermann L.corbierei Fremy L. cryptovaginata Schkorbatow L. digueti Gomont

L. epiphytica Hieron L. gardneri (Setchell and Gardner Geitler) L. gracilis Rabenh spring, Dlopa spring, Degala stream L.hojdenii Gomont L. infixa Fremy

Bahrka spring, Kanya Gawra spring (concret tank) Jale thermal spring, Mersaid thermal spring Lesser Zab River(Altun Kopre) Bekhal spring, Rubary Koya Bekhal spring, Beer a Baraza small spring Gomaspan darband Rubary Koya Rubary Koya Smaqulu bridge Kasnazan Kahreeze Kahreeze Qoritan, Kasnazan Kahreeze, Gomasheen pond, Rebury Koya Degala stream Degala stream, Gomasheen stream, Jazshnakan Kahreeze, Kanya Gawra (concret tank) Graw Haji Omaran thermal spring Degala stream Kanya Gawra, Dlopa spring, Dermanawa spring, Rubary Koya, Kasnazan Kahreeze, Wastewater(at Saadawa village, Greater Zab River at Kudar area) Darbandy Gomaspan Serta spring, Graw Haji Omaran thermal Degala stream, Jazshnakan stream Bekhal spring, Graw Haji Omaran thermal spring, Shekhi Balakanspring, Azadi spring Sisawa spring, Khrwatan spring, Sardaw spring Qush Tepe(silted channel on Arbil-Kirkuk road), Khrwatan spring, Sardaw spring Degala stream Degala stream, Smaqulu spring Lesser Zab River (Altun Kopre), Karhres Qoritan, Dolpa spring, Kassnazan impoundment, Dlopa basin Kassnazan impoundment, Dlopa basin Debaga spring, Beer a Baraza spring, Basstora spring, Degala stream Kany- Hanjir, Piawan spring, Hamammok Degala stream Krhres Qoritan, Shekhi Balakanspring, Graw Haji Omaran thermal spring,Chneran spring, Spigra spring

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L. kashiapii Ghose L. kuetzingii Schmidle

L. lachneri (zimm.)Geitler

L. lagerheimii Gomont

L. laxespirialis Skuja L. limnetica Lemmer

L. lutea

(Ag.) Gomont

L. martensiana Meneghini

L. mesotrica Skuja L. nordgardhiiWille

L. perelegans Lemmermann L. putealis Montagne L. semiplenaWille L. taylorii Drouet and Strickland L. versicolor (Wartmann)Gomont

4- Microcoleusacutissimus Gardner M. paludosus (Ktz.) Gomont

M. vaginatus (Vauch.) Gomont

5-Oscillatoriaacuta Bruhl and Biswas

O. acuminatum Gomont

Gomaspan stream Korre stream, Jazshnakan Kahreeze, Wastewater, Azadi spring, Zar- gali thermal spring, Piawan spring, Qalasnji Khwara spring Qush Tepe(silted channel on Arbil-Kirkuk road), Kanya Gawra(concret tank), Dermanawa spring, Rubary Koya, Basstora stream, Kasnazan Kahreeze, Gomasheen pond Kuna Dlopa spring, Korre stream,Shekhi Balakanspring,Zar gali thermal spring, Aqubani Saru spring, Piawan spring Suse stream Wastewater( at Tarjan village) , Suse stream, Kasnazan impoundment, Kasnazan Kahreeze, Dlopa basin Wastewater(at Saadawa village, Gamesh Tapa village) Jale thermal spring, Suse stream, Wastewater( at Tarjan village, Gamesh Tapa village), Kasnazan impoundment, Dlopa basin Shekhi Balakanspring,Zar gali thermal spring, Sheraswar spring Chneran spring Kany Gawra, Dlopa spring, Hamammok spring, Dermanawa spring, Mersaid thermal spring Darbandy Gomaspan stream Kany Shekh spring Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin, Wastewater(at Tooraq village, at Hawera sub district, Greater Zab River at Kudar area) Darbandy Gomaspan stream Darbandy Gomaspan stream, Gomasheen stream, Shekhi -Balakan spring, Graw Haji Omaran thermal spring, Piawan spring, Qalasnji saru spring, Haji Ahmad spring Basstora stream, Graw Haji Omaran thermal spring, Sheraswar spring, Aqubani saru spring, Spigra spring, Seta spring Basstora stream,Zar gali thermal spring, Qalasnji Khwaru spring, Haji Ahmad spring, Wastewater(at Tooraq village, at Jimakah & Binberz village) Kasnazan impoundment, Sulauke stream, Wastewater( at Arab-Kand village, at Tarjan

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O. acutissima Kufferath O. agardhii Gomont

O. amoena (Ktz.) Gomont

O. amoena var. nongranulata Ghose

O. amphibia Agardh

O. amphigranulata Van Goor O. anguina (Bory) Gomont

O. animelis Agardh O. annaeGomont O. articulata Gardner

O. boryana Bory O. brevis (Ktz.) Gomont O. chalybea Mertens

O. chlorina Kuetz

O. curvicepsAgardh

village, Gamesh Tapa village) Shekhi Balakan spring, Qalasnji Khwaru spring Serta spring, Korre small stream, Bistana stream and spring, Khrwatan spring, Kany Shekh, Smaqulu spring, Kasnazan impoundment, Dlopa basin Kuna Dlopa spring,Rubary Koya, Hamammok spring, Sarta spring, Kany Harir, Sardaw spring, Sorad spring, Shekhi Balakan spring, Zar gali thermal spring,Grawi Haji Omaran thermal spring, Azadi spring, Aquabani Sara spring, Piawan spring, Haji Agha spring, Qalasnji Khwaru spring, Smaqulu spring, Wastewater(at Tooraq village, at Arab-Kand village), Gomasheen pond, Jazshnakan stream, Degala stream, Kasnazan spring, Kasnazan impoundment, Dlopa basin Shekhi Balakan spring, Zar gali thermal spring, Sarta spring, Haji Agha spring,Sheraswar spring Qush Tepe silted channel on Arbil 窶適irkuk road, Pir Dawood pond, Grawi Haji Omaran thermal spring, Sarta spring, Kasnazan impoundment, Dlopa basin Bawyan spring near Batas, Mulla Omer fouled channel on Arbil Massif road Bawyan spring near Batas, Bekhal spring, Grawi Haji Omaran thermal spring, Azadi spring, Aquabani saru spring, Spigra spring Dermanawa spring Grawi Haji Omaran thermal spring, Azadi spring Kahres Qoritan outflow on Arbil Makhmur road, Wastewater(at Saadawa village, Hawera sub district, Greater Zab River at Kudar area) Wastewater( at Tooraq village, at Jimakah &Binberz village, Gamesh Tapa village) Kasnazan impoundment, Dlopa basin Darbandy Gomaspan stream, Degala stream, Wastewater( at Tarjan village, Greater Zab River at Kudar area) Wastewater( at Jimkah & Binberz village, Gamesh Tapa village), Grawi Haji Omaran thermal spring, Azadi spring, Shekhi Balakan spring, Zar gali thermal spring, Qalasnji Khwaru spring, Haji Ahmad spring, Seta spring, Kasnazan Kahreeze Zar gali thermal spring, Azadi spring,

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O. decolorata O. framyii De Joni O. formosa Bory

Sheraswar spring, Seta spring, Pond near suse Kasnazan impoundment, Degala stream, Smaqulu spring Smaqulu spring, Dlopa spring Kuna Dlopa spring, Jale thermal spring, Mersaid thermal spring, Wastewater( Gamesh Tapa village, Greater zab river at Kudar area), Degala stream, Shekhi Balakan spring, Grawi Haji Omaran thermal spring, Azadi spring, Sarta spring, Hanjir spring, Piawan spring, Haji Marg spring, Spigra spring, Haji Ahmad spring , Kasnazan impoundment, Dlopa basin

O. granulata Gardner

O. irrigua Kuetzing

O. jasorvensis Vouk O. laete-virens (Crouan ) Gomont

O. limnetica Lemmermann

O. limosa Roth Agardh

O. martini Fremy O. minima Gicklhorn O. mougeottiGomont

O. nigra Vaucher

Kasnazan impoundment, Dlopa basin, Wastewater( at Arab-Kand village, at Hawera sub district) Degala stream, Grawi Haji Omaran thermal spring, Azadi spring, Spigra spring,Sartka spring Smaqulu spring Wastewater( at Tooraq village, at Jimkah & Binberz village, at Tarjan village, Greater Zab River at Kudar area) , Grawi Haji Omaran thermal spring, Azadi spring,Chneran spring, Aquabani saru spring, Spigra spring, Dlopa spring Mama-Jalka spring, Sarta spring, Kany Hanjir spring, Sisawa spring, Bawyan spring, Khrwatan spring, Harir spring, Sardaw spring, Jale thermal spring, Mersaid thermal spring, Grawi Haji Omaran thermal spring, Haji Marg spring, Qalasnji saru spring, Seta spring Kasnazan Kahreeze, Darbandy Gomaspan stream, Mama Jalka spring, Sarta spring, Sisawa spring, Grawi Haji Omaran thermal spring, Azadi spring, Sheraswar spring, Piawan spring, Degala stream, Kasnazan impoundment, Dlopa basin Wastewater( at Tarjan village, at Saadawa village) Kasnazan impoundment, Dlopa basin, Kasnazan Kahreeze Kasnazan impoundment, Dlopa basin, Degala stream, Tweska stream, Pond near suse, Sulauke stream Gomasheen stream, Hamammok spring, Bahrka spring, Sarta spring, Sisawa spring, Kany Shekh spring, Sorad spring, Wastewater(

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O. obscura Bruhl

O. okeni Agardh

O. perornata Skuja O. princeps Vaucher O. prolifica (Grev.) Gomont O. proteus Skuja

O. pseudogeminata G.Schmidle

O. pseudogeminata var. unigranulata

O. raoi Detoni

O. rubescens de Candolle

O. sancta (Ktz.) Gomont O. simplicissima Gomont O. splendida Greville

Biswas

at Tooraq village, at Saadawa village, Greater Zab River at Kudar area), Grawi Haji Omaran thermal spring, Tweska stream, Kasnazan impoundment, Dlopa basin, Kasnazan Kahreeze Wastewater( at Tarjan village, Saadawa village), Grawi Haji Omaran thermal spring, Shekhi Balakan spring, Degala stream Shekhi Balakan spring, Azadi spring, Zar gali thermal spring, Sarta spring, Hanjir spring, Chneran spring, Aquabani saru spring, Piawan spring, Spigra spring Mama Jalka spring, Khrwatan spring, Sardaw spring, Degala stream Hamammok spring, Rubary Koya, Jale thermal spring, Degala stream, Bistana spring Kasnazan impoundment, Dlopa basin Mulla Omer fouled channel on Arbil Massif road, Pir Dawood pond on Arbil-Makhmur road, Wastewater( at Arab-Kand village, at Hawera village, Gamesh Tapa village), Grawi Haji Omaran thermal spring, Sheraswar spring, Dlopa spring Debaga spring, Dlopa spring, Hamammok spring, wastewater( at Tarjan village, at Hawera sub district) Dibaga spring, Korre stream, Pir Dawood pond on Arbil-Makhmur road, Jale thermal spring, Mersaid thermal spring Dlopa spring, Basstora stream, Darbandy Gomaspan stream, wastewater( at Tooraq village, at Tarjan village, at Saadawa village), Zar gali thermal spring, Chneran spring, Piawan spring Gomasheen pond, Mama Jalka spring, Sarta spring, Hanjir spring, Kany Shekha, Wastewater( at Hawera sub disrict), Shekhi Balakan, Grawi Haji Omaran thermal spring, Azadi spring, Sarta spring, Aquabni saru spring, Piawan spring, Haji Marg spring, Qalasnji saru spring, Qalasnji Khwaru spring, Haji Ahmad spring Shewa- sur stream on Koya-Kirkuk road, Degala stream Kasnazan Kahreeze, Degala stream, Smaqulu spring, Qelasinc spring, Suse stream Jazshnakan stream, Grawi Haji Omaran thermal spring, Hanjir spring, Qalasnji saru spring, Sheraswar spring, Degala stream, Kasnazan Kahreeze

TOMA & MAULOOD, Curr. World Environ., Vol. 8(1), 61-76 (2013)

O. subbrevis Schmidle

O. subliformis Kuetz

O. subtilissima O. tenuis Agardh

O. tenuis var. tergestina Rabenhorst

O. terebriformis Agardh

O. willei Gardner

O. vizagapatensis

6-Phormidiumambiguum Gomontspring

Bawyan spring near Batas, Degala stream, Gomaspan stream, Darbandy Gomaspan stream, Sarta spring, Sisawa spring, Bawyan spring, Sardaw spring, Wastewater( at Tooraq village, Hawera sub district), Grawi Haji Omaran thermal spring, Hanjir spring, Haji Marg spring, sartka spring, Haji Ahmad, Kasnazan impoundment, Dlopa basin Wastewater( at Jimkah & Binberz village, Gamesh village, Greater Zab River at Kudar area), Grawi Haji Omaran thermal spring,Azadi spring, Sheraswar spring, Chneran spring, Smaqulu spring Dlopa spring Shewa sur stream on Koya-Kirkuk road, Qush Tepe silted channel on Arbil -Kirkuk road, Dermanawa spring, Gomasheen pond and stream, Gomaspan stream, Darbandy Gomaspan stream, Wastewater( at Tarjan village, at Saadawa village, at Hawera sub district), Grawi Haji Omaran thermal spring, Zar gali thermal spring, Sarta spring, Aquabani spring, Piawan spring, Haji Marg spring, Sartka spring, Degala stream, Samqulu spring, Kasnazan impoundment, Dlopa spring Jazshnakan stream, Wastewater(at Tarjan village, at Saadawa village, at Hawera sub district) , Kasnazan impoundment, Dlopa spring Bawyan spring near Batas, Mulla Omer fouled channel on Arbil Massif road, Qush Tepe silted channel on Arbil -Kirkuk road, Hamammok spring, Dernamawa spring, Gomasheen pond and stream, Degala stream, Jale thermal spring, Mersaid thermal spring, Grawi Haji Omaran thermal spring, Zar gali thermal spring, Azadi spring, Sheraswar spring, Chneran spring, Aquabani saru spring, Piawan spring, Spigra spring, Dlopa spring, Sulauke stream, Suse stream Hamammok spring, Wastewater( at Tarjan village, Hawera sub district), Shekh Balakan spring, Grawi Haji Omaran thermal spring, Zar gali thermal spring, Azadi spring Shekh Balakan spring, Grawi Haji Omaran thermal spring, Zar gali thermal spring, Azadi spring, Sarta spring, Chneran spring, Piawan spring, Haji Agha spring,Qalasnji Saru spring Hamammok spring, Rubary Koya,

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P. anomala C.B. Roa P. autumnale (Ag.) Gomont

P. calcicola Gardner P. corium Gomont

P. dimorphus Lemm P. favosum(Bory) Gomont

P. formosum Gomont P. foveolarum Gomont P. fragile Gomont

P. inundatum Ktz P. jadinianum Gomont P. laminosum (Gom..) ex. Gomont P. luciduis Ktz P. molle Gomont P. mucicola Huber-pest and Naumann P. mucosum Gardner P. pachydermaticum Fermy spring,Degala stream P. papyraceum (Ag.)Gom P. purpurascens Kuetz P. retzii(Ag.)Gom

Jazshnakan Kahreeze, Gomaspan stream, Darbandy Gomaspan stream, Smaqulu spring, Kasnazan impoundment, Dlopa Degala stream Hamammok spring, Gomasheen stream, Sartka spring, Hanjir spring, Bawyar spring, Khrwatan spring, Kany Shekh, Sardaw spring, Sorad spring, Shekhi Balakan, Azadi spring, Sarta spring Shekhi Balakan, Grawi Haji Omaran thermal spring, Zar gali thermal spring Wastewater( at Hawera sub district, Gamesh Tapa village), Kasnazan Kahreeze, Degala stream Grawi Haji Omaran thermal spring, Azadi spring, Sheraswar spring, Chneran spring Wastewater( at Greater Zab River at Kudar area), Grawi Haji Omaran thermal Spring, Azadi Spring, Rubary Koya, Gomasheen pond, Gomasheen stream, Gomaspan stream, Kasnazan Kahreeze, Kasnazan impoundment Wastewater( at Jimkah &Binberz village, at Tarjan village) Kahres Qoritan outflow on Arbil-Makhmur road Shewa sur(large sandy stream on Koya Kirkuk road), , Grawi Haji Omaran thermal Spring, Hanjir spring, Haji-Agha spring, Haji Ahmad Kasnazan impoundment, Dlopa spring Degala stream, Kasnazan impoundment Bahrka spring Wastewater( at Hawera sub district , Greater Zab River at Kudar area) Kuna Dlopa spring, Degala stream, Gomasheen pond, Gomasheen stream Dibaga spring Dermanawa spring,Kasnazan impoundment, Kasnzan Kahreeze Sarta spring, Hanjir spring, Bawyan spring, Harir spring, Kany Shekh, Sardaw Degala stream Grawi Haji Omaran thermal Spring, Azadi spring Shekhi Balakan, Grawi Haji Omaran thermal Spring, Azadi spring, Zar Gali thermal spring, Sarta spring, Haji Marg spring,Spigra spring, Qalasnji Khwaru spring, Sartka spring,

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P. subfuscum Ktz P. subincrustatum Fritsch P. submembranaceum Gomont P. tenue (Menegh) Gom

P. uncinatum Gom P. valderianum Fritsch 7-Romeriagracilis Koezwara 8-Schizothrixferiesii Gom S. lacustris A.Braun Dermanawa spring, S. lardacea (Cesati)Gom S. rivularia(Wolle) Drouet S. tenctoria Gom S. vaginata (Naeg.)Gom 9-Spirulinalabyrinthiformis Gom S. laxissima G.S. West S. laxissima var. major G.S. West S. major Ktz

S. meneghiniana Zanard S. princeps West and west

S. subsalsa Oersted S. subtilissima Ktz

Dlopa spring 5- Order : Nostocales 1-Albrightiatortnosa Copeland 2-Anabaenaaequalis Borge A. circinalis Rabenhorst A. constricta (Szafer) Geitler

A.enlenkini Borge A. felisi Bornet A. sphaerica Barnet at Elahault

Hamammok spring, Degala stream, wastewater( at Saadawa village, at Hawera sub district) Kasnazan impoundment, Dlopa basin Gomasheen stream Grawi Haji Omaran thermal spring, Azadi spring Jale thermal spring, Mersaid thermal spring, Grawi Haji Omaran thermal Spring, Sarta spring, Hanjir spring, Sulauke stream Gomaspan stream, Hamammok spring Suse stream, Jale thermal spring, Mersaid thermal spring Qush Tepe silted channel on Arbil -Kirkuk road Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin, Darbandy Gomaspand stream Dermanawa spring Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin Suse stream Degala stream Dlopa spring, Bawyan spring, Grawi Haji Omaran thermal Spring, Sarta spring Dlopa spring Dlopa spring, Rubary Koya, Jazshnakan Kahreeze, Gomasheen pond, Degala stream, Kasnazan impoundment, Wastewater(Hawera sub district, Gamesh Tapa village, Greater Zab River at Kudar area) Dlopa spring Gomaspan stream, Grawi Haji Omaran thermal spring, Degala stream, Kasnazan impoundment, Dlopa basin Grawi Haji Omaran thermal spring Qush Tepe silted channel on Arbil -Kirkuk road, Pir Dawood pond on Arbil -Mukhmur road, Jale thermal spring, Mersaid thermal spring, Grawi Haji Omaran thermal spring, 10-Raphidiopsissubtilissima Dlopa spring Sawerdy stream Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Wastewater( Hawera sub district, Greater Zab River at Kudar area) Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin Suse stream

TOMA & MAULOOD, Curr. World Environ., Vol. 8(1), 61-76 (2013) A. spiroides Klebahn 3-Calothrixbraunii Born and Flahault C. breviarticulata West and west C. brevissima West and West C. castlelii Massal C. elenkinii Kuetz C. epiphytica G.S.West C. flusca Kuetz C. fusca (Ktz.) Bornet and Flahault

C. marchica Lemmermann C. parietina Thuret C. stellaris Bornet and Flahault C. viguieri Lemmermann 4-Cylindrosperummajus Kuetzing C. minimum G.S.West C. muscicolaKtz C. stagnale (Ktz.) Bornet and Flahault 5-Homoeothrixjanthina (Born and Flah.)Starmach H. juliana (Born and Flah.) Kirchner

6-Michrochaetecalothrichoides Hansg M. diplosiphon Gomont M. tenera Thurt 7-Nodulariaspumigena Martens in Jergens 8-Nostoccommune Vaucher N. paludosum Ktz N. sphaericum Vaucher N. spongiaeformeKtz N. verrucosum Vaucher 9-Plectonemanotatum Schmidle 10-Pseudoanabaena Schmidle Taago 11-Rivulariahaematites (D.C.) C.A. Agardh 12-Scytonemaarchangella Born S. myochrous Schmidle 13-Stigonemaminutum Agardh 14-Tolypothrixboutille (Breb. Et. Desm.) Forti T. distorta var. penicillata (Ag.)Lemmer T. nodosa Bharadus

Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin Serta spring, Kahreeze Qoritan outflow on Arbil-Mukhmur road Degala stream Darbandy Gomaspan stream, Dlopa spring, Kasnazan impoundment Degala stream Dlopa spring, Jazshnakan Kahreeze, Gomasheen pond, Gomasheen stream Samqulu spring Kasnazan Kahreeze, Bahrka spring, Dlopa spring, Hamammok spring, Basstora stream, Jazshnakan stream, Darbandy Gomaspan stream, Kasnazan impoundment Bahrka spring, Dlopa spring, Rubary Koya Kasnazan Kahreeze, Bahrka spring, Basstora stream Gomasheen Pond, Gomasheen stream Smaqulu spring Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin Kasnazan impoundment Kasnazan impoundment, Dlopa basin Dlopa spring, Rubary Koya Rubary Koya, Dlopa spring, Gomasheen Pond, Gomasheen stream, Gomaspan stream, Kasnazan impoundment Smaqulu spring Smaqulu spring Smaqulu spring Degala stream Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Dlopa basin Smaqulu spring Sawerdy stream, Smaqulu spring Smaqulu spring, Bekhal spring Kasnazan impoundment, Dlopa basin Kasnazan impoundment, Kasnazan Kahreeze Degala stream Pond near suse, Smaqulu spring, Gomaspan darband stream, Kasnazan impoundment, Dlopa basin Degala stream Gali Ali-Bag area Bekhal spring Degala stream

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green algae in Iraq, whereas the total blue green algae make up ( 11% ) of all algae of Iraq. Therefore we may say that Arbil province

represent ( 11%) of blue green algae in Iraq that are distributed throughout different lakes, rivers,stream, pond ect, and throughout the altitude in Kurdistan.

REFERENCES 1.

10.

11.

12.

Al-Kaisi, K.A., Study on algae of water system in Iraq.Ph.D.Thesis.Univ of North Wales Pangor.U.K .(1964). Abdin,G.; Al-Kaisi,K., and Naib,F., Some observation on algal flora in and around Baghdad. Bull.Coll.Arts & Sciences, Baghdad. 2: 21-43 (1957). Kolb, R.W and Krieger,W., Susswassaerlagen and Mesoptnmen & Kurdistan, Ber.Dutsch.Bot.Gse. 60: 336-355 (1942). Hinton, G.F.C and Maulood, B.K. Checklist of the algae from inland water in Iraq.J of University of Kuwait.10: 191-256 (1983). Maulood,B.K ; Hadi, R.A.M ; Saadalla, H.A.A; Kassim,T.I and Al-Lami-A.A, Checklist of algae in Iraq.Marine Mesopotamica suppl. (1): 1-128 (1993). Maulood, B.K and Toma, J.J., Checklist of algae in Iraq.Scientific Journal of Babylon Univ. 9(3):1-62 (2004). Hinton ,G.C.F. and Maulood ,B.K., Fresh water red algae anew addition to the Iraqi flora .Nova Hedwigia 32:487-497 (1980 b). Maulood ,B.K. ; Hinton ,G.C.F., Further observations on the distribution of red algaein Iraq ,with spacial reference to their ecology .Zanco (Sci.J.Univ. Sulaimaniya Iraq ) ,Series A. 6(3):1-14 (1980 a). Shalash, A .H .A., The Climate of Iraq. Baghdad .Univ. Co. Op. Printing press work soc. Amman, Jordan, P.85 (1966). Zohary, M. The flora of Iraq and its phytogeographical subdivisions. Dept. Agr. Iraq.Publ. 31: 1-201 (1950). Razoska, J. Euphrates and Tigris, mesopotamion ecology and destiny, Vol: 38. Monogr. Biol .W. Junk. The Hague-Boston, London. 122pp (1980). Maulood , B.K. ; Hinton G.C.F. and Al-Dosky, H.S., A study on the blue â&#x20AC;&#x201C;green algalflora of Erbil province ,Iraq . Zanco (Sci.J. Univ. of Sulaimaniya ,Iraq) ,Series A, 6(2): 67-90

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(1980). Al-Barzingy, Y.O.M., Phycological study within Arbil Province ,M.Sci. Thesis ,Univ. of Salahaddin â&#x20AC;&#x201C;Arbil .(1995). Maulood ,B.K. and Raoof ,I.Y., Further observation on distribution of blue - green algae in Arbil , Kurdistan of Iraq. J. D. University,aceepted for publication (2002). Aziz,A.H., A phycolimnological study on springs within Arbil province. M.Sc.Thesis. University of Salahaddin,College of Education. Arbil.Iraq (2004). Bapeer,U.H.K., Ecological study on the distribution of algae in different aquatic habitats within Erbil province. Ph.D.Thesis. University of Salahaddin.College of Sciences. Erbil. Iraq (2004). Toma, J. J., Weekly and spatial variation of physico-chemicals variables and algal composition in Kasnazan impoundment, Erbil. Iraq. Accepted for publication in Journal of Babylon University. 10(3) (2004). Goran,S.M.A., Limnology and non-Diatom phytoplankton composition of Dilope spring and Kesenzan impoundment, Hewler.Kurdistan region of Iraq.M.Sc.Thesis. University of Salahaddin.College of Sciences. Hewler. Iraq .(2006). Al-Sofi,B.A., An ecological study on the main sewage channel of Erbil city, with particular reference to self purification. M.Sc.Thesis. University of Salahaddin.College of ScienceEducation.Hawler. Iraq (2008). Abdul-Wahid, S.J., Aphycological study on some springs eithin Harir sub-district. Hawler-Kurdistan region of Iraq.M.Sc Thesis.University of Salahaddin.College of Science-Education.Erbil.Iraq (2008). Al-Barzing,Y.O.M; Goran,S.M, and Toma, J.J An ecological study on water to some thermal springs in Koya-Erbil province.Iraq.Accepted for publication in Journal of Education and Sciences (2009).

Current World Environment

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Chlorpyrifos Toxicity in Fish: A Review NOBONITA DEB and SUCHISMITA DAS* Department of Life Science and Bioinformatics, Assam University, Silchar - 788 011, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.17 (Received: January 24, 2013; Accepted: February 14, 2013) ABSTRACT Chlorpyrifos (CPF) is a broad spectrum organophosphate insecticide (OP) which is commercially used for more than a decade to control insect pest. It is the second largest selling OP and found to be more toxic to fish than organochlorine compounds. CPF passes via air drift or surface runoff into natural waters, where it is accumulated in different organisms living in water, especially in fish, thus making it vulnerable to several prominent effects. CPF is known to inhibit acetylcholinesterase, cause behavioural, neurological, oxidative, histopathological, endocrine and other effects at low doses. The present study reviews the various effects of CPF in fish.

Key words: CPF, OP, fish, toxic.

INTRODUCTION Chlorpyrifos (O,O-diethyl-O-3,5,6-trichlor2-pyridyl phosphorothioate; CPF) is a broad spectrum organophosphate insecticide (OP) that is commercially used to control foliar insects that affect agricultural crops1 and subterranean termites2 CPF, since it was first introduced into the marketplace in 1965, has been used globally as an insecticide to control pests agriculturally and in the home. It is the second largest selling OP and found to be more toxic to fish than organochlorine compounds3. Earlier reports revealed that fish kill incidents in association with chlorpyrifos in water reaching several hundred parts per billion4. CPF has an average soil half-life of 30 days and two months in less alkaline soils. It also can persist indoors for weeks to months5. CPF passes via air drift or surface runoff into surrounding waters and gets accumulated in different aquatic organisms, particularly fish, adversely affecting them6. This OP insecticide is known to inhibit acetylcholinesterase, which plays an important role in neurotransmission at cholinergic synapses by rapid hydrolysis of neurotransmitter acetylcholine to choline and acetate7. The inhibitory effects of CPF insecticide is dependent on its binding capacity to the enzyme active site and by its rate of phosphorylation in

relation to the behaviour and age8,9 and is widely used for rapid detection to predict early warning of pesticide toxicity10. It is reported to be activated by contact, ingestion and vapour action, causing convulsions and paralysis. CPF can enter the body either by inhalation of air containing CPF, ingestion of contaminated food or by dermal contact with CPF. It can cause acute poisoning and well known symptoms include myosis, increased urination, diarrhoea, diaphoresis, lacrimation and salivation11. It is also reported to be involved in multiple mechanisms like causing hepatic dysfunction12, genotoxicity13, neurobehavioral and neurochemical changes14. CPF intoxication is shown to cause a significant decrease in the reduced glutathione (GSH), catalase (CAT) and glutathione Stransferase (GST) activities15. Although the United States Environmental Protection Agency (USEPA) has terminated indoor residential use since 2000, CPF is still one of the most widely used insecticides, and more than 8 million pounds of CPF are used each year for agricultural purposes in the United States16,17. CPF is also widely used in agriculture as the substitutes for methamidophos and parathion in China, and has become one of the major pesticides detected in farm products18,19. Since agricultural uses on orchards and row crops persist, CPF has been frequently detected in air, food and

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water. Although various standards exist to minimize its exposure in food and water, CPF is frequently used and bio-accumulates in certain scenarios6,20. Fish are probably the most important non-target victims of pesticide over exposure as they have an important role in food chain. The present study thus, aims at reviewing existing literatures on the probable adverse effects of pesticide chlorpyrifos in fish.

Scheme 1: Structure of chlorpyrifos

Common name CPF is also known by its trade names Dursban and Lorsban Acute toxicity 96 h LC50 values for technical grade CPF in Bluegill sun fish, Lepomis macrochirus, is 3.3 ppb, in rainbow trout, Oncorhynchus mykiss is 3ppb and for channel catfish, Ictalurus punctatus is13.4 ppb. 96 h LC 50 values for 97.0% CPF (active ingredient, a.i.) in lake trout, Salvelinus namaycush at pH 6.0 is 140ppb, at pH 7.5 is 98 ppb and at pH 9.0 is 205 ppb while for cutthroat trout, Salmo clarki, at pH 7.5 96 h LC50 is 18.4 while at pH 9.9 it is 5.4 ppb. 96 h LC50 values for 99.9% CPF (a.i.) in fathead minnow, Pimephales promelas is 203ppb, while 96 h LC50 values for 99.0% CPF (a.i) in golden shiner, Notemigonus crysoleucas is 35ppb21. The 96 h LC50 values of CPF in juvenile and adult of Oreochromis niloticus were determined to be 98.67 µgL”1 and 154.01 µgL”1, respectively, which reveals that CPF can be rated as highly toxic to fish22. The 96 h LC50 value of CPF to Poecila reticulata was found to be 0.176 ppm/L23. LC50 for 96 h in mosquito fish, Gambusia affinis was found to be 297mg/ L 24 and LC50 value of chlorpyrifos in common carp was found to be 580 µg/L25. In addition, during toxic stress of CPF, several behavioural anomalies like gulping, increased opercular movement, erractic swimming and subsequent lethargy can be observed23.

Developmental effects A variety of studies have shown that exposure to CPF during development can cause persisting neurobehavioural dysfunction, even with low doses that do not elicit acute toxicity. CPF exposure during early development in zebrafish caused long lasting neurobehavioral deficits. Effects of CPF on zebrafish hatchling’s swimming behaviour were studied26. Results show that a persistent behavioural impairment was caused that lasts into adulthood. This early behavioural effect can be used to help determine which critical molecular mechanisms of CPF underlie the behavioural impairment26. Zebrafish, with their clear chorion and extensive developmental information base, provide an excellent model for assessment of molecular processes of toxicant-impacted neurodevelopment26. Recently, it was found that embryonic exposure of zebrafish to CPF causes significant impairment in discrimination learning and swimming speed27 The results of the study indicate that the administration of sub-chronic dose of 1 µM CPF to zebrafish larvae from 0 to 7 day post fertilization significantly impacted body morphology 28. The results also show that even extremely low sub-chronic doses of CPF administered induced specific behavioural defects or morphological deformities. Neurotoxic effects CPF can produce neurotoxic effects. Several studies have assessed the cognitive alterations after acute or chronic exposure to CPF in mammalian models 29,30 but in fish the data available are sparse. CPF causes persistent neurobehavioral impairment in zebrafish, where tests of sensorimotor response (tap startle response and habituation), stress response (novel tank diving test) and learning (3-chamber tank spatial discrimination) were conducted with adult zebra fish after early developmental CPF exposure. The study demonstrated that CPF caused selective longterm neurobehavioral alterations in zebrafish31. In another study, a significant decrease in whole brain activity of zebrafish after exposure to CPF has been found32. AChE activity Currently, reports on the toxicity of CPF on AChE activity in aquatic species focused on acute

DEB & DAS, Curr. World Environ., Vol. 8(1), 77-84 (2013) toxicity, but there are few reports on subchronic toxicity of this pesticides on AChE activity in aquatic species. CPF is well known as an AChE inhibitor33. Symptoms of high level exposure to OPs include muscle twitching, hyperactivity, paralysis, loss of equilibrium and eventually death34 whereas low level exposures have been implicated in various behavioural and physiological impairments 34. Acetylcholinesterase (AChE) and carboxylesterase (CbE) have been used as a specific biomarker for pesticides24,35. AChE in fish is mainly cholinergic and its activity is essential for normal behaviour and muscular function36. The acute systemic toxicity of CPF is caused by inhibition of cholinesterase through the active metabolite chlorpyrifos oxon, chlorpyrifos is more toxic in immature animals despite their ability to recover rapidly from cholinesterase inhibition. Chlorpyrifos itself, rather than chlorpyrifos oxon is stated, directly targets events that are specific to the developing brain and that are not necessarily related to inhibition of cholinesterase. Acetylcholinesterase is critical to the normal development of the zebrafish nervous system 37 , therefore zebrafish studies of the neurobehavioral teratology of acetylcholinesterase inhibitors like CPF are particularly relevant. CPF was a potent inhibitor of AChE activity in fingerling channel catfish38. In a study with Gambusia affinis exposed to lethal concentration of CPF for 96 h, an inhibition of AChE activity was observed24. The inhibition of AChE leading to the accumulation of ACh at synaptic junctions might have been altered the locomotor behaviour of exposed fish. A positive correlation was found between the recovery pattern of AChE activity and locomotor behaviour. The current findings clearly illustrated that the locomotor behaviour of test organism as a promising tool in ecotoxicology, to assess the recovery status of test organism after adverse affects. In a study in Poecila reticulate, brain AChE showed dose-dependent inhibition in fish. Exposure to the higher concentrations of CPF showed upto 66% inhibition of AChE23. Likewise, CbE is widely distributed in living organisms and its physiological role is still unclear, but it might be related to lipid metabolism and steroidogenesis 39 . Some environmental pollutants found to inhibit AChE activity may also inhibit CbE activity40-42 demonstrated that muscle

ChE of mosquito fish was more sensitive than brain to chlorpyrifos exposure. In a study on carp, CbE activity exhibited a doseâ&#x20AC;&#x201C;response relationship, with activity decreasing with increasing CPF. Effects of CPF on carp suggest toxic action of low dose CPF on fish recovered after a period of time and toxic action of high dose CPF on fish which was not easily recovered, but the relevant mechanism need further study43. Behavioural toxicity Behaviour is also considered a promising tool in ecotoxicology behaviour44 is an integrated result of endogenous and exogenous processes and low level of exposures have been implicated in various behavioural and physiological impairments34. In a study in zebrafish, persisting behavioral dysfunction after developmental CPF exposure was observed31,26. Swimming behaviour of fish is frequently observed as a response in toxicity investigations because altered locomotor activity can indicate effects to the nervous system. In a study, the exposure of Poecila reticulata to CPF resulted in the exhibition of aggressive behaviour, rapid gulping of water, increased opercular movement and abnormal and erractic swimming movements. Fish was stressed progressively with time before death. They were lethargic and at the time of death exhibited transient hyperactivity before collapsing23. Oxidative stress For the last decade pesticide induced oxidative stress has also become a very popular of toxicological research as a possible mechanism of toxicity45,46. An antioxidant defense system (ADS) is needed to protect biomolecules from the harmful effects of reactive oxygen species (ROS). Fish are endowed with defensive mechanisms to neutralize the impact of reactive oxygen species (ROS) resulting from the metabolism of various chemicals. These include various antioxidant defense enzymes such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPOx), glutathione S-transferase (GST), and glutathione reductase (GR). Low molecular weight antioxidants such as glutathione (GSH), ascorbate (vitamin C), and vitamin A are also reported to contribute in the quenching of oxyradicals 47. ROS which is not neutralized by this antioxidant defense system

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damages all biomolecules. One of the most important targets of ROS is the membrane lipids which undergo peroxidation (LPO). Thus, LPO estimation has also been successfully employed to signify oxidative stress induced in aquatic animals by such chemicals 48,49. Pesticides may cause generation of reactive oxygen species (ROS), which may lead to oxidative stress, indicating the role of ROS in pesticide toxicity 50. Pesticide induced oxidative stress has been also a focus of toxicological research for the last decade as a possible mechanism of toxicity51,45. The antioxidants in fish could be used as biomarkers of exposure to aquatic pollutants52. Lipid peroxidation (LPO) is one of the molecular mechanisms involved in pesticide toxicity53. In Gambusia affinis exposed to lethal concentration of CPF for 96 h, an elevated lipid peroxidation level was observed24. The same study found decreased levels of antioxidant enzyme (SOD, CAT and GR) activities in the exposed fish can also be effectively used for better assessment of chlorpyrifos toxicity in biomonitoring of aquatic environment. The treatment of Oreochromis niloticus with chlorpyrifos results in an increase in GST activity22. Inductive effects on GST activity have been observed in studies with Salmo trutta after propiconazole exposure 54 . GST-mediated conjugation may be an important mechanism for detoxifying peroxidized lipid breakdown products which have a number of adverse biological effects when it presents in higher amounts55. Induced GST activity indicates the role of this enzyme in protection against the toxicity of xenobiotic-induced lipid peroxidation. Elevated GST activity may reflect the possibility of better protection against pesticide toxicity. In guppy, Poecila reticulate exposed for 96 h to different sublethal concentrations of CPF,estimated the oxidative stress-induction potential in brain, liver and gill tissues. MDA content is induced in all tissues but maximum rise was observed in gills (153% for CPF). In the same study, with regard to antioxidant defense system (ADS), GSH level showed increase in brain and gills CPF treated (23% and 21% respectively). CAT, GST, GR and SOD levels fluctuated in all treatment groups relative to the control. Collective findings demonstrated that pesticide exposure of fish induced an increase in MDA and fluctuated ADS along with inhibited AChE activity.

Endocrine function Chlorpyrifos can interfere with steroid hormone production. CPF is suspected as triggers for harmful effects on the reproductive system in fish. In Tilapia, Oreochromis niloticus, CPF exposure decreased serum estrogen and testosterone levels. Estradiol level after 15 days of exposure decreased by 60.45%, 48.65%, 56.93% after 5, 10, 15 ppb chlorpyrifos treatments22. Cortisol, a corticosteroid hormone, is considered to be an important physiological effector of homeostasis in all vertebrates, through its effects on metabolism and immune function56. Cortisol level in Oreochromis niloticus was found to be lower than that of control level after 10 ppb (59.97%) and 15 ppb (39.41) chlorpyrifos treatments22. Genotoxicity and Mutagenic effect The genotoxic properties of CPF have been studied in a variety of assays in the past, but the results were contradictory57,58. Since there is growing a concern over the presence of genotoxins in the aquatic environment, the development of sensitive biomarkers for detection of genotoxic effects in aquatic organisms has gained importance59. It has been reported to be genotoxic in Channa punctatus60. The exposure to 0.08 lg/l of CPF caused reproductive impairment in Daphnia magna61. In a study on Channa punctatus, it was observed that CPF produced a concentrationdependent increase in DNA single-strand breaks in the form of comet induction and a time-dependent decrease in the damage, due to the DNA repair62. The decrease in DNA damage has been observed in the tissues of fishes exposed to different concentrations of CPF, although the decrease was non-linear, which may indicate repair of damaged DNA, loss of heavily damaged cells, or both63. This inverse relationship between time of exposure and DNA damage may be due to toxicity of contaminants that could disturb the enzymatic processes in the formation of DNA damage 64. Another possible explanation could be the gene activation of metabolizing enzymes such as cytochrome P450 in various tissues that provides a defensive mechanism against the persistent organic pollutants65. Histopathological changes Morphological alterations in fish livers and

DEB & DAS, Curr. World Environ., Vol. 8(1), 77-84 (2013) gills are useful biomarkers to indicate prior exposure to environmental stressors or toxicants. Although the liver is the main organ of detoxification, due to their lipophilicity, CPF have a high rate of gill absorption; this could be a contributing factor in the sensitivity of the fish to this pesticide exposure62. The aberrant hepatocytes could disturb the normal metabolism of the organisms, thereby inducing diseases or even death. Gills, on the other hand, are extremely important in respiration, osmoregulation, acid–base balance and excretion of nitrogenous wastes in fish, and they are the first area of contact of the animal with the external environment. Therefore, gill morphology is considered a useful indicator in environmental monitoring. In a study on common carp, CPF altered the structure of the gills and liver. The liver tissue of common carp revealed different degree of hydropic degeneration, vacuolisation, pyknotic nuclei, and fatty infiltration while the gills of common carp displayed varied degrees of epithelial hypertrophy, telangiectasis, oedema with epithelial separation

from basement membranes, general necrosis, and epithelial desquamation66. CONCLUSION The present paper reviews the works on effects of CPF in fish. All the workers were of the opinion that widespread use of this pesticide for agricultural as well as domestic purposes can adversely affect the non-target organisms like fish. Investigations on the effects of pesticide on fish have diagnostic significance as the results obtained can be used to predict probable mechanisms of toxicity in human. Besides, fish have proven to be useful experimental models for the evaluation of the health of aquatic ecosystems exposed to environmental pollution and the associated biochemical changes. It was found that the primary toxicity associated with acute exposure to CPF pesticides is acetylcholinesterase inhibition in cholinergic synapses and at neuromuscular junctions. Besides, oxidative stress, disruption of endocrine system, behavioural, neuro and developmental toxicity are some of the probable manifestations of CPF toxicity in fish.

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Current World Environment

Vol. 8(1), 85-91 (2013)

Microbial Contamination of Community Pond Water in Dibrugarh District of Assam PURNIMA GOGOI and DHRUBA SHARMA Department of Botany, Rajiv Gandhi University, Itanagar, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.09 (Received: February 14, 2013; Accepted: March 02, 2013) ABSTRACT Our drinking water today, far from being pure, contains bacteria, viruses, inorganic minerals and a chemical cocktail that is unsuitable for human consumption. A study was undertaken with the objectives of evaluating the viable coliforms along with other water born bacteria in pond water environment. Water samples were collected from three community ponds of Dibrugarh district which are used mostly for bathing, watering livestock as well as drinking under water crises condition. Bacteria from collected pond samples were isolated by dilution plate technique. Coliform group in water was evaluated with the reference to EPA manual Microbiology Methods. The results showed that of the three ponds, pond 1 has highest number of bacterial counts (30x104) followed by pond 3 (24 x104) whereas pond 2 showed minimum colony count (12 x 103) per ml of water. The coliform bacteria count in the above pond water sample is far above the safety limit of WHO. Besides gram negative rod shaped coliform group, two groups of gram positive round shaped (with colony colour violet and orange) and gram positive rod shaped bacteria group were also found dominant.

Key words: Viable coliforms, Gram negative, Gram positive

INTRODUCTION With two thirds of the earthâ&#x20AC;&#x2122;s surface covered by water and the human body consisting of 75 percent of it, it is evidently clear that water is one of the prime elements responsible for life on earth. Our drinking water today is far from being pure, contains bacteria, viruses, inorganic minerals (making the water hard) and a chemical cocktail that is unsuitable (if not deadly) for human consumption. The particular group in this regard is the coliforms which are considered as a warning signal and the water is subject to potentially dangerous pollution even with single coliform bacterium. Even the water used for washing and animal drinking purpose should not contain more than 50 coliform bacteria (CPCB, 2001-2002). It is well known that freshwater fish and their aquatic environment can harbour human pathogenic bacteria, particularly members of the

coliform group (Leung, Huang & Pancorbo 1992; Pullela, Fernandes, Flick, Libey, Smith & Coale1998; Ramos & Lyon 2000). The coliforms bacteria group may occur in water due to faecal contamination, i.e, discharge of faeces by humans, all warm-blooded aquatic animals and some reptiles (Enriquez et al. 2001). Coliform includes the members of the family Enterobacteriaceae, e.g. Escherichia coli, Enterobacter aerogenes, Salmonila and Klebsiella . The faecal indicator bacterium (viz. E. coli) has been considered as bioindicator of faecal contamination of drinking water. The public health burden is determined by the severity of the illnesses associated with pathogens, their infectivity and the population exposed. There has therefore been an increased interest in the application of quantitative risk assessment for microbial load in drinking sources (Suthar et al, 2009). The present study is aimed to

GOGOI & SHARMA, Curr. World Environ., Vol. 8(1), 85-91 (2013)

study the water quality standard by analyzing the viable coliforms along with other water born bacteria of three major community ponds which are used for human and animal bathing, washing clothes and also for drinking under water crises condition (winter). The data of this study may provide some important information about public health risks associated with the use of pond water in the region.

the month of August 2002. August month is the post monsoon month with aquatic bodies full of water and pollutants. The samples were collected in triplicate from each pond. Bacteria were isolated by dilution plate technique following Halvorson and Ziegler (1933) methods using nutrient agar media. Presence of Coliform group of bacteria was tested with the reference to EPA manual (1978). Schematic method for coliform detection is shown in Figure1.

MATERIALS AND METHODS Sample collection Water samples which are used mostly for consumption as well as watering livestock were collected from three ponds of Dibrugarh district in

The primary identification of the isolates was carried out on the basis of their culture characteristics on agar plates and microscopic observations. The Secondary identification of the isolates was carried out on the basis of their enzymatic characteristics (Greenberg et al, 1985).

Fig. 1: Schematic model of laboratory testing for detection of coliform group in water with the reference to EPA manual â&#x20AC;&#x153;Microbiology Methods for Monitoring the Environment- water and wastewater"

GOGOI & SHARMA, Curr. World Environ., Vol. 8(1), 85-91 (2013) After 24 hrs of incubation under anaerobic condition at 30oC, gas and acid production indicate presence of coliform bacteria. For conformation of coliform group, presumptive and confirmed tests were done using EMB agar and Endo agar medium by streak method. Besides coliform, three other bacterial species (gram positive round shaped and rod shaped) were selected for comparative analysis. The colonies formed on EMB agar were picked up on nutrient agar slant for further study. Growth conditions and growth yield The total plate count was conducted by pour plate technique on plate count agar (PCA) and counting the colonies developed after the incubation at 37°C for 24 hours (APHA, 1998). All bacteria were grown in sterilized peptone water with nitrate medium (pH=7.2) supplemented with 0.1gm KNO3. Cultures were incubated at 27ºC for 24 hours. After 24 hrs 1 ml from each tube was transferred into four test tubes (each) containing sterilized peptone water with nitrate medium for growth and estimation of enzyme activity. Growth was monitored by measuring the absorbance at 660nm using spectrophotometer. Protein content of media was estimated after different incubation period following Lowery method, 1951. After incubation the media was centrifuged to remove bacterial pellets at 20,000 rpm for 5 minutes. The unit of protein measurement was µg/ml (Figure 3). One unit is equivalent to the amount of lysine utilize in one minute under standards experimental condition. Nitrite analysis To confirm the presence of anaerobic

bacteria in the water sample and to analyze the enzymatic activities of selected bacterial strains, nitrate test was performed. Fermentation of lactose broth and demonstration of Gram-negative, non sporulating bacilli constitute a positive completed test demonstrating the presence of some member of the coliform group in the volume of sample examined. Nitrite was determined by the method of (Daniels et al. 1994). Cultures were inoculated in 10 ml sterilized peptone water with nitrate medium separately and incubated in the incubator for 1 day. 1 ml from each test tube was transferred into four test tubes containing sterilized medium. After 3 days, 8 ml of each type were separated out in centrifugal tube and were centrifuged at 20,000 rpm for 30 minutes. The supernatant were used for extra cellular enzyme and the pellets suspended in the same volume of water were used for intracellular enzyme estimation. The unit of measurement was µg/mg of protein. RESULTS The screening of three selected pond showed large number of bacterial colony in the water sample. Among the 3 ponds, pond 1 showed highest number of bacterial counts (30x10 4 ) followed by pond 3 (24 x10 4) whereas pond 2 showed minimum colony count (12 x 103) per ml of water. Microbial analysis showed four dominant types of bacterial group viz, gram negative rod shaped coliform group, two groups of gram positive round shaped (with colony colour violet and orange) and gram positive rod shaped bacteria, besides several other species (Table 1). From 1st

Table 1: Cultural characteristics of Bacteria isolated from different pond water Colony Character Growth medium Margin Elevation Colour Gram reaction Shape

Bacteria-I

Bacteria-II

Bacteria-III

Bacteria-IV

EMB Wavy Convex Metallic (coliform confirmed) Gram “- “ve Rod

EMB Entire Convex Violet

EMB Entire Convex Orange

EMB Entire Convex White

Gram “+ “ve Round

Gram “+”ve Round

Gram “+ “ve Rod

GOGOI & SHARMA, Curr. World Environ., Vol. 8(1), 85-91 (2013) Table 2: Four different types of bacteria were observed in the plates. The intensity of each type recorded in water sample was as follows

Gram”-” ve (metallic) Gram “+”ve(Violet) Gram “+”ve (Orange) Gram “+ “ve (White)

Pond A

Pond B

Pond C

++ ++ ++

+++ ++ + -

++ + + ++

+ = Few in number, ++ = Common, +++ = Abundant, - = Nil pond, about 74 numbers of coliform bacteria were counted per 100ml of water sample. Similarly, from Pond 2 and three 59 and 67 numbers of coliform bacteria were identified per 100 ml of water respectively.

The non diluted (control) sample showed maximum bacterial growth as compared to diluted samples followed by 2 timed diluted samples. However, least bacterial growth was recorded in 10 times diluted sample. An increase in growth was recorded with the increase in incubation period in

Fig. 2: Bacterial growth tested spectrophotometrically at 640nm after incubation at 30oC in peptone water medium containing potassium nitrate

Fig. 3: Bacterial population was also tested by estimating protein content / ml of culture

GOGOI & SHARMA, Curr. World Environ., Vol. 8(1), 85-91 (2013) control and 2 times diluted samples but 10 times diluted samples shows non sequential growth pattern (Fig 2). The maximum growth of bacteria I was observed in 4 th day (1.193 O.D/cell suspensions) in non diluted sample however, analogous growth was observed from 2nd to 3rd day at two times dilution. However unequal growth pattern is visible in the samples with ten fold dilution. The protein content of Bacteria I was highest (834.49 Âľg / ml) in control medium at 4th day compared to other three groups (Fig 3). In contrary, this bacterium confines maximum protein in ten times diluted sample at 1st, 2nd and 4th day consecutively in 2 times dilution. As a whole, Bacteria IV produced maximum protein (1541.6 Âľg

/ ml) at 1st day followed by Bacteria I in 10 times diluted sample. The amount of nitrite produced both by Bacteria I, III and IV was found maximum in control sample after 62, 24 and 62 hrs of incubation respectively (Fig 4). Bacteria II however, showed highest nitrate reductase activity in 2 times diluted samples after 62 hrs of incubation. The nitrate reduction of intercellular enzyme produced by Bacteria I was always high except 2 nd day of incubation, where Bacteria IV showed the highest enzymatic activity. However, the extra cellular enzymatic activity of Bacteria IV was higher in all the four days in comparison to the other three isolates.

Fig. 4: The breakdown of nitrate to Nitrite content / ml of culture caused by nitrate reductase enzymes

DISCUSSION Detection of faecal indicator bacteria in drinking water provides a very sensitive method of quality assessment and it is not possible to examine water for every possible pathogen that might be present. Ideally, drinking water should not contain any microorganisms known to be pathogenic or any bacteria indicative of faecal pollution (WHO, 1993). Similarly the washing and bathing water should not contain more than 50 coliform bacteria per 100ml of water (CPCB, 2001-2002). Coliform bacteria counted in the above study are well above the safety guidelines together with the other gram positive and gram negative bacterial group.

The selected ponds have allochthonous inputs in the form of domestic waste, bathing of human and animals, washing of cloths and utensils, etc. According to WHO guidelines (1984), the occurrence of pathogens or indicator organisms in ground or surface water mainly depends on the range of human activities and animal sources that release pathogens to the environment. Nonetheless, the inadequate availability of water, ill maintenance of pond water, unsafe disposing of human, animal and household wastes, unawareness about good sanitation and personal hygienic practices etc. are some key factors responsible for poor drinking water quality in rural India including the state of Assam (report by planning commission of India 2002).

GOGOI & SHARMA, Curr. World Environ., Vol. 8(1), 85-91 (2013)

Coliforms may be used as water quality indicator, and if such bacteria are not detected in 100ml of sample; the water can be said as safe for drinking and bathing purpose (Klen and Casida 1967). The water sample of three ponds of Dibrugarh area showed the presence of faecal coliforms i.e, E . coli , which indicates the contaminations of pond water by animal and human generated wastes. The continuous consumption of such contaminated water may pose a serious health risks in local community of the area especially during the summer season as this is a flood prone and high rainfall area (Sutar et al 2009). Borah et al. (2010) have found over 78% of tested pond samples as E. coli contaminated. MPN of fecal coliform count was reported to be around 28000 cfu/100 ml in Kakotibari TE and Sockieting TE of Assam. They have reported over 0.7 % population affected by the diarrheal and dysentery disease. High coliform counts were the most common reason for the failure of potable water to meet acceptable standards. Usha et al (2006) also reported the presence of faecal streptococci, Escherichia coli, Enterobacter sp., Aeromonas sp. and Vibrio sp. in lake water of Tamil Nadu. Presence of coliform count in the water sample also point towards pollution of the lake and leads to pathogenic fish diseases. In the present survey the bacterial count of about 104 to 105 are reported per ml of the sample water. The detection of pathogenic enteric bacteria in different sources of water in this area also reveals the alarming situation for water borne diseases in this particular area. Water quality signifies that pollution of the water is increasing

alarmingly and that it has created serious threat to human health and environment. The breakdown of nitrate during the ensiling fermentation is caused by nitrate reductase enzymes, found in Enterobacteria, Clostridia and Lactobacilli species. Enterobacteria are mainly responsible for degradation of nitrate in silage (Spoelstra, 1987). Nitrate reduction in a silage counteracts the acidification process (Spoelstra, 1985) resulting in a poorer quality product. Present study also depicted higher nitrate reductase activities among the isolated bacterial strains (Fig 4). The lack of safe water supply and of adequate means of sanitation is blamed for as much as 80 % of all diseases in developing countries. A regular monitoring the water quality for improvement not only prevents disease and hazards but also checks the water resources from going further polluted (Trivedy and Goel, 1986). The management of water resources is of the essence to provide safe water. Moreover, water sources must be protected from contamination by human and animal waste, which can contain a variety of bacterial, viral, protozoan and helminthes parasites. ACKNOWLEDGEMENTS The authors are highly grateful to Prof. R. Samanta, Department of Life sciences, Dibrugarh University, Assam for his valuable suggestions in conducting the work and also to the Department of Life sciences providing the essential laboratory facilities to carry out the experiments.

REFERENCES 1.

3. 4.

Anand, C., P. Akolkar, and R. Chakrabarti. Bacteriological water quality status of river Yamuna in Delhi. J. Environ. Biol. 27: 97-101 (2006). APHA. Standards Methods for the Examination of Water and Wastewater. 20th edition, American Public Health Association, Washington, D.C (1998). Borah M., J. Dutta, and A.K. Misra., Int. J. Chem. Tech. Res. 2: 1843-1851 (2010). CPCB (Central Pollution Control Board): Water Quality Criteria and Goals. MINARS/

5. 6.

17/2001-2002 Drinking Water Quality Standards. www.edstrom.com Environment Protection Agency: Microbiology Methods for Monitoring the Environment, Water and Wastes. U. S. Environmental Protection Agency, Washington, D. C., A manual of laboratory procedures (1978). Halvorson, H.O. and N.R. Ziegler., Application of Statistics to problems in bacteriology: I. A means of determining bacterial population

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by 8. the dilution plate method. J. Bacteriol. 25: 101-121 (1933). Klein D.A. and L.E. Casida, E. coli dies out from normal soil as related to nutrient availability and the indigenous microflora. Can. J. Microbiol. 13: 1456-1461 (1967). Leung, C., Y. Huang and O. Pancorbo.., Bacterial flora associated with a Nigerian freshwater fish culture. J. Aquacul. Trop. 5: 87-90 (1990). Lowry, O.H., N.J. Rosebrough, A.L. Farr and R.J. Randall., Protein measurement with the Folin-Phenol reagents. J. Biol. Chem. 193: 265-275 (1951). B. Hari Kumar, Shani Basheer and Haseena., Orient. J. Chem., 26(4): 1449-1453 (2010). Pulella, S., C. Fernandes, G.J. Flick, G.S. Libey, S.A. Smith and C.W. Coale., Indicative and pathogenic microbiological quality of aquacultured finfish grown in different production systems. J. Food Prot. 61: 205210 (1998). Ramos, M. and W.J. Lyon., Reduction of endogenous bacteria associated with catfish fillets diversity of using the grovac process. J. Food Prot. 63: 1231-1239 (2000). Suthar S., V. Chhimpa and S. Singh., Bacterial contamination in drinking water: a study in rural areas of northern Rajasthan, India. Environ. Monit. Assess. 159: 43-50 (2009). Trivedi, R.K. and P.K. Goel., Chemical and Biological Methods for Water Pollution

17. 18.

19. 20.

21.

22.

23.

24. 25.

Studies. Environmental publication, Karad 415110. India (1986). Rajesh P. Ganorkar and V.S. Jamode., Orient J. Chem., 26(3): 1199-1201 (2010) Usha R., K. Ramalingam and B. Rajan., Freshwater Lakes- A potential source for aquaculture activities- A model study on perumal lake, Cuddalore, Tamil Nadu. J. Environ. Biol. 27: 713-722 (2006). World Health Organization., Guidelines for Drinking water quality, 1,2 and 3 (1983). World Health Organization., Guidelines for drinking water quality recommendations. Geneva: WHO (1984). World Health Organization., Health Guidelines for the Use of Wastewater in Agriculture and Aquaculture. WHO Technical Report Series, Number 778. World Health Organization, Geneva, Switzerland (1989). World Health Organization., Our Planet, Our Health, Report of the WHO Commission on Health and Environment. World Health Organization, Geneva (1992). World Health Organization., Guidelines for Drinking Water Quality, Volume I, II and III, World Health Organizations, Geneva (1993). World Health Organization., Basic Environmental Health, Geneva (1997). World Health Organization., Emerging issues in water and infectious disease. Geneva: WHO (2003).

Current World Environment

Vol. 8(1), 93-102 (2013)

Seasonal Variation of Some Physico-chemical Characteristics of Three Major Riversin Imphal, Manipur: A Comparative Evaluation TH. ALEXANDER SINGH1, N.SANAMACHA MEETEI2, and L. BIJEN MEITEI* 1

Research Scholar, CMJ University, LaitumkhrahShillong, Meghalaya -793 003. 2 Directorate of Environment, Imphal East - 795 010, Manipur. *Directorate of Environment, Porompat, Imphal East-795 005, Manipur. DOI : http://dx.doi.org/10.12944/CWE.8.1.10 (Received: March 22, 2013; Accepted: April 10, 2013) ABSTRACT

Documentation on water quality based on seasonal distribution pattern of physic-chemical characteristics of the three major rivers flowing in Imphal, Manipur were carried out during July, 2011 to June, 2012. Three main seasons were classified based on the ombothermicinformation for ten years weather data of Imphal. Significant seasonal variations of the different parameters were observed and the study has a great valuein terms of river ecosystem as well as water quality in different seasons.

Key words: Anthropogenic, Eutrophication, Allochthonous, Seasonal variation, River ecosystem, population growth, pollution. INTRODUCTION Water, by means of its physical, chemical and biological characteristics, reflects the significance as potent ecological factor and quality for sustenance. However, the increasing anthropogenic influences in recent years, in and around aquatic ecosystem and their catchment areas have contributed to a large extent to various nutrient enrichment which leads to deterioration of the water quality. The increasing trend of nutrient enrichment in the system accelerates eutrophication and growth of many aquatic organisms, which exerts a great surge to the ecosystem of many fresh water bodies. The very source of potable water contains both micro and macro nutrients in permissible limit but quality of drinking water changes due to human interference and get contaminated through percolation and seepage, drains and domestic sewage (Pandey and Kumar, 1995). Now-a-days due to rapid industrialization and human population growth most of the Indian

rivers are polluted (Sahu, 1991). The physicochemical characteristics are also greatly affected due to discharge of domestic, municipal, industrial and other several factors like religious offerings, recreational and constructional activities in the catchments areas ( Pandaet al.,1991). Hill and Webb (1958) reported that rainfall pattern influences in changing the physical and chemical environment of water and helps in increasing input of pollutants. Thus, necessary knowledge of the water quality for framing, restoration and management could result only after determining the distribution patterns of ever increasing enrichment of nutrients. Therefore, the present investigation has been carried out with the objectives to assess the seasonal variation as well as water quality status basedon some physico-chemical characteristics of three major rivers of Imphal, Manipur. MATERIAL AND METHODS Samples for the characterization of different physico-chemical parameters were

SINGH et al., Curr. World Environ., Vol. 8(1), 93-102 (2013)

collected at monthly intervals from five (5) experimental sites of three rivers namely Imphal river, Nambulriver and Iril river within Imphal area of Manipur during July, 2011 to June, 2012. Water samples from different sites were collected by means of shallow water sampler in a polystyrene bottle. Some physico-chemical parameters like water temperature, conductivity, total dissolved solid, dissolved oxygen, free CO2 and pH were analyzed and recorded on the spots immediately after collection of the water samples. Analysis for the remaining physico-chemical parameters were carried out in thelaboratory. The methods used for the estimation of the variables were standard methods of APHA (1989) andTrivedy and Goel (1984). For statistical analysis of seasonal variation, different seasons were classified according to ombrothermicinformation based on ten years data of air temperature, rainfall and humidity. Based on the informations, March to May is considered as summer season, June to October as rainy season and November to February as winter season. Accordingly, the mean values of different parameters from five different sites of each river were used for the calculation of ANOVA (Analysis of variance) in different seasons. The methods of parker (1973) and Trivedi, Goel and Trisal (1987) were used in computing and analysis of ANOVA seasonally in different rivers.

season and minimum as 20.82 ±1.34°C in Imphal river during winter season . Conductivity Average mean conductivity from all the sites of different rivers was found maximum during summer. Maximum value is369.78 ±32.72m Siemens cm-2in Nambulriverand minimum value is during winter i.e. 94.50 ±22.60mSiemens cm-2in Iril river. Ranges of conductivity values from across the sites were67.33mSiemens cm-2 (Irilriver during January) to 401.33mSiemens cm-2(Nambul river during May). Total Dissolved Solid Total dissolved solid concentration from all the sites of different river varied from 40.67 mgl1 (Imphalriver during January) to 181.94 mgl-1 (Iril river during August). Highest concentration of T.D.S. was recorded as 131.59 ±31.74mgl-1in Iril river during rainy season and minimum as 51.67 ±7.93mgl-1in Imphal river during winter. Turbidity Turbidity from all the sites of different rivers fluctuated from 18.40 NTU (Imphalriver during January) to 95.47NTU (Imphal river during September). Seasonally, the highest and lowest concentration of turbidity was recorded as 75.93 ±18.81 NTUinImphal river during rainy seasonand 20.98 ±2.15 NTU in Imphal river duringwinter season . pH

RESULTS The results of the physico-chemical analysis for five sites of three different rivers are depicted in table1-3. Values are mean for fivedifferent sites for each river during July, 2011 to June, 2012. Water Temperature Temperature of water of Imphal river ranges from 19.39 °C (January) to 25.33 °C (June) as compared to ranges of 21.00°C(January) to 26.34°C (August) of Nambul river and 19.50°C (January) to 25.43°C (July) of Iril river. Seasonally, the average maximum mean value was recorded as 25.02 ±0.75°C in Nambul river during rainy

The pH value of different river water shows a mark fluctuation for the different sites. The range of pH value shows a variation from 6.56 (Nambul river during January) and 8.36 (Nambul river during August).However, the highest average mean value was recorded as 8.01 ±0.26 in Iril river during rainy season and lowest 6.78 ±0.20 in Nambul river during winter season. Free CO2 During the studies, Free CO2 concentration of the riversfor different sites also shows mark fluctuation. The ranges of Free CO2 were found to be fluctuated from 2.93 mgl -1 (Irilriver during November) to 33.84 mgl-1 (Nambul river during January). The average mean concentration of Free

DO (mg/l)

FreeCO2(mg/l)

6.82

4.71

6.80

IMR

11.73

5.09

8.39

15.69

7.72

IMR

7.59

IMR

86.62

67.18

(NTU)

54.65

128.00

IMR

74.00

Turbidity

114.00

IMR

TDS (mg/l)

282.66

169.33

Siemens/cm2)

25.43

144.00

25.23

IMR

25.30

IMR

5.22

4.28

4.66

6.16

19.91

8.36

8.14

8.36

7.67

75.03

43.35

91.7

181.94

157.33

101.33

182.00

347.33

134.00

25.20

26.34

24.60

5.29

4.94

4.20

4.25

18.60

8.21

7.97

7.89

8.42

57.91

36.72

95.47

123.33

108.67

86.67

174.67

312.00

150.67

24.61

24.22

24.86

Sept

Aug

Code

Jul

2011

River

Cond.(Âľ

Temp. (0C)

Parameter

6.27

4.24

4.72

3.08

20.81

10.07

7.82

6.97

7.88

52.64

47.95

58.10

94.00

134.00

72.67

136.67

308.67

182.00

24.59

24.32

24.572

Oct

5.53

4.33

5.26

2.93

25.05

12.76

7.64

7.04

7.48

49.84

48.71

21.13

85.33

86.67

58.67

122.00

309.33

164.00

24.15

23.70

22.61

Nov

5.13

3.21

5.10

3.37

29.14

10.12

7.34

6.79

7.29

31.73

31.15

20.73

56.67

68.00

51.33

98.67

254.67

146.67

22.03

21.35

20.41

Dec

5.29

3.61

5.06

3.96

33.84

10.27

7.22

6.56

7.18

29.00

28.59

18.40

50.00

52.67

40.67

67.33

226.67

124.00

19.50

21.00

19.39

Jan

5.22

3.97

5.43

5.72

29.99

10.56

7.37

6.73

7.30

36.49

37.76

23.66

70.67

86.67

56.00

90.00

314.00

136.67

20.58

21.69

20.876

Feb

5.26

3.67

5.50

7.18

25.67

12.91

7.40

6.97

7.41

54.53

65.34

27.97

90.00

96.00

72.67

142.00

336.00

159.33

21.69

23.32

22.88

Mar

2012

5.19

4.57

5.28

4.55

20.03

12.46

7.59

7.09

7.48

60.00

70.17

37.15

101.33

102.67

84.168

156.00

372.00

182.00

23.09

24.39

23.76

Apr

6.02

4.60

5.41

5.28

17.77

15.99

7.68

7.43

7.54

70.91

89.07

55.28

122.67

126.67

92.00

190.67

401.33

200.00

23.57

24.58

24.344

May

Table 1: Monthly variations in physico-chemical characteristics of Imphal river (IMR), Nambul river (NR) and Irilriver (IR), (July 2011 to June 2012). Values are mean for five different sites of each river.

6.63

5.78

5.45

4.99

15.82

17.18

7.74

7.59

7.72

83.92

98.40

79.73

130.67

144.00

116.00

228.67

398.00

230.00

24.79

25.28

25.33

Jun

SINGH et al., Curr. World Environ., Vol. 8(1), 93-102 (2013) 95

3.60 9.12 6.28 70.26 85.33 54.00 13.08 19.81 8.76 8.56 8.49 4.09 0.22 0.26 0.39 0.032 0.252 0.082 4.46 13.67 3.67

1.90 6.58 7.23 37.34 118.93 51.07 8.33 23.86 11.60 4.01 10.91 5.38 0.19 0.29 0.51 0.023 0.388 0.032 3.40 13.00 3.33

3.61 8.83 5.54 53.47 116.53 44.80 7.87 24.20 9.14 8.15 13.35 5.53 0.36 0.40 0.38 0.028 0.284 0.032 3.67 13.80 3.20

Sept

Aug

Code

Jul

2011

River

IMR NR IR Hardness (mg/l) IMR NR IR Calcium (mg/l) IMR NR IR Magnesium (mg/l) IMR NR IR Nitrate (mg/l) IMR NR IR Inorganic PO4(mg/l) IMR NR IR Potassium (mg/l) IMR NR IR

BOD (mg/l)

Parameter

4.03 10.72 4.70 53.33 99.47 40.67 12.64 23.10 7.86 5.65 9.76 5.60 0.29 0.19 0.28 0.032 0.204 0.031 4.00 10.00 3.80

Oct 1.71 4.32 4.33 54.53 62.13 38.53 15.18 11.65 7.21 4.79 7.73 5.53 0.14 0.37 0.22 0.021 0.198 0.027 3.20 15.00 5.60

Nov 4.70 5.83 3.41 49.60 55.60 36.13 9.40 10.69 6.97 6.01 7.04 4.22 0.18 0.29 0.07 0.019 0.164 0.020 3.73 10.93 3.00

Dec 5.07 7.26 2.85 55.33 75.20 37.20 13.09 19.76 7.38 5.15 7.26 4.03 0.17 0.35 0.07 0.015 0.158 0.013 4.13 12.87 3.00

Jan 4.09 9.73 3.46 65.33 93.47 45.47 14.25 21.36 8.23 6.98 10.21 5.19 0.21 0.50 0.12 0.018 0.220 0.019 2.87 13.80 3.67

Feb 4.40 8.40 3.69 72.00 104.80 48.93 16.41 22.54 8.22 7.84 11.64 6.54 0.21 0.45 0.15 0.016 0.208 0.024 4.93 11.93 4.33

Mar

2012

4.88 10.96 3.30 85.33 111.33 67.07 18.82 22.87 12.76 8.91 11.82 7.35 0.26 0.53 0.13 0.013 0.246 0.028 4.80 13.34 6.93

Apr

5.92 9.01 3.81 95.60 114.40 83.60 21.91 24.26 19.28 10.96 13.64 9.65 0.32 0.60 0.13 0.017 0.378 0.034 7.87 15.07 7.07

May

Table 2: Monthly variations in physico-chemical characteristics of Imphal river (IMR), Nambul river (NR) and Irilriver (IR), (July 2011to June 2012). Values are mean for five different sites of each rive

5.62 6.94 4.96 100.26 126.80 86.13 20.46 25.60 19.50 12.21 15.40 7.71 0.38 0.63 0.26 0.024 0.508 0.028 8.60 17.67 5.67

Jun

96 SINGH et al., Curr. World Environ., Vol. 8(1), 93-102 (2013)

SINGH et al., Curr. World Environ., Vol. 8(1), 93-102 (2013)

Table 3 :Seasonal variations in physico-chemical characteristic of Imphal river (IMR), Nambul river (NR) andIrilriver (IR), (July 2011 to June 2012). Values are from the average mean of five different sites of each river Parameter

River Code Summer

Rainy

Winter

Total Annual

Temperature (0C)

IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR IMR NR IR

24.93 ±0.37 25.02 ±0.75 24.92 ±0.37 168.13 ±38.96 329.73 ±44.56 178.27 ±33.08 98.13 ±18.45 123.60 ±32.96 131.59 ±31.74 75.93 ±18.81 62.61 ±27.90 67.34 ±12.64 7.86 ±0.33 7.71 ±0.50 8.01 ±0.26 11.90 ±4.23 17.37 ±3.67 4.71 ±1.14 5.17 ±1.03 4.76 ±0.66 6.04 ±0.74 3.75 ±1.33 8.44 ±1.70 5.74 ±1.03 62.93 ±23.90 109.41 ±16.75 55.33 ±17.99 12.48 ±5.06 23.31 ±2.16 11.37 ±4.75 7.72 ±3.13 11.58 ±2.79 5.662 ±1.30 0.23 ±0.08 0.35 ±0.17 0.36 ±0.10 0.028 ±0.004 0.327 ±0.12 0.041 ±0.023 4.83 ±2.15 13.63 ±2.74 3.93 ±1.00

20.82 ±1.34 21.78 ±0.91 21.57 ±2.01 142.84 ±16.90 276.17 ±42.60 94.50 ±22.60 51.67 ±7.93 73.50 ±16.44 65.67 ±15.69 20.98 ±2.15 36.55 ±8.98 36.77 ±9.25 7.31 ±0.12 6.78 ±0.20 7.39 ±0.18 10.93 ±1.24 29.51 ±3.61 4.00 ±1.22 5.21 ±0.17 3.78 ±0.48 5.29 ±0.17 3.89 ±1.51 6.79 ±2.30 3.51 ±0.61 56.20 ±6.59 71.60 ±16.70 39.33 ±4.21 12.98 ±2.54 15.87 ±5.47 7.45 ±0.55 5.73 ±0.98 8.06 ±1.46 4.74 ±0.73 0.17 ±0.03 0.38 ±0.09 0.12 ±0.07 0.018 ±0.001 0.185 ±0.029 0.020 ±0.006 3.48 ±0.56 13.15 ±1.72 3.82 ±1.23

23.24 ±2.03 23.71 ±1.64 23.27 ±1.92 162.78 ±30.79 321.89 ±53.15 146.50 ±46.55 78.85 ±24.50 103.11 ±32.15 102.88 ±36.91 48.66 ±28.31 56.99 ±24.23 55.77 ±17.21 7.58 ±0.33 7.26 ±0.54 7.69 ±0.35 12.05 ±2.99 22.36 ±6.46 4.71 ±1.29 5.24 ±0.63 4.31 ±0.68 5.65 ±0.61 4.13 ±1.30 8.14 ±1.99 4.46 ±1.33 66.03 ±19.38 97.00 ±23.12 52.80 ±17.25 14.29 ±4.55 20.81 ±4.83 10.58 ±4.47 7.44 ±2.49 10.60 ±2.69 5.90 ±1.67 0.24 ±0.078 0.41 ±0.14 0.23 ±0.14 0.022 ±0.01 0.267 ±0.11 0.031 ±0.02 4.64 ±1.79 13.42 ±2.01 4.44 ±1.49

Conductivity (µ simens/cm2) T.D.S. (mg/l)

Turbidity (NTU)

FreeCO2 (mg/l)

Dissolved Oxygen (mg/l) B.O.D (mg/l)

Hardness (mg/l)

Calcium (mg/l)

Magnesium (mg/l) Nitrate (mg/l)

Inorganic Phosphate(mg/l) Potassium (mg/l)

23.66 ±0.74 24.10 ±0.68 22.78 ±0.98 180.44 ±20.38 369.78 ±32.72 162.89 ±25.06 82.95 ±9.72 108.45 ±16.13 104.67 ±16.59 40.13 ±13.90 74.86 ±12.54 61.81 ±8.34 7.48 ±0.07 7.16 ±0.24 7.56 ±0.14 13.79 ±1.92 21.16 ±4.07 5.67 ±1.36 5.40 ±0.11 4.28 ±0.53 5.49 ±0.46 5.07 ±0.78 9.46 ±1.34 3.60 ±0.27 84.31 ±11.83 110.18 ±4.90 66.53 ±17.34 19.05 ±2.76 23.22 ±0.91 13.42 ±5.56 9.24 ±1.59 12.37 ±1.11 7.85 ±1.61 0.26 ±0.06 0.53 ±0.08 0.14 ±0.012 0.015 ±0.002 0.277 ±0.090 0.029 ±0.005 5.87 ±1.74 13.45 ±1.57 6.11 ±1.54

SINGH et al., Curr. World Environ., Vol. 8(1), 93-102 (2013)

CO2 was found to be highest in Nambul river during winter season i.e. 29.51 ±3.61 mgl-1 and lowest 4.00 ±1.22mgl-1in Iril river during winter season. In the annual average,Free CO2concentration was highest inNambul river than the other two rivers.

summer i.e. 12.37 ±1.11mgl-1in Nambul river and minimum during winter as 4.74 ±0.73mgl-1in Iril river.Magnesium values from across the sites ranges from 4.01mgl-1(Imphal river during August) to 15.40mgl-1(Nambul river during June).

Dissolved Oxygen(DO) Dissolved oxygen concentration was found to be fluctuated in each sites of the rivers and it was observed that averageconcentration was high in Iril river than the remaining two rivers. The ranges of dissolved oxygen varied from 3.21 mgl-1 (Nambul river during December) to 6.82 mgl-1 (Imphal river during July) . Average mean concentration was found to be highest in Iril river during rainy seasion as 6.04 ±0.74mgl-1 and minimum of 3.78 ±0.48 mgl1 in Nambul river during winter season.

Nitrate

Biochemical Oxygen Demand Biochemical Oxygen Demand (BOD) values fluctuated from 1.71 mgl-1 (Imphal river during November) to 10.96 mgl-1 (Nambul river during April). Average BOD value shows highest in Nambulriverduring summer season i.e. 9.46 ±1.34mgl-1 and lowest value as 3.51 ±0.61mgl-1in Iril river during winter season. Hardness The concentration of hardness recorded minimum of 36.13 mgl-1 (Irilriver during December) to 126.80 mgl-1 (Nambul river during June). The average mean values of hardness from across the site of the rivers found maximum as concentration of 110.18 ±4.90 mgl -1 in Nambul river during summer season and minimum value of 39.33 ±4.21 mgl-1in Iril river during winter season . Calcium The values range from 6.97 mgl-1 (Irilriver during December) to 25.60 mgl-1 (Nambul river during June). The average mean concentration of calcium was found to be highest in Nambul river during rainy season i.e. 23.31 ±2.16mgl-1 and lowest 7.45 ±0.55mgl-1in Iril river during winter season. For annual average, the highest calcium value was observed in Nambulriveras compared to the remaining rivers. Magnesium The maximum value recorded was during

Nitrate concentration of the three river water of different sites ranged from 0.07 mgl-1( Iril river, January and December) to0.63 mgl-1( Nambul river, June). Seasonally, the average maximum mean value was recorded as 0.53 ±0.08 mgl-1in Nambul river during summer season and minimum as 0.12 ±0.07 mgl-1in Iril river during winter season. Inorganic Phosphate The concentration ranges from 0.013 mgl1 ( Iril river in January, Imphal river in April ) to 0.508 mgl-1(Nambul river in June).Seasonal maximum mean value was 0.327 ±0.12 mgl-1(Nambul river in rainy season) and minimum as 0.015 ±0.002 mgl1 (Imphal river insummer season). Potassium The concentration of potassium in all the different sites of the river exhibits variation ranging from 2.87 mgl-1 (Imphal river during February) to 17.67 mgl-1 (Nambul river during June).The average seasonal maximum mean concentration of 13.63 ±2.74 mgl-1 of Potassium was observed in Nambul river during rainy season and minimum value of 3.48 ±0.56 mgl-1in Imphal river during winter season. Annually, Nambulriver has got maximum concentration of Potassium than the other rivers. DISCUSSION Gradient in the water temperature is closely associated with ambient temperature (Munawar, 1970) and it is one of the most important factors because of its requirements in different metabolic activities of organisms in the ecosystem of different water bodies. In the present studies, the range of water temperature (19.39°C to 26.34 °C) is very much comparable with finding of Srivastava and Singh (1995). The different thermal stratification at different rivers might be due to exposure to wind (Buckley and Sublette, 1964) and small difference between surface and bottom water temperature (Hickling, 1961; Sreenivason, 1968).Therefore,

SINGH et al., Curr. World Environ., Vol. 8(1), 93-102 (2013) seasonal variation at different significant level of the three river shows at p<0.05 and p<0.01. However, insignificant variations were observed in Iril and Imphalriver during rainy season which might be due to lack of thermal exposure during rainy season. Water conductivity is mainly attributed to the dissolved ions liberated from the decomposed plant matter (Sarwar and Majid, 1997) and input of organic and inorganic waste (Wright, 1982). In the present study, the significant level of conductivity in Iril and Imphal river was found always at p<0.05 and p<0.01in all the seasons whereas in Nambul river significant level of p<0.05 was observed only during winter season. This pattern of variation was in support of the finding of Antwi and Ofori-Danson (1993) that liberation of ions results in the increase of conductivity. Total dissolved solids had a cyclic pattern of seasonal changes and maximum during rainy season and minimum in winter. This indicated that the dissolved materials were of allochthonous origin, which was brought into the river system with surface runoff. Johnson (1988) observed that total dissolved solid proportionately enhanced the electrical conductance in water and ran parallel to each other. In the present study, total dissolved solid concentration was found high during rainy season. However significant variation could not be well established during the season. During the study water turbidity was found low during the winter season and high in rainy season. It might be due to the high silt content of the water carried down into the river by the feeder streams from the catchment areas. Therefore, this signifies the variation level of p<0.05 to p<0.01 in Imphal and Iril river. But, significant level of p<0.01 was observed only in winter season. According to Khan and Chowdhury (1994) high value of turbidity during rainy seasons may be due to heavy load of silt into the river water from the feeder streams. Measurement of pH gives the intensity of acidic or basic nature of water. Changes in the pH of water may be the result of various biological activities (Gupta et al., 1996). If the water body is neither highly alkaline nor highly acidic, the pH of water is generally governed by the carbon dioxide - bicarbonate - carbonate system (Hutchinson,

1975). However fluctuation in pH is also related with input loads of pollutants in the river system (Sahuet al., 1995). The high value of pH during rainy season in the present work possibly resulted from increased rate of pollutant from the surrounding areas along with the rain water, but significant variation could not be established in this case also in all the seasons. Free carbon dioxide present in water is mainly originated from the respiration of aquatic biota, decomposition of organic matters and infiltration through the soil. It is an input parameter of the buffer system and influences the concentration of carbonates, bicarbonates, pH and total hardness in water. Higher level of free carbondioxide during winter season may be attributed to increased decomposition rate under the river bed following slowdown of river water current. In the findings of Gupta et al. (1996) and Gupta and Mehrotra (1991) maximum value of free CO2 was found in the month of January and minimum in August. This is in gross agreement with the present finding that free CO2 values wererelatively higher in summer and winter. However, significant variation was observed in two rivers namely Imphal river and Iril river at p<0.01 and p<0.05 during rainy season only. For Nambul river actual significant level could not be established. The rather high dissolved oxygen content during rainy season was largely attributed due to increase in aeration level with increasedflowcurrent of river water.Similar observation was also found by Gupta et al.(1996) that the DO content in river water is higher in monsoon as compared to summer season. The same result was also reported by Gupta and Mehrotra (1991). So, the present observation of higher DO level in rainy season than summer and winter is in conformity with the above findings by other researchers. Significant variation level at p<0.01 was found in two river(Imphal and Iril), but insignificant level of p>0.05 was observed in Nambul river. Biochemical oxygen demand in water indicates the level of organic waste pollution. According to Akpata et al., (1993), microbial oxidization of organic sub-surface leads to the increase in the level of biochemical oxygen demand

100

SINGH et al., Curr. World Environ., Vol. 8(1), 93-102 (2013)

in water bodies. Das (1978) and Das and Pande (1980) reported that high organic materials deposition promotes natural oxidation and thereby depletion of oxygen occurs when anaerobic bacteria take over the process of decomposition. This increases in the value of biochemical oxygen demand level. Higher value during summer season might be due to biological as well as natural oxidation process with increase intemperature. Even though the significant variation could not be established, the BOD level in present observation was found high in summer than rainy and winter season in the three rivers. Level of carbonates was higher during early monsoon i.e. during summer season of the present study, which is similar to the observation of Desai (1991). Kollman and Wali(1976), they observed that maximum value of carbonate was found during the month June which is early monsoon season and minimum during winter. Thus, the concentrations of hardness, calcium and magnesium were found higher during summer season and lower during winter season which is in agreement with the above findings. Significant variation was observed at p<0.01, during rainy season for the two river-Imphal and Iril, whereas for Nambul river it was observed to be at a level of p>0.05. Higher concentration of nitrate was observed during summer and rainy season and lower concentration during winter which shows mark resemblance with the finding of Bhattacharya et al., (2002). In the present study, there was no significant variation in all the seasons. Phosphorus is an important factor in ecological studies and often regarded as a limiting element in water ecosystem (Hecky and Kilhan,

1988). Both organic and inorganic forms are involved in transformation (Holtanet al.,1988). The high values of phosphate during rainy season might be due to transport from the surrounding catchment areas. Significant variation at the level of p<0.05 and p<0.01 were also observed during rainy season except for Nambul river. The low values of the nutrient during winter season might be probably due to lowering in input of pollutant in the river system which conforms the findings of Clarke (1924). In general, concentration of potassium in natural waterislow, but high value being an indication of pollution by domestic waste (Trevedy&Goel, 1984). Potassium value exhibit high during summer and rainy season and low during winter reason. It was due to rain runoff of decomposed plant materials from surrounding catchment area of the river, which help in increasing in the concentration of potassium in the water. In rainy season analysis of variance shows significance at a level of p<0.01 and p<0.05 for Imphal and Iril river whereas Nambul river at p>0.05 insignificance level.

CONCLUSION The seasonal distribution pattern of different parameters were found to be influenced by different environmental factors for the three major rivers in Imphal valley. The presence of nutrient at different levels in the river water throughout the study period offer an excellent opportunity to characterize the quality of the water of the three major rivers in different seasons.This will be highly relevant because these three rivers are the main water resource for the people inhabiting around the Imphal city.

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Akpata, T.V.I., Oyenekan, J.A. and Nwanko, D.I., Impact of organic pollution on the bacterial, plankton and benthic population of Lagos lagoon, Nigeria.Intl. J. Eco. and Env. Sci.19: 73 â&#x20AC;&#x201C; 82 (1993).

Antwi, L.A.K. and Ofori-Danson, P.K. Limnology of a Tropical Reservoir (The Kpong Reservoir in Ghana). Trop. Ecol. 34(1): 75-87 (1993). APHA., Standard Methods for the

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Examination of Water and Waste Water Analysis, (17th Edn.), Washington D.C (1989). Bhattacharya, A.K., Choudhuri, A., and Mitra, A., Seasonal distribution of nutrients and its biological importance in upper stretch of Gangetic West Bengal. Indian J. Environ. & Ecoplan. 6(3): 421 - 424 (2002). Buckley, B.R. and Sublette, J.E., Chironomidae (Diptera) of Louisiana II. The limnology of the upper part of Cane River Lake, Natchitoches Parish, Louisiana, with particular reference to the emergence of Chironomidae. Tulane Studies in Zoology 11(4): 151-166 (1964). Clarke, F.W. , The data of Geochemistry (5th Edn.) Bull. U.S. Geol. Surv.770.U.S.Govt. printing offic, Washington D.C. 841 pp (1924). Das, S.M., High Pollution in lake Nainital (U.P.) as evidenced by biological indicators. Science & Culture 44: 236-237 (1978). Das, S.M. and Pande, J., Pollution, Fish mortality and Environmental parameters in lake Nainital.J.Bombay Nat. Hist. Soc. 79: 100-109 (1980). Desai, P.V.,The impact of mining on the Mayem lake of Bicholim.Goa.In Current Trends in Limnology-1. 279 - 288 (1991). Gupta, A.K. and Mehrotra, R.S. , Ecological studies on water moulds of Kurukshetra. pp. 47-64. In. Current Trends in Limnology 1: 47-64 (1991). Gupta, R.K., Sharma, M., Gorai, A.C. and Pandey, P.N., Impact of Coal Mining Effluents on the physico-chemical charactericts of Raja Tank, Jaria (Dhanbad).J. Freshwater Biol. 8(2): 63-73 .(1996). V. Madgare, S.A. Iqbal, S. Pani and N. Iqbal., Orient J. Chem., 26(4): 1473-1477 (2010). Hecky, R.E. and Kilhan, P. , Nutrient limitation of phytoplankton in freshwater and marine environment. A review of recent evidence on the effect of enrichment. Limnol. Oceanogr. 33: 796-822 (1988). Hickling, C.F., Tropical Inland Fisheries . Longman, London (1961). Hill, M.B. and Webb, J.E., The ecology of Lagos lagoon II. The topography and physical feature of Lagos harbour and Lagonlagoon.Philosophical Transaction of

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the Royal Society of London 214(B): 319333 (1958). Holtan, H., Kamp-Nielsen, L. and Stuanes, A.O., Phosphorus in soil, water and sediment: An Overview. Hydrobiologia 170: 19-34 (1988). Hutchinson, G.E., A Treatise on Limnology. III. Limnological Botany. Willey, New York, U.S.A (1975). Johnson, M.E.C., Total solid content in two freshwater lakes. Indian. J. Bot. 11(2): 188190 (1988). Khan, M.A.G. and Chowhdury, S.H., Physical and chemical limnology of lakeKaptai, Bangladesh.Trop. Ecol. 35 (1): 35-51 (1994).. Kollman and Wali., Inter seasonal variation in environmental and productivity relations of Potamogrtonpectinatus communities. Arch. Hydrobiol. Suppl. 50: 439-472 (1976). Munawar, M., Limnological studies of freshwater ponds of Hyderabad, India. Hydrobiologia 36(1): 127-162 (1970). Panda, R.B., Shau, B.K., Sinha, B.K. and Nayak, A., A comparative study and diurnal variation of physico-chemical characteristics of river, well and pond water at Rourkela Industrial Complex of Orissa.J. Ecotoxicol. Environ. Monit., 1(3): 206-217 (1991). Pandey, R. and Kumar, A., Comparative evaluation of potable water quality of tribal and non-tribal villages of SantalPargana, Bihar. Ecol. Env. &Cons. 1(1-4): 71-74 (1995). Parker, R.E., Introductory Statistics for Biology.Edward Arnold (publisher) Ltd. 25Hill Street, London (1973). Sahu, B.K., A study of the aquatic pollution load in the river Brahmani, Ph.D. Thesis, Sambalpur University, Sambalpur (1991). Sahu, B.K., Rao, R.J. and Behera, S.K. Studies of some physic-chemical characteristics of Ganga river water (Rishikesh-Kanpur) within twenty four hours during winter,1994. Ecol. Env. &Cons. 1(1-4): 35-38 (1995). H.C. Kataria and S. Sharma., Orient J. Chem., 26(1): 337-338 (2010). Sarwar, S.K. and Irfan-UI-Majid., Abiotic features and diatom population of Wularlake, Kashmir. Ecol. Env. &Cons. 3(3): 121-12 (1997).

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studies. Environmental publication, Karad, 215 pp (1984). Trivedy, R.K. ,Goel, P.K. and Trisal, C.L., Practical Methods in Ecology and Environmental Science. Environmental publication, Karad , 340 pp (1987). Wright, R., Seasonal variation in water quality of a West African river (R. Jong in Sierra Leone). Revue dâ&#x20AC;&#x2122;HydrobiologieTropicale. 15(3): 193-199 (1982).

Current World Environment

Vol. 8(1), 103-106 (2013)

Drinking water assessment of 4 locations from Ghaziabad, Uttar Pradesh SHIKHA BISHT1*, B. A.PATRA2 and MONIKA MALIK3 1

Galgotias College of Engineering and Technology, 1, Knowledge Park-2, Greater Noida - 201306, India. 2 Thermo Fisher Scientific, Thermo Electron LLS India Pvt. Ltd., 102, 104, Delphi â&#x20AC;&#x153;Câ&#x20AC;? wing, Hiranandani Business Park, Powai, Mumbai - 400 076, India. 3 Galgotias College of Engineering and Technology, 1, Knowledge Park-2, Greater Noida - 201 306, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.11 (Received: December 20, 2012; Accepted: January 19, 2013) ABSTRACT In this study drinking water samples from 4 different locations in Ghaziabad were collected by random grab sampling. These were analyzed for physiochemical and elemental parameters. The parameters tested were pH, Nitrate, Fluoride, Chloride,Sulphate, Total Dissolved solids, Hardness, Alkalinity, Calcium, Magnesium, Aluminium, Boron, Zinc, Selenium, Manganese, Iron, Chromium, Copper, Lead, Cadmium, Arsenic and Mercury.

Key words: Physiochemical, elemental analysis, drinking water, Ghaziabad,Lohia Nagar, Sec-16, Jatwara, Sahibabad. INTRODUCTION The district of Ghaziabad is situated in the middle of Ganga-Yamuna doab. It lies on the Grand Trunk road about a mile east of the Hindon river in Latitude 280 40' North and Longitude 770 25' East, 19 Kms. east of Delhi1.Since a few years, drinking water problem has increased in the area. In this study, drinking water samples have been collected from 4random locations from the area. Different parameters were examined using Indian Standards2 to find out their suitability for drinking purposes. During this examination, mainly the physico chemical parameters and the elemental concentrations were taken into consideration. MATERIAL AND METHODS Standard methods of collection, preservation and analysis were adopted. Grab sampling method was used for the collection of 4drinking water samples. The locations were selected randomly in the district of Ghaziabad. The analysis of physiochemical parameters was done by procedure adopted from standard methods:

APHA3 and the elemental analysis weredone using ICPMS (Inductively Coupled Plasma Mass Spectrometer, PERKIN ELMER, ElanDRCe). RESULTS AND DISCUSSION Sample 1,Lohia Nagar All physiochemical parameters were found to be under the maximum permissible range for drinking purposes. This is with the exception of fluoride which was observed to be 3.723 ppm in the water sample analyzed. Fluoride is released into the ground water through weathering of primary silicates and associated accessory minerals4. Mineral fluorides are present in underground water structures in the form of leachates from fluorospar, Apatite, Cryolite and fluorosilicates5-6. When rain water percolates through the ground, fluoride ions are picked up 9. In arid regions with limited water recharge and with fluoride bearing minerals deposits present, the ground water becomes rich in fluoride5. It combines with the hydrochloric acid of stomach and leads to the formation of hydrogen fluoride which is highly

BISHT et al., Curr. World Environ., Vol. 8(1), 103-106 (2013)

104

corrosive7) Very low doses of fluoride (<0.6 mg/L) in water promote tooth decay. However, when consumed in higher doses (>1.5 mg/L), it leads to dental fluorosis or mottled enamel and excessively high concentration (>3.0 mg/L) of fluoride may lead to skeletal fluorosis8. Sample 2,Sec-16 All physiochemical parameters were found to be under the maximum permissible range for drinking purposes. Except fluoride, the value for which was found to be 1.66 ppm.

found to be under the maximum permissible range for drinking purposes exceptnitrate and fluoride. The values for these were found to be 187.583 and 3.472 ppm respectively for the water sample analyzed. Such high concentration of nitrate in drinking water may be attributed to the leaching of organic material biodegradation products into water sources. Nitrate has long been associated with the occurrence of blue baby disease in infants9 or infantile methaemoglobinaemia, which is caused due to bacterial reduction of nitrate into nitrite in stomach10.

Sample 3, Jatwara All physiochemical parameters were

Sample 4, Sahibabad The values for except Aluminium, Iron and

Table 1: List of methods and instruments used for physiochemical and elemental analysis S. No.

Parameter

Method/ Instrument used

1 2 3 4 5 6 7 8 9 10 11

pH Total Dissolved Solids Chloride Hardness Fluoride Sulphate Nitrate Alkalinity Calcium Magnesium Elemental Analysis (Al, B, Zn, Se, Ca, Mn, Fe, Mg, Cr, Cu, Pb, Cd, As, Hg)

pH meter Total Dissolved Solids dried at 1000C Argentometric method EDTA titrimetric method SPADNS method Turbidity method Ultraviolet Spectrophotometric Screening Method Titration method Detection by AAS Detection by AAS Detection by ICPMS, Prekin Elmer, ElanDRCe

Table 2:Values for Physiochemical Parameters obtained by chemical methods S. No.

Parameter

Unit of IS measurement 10500 value

Lohia Nagar

Sec-16

Jatwara

Sahibabad

1 2 3 4 5 6 7 8

pH Sulphate TDS Nitrate Chloride Hardness Fluoride Alkalinity

mg/L % mg/L mg/L mg/L mg/L mg/L

7.19 20.5 0.06 99.79 51.984 161.28 3.723 51.22

8.03 19 0.018 5.658 11.996 88.32 1.66 11.82

7.24 76 0.113 187.583 363.887 291.84 3.472 35.46

7.91 38 0.0592 5.365 2.931 49.92 4.68 23.64

7.5-8.5 400 0.2 100 1000 600 1 600

BISHT et al., Curr. World Environ., Vol. 8(1), 103-106 (2013)

105

Table 3: Values of elemental analysis obtained by Atomic Absorption spectrophotometer (AAS) and Inductively Coupled Plasma Mass Spectrometer (ICPMS) S. No.

Parameter

Symbol

Unit of measurement

IS 10500 Lohia max. Nagar value

Sec-16

Jatwara Sahibabad

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Aluminium Boron Zinc Selenium Calcium Manganese Iron Magnesium Chromium Copper Lead Cadmium Arsenic Mercury

Al B Zn Se Ca Mn Fe Mg Cr Cu Pb Cd As Hg

ppb ppb ppb ppb ppm ppb ppb ppm ppb ppb ppb ppb ppb ppb

200 5000 15000 10 200 300 1000 100 50 1500 50 10 50 1

196.13 0.052 0.029 0.111 10.887 3.36 186.53 18.816 0.299 0.0476 0.004 0.019 7.451 0.031

0.01 0.371 0.013 0.0336 26.482 4.798 387.16 64.482 0.835 1.258 0.036 0.044 2.94 ND

fluoride were found to be high in the sample analyzed. The value for Aluminium was observed to be 228.88 ppb which is higher than the IS prescribed limit of 200 ppb. The valuesfor Iron was recorded to be 4598.76 ppb and for fluoride as 4.68 ppm.All other physiochemical parameters were found to be under the maximum permissible range for drinking purposes. Long-term exposure to such high levels of Aluminum may lead to the occurrence of Alzheimerâ&#x20AC;&#x2122;s disease11. Aluminium accumulation in the brain is proposed to be associated with neurodegenerative diseases, including Parkinsonâ&#x20AC;&#x2122;s disease, amyotrophic lateral sclerosis and dialysis encephalopathy12. Aluminium negatively impacts neurotransmission, either by directly inhibiting the enzymes responsible or by affecting the physical properties of synaptic membranes13. The principal forms of mineralized ferric iron found in soils are amorphous hydrous ferric oxide, maghemite, lepidocrocite, hematite,and goethite13. High amount of Iron leads to the growth of iron bacteria in the pipelines thereby deteriorating the microbiological quality of drinking

0.017 0.256 0.318 1.446 17.258 62.54 626.94 34.997 1.143 1.302 0.063 0.081 3.588 ND

228.88 0.456 0.238 0.118 8.886 19.019 4598.76 9.971 0.547 2.037 0.435 0.128 3.142 ND

water14. Excessive ingested iron can also cause excessive levels of iron in the blood because high iron levels can damage the cells of the gastrointestinal tract preventing them from regulating iron absorption15. CONCLUSION Drinking water from Lohia Nagar & Sector 16 couldbe used for drinking after removal of excess of fluoride. Also drinking water from Jatwara could be used for drinking after removal of excess of fluoride and nitrate. Drinking water from Sahibabad could also be used for drinking after removal of excess of fluoride, Aluminium and Iron. ACKNOWLEDGEMENTS The authors are thankful to Arbro Analytical Division, New Delhi for providing research facilities.

106

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www.ghaziabad.nic.in, downloaded 11 October. IS 10500:2004, Drinking Water Specifications. APHA. Standard Methods for the examination of water and wastewater, Pg 2:26-2:29, 2:36-2:39, 2:54-2:56, 4:53-4:56, 4:66-4:68, 4:79-4:83, 4:86-4:91, 4:114-4:115, 4:176-4:179. American Public Health Association (1995). Apambire W. B., Boyle D. R. and Michel F. A., Geochemistr y, genesis and health implications of floriferous ground waters in the upper regions of Ghana. Environ. Geol., 13-24, 33 (1997). Thakare S. B., Parvate A. V. and Rao M.,Analysis of fluoride in the ground water of Akola district, Indian J. Environ. andEcoplan, Vol. 10 No.3, 657-661 (2005). S. Suratman, Orient J. Chem., 27(4): 14971501 (2011). Manjunath D. L.,Environmental studies 2nd edition, Pearson Publications, 150 (2008). Tiwari K., Dikshit R. P., Tripathi I. P. and Chaturvedi S. K., Fluoride content in drinking water and ground water quality in rural area of tahsil Mau, district Chitrakoot, Indian J. Environmental Protection, Vol. 23, No. 9,

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1045-1050 (2003). Agrawal K. C., Environmental pollution causes, effects and controls, 56-83 (2001). Harrison Roy M., Pollution causes, effects and control 3rd edition, 54-65 (1996). Pandian M. Rajasekara, Banu G. Sharmila, Kumar G. and Smila K. H., Physico-chemical characteristics of drinking water in selected areas of Namakkal town (Tamil Nadu), India, Indian J. Environmental Protection, Vol. 10, No. 3, 789-792 (2005). Gonclaves P.P., Silva V. S., Does neurotransmission impairment accompany aluminum neurotoxicity? Journal of Inorganic Biochemistry, 1291-1338 (2007). Vance David B., Iron - the environmental impact of a universal element, National Environmental Journal, May/June Vol. 4 No. 3, 24-25 (1994). Goel P. K.,Water pollution Causes, Effects and Control, 1-27, 97-115 (2001). El-Harbawi M., Sabidi A.A.B.T., Kamarudin E.B.T., Hamid A.B.A.B.D., Harun S. B., Nazlan A. B, Xi-Yi C., Design of a portable dual purpose water filter system. Journal of Engineering Science and Technology, 165175 (2010).

Current World Environment

Vol. 8(1), 107-115 (2013)

Hydro Biological Characteristics of Some Semi-intensive Fish Culture Ponds of Lumding Town of Nagaon District, Assam TAPASHI GUPTA1 and MITHRA DEY2 1

Department of Zoology, Lumding College, Lumding, Assam - 782 447, India. Department of Ecology & Environmental Sciences, Assam University, Silchar - 788 011, India.

DOI : http://dx.doi.org/10.12944/CWE.8.1.15 (Received: December 08, 2012; Accepted: December 25, 2012) ABSTRACT Hydrobiological assessment is useful for assessing the ecological quality of aquatic ecosystem since biological communities integrate the environmental effects of water chemistry. Ten fish ponds from Lumding town, which were under semi-intensive culture practice, were selected for hydrobiological investigations. Physico-chemical properties were studied for a period of two years from July 2009 to June 2011.Some selected parameters like pH, dissolve oxygen, free carbon dioxide, TDS , total alkalinity, total hardness, sp. Conductivity, transparency and BOD were studied on some fish pond water. PH ranges from 6.1 to8.5. Temperature ranges from 180C-320C. Color shows light green to dirty green. Transparency ranges 17-42cm, dissolve oxygen ranges from 3.28.0 ppm, total alkalinity ranges from 7.9-20.0ppm, Hardness ranges from 60-135 ppm, sp.conductance ranges from123-247Âľmhos/cm and BOD ranges from3.1-5.0ppm. The phytoplankton belonging to division Chlorophycae and Cyanophycae are predominant over the others and zooplanktons belonging to group Protozoa, Rotifers are predominant. . A total of 30 species of belonging to Chlorophycae. Cyanophycae were identified and a total of 20 species of Rotifera, 2 species of Cladocera and 1 genus of Copepods were found. The present study is expected to help achieve better and higher yield of fish by the fish farmer with increasing awareness regarding the hydrobiological feature of the pond and implement scientific management practices accordingly.

Key words: Hydrobiological characteristics, Chlorophyceae, Cyanophyceae, Euglenophyceae. INTRODUCTION Lumding is situated in Nagaon District of Assam and lies between 25 045 /- 26 045 North latitudes and 91 0 50 / -93 0 20 / East Latitudes. Lumding is the second biggest town in Nagaon district of Assam. A large section of the people of Lumding depends on Agriculture, Poultry, and Fishery etc. as their means of livelihood. There are about 171 fish ponds constructed and stocked with fish in Lumding and its adjacent area. Some of these are not utilized to its full potential. Studies on physico-chemical condition of ground water of Lumding have already been done by Mrinal Kanti Paul(M.K.paul&A.K.Mishra2009) but the detailed data on the hydrobiology of available water bodies of Lumding still remained scanty. In view of the vast extension of such water bodies which occupies about one third of the plain area of Lumding, the

present study was undertaken to evaluate the hydrobiology of ten ponds of Lumding, which will provide certain information in the survey of the Fishery resources of Lumding and in the proper planning of the fisheries management programme of the town. The interrelationship between the physico-chemical parameters and plankton production of pond water and its relation with fluctuation of plankton are of great importance and basically essential in fish culture. Fishes are dependent on physico-chemical parameters. Any change of these parameters may affect the growth, development and maturity of fish (Jhingran,1985). Phytoplankton is the major primary producers in many aquatic systems and is important food source for other organisms (Sukumaran et al,

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2008). Phytoplanktons not only serve as food for aquatic animal, but also play an important role in maintaining the biological balance and quality of water (Pandey et al.). Zooplankton constitutes important food item of many fishes. The larva of carps feed mostly on zooplankton (Dewan et al,1977). Zooplankton also plays an important role in the food chain, as they are second in trophic level as primary consumers and also contributers to next trophic level(Quasim,1977). The productivity of freshwater community that determines the fish growth is regulated by the dynamics of its physicochemical and biotic environment (Wetzel, 1983). The pH, dissolved oxygen, alkalinity and the dissolved nutrients are important for the phytoplankton production ( Bais & Agarwal, 1990). Plankton diversity responds rapidly to change in the aquatic environment particularly in relation to nutrients. MATERIALS AND METHODS The study was conducted during July 2009 to June 2011. Water samples were collected from ten locations randomly. Analysis of water samples were done following standard methods (APHA, 1995) and Trivedy & Goel(1984). Plankton samples for this study were collected with plankton net made of bolting silk cloth no.25 (mesh size: 0.030.04mm).Plankton net was used to collect plankton samples once in every month. Phytoplankton samples were preserved in Lugolâ&#x20AC;&#x2122;s iodine solution, while zooplankton samples were preserved in 4% formalin solution and then transported to laboratory for plankton analysis (Lackey, 1938) The preserved samples were allowed to settle for 24 hrs and the surface water free of phytoplankton was siphoned out until the sample was reduced to 10ml. 1ml is pipetted from 10ml after shaking in to a sedwick rafter counting cell and mounted on microscope. The phytoplankton were counted and then identified. The volume of water filtered was calculated using the formula: ĂŻ r2h . r = radius of the net used h= the distance of trawling

The actual number of each phytoplankton group/lit. of water filtered was calculated. This was then converted to number of individual group per cubic meter (m3). The zooplankton samples were analyzed in similar way like that of phytoplankton. The identification of plankton species was done with the aid of plankton identification key and monographs (Neeedham and Needham, 1962 ) , Tonapi (1980), Battish (1992) and Bellinger (1992). Pond water was collected from various depths by using boat and was collected to laboratory and analysis of water samples were done following standard methods (APHA, 1992), Trivedy and Goel (1984). RESULTS AND DISCUSSION Depth Minimum water depth was recorded during summer, which shows an increasing trend from July onwards and attained peak during AugustSeptember, followed by a gradual decreasing trend till May-June. The water depth in Pond NO.1 was highest (av. 3.26 m) and that at Pond No.6 was lowest (av. 1.41 m). Transparency Water transparency is an important factor that controls the energy relationship at different trophic levels. It is essentially a function of reflection of light from the surface and is influenced by the absorption characteristics of both of water and of its dissolved and particulate matter (Stepane,1959). Very high fluctuation of transparency was observed in Pond No.6 followed by others in decreasing order. From October to April, the poor to medium transparency were mainly caused by the abundance of zoo and phytoplankton population. The Murabasti ponds, which showed minimum transparency fluctuation, were most productive. In Pond No.6 transparency was very high (80-200cm) during initial period and the pond was very unproductive due to poor availability of plankton in pond water. A very high transparency, therefore, indicate the unproductive nature of water. Water transparency in the range of 20-50cm was found to be conducive for fish ponds.

12.5±0.5

1.3±0.2

T.Hardness(ppm)

5.5±0.1

BOD(ppm)

4.2±0.4

145.4±60.5 220±129

142±4.9

1.3±0.2

10.5±0.2

16±1.7

TDS(ppm)

Sp.Con.(µ mhos/cm) 123.2±2.9

10±0.2

Free CO2 (ppm)

alkalinity(ppm)

Total

8.5±0.7

2.5+ 0.3

3.2+ 1.2

7.1±0.2

DO(ppm)

18.431.6 (27.6)

Water temp0C

42.2 (35.2)

25.6-

18-32

(31.0)

(26.6)

24.2-39

ency(cm)

(2.5)

4.5(3.3)

Transpar-

1.8-3.4

2.2-

Depth

Pond 2

Pond 1

Parameter

(2.5)

1.9-3.2

Pond 4

247±64.3

1.5±0.2

3.9±2.9

7.9±0.2

7.1±0.06

8.8+ 0.2

142.3±4.9

1.4±0.3

7.7±1.2

9.4±1.2

6.6±0.8

5.0+ 0.4

(26.0)

18-32

(25.6)

17.5-35.5

(3.26)

2.19-4.6

Pond 5

150.9±7.5

1.2±0.2

12.7±2

9.8±0.6

6.9±0.4

6.9+ 0.3

(26.4)

18-31.4

(51.4)

31.6-36.0

(1.4)

0.78-2.2

Pond 6

93.2±2.9

1.5±0.08

7.6±2

12.4±1.8

6.2±0.9

6.2+ 0.6

(25.5)

18-30

(25.5)

18.0-35

(2.5)

1.82-3.45

Pond 7

4.3±0.3

2.0±0.13

2.5±0.06

3.5±0.08

3.6±0.13

Pond 9

(3.2)

25.6-42

8.0±0.4

6.5+ 0.4

(28.0)

18.4-31.6

(31.0)

15±1.7

12.2±1.2

11.2±1.6 20.2±1.1

6.1±1.1

6.0+ 0.4

(25.6)

18-31

(26.0)

(3.4)

2.4-4.5

Pond 10

3.1±0.1

3.3±0.08 2.4±0.06

220±129 87.6±36.7

123.2±2.9 142.3±4.9 123±3

1.36±0.26 1.5±0.08 1.3±0.1

22±3.5

17±4.8

7.7±0.4

5.3+ 2.1

(27.0)

18-32

(26.0)

18.4-34.8 17-35

(3.26)

2.18-4.57 2.3-4.6

Pond 8

215.7±128.5 139.3±86.7 218.8±20.6 145.4±60.5 201±153.7 209±128

93.2±2.4

1.6±0.1

abs

16±0.1

8.4±0.4

7.2+ 0.2

(27.0)

18-32 (26.6) 18-31.6

(35.2

18-35 (26.0) 25.7-42.0

(2.52)

1.82-3.45

Pond 3

Table 1: Physico-chemical parameters of Ten ponds of Lumding of Nagon district of Assam , India, during July2009-June 2011 (units in mg/l +Standard Deviation, unless otherwise mentioned). MEAN mg/l ± SD

GUPTA & DEY, Curr. World Environ., Vol. 8(1), 107-115 (2013) 109

Pond 1

Chlorophycae 1. Spirogyra 4 2. Chlorella 92 3. Ulothrix 2 4. Chlamydomonas 15 5. Volvox 10 6. Endorina 7. Microcystis 20 8. Oedogonium 22 9. Closterium Cyanophycae 1.Oscillatoria 5 2.Nostoc 42 3.Anabaena 5 4.Gloeotrichia 3 5.Spirulina 5 Euglenophycae 1. Euglena 12 Zooplankton(No. sp-1) Rotifers. 1. Branchionus rubens 2 (male & female) Protozoans 1. Paramoecium 12 2. Giardia 11 3. Amoeba 12 Copepods 1. Cyclops 25 Cladocera 1. Daphnia 28 2. Ceriodaphnia 11

Parameter

11 24 22 10 16 13 11 12 20 2 5

8 5 12 13 14 -

22 5 24 4 4

10 21 35 12 2

Pond 3

3 33 6 5 15 12 12 2

Pond 2

16 2

4 2 2

4 21 1 4

2 10 4 11 2 6 1

Pond 4

50 -

2 1 4

2 1 2 1

4 12 2 4 3 4 1 -

Pond 5

35 -

7 4 6

2 2 2

2 12 3 20 1 4 2 -

Pond 6

21 2

4 2 2

5 10 2

1 10 1 2 15 1 6 8 2

Pond 7

22 1

4 2 -

5 8 3 1 1

5 14 6 3 11 2 4 9 4

Pond 8

23 3

2 1 2

4 9 2 3 -

2 8 2 8 14 8 7 -

Pond 9

Table 2: Plankton Composition in the water sample of Ten Semi-intensive fish culture ponds during July2009-June 2011.

38 -

1 2

2 4 1 -

3 10 4 3 10 2 2 2 -

Pond 10

110 GUPTA & DEY, Curr. World Environ., Vol. 8(1), 107-115 (2013)

GUPTA & DEY, Curr. World Environ., Vol. 8(1), 107-115 (2013) Temperature The water temperature at different location of Lumding ranged from 18-320C with mean value of 26.50C, 260C, 270C, 260C, 26.50C, 250C, 26.40C, 27 0C, 25 0 C and 26 0C respectively. The water temperature remained below 200C for two months (December and January). The water temperature of the ponds remained within the range of 20-320C for about ten months in a year. The comparative higher temperature in tropical waters than in temperate region is considered to be beneficial for higher productivity in the former. The average water temperature of the ponds at different locations ranged between 25-270C. In the present study, it was generally noted that the growth of carps was optimum in the temperature range of 23-300C. Dissolved Oxygen The dissolve oxygen is the most important and critical parameter requiring continuous monitoring in aquaculture production systems. This is due to the fact that fish aerobic metabolism requires dissolved oxygen (Timmons et al.2001). The dissolved oxygen content of ten ponds ranged

111

from 2.5-8.8ppm. Dissolve oxygen was higher during winter and lower during summer months. Bhowmick (1968), Jana(1973) and Chakraborty (1980) recorded a fluctuation of dissolve oxygen content in their experimental ponds located at West Bengal. During summer, when the temperature was high, fishes in some ponds at Lumding started surfacing during early in the morning when the oxygen content fell below 2.0ppm. pH The pH of water at different selected ponds ranged from 6.1-8.5. Pond No 2,3 and 10 were slightly alkaline whereas Pond No 5, 6, 7 and 9 were slightly acidic rests are within range. A slightly alkaline water (7.2-8.0) may be considered conducive for fish production. Nees (1946) and Banerjea (1967) observed the variation in water pH from 7.1-8.0 as optimum for fish production. Total alkalinity The total alkalinity of ten ponds of Lumding ranged from 7.9-20.5. Total alkalinity was minimum during the rainy day and maximum during

Fig. 1: Percentage abundance of major phytoplankton taxa in ponds 1-10

Fig. 2: Percentage abundance of major zooplankton taxa in ponds 1-10

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summer season. However the total alkalinity is very low, indicating a paucity of carbonates. It implies that people would have to subject the water to treatment before fish farming as the changes of total alkalinity were influenced not only by climatic factors such as temperature and rainfall but also by fish culture practices such as liming and fertilization. Total alkalinity less than 100mg/l is not suitable for fish culture (Scroeder, 1980, Banerjea 1967). Free Carbon dioxide The free CO2 content in ponds at ten centres ranged from 3.9-22mg/l. To maintain a moderate level of CO 2 in pond water, organic manures were applied uniformly at a regular interval to all the centres. But in the pond No 3 free carbon dioxide was absent. Absence of free carbon dioxide is due to its utilization by algae during photosynthesis or carbonate present (Manjare et al. 2010). Total Hardness The total Hardness ( Calcium +Magnesium hardness) at ten ponds ranged from 3.1-8.0 ppm The growth of plankton and fish were low as hardness was very low. Lakshmanan et al (1967) also recoded poor production of plankton and fish in acidic ponds in Assam having poor calcium content. Total Dissolved Solids Electrical conductivity can be used as an index of TDS (Sreenivasan,1964). TDS may consists of different kinds of nutrients and minerals.High amount of total dissolved solids was observed in pond no 9 during survey period.The total dissolved solids in ten ponds of Lumding fluctuated between 87-220 ppm. Highest value was recorded during October and lowest was recorded in June. Specific Conductivity Conductivity is an important parameter to determine the quality of water. The specific conductivity of ten ponds ranged from 93-247 umhos/cm.The maximum conductivity was recorded during summer season while minimum during winter season. Bhatt et al. (1999) observed the highest conductivity values in the month of May and lowest in the month of December from Taudaha

lake. The specific conductivity of a freshwater pond should be in the range of 24-600 umhos/cm for optimum fish production and if less than 100 umhos/ cm the pond might be poorly productive. Biological Oxygen Demand The BOD of ten ponds ranged from 0.67.2 mg/l. The normal level of Biological oxygen demand is 1.4-2.4 ppm. BOD is an indicator of organic pollution. BODS were more or less low in all the ten ponds of Lumding, which indicates low level of organic pollution of pond water. Plankton composition was studied as the productivity of pond depends on plankton community. Plankton community is a heterogenous group of tiny plants (phytoplankton) and animals (zooplanktons) adapted to suspension in the sea and freshwater.

Phytoplankton and Zooplankton The phytoplanktons of Assam beels were found very low except few beels. This was due to heavy growth of macrophytes, whereas availability of phytoplankton’s in the West Bengal beels ranged from 396-14987UL -1 (Sugunan, 2000). Quality composition of phytoplankton’s also varied in the beels of Assam and West Bengal. It varied from beel to beel and no definite pattern was followed. The phytoplankton’s comprises major portion in the pond. The basic process of phytoplankton production was dependent upon temperature, turbidity and nutrients as reported by Sreenivasan et al.(1979) and Sukumaran and Das(2002).The phytoplankton belonging to division Chlorophycae and Cyanophycae are predominant over the others. During the study period, a total of 1195 genera were observed among them 573 were phytoplankton and remaining 622 were Zooplankton. The phytoplankton’s present in different divisions were chlorophyeae (515), cyanoplyeae (262) and Euglenophycae(36). A total of 622 Zooplankton were observed among them Rotifers (26), protozoans (143), copepoda (173) and cladocera (280). CONCLUSION Quality of an ecosystem depends on the physico-chemical characteristics and biological

GUPTA & DEY, Curr. World Environ., Vol. 8(1), 107-115 (2013) diversity of the system(Tiwari and Chauhan,2006). Table 1 depicts the chemical variables of the water of ten ponds selected forstudy. The study clearly showed that the productivity of the ponds varied significantly depending upon the climatic conditions and their hydro biological and soil qualities. Pond No. 10 having high transparency, poor alkalinity was least productive whereas Pond No 5 having normal pH, Alkalinity having favourable physicochemical conditions was highly productive. The physico-chemical characteristics of ten ponds are given below in Table1. Variations in percentage occurance of major phytoplankton taxa in ponds 1 to 10 are shown in Fig 1. Major taxa present are Chlorophyceae, Cyanophyceae and Euglenophyceae. Among the three groups Chlorophyceae is present in all ponds. Euglenophyceae is totally absent in Pond 8. Cyanophyceae is present in Pond 5 and 6 in very low percentage.Planktonic algae are particularly sensitive to chemicalchanges and myriad environmental conditions promote the development of the algal spores present in the sediment (Rodhe,1948). Chlorophyceae and Cyanophyceae are the most common group of phytoplankton in the ponds studied. Variations in percentage occurance of major zooplankton taxa in ponds 1 to 10 are shown in Fig 2. Major taxa are Rotifers, Protozoa,

113

Copepoda and Cladocera. Among the four groups Protozoa, Copepoda and Cladocera are present in all ponds. Rotifers are present in nine pone ponds but totally absent in pond 8. Protozoa is the most common group of zooplanktonin the ponds studied but in pond 4, 5, 7, 8, 9, and 10 in low percentage whereas Cladocera are present in highest number than others. The highest phytoplankton abundance was found in August. The highest abundance of Zooplankton was recorded in July and lowest value was recorded in November. The details of pond ecosystem in Lumding of Nagaon district, Assam has not been studied earlier and perfect accounts of physico-chemical and biological aspects are not available and no such type of studies on fish culture in relation to water quality have been carried out here. Therefore, the present studies have been conducted, focusing monitoring of water quality and fish food organism of some semi-intensive fish culture ponds. The present findings indicate that water quality of all the ten ponds have good potential for fishery practice. The small rural ponds can be a very good source of income from fishery which can be augmented with scientific management as small ponds are more manageable and high yielding than larger ones. Hence it is necessary to protect and conserve these small water bodies. This demands immediate action from fishery biologists, planners and policy makers.

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Delhi (1992). Bellinger, E.G., A key to common Algae. The institute of water and environmental management, London (1992). Bhatnagar, A. and Garg, S.K., Causative factors of fish mortality in still water fish ponds under sub tropical conditions. Aquaculture, 1(2): 91-96 (2000). Bhatnagar, A., Productivity and fish biodiversity of selected ponds of Haryana. Project report submitted to Department of Fisheries, Government of Haryana (2008). Bhatt, I.R., Lacoul, P., Lekhale, H.D., and Jha, P.K., Physico-chemical characteristics of

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Current World Environment

Vol. 8(1), 117-121 (2013)

Physico Chemical Assesment of Groundwater in Indore City MONIKA GURJAR1, VIJAY R. CHOUREY1*, DHANANJAY DWIVEDI2 and ROOPLEKHA VYAS1 1

Department of Chemistry, Govt. Holkar Science College,Indore - 452 012, India. 2 PMB Gujarati Science College, Indore, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.13 (Received: March 13, 2013; Accepted: March 28, 2013) ABSTRACT

The present work deals with the assessment of the ground water of some selected area of the Indore city. The investigation was carried out in the month of March and April-2012. The sites were selected to cover the Indore city including residential, commercial, industrial and agriculture area. Various parameters were studied andcompared with the IS specification. Some parameters have been foundundesirable in some location, mainly KabirKhedi and Pologround area which need proper attention. Rest of the sample area has deviation within desirable and undesirable extent of tolerance.

Key words: Physico-chemical parameters, Contamination, Renewable. INTRODUCTION Groundwater is one of earthâ&#x20AC;&#x2122;s most vital renewable and widely distributed resources as well as an important source of water supply, throughout the world. In India, most of the population depends on the groundwater as it is the only source of drinking water supply1. The groundwater is believed to be comparatively much clean and free from pollution than surface water. It can become contaminated naturally or because of numerous types of human activities. Residential, municipal, commercial, industrial, and agricultural activities can all affect groundwater quality2. Groundwater can be optimally used and sustained only when the quantity and quality is properly assessed3. A large volume of chemical data on ground water from different parts of country has been generated from the point of view of its suitability for drinking purpose4-5.

flow through the city. The city is becoming centre in many aspects, such as commercial, industrial, educational etc. Ground water is being polluted due today to day the increase in the garbage, industrial waste and drainage linkages6-8. The present study is related with the assessment of the quality of the ground water of some selected area of the Indore city. Itis necessary to evaluate to quality of ground from the health point of view. It should be safe in this respect. The investigations were performed on the sample collected in the month of March and April 2012.All the studies sites have been selected to cover the Indore city. The parameters studied are colour, odour, temperature, turbidity, conductivity, pH, alkalinity, total hardness, calcium hardness, magnesium hardness, TDS, chloride, iron, fluoride, nitrate, phosphate, and sulphate. MATERIAL AND METHODS

Indore is the largest city in Madhya Pradesh State. It is situated on the Malwaplateau. Two small rivulets the Saraswati and the Khan are

All the chemical and reagent used were of GR or Analar grade. Stock solutions were

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prepared in conductivity water. Water sample were collected in cleanJrrican bottles from different selected points. The sample collection area has been assigned as sample point S. It isfrom S1 to S10. pH, Conductivity and spectrosphotometer measurement have been carried out on Systronicmake instruments. Other parameters have been evaluated volumetrically. RESULT AND DISCUSSION An attempt has been made to correlate the parameters of sample collected from different area of Indore city. Studied parameters have been summarized in the table. The results of different area have also been individually discussed. The values obtained are compared[9],[10] with the desirable and permissible limit as issue by Government of India i.e. IS 10500-1991. Sample 1, (S1)- from Vijay Nagar Vijay Nagar is a commercial as well as residential area. One nalah flows nearby the area. Sample is slightly acidic as pH is 6.18. Colour (3 Hazen unit) shows that, there is metal ions with iron (0.7 mg/L). Other metal ions and organic compound are present, as TDS is above desirable limit. Alkalinity is above desirable limit (310mg/L) and calcium hardness is very low (40mg/L). Consumptio of water for long time may cause fluorosis. Fluorosis is prevalent in areas where ground water is high in alkalinity and low in Calcium. The fluoride is just ready to cross desirable limit (0.49mg/L). Total hardness is lowest among the samples studied. Sample 2, (S2)- from KabitKhedi KabitKhediis mixed type of industrial cluster having foundries and chemical industries. It has agriculture land and trenching plant is also there onenalah flows nearby the area. Color of sample (3 Hazen unit)confirms the high concentration of nitrate (57.0mg/L), iron (2.7mg/L). TDS (organic and inorganic components) (829 mg/ L) and Alkalinity (440mg/L) is also high. Fluoride (0.52 mg/L) just has crossed the desirable limit.This very low calcium hardness may cause osteoporosis and fluorosis. Magnesium hardness is high

(permissible) and sulphate is low. It is not harmful. High concentration of nitrates (57.0mg/L) is to be found, as fertilizers are used by farmers. Industrial effluents, animal excreta and microbes in soil are also responsible for its toxic pH (6.5), again confirms the high concentration of iron (0.74 mg/L). Turbidity is high among the sample studied (1.1NTU). This is responsible for the development of â&#x20AC;&#x153;iron bacteriaâ&#x20AC;?, that is cause of unacceptable odour, corrosion of supply pipes etc.Observation suggested that water is not foundand suitable for drinking as well as domestic use. Taste is not acceptable as TDS, Magnesium, iron, nitrates are higher. Sample 3, (S3)-from MotiTabela It is residential area. Observation of data shows that sample is slightly alkaline having pH (7.28). At this pH iron is 0.74mg/L i.e.it is more in ground water hence iron(III) hydroxide may cause the formation of iron bacteria. Turbidity (1.3NTU), Colour (2 Hazen unit) is due to the iron. Again alkalinity (330mg/L) and Fluoride (0.38mg/L) are acceptable but calcium hardness is low (below desirable limit), it may cause osteoporosis. Sample 4, (S4)- from Pologround Pologroundis a small industrial area situated in the mid of the city, having maximum units of industries including, fabrication, anodizing foundry, textile, soyabin oil factory and some drug units. Result show that sample is a slightly acidic with pH (6.96). Soluble iron (1.01mg/L) and high nitrate (toxic) (109mg/L) reveal the (4 Hazen unit) colour of the sample. Nitrate concentration is due to industrial effluents. Alkalinity is higher (500mg/ L) and calcium (64mg/L) is below desirable, with acceptable fluoride (0.57mg/L). It may be a cause for osteoporosis and fluorsis. Conductivity (3000ÂľS) and alkalinity are (500mg/L) highest among the sample. Water is not potable as the total hardness (460mg/L) and magnesium (72mg/L), all this have high values. Taste is also not acceptable due to high concentration of chloride, TDS, alkalinity and nitrates Sample 5, (S5)-0 from Gandhi Nagar Gandhi Nagar is also residential area. All the parameters have been fund within either

Commercial &

Parameters

Colour(Hazen unit) Temperature(Â°C) Turbidity (NTU) pH Conductivity(Âľs) Alkalinity (mg/L) Total Hardness (mg/L) Calcium Hardness(mg/L) Magnesium Hardness(mg/L) T.D.S.(mg/L) Chloride (mg/L) Iron (mg/L) Fluoride(mg/L) Nitrate (mg/L) Phosphate (mg/L) Sulphate (mg/L)

Sample Collection Type of are

S.No.

01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16

3 31.3 1 6.81 1170 310 240 40 33.6 680 110 0.74 0.49 5.7 0.23 5

Vijay Nagar Agricul. Indust. S1 3 31 1.1 6.5 1644 440 400 24 81.6 829 100 2.7 0.52 57 0.68 17

Kabit Khedi Resid. Indust. S2 2 32 1.3 7.28 919 330 260 32 43.2 459 120 0.74 0.38 3.9 0.77 7

Moti Tabela Resid. Indust. S3 4 30.7 0.9 6.96 3000 500 460 64 72 1005 150 1.01 0.57 109 0.9 10.5

Polo ground Resid. Indust. S4 0 31 0.08 6.97 1378 450 380 96 33.6 687 190 0.32 0.95 2.7 0.04 19

Gandhi Nagar Resid. Indust. S5 0 33 0.9 7.06 605 280 260 48 43.2 305 60 0.47 0.23 5.65 0.33 5

Sudama Nagar Resid. Indust. S6 0 31.7 0.9 7.11 866 320 280 6 24 432 90 0.14 0.76 3.8 0.33 17

Bangali Square Resid. Indust. S7

Table 1: Sample collection point and values of studied parameters.

0 31.9 0.07 7.32 972 340 340 72 38.4 487 120 0.2 0.52 10 0.24 18

0 32.3 0.8 7.99 1055 330 320 48 48 526 130 0.04 0.92 11.4 0.06 16

0 30.6 0.06 7.04 900 340 320 56 43.2 405 120 0.27 0.6 10.1 0.68 12

Rajendra YashwantPipliapala Nagar Club Resid. Resid. Indust. Indust. Indust. S8 S9 S10

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desirable of permissible limits. pH is 6.97.Iron (03mg/L) and nitrates (2.7mg.L) are lowest among the sample studied. It reveals zero Hazen units of colour. Value of calcium is96mg/L and fluoride is0.95mg/L. Nitrates, phosphate,sulphate are less soluble, it reduces the conductance but due to chloride (190mg/L) it increases to average that make water suitable for drinking. Sample 6, (S6)- from Sudama Nagar Sudama Nagar is also a residential area. pH (7.06) is almost neutral. TDS (305mg/L), alkalinity (280mg/L), chloride (60mg/L), fluoride (0.23mg/L) are the lowest values among studies samples. Low chloride reveals lowest value of conductance (605µS). It matsalso cause of the bacterial or viral infection. Though it is suitable for drinking. Sample 7,(S7)- from Bangali Square Bengali Square is residential as well as commercial area. Slightly alkalie pH (7.11), low TDS (432mg/L), iron (0.14mg/L), nitrate (3.8mg/ L),chloride (90mg/L) reveal zero Hazen unit of colour. Taste is acceptable. Calcium (64mg/L) and magnesium (24mg/L) are below then desirable. Alkalinity (320mg/L) and fluoride (0.76mg/L)are within permissible shows the possibility of fluorosis after long time use. Taste is acceptable and water is suitable for drinking. Sample 8, (S8)- from Rajendra Nagar Rajendra Nagar is residential area situated near the railway station. Sample is slightly alkaline. All the parpameter deviates slightly from standard value except chloride (120mg/L). Taste of water is acceptable and is suitable for drinking. Sample 9, (S9) – from Yashwant Club Yashwant club is residential area. Almost sample is alkaline, pH is (7.99). All parameters are near about the desirable limits except pH (7.99). Fluoride is within (0.92mg/L) permissible limit while calcium (48gm/L) and chloride (130mg/L) are below the desirable range. Colour and taste are acceptable.

Sample 10, (S10)- from Piplya Pala Pipliyapala is a residential area. pH is Neutral (7.04).TDS (405mg/L), calcium (56mg/L), chloride (120mg/L) are below their desirable limit, Remaining are with permissible limit. Calcium deficiency is possible after long time consumption. Chloride in all the studiedsamples is to be found below desirable range. Sulphate and turbidity are very low in all the sample. Temperature parameter give an idea about the self purification of water body. Its variation is negligible. Conductivity of sample is accordance to pH. It also depends on the solubility of inorganic salts and hardness etc. CONCLUSION The assessment of ground water by physical and chemical analysis could help in understanding the extent of ground water pollution by surrounding human activities.The result and discussion exhibits that some parameters are undesirable mainly to nitrates, chlorides, calcium, magnesium, hardness and alkalinity. It has been concluded that Kabit-Khedi and Pologround area need proper attention hence regular periodical checking is required. The rest of the samples areas have deviation within desirable and undesirable to the extent of tolerance. The findings of the work exhibits that the few parameters have values that is undesirable as nitrates, chlorides, hardness, turbidity, conductance, alkalinity, in the sample sources studied as reported in the summary of the work. ACKNOWLEDGEMENTS One of the author (MG) in thankful to Head of the Institute and also the Head of the Department for providing research facilities.

REFERENCES 1.

Mahmood A., Kundu., “Stattus of water supply, sanitation and solid waste

management in urban areas” New Delhi, National Institute of Urban Affairs (NIUA)

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(2005). Jalali, Kim et al; “ A review of methods for assessing aquifer sensitivity and ground water vulnerability to pesticide contamination” US, EPS, EPA/813/R-93/002; U.S. EPA (1993) Rao K.S.and Rao G.S., “GIS based ground water assessment model, GIS @ development” Nov-Dec.-(1999). Garg N.K. and Hassan Q., Alarming Scarcity of water in India., J. Current Sci., 98:932-941, (2007). Staflard D.B., “Civil engineering application of remote sensing and geographic information systems” New York. A(1991). DhananjayDwivedi and Vijay R. Chourey; Adsorption studies of toxic metals from waste water. J. Current World Environment.,

10.

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vol.4(1), 179-182,2009. DhannajayDwivediand Vijay R. Chourey; Physico-Chemical characterization of water body; J. Current World Environment., vol. 07(1), 125-131,2012. DhananjayDwivedi, KirtiYadav and Vijay R. Chourey: Applicability of organic polymer for pretreatment of waste water.J. Current World Environment., vol. 07(2), 305-308,2012 World Health Organization, WHO guidelines for drinking water, 3rd edition [online; web] Accessed on 5 th Jan 2009 URL http;// www.who.int/water_sanitation_health/dwg/ gdwg 3 rev/en. (2008). Government of India., Drinking water specifications IS-10500, Bureau of India Standards, New Delhi, (1991).

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Biodiversity of Rhizospheric Soil Bacteria and ArbuscularMycorrhizal (AM) Fungi in Some of the Wild Medicinal Legumes of Barak Valley F. MALINA SINGHA1* and G. D. SHARMA2 1

Department of Life Science and Bioinformatics, Assam University, Silchar - 788 011, India. 2 Vice Chancellor BilaspurVishwavidyalaya, Vil. SendriRatanpur Rd. Bilaspur Dist. Bilaspur, Chattisgarh - 495 009, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.14 (Received: March 09, 2013; Accepted: March 21, 2013) ABSTRACT Present investigation was aimed to isolate and study the rhizobacteria and AM fungi from rhizosphere of wild legumes: Mimosa pudica(sensitive plant), Crotolariapallida (Sunhemp), Cassiatora(Sickle pod) andDesmodium.The molecular characterization of four bacterial isolates were done. Four bacterial speciesBacillus megaterium, Bacillusaerophilus, Microbacterium laevaniformans and Staphylococcus xylosuswere isolated from strains M1, RT,D5 and D7 respectively.Also,the distribution of AM fungi population was studied from rhizosphere soils of these legumes.Among the AM fungi,Glomusspecies was dominant and bacterial genus Bacilluswas found to be dominant.Maximum number of VAM infection was found in the rhizosphere soil of Mimosa pudicaof Srikona.

Key words: ArbuscularMycorrhizal Fungi, Glomus, Spore population, Diversity. INTRODUCTION Leguminous plants are abundant in Barak Valley , where they grow in barren soils and drysites that are unsuited for most crops.Medicinal plants are the rich heritage of country serving the age old medicinal system i.e.Ayurveda.Despite being so important these plants have been totally neglected as far as biofertilizers are concerned. For their utilization,medicinal plants are indiscriminately taken from wild habitats causing their depletion andextinction.Pertaining to the negligence toward the rhizobialandVAM biodiversity,we took the initiative to characterize the microbial diversity associated with the medicinal legumes.Rhizobia are of particular interest due to their symbiotic nitrogen fixing ability with members of Leguminosaewhich is the second largestfamily of flowering plants and includes more important drugs than any other family. Rhizobia are genetically diverse and physiologically heterogeneous group

of symbiotic nitrogen fixing bacteria that form nodules on the roots or rarely on the stem of legume hosts, within which thebacteria fix atmospheric nitrogen into ammonia.Leguminous plants are said to behighly specific to nodulatingorganisms1 . (SubbaRao,1999). The root nodule formation and fixationof nitrogen from the atmosphere in the rootsof leguminous plants occur only if the specificcrossreacting species of Rhizobia is present inthe soil. The productionof specific flavonoidsby the plants may also attract specificRhizobium strains and facilitate their entry intothe host plant and nodule formation 2 . (SubbaRao,1993). Arbuscularmy corrhizae (AMs) are characterized by the formation of uniquestructures such asarbuscules andvesicles by fungi of the phylumGlomeromycota (AM fungi). Oftheseven typesof mycorrhizae described in currentscientific literature (arbuscular, ecto, ectendo,arbutoid, monotropoid, ericoid and orchidaceousmycorrhizae), the arbuscularand ectomycorrhizaeare the most abundant and widespread 3 . (SiddiquiandPichtel,2008). The

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Vesicular ArbuscularMycorrhiza(VAM) fungi, grouped in the phylumGlomeromycota,are the commonestmycorrhizal type involved in agricultural systems4.(Bethlenfalvay, 1992).AM fungi (AMF) help plants to capturenutrientssuch as phosphorus and micronutrients from the soil. It is believed that the development ofthe arbuscular mycorrhizalsymbiosis played a crucial role in the initial colonisation of landby plants andin the evolution of the vascular plants. Our present investigation was aimed to isolate and study therhizobacteria and AM fungi from rhizosphereof wild legumes : Mimosapudica (sensitive plant), Crotolariapallida (Sunhemp),Cassia tora(Sickle pod) and Desmodium. collected from Assam university, Rongpur,Irongmara andDoluof Barak Valley. Also,the distribution of AM fungi population was studied fromrhizospheresoils of these legumes.Among theAM fungi,Glomusspecies was dominant. MATERIALS AND METHODS Experimental sites Four regions of Barak Valley(Assam University, Rongpur, Irongmara and Dolu) were selected. The vegetation in the valley is mostly Tropical evergreenand there are large tracts of Rain forests in the northern and southern – eastern parts of the valley. Collection of root nodules Root nodules offour commonly growing wild legumes Mimosa pudica (sensitive plant), Crotolariapallida (Sunhemp),Cassiatora (Sickle pod) and Desmodium were collected and transported to the laboratory in plastic bags along with seedlings.

Isolation of rhizobia Nodules were separated from the roots and washed in sterilized distilled water for several times. Following serial dilution agar plate techniquebacterial isolation was carried out5,6.After that these plates were incubated at 28±1ºC and observed daily. Bacterial colonies appeared after 2-3 days were picked up and streaked on YEMA plates. Pure cultures were obtained with one or more further sub – culturing steps. Isolation ofVAM andestimatonof AM fungal colonization and AM fungal spores Staining of mycorrhizal roots were done7.VAM isolation was done using wet sieving and decantation method8. RESULTS Agood number of isolates wereobtained from root nodules of Mimosa pudica (sensitive plant), Crotalaria pallida Sunhemp), Cassia tora(Sickle pod) and Desmodium.Out of the total 20 isolates,only four isolates(M1,RT1,D5and D7)were subjected to molecular characterization test.The isolates were round in shape,gummy white colour,smooth margin and superficial in position.Four bacterial species Bacillus megaterium, Bacillus aerophilus, Microbacterium laevaniformans and Staphylococcus xylosus were isolated from strains M1,RT1,D5 and D7 respectively as shown below: Further studies on vesiculararbuscular fungal spore population were studied.A total of 17 fungal taxa were isolated from the collected soil samples.The isolated spores belonged to the genus Gigaspora,Ambispora , Acaulospora and

Table 1: Assam bacteria: 16SrRNA gene – based identification Strain number M1 RT1 D5 D7

Taxonomy

Gene homology(%)

Bacillus megaterium Bacillus aerophilus Microbacteriumlaevaniformans Staphylococcus xylosus

96 93 96 98

16S rRNA(bp) 1471 1000 1470 132

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Table 2: The abundance of spore population at three sites of Barak Valley AM fungi

Rongpur

Irongmara

Dorgakuna

Total of three sites

Aug Sept Oct Nov Aug Sept Oct Nov Aug Sept Oct Nov Aug Sept OctNov Gigaspora Ambispora Acaulospora Glomus Total AM spore population

2 1 0 6

4 3 012 9

11 3

12 4

5 2 0 5

7 2 0 7

911 689 3 4 0 0 9 11

13 0 00 3

1 0 4

2 0 7

13 1929 36 2 3 6 8 10 0 0 12 9 14 20 27 32 30 + 45 + 65 + 80 =220

Table 3: Percentage of mycorrhiza infection in Mimosa pudica at different sites of Cachar district Site

Total no. of root segments

No. of segments infected

Percentage infection

11 15 12 11

09 12 08 04

81.8% 80% 66.6% 36.36%

Rongpur University campus Dorgakona Dolu

Glomus.The number of Glomusspecies were found to be dominantamong all.The following table shows the spore density from some wild legumerhizosphere soil. DISCUSSION The results of present investigation indicated that root nodules of leguminous plants are the habitat of many species of bacteria like Bacillus megaterium, Bacillus aerophilus, Microbacterium laevaniformans and Staphylococcus xylosus.The abundance of root nodules were also studied in the selected plant species.Nodules were highest inMimosa pudica , Crotolariapallid and Desmodium while totally

absent in Cassia tora.The absence of nodulation may be due tothe absence of specific no dulating Rhizobiumstrain in therhizospheresoil (Sundar et al).Also, the rhizosphere soils are the habitat of many AM fungal taxa like Gigaspora,Ambispora, AcaulosporaandGlomus .The genus Glomus was found to be the most dominant,second dominant genus wasGigasporafollowed by Ambisporaand Acaulospora.Further,the number of spores were less in number during Augustand September and gradually increased towards November. Percentage of mycorrhizal infection was studied at five different sites of Cachar district. The percentage of infection was highest in Srikonaand lowest in Dolu area. The variation of percentage infection may be due to the soil characteristics.

REFERENCES 1.

SubbaRao, N.S.,Soil Microbiology . Fourth edition . Oxford and IBH Publishing Co. Pvt. Ltd ., New Delhi , India (1999). SubbaRao , N. S. Interaction of nodulated tree species with other microorganisms and plants . In : Symbiosis in Nitrogen Fixing Trees (Eds.) N. S. SubbaRao and C . Rodriguez-Barrueco, Oxford and IBH

Publishing Co ., New Delhi . pp .250 (1993). Siddiqui , Z.A. and Pitchel J,Mycorrhizae : an overview ; In : Z.A. Siddiqui , M.S. Akhtar , K. Futai (Eds) . pp . 1-35.Mycorrhizae : Sustainable Sgriculture and forestry . Springer (2008). Bethlenfalvay, G.J. Mycorrhizae in the agricultural plant-soil system. Symbiosis

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SINGHA & SHARMA, Curr. World Environ., Vol. 8(1), 123-126 (2013) 14:413-425 (1992). Somasegaran P. and Hoben H.J., Collecting nodules and Isolating Rhizobia . In : Handbook of rhizobia : methods in Legume-Rhizobium Technology . Springer , New York . p.13 (1994). Vincent J.M.,A manual for practical study of root nodule bacteria. Blackwell ScientificPublishers , Oxford , p. 164 (1970). Philips, J.M .& Hayman, D.S. Improved

procedure for clearing roots and staining parasitic and vesicular-arbuscularmy corrhizal fungi for rapid assessment of infection. Transactions of the British Mycological Society, 55,158(1970). Gerdemann, J.W.,and Nicolson,T.H. Spores of arbuscularmycorrhizalEndogone extracted from soil by wet sieving and decanting. Trans.Br.Mycol. SOC., 46: 235-244 (1963).

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The Seasonal Variation in Ionic Composition of Pond Water of Lumding, Assam, India TAPASHI GUPTA and MRINAL PAUL Department of Zoology, Lumding College, Lumding, Assam - 782 447, India. Department of Chemistry, Lumding College, Lumding, Assam - 782 447, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.12 (Received: December 08, 2012; Accepted: December 26, 2012) ABSTRACT Ionic composition of water is an important parameter to determine the quality of water. The seasonal variations in TDS and conductivity are mainly due to the ionic composition of water. In the present study, the seasonal variations in TDS and conductivity of freshwater pond of Lumding were studied during the year 2010-2011. A positive correlation between TDS and conductivity was observed.

Key words: Conductivity, TDS, Lumding pond.

INTRODUCTION The term ionic composition means conductivity of water.Conductivity is a measure of the ability of water to pass an electrical current. Conductivity in water is affected by the presence of inorganic dissolved solids such as chloride, nitrate, sulfate, and phosphate anions (ions that carry a negative charge) or sodium, magnesium, calcium, iron, and aluminum cations (ions that carry a positive charge). Organic compounds like oil, phenol, alcohol, and sugar do not conduct electrical current very well and therefore have a low conductivity when in water. Conductivity is also affected by temperature: the warmer the water, the higher the conductivity. For this reason, conductivity is reported as conductivity at 25 degrees Celsius (25 C). Conductivity measurement is useful in estimation of the inorganic constituents in water. Dutta et al.(1988)have viewed that the levels of specific conductance depends on the inputs of large amount sa;lts and salts carried by cannals from the adjacent agricultural sites. It indicates the presence of dissolved nutrients in water. Electrical conductivity can be used as an index of TDS

(Sreenivasan, 1964). After the removal of suspended solids, the material left in water is considered to be dissolved solid, which is in the formof solid residue after evaporation of water. TDS may consists of different kinds of nutrients and minerals. The present study deals with the study of seasonal variations in the conductivityand TDS of freshwater pond at Lumding. Conductivity measures the capacity of a substance or solution to conduct electrical current. The electrical conductivity was found to fluctuate between108.00 µS/cm (November, 2011) and 246.30 µS/cm (May, 2011) in this pond and that falls within the range observed for Indian waters. Olsen (1950) classified the name for water bodies having conductivity values greater than 500.00 µS/ cm as eutrophic. MATERIAL AND METHODS The study was conducted during May 2011to November 2011. Water samples were collected from five locations randomly. The conductivity was measured by using standard conductometer and TDS was

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determined by procedure given by APHA, (1995) and Trivedy & Goel(1984). RESULS AND DISCUSSION The monthly values of conductivity and TDS are given in table1 Specific Conductance is a measure of how well water can pass an electrical current. It is an indirect measure of the presence of inorganic dissolved solids, such as chloride, nitrate, sulfate, phosphate, sodium, magnesium, calcium, and iron. These substances conduct electricity because they are negatively or positively charged

when dissolved in water. The concentration of dissolved solids, or the conductivity, is affected by the bedrock and soil in the watershed. It is also affected by human influences. For example, agricultural runoff can raise conductivity because of the presence of phosphate and nitrate. Conductivity in streams and rivers is affected primarily by the geology of the area through which the water flows. Streams that run through areas with granite bedrock tend to have lower conductivity because granite is composed of more inert materials that do not ionize (dissolve into ionic

Table 1: Monthly values of TDS of five ponds of Lumding (mg/l) Months

Pond 1

Pond 2

Pond 3

Pond 4

Pond 5

April -11 May-11 June-11 July-11 Aug-11 Sept-11 Oct-11 Nov-11 Dec-11 Jan-11 Feb-11 Mar-11 Stdev-

120 180 200 287 250 200 195 35 30 40 50 85 ±86.7

90 150 200 600 550 500 245 40 35 40 45 80 ±205.0

125 180 200 260 250 150 100 90 80 90 100 120 ±60.47

126 185 250 553 500 200 100 100 90 90 100 120 ±153.68

126 180 300 460 466 250 180 120 110 100 100 126 ±127.8

Table 2: Monthly values of Conductivity of five ponds of Lumding (µmhos/cm) Months

Pond 1

Pond 2

Pond 3

Pond 4

Pond 5

April-11 May-11 June-11 July-11 Aug-11 Sept-11 Oct-11 Nov-11 Dec-11 Jan-11 Feb-11 Mar-11 Stdev-

110 110 120 123 100 105 110 90 100 105 105 110 ±8.84

120 125 130 140 143 110 105 100 100 110 110 120 ±14.5

50 60 80 93 80 70 60 25 26 30 35 40 ±23.3

125 130 135 140 143 120 110 105 100 100 110 120 ±15.8

200 220 240 247 230 220 200 150 170 180 190 190 ±29.2

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Conductivity TDS

Fig. 1. Conductivity vs TDS of pond 1

Conductivity TDS

Fig. 2. Conductivity vs TDS of pond 2

Conductivity TDS

Fig. 3. Conductivity vs TDS of pond 3

Conductivity TDS

Fig. 4. Conductivity vs TDS of pond 4

130

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Conductivity TDS

Fig. 5. Conductivity vs TDS of pond 5

components) when washed into the water. On the other hand, streams that run through areas with clay soils tend to have higher conductivity because of the presence of materials that ionize when washed into the water. Ground water inflows can have the same effects depending on the bedrock they flow through. Indirect effects of excess dissolved solids are primarily the elimination of desirable food plants and habitat-forming plant species. Agricultural uses of water for livestock watering are limited by excessive dissolved solids and high dissolved solids can be a problem in water used for irrigation. The monthly values of conductivity and TDS are given in table 1. The conductivity were found to be in the range between 100-123µmhos/ cm at pond 1, 100-143µmhos/cm at pond 2, 21-93 µmhos/cm at pond 3, 100-247 µmhos/cm at pond 4 and 100-143 µmhos/cm at pond 5. The maximum conductivity was recorded during the summer season while minimum during winter season. Bhatt et al. (1999) observed the highest conductivity

values in the month of May and lowest in the month of December from Taudaha lake. The increase in the value of conductivity during summer may be due to low water level input of large amount of salts from the adjacent agricultural fields ( Sharma and Rathore, 2000). The TDS Values were ranged between 35 to 195mg/l at pond 1, 40 to 245 mg/l at pond 2, 90 to 260mg/l at pond 3, 90 to 553mg/l at pond 4 and 100 to 466mg/l at pond 5. The maximum values of TDS occurred during summer and monsoon months while minimum during winter months. Qumerunsisa(1985) found the maximum TDSduring summer season and minimum during monsoon months. Sakhare and Joshi (2003) also found the higher value of TDS during summer months. During study a positive correlation was observed between TDS and conductivity. TDS showed a positive alliance with electrical conductivity (Wiiliams, 1966; Khan and Khan, 1985 and Kumar & Paul, 1990).

REFERENCES 1.

APHA, Standard Methods for Analysis of Water and Wastewater. American Public Health Association, Washington D.C., pp.21193 (1989). Bhatt, I.R., Lacoul, P., Lekhale, H.D. and Jha, P.K., Physico-chemical characteristics and Phytoplanktons of Taudaha lake, Kathmande. Poll. Res. 18(4): 353-358 (1999).

Khan, I.A. and Khan, A.A., Physicochemical conditions in Seikha Jheelat Aligarh, Environment and Ecology. 3(2): 269-274 (1985). Qumerunnisa, Ecology of freshwater ciliates. Ph.D. thesis, Marathwada University, Aurangabad (1985). Sakhare, V.B. and Joshi, P.K., Physico-

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chemical limnology of Panas: A minor wetland in Tuljapur Town, Maharashtra, J. Aqua. Biol. 18(2): 93-95 (2003). Sharma, R.K. and Rathore, Vinita, Pollution ecology with reference to commercially important fisheries prospect in rural based water body: The lake Sarsal Nawar, Etawah in U.P.(India). Poll. Res. 19(4): 641-644 (2000). Sreenivasan,A., Hyderobiological studies of a tropical impoundment, Phavanisagar

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Reservoir, Madras State, India, year 195661. Hydrobiologia. 24(4):514-539 (1964). Trivedy, R.K. and Goel, P.K., Chemical and Biological methods for water pollution studies, environmental publications, Karad (India) 248pp (1984). Williams,W.D.,Conductivity and the concentration of total dissolved solids in Australian lakes. Aust. J. Mar. Freshwater Res. 17: 169-176 (1966).

Current World Environment

Vol. 8(1), 133-141 (2013)

Seasonal Variation of Zooplankton Population with Reference to Water Quality of Iril River in Imphal THANKHUM SARON and L. BIJEN MEITEI* Research Scholar, CMJ University, LaitumkhrahShillong, Meghalaya -793 003 Directorate of Environment, Porompat, Imphal East-795 005, Manipur. DOI : http://dx.doi.org/10.12944/CWE.8.1.16 (Received: March 20, 2013; Accepted: April 12, 2013) ABSTRACT The zooplankton population of Iril river of Imphal valley of Manipur was investigated with reference to water quality. The fish biodiversity potential of the river remain intake despite the suburban exposure of the river. Since plankton play a great food chain role for fish community, knowing the population of zooplankton as secondary resource is needed. Deterioration of water quality in urban area remain, in most cases, a basic feature. The present investigation endeavour to establish the influence, if any, of water quality of a river in sub-urban settings to the zooplankton population. Five sites were selected stretching from upstream before the river enter the urban area to the downstream as the river exit the urban area. Since the river is in suburb and for some special physical features the Irilriver maintain a significant volume and there seems to be dilution effect and pollution of the river remain a lesser concern. Nevertheless, the study establishespossible influences of the change in water quality to plankton population.

Key words:Anthropogenic, aquatic, biodiversity, ecological, ecosystem, ichthyo-fauna, physico-chemical, pollution, population,productivity, zooplankton.

INTRODUCTION The potential of rivers as good habitats for ichthyo-fauna seems degraded with onslaught of anthropogenic interference impairing the quality and quantity of river water.The Manipur Central Valley districts are endowed with many wetlands which are often connected with rivers and as such the rivers pose important source of fish resources. The recent changes in water quality impair the potential of the rivers to a significant degree. The Iril river, which is very important for water supply of the Imphal city also cater for the protein food need of the people around with its fish resources.Moreover ecologically the ichthyo-faunalbiodiversity of the river is significant.While most of the other rivers in the Imphal city have lost such inevitable characteristics, the Irilriver still maintain a part of its pristinefeatures.However the onslaught of urban exposures impacts the river and the biotic

components.The study on zooplankton population with reference to water quality was carried out.The results may reveal an in-depth inference for better conservation of the river while it is not too late.The river is connected with five very important major wetlands in the valley indirectly and knowledge of its ecological health is a good approach towardsholistic means for overall aquatic ecosystem health in the beautiful valley of Manipur. Discharge of waste and surface run off causes deleterious effect in floraand fauna and other aquatic organisms(Sahet al.,2000).Water qualities of rivers have beendeteriorated due to disposal of garbage, religious offerings, sewage, recreationaland constructionalactivities inthe catchment areas(Singhet al.,2012).The problem of anthropogenic environmental distortion continuously affects rivers (NanditaChakrabortyet al.,1995).

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There is indication that the headwaters to mouth, the physical features vary significantly within a lotic water system and present a continuous gradient of physical variations, which evolves association within biota and other a-biotic features (Pathani and Upadhyay, 2006). Thus the biota of an aquatic ecosystem directly reflects the conditions existing in the environment(Bhattet al., 1984). Monitoring of zooplankton communities is needed to allow us to predictively model the ecosystem (Deborah and Robert, 2009). The zooplankton are known not only to form an integral part of the lotic community but also contribute significantly to the biological productivity of the fresh water ecosystem (Makarewicz & Likens, 1979). Zooplankton populations can expand in rivers by growth of the suspended organisms (Talling & Rzoska,1967) or by the hatchingof resting eggs in river sediments(Moghraby,1977). However zooplanktons are being transported as river inundates the floodplains because the numerous small lakes loss zooplanktons to the flow ( James and William, 1988 ). Site description Manipur lies in the extreme part of the North-East India, a sub- Himalayan hilly state, stretching from 23o50Ń - 25o41Ń and 93o 02´ E – 94o48É. The total geographical area is 22, 327 sq. km of which only about 10% is the enchanting central valley and the rest is surrounding ranges of hills of altitude 800 m to 3000 m above the mean sea level. Thus the central valley comprises 2238 sq. km of which wetlands occupies about 524.51 sq. km.Irilriveris one of the major tributaries of Manipur river system in the central valley district of Manipur. It originates from Lakhamei village of Senapati district near the border with Nagaland with some tributaries originating from Ukhrul district and ultimately flows through the valley to meet Imphalriver in the southern suburb of Imphal city. Five sites were selected starting from the point where the river enter the greater Imphal city area and ending at the conjoining point with Imphal river as the river exit the greater Imphal area to be a part of Manipur river system.The extent of length of the river in the study area is about 20 kilometers. Methodology The five sampling sitescomprises two in

the upstream to Imphal city, one at Imphal city area and two in the downstream. Analyses were carried out in monthly interval in the year 2012. Studies on seasonal zooplankton population is based on Standard methods of APHA (1989), Adoni (1985), Lackey (1938), Edmondson (1974)and Needham and Needham (1966),. Nylon- bolting net(mesh size; 60-80 µm) was used for collecting zooplankton. Analysis of physico-chemical parameters were done based on standard methods of APHA( 1989) and Trivedy and Goel(1984).For the statistical calculation including ANOVA(Analysis of variance) methods of Parker (1973), Trivedi, Goel and Trisal (1987) and Kothari (2004) were used in computing the analysis. RESULTS The results of the studiesare logically classified into two sets namely pre-urban exposure sites and post-urban exposure sites. Means of the sites for the respective category is taken and the results are reproduced as Table 1,2and 3. This categorization presents a vivid account if urban exposure of the river gives impact to water quality and zooplankton population. The temperature of water for pre-urban sites ranges from 19.98 ± 0.210C in January to 25.42 ± 0.020C in July and for post urban sites it ranges from 20.36 ± 0.19 0C in January to 25.61±0.16 0C in July. The mean of PH value increases in the post urban exposure sites in the months ranging from February to May and Septemberto November. There is,however,no significant co-relation of PH with zooplankton population. The value of PH ranges from 7.30± 0.10 in January to 8.42 ± 0.07 in August. In the post-urban sites it ranges from 7.23 ± 0.04in January to 8.56 ± 0.15 in September. There is slight increase in the value of PH with the increase in river volume due to seasonal flood. The conductivityvalue ranges from 65.00 ± 2.36µ Siemens/ cm² inJanuary to 185.00 ± 2.36 µSiemens/cm² in June for pre-urbansites.It ranges from 71.11±6.94 µ Siemens/ cm² in January to 237.78 ± 15.03 µ Siemens/ cm² in June for the posturban sites.There is no significant co-relation of conductivity with zooplankton population.

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

19.98 ±0.21 20.36 ±0.19 7.30 ±0.10 7.23 ±0.04 65.00 ±2.36 71.11 ±6.94 41.67 ±2.35 48.89 ±6.94 25.22 ±0.12 31.09 ±3.05 5.28 ±0.00 5.28 ±0.20

Jan 20.75 ±0.03 20.78 ±0.05 7.35 ±0.03 7.43 ±0.04 75.00 ±2.36 94.44 ±25.24 51.67 ±2.35 65.56 ±15.40 27.27 ±1.27 42.75 ±10.77 5.18 ±0.14 5.35 ±0.47

Feb 21.65 ±0.03 21.71 ±0.03 7.35 ±0.03 7.46 ±0.02 128.33 ±7.07 152.22 5.09 63.34 ±4.72 116.67 ±3.34 33.38 ±1.63 50.79 ±7.71 5.08 ±0.00 5.35 ±0.31

Mar 22.80 ±0.10 23.29 ±0.16 7.55 ±0.03 7.64 ±0.02 143.33 ±0.00 167.78 ±20.09 76.67 ±4.72 117.78 ±18.36 45.30 ±4.34 68.62 ±0.51 5.28 ±0.28 5.28 ±0.20

Apr

N.B.:Pre-urban- before urban exposure ;Post-urban- after urban exposure

Dissolved Oxygen (ppm)

Turbidity (NTU)

Total Dissolved Solids (ppm)

Conductivity (µSiemens/cm2)

means

parameters

Temperature

Site

Physico-chemical

23.85 ±0.03 23.88 ±0.05 7.65 ±0.03 7.71 ±0.02 165.00 ±11.78 126.68 ±89.52 100.17 ±28.52 133.11 ±11.65 58.92 ±0.78 84.91 ±5.18 5.99 ±0.14 5.14 ±0.31

May 24.70 ±0.24 24.88 ±0.35 7.82 ±0.02 7.81 ±0.07 185.00 ±2.36 237.78 ±15.03 125.00 ±7.07 152.22 ±13.88 74.27 ±2.74 93.44 ±2.67 6.29 ±0.00 6.43 ±0.42

Jun 25.42 ±0.02 25.61 ±0.16 7.98 ±0.21 8.06 ±0.15 160.00 ±9.43 188.89 ±15.75 130.00 ±14.14 156.66 15.28 52.20 ±1.09 63.55 ±10.15 5.18 ±0.14 5.15 ±0.12

Jul

2012

25.25 ±0.03 25.39 ±0.14 8.42 ±0.07 8.33 ±0.09 181.66 ±2.35 192.22 ±12.62 143.34 ±9.43 180.00 ±8.82 89.75 ±3.56 94.24 ±1.34 7.51 ±0.00 7.38 ±0.12

Aug 24.67 ±0.00 24.66 ±0.12 8.39 ±0.02 8.56 ±0.15 175.00 ±2.36 182.22 ±12.62 120.00 ±14.14 135.56 ±8.39 65.75 ±1.53 73.87 ±2.98 7.61 ±0.14 6.70 ±0.54

Sep

Table 1:Physico-chemical properties of Irilriver in Imphal (average values)

23.77 ±0.14 24.40 ±0.15 7.85 ±0.07 7.99 ±0.10 126.67 ±0.00 153.33 ±23.34 81.67 ±2.35 94.44 ±13.88 43.57 ±0.05 65.16 ±13.09 6.60 ±0.14 6.02 ±0.47

Oct 22.33 ±0.14 22.84 ±0.28 7.52 ±0.02 7.77 ±0.15 110.00 ±4.71 154.44 ±38.92 75.00 ±2.36 92.22 ±18.36 39.60 ±0.95 60.59 ±11.01 6.40 ±0.15 5.95 ±0.31

Nov

7.48 ±0.02 96.67 ±9.43 108.89 ±16.78 48.34 ±2.35 56.67 ±10.00 28.48 ±5.87 36.42 ±5.89 5.69 ±0.57 5.28 ±0.35

20.45 ±0.03 20.51 ±0.03 7.42±0.07

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Pre-urban

Free CO2 (ppm)

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

2.31 ±0.16 3.63 ±0.69 2.59 ±0.21 2.90 ±1.68 32.00 ±2.83 37.33 ±4.16 0.034 ±0.002 0.065 ±0.034 0.027 ±0.007 0.029 ±0.004 1.67 ±0.00 2.11 ±0.38

Jan 3.3 ±1.56 4.33 ±2.31 3.05 ±0.00 3.86 ±0.46 39.00 ±4.24 46.67 ±5.03 0.072 ±0.028 0.156 ±0.016 0.014 ±0.001 0.024 ±0.011 2.67 ±0.47 3.45 ±1.07

Feb 7.48 ±1.56 9.46 ±1.54 3.35 ±0.42 3.96 ±0.31 45.00 ±1.41 49.33 ±4.16 0.094 ±0.029 0.174 ±0.041 0.017 ±0.003 0.024 ±0.006 3.84 ±0.23 4.33 ±1.21

Mar 4.29 ±0.16 7.33 ±1.90 2.44 ±0.00 3.86 ±0.46 52.00 ±2.83 71.33 ±4.16 0.088 ±0.006 0.167 ±0.030 0.019 ±0.004 0.029 ±0.006 4.34 ±0.47 8.67 ±0.67

Apr

N.B.:Pre-urban- before urban exposure ;Post-urban- after urban exposure

Potassium (ppm)

Inorganic Phosphate (ppm)

Nitrate (ppm)

Hardness (ppm)

B.O.D. (ppm)

means

parameters

Post-urban

Site

Physico-chemical

2.53 ±0.16 7.48 ±2.48 3.50 ±0.21 4.26 ±0.31 70.00 ±5.66 93.33 ±13.32 0.112 ±0.027 0.150 ±0.030 0.027 ±0.004 0.032 ±0.001 5.00 ±0.00 5.89 ±1.07

May 3.52 ±1.24 6.01 ±1.02 4.26 ±0.00 5.48 ±0.31 71.00 ±4.24 94.67 ±14.47 0.082 ±0.028 0.136 ±0.043 0.018 ±0.002 0.028 ±0.004 3.00 ±0.00 6.56 ±0.84

Jun 8.36 ±3.11 11.00 ±1.10 5.18 ±0.43 6.29 ±0.17 40.00 ±0.00 49.33 ±3.06 0.083 ±0.013 0.143 ±0.019 0.028 ±0.005 0.054 ±0.008 2.00 ±0.47 2.89 ±0.70

Jul 13.97 ±0.16 18.33 ±1.27 5.79 ±0.00 7.61 ±1.10 98.00 ±2.83 123.33 ±2.31 0.208 ±0.048 0.332 ±0.068 0.038 ±0.006 0.059 ±0.012 5.17 ±0.23 6.89 ±1.02

Aug

2012

13.20 ±0.31 14.75 ±1.44 4.57 ±3.23 6.19 ±0.63 79.00 ±7.07 116.00 ±5.30 0.238 ±0.023 0.426 ±0.084 0.042 ±0.001 0.075 ±0.014 3.33 ±1.41 5.56 ±1.83

Sep

Table 2: Physico-chemical properties of Irilriver in Imphal (average values)

7.92 ±0.62 8.43 ±0.92 3.66 ±0.43 5.38 ±0.47 39.00 ±1.41 42.67 ±2.31 0.188 ±0.006 0.357 ±0.142 0.039 ±0.019 0.062 ±0.026 1.17 ±0.23 2.44 ±0.84

Oct 2.09 ±0.16 5.13 ±1.09 3.66 ±0.43 4.25 ±0.33 39.00 ±1.41 42.67 ±4.16 0.132 ±0.041 0.277 ±0.081 0.032 ±0.000 0.055 ±0.023 1.50 ±0.24 2.33 ±1.57

Nov

1.43 ±0.16 3.01 ±0.83 2.29 ±0.22 2.84 ±1.07 44.00 ±2.83 44.00 ±5.29 0.065 ±0.026 0.083 ±0.016 0.023 ±0.016 0.038 ±0.012 2.33 ±0.00 2.67 ±1.00

Dec

136 SARON & MEITEI, Curr. World Environ., Vol. 8(1), 133-141 (2013)

Pre-urban

Rotifera

Post-urban

Pre-urban

Post-urban

Pre-urban

Post-urban

Pre-urban

6.30 ±0.34 6.06 ±0.37 2.67 ±0.04 2.58 ±0.31 1.2 ±0.08 1.24 ±0.25 10.17 ±0.30 9.88 ±0.81

Jan 6.30 ±1.10 7.58 ±0.40 3.96 ±0.68 3.66 ±0.30 1.17 ±0.30 1.62 ±0.16 11.43 ±0.72 12.86 ±0.66

Feb 7.17 ±0.30 8.46 ±1.47 3.21 ±0.04 3.04 ±0.76 1.53 ±0.72 2.26 ±0.54 11.91 ±0.47 13.76 ±0.65

Mar 8.82 ±0.34 8.62 ±1.24 4.38 ±0.42 5.46 ±1.00 1.77 ±0.13 1.94 ±0.39 14.97 ±0.21 16.02 ±0.83

Apr

N.B.:Pre-urban- before urban exposure ;Post-urban- after urban exposure

Total zooplankton

Copepoda

Cladocera

means

group

Post-urban

Site

Zooplankton

4.02 ±0.51 4.48 ±0.35 1.59 ±0.47 1.94 ±0.27 0.87 ±0.30 0.94 ±0.09 6.48 ±0.34 7.36 ±0.21

May 5.70 ±0.93 6.00 ±0.51 1.98 ±0.25 2.48 ±0.74 0.93 ±0.13 1.04 ±0.09 8.61 ±0.81 9.52 ±0.67

Jun 3.60 ±0.93 4.78 ±0.31 1.98 ±0.76 2.04 ±0.54 1.05 ±0.30 0.72 ±0.33 6.63 ±0.13 7.54 ±0.51

Jul

2012

4.74 ±0.25 5.14 ±0.45 2.85 ±0.13 2.08 ±1.52 1.14 ±0.25 0.94 ±0.43 8.73 ±0.13 8.16 ±1.17

Aug 5.97 ±0.55 5.96 ±0.54 2.85 ±0.21 2.72 ±0.18 1.29 ±0.04 1.54 ±0.14 10.11 ±0.38 10.22 ±0.86

Sep

Table 3: Zooplankton population count of Iril river in Imphal (average values in U/L)

7.05 ±0.55 7.70 ±0.50 2.76 ±0.85 2.12 ±0.34 1.59 ±0.47 2.42 ±0.33 11.40 ±0.76 12.24 ±0.48

Oct

7.35 ±0.72 8.14 ±0.59 2.73 ±0.04 2.66 ±1.07 1.71 ±0.47 1.58 ±0.18 11.79 ±0.21 12.38 ±1.35

Nov

6.30 ±0.34 6.26 ±0.15 2.55 ±0.04 2.40 ±0.16 0.84 ±0.17 1.82 ±0.40 9.69 ±0.47 10.48 ±0.56

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The Total dissolved solids (TDS) value ranges from 41.67±2.35 ppm in January to 143.34 ±9.43ppm in August for pre-urban sites and for posturban sites it ranges from 48.89 ± 6.94 ppm in January to 180.00 ± 8.82 ppm in August. It shows negative co-relation with Zooplankton population,r =-0.531, p> 0.05 and significant at 5% level for preurban sites however there is no significant corelation in the post urban sites.

There is no significant co-relation of Nitrate, Inorganic phosphate and Potassium with zooplankton population.

It is important to note that there is no significant co-relation of the physico-chemical parameters with zooplankton population in the posturban sites.

Inorganic phosphate content for pre-urban sites ranges from 0.014 ± 0.001 ppm in February to0.042 ± 0.001 ppm in September. Whereas for post-urban sites it ranges from 0.024 ± 0.011 ppm in February to 0.075 ± 0.014 ppm in September.

Turbidity ranges from 25.22 ± 0.12 NTU in January to 89.75 ±3.56 NTU in August for pre-urban sites and for post-urban sites it ranges from 31.09 ±3.05 NTU in January to 94.24 ± 1.34 NTU in August and no significant co-relation with zooplankton population. Dissolved oxygen(DO) recorded minimum of 5.08 ± 0.00 ppm in March to maximum of 7.61±0.14 ppminSeptember for pre-urban sites and minimum of 5.14±0.31ppm in May and maximum of 7.38 ± 0.12 ppm in August for posturban sites. Free CO2 ranges from 1.43 ± 0.16ppm in December to 13.97 ± 0.16 ppm in August for preurban sites and for post-urban sites it ranges from 3.01 ± 0.83ppm in December to 18.33 ± 1.27 ppm in August . Bio-chemical oxygen demand (B.O.D)of pre-urban sites showed negative co-relation with zooplankton population,r=-0.537,p>0.05 and significant at5%level. The value ranges from 2.29 ± 0.22ppm in December to 5.79 ± 0.00ppm in August for pre-urban sites and from 2.84 ± 1.07 ppm in December to 7.61± 1.10 ppm in August for posturban sites. Hardness values for pre-urban sites ranges from 32.00± 2.83 ppm in January to 98.00± 2.83 ppm in August.For post-urban sites the value ranges from 37.33 ±4.16 ppm in Januaryto 123.33 ± 2.31 ppm in August. There is no significant corelation with zooplankton population.

The value of nitrate in pre-urban sites ranges from 0.034 ±0.002 ppm in January to 0.238 ± 0.023 ppm in September. For post-urban sites the value ranges from 0.065 ± 0.034 ppm in January to 0.426 ± 0.084 ppm in September.

The value of Potasium for pre-urban sites ranges from 1.17 ±0.23 ppm in October to 5.17 ± 0.23 ppm in August whereas for the post-urban sites it rangesfrom 2.11 ± 0.38 ppm in January to 8.67 ± 0.67 ppm in April. The Rotifera population count for pre-urban sites ranges from 3.60 ± 0.93 U/L in July to 8.82 ± 0.34 U/Lin April. For post-urban sites it ranges from 4.48 ± 0.35U/L in May to 8.62 ± 1.24 U/L in April. For population count of Cladocerafor the pre-urban sites, the values rangefrom1.59 ± 0.47U/ L in May to 4.38 ± 0.42 U/L in April.For post-urban sites it ranges from 1.94± 0.27 U/L in May to 5.46 ± 1.00 U/L inApril. The Copepoda population count for preurban sites ranges from0.84± 0.17 U/L in December to 1.77 ± 0.13 U/L inApril. For post-urban sites it ranges from 0.72 ± 0.33 U/L in July to 2.42 ± 0.33 U/L in October. As a whole, the total zooplankton population for pre-urban sites ranges from 6.48 ± 0.34 U/L in Mayto 14.97 ± 0.21 U/L in April. Thus the primary peak of population growth is in April with a secondary peak in November. For post urban sites, the time of primary and secondary peaks are in similar pattern even as the value of count ranges from 7.36 ± 0.21 U/L inMay to 16.02 ± 0.83 U/L in April. The sudden drop of zooplankton population from April to May is due to early seasonal rain followed by flood.

SARON & MEITEI, Curr. World Environ., Vol. 8(1), 133-141 (2013) ANOVA (Analysis of variance) is calculated for the three zooplankton groups. For pre-urban sites the calculated value of F-ratio is 76.6 and for post-urban sites the F-ratio is 75.43,both of which are very much greater than the table valueof 3.32 at 5% level with d.f. being v1=2and v2=33.Thus there is significant difference in sample means for the three groups of zooplanton. It is therefore concluded that the change in populationof zooplankton population during the seasons is highly significant.

Discussions From the results it can be established that zooplankton population of the river has no significant co-relation with most of the physicochemical parameters except for Total dissolved solids (T.D.S.) and Bio-chemical oxygen demand ( B.O.D.) in the pre-urban sites. The negative corelation may rather be established for decrease in population due to flooding of the river than any possible impact of the values of the parameters. Though the F-ratio for variance of pre-urban to post urban sites of Nitrate ( 5.59 at 5% level with d.f. being v1= 1 and v2= 22 when the table value is 4.30) and Inorganic phosphate (7.241 at 5% level with d.f. being v1= 1 and v2= 22 when the table value is 4.30) are significant, these parameters do not affect zooplankton population in pre and post urban exposure since there is no significant variance of the later in the two sets of sites. The change in water quality of the river, with reference to the remaining physico-chemical parameters, shows no significant variance after urban exposure (except for Inorganic phosphate and Nitrate). Though total zooplankton population is negatively co-related with TDS and

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BOD, the two physico-chemical parameters exhibit no variance in pre- and post-urban exposures, and there is no significant variation of the zooplankton population in the two sets of observations. The peculiar river basin setting of Irilriver in the area, that is natural reservoir like feature, help in dilution of the pollutants specially in two of the posturban sites. It is formed due to confluence of heavily silt loaded streams in the midst. Moreover on account of the rivers situation at the periphery of the main urban area and no particular sewage draining into the river, pollution of the river is at a low level. Plankton densities in unregulated tropical rivers are often low ( James& William,1988). Rzoska(1978) found that reproduction of zooplankton in rivers is rarely observed at velocities in excess of 0.4 m. s-1. The drop of population in May be due to this reason of increased velocity. Velocity of the river water flow is maximal during flood time. NanditaChakrabortyet al., (1995) established role of nutrient gradient in unequal distribution of plankton species in Hooglyriver. However significant co-relation is not observed in the present studies, which may be due to very low level of nutrient content in the study sites. Pathani and Upadhyay (2006) reported increase of zooplankton population from winter season and reaching maximum in summer. The present finding is in similar patter except for a slight decline in the month of December. It thereby creates two peaks â&#x20AC;&#x201C;one primary peak of zooplankton population in April (Spring) and one secondary peak in November (Autumn). The primary peak could have been shifted to later month of summer

Fig.1: Mean zooplankton population of the two sets of sites for Irilriver 2012

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season if the arrival of seasonal rain was normal. This season early seasonal rain accompanied with high flood in May could have led to decrease in zooplankton population in May. The bimodal pattern of this zooplankton population peak is grossly in association with findings, ofMathew (1978)and Sinha (1992). Bhatt et al., (1984)reported maximal zooplankton population during the period of minimum velocity. The present peak in April is in association with this observation.Exposure to contaminants can severely impact zooplankton (Bradley and Roberts, 1987) but the insignificant variation of zooplankton populationof pre and post urban exposure sites in the present studies is associated with low pollution level even after the river enter the urban area.

CONCLUSION 8. As for the present time, pollution level of Irilriver is not alarming and conservation of the river is very much needed for preventing further ecological deterioration, because the water of the river is ultimately needed for water supply of the Imphal city. Moreover Iril is the only river in the Imphal area keeping intake its bio-diversity specially the ichthyo-fauna. Monitoring of zooplankton communities is needed to allow us to predictively model the ecosystem ofIrilriverand it will be helpful in modeling for conservation of the river ecosystem. REFERENCES 1.

Adoni, A.D., Workbook on Limnology.Indian MAB Committee Dept. of Envi, Govt. of India.Pratibha Publishers, Sagar, India.p. 216 (1985). Alexander Singh,Th.,Bijen Meitei, L., and SanamachaMeetei, N., Distribution Pattern of Enteropathogens in Greater Imphal Area of Imphal River, Manipur. Current world Environment 7(2): 259-265 (2012). APHA ,Standard Methods for the Examination of Water and Waste- Water Analysis. (17 th Edn.), Washington D.C. (1989). Bhatt, S.D., YashodharaBisht and UshaNegi, Ecology of the Limnofauna in the River Kosi of the Kumaun Himalaya (Uttar Pradesh).Proc. Indian natn.Sci. Acad. B50 No

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4: 395-405 (1984). Bradley,B.P.,Roberts, M.H.,Jr., Effects of contaminants on estuarine zooplankton. InS.K. Majumdar, L.W. Hall, Jr., and H.M. Austin, Contaminant Problems and Management of LivingChesapeake Bay Resources, The Pennsylvania Academy of Science, Philadelphia, Pa., PP. 417-441 (1987). Deborah K. Steinberg and Robert H. Condon,Zooplankton of the York River Journal of Costal Research,Sl. 57: 6679(2009). Edmondson, W.T., A simplified method for counting phytoplankton. In: A manual on methods of or measuring primary production in aquatic Environment .R.A. Vollenweider (ed.), 1BP 12(1974). James F. Saunders, III& William M.Lewis,Jr.,Zooplankton abundance and transport in a tropical white- water river.Hydrobiologia 162:147-155(1988). Kothari, C.R., Research methodology Methods and Techniques (Second revised edition), New Age International Publishers , 401 (2004). Lackey, J.B., The manipulation and counting of river plankton and changes in some organisms due to formation preservation. U.S. Public Health Report, 53: 2080-2093 (1938). G.S. Kalwania and Radhey Shyam., Orient J. Chem., 28(1): 457-552 (2012). Makarewicz, J. C., and Likens, G. E., Structure and function of the zooplankton community of mirror lake, New Hampshire. Ecol. Monogr.19: 109-127 (1979). Mathew, P.M., Limnological investigation on the plankton of Govindgarh lake and its correlation with physico-chemical factors. p. 46-55, IN : Proc. Sem.Ecol. Fisheries Freshwater Reservoirs (Saigal, B.N. Ed.). CIFRI, Barrackpore, 27-29: 1969 (1978). Moghraby, A. el., A study of diapauses of zooplankton in a tropical river-the Blue Nile. Freshwat.Biol. 7: 207 -212(1977). NanditaChakraborty, Chakrabarti, P.K., Vinci, G.k., andSugunan, V.V., Spatiotemporal distribution pattern of certain plankton of river Hooghly.J.Inland Fish. Soc. India 27(1):

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A Review of Dichlorvos Toxicity in Fish SUCHISMITA DAS Department of Life Science and Bioinformatics, Assam University, Silchar - 788 011, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.08 (Received: February 08, 2013; Accepted: February 23, 2013) ABSTRACT Among the wide majority of pesticides, dichlorvos (2, 2-dichlorovinyl dimethyl phosphate), a organophosphate compound, is commonly used as agricultural insecticide. It is extremely toxic to non target organisms like fish and hampers fish health through impairment of metabolism, sometimes leading to death. As one of the few organophosphates still registered for use, dichlorvos has elicited worldwide concern for many reasons. This study is a review of potential adverse effects of dichlorvos in fish.

Key words: Dichlorvos, Toxic, Acute, Chronic, Fish.

INTRODUCTION Use of pesticide has become a necessary evil for developing countries like India where it is estimated that approximately 30% of its crop yield valued at Rs.60,000 crores are lost due to pest attack each year 1 . Amongst others, organophosphorus pesticides (OPs) are the most commonly used pesticides in the world due to their quick degradation2. Unfortunately, OPs lack target specificity and can cause severe, long lasting population effects on terrestrial and aquatic nontarget species, particularly vertebrates 3. Quick degradation is probably the reason why, irrespective of reports of health hazardous, developing countries especially, in the Asia-Pacific region, use these chemicals for agricultural and public health purposes 4,5. Dichlorvos (2, 2-dichlorovinyl dimethyl phosphate) was first introduced in 19616. It has a molecular formula C 4H 7 Cl 2O 4P and molecular weight to be 220.98 (Fig 1). It is also known by its trade name DDVP, Dedevap, Nogos,Nuvan, phosvit or Vapona7. It is one of the most commonly used organophosphate pesticides in developing countries8. It is classified by the WHO as a Class IB,

â&#x20AC;&#x2DC;highly hazardousâ&#x20AC;&#x2122;chemical9. Dichlorvos is usually used as an agricultural insecticide on crops and stored products but is also used as an antihelminthic (worming agent) for dogs, swine, and horses, as a botacide; agent that kills fly larvae10. It is poisonous if swallowed, inhaled, or absorbed through the skin11. It is extremely toxic pesticides to aquatic organisms and hampers fish health through impairment of metabolism sometimes leading to death. As one of the few organophosphates still registered for use, dichlorvos has elicited worldwide concern for many reasons. Although dichlorvos serves as a contact and stomach insecticide for food and non-food crop pests, it is also toxic to fish and other aquatic organisms12-14. Dichlorvos is also commonly used in fish farming to eradicate crustacean ectoparasites. It is specially used in the treatment of sea lice (Lepophtheirus salmonis and Caligus elogatus) on commercial salmon farms. But this pesticide often ends up producing both lethal and sub-lethal effects on the fish 15 and even zooplanktons16. At only 1 ppm, dichlorvos, showed both acute and chronic toxicity in fish17. Some other workers have also noted adverse effects of dichlorvos in fish18-20. The present study is an attempt to review the potential adverse effects of dichlorvos in fish.

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Fig. 1: Dichlorvos (2, 2-dichlorovinyl dimethyl phosphate) Acute toxicity of dichlorvos on fish The acute toxicity of dichlorvos to fish has been previously determined by a number of researchers. Its toxicity for freshwater and estuarine fish is moderate to high, and it does not bioaccumulate in fish 21 . For freshwater and estuarine fish, 96h-LC50 values range from 0.2 to 12 mg/L22. For marine fish, the toxicity was estimated to be more than 4 mg/L for adults and pre-adults of Atlantic salmon (Salmo salar)23. The 96h-LC50 value of dichlorvos obtained for fingerlings of European sea bass (Dicentrarchus labrax) was 3.5 mg/L15. A comparison of the 96h-LC50 values published for several teleost fish species 22 indicates that fingerlings of the European sea bass are more resistant to dichlorvos exposure than the most part of the other species of estuarine and freshwater fish studied. However, the comparison with fathead minnow (Pimephales promelas) or with mosquito fish (Gambusia affinis) of similar size indicates that sea bass fingerlings are more sensitive to dichlorvos, since 96h-LC50-values of 12 and 5.3 mg/L have been reported 22 for both species, respectively. In a study, it was found that 100% of 100 g salmon (Salmon salar) survived after 24 h of exposure to 1, 3, and 5 mg/L of dichlorvos24. The 96h-LC50 value of dichlorvos obtained for Labeo rohita was 16.71ppm. The fish in the same study exhibited erratic swimming, copious mucus secretion, loss of equilibrium and hitting to the walls of test tank prior to mortality in acute toxicity tests25. The 96-h LC 50 values of Dichlorvos has been reported in Cirrhinus mrigala to be 9.1ppm26, in Zebra fish, the 24-hpost fertilization LC50 value of dichlorvos in the semi static test was 39.75 mg/L27 and 48-h LC50 values to be 0.5-10mg/L of dichlorvos

formulations in carp28. A study report indicated that 96-h LC50 value in rainbow trout was 0.93 mg/L29 and on golden orfe was 0.45mg/L30. In another study, 100% lethality at 10 mg/L in fry of rainbow trout was found31. In Tilapia mossambica with three size groups, 96-h LC50 values were found to be 1.41.9mg/L, the smaller sizes being more sensitive32. 24, 48 and 96-h LC50 values of dichlorvos in common carp to be 3.8, 2.7, 2.3mg/L respectively and 4.1, 4.0 and 3.7 mg/L in Java carp respectively.33 In harlequin fish found 24-h LC50 value to be 12mg/L and 48-h LC50 value to be 7.8mg/L34 while 24 and 48-h LC50 in bluegill sunfish to be 1 and 0.7mg/L respectively35. Again, 96-h LC50 in bluegill and spots were reported to be 0.48 and 0.55mg/L respectively36. Chronic toxicity of dichlorvos on fish Effects on Choline esterase activity Dichlorvos is an organophosphorus insecticide reported to be neurotoxic due to its irreversible inhibitory effect on AChE37. The enzyme AChE degrades the neurotransmitter acetylcholine in cholinergic synapses. The inhibition provokes an accumulation of acetylcholine in synapses with disruption of the nerve function that can end in the death of the organism. Several authors have been reporting significant inhibition of ChE activity in fish at sub-lethal concentrations of dichlorvos38-41. In sea bass, dichlorvos significantly inhibited the activity of ChE in the selected tissues, both in vitro and in vivo conditions. Differences in ChE sensitivity were found in relation to the age of the fish and the tissue analysed. Sea bass fingerlings are able to tolerate high levels of head and muscle ChE inhibition before death15. Similar results were obtained for pinfish (Lagodon rhomboides)42 and European eel (Anguilla anguilla)43. Brain tissue showed higher ChE activity than muscle, whole blood or plasma tissues. On the contrary, in fingerlings, the highest ChE activity was obtained in muscle. This is in agreement with the results obtained by other researchers44-46. Skeletal muscle presented higher ChE activity than brain tissue in juveniles of goldfish (Carassius auratus) of size ~5 g exposed to three different pesticides47. Chronic dichlorvos exposure impaired mitochondrial energy metabolism and neuronal apoptotic cell death in brain 48. AChE activity of Tilapia mossambica in relation to the interacting effects of aging and sub-lethal

DAS, Curr. World Environ., Vol. 8(1), 143-149 (2013) concentrations of dichlorvos was studied49. The enzyme activity of brain and liver decreased with increasing size (and age) and dichlorvos exposed fish showed considerable inhibition of brain and liver AChE. There was a positive correlation between dichlorvos concentration and the time of exposure when the degree of enzyme inhibition was considered. Brain exhibited a higher degree of enzyme inhibition in all age groups of fish as compared to liver. Small fish were more susceptible to the insecticide with respect to AChE activity. When transferred to clean water, most of the exposed fishes recovered their AChE activity and the recovery was greater in liver than in brain49. Effects on Antioxidants It has now been established that OP pesticides induced oxidative stress50. An antioxidant defence system (ADS) is needed to protect biomolecules from the harmful effects of ROS. Fish are endowed with defensive mechanisms to neutralize the impact of reactive oxygen species (ROS) resulting from the metabolism of various chemicals. These include various antioxidant defence enzymes such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPOx), glutathione S-transferase (GST), and glutathione reductase (GR). Low molecular weight antioxidants such as glutathione (GSH), ascorbate (vitamin C), vitamin A and E are also reported to contribute in the quenching of oxy radicals51. ROS which is not neutralized by this antioxidant defense system damages all biomolecules. One of the most important targets of ROS is the membrane lipids which undergo peroxidation (LPO). Thus, LPO estimation has also been successfully employed to signify oxidative stress induced in aquatic animals by such chemicals52. Decreased GSH levels and also decreased MnSOD activity were observed, in the brain mitochondria isolated from low-level chronic dichlorvos treated rat43. Also, in fish exposed to dichlorvos for 24 h, at concentrations of 1 or 5 mg/L, a dose-dependent increase was noted in the activities of SOD and CAT in the liver and brain. A rise was also observed in the level of GSH and changes were noted in MDA level in these organs. The increase in GSH was noted mainly in the brain and was accompanied by a decrease in MDA level. The decrease was greater at the exposure to the higher dose of the compound53.

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Chromosomal aberrations and carcinogenic effects Dichlorvos concentration of 0.01 ppm caused chromosomal aberrations in the form of centromeric gaps, chromatid gaps, chromatid breaks, sub-chromatid breaks, attenuation, extra fragments, pycnosis, stubbed arms etc in kidney cells of Channa punctatus after exposure periods of 24, 48, 72 and 96 h54. Interestingly, there was an inverse relationship between duration of exposure and aberration frequency. Longer exposures to dichlorvos were associated with lower frequencies of aberrations. The toxicity of dichlorvos has also been related to alterations in DNA replication, which causes mutations55 and cellular hyperproliferation as a result of local irritation56-58. Dichlorvos has carcinogenic potential, which has been reviewed on several earlier occasions by several workers59-62. Immune response Dichlorvos has the potential to induced altered immune response in fish and it was reviewd by Dunier et al. 199163. Developmental effects Dichlorvos exposure during early development in Zebra fish caused clear behavioural impairments detectable during the post hatching period. It also showed mortality and developmental abnormalities27. Histopathology Histopathology is an important tool in assessing pesticide toxicity64. The histopathological effects of liver tissues in Cirrhinus mrigala chronically exposed to dichlorvos showed hepatic lesions in the liver tissues were observed which were characterized by cloudy swelling of hepatocytes, congestion, vacuolar degeneration, karyolysis, karyohexis, dilation of sinusoids and nuclear hypertrophy. In the same study, changes in gills such as hyperplasia, desquamation, and necrosis of epithelial, epithelial lifting, oedema, lamellar fusion, collapsed secondary lamellae, curling of secondary lamellae and aneurism in the secondary lamellae were observed after exposure to dichlorvos26. The effects of sub-lethal doses of dichlorvos on lipid composition and metabolism

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of rainbow trout skin cells in primary culture were investigated and it was suggested that dichlorvos may have direct effects on fish skin that could have important consequences for fish health in general65. In another study in air-breathing catfish Clarias batrachus exposed to lethal and sublethal concentrations of the dichlorvos, significant cytoarchitectural changes in the oocytes, including pronounced vacuolation, degeneration and deformation were observed 67. Clumping of the cytoplasm and karyohypertrophy were also evident and rupture of the cell wall, with extrusion of the cytoplasm and the nuclei, was observed in the same study 67. Pesticides are also reported to cause changes in structure and functions of fish gonads68. Although the studies with dichlorvos are scarce, the effects of sublethal concentrations of dichlorvos (0.65 mg/l, 0.90 mg/l and 1.17 mg/l) on the gonadosomatic index of the fish, Cyprinus carpio communis was studied69. The Ganadosomatic index decreased with the increase in concentration, whereas it increased with increase in exposure at all concentrations69.

CONCLUSION Dichlorvos toxicity in fish has been studied by several workers who have shown that at chronic level, it causes diverse effects including oxidative damage, inhibition of AchE activity, histopathological changes as well as developmental changes, mutagenesis and carcinogecity. With reports of dichlorvos usage and its adverse effects on non-target organisms like fish, it has become essential to formulate stringent rules against indiscriminate use of this pesticide. Since dichlorvos is present in the environment with other similar organophosphate compounds, additive responses to organophosphate compounds may induce lethal or sublethal effects in fish. It is, therefore, a matter of great public health significance to regularly monitor the pesticide residues in foods and humans in order to assess the population exposure to this pesticide. Besides, for a safe use of this insecticide more experimental work should be performed to determine the concentration and time of exposure that do not induce significant sublethal effects on fish.

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354–361 (1994). International Agency for Research on Cancer (IARC). Overall Evaluations of Carcinogenicity: An Updating of IARC Monographs, Volumes 1 to 42. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, Supplement 7 (1987). National Toxicology Program (NTP) Toxicology and carcinogenesis studies of dichlorvos in F344/N rats and B6C3F1 mice. U.S. Dept. of HHS, PHS, NIH, NTP Technical Report No. 334 (1989). Dunier, M. Siwicki, A.K. and Demael, A. Effects of organophosphorus insecticides: effects of trichlorfon and dichlorvos on the immune response of carp ( Cyprinus carpio).III. In vitro effects on lymphocyte proliferation and phagocytosis and in vivo effects on humoral response. Ecotoxicol. Environ. Safety 22: 79-87 (1991). Das, S. and Gupta, A., Effect of Malathion (EC50) on Gill Morphology of Indian Flying Barb, Esomus danricus (HamiltonBuchanan). World Journal of Fish and Marine Sciences 4: 626-628 (2012). Ghioni, C. Tocher, D. R. and Sargent, J. R. Effects of dichlorvos and formalin on fatty acid metabolism of rainbow trout (Oncorhynchus mykiss) skin cells in primary culture. Fish Physiol biochem, 18: 241-252 (1998). M. Hussain, I. Ahmed, P. Rao and Satya Narayan, Orient. J. Chem., 27(4): 1747-1753 (2011). Benarji, G., and Rajebdranath, T. Dichlorvos-induced histoarchitectural changes in the oocytes of a freshwater fish. Funct Dev. Morphol. 1: 9-12 (1991). Singh, H. and T.P. Singh, Effect of pesticides on fish reproduction. Ichthyologia, 15: 71-81 (1982). Mir, F.A. Shah, G.M. Jan, U. and Mir, J.I. Studies on Influences of Sublethal Concentrations of Organophosphate Pesticide; Dichlorvos (DDVP) on Gonadosomatic Index (GSI) of Female Common Carp, Cyprinus carpio communis. American-Eurasian Journal of Toxicological Sciences 4: 67-71 (2012).

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Phytochemical Analysis of Hot Petroleum Ether Extracts of Piper nigrum ADITI GUPTA*, MONIKA GUPTA and SUDHAKAR GUPTA Department of Chemistry, Lovely Professional University, Phagwara, Punjab - 144 806, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.18 (Received: March 07, 2013; Accepted: March 20, 2013) ABSTRACT The genus Piper belongs to family piperaceae which has over 700 species distributed in both hemispheres. The piperaceae family is a source of many biologically active photochemical with tremendous potential for medicinal uses. A wide range of secondary metabolites mainly alkaloids, amides and terpenes are reported from the various species of piper which are of great economical and medicinal importance. This paper reports the isolation of various sesqueterpenes such as δ–elemene, δ–cadinene, α–copane, caryophyllene, α–caryophyllene, β–bisabolene, and methyl benzene from the oil of the hot petroleum ether extract of Piper nigrum seeds. These phytochemicals are analysed by GC-MS spectral analysis.

Key words: Piper nigrum, dried fruits, volatile oil, GC-MS.

INTRODUCTION

Piper nigrum, belong to family piperaceae is a monoecious, perennial climbing herb, native of Southern India and Srilanka, cultivated in tropical regions1. It is found in vast altitudinal diversity and shows great adaptability to a wide range of climatic and soil conditions which leads to interspecies diversity2. Various pharmacological activitiessuch as antimicrobial 3, analgesic, antipyretic, antiinflammatory, anticonvulsant, CNS depressant4, antimutagenic 5 , antioxidant and radical scavanging 6-7 , antiinsecticidal 8 , synergist 9 , allelopathic 10 and antirheumatism 1 have been reported. It is found to be helpful in reducing pain, chills, flu, colds, feverand muscular aches1. The dried fruits act as a source of medicine for aphrodisiac, carminative, antiseptic, diuretic, galactagogic and emmenagogic12. The aromatic fruits are used as spices and unripe fruit is a source of black pepper11. It has many physiological activities and therefore is of high commercial, economic and medicinal importance13. During our research for novel bioactive natural products, the seeds of the plant are soxhalated with various organic solvents. All the extracts were showing the potential for

further treatment. The petroleum ether extract after keeping untouched for twenty days, separated into thick lower solid portion and upper oily fraction. The oily fraction obtained from the petroleum ether extract on GC-MS analysis showed the presence of seven different components. MATERIALS AND METHODS Seeds of Piper nigrum were purchased from the specific seed shop at Jammu district and identified by Dr. Gurdev Singh of Botany department at Lovely Professional University. Dried and crushed seeds (1 Kg) of Piper nigrumwere soxhalated in ethanol for around 72 hours. The ethanol extract was than distilled with light petroleum ether, toluene, chloroform and ethyl acetate according to their polarity gradients. The oily fraction of petroleum ether extract was subjected to GC-MS for identification of different components present in it. Analysis of oily fraction The GC-MS spectra of oily fraction of hot petroleum ether extracts of Piper nigrum recorded from Varian 4000 GC-MS/MS unveiled the presence of following components :

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Table 1: Different components from hot petroleum ether extract of Piper nigrum

CH3

Compound number

RT (min)

Peak name

Area

Amount/Rf

1 2 3 4 5 6 7

5.949 34.467 36.378 38.378 39.904 41.829 42.356

Methyl benzene δ – elemene α – copane Caryophyllene α-caryophyllene β–bisabolene δ –cadinene

833309 2804 18083 91584 9096 19815 9482

84.671 0.285 1.837 9.306 0.924 2.013 0.963

H2C

H3C

CH3

H CH3

H3C

H3C H3C

H3C

CH3

H3C

CH3

CH3 CH3

H2C

H3C

CH2

H3C

CH3

Fig. 1: Various components from hot Petroleum ether extracts of Piper nigrum

Among these chemical constituents methyl benzene is present as major component and ä – elemene as minor component, structures are given below

ACKNOWLEDGEMENTS The author is thankful to IIIM Jammu for GC-MS and Lovely Professional University for its lab facilities.

REFERENCES

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Reshmi S.K., SathyaE. and DeviP.S., J. of Medicinal Plants Research.,4(15): 15351546 (2010). Parthasarathy U., Asish G.R., Zachariah T.J., SajiK.V., George J.K., Jayarajan K.,Mathew P.A. and Parthasarathy V.A., Current Science., 94(12): 1632-1635 (2008). Dorman H.J.D. and Deans S.G., J.of Applied Microbiology, 88(2): 308-316 (2000). MadhaviB.B.,NathA.R.,BanjiD., MadhuM.N., RamalingamR. and Swetha D., Int. J. of Pharmacy and Pharmaceutical Sciences., 1(2): 156-161 (2009). El H.R., Idaomar M., Alonso-Morago A., Munoz S.A., Food Chem.Toxicol., 41(1): 4147 (2003). Gulcin I., Int . J . Food Sci. Nutr., 56(7): 491499 (2005). L.R. Giri, S.V. Kolhe and D.T. Tayade., Orient

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J. Chem., 28(1): 603-606 (2012). CFSu. Helen. and Horvat R., J. Agric. Food Chem., 29(1): 115-118 (1981). Scott I.M., Jensen H.R., Philogene B.J.R. andArnason J.T., Phytochemistry Reviews 7(1): 65-75 (2008). Siddiqui Z.S., Acta Physiologiae Plantarum., 29(4): 303-308, 2007. Francois T., Michael J.D.P., Lambert S.M., Ndefor F., Vyry W.N.A., Henri A.Z.P. and Chantal M., African J. of Biotechnology., 8(3), 424-431, 2009. Gadir W.S.A., Mohamed F. and Bakhiet A.O., Research J. of Microbiology., 2(1): 824-830, (2007). Siddiqui B.S., Gulzar T., Begum S., Afshan F. and Sattar F.A., Natural Product Research., 19(2): 143-150 (2005).

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Vol. 8(1), 153-156 (2013)

Asessment of Ground Water Quality of Rural Parts of Kapadwanj and its Impact on Human Health S.N. PANDYA*, A. K. RANA1, D.K. BHOI and F.J. THAKOR *Department of Chemistry, J & J College of Science, Nadiad - 387 001, India. 1 Department of Biology, Navjivan Science College, Dahod - 389 151, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.19 (Received: January 21, 2013; Accepted: February 10, 2013) ABSTRACT Assessment of ground water quality of rural parts of kapadwanj .Its physio-chemical analysis such as temperature , pH, biological oxygen demand, total dissolved solids, chloride, total alkalinity, calcium and magnesium hardness, sulphate, phosphate, nitrate of ground water was carried out from twenty sampling stations of rural parts of Kapadwanj region are during the February- 2012 and July - 2012 in order to assess water quality index.

Key words: Assessment, Physico-Chemical analysis, ground water, Kapadwanj Human health. INTRODUCTION Water is most essential for existence of life on earth and is a major component for all forms of lives, from micro-organism to man .Various physico-chemical parameters have a significant role in determining the potability of water . As Per World Health Organization,safe and wholesome drinking water is a basic need for human development ,health and well being, and it is an internationally accepted human rightâ&#x20AC;?Water intended for human consumption must be free from harmful micro organism, toxic substances, excessive amount of minerals and organic matter. Over burden of the population pressure,unplanned urbanization,unrestricted exploration and dumping of the polluted water at inappropriate place enhance the infiltration of harmful compounds to the ground water .In continuation of our earlier analysis on ground water1-3, here we report the Physico-Chemical analysis of ground water of rural parts of Kapadwanj region. Kapadwanj is located in Kheda District of Gujarat. Ground water is generally used for Drinking and other domestic purposes in this area. The use of fertilizers and pesticides, manure, lime, septic tank, refuse dump, etc. are the main sources of ground water pollution4. In the absence of fresh water supply, people residing

in this area forced to use Bore wells water for their domestic and drinking consumption. In order to assess water quality index, we have carried out the Physico-Chemical analysis of ground water. EXPERIMENTAL Analysis of water samples was done as per standard procedure1234 .In the present study ground water samples from twenty different areas located in and around Kapadwanj region were collected in brown glass bottles with necessary precautions. Physico-chemical analysis All the chemicals used were of AR grade. Double distilled water was used for the preparation of reagents and solutions. The major water quality parameters considered for the examination in this study are temperature, pH, biological oxygen demand (BOD) , total dissolved solid (T.D.S.), total alkalinity, calcium and magnesium hardness, sulphate, phosphate and nitrate contents6. Temperature, pH, TDS, Phosphate, Nitrate values were measured by water analysis kit and manual methods. Calcium and Magnesium hardness of water was estimated by complexometic

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titration methods 7 . Chloride contents were determined volumetrically by silver nitrate titrimetric method using potassium chromate as indicator and was calculated in terms of mg/L. Sulphate contents were determined by volumetric method7.

BOD BOD is the measurement of the amount of biologically oxidizable organic matter present in the waste.The increased levels of BOD indicated that the nature of chemical pollution.BOD of ground water is between 0.8 to 2.1.

RESULTS AND DISCUSSION The Physico-chemical data of the ground water samples collected in February-2012 and July2012 are presented in Table-1 and Table-2 respectively. The results of the samples vary with different collecting places because of the different nature of soil contamination7. All metabolic and physiological activities and life processes of aquatic organisms are generally influenced by water temperature. Temperature Temperature is one of the most essential parameters in water. It has significant impact on growth and activity of ecological life and is greatly affects the solubility of oxygen in water. In the study temperature ranged from 27.1o C to 33.5o C.

Chlorides Chlorides are common constituents of all natural water. Higher value of it impacts a salty taste of water, making it unacceptable for human consuption. The chlorides contents in the samples between 26.98 mg/L to 215.04 mg/L Natural water contains low chloride ions. In the present study sample station No. 17 shows 215.04 mg/L chloride. Which is highest value in twenty different sampling station. As per ISI the desirable limit of chloride for drinking water is 250mg/l and the permissible limit is 1000mg/l. Total Alkalinity Total alkalinity is the quantitative capacity of an aqueous media to react with H+ ions . In the study total alkalinity ranged from 148mg/L to 760 mg/L.

pH The pH value of drinking water is an important index of acidity, alkalinity and resulting value of the acidic-basic interaction of a number of its mineral and organic components. pH below 6.5 starts corrosion in pipes .Resulting in release if toxic metals. In the study pH ranged from 6.9 to 8.2.The tolerance pH limit is 6.5 to 8.5. TDS A large number of solids are found dissolved in natural water the common ones are carbonates,bicarbonates,chloride,sulphate,phosphate ,iron,etc.In other words TDS is sum of the cations and anions concentration.A high contents of dissolve solids elevates the density of water,influences solubility of gases(like oxygen) reduces utility of water for drinking irrigation and industrial purpose. In the present study TDS ranged from 210 mg/L to 1300 mg/L. According to WHO 9 and Indian standards TDS values should be less than 500 mg/L for drinking water. All the sample station except sample station no 2, 10, 12, 13, 15, 18 higher ranged as prescribed by WHO and Indian standard10-16.

Calcium Hardness The Calcium hardness ranged from 11.22 to 144.3mg/L The tolerance range for calcium hardness is 75 - 200 mg/L. Calcium contents in all samples collected fall within the limit prescribed. Calcium is needed for the body in small quantities, though water provides only a part of total requirements1 1.18-20 . . Magnasium Hardness Magnesium hardness ranged from 19.44 -155.42 mg/L. The tolerance range for Magnesium is 50 - 100 mg/L Sulphate Sulphate ranged from 27.14 mg/L to 384.30 mg/L. The tolerance range for sulphate is 200-400 mg/L. The high concentrations of sulphate may induce diarrhoea and intestinal disorders. Phosphate Phosphate in water occurs in the form of orthophosphate, polyphosphate and organic phosphate. In the present study phosphate ranged

PANDYA et al., Curr. World Environ., Vol. 8(1), 153-156 (2013) from 6.0 mg/L to 42 mg/L. The evaluated value of phosphate in the present study are much higher than the prescribed values 13.,22-23. The higher value of phosphate is mainly due to use of fertilizers and pesticides by the people residing in this area. If phosphate is consumed in excess, phosphine gas is produced in gastro-intestinal tract on reaction with gastric juice. This could even lead to the death of consumer. Nitrate In the study Nitrate ranged from 75 mg/L to 395.0 mg/L. The tolerance range for Nitrate 2045 mg/L. Nitrate nitrogen is one of the major constituents of organisms along with carbon and hydrogen as amino acids, proteins and organic

155

compounds present in the bore wells water 14.22-24 In the present study nitrate nitrogen levels show higher values than the prescribed values14 ,23,24. This may be due the excess use of fertilizers and pesticides in this area. ACKNOWLEDGEMENTS The Authors are thankful to the UGC for financial assistance in the form of Minor Research Project [F No. 47-511-2008[ WRO] Date : 2-2-2009] The Authors are also thankful to “The Nadiad Education Society, Nadiad and “ The Principal of J & J College of Science,” Nadiad for providing necessary facilities.

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A.K.Rana, M.J.Kharodawala, J.M.Patel, R.K.Rai B.S.Patel and H.R.Dabhi, Asian J. Chem, 14: 1209 (2002). A.K.Rana, M.J.Kharodawala , H.R.Dabhi , D.M.Suthar ,D.N.Dave, B.S.Patel, R.K.Rai, Asian J. Chem, 14: 1178 (2002). M.J.Kharodawala, D.M.Suthar ,D.N.Dave, J.M.Patel, ,B.S.Patel R.K.Rai and H.R.Dabhi Orient. J. Chem. (2004). P.A.Hamilton and D.K.Helsel Ground Water 33: 2 (1995). E.Brown, M.W.Skovgstd and M.J. Fishman Methods for Collection and Analysis of water Samples for Dissolved Minerals and Gases, 5 (1974). N. Manivasagam, Physico-chemicals Examination of water, Sewage and Industrial Effuents, Pragati Prakashan, Meerat (1984) A.I.Vogel,Text Book of Quantitative,Inorganic Analysis,4th Edn,ELBS, London (1978) APHA; American Public Health Association . Standard methods for Examination of water and waste water,16th Edn APHA –WPCE – AWWA,Washington.(1985). International Standard for drinking water,3rd Edn WHO Geneva (1971). The Gazette of India ;Extraordinary, part- II , 3: 11 (1991). A.J.Dhembare, G.M.Pondhe and C.R.Singh. Poll. Res., 17: 87 (1998).

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J.E.Mekee and H.W.Wolf, Water Quality Criteria. The Resourses Agency of California State water Quality control Board (1978). APSFSL, Andhra Pradesh State Forensic Science Laboratories, Annual Report (1988). D.G.Miller,Nitrate in Drinking Water ,Water Research Center,Medmenham (1981). NEERI;National Envirnment Engineering Research Institute,Disiafection of Small Community Water Supplies, Nagpur (1972) B.H.Mehta and M.B.Mehta Asian. J. Chem, 12: 122 (2000). S.Ghoshal,S.S.Dedalal and S.C.Lahiri J. Indian. Chem. Soc. 81: 318 (2004). S.S.Dara, Envirnmental Chemistry and Pollution Control ,S.Chand & Company ,New Delhi.P-356 (2004). J.W.White, J. Agri. Food Chem. 23: 886 (1975) B.K.Sharma and H.Kaur “Envirnmental Chemistry”publishing house Merrut (2004) BIS,Specification for drinking water IS:10500:19) Bureau of Indian standard, New Delhi (1983) Indian standard specification for drinking water, ISI, New Delhi IS: 10500 (1991). WHO (World Health Organization) Guidelines for drinkig water quality1(1984). ICMR manual of standard of quality for drinking water suppliers. ICMR, New Delhi

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PANDYA et al., Curr. World Environ., Vol. 8(1), 153-156 (2013) (1975). Chandulari Subba Rao,B sreenivasa Rao, A.V.L.N.SH. Hariharanand Manjula Bharahi. Determination of water quality index of some

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areas in Guntur District Andhra Pradesh IJAGPT 1: P-79-86(2010) D.K.Bhoi ,D.S.Raj.,Y.M.Mehta, Asian journal of Chemistry 17(1): 404-408 (2005).

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Isolation and Characterisation of Diazotrophic Bacteria from Rhizosphere of different Rice Cultivars of South Assam, India FOLGUNI LASKAR* and G.D.SHARMA Department of Life Science and Bio-Informatics, Assam University, Silchar - 788 011, India. Department of Life Sciences, Bilaspur University, Chattisgarh - 495 009, India. DOI : http://dx.doi.org/10.12944/CWE.8.1.20 (Received: March 24, 2013; Accepted: April 14, 2013) ABSTRACT Free living heterotrophic bacteria were isolated from the rhizosphere of 10 local and cultivated varieties of rice grown in Karimganj district of South Assam. Among the 25 isolates, 11 isolates withplant growth promoting activity were identified based on phenotypic and 16S rDNA sequence analysis. The strains were identified as Shingomonasa zotifigens, Pseudomonas putida, Stenotrophomonas maltophila, Acinetobacter radioresistance, Alkaligenes faecalis, Enterobacter cloaceae subsp. dissolvens, Pantoea agglomerans, Klebsiella pneumoneae, Achromobacter xyloxidans, Herbispirillum rubrisubalbicans and Herbispirillum sp. The efficient strains are isolated from the local varieties of rice plant. The isolate KR-23 (Sphingomonas azotifigens) was a novel bacteria reported for the first time as nitrogen fixing bacteria from India. The nitrogen fixing ability along with IAA production, ACC deaminase activity and P-solubilisation by the bacteria has shown their potential for plant-growth-promoting rhizobacteria. KR-6 (Stenotrophomon asmaltophila) and KR-7(Herbispirillum rubrisubalbicans) have been reported earlier as plant pathogens but they have shown a high potential for nitrogen fixing and auxin producing activity in the present study.

Key words: Nitrogen fixation; Plant growth promoting rhizobacteria; 16S rDNA sequence; Indole-3-acetic acid; ACC deaminase activity.

INTRODUCTION Free living nitrogen fixing bacteria have been considered as an alternative for inorganic nitrogen fertiliser for promoting plant growth (Ladha and Reddy, 2000; Park et al., 2004). Inspite of the fact that a variety of nitrogen fixing bacteria have been isolated from the rhizosphere of various crops, interest in isolating more beneficial plant growth promoting bacteria has increased recently due to their potential use as bio fertiliser (Vessey, 2003). Cultivated rice (Oryzasativa) originated from species of wild rice and was domesticated several thousand years ago (Hoshikawa,1989; Oka,1988; Kennedy et al., 2001). Wild rice species are likely to harbour unique populations of nitrogen-fixing bacteria that differ from those in extensively bred modern varieties of cultivated rice (Hurek et al., 2000). Production of phytohormones (Tienet al., 1979; Haahtelaet al.,

1990) and competitive suppression of plant phytopathogens (Glick, 1995, Park et al., 2004) are the beneficial effects of these microbes on plant. The agricultural soil of South Assam experience heavy annual rainfall, resulting in leaching of nutrients causing economic loss to the farmers (Anonymous, 2007). The use of bio-fertilisers may be an alternative to the chemical fertiliser for achieving sustainable rice farming while improving productivity in rice-agro ecosystem. The objective of the present study was to isolate, identify and molecular characterisation of diazotrophic bacteria from the rhizosphere of native local varieties of rice from different microhabitats of South Assam, India and characterise them for nitrogen fixation and plant growth promoting activities.

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LASKAR & SHARMA, Curr. World Environ., Vol. 8(1), 157-163 (2013) MATERIALS AND METHODS

Bacterial growth media Burk’s N-free medium comprising : 10g glucose, 0.41g KH2PO4, 0.52g Na2SO4, 0.2g CaCl2, 0.1g MgSO4.7H2O, 0.005g FeSO4.7H2O, 0.0025g Na 2MoO4.2H2O, 1.8g agar (all per litre distilled water) for semi solid and 15g agar for solid medium was used throughout the study (Wilson and Knight, 1952). The pH of the medium was adjusted to 7±0.1 before autoclaving at 1210C for 15mins Soil sample collection and isolation of diazotrophs Ten native rice cultivars grown under different microhabitats in Karimganj districts of South Assam were randomly selected. Riceplant were uprooted from a depth of 0-5cm for rhizospheric soil sampling. The samples were then immediately placed in sterilized plastic packs and sealed brought to the laboratory and stored at a temperature of 4oC. Ten grams of the rhizospheric soil sample was transferred to a 250ml of Erlenmeyer flask containing 90ml of sterile distilled water and shaken (120rpm) for 30mins. Serial dilution was made and 0.1ml aliquots (103-105) were spread on plates containing Burk’s N-free medium. The plates were incubated for 7 days at 300C. Morphologically different colonies appearing on the medium were isolated and sub-cultured for further analysis. Phenotypic characterisation of the bacterial isolates Physiological and biochemical characters of the bacterial isolates were examined according to the methods described in Bergey’s Manual of Systematic Bacteriology (Holt et al., 1994). Colour, pigment, form, diameter, elevation, margin, surface, opacity and texture of the colonies of respective isolates were observed. Motility and morphology were examined with the help of phase contrast microscopy. The gram reaction was performed as per standard protocol. Plate assays were performed for determining the starch hydrolysis, carbon source utilisation of the isolates. MR-VP test, indole test, urea hydrolysis test were also performed. 16S rDNA gene amplification and sequencing Genomic DNA was obtained by using

standard bacterial procedure (Sambrook et al., 1989; Park et al.,2004). Extraction of the lysate was done two times with chloroform to remove residual phenol. The primers used for PCR amplification of the 16s ribosomal DNA are 27F (5"-AGAGTTTGATC CTGGCTCAG-3") and 1492R (5"-TACGGTTACCT TGTTACGACTT-3") (Weisberg et al.,1999). Each PCR mixture (50µl) contained primers (at a concentration of 20pmol) a mixture of dNTP (Promega Co., Southampton, England) (at a concentration of 200µM), Taq polymerase buffer and chromosomal DNA (ca 100ng) and enzyme (4µl) were added to the reaction mixture. The thermo cycling condition consisted of an initial denaturation step at 940C for 4min, 35 amplification cycles of 940C for 1 min, 580C for 1 min and 720C for 3 min and a final extension step of 720C for 10 min with Gene-Amp PCR system (Perkin-Elmer Co., Norwalk, Conn.). PCR products were run and visualised on a 0.7% agarose gel. The 16S rDNA nucleotide sequences was determined by PCR direct sequencing using ABI PRISM 310 Genetic Analyser (PE Applied Biosystems, Foster City, CA) and Big Dye Terminator cycle system (PE Applied Biosystems). Related sequences were obtained from Genebank Database, National Centre for Biotechnology Information(NCBI) using BLAST, Version 2 (Altschul et al., 1990; Park et al.,2004).The sequences were aligned and the consensus sequences was computed using Clustal W software. The evolutionary history was inferred using the Neighbor-Joining method (Saitou N et al., 1987) and the evolutionary distances were computed using the Maximum Composite Likelihood method (Kumar S et al., 2004) MEGA version 5 (Kumar et al., 1993). Acetylene reduction assay (ARA) Nitrogenase activity of bacterial strains was determined in semisolid nitrogen free malate medium (by using acetylene reduction assay (ARA; HARDY et al. 1973). Pure bacterial colonies were inoculated on to NFM medium in McCartine vials of 10 ml capacity and incubated at 28 ± 2 °C for 48 h. Acetylene gas (10% vol/vol) was injected to the vials. After incubation for 16 h at 28 ± 2 °C, gas samples (100 ìl) were analyzed on a Hewlett Packard gas chromatograph (Model HP 6890, USA) using Porapak-N column and H2 flame ionization detector. After completion of ARA the cell were

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predigested by adding 10% SDS and sonicated briefly. Protein concentration in the resulting mixture of suspension was determined by Lowry’s method. (Lowry et al.,1951).

Statistical analysis Results of the measurements were subjected to analysis of variance (ANOVA) using SAS package, Version 8.2 (SAS, 2001).

Indole-3-acetic acid production IAA production by the isolates was determined by growing the isolates in Burk’s medium supplemented with L-tryptophan (100mg/l) at 300C. The supernatant of the culture fluid was obtained by centrifuging the stationary phase cultures at 10,000rpm for 15min and the pH was adjusted to 2.8 with 1N HCL. The auxins from the acidified cultures extracted with the equal volumes of ethyl acetate (Park et al., 2004; Tienet al., 1979) was evaporated to dryness and re-suspended in 4ml of ethanol. Analysis of the samples was done by HPLC (Water series 474, USA) using UV detector on a Nova-Pak 5-ODS C-18 column. Methanol: acetic acid: water (30:1:70 v/v/v) was used as mobile phase at a rate of 0.6mlmin-1 (Rasulet al., 1998). Pure indole-3-acetic acid (Sigma USA) was used as standard. The IAA of the samples was quantified by comparing the retention times, peak areas, and UV absorbance spectra with those of the standard using a Millenium 32 Login software with an interface (Waters, USA) attached with computer.

RESULTS

Phosphorous solubilisation Test for P-solubilisation was done following Goldstein (1986). The appearance of clearing zone around bacterial colonies after 96h of growth at 300C was used as indicator for Psolubilisation. Plates inoculated with heat killed cells served as control. ACC deaminase activity ACC deaminase activity was determined following the method described by Glick et al., 1995. For this 1 µl of each LB pure bacterial culture was inoculated into agar plates containing NFb or NFbACC modified by addition of 1-aminocyclopropane1-carboxylate (5.0 gl-1) as unique nitrogen source. Plates were incubated at 280C and observed daily for colony formation for upto 4 days. Colonies were re-inoculated and incubated in the same experimental conditions. Newly colonies formed in NFb with addition of ACC were considered positive for ACC deaminase activity.

The isolation and identification of diverse groups of diazotrophs has paved the way to decrease the costs and use of inorganic N-fertiliser as well as minimises the risk of pollution of agroecosystem from the application of chemical fertilisers. Previous researches on isolation of nitrogen fixing bacteria have revealed a broad diversity of diazotrophs associated with different crop rhizosphere (Vessey, 2003). Diverse free living or associative N2-fixing microorganisms (aerobes, facultative anaerobes, heterotrophs, phototrophs) grew in wetland rice fields and contributed to soil N. The location, variety of rice plant, soil type and ARA, IAA activity and ACC deaminase activity of different isolates from rhizosphere soil has beenshown in Table 1. Total 25 free living nitrogen fixing bacterial isolates were isolated on Burk’s nitrogen free media. The isolates were then purified and sub-cultured on solid nitrogen free medium. The ability to reduce acetylene was an indicator of nitrogen fixing potential and was specific for monitoring functional nitrogen fixing potential (Andrade et al., 1997). Out of 25 isolates, 11 were selected for their efficiency in nitrogen fixing, having ARA activity , IAA activity and ACC deaminase activity. Among all the strains KR-23 exhibited highest nitrogenise activity (300 nmolC2H4 h-1mg-1protein). Biochemical characterisation of the strains showed that all the strains were gram –ive, motile rods and having varying metabolic activities. The biochemical characteristics of all the isolates are given in Table 2. From 16S rDNA sequence analysis of the strains it was observed that ninety nine percent sequence identity was observed between the 16S rDNA sequence of KR-4 with Pseudomonas putida; KR-23 and KR-5 with Spingomonas azotifigens; KR-6 with Stenotrophomonas maltophila; KR-16 with Herbispirillum sp. KR-7 with Herbispirillum

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LASKAR & SHARMA, Curr. World Environ., Vol. 8(1), 157-163 (2013) Table 1: Plant source, isolate number, location and acetylene reduction assay of different isolates from rhizosphere of rice plant

Native rice cultivers

Bacterial Isolates

Microhabitats

Nitrogenase activity (ethylene/h/ mg protein)

IAA activity (mg/ml)

ACC deaminase activity

K1 K22 K16 K2 K18 K9 K3 K4 K5 K7 K11 K12 K15 K17 K6 K8 K23 K34 K33 K76 K28 K20 K61 K81 K19

Akbarpur Nilambajar Kanisail Nilambajar Ghoramara Akbarpur Kanisail Laxmibajar Chorgola Akbarpur Ghoramara Asimganj Patharkandi Patharkandi Asimganj Chorgola Ghoramara Kanisail Nilambajar Akbarpur Chorgola Laxmibajar Nilambajar Chorgola Asimganj

19.85±2.35 42.83±3.45 205±2.11 11.43±3.45 39.89±4.23 32.11±3.22 89.12±4.22 280±2.11 300.21±3.45 180±3.45 56.77±2.11 90.89±3.24 106.6±4.54 45.67±2.44 150±2.32 115.66±2.56 290.22±3.45 210±2.34 140.77±3.23 112±1.23 68.88±2.55 54.32±3.23 75.77±3.11 67.76±2.13 56.66±3.24

1.22±1.09 1.04±1.22 0.09±1.89 2.23±2.21 1.45±1.22 1.01±1.21 0.01±1.01 0.89±1.45 0.98±1.25 1.09±2.21 1.45±1.22 1.87±1.50 0.03±1.22 0.11±1.23 0.89±1.22 0.98±1.44 -

+ + + + + + + + + + + + -

Ranjit

Badah

Jaya Biroin

Kalijeera

Latma

Latiali

Pankaj

Each value represents mean of three replicates. The difference between the results is significant at a level of 5% significance. (P≤0.05).

Table 2: Biochemical characteristics of diazotrophic isolates Biochemical tests Indole test Voges-Proskauer test Gas production from glucose Starch hydrolysis Urea hydrolysis Nitrate reduction Catalase test Oxidase test Gelatin hydrolysis

K23

K16

K28

K18

K34

K15

K20

+ + + + -

+ + + +

+ + + -

+ + + +

+ + + + +

+ + + -

+ + + + -

+ + -

LASKAR & SHARMA, Curr. World Environ., Vol. 8(1), 157-163 (2013)

Fig. 1: Phylogenetic tree derived from analysis of the 16S rDNA sequences of Strain KR-23, KR-4, KR-6, KR-16 and KR-7 and related sequences obtained from NCBI. Scale bar, 0.02 substitutions per nucleotide position

161

162

LASKAR & SHARMA, Curr. World Environ., Vol. 8(1), 157-163 (2013)

rubris uba lbicans , KR-28 with Klebsiella pneumonia, K15 with Pantoe aagglomerans, KR34 with Acinetobacter radioresistance, KR-18 with Enterobacter cloaceae sub sp dissolvens, KR-8 with Alcaligenes faecalis and KR-20 with Achromobacter xyloxidans. Isolation of all the above bacteria were already reported from different crops by many workers (Bhromsiriet al., 2010; Sa et al. 2009; Uretaet al., 1995; Gholamiet al., 2009; Xieet al., 2006). A phenogram reflecting the relationship among the strains and candidate sequences of various nitrogen fixing strains obtained from database of NCBI has been presented in Fig 1. The sequences obtained were submitted to NCBI with accession numbers KR-4: JN222977, KR-23: JN085438, KR-5: JN085437, KR-6: JN085439, KR16:JF990839, KR-7:JF906701, KR-28:JN162393, KR-8: JN162397, KR-20: JN162396, KR-15: JN162392; KR-34: JN162392, KR-18: JN162395. DISCUSSION Plant growth promoting rhizobacteria offer an environmentally sustainable approach to increase crop production and health. The IAA production and ACC deaminase activity of the microbes help in the stimulation of growth and pathogenesis of the plants. In this study all the 11 strains produced considerable amount of IAA and are also capable of ACC deaminase activity which can be comparable to the earlier studies on various bacteria by different workers (Malik et al., 1997; Sucksstorff and Berg, 2003; Park et al., 2004; Xieet al., 2006). The amount of ARA and IAA activity and the capability of ACC deaminase activity is shown in Table 1. Among all the isolates Sphingomonas azotifigens, Pseudomonas putida, Pantoeaagglo merans, Enterobacter cloaceae sub sp. dissolvens,

Klebsiella pneumoneae and Herbispirillum sp can solubilise phosphorous. This study reports the isolation and characterisation of the strains of S.azotifigens, S. maltophila, P. putida, Herbispirillum sp., H. rubrisubalbicans, P.agglomerans, A.xyloxidans, A radioresistance, A. faecalis, E. cloaceae subsp. dissolvens and K. Pneumoneaefrom the inorganic fertiliser rich rhizosphere soil of rice agro-ecosystem of South Assam confirming their nitrogen fixing potential.

Sphingomonas azotifigens is reported from the rice fields of South Assam for the first time in India in our study. All the 11 isolates are capable of IAA production and ACC deaminaseactivity, among them some are capable of P-solubilisation. The isolates Pseudomonas putida, Sphingomonas azotifigens, Herbispirillum sp and has been regarded as PGPR in earlier studies (Gholami, 2009; Park et al., 2004; Baldaniet al., 2009), but Stenotrophomonasmaltophila and Herbispirillum rubrisubalbicans, as producer of IAA and capable of ACC deaminase is also reported first time in our study. These two bacteria are repor ted as pathogenic and endophytes in many earlier study(Reinhardt et al.,2008;Denton et al.1999; Hale et al., 1972; Gillis et al ., 1990). An increased knowledge of the role of these isolates in plant growth promotion under pot culture as well as field condition is required to prove them as plant growth promoting rhizobacteria. ACKNOWLEDGEMENTS The authors are grateful to the Head, Department of Life Science, Assam University (Silchar), India for providing laboratory facile.

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