Combine files 8(2) by Nilofar Iqbal

Current World Environment

Vol. 8(2), 165-168 (2013)

Effect of Hydraulic Retention Time and Recycle Ratio on Anoxic/Oxic Bioreactor and Artificial Wetland Performance for Domestic Wastewater Treatment JOHN LEJU CELESTINO LADU1,2*, MEILING ZHENG1, PAUL LADU DEMETRY3 and XIWU LU1 1

School of Energy and Environment, Department of Environmental Science and Engineering, Southeast University, Nanjing, 210096, P. R. China 2 College of Natural Resources and Environmental Studies, Department of Environmental Studies, University of Juba, South Sudan 3 Ministry of Environment and Sustainable Development, Republic of South Sudan http://dx.doi.org/10.12944/CWE.8.2.01 (Received: April 06, 2013; Accepted: May 14, 2013) ABSTRACT In this study, the effect of Hydraulic retention time (HRT) and recycle ratios on anoxic/oxic Bioreactor and Artificial wetland Performance for domestic wastewater treatment were experimented. Chemical Oxygen demand (COD), Ammonium nitrogen (NH4+-N), Nitrate nitrogen (NO3â&#x20AC;&#x201D;N) and Total phosphorus (TP) removal were examined. The temperature was maintained at 20 to 24 and pH ranges was 7.6 â&#x20AC;&#x201C; 8.1. The result revealed average COD removal efficiencies of 47, 68, 74, 83 and 85% at HRT of 1.5, 4, 2, 3 and 5hrs, and recycle ratios of 3, 2, and 1. Average removal of NH4+-N was 78, 85, 88 and 89 % at HRT of 5, 3, 4 and 1.5hrs and recycle ratios of 1, 2, and 3. Average removal of NO3--N was 92, 94, 95 and 97% at HRT of 2, 1.5, 3, 5 and 4hrs and recycle ratios of 3, 1 and 2. The average removal of TP was 78, 85, 88 and 89% at HRT of 5, 3, 2 and 1hr with recycle ratios of 1, 2, and 3 respectively. The system removed up to 74.1, 85%, 94.4% and 85% of the COD, NH4+-N, NO3--N and TP at different HRT, recycle ratios and with proper pH control using external source of alkalinity. The optimum recycle ratio was found to be 3. The result revealed high removal performance at increasing HRT and recycle ratios.

Key words: Hydraulic retention time (HRT), Recycle ratios; Anoxic/Oxic bioreactor; Artifical wetland; Alkalinity. INTRODUCTION China is experiencing rapid urban growth. Mounting population, industrialization, urbanization and changing life style are contributing to the random generation and disposal of wastewater which in turns pollute the water environment. Nowadays, domestic wastewater has been widely studied by many researchers using different treatment processes, either by application of highrate aerobic systems [1, 2, 3], or by application of lowrate systems [3] and vertical flow constructed wetlands [4]. Constructed wetlands are considered as an appropriate technology for treating domestic

sewage in the rural areas of China with climatic, population, and socioeconomic considerations [5]. To meet the standard effluent quality discharge of China, integrated A/O system and constructed wetlands was used and considered to be the best option for domestic wastewater treatment. MATERIALS AND METHODS Experimental set-up The experimental system was made up of an influent tank, pumps (model BT100), the integrated A/O system and artificial wetlands, an air compressor for aeration and automatic aeration

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mixers to provide aeration in the oxic zones. The anoxic reactor has a total effective volume of 60 L and the oxic reactor has three segments with a total capacity of 27L. The reactor was connected in series with an internal diameter of 0.2m and a height of 2m for the anoxic columns. The oxic column has width size of 30cm and effective depth of 10cm, 20 and 30cm for first, second and third oxic segment. The height difference between each adjacent unit of Oxic is 0.5m. The domestic sewage drops to some porous baffles after it was pumped to a certain height. Both of the reactorâ&#x20AC;&#x2122;s columns (A/O) were filled with a non-woven fabric filter materials. The artificial wetland has a plot area of 1.2m2 and bottom slope of 0.003%. Each chamber was composed of three different layers of matrix particles of different sizes: the 200mm layer of coarse gravel (20 to 40mm in diameter) and the 250 mm layer of grit gravel in the bottom, in the upper is a 100mm layer of fine sand (0.5-1.2 mm in diameter). The artificial wetland was planted with Chinese celery (Oenanthe javanica). Temperature was maintained in the range of 20 to 26. Wastewater for the experiment and Analytical Procedures Raw wastewater from a campus main manhole was pumped into a storing tank for sedimentation and then fed into the reactor. The A/ O reactor was inoculated with sludge obtained from Wuxi municipal sewage treatment plant. The raw domestic wastewater composition is shown in Table 1. The influent and effluent samples were collected in separate bottles after every two days and stored in refrigerator at 4oC before experimental tests. The internal recycle ratio, R, can be defined as the ratio of returned flow rate (Qr) to that of the main influent flow rate (Q0). All the analyses were carried out in accordance to6. The influent and the effluent COD, NH4+-N, NO3--N and TP were measured according to7.

respectively. It can be noted that, COD removal efficiency increases with increase in HRT (fig. 1 (a)). The overall removal efficiency of COD was 70.4%. This result obtained is quite similar to the study conducted by [8, 9]. In this study, the average removal of COD was 42, 68, 74, 83, and 85% with effluent concentration of 34, 17.5, 11.7, 7.7 and 15.9mg/l under HRT of 1.5, 4, 2, 3 and 5hrs, with recycle ratios of 3, 2 and 1 respectively. NH4+-N and NO3--N removal The overall removal of NH 4+-N by the reactor was 85% quite similar to that obtained by [8]. The average concentrations of NH 4+ -N in the influent, anoxic oxic and artificial wetland during the experimental operations were 11, 2.4, 1.1 and 1.5mg/L respectively. The average removal of NH4+N were 78, 85, 85, 88 and 89 % with effluent concentration of 1.9, 1.2, 1.3, 2.1 and 1.2mg/l operated with HRT of 5, 3, 2, 4 and 1hr respectively (fig. 1(b)). According to literatures and a study by [10] , the optimum pH condition for nitrifying bacteria is 7.5 to 8.6. For this study, the value of pH was maintained between the ranges of 7.6 to 8.1 indicating satisfactory condition of the reactor. In order for simultaneous nitrification and denitrification to take place in the anoxic reactor, the reactor was intermittently aerated. The average DO concentration in the reactor was in range of 2.2 to 3.1 mg O2/l, respectively. During the operation, there was high concentration NO 3 - -N in the effluent of the nitrification reactor (oxic). The overall removal of NO 3 --N by the system was 94%. The average removal of NO3--N was 92, 94, 94 and 97% with effluent concentration of 0.3, 0.2and 0.5mg/l operated with HRT of 2, 3, 5and 4hrs and recycle ratios of 2, 3, and 1 respectively (fig. 1 (c)). Increase Table 1: Composition of the studied area domestic raw wastewater Parameter

Min

Max

COD (mg/L) NH4+-N (mg/L) NO3--N (mg/L) TP pH

56.2 7.13 3.4 2.9 7.7

148.1 24.99 6.2 5.4 8.2

Average

RESULTS AND DISCUSSION Organic material removal (COD) The average concentrations of COD in the influent and effluent during the experimental operations were 91.1mg/L and 17.4mg/L

92.5 11.04 4.8 3.8 7.9

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(a)

(b)

(c)

(d)

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Fig. 1: Effect of HRT on removal efficiency of (a) average COD, (b) average NH4+-N, (c) average NO3â&#x20AC;&#x201D;N and (d) average TP concentration in the influent, anoxic, oxic reactors and artificial wetland

in recycle ratio (R) enhances the denitrification efficiency of A/O but according to [11], high increase of recycle ratio also inhibits denitrification.

steadily during the winter season, TP removal wasnâ&#x20AC;&#x2122;t affected. CONCLUSIONS

Total phosphorus removal The removal of TP was quite stable despite the concentration of TP in the influent was ranging between 2.9mg/l to 4.5mg/l. The effluent TP was mostly below 0.5 mg/. Most of the TP removal was accomplished in artificial wetland. The overall removal efficiency was 83%. The average removal of TP was 78, 85, 88 and 89% with influent and effluent concentration of 4.3, 3.5, 4.5, 2.9, 3.8mg/l and 0.5, 0.6, 0.7, 0.5 and 0.8mg/l operated with HRT of 5, 3, 2, and 1hr with recycle ratios of 3, 2 and 1 respectively (fig. 1(d)). Although temperature fluctuates and reed in the artificial wetland withered

This study used A/O and constructed wetland for treatment of campus domestic wastewater at different operating condition. According to the result obtained during the whole experimental operation, the A/O reactor and constructed wetland emerge to be well suited to the treatment of this kind of low strength campus domestic wastewater. Since heterotroph uses organic substrates as a source of carbon, heterotrophic denitrification is responsible for COD degradation. In the constructed wetland, most of the TP removal was accomplished by medium

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interception, microbial transformation and plant adsorption. The result obtained revealed that, the A/O reactor and constructed wetland is suitable and efficient in organic matter and nutrient removal

ACKNOWLEDGMENTS This research has been supported by the National Natural Science Foundation of China (51078074) and the Key Project of Chinese Ministry of Education (308010).

REFERENCES 1.

Nolde, E., Greywater reuse systems for toilet flushing in multi-storey building-over ten years experience in Berlin. Urban Water 1: 275–284 (1999). Jefferson, B., Laine, A.L., Judd, S.J., Stephenson, T., Membrane bioreactors and their role in wastewater reuse. Water Sci. Tech. 41(1): 197–204 (2000). Jefferson, B., Laine, A., Parsons, S., Stephenson, T., Judd, S., Technologies for domestic wastewater recycling. Urban Water 1: 285–292 (1999). Otterpohl, R., Braun, U., Oldenburg, M., Innovative technologies for decentralised water, wastewater and biowaste management in urban and peri-urban areas. Water Sci. Technol. 48(11/12): 23–32 (2003). Min Tao, et al., How Artificial Aeration Improved Sewage Treatment of an Integrated Vertical-Flow Constructed Wetland. Polish J. of Environ. Stud. Vol. 19(1): 183-191 (2010). CJT 221. Determination method for municipal sludge in wastewater treatment plant[S] (2005). APHA. Standard Methods for the

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Examination of Water and Wastewater, 19th ed. WashingtonDC, Amer Public Health Assoc, 1995 (1999). Gurung, A., Kang, W.Chang and Oh SangEun. Removal of nitrogen from anaerobically digested swine wastewater using an anoxic/ oxic (A/O) process complemented with a sulfur-packed biofilter African Journal of Biotechnology. 10(48): 9831-9838 (2011) Chul Hee Won and Jay Myoung Rim, Anaerobic/oxic Treatment of Slurry-type Swine Waste, Environ. Eng. Res. 13(4): pp. 203~209 (2008) Yoo H, Ahn KH, Lee HJ, Lee KH, Kwak YJ, Song KG., Nitrogen removal from synthetic wastewater by simultaneous nitrification and denitrification (SND) via nitrite in an intermittently aerated reactor. Water Res. 33: 145-154 (1999). Tan TW, Ng HY., Influence of mixed liquor recycle ratio and dissolved oxygen on performance of pre-denitrification submerged membrane bioreactors. Water Res. 42: 1122-1132 (2008).

Current World Environment

Vol. 8(2), 169-178 (2013)

Sodium Adsorption Ratio (SAR) Prediction of the Chalghazi River Using Artificial Neural Network (ANN) Iran GHOLAMREZA ASADOLLAHFARDI1* , AZADEH HEMATI2 , SABER MORADINEJAD1 and RASHIN ASADOLLAHFARDI3 1

Civil Engineering Department, Kharazmi University, Tehran Iran. 2 Semnan Regional Water Company, Semnan, Iran. 3 Civil company, Vancouver, Canada. http://dx.doi.org/10.12944/CWE.8.2.02 (Received: April 25, 2013; Accepted: June 12, 2013) ABSTRACT

Considering the significance of the Sodium Adsorption Ratio (SAR) for growing plants, its prediction is essential for water quality management for irrigation. The SAR prediction in Chelghazy River in Kurdistan, northwest of Iran, using an Artificial Neural Network (ANN) was studied. The study applied the Multilayer Perceptron (MLP) of the ANN to average monthly data, which was collected by the water authority of the Kurdistan province for the period of 1998-2009. The input parameters of the MLP network was pH, discharge, sulfate, sodium, calcium, chloride, magnesium and bicarbonate, and output was predictive of the SAR. The results showed a correlation coefficient 0.976 between actual and predicted SAR, which means the accuracy of the model is acceptable. The model uses the input parameters to predict the SAR at the same month. The sensitivity analysis indicated the prediction of the SAR was affected by merely pH and calcium. As a whole, the MLP of the ANN may be applicable for prediction of the SAR which is necessary parameter ration for agriculture.

Key words: Artificial neural network (ANN), Sodium Adsorption Ratio (SAR); Chalghazi River, Root Mean Squared Error (RMSE). INTRODUCTION Water quality management is the surface water and groundwater quality control at any time for supplying water at a required quality for a specific use. Long-term strategies for national water resources development in a country is based on water supply, demand management, water reform, compliance with environmental aspects, and finally management of the water consumerâ&#x20AC;&#x2122;s activities. Identifying and estimating the basic parameters which affect the quality of water resources helps in implementing policies and strategies. River quality control requires additional investment for wastewater treatment and collection systems. On the other hand, it may lead to restricted development in the basin and could have a significant economic impact. For water quality control it is necessary to know physical, chemical and biological characteristics of the river. To reach

this objective, it is necessary to have proper monitoring of water quality. Having enough data without proper interpretation cannot help water quality management adequately. There are several methods for analyzing water quality data, such as statistical models, deterministic models and artificial neural models Asadollahfardi et al. (2011 - 2012) . Dogan et al. (2007) used the ANN to forecast BOD concentration using data from eleven stations on the Melen River in 2001-2002, including COD, temperature, DO, chlorophyll-a, ammonia, nitrite and nitrate. They concluded that the ANN model provides a reasonable estimate for BOD parameter. Singh et al. (2009) applied the ANN to predict dissolved oxygen and BOD using ten years of data at eight different stations in India. The input of the model consisted of eleven monthly water quality parameters, and the predictions and actual data had a good agreement. Huang and Foo (2002) applied the ANN for the assessment of the variation

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of water salinity in the Apalachicola River in Florida. They employed part of existing data for testing and the remainder of the data for the validity of the ANN model. Maier and Dandy (2002) reported 41 successful case studies of prediction of water changing, which uses the MLP neural. Coppola et al. (2003) described the successful application of the technology for three kinds of management and underground water prediction. In the first instance, an ANN was trained by simulation of data collected from a numerical model based on physical data in the appropriate places, with various pumping and climate conditions. The ANN obtained a high precision for forecasting, and its altering statue equations were substituted in the multipurpose optimal formula. In the second and third instances, the ANNs were developed according to climate and hydrology real data for the different environmental hydrology conditions. For the second problem, an ANN was developed using the information collected over five years and eight months and under various climates and pumping conditions to predict the heights in a limestone and ice layer under the multi-layer soil. Misaghi et al. (2003) studied water quality in the Zayandeh Rud River applying a General Regression Neural Network (GRNN) for ten years of BOD and DO. Musavi-Jahromi and Golabi (2008) applied the ANN to monthly water quality of the Karoon River, Iran, using CO, HCO3-, SO4, CL, Na, Ca, Mg and K as inputs and TDS, EC and SAR as outputs. Their results were satisfactory. Kanani et al. (2008) studied water quality in the Achechay River, but they selected a water quality monitoring station and applied MLP and Input Delay Neural Network (IDNN) models. They predicted TDS parameters using discharge as input data to the models. Olyaie et al. (2010) employed the MLP model with water quality parameters including BOD and DO in Hamadan Morad Beik River. Their outcome was satisfactory. Asadollahfardi et al. (2010) applied the MLP model to total phosphor and total nitrogen data in an Anzaliy Wetland (Iran) study and obtained acceptable prediction for eutrophication in the wetland. Asadollahfardi et al. (2012) applied the MLP and Elman dynamic of the ANN to two stations of Talkheh Rud River and predicted TDS of the river one month in advance, and the results were acceptable. Generally for

assessment of the dispersion risk of irrigation water it is significant to consider the ratio of sodium to other exchangeable cations on soil colloids. High sodium ions in water affect the permeability of the soil and cause of infiltration problems. When sodium exists in the soil in an exchangeable form, it replaces the calcium and magnesium absorbed on the soil clays and causes dispersion of soil particles. The SAR has a proper criterion for irrigation water suitability. If calcium and magnesium are the predominant cations absorbed on the soil exchange complex, the soil tends to be easily cultivated and has a permeable and granular structure Asadollahfardi et al. (2010). Zhang and Stanley (1997) using the artificial neural network (ANN) modeling technique were used to establish a model for forecasting the rawwater coloring in a large river. In this research the potential applications of ANN in the water treatment industry are also discussed. Results indicate that the ANN modeling scheme shows much promise for water quality modeling and process control in water treatment. Keiner and Yan (1998) studied sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery using neural network models. It was found that a neural network with two hidden nodes, using the three visible Landsat Thematic Mapper bands as inputs, was able to model the transfer function to a much higher accurately than multiple regression analysis. The RMS errors for the neural network were <10%, while the errors in regression analysis were >25%. Zhang et al. (2002) studied water quality in the Gulf of Finland using an empirical neural network and combined optical data and microwave data. The results showed that the estimation accuracy of the major characteristics of surface waters using the neural network is much better than those from the regression analysis. The study area is a part of the Sirwan Basin with a total area about 105,000 hectares which contain 3.8% of the Kurdistan provincial area. The north of the basin is surrounded by the Sefed River catchment area, east of the area is the Ghaveh River, and west of the area has a common boundary with the Seravan River. The catchment is located between 46째, 46', 40" and 47째, 20', 00" East longitude and 35째, 24', 44" and 35째, 43', 23" North latitude (Figure 1).

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The height of the area varies from 1500 to 2900 meters. All of the surface runoff of the basin is collected by the Chelghazy and Khalefeh Tar Khan main river (Mohammady and Fathi, 2004). Figure 1 shows the study area. The weather conditions of the basin are similar to subtropical dry region weather. Its winters are cold; its summers are relatively warm and dry, and its rainy season is from October to May. The average annual minimum and maximum temperatures between 1990 and 2005 were 6.3 and 21.8 degrees Centigrade, respectively. The average annual minimum and maximum humidity between 1990 and 2005 was 26.7% and 21.8%, respectively. The annual total rainfall was 395 mm, Islamic Republic of Iran Meteorological Organization (1983). The basin is part of the Kurdistan Province, which is geologically quite active. The land straddles the seduction zone between the colliding Eurasian and African tectonic plates. Locally, the breakaway Arabian micro plate is being sub ducted under the Iranian and Anatolian Micro plates at the rate of a few inches a year, and as a result the Zagros mountains and Kurdistan— the point of this collision—are being compressed and pushed upward several inches a year (Hooshmand Zadeh, 1995).

pkc=solubility constant for calcite; and p=negative logarithm of ion concentration (meq/L). The amount of p (k2-KC), p (Ca+Mg) and p (Alk) related to Ca +++Mg ++ +Na + , Ca +++Mg ++ and CO 3-- +HCO 3 -respectively can be found in Bouwer (1974).

The high concentration of sodium in irrigation water may negatively affect the soil structure and decrease the soil hydraulic conductivity in fine-textured soil. The degree to which sodium will be absorbed by a soil is a function of the amount of sodium to divalent cations(Ca and Mg) and is regularly stated by the sodium adsorption ratio(SAR) (Bouwer and Idelovitch 1987). The SAR is a general water quality index that indicates the percentage of sodium in the water and function of the ratio of sodium to divalent cations such as Ca and Mg. The SAR parameter is obtained from the Eq. (1). (Asadollahfardi et al. 2011):

Methodology The ANN is a data processing system, based on an idea similar to the processing of the human brain that treats data as a steady network parallel to each other in order to solve a problem. With the networks, the structure of data is designed to help programming knowledge in which the behavior is the same as natural neural and its component. An artificial neural system consists of three components, including weighting (W), bias (b) and transfer function (f). These three components are unique to each neural system. In Figure 2, “p” and “n” equal input and output while “a” equal net input. The junctions of 1 and 2 in Figure 2 show the schematic of the artificial neural system. The function of artificial neural network would be called “p”.

...(1) SARadj=SAR[9.4-p(k2-kc)-p(Ca+Mg)-p(Alk)] ...(2) Where pk2=negative logarithm of the second dissociation constant for carbonic acid;

The adjusted SARadj value typically is computed, which take into account the effects of rainfall. Sodium also has adverse effects on the crops such as leaf burn in almond, avocado, and stone fruits (Bouwer and Idelovitch 1987). Ayers and Tangi (1981) suggested that whether the SARadj water for irrigation is below 3, there are no sodium problems if the SAR is between 3 and 9 there are increasing problem and whether the SAR is above 9, there are severe problems. The first objective of this study was set to develop an ANN-based prediction model for monthly SAR. Development of the model uses the discharge, sodium, calcium, magnesium, chloride, sulfate, bicarbonate, pH and SAR data for a station of the Chalgazi River Basin in the Kurdistan Province, which were collected from the Water Authority of Kurdistan. The second aim was using sensitivity analysis to find out which of the mentioned parameters were significant in the prediction of the SAR.

...(3) ..(4)

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The MLP is a static neural network which has three layers including an input layer, hidden layer and output layer. Figure 2 shows the schematic of the ANN. Figure 3 shows schematically tangent – sigmoid transfer function and linear transfer function. Number of neurons in the hidden layers for each model may be obtained using trial and error. The function of the network can be modeled by equations 5 and 6 (Menhaj, 1998): 1 j

R i=1

a (t) =F{Σ

1 j,i i

w p (t)+b j}

a2k(t) =G {Σs1j=1 w2k,j aJ1(t)+b2k }

...(5) ...(6)

Where, R = numbers of input vector components. S1 and S2 = numbers of neurons in hidden and output layers, respectively. P = input vector. W1 and W2 = weighting matrix in hidden and output layers, respectively. b1 and b2 = bias vectors in hidden and output layers, respectively. G and F = neuron transfer functions in hidden and output layers, respectively (Menhaj and Safepoor. 1998). For assessment of water quality, we applied the MLP model using average monthly data. According to the Universal Approximator, each multi-layer Perceptron of the ANN with a sigmoid hidden layer and a linear output layer is able to predict each complicated function if the number of neurons is selected precisely (Cybenko, 1989; Hornik, 1991, 1993; Leshno et 1993). This theory decreases the number of hidden layers to the least and decreases the complexity of the network. According to the mentioned theory, all models applied in this research are the MLP with a hidden layer, tangent sigmoid transfer function and linear layer outputs. Figure 4 illustrates the MLP neural network schematic. For calculation of the amount of error in predicting the desired parameter and performance evaluation of models, we used R2 and Root Mean Squared Error (RMSE), as shown in Equations 7 and 8 (Kennedy and Neville, 1964).

( ∑ ( X − X )(Y − Y )) = ∑ ( X − X ) (Y − Y ) i

...(7)

...(8)

Where Xi, Yi, X and Y = the measured data, predicted data, the average of measured data and the mean of predicted data, respectively (Preis et al, 2008; Singh, 2009). The statistical summary of the data is shown in Table 1. Learning Rate There is a parameter called the learning rate in the training algorithm of back propagation, which is on the basis of the steepest descent. Its objective is to minimize the sum square error of outputs. The learning rate is indicated by a symbol á and determines the velocity of convergence in this algorithm. The performance of the steepest descent algorithm is enhanced if the learning rate is allowed to alter during the training process. Maier and Dandy (2000), in a review , studied Neural networks for the prediction and forecasting of water resource variables .They stated that in a review of 43 papers dealing with the use of neural network models for the prediction and forecasting of water resources variables are undertaken in terms of the modeling process adopted and at the vast majority of these networks was trained using the back propagation algorithm. RESULTS AND DISCUSSION The MLP model was used for the twelve years monthly (period 1998-2010) data of the Chalgazi River which was collected by Water Authorities of Kurdistan province, Iran. As mentioned previously, according to the universal approximator number of hidden layer decrease to a hidden layer. The rate of the network efficiency depends on applying the appropriate number of neural in the hidden layer. Table 1 indicates a statistical summary of the data that was used in this study. The input layer of the model consisted of eight parameters, including the amounts of sodium, magnesium, calcium, sulfate, chloride, bicarbonate, pH and discharge, which were applied simultaneously, and the output was the SAR. 70% of the data was used for training, 5% for validation and 25% was used for testing of the model. Because

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network. As shown in the both tables, the minimum rate of RMSE occurred while we applied three neurons in a hidden layer. Figure 6 shows the actual and the forecasted SAR. Considering the figure, there is good conformity between the actual and the predicted data, and the correlation coefficient was R2 = 0. 9757. Hence, the developed model may apply for the SAR prediction in water quality management. Comparing the results of this study with the work of Musavi-Jahromi and Golabi (2008) in Karoon River, Iran, there are similarities and

of the importance of training most of data should be used as training data. The RSME errors while it used a different number of neurons in a hidden layer for training, testing and total, as shown in Tables 2. Table 2 shows the result of using a different number of neurons in the hidden layer while sodium, magnesium, calcium, sulfate, chloride, bicarbonate, pH and discharge were used as inputs simultaneously, and the SAR was an output of the

Table 1: A statistical summary of different parameter data applied in this study Statistical summary

Na Mg/L

Mg Mg/L

Ca Mg/L

SO4 Mg/L

Cl Mg/L

HCO3-Mg/L

pH Mg/L

Q M/S

SARadj Mg/L

Maximum Minimum Mean Standard Deviation

1.41 0.18 0.50 0.38

4.42 0.21 0.955 0.81

6.64 1.49 3.481 3.22

1.65 0.05 0.359 0.34

0.85 0.06 0.229 0.2

1.66 5.25 2.47 1.69

8.9 7.7 6.04 3.8

62.2 0.02 7.08 61.1

419 115 196.5 133.9

Table 2: The rate of RMSE error for prediction of SAR using neuron 2 to 20 in the hidden layer Number of neurons

Training Testing Total Number of neurons Training Testing Total

0.0108 0.010 0.0113 0.0116 0.0118 0.0117 0.0114 0.0118 0.012 0.0117 0.0245 0.0240 0.0242 0.0247 0.0248 0.0248 0.0243 0.0245 0.024 0.0249 0.0176 0.0173 0.0175 0.0179 0.0174 0.0182 0.0181 0.0179 0.018 0.0181 12 13 14 15 16 17 18 19 20 0.0120 0.0121 0.0121 0.0120 0.0246 0.0244 0.0244 0.0244 0.01828 0.01832 0.01814 0.0182

0.0120 0.0120 0.0120 0.0121 0.0121 0.0244 0.0244 0.0241 0.0242 0.0241 0.01831 0.01841 0.0182 0.01821 0.01838

Table 3: Summary of sensitivity analysis (Correlation Coefficient) for each input parameter Parameters

+10%

No Changing Data

-10%

pH Ca+2 Q Cl-1 HCO-3 Mg+2 SO4-2 Na+

0.0239 0.9938 0.994 0.9939 0.9937 0.9937 0.9936 0.9938

0.9939 0.9937 0.9943 0.9937 0.9937 0.9937 0.9941 0.9938

0.9937 0.9261 0.9937 0.9938 0.9941 0.9937 0.9939 0.994

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agreement between the two results, which confirm the suitability of the ANN model to predict the SAR in river water quality. The differences between the two works are: (1) we gave evidence for using a hidden layer and clearly mentioned type of the model which we applied, and (2) it was evaluated

which of the input parameters were significant to forecast the SAR by use of sensitivity analysis. They worked for several water quality monitoring stations, yet in the Chalghazi River there are not as many monitoring stations.

Fig. 1: The map of the study area

Fig. 2: The schematic of the Artificial Neural Network (ANN)

Fig. 3: Transfer function Tangent Sigmoid

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Fig. 4: Multi-layered Neural Network schematic

Fig. 5: Comparison of the actual and the forecasted the SAR for period 1998-2010

Fig. 6: The normal plot between observed and predicted the SAR under changing pH

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Fig. 7: The normal plot between observed and predicted the SARadj under changing Ca+2 Katoozian et al. (2011) applied the ANN model to Chalghazy and Ghashlagh River water quality parameters using data in the period 19892003. The input parameters, which they applied, included EC, discharge, pH and rainfall of two mentioned stations, and they predicted the SAR. The maximum correlation coefficient between predicted and actual SAR was 0.8113. They did not carry out sensitivity analysis. The main advantage and differences between this study and the work of Katoozian et al. (2011) are: 1. Data for this study belonged to the period 1998-2009, 2. The input parameters to the MLP were rate of flow, pH , Ca, Na, SO4, bicarbonate, chloride and magnesium 3. The correlation coefficient between prediction and actual SAR was 0.9757, and the minimum RMSE in training, testing and total were 0.0113, 0.0242 and 0.0175, respectively, in three neurons in the hidden layer. 4. Sensitivity analysis was done in this work, which was not done at work of Katoozian et al. (2011) Figure 5 showed Comparison between actual and predicted SAR, as shown actual and predicted SAR are close together. Sensitivity analysis To assess the effect of each input

parameter to the result of the SAR prediction, we increased or declined 10% of one of the input parameters while the other was kept unchanged; then the role of variation of each parameter in prediction of the SAR was identified. We drew the normal plot between the observed and the predicted data for the SAR after changing each input parameter. Figures 6 and 7 indicate the results of the normal plot between the observed and the predicted SAR while each input parameter was changed 10%. The prediction of the SAR was affected only by two of the parameters including pH and Ca, while the other parametersâ&#x20AC;&#x2122; effects were not considerable. As indicated in Figure 6, the correlation coefficient for altering pH is 0.0239. This means that the pH has a significant affect on the SAR prediction, however, the discharge, sodium, magnesium, sulfate, chloride; bicarbonate did not affect the prediction noticeably. It may show that the role of the discharge to the SAR perfection is not vital. Figure 7 shows the normal plot for the variation of calcium, as shown in the figure, R2 =0. 92, which means that the calcium has an effect on the SAR prediction; however, the effects are less than the pH variation. Summary of the sensitivity analysis for each input parameter are summarized in Table 3. CONCLUSION Taking into consideration the results and discussions of the applied MLP networks with different neural combinations, the following

ASADOLLAHFARDI, Curr. World Environ., Vol. 8(2), 169-178 (2013) conclusions can be made: (i) The MLP network is adequate for estimation of the SAR prediction, and its accuracy is precise and applicable. (ii) The minimum RSME error during training, testing and total was 0.01 when applying the MLP network using 3 neural in the hidden layer.

(iii)

(iv)

(v)

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The correlation coefficient between actual and predicted data is 0.9757, which may show the modelâ&#x20AC;&#x2122;s prediction accuracy. The results of sensitivity analysis show pH and calcium parameters are sensitive for prediction of the SAR. The outcomes and model may be applicable for water quality management for planning of agricultural water usage.

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Asadollahfardi G. Khodadadi A. and Gharayloo R., The assessment of effective factors on Anzali wetland pollution using artificial neural network. Asian j 7(2): 23-30 (2010). Asadollahfardi G. and Asadollahfardi R., The usage of polluted water for agriculture. ISSN: 976-3-8465-1196-1, Lambert academic publishing, Germany (2011). Asadollahfardi G. Taklify A. and Ghanbari A., Application of Artificial Neural Network to predict TDS in Talkheh Rud River. Journal of Irrigation and Drainage Egngeering, 363370, DOI:10.1061 (ASCE) IR, 19434774.0000402 (2012). Ayers R.S.and Tanji K. K., Agronomic aspects of crop irrigation with wastewater , Pro. water Forum 81,1, ASCE, New York N.Y.pp 579586 (1981). Bouwer H. and Idelovitch E., quality requirement for irrigation with sewer water, j. Irrigation. Drainage. Engineering , 113 (4), 516-535. Bouwer H., Wastewater reuse in arid area water reuse,E.J.Middlebrook,ed,Ann Arbor science publisher, Inc.Ann Arbor, Mich. , pp 137-180 (1976). Cybenko G., Approximation by superposition of a sigmoid function. Math Control signals system j, 2: 303-314 (1989). Coppola E. Poulton M. Charles E. Dustman J. and Szidarovsky F., Application of artificial neural networks to complex ground water management problems. Natural resources research j, 12(4): 303-320 (2003). Dogan E. Sengorur B., Modelling biological

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Current World Environment

Vol. 8(2), 179-187 (2013)

Air Microbial Contamination at the Holy Mosque, Makkah, Saudi Arabia A.A.ABDEL HAMEED* and T. HABEEBALLAH Department of Environmental and Health Research, The custodian of the Two Holy Mosques, Institute for Hajj and Umrah, Umm-Al Qura University, Saudi Arabia - 21955 http://dx.doi.org/10.12944/CWE.8.2.03 (Received: July 15, 2013; Accepted: August 20, 2013) ABSTRACT Airborne microbial contamination was collected from the main directions of the holy mosque (Al-Haram mosque), Makkah city, by using the gravitational method.Bacteria, fungi and actinomycete concentrations ranged between 1470 - 21800 CFU/m3; 44 - 572 CFU/m3, and 0.0 - 264 CFU/m3, respectively at all directions. Bacterial concentrations significantly differed between directions, and Gram positive bacteria constituted ~ 90-100% of the total bacterial isolates. Gammaproteo bacteria were the common Gram negative bacteria, and Aspergillus was the predominant fungal genera. Mesophilic bacteria negatively related (P< 0.05) with relative humidity. Human activities had more effective influence on the microbial concentrations than the meteorological factors.

Key words: Air, Biocontamination, Directions, Biodiversity, The holy mosque, Makkah.

INTRODUCTION Atmospheric particles of biological origin are diverse group of microorganisms and their execrations. Airborne microorganisms originate from many sources: animal, human, and vegetation. The number and composition of airborne microorganisms have increased in the urban and rural areas 1.The presence of microorganisms depends on seasonality, geographical conditions, meteorological factors, type of sources2, 3 4, and air pollution5.Airborne microorganisms may contribute ~ 20%, 22% and 10% of the total particulate matters in the remote continental, populated-continental, and remote maritime environments, respectively6. The concentrations and composition of airborne microorganisms undergoes daily, weekly and seasonally changes7. Millions of people arrive to the Holy City, Makkah city, particularly in the Ramadan month,the fasting month, every year. Microbial contamination represents a dangerous risk factor in many human activities areas8, as airborne microorganisms cause allergy, infections, and toxicity9,10. Some studies

have been carried out on microbial contamination in the atmosphere of Saudi Arabia cities: such as Riyadh11, Hofuf12, Makkah13, and Taief14. However few studies have been performed on the airborne microorganisms in the area near and around the holy mosque. The results showed that microbial concentrations differed depending on methodology and sampling location15, 16. Until now no complementary studies have dealt with airborne microbial community at the main directions of the holy mosque that may be differed in their human activitiesand topographical features. The evaluation of microbial contamination, in places at risk, is considered a basic step toward prevention and control. The present study aims to gain more insight into the variability of airborne bacteria, fungi, and actinomycetes at the main directions of the holy mosque, in order to determine its microbial air quality and give site specific information. MATERIALS AND METHODS Site description The Holy City,Makkah, is located at an

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altitude of 277 m, 21°29' N 39°45' E, and ~ 80 km inland from the Red Sea, with a population of ~2,000, 00017. The area around the holy mosque comprises the old city; which is characterized by heavy traffic, parking, hotels, and hospitals with no predominant plant cover. Four sampling sites were selected to carry out the present study. Air samples were collected at the main directions (North, South, West and East) of the holy mosque (Fig. 1), in order to represent various geographical features and human activities. A brief summary of the general human activities and environmental characteristics at each direction are shown in Table 1. During every sampling event, temperature and relative humidity were measured using a portable Psychrometer (Extech -model 42270, China), adjusted to record data at every 10 min intervals. Temperatures ranged between 27– 35oC with mean values of 30.3 oC, 29.6 oC, 31.4oC and 30.8 oC at the North, South, East, and West, respectively. Relative humidity ranged between 32– 63% with mean values of 38.7%, 43%, 34% and 42% at the corresponding directions, respectively. Wind speed records were obtained from The Presidency of Meteorology and Environment, Makkah. The wind speed ranged between 0.5 to 1.5 m/s, with north-east was the prevailing wind direction. Sampling strategy A total of 16 samples were collected between 19 th to 27 th days of Ramadan (7-15, August, 2012). Two consecutive samples were collected every sampling event. Air samples were collected at ~1 - 3 m height above the ground level, between 19.00 PM and 24.00 AM, the night time. This time was chosen because it is the time of the overcrowding in the holy mosque during the Ramadan month. The gravitational method was used to collect airborne culturable microorganisms. The Petri plates, in triplicate, containing trypticase soya agar, czapek’s dox agar, and starch casein agar (Hi-Media Laboratories, Mumbai, India) media were used to collect bacteria, fungi and actinomycetes, respectively. The sampling time varied within 10-20-min. The exposed plates were incubated for 5– 7 days at 28oC for fungi; 48 hrs at 22 and 37 oC for psychophilic, and mesophilic bacteria; respectively, and 10 days at 25 oC for actinomycetes.

The resultant colonies were counted and converted into colony forming unit per cubic meter of air (CFU/m3) using Omeliansky formula18: N=5a x 104 (bt)-1

Where: N=colony forming unit per cubic meter of air (CFU/m3) a= number of colonies per Petri dish, b=dish square centimeter, t= exposure time (min). All the grown fungal colonies, and five to ten bacterial colonies which appear in more than 5% of trypticase soya agar were purified and identified to the genus level. Aspergillus was identified to the species level. The bacterial isolates were identified on the basis of Gram stain, oxidase, and catalase tests19. Fungal isolates were identified using macroscopic and microscopic features20-23. Statistical analysis Data was analyzed using the non parametric statics. The kruskal Wallis test was used to compare microbial contamination at the different directions (p<0.05), followed by post hoc test (Student t-test). The assumption for this test is that the samples from different groups are randomly independent.Spearman’s rank correlation test (rs) was used to determine the relationships between microbial concentrations and meteorological factors. RESULTS The range and mean concentrations of airborne culturable microorganisms at the main directions of the holy mosque are shown in Table 2. The bacterial concentrations ranged between 1470- 21800 CFU/m3, with mesophilic bacterial concentrations exceeded psychophilic concentrations. The highest bacterial concentration was found at the north direction, and the lowest at the East. Fungal concentrations ranged between 44 - 572 CFU/m3, with the highest concentrations were found at the North and West directions. Airborne actinomycete concentrations were found in the range of 0-264 CFU/m3 (Table 2). Mesophilic and psychophilic bacterial concentrations significantly differed between the all directions (P<0.05), however fungi and actinomycete

HAMEED & HABEEBALLAH, Curr. World Environ., Vol. 8(2), 179-187 (2013) concentrations did not show any significant differences. A total of 502 bacterial isolates belonging to 11 genera were identified (Fig. 2). Gram positive and negative bacteria constituted 90-100% and 2.4

181

- 9.4%, respectively of the total isolates. Staphylococci (4.2-26%), and Bacillus (5.5- 30.9%) were the dominant Gram positive bacteria. Streptococci and spore-formers were only detected at the north and south directions, respectively. Gammaproteobacteria (Pseudomonas) constituted

Table 1: A brief description of the environmental features around the holy mosque Direction

Denomination

General environmental characteristics

North

Shamiah

South

Ajeadh

East

Ghaza

West

Shobaikah

Constructions, demolition, unpaved roads, small workshops, dusty environment, light vehicles (motorcycle) Considered closed area, tall buildings, steady air, high Worshipers density, spray humidifiers. Considered open area, good natural air ventilation, library, near to bus parking. Similar to south direction, high Worshipers density, fair natural ventilation, spray humidifiers.

Table 2: The range and mean concentrations of airborne microorganisms at the main directions of the holy mosque CFU/m3

Indicator

Bacteria 22 oC Bacteria 37 oC Fungi Actinomycetes

North

South

East

West

(8.76x103- 1.74x104) [1.13x104±4.09x103] (1.10x104- 2.18x104) [1.41x104±5.13x103] (1.17x102 - 4.40x102) [2.60x102±1.61x102] (8.8x101- 2.64x102) [1.54x102±8.4x101]

(2.38x103-1.58x104) [6.65x103±6.16x103] (2.25x103- 1.76x104) [8.60x103±6.63x103] (1.17x102 - 5.72x102) [2.60x102±2.12x102] (8.8x101- 1.76x102) [1.28x102±3.6x101]

(1.47x103-3.21x103) [2.29x103±7.38x102] (1.85x103-3.66x103) [2.86x103±7.66x102] (4.4x101-2.34x102) [1.461x102±8.0x101] (5.9x101-1.76x102) [1.03x102±5.1x101]

(1.54x103-4.76x103) [3.25x103±1.56x103] (1.94x103-6.22x103) 4.11x103±2.02x103] (4.4x101- 3.08x102) [1.98x102±1.54x102] (0.00 - 1.32x102) [7.7x101±5.5x101]

(Range), [mean ± standard deviation]

Table 3: Similarity triangle depicting agreement ratios among microbial isolates at the different directionsof the holy mosque Direction

N S E W

Bacteria

Fungi

1.0

0.84 1.0

0.94 0.7 1.0

0.88 0.94 0.82 1.0

1.0

0.28 1.0

0.65 0.38 1.0

0.46 0.11 0.46 1.0

N: North, S: South, E: East, W: West

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8.75% of the total isolates at the south direction (Fig. 2). A total of 112 fungal isolates belonging to 19 genera were identified (Fig. 3). Aspergillus represented by Aspergillus fumigatus, Aspergillus niger and Aspergillus flavus . Aspergillus niger (14.27 %- 46.9%) and Fusarium (6.90% - 13.62%) were the common fungal isolates. The highest fungal diversity was found at the south direction, among

which Epicoccum , Mucor , Trichophyton , Chaetomium, Cladosporium, Alternaria, Emericella were detected. Table 3 shows the agreement ratios between the identified microbial isolates between directions. The agreement ratio is used to compare the identified microorganisms among sampling

Fig. 1: A diagram of the holy mosque showing sampling points

Fig. 2: Identification of airborne bacterial genera at the different directionsof the holy mosque

HAMEED & HABEEBALLAH, Curr. World Environ., Vol. 8(2), 179-187 (2013)

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Fig. 3: Identification of airborne fungal genera at the different directionsof the holy mosque sites, as it reflects the number of shared genera at the different sites in relation to the total number of genera 24 . High agreement ratios were found between bacterial genera at the all directions. The agreement ratios for fungi were relatively lower than bacteria, the highest ratio (0.65) was found between the North and East directions. No clear relationships were found between the meteorological parameters and airborne microorganisms. The relationships differ according to type of bio-contaminant and direction. However, relative humidity was considered the main factor affecting survivability of mesophilic bacteria (r=- 0.4 - - 0.8). Actinomycetes negatively related with temperature, however fungi negatively and positively related with relative humidity, and temperature, respectively. Wind speed show weak negative and positive relationships with microbial concentrations. DISCUSSION Airborne microbial contamination is a significant issue in the crowded centers and cities,

as air serves as a transmission vehicle for pathogens that have linked with adverse health effects ranging from infectious diseases to allergies and cancer 25. Airborne microorganisms affect individuals who are at risk, immune-compromised, elders and children, particularly in overcrowded areas, however, human responses depend on type of microorganism, and individualâ&#x20AC;&#x2122;s immune system26. Various sampling methods are used to collect airborne microorganisms including, impaction, impingement, filtration and gravity deposition 27. Passive and active sampling methods are based on different principles. The passive samplers yielded data with the lowest standard deviation in comparison with the active samplers 28 . In the present study, the gravitational method was used because it is a simple, cheap, and many places can be checked at the same time.The gravitational method is a non-quantitative method29, as it is affected by the size and shape of the particles, and motion of the surrounding atmosphere 30. Omeliansky formula is not a universal conversion formula; however it is used to allow comparing our results with other results that were obtained by using the active samplers.

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Airborne microbial concentrations ranging from 4,500â&#x20AC;&#x201C;10,000 CFU/m3 have been suggested as the upper limit for ubiquitous bacterial aerosols31, and concentration < 100 cfu/m3 may be unhealthy to immunosuppressed people32. In the present study bacterial concentrations exceeded 104CFU/m3 at the North and South directions. However, fungal concentrations did not exceed the allowable guideline limit value of 500 CFU/m 333. Actinomycetes exceeded 100 CFU/m3, strongly contaminated air, and 10â&#x20AC;&#x201C; 100 CFU/m3, moderately contaminated air at some directions as suggested by Polish Standards34. Airborne bacterial concentrations exceed 1x104 CFU/m3 over land35, as bacteria may be suspended as individual cells or attached to other particles such as soil and leaf36. Airborne fungal concentrations generally ranged from 100-103 CFU/ m337, and averaged ~104 CFU/m3 in the urban air1. Airborne actinomycetes averaged 102 CFU/m3 in the Cairo city centre 38, as actinomycetes are highly dependent on the amount of dust in the air39. Airborne microbial contamination is affected by multiple variables. These variables continuously changed, such as anthropogenic influence, human activity, topography, microenvironmental conditions, type of sources, and seasonality 1. In the present study traffic flow disturbed dust particles at the north direction that might be the reason for increasing of microbial concentration. The lowest microbial concentration was found at the East direction. This is attributed to the absence of direct human disturbances, and good natural ventilation. Generally microbial concentrations in the urban environment are influenced by human activities 40 , and their composition varies in different cities41.In the present study there were unclear correlations found between airborne microorganisms and meteorological factors. This is attributed to the influence of irregular disturbances and human activities, which may have more influence on microbial concentrations than meteorological factors near the holy mosque. The lack of significant relationships does not mean that meteorological factors have no effects on microbial survivability, because in un-standardized conditions severe microbial variations are expected.

In the present study Gram positive bacteria were common. This could be explained on the bases of their cell wall structure and continuous sources. The low frequent detection of Gram negative bacteriais attributed to their sensitivity to the air environment 41, and the initial shock due to desiccation after aerosolization 42 .Firmicutes, Proteobacteria and Actinobacteria are common bacterial types in the urban environment, where Gammaproteobacteria and Betaproteobacteria have been regularly identified 1. Mouli et al. 43 found airborne Gram positive bacteria in the range of 60% - 90% of the total bacterial population, in Tirupati, India; however Bacillus constituted 47.62% and Acinetobacteria 14.27% in the atmosphere of El Taief, Saudi Arabia44. Bacillus, Micrococcus and Staphylococci differed from place to place depending on the micro-environment 45. In the present study the frequent detection of Pseudomonas species at the south direction is of a particular interest as the spray humidifiers, and water reservoirs are suspected to be their sources. Airborne fungi is likely to be similar in most parts of the world, however the dominating genera may differ from area to another, depending on the density of plant cover, geographical location, and human activity46. In the present study, Alternaria, Penicillium and Cladosporium were found in low counts because Penicillium and Cladosporium favor low temperature conditions, and sensitive to solar radiation 47. Alternaria proliferates in the presence of suitable humidity, temperature, and vegetation debris 48 , these conditions are not available in the Saudi Arabia, as low humidity, high temperature and no permanent plant cover are the main characters of Makkah city. Fusarium can grow in water pipes, fresh water and humidifiers49, this confirms the presence of Fusarium in the air around the holy mosque. In the present study phyloplane and water indicators fungi50 were detected in lower counts than soil fungi. Actinomycetes may induce respiratory symptoms10, streptomycetes have been implicated in many diseases and several species stimulate lung macrophage reactions that lead to inflammation of the lung9. Aspergillus, Eurotium, Penicillium and Trichoderma species have been known as a cause of allergenic alveolitis 51 .

HAMEED & HABEEBALLAH, Curr. World Environ., Vol. 8(2), 179-187 (2013) Aspergillus flavus and Aspergillus fumigatus cause aspergillosis52. Gram negative bacteria are an important source of endotoxins, which are the main pulmonary immunotoxicants 53. Gram-positive bacteria should also be regarded as potential immunotoxicants 54.Bacillus species have been found to be associated with allergic alveolitis 55.The potential for extensive transmission of airborne infectious agents is present in large public settings; however the duration of exposure may be short. At the holy mosque, particularly in the Ramadan month, the duration of exposure to microbial contamination may be extended to be >10 hour/ day and the probability of infection may be present. Therefore a program for surveillance, prevention and control of airborne microbial contamination should be established at the holy mosque.

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CONCLUSION Airborne microbial concentrations not significantly varied between the main directions of the holy mosque. Airborne bacteria were the main microbial contaminants.The biodiversity of bacterial and fungal generawere higher at the south direction; however the north had the largest microbial concentrations. The anthropogenic activities are the main variables controlling air bio-contamination around the holy mosque. The spray humidifiers are suspected to be the main emission source of Pseudomonasbacteria. People may be exposed to infectious agents at the holy mosque; therefore the microbial contents should be included in the air quality standards and reports.

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Current World Environment

Vol. 8(2), 189-201 (2013)

Availability of Surface Water of Wadi Rajil as a Source of Groundwater Artificial Recharge: A Case Study of Eastern Badia /Jordan RAKAD A. TA’ANY* Al-Balqa-Applied University, Faculty of Agricultural Technology, Department of Water Resources and Environmental Management, Al-Salt, Jordan. http://dx.doi.org/10.12944/CWE.8.2.04 (Received: July 09, 2013; Accepted: August 15, 2013) ABSTRACT Wadi Rajil catchment area is considered as one of the major wadis entering the Azraq Basin from the north. It is ungauged wadi and covers an area of about 3910km2. The annual average rainfall on Wadi Rajil catchment area is about 126.6mm. Heavy thunderstorms occur in April and May, causing significant floods covering the area. The flood waters are not utilized, and a small portion infiltrates into the ground, where the great portion of these waters remain over Qaa’ Azraqfew months before evaporation. Due to the absence of the hydrometric stream flow station, no data are available about surface water runoff in Wadi Rajil catchment area. Therefore, the first part of this study calculates the surface water potential of Wadi Rajil to be utilized for groundwater artificial recharge, applying the SCS curvilinear synthetic unit hydrograph method. The synthesis unit hydrograph of Wadi Rajil catchment is characterized by a peak value of 1146 m3/s (4047 cfs) per one inch of rainfall excess. Flood hydrographs for 10,25,50, and 100 years return periods were derived and their peak flow are found to be 10,8,186,412, and 680 m3/s, respectively and the corresponding flood volumes are 0.95, 16.53, 36.89, and 61.5 MCM, respectively.Groundwater artificial recharge conditions are suitably prevailing in the most northern and central part of the catchment area, whereas, geological, Hydrogeological, and water quality characteristics of the floodwater encourage artificial replenishment of the exploited aquifer in the study area.

Key words: Wadi Rajil, Hydrometric, Unit hydrograph, Geological, Artificial recharge. INTRODUCTION Azraq basin is located in the Northeastern part of Jordan and extends northwards into Syria and southwards into Saudi Arabia. The Azraq Oasis (called locally Sabkhah or Qa’a Azraq) which is located in the central part of the basin is at a distance of about 120 km northeast of Amman. Qa’a Azraq is a relative large mudflat located in the central part of the basin. Two villages are located on the western side of the Qa’a Azraq; these are Azraq Shishan and Azraq Druze. A well field called AWSA was established north of Azraq Druze Springs (northern springs) where about 15-20 million m3 per year (MCM/a) of water is pumped to the capital Amman for drinking purposes since 1982. Farmers in the area are using around 45 MCM/a. Therefore, the total abstraction from the basin is about 65 MCM/a (El Naqa et al., 2007).

The over-pumping from the shallow groundwater aquifers, the water level dropped dramatically and signs of salinization and depletion are starting to occur. Therefore, it is necessary to determine the location of this interface, since saline water, intrusion has started and is predicted to accelerate in the near future. (Bajjali, and Hadidi, 2005). A number of major wadis drain radially into the Azraq depression. These wadis are characterized by wadis shallow flow-beds with relatively low slopes. None of the wadis within the basin is being gauged.Wadi Rajilcatchment area is considered as one of the most significant wadi draining the Azraq basin from its northern part. The general shape of Wadi Rajilcatchment area is trapezoidal, with its longer axis in general oriented NE-SW direction. The slope of the area is from NW

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to SE and the average slope of stream channels varies from 1% to 3% Elevation ranges from 1550 m above mean sea level (a.m.s.1) at Salkhad in Syria to 500 m a.m.s.1 at Qaa’ Azraq. Considerable part of the drainage is nearly flat. The main objective of this study is to estimate the peak discharge and the flood volumes for different return period in Wadi Rajil catchment area, and the potentiality of using this water for groundwater artificial recharge. MATERIALS AND METHODS Description of the study area Wadi Rajil catchment area lies between 313 to 400 E and 138 to 228 N According to Palestine Grid, and it covers 3910 km 2,Figure 1.Intermittent flow in the wadi occurs in winter and drains into Qaa’ Azraq, where it evaporates within a few months without utilization. The climate in the Azraq Basin belongs to the Mediterranean bio-climatic region, which is characterized by dry hot summers and wet, cold winter. Most of the study area is arid and small portion can be considered as semi-arid. As in most arid and semi-arid areas, temperatures exhibit large seasonal and diurnal variations with absolute daily temperatures ranging from a maximum of about 46 ºC (January of 1993), (JMD, 2010). The thunderstorm rainfalls from the great part of the total rainfall in the study area, which is characterized by irregular intensity and duration. The heaviest rainfall over 24 hours is usually recorded between December and March and no significant normal rainfall is to be expected in October and May. The average annual rainfall over the sub-catchment area is 126.6 mm and ranges between less than 50mm in the south to more than 300 mm in the northern part of the sub-catchment. Geology Azraq Basin in general and Wadi Rajil catchment area in particular is a part of the limestone plateau in east Jordan. The northern part of this plateau is covered by six basalt flows, tuff and volcanic eruption originated mainly in Jabel Arab in Syria and many other relatively small

volcanoes in the area occurred during the MioceneQuaternary. These flows overlie Tertiary rocks in the northern part of the catchment area. The youngest sediments in the Qaa’ consists of gravels and sands of fluviatile origin (NRA, 1992).The outcropping formations are, the Rijam and wadi Shallala in the central and eastern part of the basin, both of Eocene age. The northern part of the Azraq basin is dominated by Miocene to Pleistocene basalt whereas to the west and south by Rijam and Muwaqqar formations of late cretaceous- Early Ter tiary age. Regional distribution of the outcropping geological formations is shown in Figure 2. The area as the whole of Jordan was effected by the transgressions and regressions that occurred during the time from Cenomanian until upper Eocene (NRA, 1992). These transgressions and regressions are represented in the Azraq Basin by the changes of facies in the Ajlun Group (limestone, dolomite, marl, shale and dolomitic limestone) and Belqa Group (marl,limestone ,chert, silicified, limestone, dolomite and chalk),that crop out in the central, western and southern part of the basin. During the period from upper Oligocene and into the lower Miocene, the Azraq Basin has gone under erosion and tectonic activity,(Bender, 1974). In the Azraq playa (wetland reserve), the basalt is missing. Upper Tertiary sediments (B5) (Wadi Shallala) are located in the structural depression zones. The (B5) Formation consists of Marly Clayey layers in the area of AWSA well field and acts here as an aquitard between the B4 (Rijam) and the Basalt aquifer. Towards the southeast, the B5 Formation contains more sandy layers and it is classified as an aquifer in this area. South of the basalt areas Paleocene and Eocene,marly limestone, chalks, and chalky limestone with chert layers of the B4 formation, dominate the landscape. The B4 formation is underlain by the Maastrichtian B3 (Muwaqqar) formation. B3 formation reaches a thickness of about 300 m and consists of marl and marly

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191

limestone with some gypsum and evaporite. The underlying Campanian to Turonian B2/A7 formations (Amman/Wadi Sir) is mainly formed by chert and limestone, (El Naqa, 2010).

The lag time (La) is calculated from the following formula;

Methodolgy There are several methods for determining the peak discharge in un-gauged watersheds. In this study, the SCS-curvilinear synthetic unit hydrograph concept was applied to estimate the peak discharge for the un-gauged Wadi Rajil catchment area.

Where, Ct, is aregional constant representing watershed slope and storage (Subramanya, 1984, Chow et al, 1988, Linsely, et al, 1988), L, is the hydraulic length, Lc,is the centroid length and S1 , is the slope. The standard duration of rainfall (Dr) is calculated as: Dr=La/5.5 ..(3)

Derivation of the Unit Hydrograph The most common method of deriving unit hydrograph synthetically is the soil conversation services (SCS) curvilinear unit hydrograph method, Chow, et al, 1988, Wanielista, 1990). The time to peak or the time required to reach the peak discharge (Tp) is defined as: Tp=Dr/2+La

Table 1: Arrangements of incremental values of the storm of certain return period

T(1) T(2) . . . T(n/2)-2) T(n/2)-1) T(n/2) T(n/2) +1) T(n/2) +2) . . . T(n-1) T(n)

...(2)

The peak discharge (Qp) can be calculated using the SCS formula: Table 2: Unit Hydrograph calculations of Wadi Rajil catchment area T/TP

T (hr)

Q/QP

Q (cfs)

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.5 4.0 4.5 5.0

0.00 1.83 3.65 5.48 7.31 9.14 10.96 12.79 14.62 16.44 18.27 20.10 21.92 23.75 25.58 27.41 29.23 32.89 36.54 40.19 43.85 47.50 51.16 54.81 63.95 73.08 82.22 91.35

0.00 0.015 0.075 0.160 0.280 0.430 0.600 0.770 0.890 0.970 1.000 0.980 0.920 0.840 0.750 0.660 0.560 0.420 0.320 0.240 0.180 0.130 0.098 0.075 0.036 0.018 0.009 0.004

0.00 607.08 3035.40 6475.52 11332.16 17402.96 24283.20 31136.44 36020.08 39257.84 40472.00 39662.56 37234.24 33996.48 30354.00 26711.52 22664.32 16998.24 12951.04 9713.28 7284.96 5261.36 3966.26 3035.40 1456.99 728.50 364.25 161.80

...(1)

Where, Tp=is time to peak in hours Dr= is the standard duration of rainfall La= is the lag time

Time Increment

La = Ct ((L* Lc)/â&#x2C6;&#x161; (Sl)) ^0.38

Rainfall P(n) P(n-2) . . . P(5) P(3) P(1) P(2) P(4) . . . P(n-2) P(n)

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192 QP=(484/TP)*A

...(4)

Where, A, is the catchment area in (mi2) and Qp in ft3/sec (cfs). Critical Arrangement of the storm The incremental values of the storm of certain return period (e.g. 25-year), were arranged in descending order and re-arranged as shown in Table 1, below: From this arrangement, it is indicated that T (n) is the last time increment in 24 hrs andP (1) is the first and consequently the maximum incremental rainfall. This is the critical arrangement of the storm, which produces maximum peak discharge in its flood, (Matthai, 1969).

Derivation of the Flood Hydrographs The flood hydrograph of each frequency storm is derived by combining of the hydrograph obtained for each incremental net rainfall or runoff (r1, r2,……., ri). In this combination procedure, the shifting of the hydrographs according to its time increment should be considered, (Chow et al., 1988). Estimation of peak discharge In this study, the unit hydrograph approach is applied to determine the peak discharge values.The hydrologic characteristic of the drainage area such as the area of the basin(A),hydraulic length (L), centroid length (Lc) and the elevation deference between the highest point of the main stream and the outlet(H) are calculated from the topographic maps related to the

Table 3: Calculation of effective rainfall for Wadi Rajil Catchment Area for 10-year return period Time (hrs)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Rainfall intensity (mm/hr)

Rainfall (mm)

Rainfall Increment (mm)

Critical Arrangement

(P-Ia) (mm)

(P-Ia -f) (mm)

Effective Rainfall (inch)

10.25 6.72 5.00 4.10 3.52 3.14 2.75 2.50 2.30 2.13 2.00 1.88 1.79 1.70 1.63 1.58 1.50 1.47 1.40 1.38 1.34 1.30 1.28 1.26

10.25 13.4 15.00 16.40 17.60 18.84 19.25 20.00 20.70 21.30 22.00 22.56 23.27 23.80 24.45 25.28 25.50 26.46 26.60 27.60 28.14 28.60 29.44 30.24

10.25 3.15 1.60 1.40 1.20 1.24 0.41 0.75 0.70 0.60 0.70 0.56 0.71 0.53 0.65 0.83 0.22 0.96 0.14 1.00 0.54 0.46 0.84 0.80

0.14 0.22 0.41 0.54 0.65 0.70 0.70 0.71 0.84 1.20 1.60 10.25 3.15 1.4 1.24 1.00 0.96 0.83 0.80 0.75 0.60 0.56 0.53 0.46

0 0 0 0 0 0 0 0 0 0 0 0 0 0.71 1.24 1.00 0.96 0.83 0.80 0.75 0.60 0.56 0.53 0.46

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.24 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00945 0 0 0 0 0 0 0 0 0

TAâ&#x20AC;&#x2122;ANY, Curr. World Environ., Vol. 8(2), 189-201 (2013) catchment.Whereas the Curve Number (CN) is calculated from the topographic maps, geologic maps and land use map available for Azraq Basin. The calculation of the unit hydrograph (UH) and the derivation of the flood hydrographs of 10, 25,50and 100years return period for Wadi Rajil catchment area were performed. Unit Hydrograph of Wadi Rajil Catchment area The calculation of UH of Wadi Rajil Catchment areawas done using the English unit, then the obtained peak discharge(Qp)values were converted to the metric units. The parameters taken from the topographic map were:

193

From Equation (2), the calculated lag time (La)is:

La = 18.35 hrs. From Equation (3), the standard duration (Dr) is:

Dr = 3.34 hrs. The La value is corrected for Dr = 1 hr. instead of 3.34hr, using Snyderâ&#x20AC;&#x2122;s Formula:

A=1527.3 square mile (mi2) L=118.75 mi Lc= 59.38 mi H=3444.9 ft Table 4: Calculation of effective rainfall for Wadi Rajil Catchment Area for 25-year return period Time (hrs)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Rainfall intensity (mm/hr)

Rainfall (mm)

Rainfall Increment (mm)

Critical Arrangement

(P-Ia) (mm)

(P-Ia -f) (mm)

Effective Rainfall (inch)

12.90 7.95 6.10 5.00 4.21 3.72 3.35 3.00 2.80 2.60 2.45 2.30 2.19 2.10 2.00 1.94 1.86 1.81 1.76 1.70 1.66 1.60 1.57 1.53

12.90 15.90 18.30 20.007 21.05 22.32 23.45 24.00 25.20 26.00 26.95 27.60 28.47 29.40 30.00 31.04 31.62 32.58 33.44 34.00 34.86 35.20 36.11 36.72

12.90 3.00 2.40 1.70 1.05 1.27 1.13 0.55 1.20 0.80 0.95 0.65 0.87 0.93 0.60 1.04 0.58 0.96 0.86 0.56 0.86 0.34 0.91 0.61

0.55 0.58 0.61 0.80 0.86 0.91 0.95 1.04 1.13 1.27 2.40 12.90 3.00 1.70 1.20 1.05 0.96 0.93 0.87 0.86 0.65 0.60 0.56 0.34

0 0 0 0 0 0 0 0 0 0 0 2.21 3.00 1.70 1.20 1.05 0.96 0.93 0.87 0.86 0.65 0.60 0.56 0.34

0 0 0 0 0 0 0 0 0 0 0 1.21 2.00 0.70 0.20 0.05 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0.047 0.079 0.028 0.008 0.002 0 0 0 0 0 0 0 0

TAâ&#x20AC;&#x2122;ANY, Curr. World Environ., Vol. 8(2), 189-201 (2013)

194 Where,

is the corrected lag time and is one hour duration. Then, theTp was calculated using formula (1):

Finally, the estimated Qp was obtained using Equation (4):

= 40471.6 or 1146 m3 / sec (cms) The T/Tp and Q/Qp values of the generalized dimensionless UH of the SCS were

used to derive the synthetic UH of Wadi Rajil catchment area. Table 2, shows the calculation of Wadi Rajil UH. The UH of Wadi Rajil is also illustrated in Figure 3. Derivation of Wadi Rajil Flood Hydrographs The intensity duration frequency curves (IDF) of Azraq rainfall station and the CN method mentioned previously, were utilized to calculate the effective rainfall (runoff). The IDF curves are shown in Figure 4.From these curves ,the 10 ,25,50 and 100 years return period rainfalls for duration of 24 hours were obtained hourly, the results of calculation are tabulated in Tables (3,4,5,and 6).These tables also show the critical arrangement of the incremental rainfall to obtain the maximum flood of 10,25,50 and 100 years return period storm.

Table 5: Calculation of effective rainfall for Wadi Rajil Catchment Area for 50-year return period Time (hrs)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Rainfall intensity (mm/hr)

Rainfall (mm)

Rainfall Increment (mm)

Critical Arrangement

(P-Ia) (mm)

(P-Ia -f) (mm)

Effective Rainfall (inch)

14.50 9.30 7.20 5.75 4.80 4.22 3.80 3.46 3.24 3.00 2.80 2.70 2.54 2.42 2.35 2.27 2.18 2.10 2.05 2.00 1.94 1.88 1.81 1.78

14.50 18.60 21.60 23.00 24.00 25.32 26.60 27.68 29.16 30.00 30.80 32.40 33.02 33.88 35.25 36.32 37.06 37.80 38.95 40.00 40.74 41.36 41.63 42.72

14.50 4.10 3.00 2.40 1.00 1.32 1.28 1.08 1.48 0.84 0.80 1.60 0.62 0.86 1.37 1.07 0.74 0.74 1.15 1.05 0.74 0.62 0.27 0.09

0.27 0.62 0.74 0.80 0.86 1.05 1.08 1.28 1.37 1.00 3.00 14.50 4.10 2.40 1.48 1.32 1.15 1.07 1.00 0.84 0.74 0.74 0.62 0.09

0 0 0 0 0 0 0 0 0 0 0 4.77 4.10 2.40 1.48 1.32 1.15 1.07 1.00 0.84 0.74 0.74 0.62 0.09

0 0 0 0 0 0 0 0 0 0 0 3.77 3.10 1.40 0.48 0.32 0.15 0.07 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0.148 0.122 0.055 0.019 0.013 0.006 0.003 0 0 0 0 0 0

TAâ&#x20AC;&#x2122;ANY, Curr. World Environ., Vol. 8(2), 189-201 (2013) The incremental runoff values were applied to the UH with the time lag, and the individual hydrographs were obtained for each incremental runoff. The addition of these hydrographs give the total storms hydrographs .The application of the procedure to 10,25,50,and 100 years storms for Wadi Rajil catchment are shown in Table 7and the resulted flood hydrographs are illustrated in Figure 5. The calculated peak discharges were 10.8,186,412and 680 m3/sfor the 10, 25, 50, and 100 year return period respectively. The calculated flood volumes were 0.95,16.5,36.9and 61.5 million cubic meter (MCM)for the 10,25,50,and 100 year return period respectively. Possibilities of Artificial Recharge As noticed from the previous section, the

195

study area in particular as well as desert area in Jordan in general receive a low precipitation amount, where most of rainfall occurs in few storms of high intensity and short duration. Flush floods occur in desert areas, due to the low infiltration index. Most of the floodwater evaporates and very little amount for the time being has been utilized. Due to this, the ideal solution is the better management of such water by using it in the replenishment of the over pumped aquifer by artificial recharge techniques. Artificial recharge is essential on enhancement of natural recharge ; therefore an understanding of the hydrologic cycle precedes developments of sites selection criteria .Five facets of the hydrologic cycle that need to be well understood(Chidly,1981). These are precipitation,

Table 6: Calculation of effective rainfall for Wadi Rajil Catchment Area for 100-year return period Time (hrs)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Rainfall intensity (mm/hr)

Rainfall (mm)

Rainfall Increment (mm)

Critical Arrangement

(P-Ia) (mm)

(P-Ia -f) (mm)

Effective Rainfall (inch)

16.20 10.30 7.90 6.40 5.50 4.87 4.38 3.92 3.70 3.48 3.24 3.08 2.90 2.78 2.67 2.59 2.46 2.39 2.30 2.26 2.20 2.15 2.10 2.05

16.20 20.60 23.70 25.60 27.50 29.22 30.66 31.36 33.30 34.80 35.64 36.96 37.70 38.92 40.05 41.44 41.82 43.02 43.70 45.20 46.20 47.30 48.30 49.20

16.20 4.40 3.10 1.90 1.90 1.72 1.44 0.70 1.94 1.50 0.84 1.32 0.74 1.22 1.13 1.39 0.38 1.20 0.68 1.50 1.00 1.10 1.00 0.90

0.68 0.74 0.90 1.00 1.13 1.22 1.39 1.50 1.72 1.90 3.10 16.20 4.40 1.94 1.90 1.50 1.44 1.32 1.20 1.10 1.00 0.84 0.70 0.38

0 0 0 0 0 0 0 0 0 0 0 9.68 4.40 1.94 1.90 1.50 1.44 1.32 1.20 1.10 1.00 0.84 0.70 0.38

0 0 0 0 0 0 0 0 0 0 0 8.68 3.40 0.94 0.90 0.50 0.44 0.32 0.20 0.10 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0.342 0.134 0.037 0.035 0.020 0.017 0.013 0.008 0.004 0 0 0 0

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Table 7: Flood hydrographs of 10, 25, 50 and 100 year return period for Wadi Rajil Catchment Area T

Flood Discharge (cfs)

(hrs) 10 year

25 year

50 year 100 year

0 0 0 0 0 1 2.2 10.8 34.0 78.7 2 7.1 50.5 139.1 287.8 3 11.5 123.0 284.8 526.5 4 34.0 288.0 727.5 1430.0 5 51.0 579.0 1322.0 2405.0 6 71.8 896.0 2016.0 3518.0 7 98.3 1272.0 2853.0 4941.0 8 124.7 1705.0 3800.0 6482.0 9 162.5 2214.0 4968.0 8494.0 10 207.9 2861.0 6411.0 10984.0 11 229.6 3488.0 7674.0 12798.0 12 260.8 3997.0 8844.0 14708.0 13 298.6 4555.0 10133.0 16959.0 14 321.3 5105.0 11296.0 18752.0 15 346.0 5561.0 12330.0 20447.0 16 366.6 5977.0 13251.0 21983.0 17 374.2 6286.0 13905.0 22949.0 18 381.0 6470.0 14343.0 23671.0 19 380.3 6569.0 14566.0 24031.0 20 374.2 6565.0 14568.0 24019.0 21 355.8 6427.0 14241.0 23408.0 22 352.4 6239.0 13934.0 23088.0 23 334.5 6063.0 13497.0 22345.0 24 315.6 5791.0 12907.0 21337.0 25 300.5 5498.0 12285.0 20398.0 26 274.0 5168.0 11512.0 19038.0 27 253.2 4779.0 10685.0 17707.0 28 232.4 4406.0 9868.0 16404.0 29 218.1 4074.0 9161.0 15309.0 30 199.4 3776.0 8469.0 14144.0 31 185.2 3485.0 7828.0 13096.0 32 170.1 3221.0 7223.0 12084.0 33 160.6 2985.0 6719.0 11277.0 34 144.1 2763.0 6179.0 10310.0 35 135.1 2536.0 5705.0 9549.0 36 126.1 2357.0 5298.0 8889.0 37 115.3 2184.0 4900.0 8186.0 38 106.3 2012.0 4513.0 7547.0 39 98.7 1858.0 4174.0 6988.0 40 89.6 1711.0 3835.0 6401.0 41 86.0 1584.0 3575.0 6010.0 42 76.7 1472.0 3291.0 5494.0 43 70.7 1346.0 3019.0 5038.0 44 69.2 1254.0 2836.0 4789.0 45 60.3 1170.0 2608.0 4342.0 46 54.8 1058.0 2370.0 3941.0 47 50.6 963.0 2163.0 3623.0 48 46.1 880.0 1980.0 3312.0 49 43.5 810.0 1829.0 3078.0 Volume of flood water for different return periods in million cubic meter (MCM)

Flood Discharge (cfs)

(hrs)

10 year

25 year

50 year

100 year

50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

40.8 36.4 34.3 32.1 30.5 27.4 25.0 23.6 21.7 19.8 18.1 17.0 16.1 15.1 13.7 12.5 11.3 10.5 9.3 8.7 8.5 7.8 7.6 6.9 6.1 5.7 5.2 4.7 4.3 4.2 4.0 3.8 3.3 2.6 2.4 2.4 2.1 2.0 1.9 1.9 1.8 1.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.95

756.0 700.0 641.0 598.0 562.0 523.0 479.0 441.0 409.0 377.0 346.0 319.0 297.0 280.0 260.0 239.0 218.0 199.0 181.0 164.0 154.0 145.0 137.0 129.0 119.0 108.0 98.8 90.5 82.2 75.9 72.2 68.9 64.3 56.1 47.5 43.2 40.1 36.9 34.9 33.8 32.3 30.2 20.6 6.7 1.8 0.3 0.0 0.0 0.0 0.0 0.0 16.53

1703.0 1564.0 1444.0 1344.0 1263.0 1168.0 1071.0 992.0 919.0 848.0 776.0 718.0 671.0 628.0 583.0 534.0 488.0 447.0 405.0 371.0 348.0 326.0 308.0 288.0 264.0 242.0 222.0 203.0 185.0 172.0 163.0 155.0 143.0 123.0 107.7 98.9 90.6 83.4 78.9 76.0 72.3 67.3 39.3 17.4 7.4 3.9 1.6 0.5 0.0 0.0 0.0 36.89

2866.0 2611.0 2420.0 2258.0 2122.0 1947.0 1783.0 1663.0 1540.0 1413.0 1297.0 1203.0 1126.0 1055.0 971.0 888.0 812.0 704.0 675.0 622.0 591.0 547.0 520.0 481.0 438.0 403.0 371.0 339.0 309.0 290.0 276.0 261.0 237.0 200.0 179.0 169.0 152.0 141.0 135.0 129.0 121.0 111.8 50.2 25.8 18.4 11.5 7.7 4.5 2.1 0.7 0.0 61.5

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Applying these points on Wadi Rajil catchment, the different parameters of the hydrologic cycle are discussed in the previous section and the results are tabulated in Tables (3, 4, 5.6 and 7). From these tables the surface runoff in the area is available during the winter season.

conditions prevailing in the Upper Aquifer Complex in the area, there is an enough space for ground water aquifer since it is all over the basin is over pumped as indicated from the groundwater withdrawals in the area of study, Figure 6. In addition, the hydraulic characteristics of the aquifer as indicated from the pump test analyses of the groundwater wells operating in the areaare as follows: the discharge, specifics capacities and transmissivities are ranging between 70-300m3/ hr,0.2-35200m 3 /hr/m and 15-72300m 2 /d, respectively, (El-Naqa and Al-Shayeb 2008).Therefore, the aquifer has a good potential to accept recharged water. Furthermore, the depth of the water table in the area is ranging between 20-70m from the ground surface.

The water quality of surface runoff of Wadi Rajil is considered to be of good quality,Table 8.whereas, the electrical conductivity (EC µS/cm) is considered low and highly appropriate since the water flows mostly on the basalt floes or the weathering products of the basalts or the volcanic ashes in most of the drainage areaand in general will not affect negatively the groundwater quality in the area after its percolation through the highly fractured basalt.

As indicated from the above discussion on the situation of Wadi Rajil catchment, artificial recharge is considered of high potential to replenish the Upper aquifer. Concerning the technique of artificial recharge, which should be developed in the study area. It is suggested to use deep trench technique, Figure 7, whereas the course of Wadi Rajil itself as well as its tributaries are of wide type and under these circumstances check or desert dams are not feasible (Rimawi et al., 1995).

surfaceinfiltration, soilmoisture, surface runoff, interflow, and evapotranspiration. In addition to these facts, the following questions must be quantified concerning viable sites selection criteria(CGWB, 1994): how much rechargeable water is available? when and at what depth ?how will the quality of water change after recharge and how quickly will the aquifer plug due to chemical, physical or bacterial processes.

Talking into consideration the hydrological Table 8: Quality of Surface runoff and Groundwater of Wadi Rajil catchment area Parameters Date Temperature (ºC) EC (µ/cm) pH-value Ca (meq/L) Mg (meq/L) Na (meq/L) K (meq/L) Cl (meq/L) HCO3 (meq/L) SO4 (meq/L) NO3 (meq/L) Turbidity Color TSS (g/L)

Flood Water

Groundwater

14.3.2003

16.1.2006

25.2.2009

Representative

16.2 218 7.5 1.18 0.25 0.76 0.12 0.45 1.72 0.12 0.06 610 18 0.35

14.5 225 7.7 1.12 0.21 1.05 0.10 0.52 1.65 0.4 0.04 430 12 0.21

15.0 185 7.8 1.06 0.18 0.65 0.08 0.35 1.48 0.10 0.02 240 8 0.45

25.2 550 7.9 0.92 0.72 3.69 0.26 2.35 2.26 1.08 0.08 0.0 0.0 0.0

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Fig. 1: Location Map of Wadi Rajil Area Catchment Area

Fig. 2: Geological map of the Azraq Basin

Fig. 3: Wadi Rajil Unit Hydrograph

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Fig. 4: Azraq Intensity Duration Frequency Curves, (Ta’any, 2002)

Fig. 5: Flood hydrograph of 10, 25, 50-and100 year return period for Wadi Rajil catchment area

Fig. 6: Groundwater Fluctuation in Azraq – 12 Observation Well, (Bajjali, and Hadidi, 2005)

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Fig. 7: Deep Trench for Artificial Recharge Purposes The proposed technique is usually preferred by constructing successive trenches cross the wadi course.Trenches are filled with boulder, gravels and sands (volcanic ashes) in sequence from bottom to top. Using these techniques, the suspended mater will be removed and good water quality will reach the aquifer and no negative impacts will be expected in the groundwaterquality.

Wadi Rajil catchment area has led to the following results: ´

´ CONCLUSIONS Generally, the northern part of the Azraq Basin receives higher rainfall amounts than the other parts of the basin and accordingly most of the groundwater resources are originated from north of the Azraq basin.The investigation of the availability of surface water and the prevailing conditions for groundwater artificial recharge for

The thunderstorm rainfalls from the great part of the total rainfall in the study area, which is characterized by irregular intensity and duration. The heaviest rainfall over 24 hours is usually recorded between December and March. The calculated peak discharges for the studied catchment area were 10.8,186,412and 680m3/s for the 10, 25, 50, and 100 return period, respectively. The estimated flood volumes from the resulted flood hydrographs of Wadi Rajil catchment area were 0.95, 16.5, 36.9 and 61.5 MCM for the 10, 25, 50, and 100-year return periods, respectively. Geological, hydrogeological and

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available basalt boulders, gravels as well as volcanic ashes will be the appropriate method to be used for artificial recharge in Wadi Rajil catchment area .

waterquality offloodwater are found to be highly suitable for artificial recharge of the Upper Aquifer System. Deep long narrow trenches refilled with the

REFERENCES 1.

Bajjali, W. and Hadidi, K., Hydrochemical Evaluation of Groundwater in Azraq Basin, Jordan Using Environmental Isotopes and GIS Techniques, Proc. of the 25th Annual ESRI International User Conference, San Diego, California, July 25 – 29 (2005). Bender, F., The geology of Jordan, contribution to the regional geology of the earth, supplementary edition of volume 7.Gebrueder Borntraeger, Berlin (1974). Central Ground Water Board (CGWB). Manual on Artificial Recharge of Groundwater, Technical Series: M, No.3. Ministry of Water Resources, Government of India, pp 215 (1994). Childley,T.R.E., Assessment of groundwater recharge, Lloyd, J.W. (Ed). Case studies in ground water resources evaluation. Clarenden Press, oxford (1981). Chow,V.T., Maidment,R.Dand Mays,W.L.,. Applied Hydrology .International Edition, Mc Graw-Hill Book Company, NewYork (1988). El Naqa, A., Study of salt-water intrusion in the Upper Aquifer in Azraq Basin. IUCN, Jordan (2010). El-Naqa, A. and Al-Shayeb. A.,Groundwater Protection and Management Strategy in Jordan. Springer, Water Resources Management, 23: 2379–2394 (2008). El Naqa, A. Al Momani, M.; Kilani,S. , A. and Hammour, N., Groundwater Deterioration of Shallow Groundwater Aquifers Due to Overexploitation in Northeast Jordan. Clean,

10.

11.

12.

13.

14.

15.

16.

35(2): 156-166 (2007). JMD (Jordan Meteorological Department), Annual Report, Ministry of Transport. Amman, Jordan (2010). Linsely, R,K,Kohler , M, A, and Paulhus, J.L.H., Hydrology for engineers .international (SI metric edition) McGraw Hill, N.Y, USA (1988). Matthai, H.F, Floods of June 1955 in south plate River Basin, Colorado. Water Supply Paper 1850-B, U.S Geological Survey, Washington, D.C (1969). NRA (Natural Resources Authority), The Geology of the Azraq Basin. Internal report of NRA, Amman, Jordan (1992). Rimawi, O, Salameh, E and Abu Obeid, H., Environmental impact assessment of Wadi Rajil Dam. Internal report submitted to Azraq Oasis Project, UNDP-Sponsored Project (1995). Subramanya, K., Engineering, Hydrology. Tata MC Graw-Hill Publishing Company LTD, New Delhi Metthai, H.E., 1969:”Floods of June 1955 in South Plate River Basin”, Colorado Water Supply Paper 1950-B, U.S. Geological Survey, Washington, D.C (1984). Ta’any R., Rainfall –intensity- durationfrequency curves for Azraq area. Unpublished Figure. Water Authority of Jordan, Amman (2002). Wanielista, M., Hydrology and Water Quantity Control, John Wiley (1990)

Current World Environment

Vol. 8(2), 203-213 (2013)

Gas Exchange, Chlorophyll Fluorescence and Antioxidants as Bioindicators of Airborne Heavy Metal Pollution in Jeddah, Saudi Arabia I.A. HASSAN1,2, J.M. BASAHI2,3 and I.M. ISMAIL2,4 1

Faculty of Science, Alexandria University, Alexandria, 21526 El Shatby, Egypt. 2 Centre of Excellency in Environmental Studies, King Abdulaziz University, P.O. Box 80216, Jeddah 21589. KSA 3 Faculty of Environment, Meteorology and Arid Land Agriculture, King Abdulaziz University, Jeddah 21589, KSA. 4 Department of Chemistry, Faculty of Science, King Abdulaziz University, P.O. Box 80203 , Jeddah 21589. KSA. http://dx.doi.org/10.12944/CWE.8.2.05 (Received: July 09, 2013; Accepted: August 05, 2013) ABSTRACT Lettuce ( Lactuca sativa L. cv. Romaine) plants were exposed to different levels of urbanization in Jeddah city, Saudi Arabia. They showed different degrees of visible injury symptoms and dramatic changes in enzymatic activities as well as net photosynthetic rates (PN), variable to maximum chlorophyll fluorescence (Fv /Fm) and stomatal conductance (gs). Visual symptoms of phytotoxicity of heavy metals were observed on plants grown at industrial and urban areas, where the concentrations of metals was about 36 times higher than in other sites. The decrease in chlorophyll reached 70 and 64% in plants cultivated in the industrial and urban regions, while lengths of shoots reduced by 50 and 41% in plants collected from the same locations, respectively. The reduction in chlorophyll and other physiological and biochemical parameters were correlated with the concentrations of airborne pollutants measured in the atmosphere of the locations examined. Moreover, lettuce plants cultivated in the industrial region accumulated more heavy metals than others, which can pass into the human food chain. Photosynthetic efficiency was significantly decreased and lipid peroxidation was enhanced. Antioxidant enzymes were significantly altered during exposure. The biochemical and physiological parameters measured in the present study clearly showed that they could form the basis of a plant biomarkers battery for monitoring and predicting early effects of exposure to airborne heavy metals. Key words: PN â&#x20AC;&#x201C; net photosynthetic rate; gs - stomatal conductance; Fv/Fm - maximum quantum efficiency of PSII photochemistry; biomonitoring.

INTRODUCTION The rapid increasing population in urban areas led to anthropogenic activities and fossil fuel combustion. Emissions from road traffic that uses fossil fuel, industry, agriculture, sewage sludge, and waste incineration are the chief sources of air pollution1, 2. Air pollutants especially heavy metals are hazardous and toxic to human beings depending on their concentrations in the food stuff 3-4. Presence of airborne heavy metals in vegetable crops above the permissible limit may lead to severe health hazards to the people

consuming it5. So the estimation of their levels in contaminated food is very important for the safety of human health3, 6. Increasing industrialization, urbanization and vehicular traffic in Jeddah city could increase levels of heavy metals in air and soil [2] which lead to a high pollution pressure on the biota and eventually, would pose a threat to food safety and human health7,8. Metal pollutants found as superficial contaminants on leaves thereby, they are especially

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useful as biological indicators to assess air pollution indicator for metal pollution9 - 17. Because of the different characteristics of foliar uptake, accumulation and translocation of atmospheric heavy metals by leaves, plant leaves are used as bioindicators and/or biomonitors of heavy metal pollution in the terrestrial environment18-20. Although it was reported that mosses and lichens are good monitors of heavy metal pollution, higher plants can be used as biomonitors in areas that do not have these species21- 23. Photosynthesis (PN) is inhibited by air pollution and other environmental stresses24-28. Ouzounidou et al.29 found reductions in rate of photosynthesis stomatal conductance (g s), the maximum quantum yield of primary photochemistry, variable fluorescence (Fv) and chlorophyll concentration in Ni-stressed wheat. Recently, a marked toxicity of heavy metal pollution to photosynthetic apparatus in maize plants was reported30. They found a decline of fluorescence induction kinetics as well as of chlorophyll and carotenoid concentrations in Ni-stressed plants of maize. However, the main mechanism primarily affecting photosynthesis in response to heavy metals is not clear17. Heavy metals have detrimental effects on the enzymatic capacity and gs of the photosynthetic apparatus31. In Saudi Arabia, air pollution due to the heavy metals arises from road traffic that uses fossil fuel, industry, agriculture, sewage sludge, and waste incineration as well as from the dust storms3234 . However, Studies regarding the contamination of heavy metals in the vegetable crops are scanty. Therefore, it is important to study the heavy metals contamination in plants m that could presumably be used as a biological indicator of heavy metal pollution so as to decide if it is safe or not for human consumption2, 34. Airborne heavy metals are hazardous and toxic to human beings depending on their concentrations in the food stuff4. During the past few decades, there has been an increase in the use of levels of higher plant as biomonitors of heavy metal pollution in the arid and semi-arid environments such as Saudi Arabia9, 32 - 36.

The aim of present study was aimed at evaluating lettuce (Lactuca sativa L. cv Romaine) leaves as a biomonitor of airborne heavy metals in order to assess whether the vegetable crops were safe for human consumption. MATERIALS AND METHODS Plant material, growth conditions and experimental design Seeds of Lettuce (Lactuca sativa L. cv Romaine) plants were washed with distilled water to remove excess pesticides or herbicides and to break dormancy. Experimental design and growth conditions were discussed elsewhere2. Gas exchange and fluorescence measurements The photosynthetic gas-exchange measurements were done by a portable photosynthesis system LI 6000 (Li- Cor, USA). The pots were located in a climatic box, where plants were adapted for 1 h at a photon flux density (PFD) of 450 mmol m-2 s-1 (PAR). The leaf gas-exchange was determined under the following conditions: PFD of 900 mmol m-2 s-1, leaf temperature of 31.50C, ambient CO2 concentration of ca 400 mmol mol-1 and relative air humidity of about 65%. For each measurement, the first top fully developed leaves from the main stems of six plants were used on weekly basis16. Chlorophyll fluorescence was measured by a Fluorescence Monitoring System (FMS, Hansatech Instruments, U.K.). Measurements were made in ambient [CO2] (Ca, 450 mmol mol-1) on individual leaves enclosed into a leaf cuvette under a rate of 0.44 L min-1 air flow, relative humidity within the cuvette at 50-55%, a leaf temperature of 400C and 900 mmol m -2 s -1 of light intensity 31. The maximum quantum yield of PSII in dark adapted leaves was estimated by the ratio between variable and maximal fluorescence, Fv /Fm = (Fm - F0)/Fm. The efficiency of water-splitting apparatus was estimated by ratio between basal and variable fluorescence, F0 / Fv 37. Oxygen concentration was lowered to 1.5% when testing leaf gas exchange under non-photorespiratory conditions17. Gas exchange parameters and chlorophyll fluorescence yield were measured simultaneously.

HASSAN et al., Curr. World Environ., Vol. 8(2), 203-213 (2013) Pigment concentration Chlorophylls (a & b ) were extracted in 85% acetone and measured on a UV-1800 Spectrophotometer (SHIMADZU) and their concentrations were calculated21. Leaves of the same age as those in the gas-exchange analyses were used. Antioxidant enzymes Tissue samples of 5 young and 5 expanded leaves were homogenized and dialyzed38. The dialyzed samples were used for enzymatic and protein content determinations. Activities of CAT, POX, and SOD were determined39. One unit of CAT and POX is defined as the number of mmoles of H2O2 consumed per minute, and one unit of SOD as the enzyme content which gives 50% inhibition of cytochrome c reduction. Lipid peroxidation Lipid peroxidation of lettuce leaves (n = 10) was determined by measuring malondialdehyde (MDA) production 40 . Tissues samples were homogenized in 0.1% trichloro acetic acid, centrifuged (20,000g, 15min) and the supernatants were collected. To 1 ml aliquots of supernatant, 4 ml of a solution of 20% trichloroacetic acid and 0.5% thiobarbituric acid was added; the mixture was heated (95 1C; 30min),quickly cooled, and then centrifuged (10,000g,10min).

205

Supernatants were used to determine MDA content at 532 nm41. Elemental analysis The elemental analysis was performed by inductively coupled plasma optical emission spectrometry (ICP-OES) using IRIS Intrepid II XSP instrument2. Six point calibration procedure was applied with multi-element calibration solution (Merck ICP multi-element standard solution IV)42. Statistical analysis Data were subjected to one way ANOVA, using the SATATGRAPHICS statistical software package. Least Significant Difference (LSD) Test was applied to assess the significant differences among the mean values of different attributes. The values are means of ten replications. Data were log transformed prior to analysis to ensure normality and equality of variance. The relationships between sites and different parameters were assessed using correlation analysis. There were 6 replicates RESULTS Toxicity symptoms and plant growth Lettuce plants developed visible injury symptoms, especially in older leaves collected from industrial and urban areas which exhibited chlorotic and brown necrotic lesions (Fig. 1). Furthermore,

Table 1: Physiological parameters (Net Photosynthetic rates (PN), Stomatal conductance (gs), Chlorophyll a and b contents, and fluorescence parameters) of lettuce (Lactuca sativa L) plants collected from different sites along urbanization gradient. (Each figure is a mean value of 10 replicates ± SE) Parameter

Control

Rural

Urban

Suburban

Residential Industrial

PN(µmol m -2 s-1) gs(mmol m-2s-1) Chl a(mg g-1) Chl b(mg g-1) Chl a/Chl b Cartenoids (mg g-1) F0 Fm Fv Fv/Fm

23.47+3.2 245+25.2 3.42+0.05 1.86+0.008 1.84+0.005d 1.56+0.007d

20.19+2.8 215+19.6 2.59+0.04 1.47+0.009 1.76+0.007d 1.39+0.008c

11.45+2.1a 125+15.3a 1.24+0.009a 0.80+0.03a 1.55+0.09c 0.75+0.007b

14.72+1.9 174+11.8 2.07+0.01 1.51+0.03b 1.37+0.006a 0.91+0.008c

15.04+2.5 163+14.7b 1.94+0.03b 1.72+0.05 1.13+0.002b 0.82+0.008b

613±34.0a 3037±397.2 2423±153.0d 0.794±0.001f

713±29.5a 2829±75.2 2116±67.8c 0.747±0.009e

901+27.2e 769+22.9c 2206+68.9 2511+65.4 1580+88.9 a 1881+91.7b 0.716+0.004b 0.749+0.003d

10.93+1.5a 132+20.1a 1.02+0.17a 0.76+0.04a 1.34+0.04a 0.64+0.006a

726+30.6b 854+33.7d 2699+89.7 2304+71.6 1980+54.8b 1589+78.5 a 0.733+0.007c 0.689+0.004a

HASSAN et al., Curr. World Environ., Vol. 8(2), 203-213 (2013)

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accentuated necrosis and leaf fall were observed in the oldest plant leaves collected from the same areas during the third week of exposure. The growth of lettuce shoots was significantly reduced in industrial, urban and residential areas (p <0.05) when compared to the control. Length of shoot was decreased by 51, 41, 25, 30 and 18% in plants collected from industrial, urban, suburban, residential and rural sites, respectively (Fig 2).

residential and rural sites, respectively (Table 1). Stomatal conductance (gs) was also decreased by 46, 49, 29, 33 and 12% in plants collected from the same sites, respectively (Table 1).

Figure 3 shows that soils collected from industrial and suburban sites have the highest concentrations of heavy metals.

Table 1 also shows that the maximum quantum yield of PSII ( F v/F m) was decreased significantly (P ≤ 0.05) at industrial and urban sites by 13 and 10%, respectively, while the reductions were insignificant (P > 0.05) in other sites (Table 1). Leaves collected from different sites had a higher basal fluorescence (F0) level (p ≤ 0.01), and a significant decrease in both maximal fluorescence induction (Fm) and variable fluorescence (Fv) value (p ≤ 0.05) when compared to control.

Gas exchange, chlorophyll fluorescence and pigments Net Photosynthetic rates ( P N ) were decreased by 53, 51, 37, 36 and 14% in plants collected from industrial, urban, suburban,

The superficial observations were consistent with the chlorophyll contents and the fluorescence parameters (Table 1). Chl a , b and Chl a/b ratio were decreased by 70, 59 and 27% in plants collected from industrial area, and by 64, 57

Table 2: Response of Antioxidant Enzymes (U/mg protein) and lipid peroxidation (nmol/g fresh wt.) to accumulation of heavy metals Parameter

Control

Rural

Urban

Suburban

Residential

Industrial

LSD

SOD CAT POX MDA

300 a 3.67 c 36.2bc 0.154a

310a 3.16b 31.9b 0.163a

421 b 2.27a 26.1ab 0.201b

354 c 3.01b 32.3b 0.187b

395d 2.87a 33.6b 0.190b

413e 2.16a 25.4a 0.235c

19 0.71 6.45 0.02

Means not followed by the same letter(s) are significantly different from each other at P < 0.05

Table 3: Correlation matrix of different physiological and biochemical; parameters measures (*p< 0.01, **p< 0.001). n= 20 Site PN site — PN gs Chl a Chl b Chl a/b Fv/Fm SOD CAT POX MDA

Chl a

-0.745** -0.639** -0.602** — 0.528** 0.764** — 0.017 —

Chl b

Chl a/b Fv/Fm

SOD

CAT

POX

MDA

-0.549** 0.361** 0.010 -0.318* —

-0.261* 0.209* 0.002 0.428** -0.371** —

0.374** -0.402** -0.021 0.028 0.005 0.021 0.002 —

-0.521** 0.011 0.003 0.017 0.011 0.021 0.002 -0.109* —

-0.370* 0.073 0.107 0.017 0.001 0.003 0.012 -0.121* 0.0162 —

0.417** -0.163* -0.261* -0.192* 0.031 -0.105 -0.219* 0.205* -0.201* -0.015 —

-0.109* 0.872** 0.106 0.519** 0.198* 0.231* —

HASSAN et al., Curr. World Environ., Vol. 8(2), 203-213 (2013) and 16 in plants collected from Urban areas, respectively. These parameters were decreased at other sites but at relatively lower extents (Table 1). Antioxidant enzymes and Lipid peroxidation SOD was increased by 38, 40, 18, 32 and 31% in leaves collected from industrial, urban, suburban, residential and rural areas, respectively (Table 2). On the other hand, CAT activities were reduced by 41, 38, 18, 22 and 14% in the same site respectively (Table 2). Moreover, POX was reduced by 30, 28, 11 in leaves collected from industrial, urban, suburban sites, respectively, while there was no significant (P > 0.05) effect on leaves collected from residential or urban areas (Table 2).

207

Lipid peroxidation as measured by MDA content in lettuce leaves increased significantly (p â&#x2030;¤ 0.05) in plants collected from industrial, urban, suburban and residential areas by 52, 30, 21 and 23%, respectively (Table 2). Rural area had no significant (P > 0.05) effect on MDA (Table 2). A least-squares linear regression analysis was obtained for all sites and different physiological and biochemical markers (Table 3). The results show that the correlation coefficients (r) were significant at p<0.001 for gas exchange measurements (PN, gs. Fv /Fm), Chl contents, SOD, CAT, POX and MDA (Table 3).

Fig. 1: Small chlorotic stippling on the old leaves of the plant. (a) Control plants, (b) plants collected from urban and industrial areas. Arrows indicate Chlorotic and necrotic lesions on leaves

Fig. 2: Shoot lengths of plants collected from different sites. Results are expressed as mean + 1 SE of ten replicates

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Fig. 3: Percentage of different heavy metals collected from different areas

HASSAN et al., Curr. World Environ., Vol. 8(2), 203-213 (2013) DISCUSSION Urban atmospheres, particularly those of megacities tend to have higher concentrations of heavy metals and other pollutants than rural (agricultural) ones, reflecting varying contents of contaminants from industrial and vehicular emissions as well as ash and soot coal fires5,7,14,43, 44 . Nevertheless, here are limited studies on environmental pollution by heavy metals in Saudi Arabia. The reduction in growth recorded in the present study is in agreement with the results reported in literature about effects of heavy meal pollution on growth and yield of lettuce (L. sativa L.), bean (phaseolus vulgaris L.) and Lupinus albus L. plants40, 42 - 48. Chlorophyll content is often measured in plants in order to assess the impact of environmental stress, as changes in pigment content are linked to visual symptoms of plant illness and photosynthetic productivity46-49. Researchers have reported decreased chlorophyll in several different plant species under the impact of heavy metals21. Heavy metals inhibit metabolic processes by inhibiting the action of enzymes, and this may be the most important cause of inhibition21, 47, 50, 51. The percentage reduction in Chl. Contents reported in our study is higher than those recorded in other urban areas in Turkey21, 51 and Nigeria48. This higher percentage of reduction in Chl content of lettuce in the present study is an indicator of disturbances of the pigment synthesis mechanism and inhibition of degradation due to heavy metal effects. Such reductions in Chl content would lead to reduction in photosynthetic rates and eventually growth. Both chlorophyll and A showed a strong negatively correlation with urban and industrial sites, which are characterized by high heavy metal contents in their soils. The chlorophyll ratio, which is used as a stress indicator, decreased significantly with increasing metal concentrations. Such alteration indicates a change in the PSII/PSI ratio in stressed leaves47. Plants

have

evolved

complex

209

antioxidant system to mitigate oxidative stress caused by heavy metals and by other biotic and abiotic stresses. These antioxidants play an important role in the cellular defense strategy. Metals are known to cause molecular damage to plant cells either directly or indirectly through the burst of Reactive Oxygen Species (ROS), which can react with fatty acids leading to the peroxidation of lipids, destroying biological membranes40. Antioxidants like POX, SOD and CAT are ubiquitous and they play an important role in detoxification of toxic metal ions47, 53. They play a crucial role in plant growth and development. Moreover, they are a potential indicator for metal toxicity21, 51, 54. Our results demonstrated that SOD increased linearly with urbanization and contents of heavy metals in soils. Excess of heavy metals can persuade oxidative stress in plants, which can escort formation of ROS. Antioxidant enzymes may alter the H2O2 to the H2O in the plant cells and counteract the toxicity effect of H2O2 54 -55. Hence to shield cells against oxidative stress, antioxidant enzymes augmented proportionally, which is also consistent with our results. On the other hand, activities of CAT and POX were decreased linearly with increasing concentrations of heavy metals. Both increases and decreases were detected in POX and CAT21, 51,54. Exposure to high concentrations of heavy metals resulted in a decreased antioxidant capacity56-57. In our study, CAT and POX were inhibited with extended exposure to heavy metals at different sites, in exposed leaves. This is in a agreement with other studies bean, (Phaseolus vulgaris L.)58 59 , pea, (Pisum sativum L.),60, and in lettuce (Lactuca sativa L.) plants40. MDA is a cytotoxic product of lipid peroxidation and its formation is routinely used as a general indicator of the extent of lipid peroxidation resulting from oxidative stress40,61. The elevated MDA content obtained in lettuce leaves in the present study suggests that heavy metals, induced oxidative damage in lettuce as evidenced by increased lipid peroxidation through either indirect production of ROS or through inhibition of oxidative

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stress enzymes40. Furthermore, MDA content was increased in leaves of a mangrove plant (Bruguiera gymnorrhiza) when exposed to multiple metals62. Therefore lipid peroxidation is recommended as a biomarker of heavy metal stress for pollution monitoring purposes. In general, airborne heavy metal pollution induced senescence in lettuce in the present study, as measured in general as photosynthetic efficiency reduction, decrease in the overall antioxidant capacities of lettuce plants and a MDA production. These alterations were accompanied by an inhibition in the classical endpoint, shoot growth, at the end of exposure. These biomarkers could be used in integrative approaches with classical endpoints in ecotoxicological tests; especially this study was conducted real field conditions. Therefore they could form the basis for monitoring and be predictive of early effects of this pollutant before they give rise to significant changes in natural community structures.

CONCLUSIONS Laboratory and field studies have provided encouraging insights into the capacity of lettuce plants to act as biomonitors of air pollution through the use of biomarkers. However, a better understanding of the overall process of metalinduced senescence, describing the cascade of their effects in plants is needed for a selection of relevant biomarkers of heavy metal stress. Lettuce plants proved to be suitable as usage in environmental studies as a bioindicator. ACKNWOLEDGEMENTS Authors are indebted to Scientific Deanship at King Abdulaziz University for continuous support. This work is supported by a grant (4/H/1433). We would like to thank Prof N. Saied (Braunschweig, Germany) for her technical support and Ms Samah Shata for her keen assistance.

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Current World Environment

Vol. 8(2), 215-220 (2013)

Effect of Potato Starch on Thermal & Mechanical Properties of Low Density Polyethylene SHAHRZAD KHORAMNEJADIAN1*, JAMILEH JAMALI ZAVAREH2 and SHIRIN KHORAMNEJADIAN3 1

Department of Environment, Damavand Branch,Islamic Azad University, Damavand, Iran. 2 Department of Environment, Alborz province, Karaj, Iran. 3 Chemical Engineering Student, Islamic Azad University, Tehran, Iran. http://dx.doi.org/10.12944/CWE.8.2.06 (Received: October 05, 2012; Accepted: June 05, 2013) ABSTRACT In this article, biodegradability of Low Density Polyethylene (LDPE) with potato starch was studied. Polyethylene grafted maleic anhydride (PE-g-MA) used as a compatibilizer. Samples with different levels of potato starch (as10%, 20%, 30% and 40%) with constant amount of PE-g-MA as 5% were prepared. In all samples amount of compatibilizer are the same. The effect of potato starch content on the thermal properties of blend studied with a differential scanning calorimeter (DSC). Result show with increasing potato starch content, crystallization decreased. The biodegradation of blends was studied with soil burial and exposure to mould growth. Biodegradation determined by weight lose, the change in tensile properties of the sheets and mould growth. The results showed that with increasing potato starch content biodegradability of blends increased. Biodegradation of the samples due to soil burial after 8 months revealed that the weight of the blends was decreased by increasing the potato starch level.

Key words: Potato starch, LDPE, DSC, Soil burial, tensile. INTRODUCTION Plastics are one of the major parts of municipal waste1. Most of the studies developed by blending petroleum based polymers with natural biodegradable materials that not only conserved the environment, petroleum reserves and landfills but also decrease the CO2 production and generally culminate to the sustainable development. The biodegradable polymers are the materials that converted in to the natural compounds of water, CO2, methane and other biological component by microorganisms such as fungi, bacteria, algae and other natural agents2. Low density polyethylene is employed in packaging industries and production of bags, composites and agricultural mulches3. Study on the starch based synthetic polymers has begun from 1970s 4. There is a special attention to use starch as biodegradable filler5. Starch is an abundant,

biodegradable, recycling and inexpensive natural polymer obtainable from many botanical sources like potato, Cassava, cornâ&#x20AC;Ś6, 7, 8. Biodegradable starch based polymer has a potential to produce in a large scale and low cost9.Usage of starch based polymers has a benefit for environment conservation, because they reduce an exploitation of the nonrenewable resource. Consume a nonrenewable resource emit CO2 that caused a global warming . Starch composed of amylose and amylopectin. The amount of amylose and amylopectin are different between varies source of starch. Rate on this two had an effect on product behavior. Potato is one of the sources of starch in the world. A biodegradable plastic is the one which can be processed by the bacteria to the simpler forms. Biodegradable plastics has similar properties

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like as the common plastics but it can be degraded by microorganism after disposal in the soil or other environments 10 .Biodegradation occurs when microorganism such as bacteria or fungi consumes polymer in an aerobic or anaerobic environment. Output of degradation process includes: Carbon dioxide, methane and other natural products11. Several mechanisms are involved in the degradation of plastics, one of them is a microbial degradation in which microorganisms such as fungi or bacteria consume the materials. The degradation process is based on the plastics environment and their application. It’s better to estimate the biodegradability characteristics of the plastic materials under natural condition where the plastic wastes are exposed under the natural biological process in the nature12. Weight loss is a common method to measure the rate of biodegradation of polymer samples. In this project biodegradable compound of Low Density Polyethylene (LDPE) with potato starch was made. Polyethylene grafted maleic anhydride (PE-g-Ma) used as a compatibilizer. Potato starch used as biodegradable filler in a different amount of 20, 30 and 40 percent. The amount of comaptibilizer was the same in all samples and about 10%. Biodegradability of compounds was determined by soil burial test and exposure to the mould growth. The effect of biodegradable filler on mechanical and thermal properties of blend were studied. EXPERIMENTAL Low Density Polyethylene (LDPE) with commercial grade 0200 prepared from Bandar Imam petrochemical complex, IRAN. Food grade potato starch obtained from Alvand co. IRAN. Glycerol with food grade belongs to Merck co. Germany. Polyethylene grafted maleic anhydride (PE-g-Ma) produces in Karankin Co., IRAN. Olive oil used as a moisturizer. Starches powder plasticized with 25wt% glycerol at 180°c for 10 minute. Samples were processed in HBI system (HaakeBuchler Company from UK) with 60 rpm in 160°C. Sample sheets (0.4 mm thickness) were prepared by using Hot Mini

Press.The tensile properties were measured by Santam (STM-20) instrument. The suspension prepared in distilled water with 0.05% dioctyl sodium sulphosuccinate. Spore solution was put in sterile Petri dish. The polymer samples immerse into suspension. Then transferred to another sterile Petri dish and incubated in humidity greater than 90% and 30° C for 84 days. According to standards 8 kind of mould species included Aspergillus niger, Aspegillu sterreus, Aureobasidium pullulans, Poecilomyces variotii, Penicillium funiculosum, Penicilliumochro chloron, Scopulariopsis brevicaulis, Trichoderma viride used for test. A METTLER-TOLEDO differential scanning calorimeter (DSC) was used for Thermal analysis. Samples of 10 to 15 mg were initially heated in a nitrogen atmosphere from 25°C to 170°C at a heating rate of 10 oC/min. The samples were then cooled from 170°C to 25°C at a cooling rate of 10oC/min. The melting point reported here is the temperature of the maximum in the melting peak. Samples cut in strip shape and buried into soil for 8 months. Samples were weighted before soil burial. At the end of the second, fourth and eight month samples were removed of soil and weighted. RESULT AND DISCUSSION The weight loss of polymer sheets during biodegradation in soil indicates the amount of degradation in natural environment. Soil microorganism is attacking the samples. Potato starch content consumed by soil microorganisms, then make a fracture in polymer chain. In general, the potential of soil biodegradation is calculated by the following equation: Soil biodegradation (%) = [(W-W0) / W0] × 100 ...(1) Here W is a secondary weight of sample and W0 is a primary weight of sample. According to the Fig 1, after eight months soil burial pure LDPE didn’t show any change in weight. Weight loss of samples with different amount of potato starch has been observed from second

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Table 1:Thermal properties of LDPE/ Potato starch compounds Potato starch content (%)

Crystallization temperature (Tc)

Melting temperature (Tm)

99.93 100.7 100.11 100.27

111.17 110.98 112.06 111.91

0 20 30 40

Table 2: Visual examination of mould growth of LDPE/ Potato starch compounds1 Potato starch content (%)

Extent of growth

0 20 30 40

0 2 3 3

0= no growth apparent under a nominal magnification of approximately 50× 2= growth plainly visible to the naked eye, but covers less than 25% of the test surface 3= growth plainly visible to the naked eye and covering more than 25% of the test surface

Table 3: Mechanical properties of LDPE/ Potato starch compound. Content of potato

Elongation at break (%)

Tensile strength (Mpa)

starch (%)

before

after

before

after

0 20 30 40

286.846 38.26 20.74 15.13

283.321 28.03 11.1 4.03

2.85 2.54 2.17 2.02

2.01 1.498 1.32 1.112

months. Highest degree of biodegradation belonged to the sample with 40% potato starch content. Weight loss indicated the starch removal from the polymer matrix by soil microorganisms. Soil environment contain a different kind of microorganism and macro organisms. Soil microorganisms attacked the polymer strips. Microorganisms attracted to the potato starch content of compounds. Microorganisms consumed potato starch in the polymer matrix and caused a fractured in the LDPE chain. Because of the existence of maleic anhydride – that made a

chemical bond between LDPE and potato starchdegradation of potato starch caused a fracture in the polymer matrix and biodegradation of LDPE7. Fig 2, show the DSC heating curve of LDPE/ Potato starch compounds. The ‘‘crystallization temperature (Tc)’’ an ‘’melting temperature (Tm )’’ expressed on table 1. It can be seen there is a slight increase in Tc, and also incorporating the starch in the polymer causes small variation in Tm.

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Fig. 1: Weight loss of different polymeric samples during 8 months soil burial

Fig. 2: DSC heating curve of LDPE/ Potato starch compounds

Fig. 3: DSC cooling curve of LDPE/ Potato starch compounds.

KHORAMNEJADIAN et al., Curr. World Environ., Vol. 8(2), 215-220 (2013) Rate of amylopectin and amylose of starch affects starch based product. Highest amount of amylase in the potato starch caused an increasing in the crystallinity of final potato starch based product. It might be brought about by the presence of the potato starch particles in polyethylene matrix that hinder the crystallization of LDPE molecules, therefore disordering increases a bit and crystallinty content decreases. This can be a result of nucleating effect of potato starch that causes the crystallization of PE molecules starts sooner and the peak temperature take places in higher temperature. Crystallization peak area for LDPE/potato starch compounds were smaller than that of LDPE, because of hindering effect of potato starch particles. This result also reported by other researchers8. Fungi colonized potato starch/LDPE surface over 80% of samples with 30% and 40 % of potato starch at the end of incubation. After 84-days incubations LDPE strips didn’t exhibit color change or mould growth. Result similar to other researchers work on polymer degradation10. Table 2 show the results of visual examination mould growth of LDPE/ Potato starch Potato starch in polymer compounds had a digestible link for mould and fungi. Microorganisms recognized the potato starch carbon link as a nutrient source. Consumption polar hydrophilic starch caused the fractured into the polymer chain. Maleic anhydride created a link between two incompatible particles, so with starch removal a gap appeared in the polymer chain. Through the gap microorganism’s access to the carbon link of low density polyethylene, the result is the polymer biodegradation.

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Table 3.Contain a result of mechanical properties of LDPE/ potato starch compounds. Because of holes formed during biological degradation in soil mechanical properties of compound decreased4.Highest destruction referred to samples with 40% of potato starch content. Expected with the increase the test time the better result is observed. That situation in accordance with Results is similar to other research 13 . Soil microorganisms attacked the polymer. First of all, microorganisms attracted to the potato starch content of blends. Microorganisms consumed potato starch in the polymer matrix and caused a fractured in the LDPE chain. Because of the existence of maleic anhydride – that made a chemical bond between LDPE and potato starchdegradation of potato starch caused a fracture in the polymer matrix and biodegradation of LDPE. CONCLUSION In this article biodegradable compound of Low Density Polyethylene (LDPE) with potato starch was made. Biodegradability of LDPE/potato starch compound estimated under soil burial and exposure to mould growth. Weight loses during 8 month soil burial shows the degradability of compounds in the natural environment. Thermal properties of LDPE/potato starch compound determined the effect of potato starch on melting point and other properties of final product. Microbial degradation in laboratory by 8 kinds of fungi approved the biodegradability of potato starch / LDPE compound. Existence of anhydride maleic created linkage between LDPE and potato starch, so consumption of potato starch in any environment caused a destruction of polymer matrix. Mechanical properties of LDPE/potato starch compound before and after soil burial indicated that compound were biodegradable.

REFERENCES 1.

Kozlowska, A.;Gromadzki, D.; El Fray, M.;‘tpánek, P. FIBRES & TEXTILES in Eastern Europe, 16, 6 (71): 85-88 (2008). Rutkowska, M.;Heimowska, A.;Krasowska; K.;Janik, H.; Pol. J. Environ. Stud. 11: 267274 (2002).

3. 4. 5.

Raj, B. ;Sankar, U.; Adv Polymer Tech, 23: 32-45 (2004). Ratanakamnuan,U.;Aht-Ong, D., J. Appl. Polymer Sci, 100: 2725–2736 (2006). Matzinos, P.; Bikiaris, D.;Kokkou, S., Panayiotou, C., J. Appl. Polymer Sci, 79:

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6. 7.

8. 9.

KHORAMNEJADIAN et al., Curr. World Environ., Vol. 8(2), 215-220 (2013) 2548-2557 (2001). Parra, D.F. ;Tadini, C.C.; Ponce, P.;Lugao, A.B.;carbohydr. Polym, 58: 475-481 (2004). Borghei, M.;Karbassi, A.;khoramnejadian, S.;Oromiehie, A.;javid, A.; Afr. J. Biotechnol. 9(26): 4075-4080 (2010). Ciesielski ,W.; Tomasik, P. Bull. Chem. Soc. Ethiop. 17(2): 155-165(2003). Parra, D.F.;Tadini, C.C.; Ponce, P.; Lugao,

10.

11. 12. 13.

A.B.; carbohydr. Polym, 58: 475-481 (2004). Abdul Rahman, W.;Rasit Ali, R.;Zakaria, N.; 1st IntConf Natural Res EngTech, Malaysia, (2006). Raghavan, D.; Polymer Plast Tech Eng, 34, 41-63(1995). Orhan, Y.;Hrenovi, J.;Büyükgüngör, H.;Acta Chim. Slov.51: 579-588 (2004). Wang, S.; Yu,J. ; Yu, J. polym. int.54, 279-285 (2005).

Current World Environment

Vol. 8(2), 231-240 (2013)

Localized Profile of Arsenic in Soil and Water in the Area Around Gold Mine THANES WEERASIRI1, WANPEN WIROJANAGUD2,3 and THARES SRISATIT4 1-3

Faculty of Environmental Engineering, Khonkaen University, Thailand. Centre of Excellence on Hazardous Substance Management, PERDO, Bangkok, 10330 Thailand. 4 Faculty of Environmental Engineering, Chulalongkorn University, Thailand.

http://dx.doi.org/10.12944/CWE.8.2.08 (Received: July 17, 2013; Accepted: August 12, 2013) ABSTRACT Soil and water samples from the area vicinity to gold mine at Wangsaphung District, Loei province, have been collected to investigate the arsenic concentration. Five boreholes were drilled into the ground until reaching to gravel layer or bedrock, and Soil samples were collected at every 0.50 - meter depth. Four boreholes are located inside the catchment in which the gold mine situated whereas the other one was bored at the outside. In addition, 13 sets of surface water and 8 sets of groundwater were also collected. The results of concentration test indicated that soil samples within at least 3 boreholes have arsenic content enormously exceeded the maximum concentration limits (MCL) specified by the Office of National Environment Board of Thailand. Geologic condition underneath soil layer also play an important role on the concentration of arsenic. Soil column placed on the originally-deposited gravel bed can retain less concentration of arsenic, whereas soil column on bedrock can retain much more. For water samples, arsenic contents were generally less than 10 Âľg/l, the MCL specified by U.S.EPA, except that there is one interesting location found extremely high. That location give an useful information for further finding of arsenic pathway.

Key words: Contamination, Arsenic, Gold mine, maximum concentration level

INTRODUCTION Exposure to arsenic can result in a variety of health problems in humans, including various forms of cancer (e.g. skin, lung, and bladder), cardiovascular and peripheral vascular disease, and diabetes. Human encounter arsenic from natural and anthropogenic sources (Henke, 2009). Environmental Protection Agency (U.S. EPA) specified that the arsenic contamination in drinking water should be less than 10 Âľg/l. In case of soils used for agriculture and for other usages, the Office of National Environment Board of Thailand set the maximum concentration limits (MCL) to be of 3.9 mg/kg and 27 mg/kg, respectively. Arsenic enters the environmental through herbicides, wood preservatives, and mining

industry (Chopra, Parmar, 2007). It can distribute in either soil or water, transport to other places, pollute to water resources, and subsequently affect water for daily consumption. Gold mining also contributes to the distribution of arsenic. During gold extraction, arsenic, which is the composition of Arsenopyrite, is also separated and diffused into soil and water, and pollutes to the environment (Henke, 2009). Gold mining at Wangsaphung district, Loei province of Thailand, is the one of mining industry that encountered this problem. After starting its work in 2006, villagers from 6 villages complained that the natural water they normally use become contaminated with arsenic resulting in affected human life, which has never been before. Related government agencies and staffs from the goldmine have investigated the arsenic contamination in both

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surface water and groundwater, the study revealed that contamination level is less than MCL. The objective of this study is to investigate whether there are arsenic contaminated in soil and find the amount of concentration both in water and soil. It would be the first study for investigating arsenic in soil for this area and the results will give the preliminary guidelines for further studies in the distribution, direction, and transportation of arsenic, which will be advantageous for managing the agriculture and living area in near future. General Information Loei, one of 76 provinces of Thailand, is situated in Northeastern part attached to the Maekong River and border of Republic of Laos. The area of this study is in Wangsaphung district of Loei province (Figure 1), which is mountainous and plateau area. The altitude of gold mine is about 300 meters from mean sea level. Within 5 kilometers from the goldmine, there are 6 villages that have the most impact from arsenic including Ban Nam Huai, Ban Na Nong Bong, Ban Huai Phuk, Ban Kok Sathon, Ban Kaeng Hin, and Ban Tak Daed (Figure 2). The nearest village to the goldmine, 250 meters from the mine and at the altitude of 277meters from the mean sea level, is Ban Na Nong Bong. In those 6 villages, the farthest one is Ban Tak Daed, which is 5 kilometer from the mine and at the altitude of 276 meters from the mean sea level. Most of lands were engaged in farming and cropping plants such as bananas, tapiocas, nuts, and rubber trees. Within catchment area that goldmine situated, there are many small waterways such as Huai Nam Chan, Huai Muno, Huai Haeng, Huai Khok Yai and Huai San, flowing form high elevation at the top of plateau directing to lower elevation area and combining to be one stream, called Nam Huai stream, finally joint together with Loei River. Geological characteristics The area in Loei province consists of metamorphic, sedimentary, and igneous rocks, dating back from Silurian - Devonian to Quaternary period. The rock in each period has its own characteristics. Fossils can be found in some of sedimentary rocks, which can be exactly dated. Geological structure of rocks lies in North-South

direction. The observed igneous rocks include volcanic and plutonic rocks, which mostly classified as granitic rocks. Sedimentary rocks are from regional, contact, or from thermal metamorphism. (Putthapiban, 1987) The geological map of Thailand No. 5343 IV (Figure 4), located the area in between 17o15’ N – 17o30’ N latitude and 101o30’ E – 101o45’ E longitude covering the study area, shows that the underlaid rock types are micaceous sandstone, siltstone, shale, mudstone, and dark gray with plan fossils. The altitudes of rock at the location corresponding to gold mine and nearby villages are approximately 300 meters from mean sea level. The mineral and potential mineral map No. NE 47-12 (Figure 3), located in between 17o00’ N – 18 o00’ N latitude and 100 o30’ E – 102 o00’ E longitude covering the study area, displays that there are many minerals in this area either metallic or non-metallic, e.g. iron (Fe), gold (Au), copper (Cu), lead (Pb), zinc (Zn), manganese (Mn), coal (anthracite) and gypsym (CaSO 4 × 2H 2 O). Determining throughout the map, there is the gold mineral in many places seem to be as the whole area not concentrated only on the study area. Sampling collection and testing Soil and water samples were collected to quantify arsenic contaminant. The positions of sampling are mostly in the catchment area covering gold mine and affected villages. However, another position of soil and water samples outside the water basin was also acquired for comparison. The details of soil and water samplings are shown below: Soil sampling Five boreholes (BH) have been drilled into the ground and soil samples were collected at 0.50 meter along the depth of borehole. Total depth of each borehole depends on the level of rock or gravel bed underneath, or until the standard penetration number, the number of hammer drops to push sampler into the ground, is greater than 50 Bl/ft (ASTM, 2000). The position of each borehole are depicted in Figure 5. As clearly seen, BH 5 is at Ban Kok Chumsaeng outside the study catchment. Each soil sample was measured pH value before wrapping with foil sheet and coated with paraffin to

WEERASIRI et al., Curr. World Environ., Vol. 8(2), 231-240 (2013) protect the moisture loss and oxidizing reaction that might be occurred during carry on for further tests in laboratory. Water sampling Surface water samples have been collected from 13 positions and samples of groundwater have been collected from 8 position. All positions were shown in Figure 5. The samples are treated to remain acidic by nitric acid (5% concentration), and poured in the light brown bottles, sealed with masking tape for conducting arsenic contamination test. Testing Inductively Coupled Plasma Mass Spectrometry (ICP-MS) method was utilized to quantify the arsenic contaminants in either soil or water. This technique provides high precision determination of substance, even metallic or nonmetallic, from relatively small amount of samples (Skoog et al., 2007). The procedure starts from grinding/homogenization, weighing, digestion, dilution, and final measurement. Since this technique related to analytical chemistry and spectrometry, more details of this method can be found in Bailey et al, (2003). RESULTS AND DISCUSSION Arsenic contamination in water Laboratory results reveal that the amount of arsenic in surface water and groundwater (Table 1 and Figure 6) are not more than MCL of 0.01 mg/ l in general areas, except at one position called Phulek creek. Arsenic content at that location significantly exceeds MCL both in surface water (SW1, SW2, SW3 and SW4) and groundwater (GW3 and GW8). Considering the geography map, the position of Phulek creek is at the mouth of mountainous pass, therefore it may be possible that the water would flow from upper area nearby goldmine and carry arsenic to the sampling location as SW1, SW2, SW3 and SW4. Arsenic contamination in soil Soil samples from 5 boreholes have been classified using the Unified Soil Classification

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System. Soil profiles and their altitudes were orderly arranged from high to low elevation of existing ground level; those are BH5, BH4, BH1, BH2, and BH3, respectively, as shown in Figure 7. These boreholes represent rather similar soil profiles which are the alternate layer of clay, silty clay, and sandy silty clay. However, most soil types were classified as silty clay and sandy silty clay, as can be seen in Shepard chart shown in figure 8. Because of their high cohesion, silty clay and sandy silty clay can allow lower permeable than coarse grained soil as sand and gravel. Contaminant test results reveal that all soil samples have arsenic contaminants and most of them contain more than 3.9 mg/kg, the MCL designated by the Office of National Environment Board of Thailand, as detailed in Table 2. The average arsenic contaminant in some boreholes present somewhat higher than 27 mg/kg, the second level of MCL for other usage in Thailand, Table 1: Arsenic Contamination in waters

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Table 2: Arsenic Contamination in soils

WEERASIRI et al., Curr. World Environ., Vol. 8(2), 231-240 (2013) such as BH1, BH4, and BH5, with the average value of 41.90, 48.84, and 30.94 mg/kg, respectively. It can be noticed that even in the soil samples of BH5 which were located outside of study catchment also have much high arsenic content. By the reasons of location at outside and highest ground elevation of BH5, it can be indicate that there also exists arsenic in nearby catchment. The arsenic content found in whole area may not merely come from

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anthropogenic sources as goldmine or some other mining activities. However, site characterization in the catchment around and close to goldmine may possible give the best indicator for finding out the elevated arsenic. Arsenic concentration versus depth, as in figure 9, illustrates that there are seriously potential risk to human health since there are much higher

Fig. 1:Loei province is situated at the northeastern part of Thailand and Wangsaphung is district in Loei province

Fig. 2: Location of gold mine and 6 villages that have the most impact from arsenic

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Fig. 3: Map of potential mineral resources at Wangsaphung, Loei province. (Department of Mineral Resources, 2001)

Fig. 4: Thai Geological map No.5343 IV covering study area. (Department of Mineral Resources, 2008)

WEERASIRI et al., Curr. World Environ., Vol. 8(2), 231-240 (2013) of arsenic content than MCL in root zone, about within 1 m depth from existing ground level, especially at BH1, BH4, and BH5. Remarkable notice was found at BH4 which is the location of plain area at the mountain pass nearby goldmine. Within 4 m depth from top soil, range of arsenic contents are 42.27 mg/kg to 118.2 mg/kg which is the largest quantity compared to those of soils at

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corresponding depths in other boreholes. Elevated arsenic only exists in the top four meter depth, however, it gradually decreases with greater depth and finally reach to the concentration quantity approximately close to those in the soils at BH2 and BH3. As of such appearance, this location may be a possible place that arsenic-carrying water passes through. Greater detailed study starting from

Fig. 5: Position of water sampling and location of soil drilling

Fig. 6: Arsenic concentration in water at each position, orderly plotting from high to low elevation of existing ground level

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this location would probably point out its pathway which finally can give the source. Considering geological characteristics, depicted in Figure 4, it can be seen that the bottom of BH2, BH3, and BH4 are placed on the originally deposited gravel, which is somewhat loose media, whereas BH1 and BH5 placed on sandstone which is denser. Arsenic concentration at the bottom of bore holes seem to be quite different. At the lower part near the bottom of BH2, BH3 and BH4, which

place on the gravel layer, the concentration of arsenic is lower compared to those of BH1 and BH5. Especially in BH4, the concentration of arsenic is even so high at the upper depth but abundantly decreases to the low value near the bottom part. Geologic condition plays an influence on the accumulation and the occurrence of arsenic in the deeper soil layer. As of having more pores in gravel, water can easier flow pass with arsenic, leading less accumulation of arsenic in that place. Unlike BH2, BH3, and BH4, the BH1 have arsenic quantity

Fig. 7: Soil profiles and arsenic contaminated in soil relative to depth

Fig. 8: Soil types identified using Shepard triangular. Most soil samples at each borehole were classified to be silty clay, sandy silty clay and silty clay with sand

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Fig. 9: The amount of Arsenic contaminated in soil versus depth of each borehole. increased with depth and still retained high arsenic content at the bottom due to the densely impermeable bedrock. Since higher arsenic content present at the bottom, it also reveals that arsenic can comes from bed material which may be arsenopyrite or other arsenic-bearing minerals. CONCLUSION This study reveals that the arsenic contaminant can be found at all excavation points. The contamination does not only occur in the study catchment. It is possible that the arsenic originally exist over there for long time before. Soil samples of at least 3 locations have arsenic contaminant greater than MCL of 3.9 mg/kg. In most area Arsenic

content in water is less than MCL of 10 Âľg/l, except for those at the location called Phulek creek. Surface water at Phulek creek have remarkable contaminant, and consistently agree with those in top soil of adjacent borehole. This position is the mouth of mountain pass, where the water can flow from upstream nearby goldmine and downward passing through. Because of its plain area, the water might drain arsenic from goldmine and settle there. The study indicates that more information can be taken from the contaminant in soils. The location for further study can be selected from these findings. The influence factors of studying arsenic distribution such as the geological characteristics, compositions of soil, porosity and permeability of

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soil, may be needed to be determined. The arsenic mobility which would threaten villages, will be of greater importance in next study.

ACKNOWLEDGEMENTS This work has been supported by the Higher Education Research Promotion and National Research University Project of Thailand, Office of the Higher Education Commission.

REFERENCES 1.

American Society for Testing and Materials Annual Book of ASTM Standards. West Conshohocken, PA.,Vol.04.08 (2000). Bailey, R.M., Stokes, S., Bray, H., Inductively Coupled Plasma Mass Spectrometry (ICPMS) for dose rate determination: some guidelines for sample preparation and analysis, Oxford, UK:Oxford Luminescence Research Group, School of Geography and the Environment, University of Oxford, (2003). Chopra, H.K., Par mar, A. Engineering Chemistry - A Text Book. India: Alpha Science International Ltd., 5-10 (2007). Department of Mineral Resources, Bureau of Geological Survey, Geological map of Thailand 1:50,000, Loei, Thailand (Sheet 5343IV) (2008). Department of Mineral Resources, Mineral resources map 1:250,000 (Sheet NE4712),From http://www.dmr.go.th/download/

10.

map/250000/NE47-12.pdf, Retrieved January 6 (2010). Henke, K.R., Arsenic Environmental Chemistry Health Threats and Waste Treatment. 1st ed., John Wiley & Sons. Ltd.,15, 238-243 (2009). Putthapiban, P., Geology of AEM area, Loei Province and mineral potential. 4th Academic conference, Department of Mineral Resources, p.39-67 (1987). Shepard, F.P., Nomenclature based on sandsilt-clay ratios. J. Sed. Petrol. 24, 141- 158 (1954). Skoog, D.A., Holler, F.J., Crouch, S.R. Principles of Instrumental Analysis. 6th ed. Canada: Thomson Brooks/Cole, 291-299 (2007). United States Environmental Protection Agency, Arsenic in Drinking Water, http:// www.epa.gov/safewater/arsenic/index.html, Retrieved February 10 (2010).

Current World Environment

Vol. 8(2), 241-250 (2013)

Heavy Metal Runoff Dynamics from Farmland Around IKPA River Basin, Nigeria EDEM, I. DENNIS1*, ROSEMARY A. ESSIEN2 and UTIBE-ABASI H. UDOH3 1

Department of Soil Science and Land Resources Management, Faculty of Agriculture, University of Uyo, P.M. B.1017, Uyo, Akwa Ibom State, Nigeria. 2 Department of Crop Science, Akwa Ibom State University. 3 Department of Animal Science, Faculty of Agriculture, University of Uyo, Uyo. http://dx.doi.org/10.12944/CWE.8.2.09 (Received: July 23, 2013; Accepted: August 20, 2013) ABSTRACT

Discharges of zinc, copper, cadmium and lead from farmland were examined based on field measurements conducted between May 18 and October 14, 2012 on poultry droppings and NPK fertilizers. The study fields are located on 15 % slope gradient area where water body of a river was contaminated with water drained from upstream farmlands. The area of the farmland is 10.7 ha, of which 0.5 ha had been used for cassava cultivation under vetiver hedge management. The mean level of Cu concentration on application of fertilizers was significantly high when compared with the control (C) plot, leading to the conclusion that fertilizer application (organic or inorganic) affects Cu level in a farmland (PD-5.66, NPK-5.82, C- 2.76). Also greater percent of this metal was easily washed off during rainstorm into the stream (PD-5.90, NPK-6.06, C-4.70). Lead concentrations in soil were 0.232, 0.211 and 0.145 mg/kg and in runoff water, 0.12, 0.25, 0.17 mg/kg for Poultry droppings and NPK, amended soils and control respectively. The acidity level in runoff water and soils was the same, whereas organic matter content was 300 % higher in the soil. This implied that the organic matter was not easily removed from the soil during storms that resulted in overland flow.

Key words: Heavy metals, Runoff, Ecosystem, Farmland, Drained, Ikpa river, Poultry droppings.

INTRODUCTION Soils are not only a medium for plants to grow or a pool to dispose of undesirable materials, but also a transmitter of many pollutants to surface water, atmosphere and food. Therefore accumulated pollutant in surface soil can be transported to different environmental components. Soil pollutant may threaten the human health not only on hygienic quality food, but also on drinking water. In recent years, environmental problems such as heavy metal pollution have become important issues1. Some heavy metals are necessary to support life, but other heavy metals form toxic chemical compounds can affect the ecosystem2. The quality of life on earth is linked undeniably to the overall quality of the environment3. Pollution of the biosphere by heavy metals due to the industrial, agricultural and domestic activities has created a serious problem for safe and rational

utilization of soils. Agronomic application of fertilizers and pesticides continue to contribute to metal accumulation in the soil. The pollution of the ecosystem by heavy metals is a real threat to the environment because metals cannot be naturally degraded like organic pollutants and persist in the ecosystem having accumulated in different parts of the food chain4. Fertilizer toxicity may affect all forms of different organisms. Physical, chemical and biological processes many combine under certain circumstances to concentrate metals rather than dilute them. Zn, Cu, Cd and Pb are listed in the environmental quality standard for soil and water pollution in Nigeria5. These heavy metals have not only drawn attention in terms of their listing as part of the environmental standards, but it has also been pointed out that there is some level of toxicity with

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regard to drinking water and aquatic life. Since lead inhibits the supply of metabolic products that acts as electron acceptors, it tends to inhibit the activity of nitrate reductase6. They also reported that concentration of arsenic in surface water around agricultural field is high. In this study, water and sediments discharge of Zn, Cu, Cd, and Pb from farm land were examined using field data of 2012 rainy season. In particular, the study focused on the effect of fertilizer applications and rainfall runoff on the discharge of heavy metal from farmland. MATERIALS AND METHODS The research was conducted in a continuous cropped arable experimental plots located at Faculty of Agriculture, University of Uyo Teaching and Research Farm (FAUUTRF), AfahaOku, Uyo, Nigeria. The area lies between latitudes 40 52’ and 50 3’N and longitudes 70 51’ and 80 20’ E and altitude 65 m from the sea level. The area is divided into two distinct seasons, the wet and dry seasons. The wet or rainy season begins from April and lasts till October. It is characterized by heavy rainfall of about 2500-4000 mm per annum. The rainfall intensity is very high and there is evidence of high leaching and erosion associated with slope and rainfall factors in the area [7]. In the area measuring 0.5ha on a slope of 15 %, were prepared 12 plots; each 60 x 5 m2, separated from each other by foot tracts. Application of treatments Poultry manure (Organic) of 20 t ha-1 and inorganic fertilizer (NPK) 300 kg ha-1 [8] were allocated to the experimental plots that were replicated three times to measure heavy metal concentration between fer tilizer types. The experimental field was cleared and seed bed was well prepared by ploughing and harrowing during the season. The well-cured poultry manure was applied at two weeks before planting by broadcasting and completely worked into the soil. While the inorganic fertilizer was applied 2 weeks after planting. One Cassava cutting was sown at 1m interval during the cropping seasons giving a total of 270 plants per plot and plant population of 3240 plants per 0.36 hectare planted area. A trench measuring 1.5m high and 1.2m wide were dug across each experimental plot to accommodate

runoff collecting tanks that were installed there. There were three collecting tanks (90 cm high and 58cm in diameter) in each of the plots. The collecting tanks were placed directly under the three PVC pipes installed at the silled end of the weirs. At the bottom end of each collecting tank, just below 1cm above the floor of the tank, was a tap installed, through which the runoff water was discharged after taking the measurement. Sampling strategy Soil sampling A total of 36 soil samples (18 each) of poultry and inorganic fertilizer applied soils respectively from locations labeled P1, P2, P3,P4 P5 and N1, N2, N3, N4, N5 were collected from the soil surface using stainless steel auger. In addition these samples, control soil samples (C1, C2) were collected from the farmland. The collected samples were sieved through a 2 mm sieve and stored for pre-washed polyethene plastic bags for subsequent sample preparation and analysis. Physico-chemical characteristics of the soils; pH, organic matter, and heavy metal contents were determined using the methods described by Gupta9. Discharge carried by runoff water The discharges from different treatments carried by runoff water into the collecting tanks were sampled from each tank after every storm for determinations of heavy metals concentration from the farm. Before taking the aliquot from the tanks into 50 cl bottle, the runoff water was thoroughly stirred. The samples taken from each of the tanks were taken to the laboratory and allowed to settle for two to three days while the water in the tanks was drained for further use. The settled aliquot was further filtered with Whatman’s filter paper (No 42) and the sediment (residue) was put into a Petridish and oven dried. The dried sample was weighed and thereafter multiplied with the total runoff water in the collecting device to obtain the total weight of soil washed by runoff into the respective collecting devices. This amount was then added to the dry weight of the eroded soil collected from the ditch and expressed in milligram per kilogram soil /litres of water (mg*kg-1 and mg/l) . The samples were then submitted for multi-element analysis in an accredited laboratory (Lasunnex laboratory Ltd. PHC).

DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013) Heavy metal determination Inorder to measure the available contents of zinc, arsenic, cadmium and lead, a single extraction method EDTA leaching test was performed. This method is commonly used by agronomists to evaluate the phyto-availability fraction of metal from soils. Approximately, 0.2 g of the soil sample was weighed and put in a 100 cm3 conical flask. Fifty cubic centimeter 50 cm3 of disodium EDTA (0.05 M at pH 7.0) were added and shaken 10 revolution per minute for an hour on the shaker. The solutions were filtered through Whatmanâ&#x20AC;&#x2122;s 0.45 filter paper and the filtrates were read for zinc, copper, cadmium and lead by Atomic Absorption Spectroscopy (AAS) It is worthy of note that, the extractable fractions of these metals in soil are the possible content which can be taken up by the plant roots, while the amount in the runoff often give an idea of the size of pool that might be emptied into the water body and caused eutrophication. Since selected soil properties of pH and organic matter play an important role in the retention and release characteristics of heavy metals, soil pH was measured in suspension (soil/water 1:2.5) and organic matter was analysed by the WalkleyBlack method [10] Statistical analysis of data The concentrations of Zn, Cd, Cu, Pb and pH and organic matter in agricultural soil were analysed to assess an adequate distinction between different cases. Contents in water and soil were compared using the t-test. A significant difference between any pair of means of sample population is concluded when the probability has a difference by 0.05. Multivariate statistical techniques, ANOVA and discriminant analyses were performed using SPSS for Windows (release Ver. 11. Inc.Chicago). RESULTS AND DISCUSSION Exploratory data analysis Tables 1 and 2 provides summar y statistics for the heavy metal, pH and organic matter contents in soil sample and runoff water from soil amended with poultry droppings and NPK fertilizer.

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The mean total pH and organic matter and heavy metals levels for both treatments are several orders of magnitude greater than the typical soil samples. The coefficients of skewness and kurtosis of the variables are higher in poultry and NPK amended soils in comparison with the coefficient of normal distribution. Therefore the medians are lower than the arithmetic means which is constant with high skewness, showing that there are some unusual high values. Also the negative skewness which is typical of environmental concentration especially in NPK amended soils indicate that 82 % of samples (soil and runoff) contain heavy metal concentrations which exceed the threshold value (5 mg/kg). The relative high CVs indicate that there is high variability at a local scale and that the variability is not distributed evenly over the area. Therefore, the variables under investigation illustrate two different behavours. Figure 1 Show the level of heavy metal concentrations, pH and organic matter levels in water and soil during the end of cropping season in soils amended with fertilizers. The acidity level in runoff water and soils was the same, whereas organic matter content was 300 % higher in the soil than in the runoff water. This implied that the organic matter was not easily removed from the soil during storms that resulted in overland flow. Zinc and cadmium concentration tended to be high in soil, while copper was observed to be more in runoff water washed from the farmland. On the other hand, lead was the only element with least concentration after the application of poultry droppings and NPK fertilizer. Soil pH and organic matter Organic matter and pH have been found to be the most important factors that control the retention mobility of heavy metals in soil. Both parameters also influenced by landuse and agricultural practices. Soil reaction which is given in terms of pH value is a measure of the free hydrogen ion (H+) concentration of soil solution. The value of the free H+ concentration in a soil influences the availability of nutrient elements and biochemical reactions in the soil. Table 3 revealed that the acidity level of this soil significantly increased to slightly acidic when fertilizers were applied in the farm. According to Akinrinde11, slightly acidity enhances

1.280

5.0600

0.193

0.322

-0.308

9.50%

range

Median

standard error of the mean

skewness

kurtosis

coefficient of variation (CV)

O(+0.00)

O(+0.67)

O(inf.)

O(-0.67)

0.67

1.50

chi-square(df=1)

.4142

p-value

normal curve GOF

4.4

5.7

0.473

sample standard deviation

maximum

0.224

sample variance

minimum

4.9

Mean

1.50

0.67

.4142

38.41%

2.271

-1.357

0.140

7.100

0.930

1.200

0.270

0.342

0.117

0.892

1.50

0.67

.4142

11.45%

0.135

-0.630

0.294

4.4750

1.920

7.040

5.120

0.720

0.518

6.283

Org. Zn Matter % ←

1.50

2.00

.1573

46.19%

2.660

-1.545

1.059

4.0200

7.300

8.120

0.820

2.594

6.728

5.615

Cd mg kg-1

1.50

2.00

.1573

46.19%

2.660

-1.545

1.059

4.0200

7.300

8.120

0.820

2.594

6.728

5.615

Cu →

Concentration in soil

1.50

2.00

.1573

89.45%

1.592

1.506

0.098

0.1250

0.620

0.700

0.080

0.240

0.058

0.268

1.50

2.00

.1573

11.30%

1.077

0.303

0.228

4.8100

1.680

5.8

4.1

0.559

0.313

4.4

1.50

0.67

.4142

51.80%

-0.233

-0.075

1.582

0.7700

11.000

12.800

1.800

3.876

15.026

7.483

1.50

3.33

.0679

26.02%

-0.162

0.886

0.596

6.2200

3.680

8.010

4.330

1.459

2.130

5.610

Org. Zn Matter % ←

1.50

2.00

.1573

20.27%

-1.382

0.678

0.463

1.7000

2.860

7.210

4.350

1.134

1.286

5.593

Cd mg kg-1

0.180

0.230

0.050

0.071

0.005

0.158

0.029 -0.931

-0.486

1.50

2.00

.1573

1.50

0.67

.4142

20.27% 44.91%

-1.382

0.678

0.463

6.2200 0.1700

2.860

7.210

4.350

1.134

1.286

5.593

Cu →

Concentration in runoff water

Table 1: Statistical summary of pH, ORG and heavy metal concentration in soil and water samples from NPK amended soil

244 DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013)

0.3080

0.5550

4.1

5.5

1.43

4.9500

0.2266

-0.2229

-1.0769

11.57%

sample variance

sample standard deviation

minimum

maximum

range

Median

standard error of the mean

skewness

kurtosis

coefficient of variation (CV)

O(+0.00)

O(+0.67)

O(inf.)

O(-0.67)

3.33

1.50

chi-square(df=1)

.0679

p-value

normal curve GOF

4.7

mean

1.50

0.67

.4142

36.59%

0.9454

0.8533

0.1135

0.9000

0.78

1.23

0.45

0.2781

0.0773

0.7600

1.50

2.00

.1573

41.44%

0.8138

0.2753

0.8261

6.1000

6.03

8.01

1.98

2.0235

4.0944

4.8833

Org. Zn Matter % ←

0.4157

6.4300

3.13

6.76

3.63

1.0182

1.0367

5.0550

Cu →

-1.9460

-0.0967

0.0194

0.1800

0.11

0.23

0.12

0.0475

0.0023

0.1783

Pbmg kg-1

1.50

3.33

.0679

1.50

0.67

.4142

1.50

0.67

.4142

28.42% 20.14% 26.64%

-2.2511 1.9547

-0.4626 0.5729

0.2077

2.0300

1.14

2.29

1.15

0.5088

0.2589

1.7900

Cd mg kg-1

Concentration in soil

0.7018

0.1080

0.7800

0.8

1.18

0.38

0.2645

0.0700

0.7333

1.50

3.33

.0679

1.50

0.67

.4142

11.75% 36.07%

-1.2092

-0.2775

0.1039

2.1600

0.67

1.92

1.25

0.2545

0.0648

1.5883

Cd mg kg-1

1.50

2.00

.1573

1.50

3.33

.0679

11.33% 16.02%

2.6958

1.2587

0.2877

4.5300

2.1

7.5

5.4

0.7047

0.4967

6.2217

Org. Zn Matter % ←

-1.9086 1.6995

0.3732

0.2183

4.9700

1.31

5.3

4 .0

0.5347

0.2859

4.5

0.31

0.43

0.12

1.50

0.67

.4142

1.50

3.33

.0679

17.45% 48.85%

0.1833 -2.4242

-0.2407 0.1509

0.4302 0.0525

5.1500 0.1900

3.05

7.49

4.44

1.0537 0.1286

1.1103 0.0165

6.0383 0.2633

Cu →

Concentration in runoff water

Table 2: Statistical summary of pH, ORG and heavy metal concentration in soil and water samples from poultry dropping amended soil

DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013) 245

DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013)

246

basic cation uptake by plant roots as it does not inhibit the activities of beneficial soil micro organisms which are affected by soil reaction (strong acidity). The pH of the soils ranged from slightly acidic (amended soil) to moderately acidic (control). Soil pH is often considered in terms of the soil capability and suitability to support plant growth. The pH of 4.8 is set as the lower limit for optimum growth of plants, and conversely the pH of 9.5 is regarded as the extreme upper limit of alkalinity at which plants can still grow. Thus, the soils generally can support plant growth. Soil organic matter usually mixed up with fine clay particles to form soil colloids. It is an

important soil fraction due to its binding properties that enhanced most physical and chemical activities in the soil. Thus, there is increased contact with other colloids and with soil solution mostly poultry droppings were added to the soil. Organic matter in poultry droppings amended soils ranged from 0.45 (plot 3) to 1.23 cmol/kg (plot 1) and 0.38 (plot 2) to 1.18 mg/l (Station 1) in the runoff water, with average values of 4.858 cmol/kg. While in the NPK organic matter level in runoff water was higher than soil (12.8 mg/l). This control plots is low in organic matter (0.705 cmol/kg). Already, this has shown in the sparse cassava growth indicating low productivity and unstable soils.

Table 3: Discriminant analyses results for two fertilizers use pattern in terms of heavy metal concentration Test of Function(s)

Canonical Correlation

Wilksâ&#x20AC;&#x2122; Lambda

Chi-square

Degree of freedom

Significance

Group cases correctly classified (%)

0.893 0.801

0.073 0.358

14.419 5.652

12 5

0.275 0.342

34.5 91.2

Poultry dropping NPK fertilizer

Table 4. Statistical Estimates of pH, organic matter and heavy metal content among treatments in soil and water samples Dependent Variable

TRTS

Soil sample

Runoff/sediment samples

Std. Error

PD NPK C PD NPK C PD NPK C PD NPK C PD NPK C PD NPK C

4.82 4.75 5.10 4.86 2.11 0.71 578 592 451 3.83 3.59 1.02 5.66 5.82 2.76 0.23 0.21 0.15

5.15 4.66 5.01 8.15 0.80 0.45 488 639 198 5.90 1.64 1.22 5.90 6.06 4.70 0.12 0.25 0.17

.178 .159 .390 .665 .594 1.456 .391 .350 .857 .408 .365 .895 .338 .302 .741 .048 .043 .106

ORG(%)

Zn (mg/kg)(mg/l)

Cd(mg/kg)(mg/l)

Cu(mg/kg)(mg/l)

Pb(mg/kg)(mg/l)

ORG = organic matter, PD = poultry dropping, NPK = blanket fertilizer, C = control, TRTS = treatments

DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013) Heavy metal contents in the soil and water at the end of farming season The mineral element originates from soil and dissolved in water for plant rootsâ&#x20AC;&#x2122; absorption but those required in small quantity for optimum performance are regarded as trace elements The concentration of these metals can however be increased to become potential pollutants if heavy metals containing in agronomic activities are introduced into the environment12. Concern over the presence of heavy metals in an environment arises from the fact that they cannot be broken down into non-toxic forms. Thus once aquatic ecosystems are contaminated by heavy metals, they remain a potential threat for many years. The results obtained are presented in Table 3. Clearly indicate that the two treatments exhibit different concentrations of heavy metals. It is evident that the two amendments had high degree of variation of heavy metals level (canonical correlation is 0.893 and 0.801) between soil and runoff. Whereas the lower the degree of withingroup variation (Wilksâ&#x20AC;&#x2122; lambda statistics), the greater the within-group variation as a proportion of the total variation. The statistically significant of NPK results also demonstrate that the originally grouped cases have very high percentage (91.2 %) of correct classification. For poultry droppings, however, the degree of heavy metal concentration is low both in soil and in runoff water, indicating that this variable is not statistically significant (p > 0.05) for discriminating the heavy metal concentration.

247

Thus only lead and cadmium were found to discriminate in NPK amended soils. All the samples analysed for zinc (Table 4) fell below the 1000 mg/kg level recorded for normal soil content13. This relatively low level of Zn could be the natural background level, and the relatively higher concentration of Zn in soil and water is attributed to the application of Zn containing fertilizers which have the effect of increasing the Zn levels of the soil. Cadmium level was found to be higher in soil and runoff water in both amended soils. Its toxicity level is evident resulting from poultry dropping (PD) and NPK fertilizer application. Surprisingly, Cd level is high when Zn level is low. This contradict the findings of Eggenberger and Waber14. that cadmium is usually present in the environment as minute impurities of Zn. Copper is important for the reproductive growth and root metabolism. A major property affecting the availability is soil pH, a measure of soil acidity or alkalinity. Cu tends to be less available in soils with high pH15. The mean level of Cu concentration on application of fertilizers was significantly high when compared with the control (C) plot, leading to the conclusion that fertilizer application (organic or inorganic) affects Cu level in a farmland (PD-5.66, NPK-5.82, C- 2.76). Also greater percent of this metal is easily washed off during rainstorm into the stream (PD-5.90, NPK-6.06, C-4.70). Lead concentrations in soil were 0.232, 0.211 and 0.145 mg/kg and in runoff water, 0.12, 0.25, 0.17 mg/kg for Poultry droppings and NPK, amended soils and control respectively.

Fig. 1: Level of heavy metal concentrations, pH and organic matter levels in water and soil in soils amended with fertilizers

248

DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013)

Fig. 2: Territorial Map of Canonical Discriminant Functions in heavy metal contaminated farmland due to fertilizer applications

DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013) Discriminant functions combined with the structure matrix The territorial map (Fig.2) revealed the relationships between the groups and the discriminant functions. Combined with the structure matrix results, it gives a graphical representation of the relationship between predictors (NPK and Poultry fertilizers) and heavy metals. The first function, shown on the horizontal axis, separates heavy metals among the treatments. Since Level of concentration is strongly positively correlated with the first function (NPK), this suggests that NPK amended soil is, in general, the most highly contaminated with heavy metals. The second function separates groups 1 and 3. pH and organic matter tend to have been the determining factor of heavy metal availability in the soil, although the map suggests that they tend to be well concentrated with a moderate amount of fertilizer application.

249

Only two discriminant functions are plotted, but since the third function was found to be rather insignificant, the territorial map offers a comprehensive view of the discriminant model. CONCLUSION The results of the study revealed that the topsoil of the study area is heavily contaminated with heavy metals-; Zn, Cu, Cd and Pb when the farmland is amended with fertilizers either organic or inorganic. This suggests that water bodies in this environments and crops, which absorbed nutrients from the soil have high coefficient of heavy metal concentration particularly Pb and Cd. Moreover, this result point to the need to adopt precision agriculture which can increase yield while decreasing environmental impacts by managing fertilizer applications.

REFERENCES 1.

Jaradat, Q.M, A.M. Massadeh, K.A. Momani and M. A.Al Saleem., The spatial distribution of Pb, Cd, Zn, and Cu in Agricultural Roadside Soils. Soil and sediment contermination. 19: 58-71 (2010). Arizono, K., Heavy metal toxicity in water in water environment. Nihon Mizukankyo Gakkaishi. J. Japan. Soc. Water Environ., 22: 341-345 (1999). Odu, C.T., Rehabilitation of soils after oil spills. In Akoroda, M. O. (ed), Agronomy in Nigeria. Department of Agronomy, University of Ibadan, Nigeria. P.223-227 (2000). Hemalatha, S and Francis K., Lead inhibition of paddy and nitrate reductase. J. Environ. Bio., 21: 355-357 (2000). FEPA., National Interim Guidelines and Standard for industrial effluents, gaseous emission and hazardous waste management in Nigeria. Federal environmental protection agency. Nigeria. Pp. 95-107 (1991). Nunez-Delgado, B., Morrison L, Gulson, L., Threshold of concern: a technique for evaluating environmental impact and amenity values. Journal of forestry 84-86 (2002) Edem, I. D, U.C. Udoinyang and S.O. Edem.,

10.

11.

12.

13.

14.

Variability of Soil Physical Conditions along a Slope as Influenced by Bush Burning in Acid Sands. International Journal of Scientific & Technology Research 1(6): 8-14 (2012). Ibia, T.O. and Udo, E.J., Guide to fertilizer use for crops in Akwa Ibom state, Nigeria. Ministry of Agriculture and Natural Resources, Uyo, Akwa Ibom State, Nigeria (2011). Gupta, P.K., Methods in environmental analysis, water, soil, and air. Updesh Purohil for Agrobios (India) (2004). Walkey, A. and I. A Black. An Examination of the degtiar off method for determining soil organic matter a proposed modification of the chromic acid titration methods. Soil Sci, 37: 29-38 (1934). Akinrinde, E.A., Issues of optimum nutrient supply for sustainable crop production in tropical developing countries. Pakistan journal of nutrition 5(4): 377-387 (2006). Cox, P.A., The element of earths. Inorganic chemistry in environment. Oxford University Press, New York (1995). National Special Programme for Food Security (NPSP). Critical values for nutrient elements (2005). Eggenberger, U. and Waber, H.N., Cadmium

250

DENNIS et al., Curr. World Environ., Vol. 8(2), 241-250 (2013) in sewage water of landfills. A statistical and geochemical evaluation, Report of November 20, 1997, for the OECD advisory group on risk management meeting,

15.

February 9-10, 1998 (1998). Aydinapl, C. and Marinowa, S., Distribution and form of heavy metals in some agricultural soils. Polish J. Environmental studies (2003).

Current World Environment

Vol. 8(2), 251-257 (2013)

Environmental Effect on The Biological Behavior of the Cucurbit Beetle Epilachna chrysomelina In Al- Qunfudah Province- Saudi Arabia SALEH A. ALDIGAIL1, AHMED I. ALSAGGAFF1, OSAMA M. BAHARETH2 and ABBAS M. AL-AZAB1 1

Department of Biological Science, King Abdul-Aziz University, Jeddah. Department of Biology, Faculty of Sciences, Umm Al-Qura University, Makkah, Saudi Arabia (KSA).

http://dx.doi.org/10.12944/CWE.8.2.10 (Received: June 26, 2013; Accepted: August 20, 2013) ABSTRACT Epilachna chrysomelina (Coleoptera: Coccinellidae) is a phytophagous insect with an economic importance of damaging the agricultural crops. The Melon Ladybird Beetle, E. Chrysomelinais is one of the major phytophagous insects that feed on cucurbit plants. It is considered an economic pest in agriculture and multi-habitat insect widely distributed throughout the world. The insect is abundant in the southern region of Saudi Arabia and choose the most favourable conditions for its life cycle completion. It prefers humid habitats with optimum temperature degrees. The generations of the insect are affected by changes in environmental conditions and its numbers increase or decline according to variation in temperature and relative humidity (RH). These factors play an important role in changing its biological behaviour particularly feeding, breeding, reproduction and development of its generations. There were significant differences between the different developmental stages in the periods of time of their development.

Key words: Saudi Arabia, Epilachna chrysomelina, Environmental, Behavior and Al- Qunfudah.

INTRODUCTION The spotted oriental cucumber beetle E.chrysomelina (F.) is an important pest which feeds on many vegetable crops. It attacks plants specially members of the family Cucurbitaceae like pumpkin, sweet gourd, bittergourd, cucumber, Cucumis mello, Cucurbita pepoand Citrullus lanatus ( Talhoq, 1982 ). According to the Maps of Plant Pests of 1980 and 1990 the spread of E. chrysomelina was the scope of many of the cities of the world. The temperature is the main factor in the activity and behavior of many insects. It helps in distribution and development of the spread of insects as well as there is a clear impact in the growth and the impact of different heat-swing . The various temperatures have significant impact on

the growth and reproductive capacity of producing generations of beetles ( Abdel-Rahman 2005 ) . Effect of temperature on the properties of reproduction in beetle Mexican beetle (Zygogramma bicolorato) .The highest fertility rate of 928 eggs and the highest proportion of vital whites are 75.6% at temperature 27 C° with a decrease in the periods before and after laying eggs whereas high temperatures up to 27 C° then height again as temperatures rise more than 27 C° .The spawning period decreased with heat rising from 92.9 days to 27.5 days. The degree of age-specific fertility also affected by temperature ( Omkaret al. ,2009). The change in humidity and temperature have an effect on the evolution of insect Larva Pupal Diapreper abbreviatus, through egg response to different temperatures in the possibility of hatching

252

ALDIGAIL et al., Curr. World Environ., Vol. 8(2), 251-257 (2013)

(Lapointe and Shapiro, 1999 and Lapointe ,2000). There is relationship between the death of the offspring and the position of eggslayed, because the movement of larvae is very limited, and that the choice of insects to find suitable place to oviposit their eggs is influenced by a large number of different factors, including the quantity and quality of food sources Singly( Myers , 1985 and Thompson and Pellmyr , 1991 ). Choose the Mexican bean beetle Epilachna varivestis to where to put their eggs significantly affects the lives of breeds and thus the strength( Ballhorn and Lieberei, 2006 ) . The present work was planned to evaluate the effect of temperature and humidity on the population abundance, behavior and life cycle of spotted orientalCucumber beetle E. chrysomelina in Al- Qunfudahprovince Kingdom of Saudi Arabia. MATERIAL AND METHODS Study area Al- Qunfudah province located on the west coast of the Kingdom of Saudi Arabia is one of the largest cities of Makka Al Mukarrama Region in Saudi Arabia, overlooking the Red Sea on the west, and away from the holy city of Mecca 350 km to the south, and away from Jeddah, 360 km (Fig. 1). Its geographic coordinates are 19 07 42. 18" N and 41 05 11. 75" E . Methods of studying the stages of cucurbits beetle Larva Larvae were transferred from cage to cage Education hatching plastic, and fed by agricultural Cucumis melo, and record the date of the first day when placed with the observation of biological behavior in the feeding process until the day that become into the next stage and the dates will be recorded in the log transformation for that with record temperatures and humidity daily by a special digital device. Pupa The pupae (first day age) were transferred to the breeding cage and left with plastic study variables atmosphere of temperature and

humidity, and are recording the history of evolution from the first day until the adult. RESULTS Characterized by an insect beetle cucurbits E. chrysomelina phytophagous of plants which favors plant cucurbits From this came the label. Adapt this insect is fast and observant with the plant that exist, but when the temperature and relative humidity, as observed through field and laboratory study they adapt and reproduce in certain times of the months of the year and under variable environmental conditions . Cucurbits beetle E.chrysomelina is considered one of the most serious pests of economic destructive to agricultural crops are characterized lend the leaves of the plant updated damage to an adult, the advantage of this insect small size and the average length of a female (8,75 ± 0,082 mm) and the average length of the male ( 8,1 ± 0,123 mm) and of Blessed red color There twelve black dot so that it is six points on each sheath Fig. (2, 4) Eggs Found that for different temperatures and relative humidity significant impact on the growth

Table 1: Mean temp. and Humidity during themonths of (Jan. - Dec. 2009) Month

Mean Temperature(C°) Humidity(%)

January February March April May June July August September October November December

23.17 21.95 22.72 25.21 28.06 31.23 31.23 31.39 29.02 27.28 27.51 24.10

62.5 66 64 64.5 65.5 58 54.5 49 57 57.5 61 62

ALDIGAIL et al., Curr. World Environ., Vol. 8(2), 251-257 (2013) and reproductive capacity to produce generations E. chrysomelina, where the female lays her eggs on the body mass of an average of 27.8 Âą 2.3 eggs on the bottom surface of the paper, where production times vary and reproduction between the months of the year. Increasing reproduction and laying eggs

253

in the periods of the month of February, March and April, while at least gradually in the months of April, May and June and disappear egg masses in the month of July and August because of the high temperature and low humidity from the normal rate. The female lays her eggs on the leaves or large peripheral protected by mucous secretions

Fig. 1: Al- Qunfudah province

Fig. 2: Male and female of Epilachna chrysomelina

Eggs

Larvae

Fig. 3: Eggs , larvae and pupa of Epilachna chrysomelina

Pupa

254

ALDIGAIL et al., Curr. World Environ., Vol. 8(2), 251-257 (2013)

Fig. 4: Average length of stages beetle cucurbits (E. Chrysomelina )

Fig. 5: Effect of temperature and air humidity on the numerical abundance of beetle cucurbits

Fig. 6: The period of time for the stages of the evolution of beetle cucurbits

ALDIGAIL et al., Curr. World Environ., Vol. 8(2), 251-257 (2013)

255

Fig. 7: Average age of the stages the growth of cucurbits beetle : (Eggs, larva, pupa and Adult ) in the absence of older leaves, they put it on solid objects, the egg spindle with an average length of (0.89 ± 0.025 mm) and the average age of the egg (7.14± 0,547) a day Fig. (3 and 4). Larvae

E. chrysomelina be voracious feeding on the leaves of the plant-year-old firstTo a length of about 1 mm and then soon grow rapidly. Larvae feed on the leaves of the plant in the early stages of its growth, especially the lower surfaces of the paper, where she works on crop damage and destruction . Body larva contains a large number of thorns black complex in part, dorsal and without the abdominal area of thorns (form 213) (Fig. 3 and 4) and the body of the larva amount of average length (9,2 ± 0,226 mm), and takes the larva grow to turn into a phase that followed average (8,2 ± 0,836) days . Pupa Larva turning to a pupa is a stage that comes before the advent the adult, where the larva turn into a pupa Average (6 ± 0,707) days and be deliberately inert on adhesion papers or on plant stems and branches through the abdomen Fig. (4). The effect of temperature and air humidity on the numerical abundance of beetle cucurbits The results of statistical analysis Simple Correlation Coefficient Table (1) showed that there is relationship and highly significant (P = 0.01) between the air temperature and the number of

eggs, and the presence of a significant relationship at the level (P = 0.05) between the humidity Fig.(5 ) The effect of temperature and humidity on the female oviposit egg masses The number of egg masses that have been collected during the months of January to June and the amount of eggs that hatch with an indication of the average temperature and humidity during thesemonths.It is noticeable that the greater the average temperature and the average moisture content, the lower the number of eggs produced. There is a correlation moral strong between the quantity of eggs produced and average temperatures, as the value of simple correlation coefficient (r) calculated at the level (P = 0.01) (0.92668) which is greater than the value scheduled (0.9170) at the same level and degree of freedom (4) . The results of this study showed that the length of E. chrysomelina steady with an average length of the adult( 8,75 ± 0,082 )mm This number indicative of the length fairly recently from insects lengths Coleoptera where recorded lengths up to 10 mm( Perry and Roitberg , 2005 ) Cucurbits beetle as in full development insects going through four stages (egg, larva pupa the adult) such as coccinellidae(Dixon , 2000) The results of the current study, it was

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ALDIGAIL et al., Curr. World Environ., Vol. 8(2), 251-257 (2013)

observed that female beetle cucurbits laid egg masses, which range between 25-30 eggs in environmental conditions suitable, and stated that insects coccinellidae put eggs in her lifetime approximately 500 eggs, ( Talor , 2000 ). found in this study that the egg beetle cucurbits tend to yellow and ranges average length of ( 0,89 ± 0,025 ) and spindle-shaped, and pointed out that the length of the egg up to 1 mm in most of coccinellidae and is considered the Mexican bean beetle is the closest are the current insect in terms of morphological characteristics (Dixon , 2000). The average age of the egg in cucurbits beetle ( 7,14 ± 0,547 ) day and the average age of the larva ( 8,2 ± 0,836 ) day and average age of pupa (6 ± 0,707) days and beetles coccinellidae up the age to 14 eggs a day appear to live larvae of 2, 5 weeks ( Hoffman and Fredsham , 1993 ). And pupa in coccinellidae beetles average age of 7 , 10 days ( Mahr,1996 ) E.chrysomelina have the ability to choose the right place to lay eggs, where if you can not find terminal leaves or large size, they put it on the hard places, and a female coccinellidae choose the right place to lay eggs( Thompson and Pellmyr , 1991) (Ballhorn et al ., 2010). There is obvious effect of the factors of the

environment through the daily average temperature and humidity on the appearance of insects cucurbits of food daily in the field and its diversity, the results showed the extent to which these insects environmental variables where the highest density of numerical in the months of February and March, April and an average temperature equivalent to 23 C° and humidity upto 75% and recorded the lowest density in the months of August and September and October, where high temperatures average 36 C° and 35% humidity. Reproduction properties in the Mexican bean beetle affected by variables of temperature and humidity, the higher the temperature less than the production of egg masses and thus less density numbers of insects ( Omkar et al ., 2009 ) . Observed a significant correlation between the number of eggs produced by female beetle cucurbits and humidity, and there is a strong significant correlation between the quantity of eggs produced and high temperatures, and these results agreed with many of the researchers , That the fixed temperature affect growth and reproductive capacity of the CoccinelleMndecimpunctata beetle where he pointed out that the temperature of 25 – 30°C is the best and most suitable for the development of these predatory beetles ( AbdelRahman , 2005 ).

REFERENCES 1.

Abdel-Rahman, Mohamed., Influence of constant temperatures on the development , and reproductive potential of the ladybird beetle , Coccinellaundecimpunctata L. ( Coleoptera : Coccinellidae ). 3rd International Conf. on IPM role in Integrated Crop Management and Impacts on Envi. And Agr. Products ,26-29-Nov. 2005, Geza ,Egypt (2005). Ballhorn , D. and R. Leiberei., Oviposition choice of Mexican bean beetle ,Epilachnavarivestis , depend on host plants Cyanogenic capacity. J. Chem. Ecol. (2006). Ballhorn, D. J. ; S. Kautz; R. Lieberei., Comparing responses of generalist and specialist herbivorous to various cyanogenic

plant features Entom. ; 134(3): pp.245 – 259 ( 2010 ). Dixon AFG. Insect Predator – prey Dynamics Lady bird Beetles and Biological Control. New York: Cambridge Univ Press. ix + 257 p (2000). Hoffman, M.P. and Frodsham,A. C., Natural enemies of vegetable insect pests . Cooperative Extension , Cornell University , Ithaca , NY (1993 ). Lapointe, S. L., Thermal requirements for development of Diaprepesabbrivatus( Coleoptera : Curculionidae ) . Environ. Entomol. 29: 150-156 (2000). Map-of-plant pests, Distribution Maps of Plant Pests(NO.June)Map 409 , Wallingford, Oxfordshire,OX 108 DE,UK (1980).

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Map-of-Pests, Distribution- maps â&#x20AC;&#x201C; of pests nos 57, 82, 182, 296, 109, 529, 530, 531, 532 manyre 56 Queen gat. London SW 75 JR, UK ,(1992). Myers , J.H., Effect of physiological condition of the host plant on the ovipositional choice of the cabbage white butterfly, Pierisrapae. J. Anim. Ecol. 54: 194-204 (1985). Omkar C. ; S. Rastogi ; P. Pandey., Effect of temperature on reproductive attributes of the Mexican beetle Zygogrammabicolorata ( Coleoptera: Chrysomelidae ). Inter. Jour. Of Tropical Insect Sci. 29 (2009). Perry , J. and B. Roitberg., Ladybird mothers mitigate offspring starvation rik by laying trophic eggs. Behavioral Ecology and Sociology 58: 578-586 (2005). Talhoq, A.S., Applied Zoology in Saudi

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Arabia, Anote on the Entomophagous Insects. Fnuna and Saudi Arabia, 4: 525- 531 (1991). Talor, E. C., Cellulose digestion in a leaf eating insect , the Mexican bean beetle, Epilachnavarivestis . Department of Biology, Univ. of New Mexico , Albuquerque, NM87131, USA (1982). Thompson J. N. and Pellmyr, O., Evolution of oviposition behavior and host preference in Leidoptera. Ann. Entomol. 36 : 65-89 ( 2003). AL-Digail S A, Ahma I A, Mahyoub J A. Effect of Temperature and Humidity on the Population Abundance of Spotted Oriental Cucumber Beetle Epilachna chrysomelina (F.) (Coccinellidae : Coleoptera) In Al Qunfudah Western Saudi Arabia. Curr World Environ 7(1): 07-12 (2012).

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Document on Fluoride Accumulation in Ground and Surface Water of Mysore, Karnataka, India S.V. MAMATHA1 and DEVENDRA J. HAWARE* Food Safety & Analytical Quality Control Laboratory, CSIR-Central Food Technological Research Institute, Mysore - 570 020, India. http://dx.doi.org/10.12944/CWE.8.2.11 (Received: April 18, 2013; Accepted: June 07, 2013) ABSTRACT We have documented various levels of fluoride in groundwater, running water (i.e streams, canals, river) and lake water in 130 samples collected from various sources in Mysore District. Mysore is one of the most popular tourist places in India. Fluoride is one of the parameter of water analysis, which is non-degradable and persists in the environment. Fluoride was assessed by Zirconyl- SPADNS method. Fluoride level varied from 0.2 mg/L to 3.0 mg/L with the highest level at Dalvoy Lake (3.0 ppm) followed by Lingambudi Borewell water (2.9 ppm) giving a cautious alarm for an awareness to the Mysoreans.Water samples from north-eastern part of Piriyapatna, a small pocket of southern part of H.D.Kote and an extreme southern part of Mysore taluk (urban) were having fluoride concentration above acceptable range of WHO and BIS standard.

Key words: Fluoride, Groundwater, Surface water, Lake Water, Mysore.

INTRODUCTION Mysore covers the geographical area of 6763.82 Sq Km. The district comprises of 1203 inhabited villages with 236 grama panchayats and 9 townships. Mysore is divided into 7 taluks namely H.D Kote, Hunsur, K.R.Nagar, Mysore city, Nanjangud, Periyapatna and T. Narasipura. Mysore district fall in the survey of India degree sheet nos. 48P, 57H and 58A. The district is situated between north Latitudes 11°45' – 12°40' and east Longitudes 75°59' -77°5' covering an area of 6269 Sq.km. The district is one of the southern most districts of the Karnataka state and is borderd by kodagu district in the west, Cannanore district of Kerala state in the south west, Chamarajanagar district in the south and south east, Mandya district in the north and Hassan district in the north west.There are 5 perennial rivers in the district namely Cauvery, Kabini, Nugu, Gundal and Lakshmanathirtha which are the major source for drinking and irrigation purpose1.

Groundwater is the only source for drinking water in rural areas due to the lack of water supply facility from surface water sources. Natural water is supplied only in the city limit and in some taluks, yet not extended to the nearby villages. The purity of water cannot be judged by visibility and odour of water sample and even visibly pure water can contain some toxic metals, pesticide residues, and high levels of nitrate, chloride and fluoride. Fluoride has a negative effect on human health below 0.5ppm and above 1.0ppm whereas in the range of 0.5-1ppm, it shows a positive effect. Fluoride is the key aspect of water quality in water supply system. Fluoride has shown to cause a significant effect on human health. A correct proportion of fluoride has a beneficial role in the formation of teeth 2 . Too low concentration (<0.5ppm) of fluoride intake may be insufficient for preventing dental caries in the early ages of children3-5. High concentration of fluoride exceeding 1.5 ppm leads to teeth mottling viz dental fluorosis6.

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Excess of fluoride in drinking water above 4 ppm causes chronic skeletal fluorosis which causes stiffness in joints, increase in bone mass and osteoporosis in the old ages. In extreme cases, paralysis and premature aging may happen. Recent research has shown chronic fluoride toxicity can cause adverse health effects such as increase lipid peroxidation and myocardial damage 7-8. Fluoride can also damage the fetus, if the mother consumes water and food, with high concentrations of fluoride during pregnancy9. The amount of fluoride in water is governed by climate, composition of rocks and hydrogeology10. Accumulation of fluoride in ground water is due to the presence of minerals fluorspar, fluorapalite, topaz and cryolite 11. Higher concentrations of fluorine are present in alkaline volcanic, hydrothermal, sedimentary, and other rocks derived from evolved magmas and hydrothermal solutions12. In processed food and beverages, fluoride can come from pesticides (like Trifluralin, Benefin), Cryolite (a naturally occurring inorganic substance), Sodium Fluoride (used as rodenticide) and Superphosphate fertilizer . Mishra et al., (2009) have conducted a study on fluoride content in plant leaf, rice crop showing the concentration upto 12.6ppm and 43.9ppm respectively13. The excess accumulation of fluoride in vegetation leads to visible leaf injury, damage to fruits and less yield14. Dry tea leaves have significantly high levels of fluoride of upto 400 ppm 15. In one study, it was shown that 37% of the fluoride in Black tea remains in oral cavity. Soil also showed different amounts of fluoride, as it is adsorbed to soil particles. Fluoride has an adequate sensitivity to cycle in the environment including plants, animals and human beings thereby causing toxicity 16. Fluoride is also absorbed by plants as the water is also used for irrigation. Thus fluoride can even enter food chain causing higher concentration of fluoride in food materials. Therefore, in the present study, the level of fluoride in various water bodies in Mysore district were determined to identify the areas with higher fluoride contamination.

MATERIALS AND METHOD A total of 130 samples of 500ml water were collected from different locations of Mysore district in clean PET bottles after rinsing with same water. The sampling points were hand pumps, open wells, tube wells, rivers, canals, ponds and lakes. The water samples were analyzed by Zirconyl- SPADNS Method17. The SPADNS colorimetric method is based on the reaction between fluoride and a zirconium dye lake. Fluoride reacts with the dye lake, dissociating a portion of it into a colorless complex anion (ZrF62-); and the dye. As the amount of fluoride increases, the color produced becomes progressively lighter. The reaction rate between fluoride and zirconium ions is influenced greatly by the acidity of the reaction mixture. If the proportion of acid in the reagent is increased, the reaction can be made almost instantaneous. For better results, it is necessary to maintain a constant temperature throughout the color development period18. Procedure The sample (50 ml) was taken in a flask and 5ml each of zirconyl-acid reagent and SPADNS solution were added. Preparation of calibration curve from standard fluoride solutions of concentrations 0.5, 1.0, 1.5, 2.0, 2.5 and 3.0 ppm was done. Readings of water samples were taken at 570 nm (UV-Visible Spectrophotometer, UV1601, Shimadzu, Japan) after setting absorbance of reference solution as zero. The graph of Concentration of fluoride V/S Absorbance was plotted to find out the concentrations of fluoride in unknown water samples. RESULTS Method validation plays an important role in the selection of an appropriate method for analysis. This method is well suited between the concentration range of 0.25ppm to 3ppm. In case of higher concentration, the sample has to be diluted. This method determines the analyte specifically even in the presence of other components like Na, K, Ca giving a confirmation of showing specificity19.

MAMATHA & HAWARE, Curr. World Environ., Vol. 8(2), 259-265 (2013) Totally, eight trials were done to standardise the method in which all the graphs have shown a linearity (Fig 2). In each trial, one spiked sample was taken. So it can be concluded that this method gives an accurate results in the laboratory20. Usually in the surface water bodies, the level of fluoride is below 0.5ppm, whereas in Dalvoy lake, Kukkarahalli Lake, Karanji Lake and Ummathur Lake, the concentration is above 1.5ppm.The fluoride concentration was ranged from 0.3pm-2.9ppm in BoreWell water with the highest fluoride level at LingambudiPalya (2.9ppm) & the lowest at Suttur (0.2ppm). In Surface Water bodies, the fluoride levels were accounted from 0.25 to 3ppm with the highest at dalvoy Lake & the lowest at Kabini & Kaveri River (Table-1). Usually fluoride level is below 0.5 ppm in stagnant water and running water whereas in

261

groundwater, the concentration varies from 1ppm to 48 ppm (21),(22). Digging up of deeper aquifers for irrigation results in the higher level of fluoride (Gupta,1995). Muktsar city in Punjab state shows the highest fluoride concentration of 42.5 ppm standing at the top place in India, which is followed by 32.5ppm of fluoride level in Delhi. In bore well water, only 28% of the water samples come under the recommended fluoride intake range of 0.5-1 ppm, 6% of the samples occupy 0-0.5 ppm range, 40% of the water samples lie in 1-1.5 ppm level, 15% of the water samples shared 1.5-2 ppm level, and 11% of the samples with the highest concentration of fluoride between 2-3 ppm (Fig 4a). In surface water, 11% of the water samples between 0-0.5 ppm, 52% of the samples between 0.5-1 ppm, 23% of the samples in the range of 1-

Table 1: Table showing the fluoride level in their respective locations

0.5-1 ppm

1-1.5 ppm

Surface Water Bodies

Bore Well Water

Vajamangala Lake, Ratnapuri Lake, Kabini river, BanniKuppa lake, Kaveri river Lakshmana Thirta river, Kodgalli lake, Shetty lake, Chikkahunsur lake,. Periyapatna lake, Ummathur lake, Bannur Lake, Varuna lake, Karanji Lake, Canal water in Mandakalli.

Muthur, Alanahalli, CFTRI, Gousianagar, Gargeshwari, Kadakola, Nanjangud, Nagarle, Chennagirikoppal, hunsur, Bannikuppa, Chamundi Hill, N.R.Mohalla. Bandi palya, Vajamangala, Mahadevapura, Jaypura, T.Narasipura, Mandakalli, Hullahalli, Devaiahnahundi, Sunnadakeri, Agrahara, Chilkunda, vidyaranyapuram, Ittigegud, Udbur, Udaygiri. Yaraganahalli, Mellahalli, Jayanagar, parasaiahnahundi, Kuvempunagar, mahadevapura, Sub-urb, yasodarapura, Krishna Murthy puram, Kalasvadi. Vivekanandanagar, Bilikere Periyapatna, chittenahalli, Sampigepura, kotehundi, T.K. layout, Ramakrishna nagar J.P.Nagar, H.D.kote, yelawala, LingambudiPalya, Hootagalli.

1.5-2 ppm

Pandavapura lake, Saligrama lake, Kukkarahalli Lake.

2-3.0 ppm

Dalvoy Lake

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Fig. 1: Location of Mysore District, India

Fig. 2: Fluoride standard calibration curve

MAMATHA & HAWARE, Curr. World Environ., Vol. 8(2), 259-265 (2013)

Fig. 3: Map showing the locations of fluoride contamination

Fig. 4(a): Percentage of sample analysed in borewell water

Fig. 4(b): Percentage of sample analysed in surface water

Fig. 5: concentration range in terms of frequency distribution in borewell and surface water

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1.5 ppm, 9% of the samples occupied 1.5-2 ppm and 5% of the samples occupied 2-3 ppm range (Fig 4b). There are maximum number of 48 samples in the range of 1-1.5ppm, 35 samples in the range of 0.5-1ppm, 18 samples in the of 0-0.5ppm, 17 samples in the range of 1.5-2ppm, 10 samples in the range of 2-2.5ppm and 2 samples in the range of 2.5-3 ppm (Fig 5). Discussion Hydrogeologically, the area of sampling points forms a part of hard rock terrain comprising of granites, gneisses, charnockites amphibolites. As the groundwater occurs in weathered zones of granites and gneiss at deeper level in the district, the fluoride content is high in this region. This being the preliminary studies, more elaborate studies should be taken up to establish the fluoride content of this region. The groundwater occurs under phreatic conditions in weathered zones of granites and gneiss, and under semi-confined to confined conditions in joints and fractures of these rocks at deeper level in the district. Physico-Chemical Parameters of water samples such as pH, temperature, colour, turbidity are correlated with the concentration of fluoride as all these parameters are interrelated to each other. Temperature A rise in temperature of water leads to the speeding up of chemical reactions in water, reduces the solubility of gases and amplifies the tastes and odours. The average temperature of the present study ranged from 27.85-29.17Â° C. pH It is known that pH of water (6.5 to 8.5) does not has no direct effect on health. But lower value below 5.0 produce sore taste and has higher value above 8.5 are of alkaline taste. The pH values of the present investigation were within the BIS standards (6.5 â&#x20AC;&#x201C; 8.5). Conductivity varies with the season as well as ions present in water. Temperature also affects the pH values; therefore the temperature at the time of analysis should be reported.

Colour Colour in water may be due to the presence of inorganic ions such as iron and manganese, humus and peat materials, planktons, weeds and industrial waste. Very slight amount of turbidity, pH interferes with the colour. Filtering may result in removal of some of the colour, leading to erroneous results. All the water samples used in the present study are colourless. Turbidity Turbidity occurs in all surface water bodies such as lakes, streams and canals. The high values of turbidity is considered as an indication of pollution by finely divided organic matters, particulate matter such as clay or silt, plankton or other microscopic organisms. Turbidity values obtained in the study are found to be less than 2 NTU. Colour and Turbidity of the samples play an important role in the determination of the fluoride. As they cause interferences, water samples should be colourless and less turbid. Alkalinity is also one of the parameter that interferes in fluoride analysis, hence should be neutralized by adding Hydrochloric acid. Veeraputhiran and Alagumuthu (2010) have produced a report on the highest fluoride concentration of 4.34 ppm in the ground water of Ottapidaram, Tamil Nadu23. Borah and Saikia (2011) found increased concentration of fluoride in ground water of Tinkusia district, Assam. Puneeth and Ashish (2012) have assessed the levels of fluoride in Tap water and bottled water in Agra city, India24. Abu Zeid (1998) et al have studied the impact of fluoride in drinking water and listed the defluoridation techniques25. Murray (1986) have estimated fluoride concentration in dry leaves upto 400 ppm and canned fish may contain upto 370 ppm. A survey study by Rajesh kumar and Yadav (2010) have shown the levels of fluoride in different cereals, vegetables and fruits with the highest levels in Rice of about 5.9 ppm and Apple of about 5.7 ppm26.

MAMATHA & HAWARE, Curr. World Environ., Vol. 8(2), 259-265 (2013) CONCLUSION This present investigation identifies the areas having higher concentration of fluoride in the lake, river and groundwater. The results have shown that the level of fluoride has crossed a warning limit in the Borewell water of southern part and western part of urban areas, southern part of H.D.Kote (Remote areas), Bilikere of HunsurTaluk and some areas of Periyapatna taluk namely Chittenahalli, Periyapatna. From the fluoride level found in ground water samples of the study area it can be concluded

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that the ground water is not safe for drinking purpose, but can be used for irrigation. High fluoride in water may cause dental fluorosis among the children and pain in joints and backbone in the aged persons. As most of the water samples do not meet the water quality standards for fluoride concentration. Defluoridation is needed as the naturally occurring fluoride level exceeds recommended limits, the work on development of simple and cost effective methods to reduce fluoride content is required. Conjuctive use of both surface and ground water practice in the canal command areas would improve the quality of ground water.

REFERENCES 1.

2. 3.

4. 5.

6. 7. 8. 9. 10. 11. 12. 13. 14.

Central Ground Water Board (CGWB), Groundwater Information Booklet, Mysore District, Karnataka (2009). Simpson A. et al, Journal of Dentistry, 29(1): 15-21 (2001). Ruan J.P., â&#x20AC;&#x153;Dental fluorosis in children in areas with fluoride-polluted air, high-fluoride water, fluoride air: a study of deciduous and permanent teeth in the shaanxi province, Chinaâ&#x20AC;?. Acta. Odontol.Scand., 65(2): 65-71 (2007). Sumalatha S. et al, curr.sci., 76: 730-734 (1999). Susheela A.K., Fluorosis management programme in India. Current science, 77(10): 1250-6 (1999). Featherstone J.D., Dental caries: a dynamic disease process. Aust. Dent. J, 5 (2008). Verma R.J. and Guna-Sherlin D.M., Food. Chem. Toxicol., 40: 1781-1788 (2002). Mahaboob Pasha P. and Sujitha N.S., Toxicol. Int., 18(2): 99-104 (2011). Cronin S.J. and Sharp D.S., Int.J .Env. Health. Res., 12(2): 109-23 (2002). Gupta S. et al, Fluoride 39: 318-320 (2006). Jitumoni Borah, Deepjyoti Saikia, Arch. Appl.Sci. Res., 3(3): 202-206 (2011). Handa B.K., Groundwater, 25: 255-264 (1975). Mishra P.C. et al, Afr. J. Environ. Sci. Technol., 3: 260-264 (2009). Anil K.K. and Bhaskara R.A.V., Physiological responses to fluoride in two cultivars mulberry. World. J. Agric. Sci., 4(4): 463-466

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(2008). Murray J.J., editor, Appropriate use of Fluorides for Human Health, WHO, Geneva (1986). Dash M.C. and Mishra P.C., Manand. Environ. Macmillan. India Limited, Chennai, 293 (2001). Andreae M.O., Methods of Seawater Analysis, Verlag Chemie Weinheim, West Germany, 2: 218 (1983). APHA, Standard Methods For Examination of Water and Wastewater 21th Ed., American Public Health Association, Washington, D.C ., 2005. AOAC peer verified methods programManual on policies and procedures, Arlington, VA (1993). Fleming J. et al, Accred.Qual.Assur. I., 87 (1996). Shivashankara A.R. et al, Fluoride, 33(2): 66-73 (2000). Gupta S.K. and Sharma P., An approach to tackling fluoride problem in drinking water. Current Science, 68: 774 (1995). Veeraputhiran V., Alagumuthu G., A report on Fluoride distribution in drinking Water. Int. Jour. Env. Sci., 1(4) (2010). Puneet Gupta and Ashish Kumar, Research report ,Fluoride ,45(3): 307-310 (2012). Abu-Zeid Khaled M., Environmental Management and Health Journal, 9: 2-3 (1998). Rajesh Kumar and Yadav S.S., S.S.M & R.A.E (2010).

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Assessment of Groundwater Quality - A Case Study of Kondapur Mandal, Medak District, Andhra Pradesh K. RAMAMOHAN REDDY1 and R. S. PATODE2* 1-2

Centre for Water Resources, Jawaharlal Nehru Technological University, Hyderabad - 500 085, India. http://dx.doi.org/10.12944/CWE.8.2.12 (Received: April 18, 2013; Accepted: June 06, 2013) ABSTRACT The suitability of groundwater for drinking purpose with respect to BIS: 10500-1991standards is assessed through statistical analysis of the data and on the basis of seasonal variation in the quality of groundwater. The study was undertaken during 2010-2011. The samples are collected during post monsoon period from bore wells being monitored by the Andhra Pradesh Rural Water Supply and Sanitation Department. The study area comprises of Kondapur Mandal, which is one of the 46 mandals of Medak District lying in the semi-arid Telangana region of Andhra Pradesh. The Mandal has 23 Revenue villages with no towns accounting to a total population of about 45000 as per census 2001. As per water quality index (WQI) values, the groundwater in the study area during post monsoon ranging from “Good” to “Unfit for drinking” and no where it was found “excellent.” The poor quality of water is due to higher concentrations of fluoride and increased total hardness values. It is found that about 84% of the samples analyzed are suitable for drinking. Correlation amongst all the parameters was found to be positive but weak. Only fluoride showed negative correlation with other parameters but it is very weak. This indicates that there is no regionally extensive factor governing the water quality and it is varying with local conditions only.

Key words : Concentration, Groundwater, Standards, Water quality index. INTRODUCTION Groundwater quality assessment is important in order to ensure sustainable safe use of water. Water quality index, based on some very important water quality parameters, can provide a simple indicator of water quality at a certain location and time. Ramakrishnaiah et al. (2009) calculated the water quality index (WQI) for the groundwater of Tumkur taluk. Yogendra K et al. (2007) worked out the water quality index of an urban water body, Gopishettykere, in Shimoga Town, Karnataka in order to ascertain the quality of water meant for public consumption, recreation and other purposes. Kavitha et al . (2010) aimed at minimizing the adverse impacts likely to occur due to water pollution as a consequence of rapid industrialization and population growth in Erode District of Tamilnadu. Sinha et al. (2006) made an effort towards assessing drinking water contamination and variation of drinking water quality

after the onset of monsoon at Hasanpur, J. P. Nagar, on the basis of calculated values of water quality indices. Once the groundwater is contaminated, its quality cannot be restored by stopping the pollutants from the source. Therefore it becomes imperative to regularly monitor the quality of groundwater and to device ways and means to protect it. Water Quality Index (WQI) is a unit-less number that expresses overall water quality at a certain location and time based on several water quality parameters. The main objective of this work is to assess the groundwater quality of Kondapur mandal of Medak District, Andhra Pradesh, based on the available physicochemical data and the analytical results of groundwater samples. Study Area The study area comprises of Kondapur mandal of Medak district, which lies between 17o 25’ 0" and 17 40’ 0" North Latitudes and 77o 55’ 0" and 78 o 5’ 0" East Longitudes. The mandal

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analyzed data of the samples (498) collected both during pre and post monsoons periods for the four years in 9 villages of the mandal were considered. Abstract of this data is given in table 1.

comprises of 23 revenue villages having an area of 149.1 Sq. Km. It is at an elevation of 525 m above MSL. The mandal headquarters (Kondapur) is located at 69 Km from Hyderabad. It comes under Sangareddy revenue division and is located along the national highway 9 between Sangareddy and Sadasivpet mandals of the same division. The rainfall distribution of Kondapur mandal for the period from 2000 to 2009 is shown in figure 1. While the normal rainfall of the area is 802 mm, the actual rainfall received ranges from a minimum of 348 mm in 2004 to a maximum of 1055.7 mm in 2005, in the period of 10 years.

RESULTS AND DISCUSSIONS Groundwater occurs under phreatic conditions in shallow weathered mantle and under semi confined conditions in the fractured zones. In weathered granite and alluvium, the transmissivity values ranges from 100 to 150 sq.m/day and the specific capacity ranges from 0.005 to 0.16 cu.m/m per unit cross-section. Groundwater in basaltic and lateritic formations of Deccan traps occurs under water table and semi-confined conditions. The transmissivity values of these formations range between 100 and 1100 m2/day and the specific capacity varies from 0.22 to 1.2 m3/m draw down. Water has become a scarce resource here not only due to deficient rainfall but also due to over exploitation of groundwater.

Methodology The data required for water quality analysis in the present study has been obtained from Rural Water Supply and Sanitation Department of Government of Andhra Pradesh. The data pertaining to the test results of the water samples analyzed from the groundwater sources of various villages in Kondapur mandal from 2007 to 2010 ( 4 years) have been collected for the study. The analytical data of the samples (171) collected during the post monsoon period of 2009(July to Dec) from all the villages of Kondapur mandal have been used to assess the groundwater quality of the area through the determination of WQI, comparison with BIS:10500-1991 for drinking water and statistical analysis. For studying the variation of water quality in pre and post monsoon periods,

Water Quality Index (WQI) The assessment of groundwater quality in the given area and its suitability for human consumption is computed based on water quality index values. The average value of each of the six water quality parameters (TDS, pH, TA, TH, Cl and F) for every village has been computed from the individual sample values and given in table 2. The

Table 1: Abstract of analytical data used for seasonal variation studies S. Village No

1 2 3 4 5 6 7 8 9

Ch Konapur Gangaram Garakurthi Girmapur Gollapally Malkapur Munidevunipally Saidapur Togarpally Total

2007 samples

2008 samples

2009 samples

2010 samples

Total

Pre M

Post M

Pre M

Post M

Pre M

Post M

Pre M

Post M

Pre M

Post M

18 0 6 0 0 32 0 7 0

5 8 0 7 7 15 8 0 12

2 6 1 9 17 7 9 9 13

0 5 6 0 0 14 0 9 0

0 13 0 8 13 15 4 0 11

3 4 10 0 28 12 9 8 20

0 0 15 0 29 0 0 12 0

6 0 0 8 0 18 0 0 20

20 19 22 17 59 54 13 28 24 256

14 17 16 15 35 59 17 17 52 242

REDDY & PATODE, Curr. World Environ., Vol. 8(2), 267-273 (2013) WQI for each village is also calculated by sub index method (SI method) and from the computed WQI values the groundwater is classified into two types, “good water” and “poor water”. The representation is shown in figure 2. Based on the water quality index values obtained by Weighted Arithmetic Index Method (WAIM), the groundwater in various villages of Kondapur mandal is categorized as Unfit for drinking in Garakur thy and Malkapur. Very Poor in Dobbakunta, Aliyabad, Ch Konapur, Gangaram and Gunthapally. Poor in Marepally, Ananthasagar, Saidapur, Munidevunipally, Mansanpally, Machepally, Mohmadapur, Gollapally, Terpole, Kutubshapet, Girmapur and Haridaspur. Good in Mallepally, Kondapur, Ch Gopularam and Togarpally.

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Based on the water quality index values obtained by Sub Index Method (SIM), the groundwater in various villages of Kondapur mandal is categorized as Good in Dobbakunta, Mallepally, Kondapur, Ch Gopularam, Munidevunipally, Machepally, Togarpally, Gollapally, Terpole, Gunthapally and Haridaspur. Poor in Marepally, Ananthasagar, Saidapur, Garakurthy, Malkapur, Mansanpally, Aliyabad, Ch Konapur, Mohmadapur, Gangaram, Kutubshapet and Girmapur. Suitability of groundwater for drinking as per BIS: 10500-1991 The suitability of groundwater in the study area for drinking purposes has also been analyzed with respect to the individual values of pH, TDS, TA,

Table 2: Mean values of different water quality parameters of different villages of Kondapur mandal S. No

Village

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Dobbakunta Mallepally Marepally Kondapur Ananthasagar Saidapur Garakurthy Malkapur Cherlagopuram Munidevunipally Mansanpally Aliyabad Ch Konapur Machepally Mohmadapur Gangaram Togarpally Gollapally Terpole Gunthapally Kutubshapet Girmapur Haridaspur

No of samples

TDS in ppm

Alkalinity (as CaCO3) in ppm

4 7 10 12 12 8 6 6 9 8 11 4 3 5 3 4 20 12 5 4 3 8 7

513 583 1150 585 772 725 407 571 542 493 718 661 1040 709 580 778 644 770 529 495 1144 669 625

7.23 7.20 7.86 7.83 7.75 7.59 7.28 7.42 7.31 7.48 7.41 7.55 7.57 7.50 7.37 7.30 7.40 7.43 7.40 7.33 7.50 7.53 7.77

280 372 341 290 432 531 251 231 319 383 347 278 308 300 459 446 178 314 266 293 372 334 353

Total Chloride Fluoride Hardness in ppm in ppm (as CaCO3) in ppm 408 446 516 357 408 533 382 307 295 310 259 265 248 268 200 292 426 259 445 474 433 438 403

124 203 281 283 368 263 184 151 140 127 261 260 211 152 275 324 167 118 102 92 137 239 224

1.01 0.40 0.70 0.38 0.74 0.55 1.61 1.17 0.52 0.60 0.64 1.12 0.97 0.78 0.75 1.02 0.53 0.58 0.60 0.92 0.78 0.76 0.54

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TH, Cl and F. The values of these parameters/ concentrations of chemical constituents have been compared with the standards prescribed by the Bureau of Indian Standards for the purpose (Yadav et al. 2010). Table 3, shows the desirable and permissible limits for each of the above constituents as per BIS: 10500 - 1991and the percent samples within each limit and exceeding the limit. The results of the analysis indicate that the groundwater in major part of the study area is suitable for drinking. However, excess concentrations of total hardness and fluoride are likely to pose constraints in the use of water for drinking in parts of the area. The number of villages exceeding the maximum permissible limits laid for each water quality parameter is represented in figure 3. From the analysis it is observed that, of

the total 23 villages, all water quality parameters are well within the maximum permissible values laid by the BIS in 10 villages. In the remaining 13 villages also the parameters pH and chloride have not exceeded the above limits. 6 villages are not safe with respect to each of the parameters, fluoride and total Hardness. 2 villages and 1 village are not safe with respect to total alkalinity and total dissolved solids respectively. Statistical analysis of data Important statistical parameters of concentrations of various chemical constituents of groundwater of the area during post monsoon period of 2009 are shown in table 4. The data shows that there is considerable variation in the concentrations of all the constituents in the area, which may be due to a host of factors including soil type, land use, geology, geomorphic set up, human activities (like open dumping of solid wastes, open

Table 3: Suitability of groundwater for drinking S.

Constituent

BIS (1991) Standard

No. 1 2 3 4 5 6

Desirable

Permissible

500 6.5-8.5 200 300 250 1.0

2000 600 600 1000 1.5

TDS (ppm) pH Total alkalinity (ppm) Total Hardness( ppm) Chloride (ppm) Fluoride (ppm)

Percent Samples Desirable Permissible 33.33 100 16.37 30.41 71.93 88.30

66.08 82.46 63.16 28.07 4.10

Not Suitable 0.59 1.17 6.43 7.6

Table 4: Important statistical parameters of the water quality data Parameters Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum

TDS

0.70 0.03 0.62 0.92 0.41 0.17 2.77 1.54 2.07 0.12 2.19

209.77 9.09 180.00 116.00 118.91 14139.38 0.61 1.04 540.00 48.00 588.00

372.81 11.82 350.00 340.00 154.58 23895.51 2.48 1.18 860.00 100.00 960.00

324.40 9.07 312.00 268.00 118.56 14056.29 -0.18 0.41 544.00 80.00 624.00

7.50 0.03 7.50 7.60 0.34 0.11 -0.94 0.17 1.40 6.90 8.30

680.43 25.29 603.00 423.00 330.70 109365.07 2.92 1.34 2106.00 178.00 2284.00

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Table 5: Variation of water quality with season S. N.

Water Quality Parameter

Villages Exceeding the permissible limit during both periods

Villages Exceeding the permissible limit only during premonsoon

Villages Exceeding the permissible limit only during post monsoon

1 2

Total Dissolved Solids Total Alkalinity

Malkapur Nil

Ch Konapur, Togarpally Gollapally, Malkapur

Total Hardness

Fluoride

Ch Konapur, Malkapur, Saidapur, Togarpally Garakurthy, Malkapur

Gollapally Munidevunipally, Togarpally Girmapur, Gollapally

Nil

Gangaram, Togarpally

defecation, water stagnation around drinking water sources, use of fertilizers for agriculture, etc.) and the extent of dissolution of minerals during the process of rock-water interaction. (Sundara Kumar et al. 2010). The Parameters, which are analyzed during water analysis, are pH, conductivity, turbidity, chlorides, total alkalinity, fluoride, nitrate, iron. The groundwater in the major part of the area is fresh with TDS in the range of 178 to 1000 mg/L. In the villages of Gollapally and Marepally the alkalinity values are found to exceed the permissible limits of 600 ppm. The total hardness data of the samples indicate that the groundwater is only moderately hard (75-150 ppm) to hard (150300 ppm) in respect of 30 % of samples and 70 % of the samples are found to be very hard (>300ppm).

Gangaram, Garakurthy, Munidevunipally

The chloride content ranges from 48 to 588 mg/L. However in some villages where it is above 250 ppm, salty taste to drinking water is imparted and thus water becomes objectionable for drinking. The concentration of Fluoride in the study area varies from as low as 0.12 mg/L to as high as 2.19 mg/L. However, about 88% of the samples have fluoride concentrations within the desirable limit of 1mg/L and only 7.6 % of the samples exceed the permissible limit of 1.5 mg/L. Seasonal variations of groundwater quality in 9 villages of the mandal have been studied using the water quality data (498 samples) collected from bore wells from pre-monsoon (2007) to post-monsoon (2010) periods and it is noted that the pH and chloride values are well within the range

Fig. 1: Rainfall distribution of Kondapur mandal

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Fig. 2: Number of villages falling under each category by two methods of WQI

Fig. 3: Water quality parameter wise number of villages exceeding the BIS Value for drinking purpose both during pre and post monsoon seasons for all the nine villages. Other observations are presented in table 5. CONCLUSION Considering all the six parameters of drinking water, it is found that more than 84 % of samples collected from the study area have all the

constituents well within either desirable or permissible limits of BIS: 10500-1991 and hence safe for drinking purpose. By analyzing the data of 498 samples of 9 villages, pertaining to both pre and post monsoon seasons for the period 2007 to 2010, it is concluded that, the quality of groundwater in these villages is changing from season to season. Hence continuous monitoring of groundwater quality is essential in order to supply potable water to the rural people.

REFERENCES 1.

CGWB, Southern Region, Hyderabad., Groundwater Information, Medak District, Andhra Pradesh (2007). Kavitha, R. and Elangovan, K., Groundwater quality characteristics at Erode district, Tamilnadu India. International Journal of Environmental Science 1(2) : 145-150

(2010). Ramakrishnaiah, C. R., Sadashivaiah, C. and Ranganna, G., Assessment of water quality index for the groundwater in Tumkur Taluk, Karnataka State. E-Journal of Chemistry. 6(2) : 523-530 (2009). Shah, M. C., Shilpkar, P. G. and Acharya, P. B., Groundwater quality of Gandhinagar

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Taluka, Gujarat, India. E- Journal of Chemistry. 5(3) : 435-446 (2008). Sinha, D. K. and Ritesh Saxena., Statistical assessment of underground drinking water contamination and effect of monsoon at Hasanpur, J. P. Nagar Uttar Pradesh. Journal of Environment, Science and Engineering. 48 : 157-164 (2006). Subba Rao Chandaluri, Sreenivasa Rao, B., Hariharan, A. and Manjula Bharathi, N., Determination of water quality index of some areas in Guntur District, Andhra Pradesh. International Journal of Applied Biology and Pharmaceutical Technolog 1(1): 78-86 (2010). Sundara Kumar, K., Sundara Kumar, P., Ratnakanth Babu, J. and Hanumantha Rao.,

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Assessment and mapping of goundwater quality using Geographical Information Systems. International Journal of Engineering, Science and Technology 2(11) : 6035-6046 (2010). Yadav, A. K., Khan, P. and Sharma, S. K., Water quality index assessment of groundwater in Todaraisingh tehsil of Rajasthan State, India-A Greener Approach. E-Journal of Chemistry. 7(SI): S428-S432 (2010). Yogendra, K. and Puttaiah, E. T., Determination of water quality index and suitability of an urban water body in Shimoga town of Karnataka. Proceedings of Taal, 2007, The twelfth World Lake conference, pp 342-346 (2007).

Current World Environment

Vol. 8(2), 275-282 (2013)

A Geo-Environmental Analysis of the Groundwater α-vis Surface Water Scenario in Guwahati City Resource vis-α NEELKAMAL DAS and DULAL C. GOSWAMI Department of Environmental Science, Gauhati University Guwahati - 781 014, India. http://dx.doi.org/10.12944/CWE.8.2.13 (Received: June 03, 2013; Accepted: July 17, 2013) ABSTRACT Guwahati city is located on a unique geo-environmental setting with an interface of hills and valleys along with a prominent river front. The existence of various surface water sources, geohydrological set up and rainfall intensity play a significant role in the ground water regime of the city. However, rapid urbanisation of the city during the last few decades has altered the landscape of the city and disturbed the water retention capacity as well as the flow dynamics of various surface water sources, thereby affecting the infiltration rate to a great extent. Unprecedented rise in the population of the city has exerted more pressure on the various sources of water, particularly the groundwater resource. It has thus become imperative to utilise the various sources of water in a more systematic and scientific manner, giving due emphasis to the water requirement and the prevailing hydrological conditions of the area. Moreover, it is also observed that the city experiences an average annual rainfall of 162 cm with about 110 rainy days per year. The city thus has enough potential for harvesting the rainwater it receives, instead of allowing it to flow untapped. Rainwater can be tapped and utilised to revive the various surface water sources of the city, thereby facilitating natural groundwater recharge, as surface water bodies like wetlands, lakes and ponds do act as potential groundwater recharge zones.

Key words : Ground water, Infiltration, Recharge, Surface water, Water table, urbanisation INTRODUCTION Groundwater constitutes about 20 percent of the world’s fresh water supply, which is approximately 0.61% of the entire world’s water, including oceans and permanent ice. Global groundwater storage is roughly equal to the total amount of freshwater stored in the snow and ice caps, including the north and south poles. In India more than 90% of the rural population and nearly 30% of the urban population depend on groundwater for drinking purpose (NRSA, 2008). Groundwater is replenished naturally by surface water from precipitation, streams and rivers. However, unplanned urbanisation coupled with rapid population growth has started exerting tremendous pressure both on the surface and subsurface water resources. Unprecedented population growth affects the hydrological cycle resulting in less subsurface infiltration rate and higher volume of surface water run-off (Schueler,

1987; Ferguson, 1994). The city of Guwahati, in spite of being located on the bank of the mighty Brahmaputra, depends heavily on the groundwater resource for its water requirements. About 69.90% of the households in the city use groundwater, while 27% depend on piped water supply and the rest on surface water obtained mainly from streams (Goswami et al., 2005). But since the last few years due to excessive growth of population and the subsequent overexploitation of groundwater, the water table in many parts of the city has been showing a declining trend. Guwahati city, the gateway of North East India is located in the Kamrup (Metropolitan) district. It is bounded by 26°05' N to 26°12' N latitudes and 91°34' E to 91°51' E longitudes. Situated on the southern bank of the river Brahmaputra, the Guwahati Municipal Corporation (GMC) area covers an area of about 216 sq. kms. The city presents an undulating topography, dotted with

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nineteen low lying hills interspersed with elongated valley fills. The southern and the eastern sides of the city are bounded by rows of hills which are extensions of the Khasi Hills of Meghalaya (Pathak, 2001). Geologically, Guwahati rests upon the typical Precambrian rock units which are overlain by young and recent alluvium. The river Bharalu dissects the main city for a length of about 9 kms (Barman, 1993). Small rivulets like Panchadhara, Kalmoni and Khonanadi flow through the fringe zone of the city in the south and south-west. It is worth mentioning that about 61.8% of the total area of the city is covered by hills, water bodies and pockets of low lying areas (Borah and Saikia, 1998). The city is located at an elevation of about 54 metres above mean sea level. The location map of Guwahati city with its Municipal ward boundaries is shown in figure 1.

topographical sheet is in 1:50,000 scale, the required portion is enlarged upto 1:25,000 scale. All the thematic details were transferred to the base map from SOI topographical sheet. Preliminary interpretation from the satellite imagery was done and landuse / landcover map and geomorphological were drawn from the imagery. The IRS imagery of 2006 on 1:50,000 scale was also used. In addition to these the hydrogeomorphological map, groundwater potential map and panel diagram of the study area were procured from various relevant organisations. The maps were then analysed and integrated using GIS techniques. To acquire the groundwater level in different parts of the study area, water levels of dug wells were also taken.

MATERIALS AND METHODS The methodology applied in this study involves both empirical analysis and field surveys. Data for the study were collected from both primary and secondary sources. Primary data on various parameters pertaining to the study area based on field surveys using a questionnaire specially designed for the purpose and making field measurements on selected geohydrological parameters like ground water level in wells, volume of surface water bodies, etc., have been collected from the field, satellite imagery, Survey of India topographical sheets, geocoded False Colour Composite (FCC) and black and white paper prints. The scale used for the Primary data extraction was 1:25000. The secondary data source comprises maps, statistics, published research papers, journals, satellite imagery, etc. These secondary data were mainly collected from various organisations and departments such as Central Groundwater Board (CGWB), Assam Remote Sensing Application Centre (ARSAC), Regional Meteorological Centre, National Institute of Hydrology (NIH), Directorate of Geology and Mining (DGM), etc.

At present in Guwahati, the Guwahati Municipal Corporation (GMC), Public Health Engineering Department (PHED) and Assam Urban Water Supply and Sewerage Board (AUWSSB) are primarily involved in distribution of domestic water supply mainly drawn from the Brahmaputra River. However, the water supplied by these agencies is able to meet the demands of just about 30 % of the cityâ&#x20AC;&#x2122;s population. The total installed capacity of potable water generation under GMC area is around 98 MLD (Million Litre per Day) while the requirement is as much as 132 MLD. The projected water demand in the existing Guwahati Municipal Area is further expected to grow to the tune of 425 MLD by the year 2025 (GMDA, 2009). Although the Brahmaputra can fulfill the water demand of all the inhabitants of this city, yet it seems that due to unorganised planning and inadequate infrastructural development of treatment plants over the years, major part of the cityâ&#x20AC;&#x2122;s population has to depend on groundwater to meet their demands. Moreover, distribution and development of the aquifers are not uniform in Guwahati and often during dry season the hand pumps and deep tube wells in many parts of the city go dry leading to acute scarcity of groundwater.

The Survey of India (SOI) topographical sheets no 78 N/12, 78 N/16 on 1: 50,000 scale were used to prepare the base map and to acquire various information about the area. Though the SOI

Surface water scenario of the study area The existing natural drainage of Guwahati comprises the Brahmaputra and its minor tributaries such as the Bharalu, Mora Bharalu, Khanajan,

RESULTS AND DISCUSSION

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Fig. 1 : Location map of Guwahati city showing its Municipal Ward Boundaries

Total area under wetland (in sq. kms.)

Fig. 2 : The natural drainage density in different wards of Guwahati city

Fig. 3 : Total area under wetland in different wards of Guwahati city

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Basistha and Bondajan. The Brahmaputra which flows in an east-west direction along the northern fringe of Guwahati is only 1.5 km wide near the city. In addition to the above mentioned tributaries, Digaru, Bonda, Amcheng, Barapani are some of the other major streams that flow through the city. The Digaru along with other tributaries like Bonda and Amcheng form small plains in between the hill ranges in the east and south-eastern part of the city. The three tributary basins of Guwahati, viz. the Bondajan basin, the Bharalu basin and the Khanajan basin have contrasting characters with a 9 degree, 6 degree and 3 degree slope respectively. This shows that the average slope of the study area falls while transversing from the eastern part to the western part, with exception of inter-basin separation. The Khanajan in the western most part of the city links Deepor Beel (wetland) with the Brahmaputra. Mora Bharalu is a small channel which is linked with Bharalu and Basistha stream in south and south-eastern part of the city and flows to the Deepor Beel.

The distribution of the surface water sources, however, is not uniform throughout the city and is controlled by the landscape patterns along with the rivers and streams which originate from the southern and north eastern highlands and flow along the natural slope gradient of the city. Wetlands are located in the central, south eastern and western parts of the city. These parts are primarily depressed valley areas with remnants of palaeochannels of Brahmaputra being traced through various studies and surveys. From figure 2, it is observed that natural drainage exists in atleast 30 wards of the city with the highest density of about 26 sq. kms. in ward number 46.

The city of Guwahati is dotted with numerous surface water bodies comprising of wetlands and ponds. These water bodies play a significant role in holding rainwater for considerable period of time and serve as reservoirs. But unprecedented urbanisation and development activities have reduced these water bodies to fragmented forms. At present, the city can boast of only six wetlands, viz., the Deepor beel, Hahsora beel, Silsako beel, Narengi beel, Borsola and Sarusola beel. The Deepor beel which is situated in the western part of the city is the largest amongst them and is also a Ramsar site. The Borsola and Sarusola beels are located in the central part, while the Hahsora, Narengi and Silsako beels are located in the eastern part of the city. Apart from the various natural water bodies, there are a number of historic water tanks or ponds within the city. These tanks which include Dighalipukhuri, Silpukhuri, Joorpukhuri, Nagputapukhuri, Kamakhyapukhuri, etc. play a critical role in maintaining surface water repositories of the city. These surface water bodies sustain water flow dynamics between the high land and low land of the cityâ&#x20AC;&#x2122;s landscape, function as storm water reservoir and act as potential sites for natural recharge of the sub surface water.

Rainfall regime of the study area Rainfall is highly seasonal in Guwahati and it falls under the regime of the south-west monsoon. The city experiences an average annual rainfall of about 162 cm, which is considerably less than the average annual rainfall of about 220 cm for the state of Assam as a whole. The average number of rainy days per year in the city is about 110 days. The average mean rainfall in the study area is shown in the form of bar diagram in figure 4.

Moreover, it is evident from figure 3 that atleast 8 wards of the city viz, 1, 2, 13, 37, 46, 47, 51 and 52 have more than 5 sq. kms. of its area under wetlands and these wetlands facilitate in maintaining the moisture content of soil in its vicinity and also in elevating the water table of the surrounding area.

In the study area, the maximum rainfall occurs during the monsoon period and the minimum during post-monsoon period, as evident from figure 5. Some of the dug wells dry up during the lean period (post-monsoon and pre-monsoon) of the year as the groundwater draft exceeds recharge of the underground aquifers. This is mainly because there are no structures to intercept and retain the excess rainfall that occurs during the monsoon period and huge amount of rainwater is lost as run off. It therefore becomes imperative that long-term measures be taken to entrap and retain rainwater during the monsoon period in utilise them in the lean periods.

DAS & GOSWAMI, Curr. World Environ., Vol. 8(2), 275-282 (2013) Groundwater scenario of the study area: The occurrence and movement of ground water is influenced by lithology, structure, geomorphology and drainage pattern of a particular

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area while replenishment or recharge is further affected by landuse, precipitation and infiltration rate. The ground water level in the study area varies according to local topographic conditions. In areas

Fig. 4 : Mean monthly rainfall in Guwahati city

Fig. 5 : Seasonal distribution of rainfall in Guwahati city

Fig. 6 : Map showing groundwater potential zones of the study area

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close to the undulating inselbergs / residual hills viz. Basistha, Borbari, Panjabari, Mathgharia, Birubari area the water level is deeper compared to the areas situated in relatively flat alluvial plains and valley-fill areas such as Rukminigaon, Wireless, Kacharibasti, Gotanagar, Jalukbari areas. In valley-fill areas depth to water level is variable depending on thickness of the residuum. Overall depth to water level gradually reduces from elevated eastern and south-eastern areas to the flat lying alluvial plains in the west. However, the depth to water level in areas like Rehabari, Nepali Mandir, Paltanbazar area is found to be deep though these are situated on valley-fill deposits. This may be due to high amount of groundwater withdrawal in the area for both domestic and commercial purposes. Geological structures may act either as conduits or barriers to the flow of groundwater. Lineaments representing faults, fractures, shear zones, etc. are the structural features that control the occurrence and movement of groundwater in hard rock terrain (Subramanian and Seshadri, 2010). In the eastern part of the study area there is a fault trending NNE-SSW which gives rise to the formation of Silsako and Hahchora beels. Another prominent fault is seen in the central part of the study area trending along NNE-SSW direction. This lies in the corridor between the Fatasil hills and the Narakasur hills. These faults are overlain by weathered rocks or alluvial plain. This zone, which includes areas such as Garchuk, Betkuchi, FatasilAmbari, Birkuchi, the Silsako and Hahchora beels has negligible thickness of clay layer in their soil profile, while the thickness of the sandy layer varies from 50-60 metres, thus resulting in easy and convenient infiltration of surface water through them. The groundwater potential zones of the study area are shown in figure 6. Hydrogeological studies revealed the presence of groundwater just under water table conditions in case of shallow aquifers; however, in case of deeper aquifers it is available within the semi-confined to confined conditions. In the loose unconsolidated formations depth to water in the open dug wells ranges from 2 to 4 metres below ground level during pre-monsoon period. Dug wells located in the foothills zone however show deeper

ground water level ranging between 5 to 10 metres below ground level during pre-monsoon period. Shallow tube wells constructed in the loose formation down to 30 metres by Public Health Engineering Department yield around 2000 to 3000 litres per hour and the well yield shows consistent behaviour throughout the year. Normal dug wells constructed in the pediment formation covering the valley parts of the city down to maximum depth of 15 metres store good quantity of water irrespective of seasonal change and can be pumped at the rate of 10 cu.m/day. However, nor mal dug wells constructed in the weathered formation of the hill areas down to maximum depth of 25 metres having water level around 5 to 7 metres during monsoon period and more than 10 metres during lean period show erratic behaviour of storage depending upon the structural pattern of the rock and seasonal rainfall. Deep tube wells constructed in the valley portion down to maximum depth of 200 metres in the western parts of the city show very good discharge of about 70 to 100 cu.m/hr. for nominal drawdown. In the central part of the city, deep tube wells down to maximum depth of 100 meters give yield upto 80 cu.m/hr. Near hillocks of the eastern and southern parts of the city, the discharge of deep tube wells down to maximum depth of 80 metres give yield upto 30 cu.m/hr for considerable drawdown. The hard rocks found in these hillocks are also potential sites for construction of bore wells. Bore wells constructed down to maximum depth of 200 metres in the hard rocks have been found to be effective for groundwater development. Fractures, fissures, joints developed during tectonic events acts as good water repository in these hard rocks. Maximum yield of such wells particularly in the Beltola and Odalbakra areas reveal that water can be drawn at the rate of 80 cu.m/hr for six to eight hours daily. As per hydrogeological studies conducted by the Central Ground Water Board during 2004 â&#x20AC;&#x201C; 2006, the net annual dynamic groundwater availability in Guwahati has been estimated to be in the tune of 11045.31 Ha-m or 11 mcm with a static ground water resource of 625152 Ha-m or 625 mcm, up to the depth of 200 metres. The current annual gross groundwater draft for all uses has been estimated to be around 2806 Ha-m. Based on the long term groundwater trend for a minimum

DAS & GOSWAMI, Curr. World Environ., Vol. 8(2), 275-282 (2013) period of 10 years, the stage of groundwater development (in %) can be expressed as, Stage (%) =

Gross Groundwater draft × 100 Net annual groundwater availability

2806 = × 100 11045.31 = 25.4 % Although this indicates the presence of ample groundwater resource and the stage of development is also within manageable proportions, it should however be taken into consideration that the utilisation of groundwater resource should be done in a scientific and systematic manner, with due emphasis on the prevailing hydrogeological conditions of the area. Groundwater development and management is the key for sustainable upliftment of a particular area and proper management practices will ensure effective utilisation of this valuable natural resource. It is imperative that designing of wells should be based on the aquifer characteristics, hydrogeologocal setup and water requirement. The ever increasing rate of population growth coupled with an expanding urban sprawl have resulted in overdependence on groundwater for meeting the daily water requirements of a major chunk of the city population. This has led to a rapid depletion of water table due to over-exploitation of groundwater in recent years. The irony of the situation is that inspite of being located on the bank of one of the world’s largest rivers – the Brahmaputra, most of the inhabitants of Guwahati city face the problem of acute shortage of water. The rolling topography of the city marked by several hills and hillocks provides a perfect setting for

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locating large-size storage reservoirs and tanks which can serve different parts of the city through a well organised network of water distribution system. Further, it is recommended that the general public, non-governmental organisations and the concerned government authorities should play a proactive role in this regard and take certain initiatives, such as, Delineation of potential recharge zones and formulation of appropriate plans and programmes to preserve these zones and to revive and reclaim the areas which have deteriorated during the course of the time. Awareness should be created among the general public by different public and nongovernmental organisations about the importance of such recharge zones for increasing the availability of water and safeguarding the environmental quality of the region.(III) Stern regulatory and authoritative steps should be taken by the concerned Governmental agencies and departments to stop the encroachment of the potential recharge zones into built-up areas. ACKNOWLEDGEMENTS The authors acknowledge the help of the scientists, academicians and officials of the various institutions and organisations, particularly, Central Groundwater Board (CGWB) NE region, Assam Remote Sensing Application Centre (ARSAC), Regional Meteorological Centre, National Institute of Hydrology (NIH), Directorate of Geology and Mining (DGM) for their cooperation and assistance during the course of this work.

REFERENCES 1.

Barman D. K., Remote sensing contribution for augmentation of urban water supply in Greater Guwahati area, National Symp. on Remote Sensing Applications for Resource management with special emphasis on NE Region, 490-496 (1993). Borah P. and Saikia R., A Geomorphological study of water logging problem in Guwahati

City, Assam, Proceedings of NAGI’s (NE Region) National Conf. on Environment & Sustainable Development, 258-265 (1998). Ferguson B. K., Storm Water Infiltration, Lewis Publishers, CRC Press Inc., Boca Raton, Florida, (1994). GMDA, Master Plan for Guwahati Metropolitan Area – 2025, Part-I, 141(2009).

282 5.

DAS & GOSWAMI, Curr. World Environ., Vol. 8(2), 275-282 (2013) Goswami D. C., Kalita N. R. and Kalita S., Pattern of Availability and Use of Domestic Water in Guwahati city, Symposium on 150 years of Guwahati under Public Administration â&#x20AC;&#x201C; A critical assessment of its Development, 71-80 (2005). NRSA, Govt. of India, Ground Water Prospect Mapping for Rajib Gandhi National Drinking Water Mission, 256 (2008). Pathak B., Study of some geophysical properties of the basement and its overlying sediments of the Greater Guwahati area, district Kamrup, Assam, Unpublished

Doctoral Thesis, Gauhati University, (2001). Schueler T. R., Controlling Urban Runoff : A practical Manual for Planning and Designing Urban BMPs, Department of Environmental Programs, Metropolitan Washington Council of Govt., Water Resources Planning Board, (1987). Subramanian S. K. and Seshadri K., Groundwater. In Roy P. S., Dwivedi R. S., Vijayan D. (Eds) Remote Sensing Applications, NRSC, Hyderabad, 203-215 (2010).

Current World Environment

Vol. 8(2), 283-290 (2013)

Determination of Invisible Environmental Pollution Due to Cell Phones EMF Radiation and projections for 2030 K. PARANDHAM GOWD, R.P. GUPTA and SANGEETA JAUHARI Aisect University, Bhopal-Chiklod Road, Raisen, Bhopal, India. http://dx.doi.org/10.12944/CWE.8.2.14 (Received: May 27, 2013; Accepted: July 17, 2013) ABSTRACT In the last decades cell phones usage have altered the land scape of modern human beings in countless ways, in office, at home and on mobility. However, created the environmental electronic pollution due to electromagnetic fields. In spite of the recent studies indicating possible harmful impact of EMF pollution on several species, there is no long term data available on the environmental impacts of EMF pollution and how much power density is radiated in the environment due to cell phones. The aim of this research work is to experimentally measure the EMF radiated electronic pollution levels of cell phones in three different states such as on(sleep/idle) mode, receive and transmit modes as an invisible environmental pollution. These measurements are carried out at the centre frequency of 1800 MHz and in the 300 MHz- 50 GHz frequency band. Another main aim is to carry out the projections of cell phones growth due to exponentially expanding mobile technology products, industrialization along with urbanization. Further to estimate the current (2013) EMF radiation pollution levels into environment and projections for 2030 due to cell phones.

Key words: Electromagnetic Field (EMF) Radiation; Radiation Survey meter; probe ; Mobile Telephony ; Environmental EMF exposures ; Electronic pollution

INTRODUCTION Current world environment is increasingly getting polluted with a new entrant called Electronic pollution which is invisible. Extraordinary developments in various fields of science and technology in last few decades have increased the human involvement deeply into the natural environment, its related ecological, biological and physical systems resulting in various undesirable and unintentional negative impacts on human health and environment. Rapid development and usage of electronic products in all walks of life, electronic pollution into environment has become a great concern to entire world community. In this electro-magnetic pollution has assumed prominent importance which is in limelight in recent times for all negative reasons. The intensity of manmade electromagnetic radiation has become so ubiquitous and it is now increasingly recognised as a form of invisible and insidious environmental

pollution which is affecting environment and human health alike in different ways1. Electromagnetic radiations are not easily recognised and detectable, However their impacts are being felt on human health hazards such as blood barrier resulting in neuronal damage, risk to children/pregnant women, DNA damage, skin problems, ringxeity including ear damage, cause for tumour in the eye, sleep disorders, headaches, increase in cancer causes which have been attributed by World health Organization(WHO) and other researchers. WHO has conducted study in 13 countries has reported 5117 brain tumour cases2-4. Professor Girish Kumar of IIT, Bombay has in his research quoted saying there are 200 research papers contributing to effects of EMF radiation to human health problems 5-6. The impact of EMF radiation on environment further escalates on forests, birds, bees and wildlife5 and7. The cello phone operators association and government of

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India reject these allegations due to lack of evidence. Thus the conflict among designers, manufacturers, corporate, distributers, government and consumers need to be controlled and resolved. In such a situation there is a great demand for determination of quantum of invisible EMF radiation into environment and society. Every year, hundreds of thousands of new cell phones are introduced into market. Mobile telecom revolution in the modern world has triggered not only the growth of world economy but has changed the life style of millions of people. Mobile telephony is growing exponentially in India and across the world. At present there are about 800 million mobile subscribers in India and over 4.03 billion in the world. The population projections for India 8, 9 China , USA10 and the entire world11-14 are as shown in the table.1 below till 2030. Due this exponential growth of population, urbanization, consumer electronics products concern for environment and human health hazards is growing through out the world. There is a great need to know what are the current EMF emissions into environment and for 2030 by cell phones. Hence, measurement and estimation of invisible EMF emissions into environment and society are required to be determined through experiments. EXPERIMENTAL In spite of the recent studies indicating possible harmful impact of EMF on several species, there are no long-term data available on the environmental impacts of EMF radiations as of now. Studies on impact of cell phones and cell phone towers and EMF radiations on birds and other wildlife are almost non-existent in India. Moreover pollution from invisible EMF radiations being a relatively new environmental issue. In this research work EMF radiations of 6 randomly selected cell phones and their EMF emissions were measured on; on, receiving and transmitting modes.

For this research work Narda 8718 B Radiation Survey Meter was used. These 8700 series EMF measurement system offers a very broad selection of probes. 8700D series probe has a quick release, eight pin connector that allows the probe to attach directly to 8718B Radiation Survey meter and hence it was used. The 8718 B Radiation Survey meter can store up to 6 probes. The procedure illustrated in Narda EM Radiation Survey Meter 8718B was followed16-17 in measuring the direct digital readings for selected seven mobiles in three conditions, i.e.; ON, Receiving and Transmitting conditions. The auto-zeroing with internal calibration and spatial averaging facility of this Radiation Survey meter were utilized for this research work. The Narda 8718 B radiation Survey meter and 8700 D antenna probe are as shown in figure 1. Below. The following salient features and steps were followed in the research work for EMF emissions measurement. (a) Connecting the antenna probe 8710 D with the Radiation Survey Meter. (b) Placing the probe inside the radiation free storage case. (c) Switching on the meter. (d) Selecting the exact probe model from the list of probes. (e) Selecting the test frequency. (f) Auto zeroing with inbuilt features of the meter. (g) Reading the back ground EMF level. (h) Measure the EMF levels in different modes (on/Tx/Rx) placing different models of mobiles at the same distance from the probe. (i) Subtracting the back ground levels from the respective readings. (j) Tabulating the EMF data according to the modes and the models. RESULTS AND DISCUSSION The EMF radiation levels of 6 randomly selected cell phones were experimentally measured using Narda Radiation Survey meter 8718 B along with probe 8700D.The EMF levels were determined under three specific conditions on cell phones, namely ON, Receiving and Transmitting conditions. These measurements were carried out at centre frequencies of 800 MHz, 1800

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Table 1: Population projections for 2030 Country

2012 Population (Billions)

2020 Population (Billions)

2030 Population (Billions)

1.240 1.339 0.304 7.060

1.326 1.423 0.325 7.900

1.460 1.454 0.351 8.800

India China USA World

Table 2: Cell phones projections for 2030 Country

2012 Population (Millions)

2020 Population (Millions)

2030 Population (Millions)

908 1046 316 6000

994.5 1071.8 338 6873

1095 1105 361 7656

India China USA World

Table 3: Average EMF radiation of a cell phone Frequency

Average Rad Power Density- On mode (w/m²)

Average Rad Power Density- Rx mode (w/m²)

0.08 0.213

3.198 4.439

1800 MHz 300 MHz – 50 GHz

Average Rad Power Density-Tx mode (w/m²) 3.354 4.2067

Table 4: EMF radiation projections of cell phones at 1800 MHz Country

India China USA World

2013 Rad Power Density (Million w/m²)

2020 Rad Power Density 2030 Rad Power Density (Million w/m²) (Million w/m²)

72.64 83.68 25.28 480.0

2903 3345 1010 19188

3045 3508 1059 20124

79.56 84.74 27.04 549.8

3180 3427 1080 21979

3335 3594 1133 23052

116.8 116.3 29.20 612.5

4669 4649 1167 24484

Tx 4896 4876 1224 25678

Table 5: EMF radiation projections of cell phones between 300 MHz- 50 GHz Country

India China USA World

2013 Rad Power Density (Million w/m²)

2020 Rad Power Density 2030 Rad Power Density (Million w/m²) (Million w/m²)

19.34 22.28 6.730 127.8

4030 4643 1402 26634

3819 4400 1329 25242

21.18 22.83 7.199 146.4

4414 4757 1500 30509

4183 4509 1421 28914

31.09 30.97 7.774 163.1

6480 6454 1620 33985

Tx 6142 6116 1535 32209

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MHz and between 300 MHz- 50 MHz frequency band. The table 1 shows the population projections for 2030 and table 2 indicates the cell

phones projections for 2030 for India, China, USA and the entire world. In this research work for calculating cell phones projections for India, China, USA and the world for 2030, it is assumed that 74.71%, 75.32, 103.9% and 87% of respective

8700D Series Probe

Fig. 1: Radiation Survey Meter 8718B with 8710 Probe

Fig. 4: Cellphone EMF Radiation Pollution Projections For India At 300 MHz-50 GHz

4â&#x20AC;&#x2122;(1.2m) Cable

Fig. 2: Radiation Survey Meter 8718B Connectivity with 8710 Probe

Fig. 5: Cellphone EMF Radiation Pollution Projections For China At 1800 MHz

Fig. 3: Cellphone EMF Radiation Pollution Projections For India At 1800 MHz

Fig. 6: Cellphone EMF Radiation Pollution Projections For China At 300 MHz-50 GHz

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Fig. 7: Cellphone EMF Radiation Pollution Projections For USA At 1800 MHz

Fig. 8: Cellphone EMF Radiation Pollution Projections For USA At 300 MHz-50 GHz

Fig. 9: Cellphone EMF Radiation Pollution Projections For World At 1800 MHz

Fig. 10: Cellphone EMF Radiation Pollution Projections For World At 300 MHz-50 GHz

countries population will be owning the cell phone connectivity. It is seen that 154% of Russian population will be having cell phone connectivity, though not included in this research work. The table 3 shows the averaged EMF radiated power density of a cell phone determined through this experimental work. The table 4 illustrate the EMF radiated power densities of India, China, USA and the entire world due to different statuses of cell phones alone such as on, receive and transmit conditions at 1800 MHz centre frequency for 2013, 2020 and 2030.

EMF Radiation projections for India In 2013 when India is asleep and all cell phones are in on(sleep) mode, India emits invisible EMF power density of 72.64 and 19.34 million watts per square meter at 1800 MHz and in 300 MHz-50 GHz frequency band into environment respectively. By 2020 these figures would be 79.56 & 21.18 million watts per square and by 2030 these figures will increase to 116.8 & 31.09 at the above stated frequencies. The radiated power densities when all cell phones of India are in receiving and transmitting modes are also shown in tables 4 and 5 at stated frequencies for 2013, 2020 and 2030 respectively.

The table 5 shows the EMF radiated power densities of India, China, USA and the entire world due to different statuses of cell phones alone such as on, receive and transmit conditions between 300 MHz and 50 GHz frequency band for 2013, 2020 and 2030.

The cell phones radiated power densities in on, receive and transmit modes by India at 1800 MHz and in 300 MHz-50 GHz band are shown in bar charts in figures 3 and 4 for 2013, 2020 and 2030 respectively.

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Assuming that 50% of cell phones of India are transmitting and 50% are receiving which is most realistic, in 2013 India will contribute 2975 and 3924 million watts per square meter at 1800 MHz and in 300 MHz- 50 Ghz band respectively. These quantities will increase to 3275.5 and 4782.5in 2020 and 2030 respectively at 1800 MHz. EMF Radiation projections for China In 2013 when China is asleep and all cell phones are in on(sleep) mode, China emits invisible EMF power densities of 83.68 and 22.28 million watts per square meter at 1800 MHz and in 300 MHz-50 GHz frequency band into environment respectively. By 2020 these figures would be 85.74 & 22.83 million watts per square and by 2030 these figures will increase to 116.3 & 30.97 at the above stated frequencies. The radiated power densities when all cell phones of China are in receiving and transmitting modes are shown in tables 4 and 5 at stated frequencies for 2013, 2020 and 2030 respectively. The cell phones radiated power densities in on, receive and transmit modes by China at 1800 MHz and in 300 MHz-50 GHz band are shown in bar charts in figures 5 and 6 for 2013, 2020 and 2030 respectively. Assuming that 50% of cell phones of China are transmitting and 50% are receiving which is most realistic, in 2013 China will contribute 3446.5 and 3426.5 million watts per square meter at 1800 MHz and in 300 MHz- 50 Ghz band respectively. These quantities will increase to 3510.5, and 4762.5 million watts per square meter in 2020 and 2030 respectively at 1800 MHz. EMF Radiation projections for USA In 2013 when USA is asleep and all cell phones are in on(sleep) mode, USA emits invisible EMF power density of 25.28 and 6.730 million watts per square meter at 1800 MHz and in 300 MHz-50 GHz frequency band into environment respectively. By 2020 these figures would be 27.04 & 7.199 million watts per square meter and by 2030 these figures will increase to 29.20, & 7.774 million watts per square meter at the above stated frequencies. The radiated power densities when all cell phones of USA are in receiving and transmitting modes are

shown in tables 4 and 5 at stated frequencies for 2013, 2020 and 2030 respectively. The cell phones radiated power densities in on, receive and transmit modes by USA at 1800 MHz and in 300 MHz-50 GHz band are shown in bar charts in figures 7 and 8 for 2013, 2020 and 2030 respectively. Assuming that 50% of cell phones of USA are transmitting and 50% are receiving which is most realistic, in 2013 USA will contribute 1034.5 and 1370.5 million watts per square meter at 1800 MHz and in 300 MHz- 50 Ghz band respectively. These quantities will increase to 1106.5 and 1195.5 in 2020 and 2030 respectively at 1800 MHz. EMF Radiation projections for Entire World In 2013 when entire world is asleep and all cell phones are in on(sleep) mode, entire world emits invisible EMF power density of 480 and 127.8 million watts per square meter at 1800 MHz and in 300 MHz-50 GHz frequency band into environment respectively. By 2020 these figures would be 549.8 & 146.4 million watts per square and by 2030 these figures will increase to 612.5 & 163.1 at the above stated frequencies. The radiated power densities when all cell phones of USA are in receiving and transmitting modes are also shown in tables 4 and 5 at stated frequencies for 2013, 2020 and 2030. The cell phones radiated power densities in on, receive and transmit modes by entire world at 1800 MHz and in 300 MHz-50 GHz band are shown in bar charts in figures 9 and 10 for 2013, 2020 and 2030 respectively. Assuming that 50% of cell phones of entire world are transmitting and 50% are receiving which is most realistic, in 2013 entire world will contribute 19656 and 25938 million watts per square meter at 1800 MHz and in 300 MHz- 50 Ghz band respectively. These quantities will increase to 22515.5 and 28081 in 2020 and 2030 respectively at 1800 MHz CONCLUSIONS The cell phones connectivity in modern society have altered the land scape of human beings in countless beneficial ways, however

GOWD et al., Curr. World Environ., Vol. 8(2), 283-290 (2013) created the environmental exposures to invisible Electromagnetic fields. As technology progresses and data demands have increased on mobile network, towns, cities and even rural villages have seen sharp increase in the cell phone numbers as projected in table 2 for India, China, USA and the entire world. Further as the costs of mobile technology and the cell phones have fallen, their uses have multiplied dramatically and the overall levels of exposure of the population and environment as a whole have increased drastically. The RF sources emit EMF radiation continuously. The level of EMF from sources has risen exponentially, by soaring popularity of wireless technology. As of now there are no long term data available on environmental impacts of invisible EMF radiation, in spite of the recent studies indicating possible harmful effects on several species. Moreover, electronic pollution from EMF radiation being a relatively new environmental issue. There is a lack of established standard procedures and protocols to study and monitor the EMF effects especially among wildlife/ environment, which often make the comparative evaluation between studies difficult. In addition the uncoordinated research in this field, the necessary regulatory policies and their poor implementation mechanism also have not kept pace with growth of mobile telephoning. There had already been some warning bells sounded in the case of bees and birds, which probably heralds the seriousness of this issue and indicates the vulnerability of other species as well. The invisible EMF radiations are being associated with the observed decline in the population of sparrow in London and several other European cities [18]. In this research work Population and cell phones projections have been stated for India, China, USA and the world for 2020 and 2030. A cell phone that is â&#x20AC;&#x2DC;ONâ&#x20AC;&#x2122;, but not in use also radiates EMF energy. The EMF radiations from 6 randomly selected cell phones were measured using 8718B radiation survey meter with antenna probe 8710D. This meter has auto zeroing and spatial averaging facility to determine radiated power density. Based on this measurements and determination the projection of invisible EMF

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radiated quantities in to environment for India, China, USA the whole world have been successfully projected with bar charts at three different status of cell phones such as on, receive and transmit modes. These projections are included for two different frequencies for 2013, 2020 and 2030. These measurements were carried out at 1800 Mhz and in 300 MHz-50 GHz frequency band. It is seen that when the entire world sleeps and cell phones are in on(sleep) mode it radiates power densities of 480, 549.8 and 612.5 millions of watts per square in 2013,2020 and 2030 at 1800 MHz. Realistically assuming 50% of world is asleep at any given time the world radiates power densities of 280, 274.9 and 306.25 millions of watts per square meter into environment by 2013, 2020 and 2030 respectively at 1800MHz. Similarly, assuming that 50% of the world is awake and is transacting routine business, the world will radiate power densities of 20656, 22575.5, 25081millions of watts into environment at any given time by 2013, 2020 and 2030 respectively at 1800MHz. This assumption of 50% of the world transacting means 50% of cell phones are in transmitting mode and rest 50% are in receiving mode. The power density quantities measured for 2013 and projected for 2030 and 2030 call for immediate uniform EMF radiation policies. This is more so when referred to International Exposure Standards, in this it is seen that USA, Canada and Japan have 12W/ m2, ICNIRP19 and European recommendation 1998adopted in India has 9.2w/m2 (Reduced by 10 times in 2012by India), exposure limit in Austria is 0.001w/ m2 . The EMF radiation projected in this research paper expected to be correct approximately will be same into the environment across the world. It cannot recognize the Geography of any country. The current EMF levels due to mobiles and projections indicate growing threat to environment which require initiation of corrective steps by world agencies across the globe. There is a strong case in point to have a uniform EMF radiation policy across the world. This is more so because of the reason that cell phones can work in Austria with exposure limit of 0.001w/ m 2 and in USA, Canada and Japan with the exposure limit of 12W/m2 , there is a strong message

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from this research paper to advocate that entire world needs a single exposure policy. The EMF projections due to cell phones alone along with other EMF sources must be used as the precautionary principle and should prevail to better the standards of EMF radiation limits to match the best in the world to sustain the environmental safety. 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. The present study was conducted with the test equipment (Radiation Survey Meter 8718B with 8710 Probe) arranged from ISRO, complex, Ayodhyanagar, Bhopal. Authors wish to thank the officials and those dear ones who provided their best cooperation in our research work from ISRO complex, Bhopal.

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Hardell L. Carlberg M, Mild KH, pooled analysis of two case controlled studies on the use of cellular and cordless tele02 phones and the risk of benogn brain tumours diagnosed during 1997-2003 Journal Int J Oncol ; 28: 509-518. WHO/Electromagnetic Fields & Public Health. www.who.int.docstore/peh-emf/ publications/fact-press/effects193.html. www.nytimes.com/2011/04/17/—/mag-17 cellphones. Brain Tumour-wikipedia, the free encyclopedia- www.wikipedia.org/wiki/ Brain_ Tumour. Report of the Inter-Ministerial committee on EMF radiationwww.dot.gov.in/ miscellenous/mc%20 Report. www.ee.iitb.ac.in/—/GK. Wildlife and Environment-Citizens for safe Technology- citizensfor technology.org/ electromagnetic-pollution-from-phone—. “World Bank Census “, data.worldbank.org www.China-profile.com/data/ fig_pop_wpp2006.htm www.pewsocialtrends.org/us-population-

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projections-2005-2050. List of countries by population-Wikipedia, the free encyclopedia. www.worldometers.info/world-population. www.Census.gov/main/www/popclock.html. United Nations-Dept of Economic & social affairs, www.un.org http://en.wikipedia.org/wiki/ List_of_countries_by_number_of_mobile_phones_in_use. Operations manual-Narda Safety Test Solutions, www.narda.sts.us/pdf_files/—/ 8715-EMRSurveymeter.pdf. Narda Model 8718 Operational ManualNarda Safety Solutions. Alfonso Balmori & orjan Halberg, The urban decline of house sparrow : A possible link with Electromagnetic radiation, June 2007, Electromagnetic Biology & medicine, informa Healthcare, www.informaworld.com. ICNIRP Guidelines for RF exposures, en.wikipedia.org/—/International Commission_on_Ioniing Radiation— Bio-initiative report published in US 2007. WHO/Electromagnetic Fields & Public Health, www.who.int/docstore/peh-emf/ publications,fact-press/efactefs193.html.

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Heavy Metal Content of Foods and Health Risk Assessment in the Study Population of Vadodara SUNEETA CHANDORKAR* and PRACHI DEOTA Department of Foods and Nutrition, The M. S. University of Baroda, Vadodara - 390 002, India. http://dx.doi.org/10.12944/CWE.8.2.15 (Received: May 21, 2013; Accepted: July 28, 2013) ABSTRACT Indiscriminate disposal of waste water by industries and use of effluent from the effluent channel for irrigation purpose in the peri-urban areas poses a major threat to food safety. The key objective of this study was therefore to estimate the heavy metal content of foods grown around the city of Vadodara and assess the health risk in the study population. A total of 40 foods and 17 water samples were assayed for heavy metal content using the AAS. The results indicated that the mean Arsenic content of cereals (4ppm), pulses (2.5ppm), other vegetables (1.95ppm), green leafy vegetables (5ppm) and roots and tubers (2.5ppm) exceeded the critical values. Cereals (1.65ppm), fruits (1.98ppm) and curd (2.8ppm) exceeded the critical limits for Cadmium. Mean Arsenic (3.79ppm) and Lead (0.17ppm) content in drinking water was higher than the limits. Health risk assessed using Total Daily Intake (TDI), Provisional Tolerable Daily Intake (PTDI), Provisional Tolerable Weekly Intake (PTWI), provisional tolerable monthly intake (PTMI), Daily Intake of Metals(DIM), Health Risk Index (HRI) and Total hazard Quotient (THQ) for Cadmium, Lead and Arsenic indicated that the study population was at risk of heavy metal toxicity.

Key words: Heavy Metals, Health Risk Assessment, Total Daily Dietary Intake, Health Risk Index, Target Hazard Quotient. INTRODUCTION Heavy metals find their entry into food from natural sources like soil, air and water through wastewater irrigation, solid waste disposal, mining, smelting, sludge applications, vehicular exhaust, fertilizers, fungicides and industrial activities 1. (Muhammed et al, 2008). 2 (Radwan and Salama, 2006). Consumption of food crops contaminated with heavy metals is a major food chain route for human exposure3 (Khan et al, 2008). The absorption of heavy metals in the system varies to certain extent depending on various factors. The gastrointestinal absorption of Cadmium was double in women with low body iron stores compared to the control group. There is evidence indicating increased fractional absorption of Lead with respect to chronic ingestion of diets with less than adequate amounts of Calcium, Phosphorus, Iron, Selenium or Zinc in experimental animals. Moreover, Lead ingested during period of fasting gets absorbed to

a much greater extent than Lead ingested with food. 4 (WHO, 1992). Heavy metals, in general, are nonbiodegradable, have long biological half-lives and have the potential for accumulation in the different body organs leading to acute as well as chronic toxic effects. 2 (Radwan and Salama, 2006). The problem of heavy metal contamination is getting serious all over the world especially in developing countries. Moreover as heavy metal bioaccumulation increases in nutrition deprived state, developing countries with higher prevalence of under nutrition are at a greater risk of heavy metal toxicity. Most countries have established parameters for monitoring safe level of intake in terms of PTWI (Provisional Tolerable Weekly Intake) PTDI (Provisional Tolerable Daily Intake), PTMI (provisional tolerable monthly intake) for heavy metals with cumulative effect on human system and the same are revised periodically. Reference doses are also available for heavy metal intake by humans. In India Food Standards and Safety Act 2006

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(FSSA) prescribes the limits of contaminants under category â&#x20AC;&#x153;Foods not specifiedâ&#x20AC;? for selected heavy metals only5. (http://www.fssai.gov.in). To formulate regulations, there is a need for a concrete data base on the heavy metal content of various foods grown throughout India. As there are no such studies reported from Vadodara, the following study was carried out to explore this specific area. METHODS AND MATERIALS Collection of Food and Water Samples Fifty households situated within 2 km area of the main vegetable market comprised the study population. Dietary intake was assessed 24 hour dietary recall and food frequency and their body weights were noted using platform scale for calculation of acute and chronic dietary exposure of heavy metals. Forty most commonly consumed foods and seventeen water samples collected from households were analysed for heavy metal content. Vegetables and fruits (high in moisture) were freshly procured from the market and processed immediately to avoid moisture loss. Wheat (Triticum aestivum) , Rice(Oryza sativa), Pearl Millet (Pennisetum glaucum), Red gram split (Cajanus cajan), , Bengal gram whole, Bengal gram split (Cicer arietinum), Green gram whole, Green gram split (Phaseolus aureus Roxb.), Moth beans ( Vigna aconitifolius) , Peas Dry ( Pisum sativum ), Ladies finger ( Abelmoschus esculentus) , Ivy Gourd ( Coccinia grandis) , Capsicum (Capsicum annum), Drumstick (Moringa oliefera), Bottle gourd (Lagenaria steraia), Cluster beans (Cyamopsis tetragonoloba) , Cauliflower (Brassica oleracea) , Brinjal (Solanum melongena), Double beans (Phaseolus lunatus), Cucumber ( Cucumis sativus ), Fenugreek ( Tr igonella foenum-graecum) , Cor iander ( Coriandrum sativum) , Cabbage ( Brassica oleracea), Spinach (Spinacia oleracea), Beetroot (Beta vulgar is), Onion, Potato (Solanum tuberosum), Carrot (Daucus carota), Lemon (Citrus limonum) , Banana (Musa acuminate), Amla (Phyllanthus emblica), Apple (Malus domestica), Tomato, Milk (Branded) and Curd (Unbranded). The study was approved by the Departmental Medical Ethical Committee and a written consent was obtained from the subjects prior to investigation.

Sample Preparation Three grams of edible portion of each foodstuff was weighed and taken in Kjeldahl flask. Wet digestion was carried out using acid mixture (3:2:1 of nitric acid, perchloric acid and sulphuric acid) till a clear solution was obtained (which was approximately 3-4 hours). The sample was then cooled and volume of all the samples was made to 10ml using deionized water. The samples were properly coded and immediately transferred to acid washed polyethylene bottles of food grade and stored in dark and cool place till further analysis6. Raghuramulu et al, 2003). Metal Analysis Atomic Absorption Spectrophotometer (Perkin Elmer AA 600) was used for analyzing metal content namely Arsenic, Lead and Cadmium. The samples were run in duplicates and the values reported are mean of duplicates. Several parameters as mentioned below were used for the Health Risk Assessment in the study population namely, Total daily dietary intake (TDI), Provisional tolerable daily intake (PTDI), Provisional tolerable weekly intake (PTWI),Provisional tolerable monthly intake (PTMI), Daily Intake of Metals (DIM), Health Risk Index (HRI), Target Hazard Quotient (THQ).The study was approved by Departmental Medical Ethical Committee. RESULTS Heavy metal content of various foods Table 1. gives the cadmium, lead and arsenic content of various food groups. The mean cadmium and arsenic content exceeded the FSSAI limits for all the food groups except green leafy vegetables. The mean lead content was below detectable limits (Nil) in all the food groups. Arsenic content was highest in cereals followed by green leafy vegetables, pulse, other vegetables and lowest in milk and milk products. Cadmium content of Ladies finger and Ivy Gourd exceeded the limit, while Capsicum, drumstick, bottle gourd, cluster beans, cauliflower, brinjal, double beans and cucumber had Cadmium content within the acceptable levels. Cadmium content of Cabbage and spinach was above the limit, while it was within limits in fenugreek and coriander. Amongst roots and tubers, Cadmium concentration of beetroot,

CHANDORKAR & DEOTA, Curr. World Environ., Vol. 8(2), 291-297 (2013) Table 1: Mean content of Cadmium, Lead and Arsenic in various foods Foodstuff Cereals Wheat Rice Pearl Millet Pulses Red gram (split) Bengal gram (whole) Bengal gram split Green gram whole Green gram split Moth beans Peas Other vegetables Ladies finger Ivy Gourd Capsicum Drumstick Bottle gourd Cluster beans Cauliflower Brinjal Double beans Cucumber Green leafy vegetables Fenugreek Coriander Cabbage Spinach Roots & Tubers Beetroot Onion Potato Carrot Fruits Lemon Banana Amla Apple Tomato Milk & Milk Products Milk (Branded) Curd (Unbranded) FSSAI Limits

Cadmium (ppm)

Lead (ppm)

Arsenic (ppm)

1.65 1.63 1.67 1.65 1.50 1.76 1.57 1.61 1.62 1.48 1.74 0.53 1.31 1.74 1.97 0.59 0.92 1.44 1.44 1.38 0.29 1.44 1.44 0.92 0.79 0.65 1.59 1.60 1.90 2.50 1.65 1.63 1.65 1.98 2.87 2.50 1.74 1.54 1.24 1.51 0.23 2.80 ≤1.5

Nil Nil Nil Nil 0.16 Nil Nil Nil Nil Nil Nil 1.25 0.08 Nil Nil Nil 0.83 Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil ≤2.5

3.30 5.00 5.00 Nil 2.15 5.00 5.00 Nil Nil 5.00 Nil Nil 1.98 5.00 4.50 5.00 5.00 Nil Nil Nil Nil Nil Nil 3.00 5.00 5.00 5.00 5.00 1.25 5.00 Nil Nil Nil 0.48 2.40 Nil Nil Nil Nil Nil Nil Nil ≤1.1

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absent in pearl millet while in pulses it was nil in Bengal gram dal, green gram whole, moth beans and fresh peas. In other vegetables it was not detected in bottle gourd, cluster beans, cauliflower, brinjal, double beans and cucumber. It was absent in three roots and tubers namely, onion, potato and carrot. It was nil in 4 out of 5 fruits analysed namely banana, amla, apple and tomato. It was absent in both milk and curd. Arsenic content of all the other foods from all the food groups was higher than the Table 2: Mean content of Cadmium, Lead and Arsenic in water

onion, potato and carrot exceeded the limits while for Mango ginger (yellow and orange) it was within the permissible value. Cadmium content of all the fruits was higher than the limit except tomato. In milk, Cadmium was within the cut off while it was above the specified limit in curd. Lead content of all cereals, pulses, other vegetables, green leafy vegetables, roots and tubers, fruits, milk and curd was within the FSSAI limit of 2.5ppm. Arsenic was

Source Corporation (8) Corporation + Purifier (3) Bore well (1) Bore well + Purifier (2) Bore well + Corporation (2) Corporation + bore well + Purifier (1)

Cadmium (ppm)

Lead (ppm)

Nil Nil Nil Nil Nil Nil

Nil 0.28 Nil Nil 0.42 Nil

Arsenic (ppm) 2.25 5.00 5.00 4.00 1.50 5.00

Figures in bracket indicate sample size.

limit of 1.1ppm. Cadmium, Lead and Arsenic content in drinking water Table 2 presents the data on metal content of water used for drinking and cooking purpose used by the study households. The water samples were classified based on their sources into six groups namely: Cor poration water, corporation + purifier water, bore-well water, bore-well +purifier, bore-well + corporation, corporation + bore-well + purifier. The Cadmium

content of water samples was nil or below detectable limits while the Arsenic content ranged from 1.5 to 5ppm and the that of lead from 0.28-0.42 ppm. The water samples exceeded the IS specified limits for lead for a few samples and Arsenic for all the samples analysed. Contribution of various food groups towards the total daily dietary intake of Cadmium, Lead and Arsenic in the study population Table 3 presents the data on percent metal

Table 3: Percent contribution of various food groups towards the total daily dietary intake of Cadmium, Lead and Arsenic Cadmium

Lead

Arsenic

Food group

Cereals Pulses Other vegetables Roots and tubers GLV Fruits Milk Curd

31 8 11 6 5 17 4 20

Cereals Pulses Other vegetables Roots and tubers GLV Fruits Milk Curd

91. 3 3 8 0 0 0 0

Cereals Pulses Other vegetables Roots and tubers GLV Fruits Milk Curd

50 9 11 9 19 3 0 0

CHANDORKAR & DEOTA, Curr. World Environ., Vol. 8(2), 291-297 (2013) contributed by various food groups in the study population. As can be seen from table 3, Cereals are the major contributors to the daily intake of Cadmium, Lead and Arsenic in the study population. Percent Cadmium contributed by various food groups was in the following order- Cereals, curd, fruits, other vegetables, pulses, roots and tubers, green leafy vegetables and milk. Percent Lead contributed by different food groups was in the following order- Cereals, pulses, other vegetables, roots and tubers, green leafy vegetables, fruits, milk and curd. Percent Arsenic contributed by different food groups was in the following order- Cereals, green leafy vegetables, other vegetables, pulses, roots and tubers, fruits, milk and curd. The percent Cadmium contributed by cereals, curd and fruits was similar. Intake of curd was low as compared to

295

cereals and fruits however on account of higher concentration of Cadmium in curd, its percent contribution increased. Approximately 85% of the total Lead intake can be attributed to cereals. Health Risk Associated with Heavy Metals in the Study Population The health risk was assessed in the study population using TDI, PTDI, PTWI, THQ and HRI. The data are presented in Table 4. TDI for a heavy metal refers to the intake of that particular metal from all the food groups and is an important indicator of health risk in the population exposed. The TDI of Arsenic was highest followed by Cadmium and Lead. The PTDI for Cadmium was more than 15 times higher that for Lead almost two times higher while for Arsenic it

Table 4: Health Risk Assessment Due to Cadmium, Lead and Arsenic in the Study Population Health Risk Indicator

Cadmium

Lead

Arsenic

TDI (mg/day) Limit (mg/day) PTDI (µg/kg bw/day) Limit (µg/kg bw/day) PTWI (µg/kg bw/week) Limit (µg/kg bw/week) THQ Limit HRI Limit

1.00 16.89 1.00 118.95 5.8 15 7.47 -

0.69 5.93 3.60 41.55 25 78.6 16.19 -

9.08 25.16 2.10 176.14 15.00 707.1 52.59 -

was ten times higher than the cutoff given by JECFA. The PTWI too exceeded the cutoffs for Cadmium, Lead and Arsenic. The THQ value is a dimensionless index of risk associated with long term exposure to chemicals based on reference upper safe limit. (Naughton and Petroczi, 2008). THQ>1 indicates health concern. According to this criterion, all the 3 heavy metals in the present study exceeded the cut off. The HRI value of >1 represents that the population is at risk. In the present study, the HRI values for all the heavy metals studied were >1. This indicates that the population is at risk of Cadmium, Lead and Arsenic toxicity. The HRI values were highest for Arsenic followed by Lead and

Cadmium. DISCUSSION Heavy metals are non-biodegradable and its bio-accumulation increases in nutrition deprived state therefore, developing countries with higher prevalence of under nutrition are at a greater risk of heavy metal toxicity. The results obtained in the present study show that the cadmium content of almost all the foods exceeded the permissible limits and higher than that reported by other investigators. Arsenic content was highest in cereals followed by Cadmium and Lead. In the present study, the mean

CHANDORKAR & DEOTA, Curr. World Environ., Vol. 8(2), 291-297 (2013)

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Lead content in cereals, pulses and other vegetables was Nil, 0.16ppm and 0.08ppm respectively while in a study conducted in Mumbai, it was 0.018, 0.253 and 0.0041ppm respectively. In the present investigation, the Lead content was nil in green leafy vegetables, milk and fruits while it was 0.01, 0.0016 and 0.0074ppm in the Mumbai study. The Cadmium concentration in cereals, pulses, green leafy vegetables, other vegetables, milk and fruits was 1.65, 1.50, 0.92, 1.31, 0.23 and 1.98ppm respectively in the present study, while it was extremely low in the Mumbai study (0.0071, 0.0079, 0.0149, 0.0032, 0.0001 and 0.00015ppm respectively). 7 Tripathi et al, 1997). In the present study, the mean Arsenic content in cereals was 3.30ppm, while it was about 20 times lower (0.2ppm) in a study conducted in West Bengal. In the present study, the Arsenic content of vegetables (Green leafy vegetables + other vegetables + roots and tubers) was 9.45ppm while it was much lower in a study by Uchino et al (2006), namely 0.0736ppm. The variations observed can be attributed to use of fertilizers (contributes to cadmium content) and soil condition that affects the absorption by plants. Arsenic content of drinking water ranged from 1.5 to 5ppm in the present study, while it was much lower in the tube-well water samples from West Bengal (0.00064-0.17ppm).8(Uchino et al,

2006). In another study carried out in West Bengal, the mean Arsenic content of water from hand tube wells and shallow big diameter tube wells was 0.107mg/L which is lower compared to the present study.9 (Roychowdhury,Tokunaga and Ando, 2003). In Korangi industrial area of Karachi, Pakistan, Cadmium content in tube-well water was 0.041ppm (nil in present study) and Lead concentration was 0.24ppm (0-0.833ppm in the present study).10 (Saif et al, 2005). In a study carried out in industrial area of New Delhi, 2 of the 10 groundwater samples (0.0153 and 0.0104 mg/L) analysed exceeded the cut off set by IS 10500 and WHO of 0.01mg/L for Cadmium, while in the present study Cadmium was absent and therefore within the safe level. Lead content in 2 out of 10 water samples (0.055 and 0.053 mg/L) from Delhi slightly exceeded the limit of 0.05 mg/L, while in the present study it was comparatively very high (0-0.833 mg/ L).11 As is evident from the present study the quantity of food consumed is the major determinant for health risk from the specific metal. Cereals were consumed in larger quantities and therefore major contributors of various metals in the study population. Health risk assessment shows that maximum risk in the population was due to the contamination with Arsenic followed by Cadmium and Lead. Due to the paucity of data from other studies, comparison is not possible for the HRI

values. REFERENCES 1.

Muhammad F., Farooq A. and Umer R., Appraisal of heavy metal contents in different vegetables grown in the vicinity of an industrial area, Pakistan Journal of Botany, 40(5): 2099-2106 (2008). Radwan A. and Salama A., Market basket survey for some heavy metals in Egyptian fruits and vegetables, Food and Chemical Toxicology 44: 1273â&#x20AC;&#x201C;1278 (2006). Khan S., Cao Q., Zheng Y., Huang Y. and Zhu Y., Health risks of heavy metals in contaminated soils and food crops irrigated with wastewater in Beijing, China J of Science of Food and Agriculture, 1997, 73: 446-454 (2008).

World Health Organisation, Cadmium Environmental health criteria, 134, WHO Geneva (1992). Food Standards and Safety Authority of India, 2006, (http://www.fssai.gov.in) accessed on 21-5-2013. Raghuramulu N., Madhavan K. and Kalyanasundaram S., A manual of laboratory techniques, National Institute of Nutrition, Indian Council of Medical Research, Hyderabad (2003). Tripathi R., Raghunath R. and Krishnamoorthy T., Dietary intake of heavy metals in Bombay city, India, The Science of the Total Environment 208: 149-159 (1997). Uchino A., Roychowdhury T., Ando M. and Tokunaga H., Intake of arsenic from water,

CHANDORKAR & DEOTA, Curr. World Environ., Vol. 8(2), 291-297 (2013)

food composites and excretion through urine, hair from a studied population in West Bengal, India, Food and Chemical Toxicology 44: 455-461 (2006). Roychowdhury T., Tokunaga H. and Ando M, Survey of arsenic and other heavy metals in food composites and drinking water and

10.

297

estimation of dietary intake by the villagers from an arsenic-affected area of West Bengal, India The Science of the Total Environment 308: 15-35 (2003). Saif S., Haq M. and Memon K., Heavy Metals Contamination Through Industrial Effluen to Irrigation Water and Soil in Korangi Area of Karachi (Pakistan). International Journal of Agriculture and Biology 74: 646 648 (2005).

Current World Environment

Vol. 8(2), 299-303 (2013)

Effect of Heavy Metal Present in Cement Dust on Soil and Plants of Nokha (Bikaner) SURUCHI GUPTA and SARIKA SHARMA Research Laboratory, Government Dungar College Bikaner, India. http://dx.doi.org/10.12944/CWE.8.2.16 (Received: June 20, 2013; Accepted: August 25, 2013) ABSTRACT In Nokha(Bikaner) cement industries emittes cement dust in nearby farmers fields. In these industries cement dust emitted contains traces of hexavalent chromium and lead well above permissible limit in area under investigation. However, cadmium and nickel were found below limits prescribed. To analyse heavy metals viz, Cr+6, lead, Cadmium and nickel one hundred and twenty samples were collected from four directions on surface and 20 cm depth, and analyzed on atomic absorption spectrophotometer. From the above study it is clear that in case of Sarvottam cement works only lead content was higher in all directions and depths than other two plants. At tiger and Nokha cement works contamination of lead was more over limited in the first 1 km except in east direction. Mobility of lead was relatively more on top soil than 20cm depth. Hexavalent chromium content in south western direction was more for Nokha cement. Whereas, it was more in east direction in case of tiger cement. This indicated influence of prevailing direction of wind on distribution of heavy metals present in cement dust. Heavy metal toxicity results in reduction in plant height, burning of leaf margins and tip, slow leaf growth and over all wilting of Prosopis cineraria , Pearlmillet and clusterbean plants, when this metal deposits in Human body results in genetic disorders. Electrostatic precipitator can be installed to reduce the cement dust emission.

Key words : Cement dust, Hexavalent Chromium, Lead, Cadmium, Nickel, Toxicity . INTRODUCTION Complex electronic chemistry of heavy metals viz.Cr+6, Pb, Cd and Ni have been a major hurdle in unraveling its toxicity mechanism in soil and plants 1 . Heavy metal toxicity in plants is observed at multiple levels from reduced yield, through effects on leaf and root growth, to inhibition an enzymatic activities and mutagenesis. The area under present investigation is a large industrial area with two cement plants running for a very long time along the roadside on NH 89. EXPERIMENTAL Study Area Nokha is located within the arid western desert region of Rajasthan at a distance of 63 km from the city of Bikaner. Its temperature varies from 48 degree in summer to 1 degree in winter with annual rainfall of about 298 mm. To study the effect

of cement dust, whole area around three cement plants namely; Sarvottam, Tiger cement and Nokha cement were studied. the Sarvottam cement plant which is located at the distance of 5 km from Nokha (Bikaner) on national highway number 89 near Charkhada village; Tiger and Nokha cement are located in RIICO industrial, Nokha area at a distance of 500m from each other. Sampling and Procedure Study area around the plants was divided into four radiant directions of east, south, west and north in clockwise manner 2,3 . Soil samples were taken at surface and 20 cm depth at 100m, 500m,1 km,2km and 3 km distances(10 samples each) in plastic bags of Â˝ kg each. Prior to analysis, the samples were cleaned using wire mesh and pebbles removed. The samples were filtered using Whatman no.42 filter paper. Cr+6, Pb, Cd and Ni was determined by atomic absorption spectrophotometer (nov AA 400) in flame mode as given by Perkin Elmer.4

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Gupta & Sharma, Curr. World Environ., Vol. 8(2), 299-303 (2013) RESULTS AND DISCUSSION

The present study was carried out to study effect of heavy metal present in cement dust on soil and plant during 2009-2010. As per central pollution control board standards of (1995), chromium(0.1 ppm),Pb(0.1 ppm),Cd(2 ppm) and Ni(3 ppm) is toxic for agricultural operations and industry5. A perusal of table1, 2, 3 and 4 revealed following results: East Direction Sarvottam Cement Lead content ranged between 0.650 to 0.112 ppm upto 500m distance all of them above limit after that it declined below limit. Hexavalent chromium, cadmium and nickel content was lower at all the distances. Tiger Cement Lead content ranged higher between 0.699 to 0.139 ppm upto 1km. Hexavalent chromium also ranged higher between 0.199 ppm to 0.108 ppm upto 500m. However, cadmium and nickel content was relatively much less compared to other two plants. Nokha Cement Lead content ranged higher between 0.515 to 0.118 ppm upto 500m distance only. Hexavalent chromium also was higher in the first 100m ranged between 0.129 ppm to 0.103 ppm, however at all other sites it was below limits. Interestingly, cadmium and nickel content was lower at all the distances both at surface and 20cm soil depths. South Direction Sarvottam Cement Lead content ranged higher between 0.708 to 0.114 ppm upto 1km distance. Hexavalent chromium, cadmium and nickel content was lower at all the distances. Tiger Cement Lead content ranged between 0.511 to 0.119 ppm all of them were above limit upto 1 km distance more so on surface soil than at 20cm depth. Hexavalent chromium ranged between 0.155 to

0.118ppm upto 500m distance, however, showed decline after that. Cadmium and nickel content was lower at all the distances. Nokha Cement Lead content ranged higher between 0.441 to 0.203 ppm upto 2km more so on surface soil than at 20cm depth. Higher hexavalent chromium ranged between 0.173 to 0.116 ppm upto 500 m distance, however, showed decline after that. Cadmium and nickel content was lower at all the distances. West Direction Sarvottam Cement Lead content ranged higher between 0.590 to 0.138 ppm upto 2km. Hexavalent chromium, cadmium and nickel content were lower at all the distances. Tiger Cement Lead content was higher ranged between 0.560 to 0.175 ppm upto 1 km distance. Hexavalent chromium ranged between 0.173 -0.105 ppm higher above limits upto 2 km distance. Cadmium and nickel content were lower than prescribed limits. Nokha Cement Lead content ranged between 0.427 to 0.137 ppm all of than above limit upto 2 km distance. Hexavalent chromium ranged between 0.136 0.104 ppm higher above limits upto 1 km distance surface soil. Cadmium and nickel content were lower than prescribed limits at all sites. North Direction Sarvottam Cement Lead content ranged higher between 0.567 to 0.154 ppm all of them above limit upto 1 km. Hexavalent chromium, cadmium and nickel content was lower at all the distances Tiger Cement Lead content was above limits ranged between 0.178 to 0.107 ppm upto 500m. Hexavalent chromium ranged between 0.162-0.119 generally higher upto 500m. Cadmium and nickel content was lower at all the distances

0.040 0.037 0.036 0.035 0.032 0.031 0.031 0.025 0.021 0.019

100 m (s) 100 m (d) 500 m(s) 500 m(d) 1 km (s) 1 km (d) 2 km (s) 2 km (d) 3 km (s) 3 km (d)

0.650 0.470 0.235 0.112 0.098 0.087 0.075 0.067 0.056 0.044

Pb 0.334 0.287 0.228 0.215 0.191 0.183 0.174 0.169 0.110 0.095

Cd 1.150 1.132 1.105 1.098 1.086 1.063 1.090 0.903 0.898 0.858

Ni 0.199 0.174 0.108 0.093 0.086 0.085 0.079 0.077 0.075 0.068

Cr+6 0.699 0.521 0.230 0.195 0.139 0.094 0.081 0.069 0.052 0.034

Tiger

0.094 0.088 0.087 0.086 0.085 0.081 0.074 0.065 0.051 0.045

Cd 0.935 0.959 0.860 0.913 0.859 0.779 0.650 0.602 0.414 0.327

Ni 0.129 0.103 0.087 0.069 0.048 0.037 0.032 0.031 0.029 0.026

Cr+6 0.515 0.393 0.270 0.118 0.092 0.088 0.071 0.065 0.053 0.046

Nokha

0.214 0.211 0.209 0.208 0.195 0.187 0.176 0.156 0.087 0.074

0.068 0.057 0.046 0.045 0.043 0.034 0.028 0.031 0.025 0.023

100 m (s) 100 m (d) 500 m(s) 500 m(d) 1 km (s) 1 km (d) 2 km (s) 2 km (d) 3 km (s) 3 km (d)

0.708 0.653 0.554 0.447 0.269 0.114 0.079 0.051 0.039 0.028

Pb 0.291 0.284 0.278 0.274 0.251 0.235 0.218 0.214 0.207 0.190

s= surface, d= 20 cm depth, Heavy metals (in ppm)

Cr+6

Distance

Sarvottam

1.083 1.071 1.064 1.046 1.053 1.048 0.962 0.955 0.839 0.549

Ni 0.155 0.124 0.118 0.107 0.073 0.081 0.080 0.078 0.065 0.064

Cr+6 0.514 0.493 0.180 0.154 0.135 0.119 0.079 0.065 0.055 0.017

Tiger

0.099 0.092 0.083 0.080 0.082 0.075 0.068 0.063 0.050 0.047

0.948 0.969 0.952 0.926 0.892 0.833 0.838 0.797 0.615 0.551

0.173 0.143 0.115 0.116 0.098 0.093 0.089 0.085 0.062 0.058

Cr+6

0.441 0.275 0.232 0.198 0.125 0.113 0.103 0.098 0.085 0.076

Nokha

0.219 0.208 0.196 0.167 0.161 0.159 0.117 0.104 0.098 0.079

Table 2: Physico-chemical properties and level of various elements in south direction of Sarvottam, Tiger and Nokha Cement

s= surface, d= 20 cm depth, Heavy metals (in ppm)

Cr+6

Distance

Sarvottam

Table 1: Physico-chemical properties and level of various elements in east direction of Sarvottam, Tiger and Nokha Cement

1.185 1.136 1.078 1.019 0.987 0.971 0.955 0.949 0.924 0.906

1.042 1.034 1.025 1.021 1.017 1.008 0.987 0.978 0.955 0.912

Gupta & Sharma, Curr. World Environ., Vol. 8(2), 299-303 (2013) 301

0.060 0.053 0.034 0.029 0.023 0.028 0.026 0.021 0.018 0.017

100 m (s) 100 m (d) 500 m(s) 500 m(d) 1 km (s) 1 km (d) 2 km (s) 2 km (d) 3 km (s) 3 km (d)

0.590 0.513 0.359 0.335 0.261 0.224 0.138 0.079 0.064 0.023

Sarvottam

0.414 0.361 0.343 0.329 0.227 0.223 0.215 0.213 0.119 0.098

Cd 1.098 1.090 1.087 1.082 1.068 1.028 1.020 0.911 0.807 0.605

Ni 0.173 0.175 0.163 0.159 0.155 0.147 0.107 0.105 0.099 0.082

0.560 0.455 0.223 0.194 0.175 0.090 0.088 0.091 0.034 0.075

Tiger

0.092 0.091 0.084 0.082 0.078 0.079 0.073 0.070 0.056 0.042

Cd 0.967 0.913 0.908 0.856 0.847 0.839 0.811 0.745 0.613 0.599

Ni 0.136 0.124 0.115 0.109 0.107 0.104 0.031 0.029 0.027 0.017

0.427 0.419 0.347 0.294 0.164 0.157 0.137 0.068 0.083 0.074

Nokha

0.234 0.221 0.208 0.197 0.180 0.166 0.178 0.129 0.117 0.104

0.098 0.084 0.079 0.068 0.055 0.051 0.050 0.045 0.030 0.027

100 m (s) 100 m (d) 500 m(s) 500 m(d) 1 km (s) 1 km (d) 2 km (s) 2 km (d) 3 km (s) 3 km (d)

0.567 0.513 0.403 0.384 0.163 0.154 0.093 0.081 0.078 0.044

Sarvottam

0.257 0.253 0.251 0.249 0.243 0.237 0.229 0.202 0.169 0.145

s= surface, d= 20 cm depth, Heavy metals (in ppm)

Distance

1.097 1.083 1.082 1.075 1.068 1.062 1.061 1.028 0.979 0.893

Ni 0.178 0.135 0.105 0.107 0.098 0.097 0. 092 0.089 0.078 0.063

0.162 0.146 0.132 0.119 0.036 0.021 0.058 0.054 0.065 0.016

Tiger

0.095 0.090 0.088 0.084 0.083 0.081 0.079 0.076 0.054 0.042

0.948 0.934 0.940 0.938 0.929 0.906 0.825 0.813 0.757 0.701

0.115 0.121 0.097 0.085 0.074 0.035 0.021 0.019 0.018 0.012

0.267 0.253 0.139 0.124 0.092 0.089 0.098 0.078 0.058 0.045

Nokha

0.213 0.202 0.195 0.187 0.181 0.178 0.156 0.139 0.098 0.081

Table 4: Physico-chemical properties and level of various elements in north direction of Sarvottam, Tiger and Nokha Cement

s= surface, d= 20 cm depth, Heavy metals (in ppm)

Distance

Table 3: Physico-chemical properties and level of various elements in west direction of Sarvottam, Tiger and Nokha Cement

0.989 0.908 0.902 0.871 0.713 0.665 0.643 0.532 0.487 0.354

1.089 1.076 1.053 1.042 1.031 1.011 0.986 0.977 0.948 0.921

302 Gupta & Sharma, Curr. World Environ., Vol. 8(2), 299-303 (2013)

Gupta & Sharma, Curr. World Environ., Vol. 8(2), 299-303 (2013) Nokha Cement Lead ranged between 0.267-0.123 ppm generally higher upto 500m distance after that it gradually declined. Hexavalent chromium was higher in the first 100m distance ranged between 0.115-0.121 ppm, however, at rest of the sites it was below limits. Cadmium and nickel content was lower at all the distances CONCLUSION This is clear from the above study that in case of Sarvottam cement works only lead content was higher in all directions and depth than other two plants. At tiger and Nokha cement works contamination of lead was more over limited in the first 1 km except in east direction. Mobility of lead was relatively more on top soil than 20cm depth. Hexavalent chromium content in south western direction was more for both Tiger and Nokha cement. This indicated influence of prevailing

303

direction of wind on distribution of heavy metals present in cement dust6. It is concluded from the present investigation that if cement dust with traces of heavy metals continues to fall on soil and plants, it will affect the yield of plants and reduction in fertility of soil. Higher concentration of heavy metals leads to stunted growth, leaf necrosis, decrease in root growth and reduced activities of various enzymes leading to less flowering and seed setting in plants effected. The accumulation of heavy metals in Prosopis cineraria , pearlmillet and clusterbean plant parts which when used by humans will also brings diseases in them viz. changes in gastro intestinal tract as well as in accumulation in liver, kidneys, thyroid gland and bone marrow. The various hexavalent chromium compounds represent the major risk especially due to genetic effect. Keeping above analysis in mind, it is strongly recommended to emit cement dust after treatment with electrostatic precipitator.

REFERENCES 1. 2. 3.

Shanker, A. K. and Carlos Cervantes. Environ int., 31: 739 (2005) Gupta, S. and Solanki, A. Int. J. Chem. Sci. 6(2): 681- 687(2008). Ibanga, I.J., Umoh, N.B. and Iren, O.B. Soil analysis and plant analysis. 39(3&4): 552 (2008). Isaac, R.A. and Kerber, J.D. Soil science society of America, Madison W.I. (1971)

Gupta, P. K. Methods in environmental analysis: water, soil and air. Agrobios (India), Jodhpur, p 18-19 (2000). Zerrouqui, Z., Sbaa, M., Qujidi, M., Elkharmouz, M., Bengamra, S. and Zerrouqi, A. Assessment of cementâ&#x20AC;&#x2122;s dust impact on the soil using principal component analysis and GIS. Int. J. Environ. Sci. Tech., 5(1):125134. ISSN: 1735-1472. (Winter,2008)

Current World Environment

Vol. 8(2), 305-308 (2013)

Cadmium Induced Histopathological Changes in the Intestine of Indian Flying Barb, Esomus danricus SUCHISMITA DAS1* and ABHIK GUPTA2 1

Department of Life science and Bioinformatics, Assam University, Silchar - 788 011, India. Department of Ecology and Environmental Science, Assam University, Silchar - 788 011, India.

http://dx.doi.org/10.12944/CWE.8.2.17 (Received: July 04, 2013; Accepted: August 13, 2013) ABSTRACT Indian flying barb (Esomus danricus) was exposed to sublethal concentrations of 636.3, 63.6 and 6.3 µgl-1 Cadmium for 28 days and intestinal histopathology was observed by light microscopy after staining with Haematoxylin-Eosine. Exposed fishes showed severe to mild superficial erosion of mucosa, dense lamina propria, chronic inflammatory cell infiltration as well as vacuolation. With the increase in exposure dose, severity of effects was observed.

Key words: Teleost, Chronic, Heavy metal, Inflammation, Ulcer.

INTRODUCTION Cd is a non essential heavy metal, mainly used for rechargeable nickel-cadmium batteries, pigments, coatings and plating, and as stabilizers for plastics 1. Cadmium naturally occurs in the aquatic environment, but is of no known biological use and is considered one of the most toxic metals2. Inhalation of cadmium-containing fumes can result initially in metal fume fever but may progress to chemical pnemonitis, pulmonary edema3, Itai-itai disease, renal abnormalities, including proteinuria and glucosuria and finally death4. Cd has been shown to inhibit enzyme integrity, interfere with RNA and protein synthesis and to complex with DNA. In aquatic systems, cadmium quickly partitions to sediment, but is readily remobilized through a variety of chemical and biological processes4,5. The Indian flying barb, Esomus danricus (HamiltonBuchanan) is an economically important cyprinid fish which mostly inhabits shallow water bodies of Northern India. This fish, owing to its particular habitat, runs the risk of being exposed to water borne toxicants including, Cd. It is very much essential to devise a rapid method to detect the effects of toxicants in various organs of fish and histopathology is one such effective tool6. Amongst

various organs, very little is known about the effects of Cd on the fish intestine which is believed to be the first organ that come into contact with foodborne contaminants7. Also, the intestine is one of the most important sites where food enters and is assimilated. Thus, toxic substances, that enter the intestine, directly affect the vitality of the organism8. Therefore intestine can serve as a potent indicator for water borne Cd. The present study was thus, aimed to determine the histopathological effects of chronic doses of Cd to Indian flying barb intestine. MATERIALS AND METHODS Fishes of similar length (46.77 ± 4.30 mm) and weight (0.86 ± 0.16 g) were collected from unpolluted, freshwater ponds near Assam University campus, Barak valley, South Assam, India9. They were acclimatized under laboratory conditions seven days prior to experimentation. Temperature, pH, hardness and dissolved oxygen under laboratory condition were 29°C, 6.8, 30 mg l1 and 5.5 mg l-1 respectively. A stock solution of actual concentration of Cd was prepared using double distilled water. Serial dilutions of stock solutions were prepared using tap water as per dilution techniques10. Three sub-lethal test concentrations

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DAS & GUPTA, Curr. World Environ., Vol. 8(2), 305-308 (2013)

viz., 636.3, 63.6 and 6.3 µgl-1 Cd were selected for inducing histological changes in fish intestine. Ten fish for each concentration of test chemical were kept separately in three litres of toxicant treated media for 28 days. Food was given during the study period. Test water was renewed every 24 hrs. After 28 days of exposure, fish were sacrificed and intestine was removed immediately and kept in 10% Formalin, as fixative, for 24 h, dehydrated, embedded in paraffin and sections cut at 5 µm thickness and stained with Harris Haematoxylin and Eosin. Changes induced by treatment in the intestinal tissues were photographed and analyzed

by light microscope at 10X eye piece magnification and 40X objective magnification {Olympus (model U-CMAD3) with Camera attachment of Samsung (model SDC-313B)}. The work was done as per the Assam University Ethical guidelines on laboratory animal care.

Fig. 1: T.S of control Intestine of Esomus danricus: (a) epithelium (b) lamina propria (c) muscularis (d) serosa H&E, 400×

Fig. 2: T.S of Intestine of Esomus danricus exposed to 636.3 µg l-1 Cadmium: (a) superficial erosion of mucosa (b) infiltration of lymphocytes, (c) vacuolation. H&E, 400×

Fig. 3: T.S of Intestine of Esomus danricus exposed to 63.6 µg l-1 Cadmium: (a) Mild mucosal erosion (b) infiltration of lymphocytes. H&E, 400×

Fig. 4: T.S of Intestine of Esomus danricus exposed to 6.36 µg l-1 Cadmium: (a) infiltration of lymphocytes. H&E, 400×

RESULTS The intestine of Esomus danricus shows four layers of tissues namely serosa, muscularis, submucosa and mucosa. The outermost serosa is followed by a well developed muscularis

DAS & GUPTA, Curr. World Environ., Vol. 8(2), 305-308 (2013) (longitudinal and circular muscle) embedded in loose connective tissue richly supplied with blood capillaries. It merges with tunica propria of the underlying mucosal coat. The mucosa is raised into several longitudinal folds (Fig.1). In 636.3 µg l-1 of Cd administered E. danricus intestine after 28 days of exposure, superficial erosion of the mucosa, vacuolation and chronic inflammatory cell infiltration were seen. Lamina propria became dense (Fig. 2). For similar exposure duration, 63.6 µg l-1 of Cd exposed intestine showed mild mucosal lesion and infiltration of lymphocytes (Fig. 3). In 6.36 µg l-1 of Cd administered intestine, infiltrations of inflammatory cells (lymphocytes) were observed (Fig. 4). DISCUSSION In the present study, the result of the effect of Cd on the gastrointestinal system of Esomus danricus clearly show that this heavy metal exert toxic effects on the different layers of intestine. The alterations in the intestine of the flying barb were more severe in higher doses. Toxic lesions most common in the intestine of fishes exposed to cadmium chloride include hyperemia, degenerative changes in the tips of villi, loss of structural integrity of mucosal folds, degenerative mucosal epithelium (hyper trophy, vacuolation, hyper-chromasia) necrosis, desquamation of mucosal epithelium, cellular debris, excessive mucus in gut of lumen, necrosis of submucosa and inflammatory infiltration of submucosa11-13. Histopathological change due to Cd, like hypertrophy may lead to increased serum glucose in the intestine, as seen in estuarine teleost fish, and is possibly due to the fulfilment of extra energy requirement under stress condition11. In another study, cadmium exposure caused degenerative changes in the tips of villi like hydropic

307

degeneration, cloudy swelling and necrosis of intestine of Ophiocephalus striatus14. In the intestine of Channa punctatus exposed to mercuric chloride, the cytoplasmic hyperchromasia, edema, loss of pepsinogen granules from chief cells, disintegration of glandular epithelium, desquamation of gastric mucosa in the stomach, hyperemia, degenerative changes in the tips of mucosal folds, hypertrophy and necrosis were observed15. Similarly, intestinal toxic lesions, includes hyperemia, loss of structural integrity of mucosal folds, necrosis, cellular debris, vacuolation in intestine of Mugil auratus exposed to inorganic and organic mercury were also observed in another study 16 . On exposure to another heavy metal, lead, hypersecretion of pepsin, leading to the degradation of tissue protein and increased ammonia and urea excretion by Channa punctutus was observed 17 . Such conditions are possibly due to the extremely adverse effects on stomach of fish due to lead nitrate toxicity. Although, the present study did not include these findings, yet we observed severe erosion of mucosa at highest sublethal exposure dose of Cd, which might hamper the normal gastrointestinal physiology. Besides, profuse infiltration of lymphocytes were observed in flying barb intestine, which was a sign of chronic inflammation. Thus, Indian flying barb intestine was adversely affected by Cd exposure which in turn might have impaired the growth rate of fishes. Hence, it is suggested that this heavy metal in higher dosage will be lethal to fish population in general. ACKNOWLEDGEMENTS We wish to thank Prof Arabinda Das, former HOD, Dept. of Pathology, Silchar Medical College, Assam for providing microscope facility.

REFERENCES 1. 2.

Butterworth, R.G., Metal Toxicology. Springer, New York, p 118. (1995). De Conto Cinier, C. Petit Ramel, M. Faure, R. and Bortolato, M., Cadmium accumulation and metallothionein biosynthesis in Cyprinus carpio tissues. Bull Environ Contam Toxicol, 61: 793–799 (1998). Hayes, A.W., Principles and Methods of

Toxicology. Taylor and Francis Publishing Inc. Philadelphia, fourth edition, (2001). Nogowa, K. Kobayashi, E. Okubo, Y. and Suwazono, Y., Environmental cadmium exposure, adverse effects, and preventative measures in Japan. Biometals, 17: 581-587, (2004). Nordberg, G.F., Cadmium and health in 21st

308

10.

11.

DAS & GUPTA, Curr. World Environ., Vol. 8(2), 305-308 (2013) century-historical remarks and trends for the future. BioMetals 17: 485–489, (2004). Johnson, L.L. Stehr, C.M. Olson, O.P. Myers, M.S. Pierce, S.M. Wigren, C.A. McCain, B.B. and Varanasi, U., Chemical contaminants and hepatic lesions in winter flounder ( Pleuronectes americanus ) from the Northeast Coast of the United States. Environ Sci Technol. 27: 2759-2771, (1993). Braunbeck, T. and Appelbaum, S., Ultrastructural alterations in the liver and intestine of carp Cyprinus carpio induced orally by ultra-low doses of endosulfan. Dis. Aquat. Organ. 36: 183–200, (1999). Hinton, D.E. and Lauren, D.J., Integrative histopathological approaches to detecting effects of environmental stressors on fishes in Biological Indicators of Stress in Fish (Adams, S.M. (Ed.). American Fisheries Symposium 8.American Fisheries Society, Bethesda, Maryland, pp 51–66. (1990). Das, S. and Gupta, A., Biometrics and growth features of Esomus danricus (HamiltonBuchanan), from Barak Valley, South Assam. J. Inland Fish. Soc. India. 41: 81-83, (2009). APHA. Standard methods for the examination of water and wastewater. 21st Edn., Washington, DC: American Public Health Association, AWWA, WPCP, (2005). Gardner, G.R. and Yevich, P.P., Histological and haematological responses of an estuarine fish to cadmium. J. Fish Res. Board,

12.

13.

14.

15.

16.

17.

Canada, 27: 2185-2196, (1970). Gutierrez, M. Establier, R. and Arias, A., Accumulation and histopathological effects of cadmium on the sapo Halobatracus didactylus. Invest. Pesq. 42: 141-154, (1978). Newman, M.W. and MacLean, S.A., Physiological response of the cunner, Tautogolabrus adspersus to cadmium.VI. Histopathology. National Oceanographic and Atmospheric Administration Technical Report. NMFS SSRF 681: 27, (1974). Bais, U.E. and Lokhande, M.V., Effect of Cadmium Chloride on Histopathological Changes in the Freshwater Fish Ophiocephalus striatus (Channa). Intl. J. Zoological Research, 8: 23-32, (2012). Sastry, K.V. and Gupta, P.K., Effects of merucuric chloride on the digestive system of Channa punctutus: A histopathological study. Environ. Res, 16: 270-278, (1978). Establier, R. Gutierrez, M. and Arias, A., Accumalation and histopathological effect of inorganic and organic mercury in the lisa Mugil auratus. Invest. Pesq. 42: 65-80, (1978). Sastry, K.V. and Gupta, P.K., Histopathological and enzymological studies on the effects of chronic lead nitrate intoxication in the digestive system of fresh water teleost Channa punctatus. Environ. Res. 17: 472-479, (1978).

Current World Environment

Vol. 8(2), 309-312(2013)

Chemical Composition and Insecticidal Activity of Essential oil obtained from DCM Extracts of Psoralea corylifolia against Agricultural pest MONIKA GUPTA, ADITI GUPTA and SUDHAKAR GUPTA Department of Chemistry, Lovely Professional University, Phagwara, Punjab -144 806, India http://dx.doi.org/10.12944/CWE.8.2.18 (Received: March 12, 2013; Accepted: May 05, 2013) ABSTRACT The insecticidal activity of essential oils obtained from DCM extracts of Psoralea corylifolia (Fabaceae) against pupa of Epilachna insect was investigated in a series of laboratory experiments. Insecticidal activity was determined at 24 ± 4°C and 68 ± 5% R.H., in dark conditions. The DCM extracts of the dried seeds of the plants were subjected to Column chromatography and the oil obtained was then subjected to hydrodistillation using a Clevenger type apparatus. The major components in these essential oils are identified using GC-MS spectroscopy and their insecticidal activity was tested. The predominant components in the oil of Psoralea corylifolia are toluene, alpha-pinene, L-beta-pinene, beta-pinene, 3-carene, limonene, Gamma terpinene, terpinolene, alpha santolina alcohol, 4-terpineol, Cyclohexene, 1-methyl-4-(1-methyl ethenyl), caryophyllene, alpha caryophyllene, thumbergene. The mortality rate of the agricultural pests was checked against 1%, 5% and 10% conc. of essential oil. The essential oil from Psoralea corylifolia shows strong toxic effect against pupa of Epilachna insect. Finding insecticidal activity is of great importance as using plant extracts as insecticides, are biodegrable and do not leave toxic residues results in better crop and better human health.

Key words: Psoralea corylifolia, Fabaceae, Epilachna insect, Mortality rate.

INTRODUCTION

Psoralea corylifolia L. is an important medicinal plant found in the tropical and subtropical regions of the world. It was found to synthesize diverse phenyl propanoids such as furanocoumarins, isoflavonoids etc 1-2 . These compounds are mainly used to cure leucoderma, leprosy, psoriasis and inflammatory diseases of skin3. The review reveals that it possess important activities like antibacterial, anti-inflammatory, antitumour, hepatoprotective, antioxidant and antihelminthic4. The insecticidal activity is due to the presence of secondary metabolites. The wild population of this medicinally important plant exhibits high mortality of the seedlings, and plant populations decline very quickly due to indiscriminate and illegal collections, and destruction of habitats. Therefore, this species has

been included in the list of endangered plants5-6. Thus the objective of the present study is to find out the insecticidal activity of essential oils against crop pests. The herbal drugs have been used throughout the world have received greater attention in recent times, because of its diversity of curing diseases safety and well tolerated remedies compared to the conventional medicines. A rational approach is being developed to use medicinal plants as an insecticide. The insecticidal activity is due to the presence of active molecules7. MATERIALS AND METHODS Collection and Identification The seeds of the plant Psoralea corylifolia were purchased from an authentic seed shop of

GUPTA et al., Curr. World Environ., Vol. 8(2), 309-312 (2013)

100 100 100 10 10 10 10 10 10 6 10 10 7 10 5 10 10 10 10 1% 5% 10 %

12 7 4

Epilachna sp. Epilachna sp. Epilachna sp.

Controlled experiments have demonstrated no toxicity against the insects. The

Psoralea corylifolia Psoralea corylifolia Psoralea corylifolia

Mc = (Mo-Mc/100-Me) * 100 RESULTS AND DISCUSSION

100 100 100

% Average Mortality Total No. of Insects dead No. of Insects dead (Hours) No. of Insects USED

1. 2. 3

Determination of Insecticidal Activity by Contact toxicity assay The Wheat leaves are taken from the field, washed, dried and then dipped in the respective percentage of essential oils (i.e. 1%, 5%, 10% v/v) for two hours and then 10 insects are allowed to feed on these leaves in each jar under controlled conditions of temperature and humidity. Control dishes with DCM, distilled water and without solvent were performed separately up to 72 hours. Mortality was assessed after 3, 4, 7 and 12 h of the treatment. The calculation of mortality rate was corrected for control mortality according to Abbottâ&#x20AC;&#x2122;s formula9:

% of Extract

Insect Assayed The Epilachna insect were collected from the fields and identified by Entomologist Dr. Sudhakar Gupta of Zoology Department of Lovely Professional University.

Insect

Insecticidal Testing The essential oils obtained were dissolved in distilled water at three different concentrations (1 %v/v, 5 % v/v, 10 % v/v).

Plant Name

GC-MS Analysis of Extracted Oil The oily fraction was analyzed by using Varian 4000 GC-MS/MS unveiled the presence of following components:

Table 1: Toxicity of Psoralea corylifolia essential oils on Agricultural insect

Extraction The seeds were dried on laboratory benches at room temperature for seven days, crushed, soxhlated with DCM to get crude extract which is than subjected to Column Chromatography and oil obtained from 1:1 Pet. Ether: DCM was hydro distilled with Clevenger type apparatus to get essential oil. The essential oil was stored in airtight glassware in refrigerator at 4p C until being used in the treatment8.

% Corrected Mortality

Jammu District and Identified by Dr. Rajesh Manhas of University of Jammu, India.

S. No.

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311

Fig. 1: Various components from Essential Oil of DCM Extracts

Fig. 2: Showing Mortality of pupa of Epilachna insect

results are mentioned below:

ACKNOWLEDGEMENTS

The essential oil from Psoralea corylifolia shows strong toxic effect against Epilachna sp.

The authors are grateful to Dr. Ravikant Khajuria of IIIM Jammu for GC-MS Analysis, Dr. Rajesh Manhas of University of Jammu for identification of plant and LPU for its Lab facilities.

REFERENCES 1.

Abhyankar G., Reddy V.D., Giri C.C., Rao K.V., Lakshmi V.V.S., Prabhakar S., Vairamani M., Thippeswamy B.S. and Bhattacharya P.S.,

Phytochemistry., 66: 2441-2457 (2005). Boardley M., Stirton C.H. and Harborne J.B., Africa. Biochem. Syst. Ecol., 14: 603-613

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3. 4.

GUPTA et al., Curr. World Environ., Vol. 8(2), 309-312 (2013) (1986). Chadha C., Wealth of India. Raw materials, vol. VIII, pp. 296â&#x20AC;&#x201C;298 (1985). Uikey S.K., Yadav A.S., Sharma A.K., Rai A.K., Raghuwanshi D.K. and Badkhane Y., International Journal of Phytomedicine., 2: 100-107 (2010). Jan S., Parween T., Siddiqi T.O. and Mahmooduzzafar, Journal of Environmental Radioactivity., 113: 142-149 (2012).

6. 7.

8. 9.

Baskaran P. and Jayabalan N., Acta Physiol. Plant., 30: 345-351 (2008). Kumar J.A., Rekha T., Devi S.S., Kannan M., Jaswanth A. and Gopal V., J. Chem. Pharm. Res., 2(5): 177-180 (2010). Sukari M.A., Rahmani M., Manas A.R. and Takahashi S., Pertanika., 14(1): 41-44 (1992). Mostafa M., Hossain H., Hossain M.A., Biswas P.K. and Haque M.Z., Journal of Advanced Scientific Research., 3(3): 80-84 (2012).

Current World Environment

Vol. 8(2), 313-318 (2013)

Spectroscopic Methods for the Detection of Organophosphate Pesticides â&#x20AC;&#x201C;A Preview VIJAY KUMAR1, NIRAJ UPADHAY1*, A. B. WASIT1 , SIMRANJEET SINGH2 and PARVINDER KAUR2 1

Department of Chemistry, 2Department of Biotechnology, Lovely Professional University, Punjab, India. http://dx.doi.org/10.12944/CWE.8.2.19 (Received: July 19, 2013; Accepted: August 21, 2013) ABSTRACT

Organophosphate pesticides are the ester forms of phosphoric acid usually considered as secure for agriculture uses due to their relatively fast degradation rates. Organophosphorus pesticides have been extensively used in the area of agriculture to manage insect or pests of a number of economically important crops. Organophosphate pesticides are well-known as the inhibitor of acetylcholinesterase activity, not in insects only, but can also affect the nervous system of other organisms as well as humans. Organophosphorus pesticides are not restricted to anticholinesterase action, but comprise genotoxicity and teratogenicity including other environmental and ecological adverse impact. Such severe health and ecological consequences signify a requirement for a better understanding of the fate of organophosphates in the environment. By kept all these things in mind we have written a review on organophosphorus pesticides. In this review we have previewed the different methods of spectroscopic methods of detection including UV-visible, X-ray, Mass analysis, NMR, electrochemical analysis (sensor based) and FTIR. Among all these mass and electrochemical studies were flourished till date and considered as advanced techniques for the analysis of other pesticides also.

Key words: Organophosphate Pesticides, UV-visible, X-ray, Mass analysis, NMR, electrochemical and FTIR.

INTRODUCTION Organophosphate pesticides (OPs) are the ester forms of phosphoric acid usually considered as secure for agriculture uses due to their relatively fast degradation rates.1Although the degradation of OPs is a linear function of microbial composition, pH, temperature, structural arrangement etc. OPs inhibit acetylcholinesterase (AChE) activity not only in insects only, but can also affect the nervous system of other organisms as well as humans.1-3 Literature data illustrated the OPs persistence in soils years after their application.4 But the reason behind this environmental persistence is not very clear. Pesticides has been transferred to humans through the food chain4,7-9 and number of environmental4-6 and health 10-14

issues have aroused the public concern during last few years. By kept all these views in mind we are going to carve a review on OPs, divided into following parts. Structural Properties of OPs Organophosphate pesticides derived from phosphorus analog PH3 having phosphorus as a core nuclei involved in oxidation states III and V. Basically organophosphate is the general name for esters of phosphoric acid. Hydrolyzed derivatives of phosphorus formal incorporation of additional oxygen atoms gives phosphinic acid (O=PH2OH) and phosphonic (phosphorus) acid [O=PH(OH)2]. Notably, these species may tautomerize between P(V) and P(III), that is, H2P(O)OH to HP(OH)2. Also a tetrahedral structure [O=PH(OH) 2] is more

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established than its isomer phosphonic acid, P(OH)3. This form can be stabilized by coordination with some metals.16 Methods of Detection of OPs The combination of FTIR, NMR and Mass data is often sufficient to determine completely the structure of an unknown molecule. There has been a longstanding interest, first among inorganic chemists, about how organophosphates bind to metals, and next by analytical chemists, about how an adequate detection device can be engineered. Ligand optimization and reporting media continue to be explored in OPs detection efforts that involve various spectroscopic techniques such as UVVisible, FTIR, Mass and NMR spectroscopy. UV- Visible Spectroscopy In the field of pesticides UV-Vis. Spectroscopy play the vital role in the detection and interaction of metal ions with organic ligands i.e. pesticides, especially with transition metal ions. P=O can obscure absorbance. Agents themselves are not significant absorbers or emitters in the UVVis spectral region17 unless they are specifically modified with a fluorescent coumarin-type leaving group. 18 With the inclusion of a photoabsorber material, such as a porphyrin, photocatalytic degradation of acephate and monocrotophos in the presence of TiO2 indicated that the decomposition of acephate begin from the destruction of C-N and P-N bonds. 19-23 The ZnFe 2 O 4 -TiO 2 composite photocatalyst is prepared by sol-gel method and used to degrade acephate successfully.24 Cu(II)Glyphosate complex was studied in tea at pH 5 at absorbance 250 nm.25 A UV-Visible based study to detection of monocrotophos at 490 nm included the effect of temperature and different regent viz. 2, 4, dinitrophenylhydrazine and NaOH at different pH level.26 The photolysis of phorate has been studied as a thin film on a glass surface and in a solution of methanol water (60:40) by ultraviolet light (λ > 290 nm). The rate of disappearance of phorate in the solution show first order kinetics with a rate constant of 4.9 × 10–5 s –1.27 Metal complexes of Fe(III), Al(III), Co(II) and Zn(II) studied by using UV-Spectrophotometer, it observed that the complexes of methylphosphonic acid, formed the M-(CH3PO3)3·3H2O, and aminomethylphosphonic acid, formed the M-OH(NH3CH2PO3)2·H2O. Also

complexes of N-phosphonomethylglycine were prepared and the formula was M-OH(−OOC–CH2– NH2+–CH2–PO32-)·2.25H2O is proposed. UV-Vis. study indicating that the complexes form by the chelation of P=O and N-H bonds by consuming two ligands and two water molecules.28 FTIR Spectroscopy IR spectroscopy is indispensible for many systems mentioned herein; direct access to monitoring the phosphoryl stretch is very useful. Electron-poor ions such as Fe(III) and Cu(II) favor stronger coordination and give [P=O] stretching frequencies concomitantly lower by 30-100 cm-1. Some other functionality, such as perchlorate Cl-O stretches, can obscure P=O absorbance. In OPs from literature following main stretching and bending frequencies observed in different solvents.29,30 OPs having the thio as well as amino salts, for the thio group ν(S-H) and ν(C-S) observed at 2550 and 730 cm-1. Ammonium salts are divided into following parts as per their IR frequencies; these are primary, secondar y and ter tiary ammonium salts. In all these salts ν(C-N) observed between the region 1380 – 1250 cm-1 and ν(N-H) between the 1550 – 1630 cm-1. For the ammonium salt a strong band of ν(N-H) at 1430cm -1 also reported in literature. In the FTIR study of copper complexes, for the yellow complex; [Cu(Ph3P=O)2 Cl2] the ν(P=O) observed at 1142 cm-1. For the dark red complex; [Cu(Ph 3 P=O) 2 Br 2 ] the ν(P=O) observed at 1145,1169 cm-1. For free Ph3P=O, ν(P=O) is 1195 cm-1. These compounds were found to be tetrahedral. The cation moiety Cu(II)-(Me3PO)4 was square planar. Arsenic analogs were yellowbrown ν(P=O) at 840 cm-1 and olive green ν(P=O) at 842 cm-1. Perchlorate species were also obtained, but the C=O stretching bands in the IR spectrum obscured the P=O stretches. In MgI2 complex with diphenylphosphinates; it was found that the PO-C bond, not the P-OC bond, was cleaved.15 In the interaction of Cu(II) with DIMP the IR frequency of ν(P-O) and ν(P-O…H) observed at 1016 and 1206 cm-1.31 Metal complexes of Fe(III), Al(III), Co(II) and Zn(II) studied by using FTIR, it observed that the complexes of methylphosphonic acid, formed the M-(CH3PO3)3·3H2O, and aminomethylphosphonic acid, formed the M-OH(NH3CH2PO3)2·H2O. Also complexes of N-phosphonomethylglycine, were prepared and the formula was M-OH(−−OOC–CH2–

KUMAR et al., Curr. World Environ., Vol. 8(2), 313-318 (2013) NH2+–CH2–PO32-)·2.25H2O is proposed. FTIR study indicating that the complexes form by the chelation of P=O and N-H bonds.28 In the FTIR study of interaction of OPs herbicide glyphosate with Fe(III) in aqueous solution at pH 4, suggests that coordination of Fe(III), or more likely Fe(OH)2+ species, occurs through the phosphonic group, glyphosate shows no evidence of coordinating the metal through the carboxylate anion or the amino group; however, significant changes are observed in the range for the phosphonic group vibrations as expected for metal-phosphonate coordination.32 NMR Spectroscopy Nuclear magnetic resonance (NMR) is a spectroscopic method that is even more important to the structure elucidation than other spectroscopic techniques. Many nuclei may be studied by NMR techniques viz. 13C, 1H, 31P, 15N, and 19F. Any atomic nucleus that possesses either odd mass, odd atomic number split in the radiofrequency region. NMR gives information about the number of magnetically distinct atoms of the type being studied.28 NMR spectroscopy supports many areas of chemistry and science. NMR spectra have found great utility in monitoring reactions and characterizing new compounds and also in detection of OPs and their fragments.33,34 There are numerous nuclei that can be brought to bear in OPs studies, especially the 31P nucleus. Analytes that contain characteristic 13C, 1H, and 31P, as well as 15N and 19F, NMR signals can be probed.35 Other NMR active nuclei and related experiments also are found in the literature. The types of experiments have involved HSQC NMR, as well as magic angle spinning.15 Next, shift reagents can change the phosphorus δ value.15 One early study involved mixtures of (Me2N)3P=O, DMMP, or (MeO)3P=O, in the presence of Be2+ and Al3+ ionic centers and a series of phosphates was treated with Co2+ and Fe3+.36 The species(MeO)3P=O, (EtO)3P=O, and (MeO)2P=O(Me) were all found to give shifts upon binding; also P-H decoupling was observed. With this technique, changes in P-S bonding can be monitored. 37 Variable-temperature 31 P NMR spectroscopy was used in studying resin-based systems with two DMMP adsorption sites, the macro-reticular region and the quaternary ammonium hydroxide ion-exchange sites.38 It was found that DMMP may migrate from one site to

315

another. There is also a report of lanthanide-induced shifts from authors who have also been active in the organophosphonate sensor area.39 An NMR spectroscopic assay was also developed to conveniently determine the purity of live agents of OPs derivatives. 31P NMR spectroscopy can also be used in studies that involve enzymes that degrade agents. Studies that successfully determine discrete cleavage events have used 31P.40 Nuclei other than 13C, 1H, and 31 P NMR also occasionally hold prominence. The 27Al, 113Cd, and 199 Hg nuclei have been utilized in terms of monitoring the adducts and mineralization.15 A 1HNMR study of phorate deals to photodegredation of phorate, indicated the P-S bond destruction. X-ray Diffraction X-ray diffraction is among the unswerving techniques to studies and elucidates the intricacies of metal ligand structure and probable binding possibilities that help open up a casement for future sensing possibilities. In study of [R3P=O—Mn+] moieties (R = alkyl, aryl) and (M = any metal), the mean P=O bond length in [ P=O—Mn+] interactions is 1.48 Å and the mean M—O bond length is 2.33 Å.15 The importance of these structures is that they resemble a deprotonated acid fragment bound through three atoms to one metal center. (CH2)2 could be thought of as holding the place of [P=OMe(OR)-]. This motif is pragmatic with respect to a degraded sample in which the (-OR) has been hydrolyzed off. Metal complexes of Fe(III), Al(III), Co(II) and Zn(II) studied by using XRDSpectrophotometer, it observed that the complexes of methylphosphonic acid formed the M(CH 3PO 3) 3·3H 2O, and aminomethylphosphonic acid, formed the M-OH(NH3CH2PO3)2·H2O. Also complexes of N-phosphonomethylglycine were prepared and the formula was M-OH(-OOC–CH2– NH2+–CH2–PO32-)·2.25H2O is proposed. X - ray study representing that metal ions concerned in octahedral structure.28 Electrochemical Almost all current instrumental techniques that explicitly determine the presence of pesticides are generally exclusive and non-portable, such as FTIR, mass chromatography and NMR spectrophotometer etc. But electrochemical methods are simple, versatile, in terms of controlling

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and altering the behavior of redox materials. Transition metal ions here have vulnerable properties. Such equipment is not too bulky and has a portable device, principally in regards to recent lab-on-a-chip research efforts. Reviews in this area mostly deal with biosensing. Organophosphonate electrochemistry with sarin, (EtO) 2 (EtSCH 2 -CH 2 S)P=O, parathion, and malathion. There were reports of a mercury surface with which polaragram data was recorded. Chemical groups point outward and waters are replaced stepwise in a Cu2+-complex by the surface-active compounds R3P=O. In the late 1990s, there are outstanding electrochemistry papers concerning with organophosphorus hydrolase.41-43 Also, some studies involve the use of phthalocyanines. Thus, this section involves structurally positioned redox active metal ions that do not directly bind with OPs donor atoms. Recently, electronic tongue array, consisting of an eight working electrodes (Au, Pt, Ir, Rh, Cu, Co, Ni, and Ag) was used to detect nerve agent stimulants DCP and DECP in aqueous environments.44,15 Mass Spectrometric The fundamental principles of mass spectroscopy (MS) to determined the mass-tocharge ratio of the molecule by ionizing it by using different procedures. The number of ions with a particular mass-to-charge ratio is plotted as a function of that ratio. The types of MS techniques include MALDI-TOF, GC-MS, ESI, SPAMS, and desorption electrospray. MALDI-TOF and MS-TOF was presented as an effective way of determining widespread emergency events.40 A detection by MS of species that include (RO) 2 P=O(R 1 ), (RO)P=O(R 1 )F, (RO)P=O(R 1 )(SR 2 ), and (R2N)P=O(OR1)(CN).44 MS also provides support for some surface-based studies. A study include the development and inter-laboratory verification of LC–MS libraries for organic chemicals of environmental concern, includes the 129 pesticides in which the monocrotophos and phorate having the m/z at 193, 98 and 75. In the study it was observed that more than 90% data was accepted in both modes.15 The determination of OPs in human blood and water using solid-phase microextraction and gas chromatography with mass (GC-MS) spectrometric detection performed. 45,46 A Multiresidue detection of pesticide in fishery

products was conducted by using the tandem solidphase extraction technique. Study includes more than 50 OPs. Zero recovery was obtained from samples fortified with acephate and monocrotophos and 118.2 and 125.4 % in sample amino-propyl, the maximum label spiked (mg/L) for both is 5.47 Method validation and comparison of acetonitrile and acetone extraction for the analysis of 169 pesticides in soya grain by liquid chromatography– tandem mass spectrometry.45-47 The interesting disulfide derivative [bis (diisopropylaminoethyl) disulfide] was determined from a soil sample (detected at 1 µg per 1.0 g of soil).15 Secondary ionization (IM-TOF-MS) was used in detecting pinacolyl methylphosphonate, diethyl phosphoramidate, and 2-(butylamino) ethanethiol.15 Some reports involve the mention of pesticides: malathion was studied with GC-FID.47 ES-MS was used to support microsynthesis of various O,Odialkyl- N,N-dialkylphosphoramidates to generate a library of mass spectra.48 Additionally the methyl esters of N,N-dialkylaminoethane- 2sulfonic acids, R 2 NCH 2 CH 2 S(O) 2 OCH 3 , were analyzed by GC-EI mass spectroscopy.49 Rapid determination of pesticide residues in Chinese materia medica using QuEChERS sample preparation followed by gas chromatography– mass spectrometry.50 In a minipig model, plasma was used in studying (iPrO(P=O)Me-(OH)) and cyclohexyl-O(P=O)Me(OH). In another study, albumin was studied; peptide fragments of human serum albumin were analyzed in response to chlorpyrifos oxon, dichlorvos, diisopropylfluorophosphate, and sarin.50-53 Complexes of Ni, Co, and Fe, were evaluated for the OPs sensing, but Cu2+ gave the best response indicating that the ligand had to accommodate enough vacancy. Thus, at this early point it was concluded that “copper complexes may adsorb and desorb phosphorus esters in air.”15 CONCLUSION Among the all methods of detections mass and electrochemical based methods are flourished in recent years but there is slow development in FTIR and UV based sensing and detection of OPs which is highlighting a gap in study. Even OPs have the short life time of decomposition but they persist and leach out in soil and environment which is the

KUMAR et al., Curr. World Environ., Vol. 8(2), 313-318 (2013) matter of huge concern, so there is need to develop the new moieties which minimize all these risks and hazards. For the future safeguard, there is need to development of antidotes for intoxication with neurotoxic is one of the most important task, not only because their potential use as chemical warfare

317

defense agents, but also for the treatment of intoxication with organophosphorus pesticides, which are very intensively used in agriculture. There is the need to develop quicker, cheapest, portable methods for agent and pesticides sensing..

REFERENCES 1.

3. 4. 5. 6.

10.

11. 12.

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Isolation and Identification of Fungi Associated with Local Fruits of Barak Valley, Assam BENKEE THIYAM and G.D. SHARMA1 Microbiology Laboratory, Department of Life Science and Bioinformatics, Assam University, Silchar - 788 011, India. 1 Bilaspur University, Village Sendri Chattisgarh - 495 009, India. http://dx.doi.org/10.12944/CWE.8.2.20 (Received: June 28, 2013; Accepted: July 17, 2013) ABSTRACT An investigation was carried to study the fungal diseases of eight selected local fruits in Cachar district and twenty three fungal pathogens were isolated which caused spoilage of fruits. Samples were plated out on potato dextrose agar (PDA) medium and incubated at 28°C±2°C. Resulting growth microscopically screened for fungal species. Aspergillus was commonest fungus found in all fruits during storage of fruits.Other genera like; Acremonium, Alternaria, Aspergillus, Chalaropsis, Cladosporium, Curvularia, Fusariumm, Mucor, Penicillium, Rhizopus, and Trichoderma were common in fruits stored stored in warm and humid condition.

Key words: Fungal pathogens, Fruits, Cachar district

INTRODUCTION Fruits make important diet for human beings. The high concentration of various sugars, minerals, vitamins and amino acids also provide a good platform for the successful growth and survival of various parasitic and saprophytic forms of fungi (Fatima et al., 2010). Fruits are highly perishable and maintain an active metabolism during the storage phase. During post harvest period diseases can affect the quality of fruits. Post harvest deterioration of fruits may take place in any stages viz. storage, transit or trans-shipment, during handling processes required to move the crop from the grower to the whole sale dealer and to retailer and finally to consumers. Different types of fruits are grown in Barak valley but low production of these local fruits could not afford the demand of the consumer as they are highly prone to fungal pathogens due to high moisture content and tropical humid climate. In Assam, actual availability of fruits and vegetables in the market goes down by 35% to 40% due to post harvest losses (State Agricultural

Policy, Assam 2004).There is no published data on pathogenic fungi which cause the post harvest diseases associated with local fruits. Present investigation was carried out to study of various fungal pathogens responsible for the post harvest, decay and deterioration of economically important fruits from the Cachar district of Assam. MATERIALS AND METHODS The area has an average altitude of 2040 m asl; falls between 24°15A N and 25°8A N latitude and 92°15AE and 93°15AE longitude and the climate is a tropical humid type. The average rainfall of the valley is 670.9 mm and the mean monthly temperature ranged between 8.5°-36.2°. During the survey infected fruits viz. Citrus limon, Mangifera indica, Musa paradisiaca, Psidium guajava, Elaeocarpus floribundus, Phyllanthus emblica, Artocarpus heterophyllus, and Carambola sp. were collected from different markets of Cachar district. Eight wild fruits were selected for the study of fruits from wooden packeted storage condition.

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THIYAM & SHARMA, Curr. World Environ., Vol. 8(2), 319-322 (2013) replicates. The plates were incubated in an inverted position at 26-30Â°C for five days.

Storage condition was in a dark room. Mature fruits as well as infected fruits were collected from these sites in a sterile polyethylene bags.

The isolated fungi were identified on the basis of macromorphological and micromorphological characteristics. The following morphological characteristics viz. colony growth, presence or absence of aerial mycelium, colony color, presence of wrinkles and furrows, pigment production etc. were recorded. In some cases the infected tissues were stained by cotton blue and Lactophenol (Mc Lean and Ivimey,1965) and observed under compound microscope. The

Samples were brought to the laboratory in separate sterilized polythene bags. (Alexopoulos,1961 and Malik,1996). The sampled fruits were surface sterilized for 3 min with 1% NaOCl and rinsed in four successive changes of sterile distilled water. The surface sterilized fruits showing symptoms of diseases were then sliced into 2mmÂ˛ pieces and plated on to steriled potato dextrose agar (PDA) in Petri dishes in three

Table 1: Occurrence of fungal pathogens on different fruits of Cachar district Fungi

No. of species

Aspergillus sp. Penicillium sp. Rhizopus sp. Mucor sp. Trichoderma sp. Curvularia sp. Cladosporium sp. Fusarium sp. Chalaropsis sp. Acremonium sp. Alternaria sp.

Fruits

Psidium guajava, Mangifera indica, Artocarpus heterophyllus Phyllanthus emblica,Citrus limon, Elaeocarpus floribundus Artocarpus heterophyllus, Elaeocarpus floribundus, Citrus limon Psidium guajava, Elaeocarpus floribundus Mangifera indica, Phyllanthus emblica Mangifera indica, Psidium guajava Musa paradisiacal, Elaeocarpus floribundus Elaeocarpus floribundus Mangifera indica Mangifera indica

04 03 03 02 02 02 02 02 01 01 01

Table 2: Extracellular enzyme production by different fungi isolated from different fruits Fungal isolates

Samples fruit

Aspergillus flavus Acremonium sp. Alternaria sp. Cladosporium sp. Curvularia sp. Fusarium sp. Penicillium sp. Trichoderma sp.

Pg Mg Ca Pe Ah Mp Cl Ef

Extracellular enzyme activity Amylase Cellulase + + ++ ++ + +

+ ++ + ++ + + -

Pectinase

Xylanase

++ ++ + + -

+ + + ++ -

++ = High activity; + = Moderate activity; - = No activity Pg, Psidium guajava; Mg, Mangifera indica; Ca, Carambola sp.; Pe, Phyllanthus emblica; Ah, Artocarpus heterophyllus; Mp, Musa paradisiaca; Cl, Citrus limon; Ef, Elaeocarpus floribundus

THIYAM & SHARMA, Curr. World Environ., Vol. 8(2), 319-322 (2013) morphological identification of fungal pathogen was based on the morphology of the fungal culture colony or hyphae, the characteristics of the spores and reproductive structures (Barnett and Hunter, 1998). Table 1. shows that twenty three fungal isolates were associated with the fruits of Cachar districts. During the survey of the storage of fruits in the market, number fungal pathogens which causes

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the spoilage of fruits were observed. Acremonium, Alternaria, Aspergillus, Chalaropsis, Cladosporium, Curvularia, Fusarium, Mucor, Penicillium, Rhizopus, and Trichoderma were isolated from fruit samples. Among the fungal isolates Aspergillus was found to be the most dominant ones responsible for extensive damage of fruits in the markets of Cachar district of Southern Assam. Similar results on post harvest fungal pathogens on market storage of fruits were reported by earlier workers (Bhale ,2011 and

Fig. 1: Displaying some fungal isolates from fruits

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Gadgile, 2011).Similarly, Rathod (2010) reported post harvest fungal diseases of some fruits of Marathwada regions of Maharashtra. Fungal isolates showed a diverse enzyme activity in terms of extracellular enzyme production in agar plates assay (Table 2). Fungal isolates, Alternaria sp. and Curvularia sp. showed high produced more amylase activity whereas it was observed in Aspergillus flavus and Cladosporium sp. for pectolytic activity. High xylanase activity was observed in Penicillium sp.. Amylolytic activity was not detected for Cladosporium sp. and Fusarium sp. whereas, Aspergillus flavus, Penicillium sp. and Trichoderma sp. lacked cellulolytic activity. Similarly,

pectinolytic activity was not observed for Acremonium sp., Alternaria sp., Fusarium sp,. Trichoderma sp. and xylanase production was not observed in Acremonium sp., Cladosporium sp., Penicillium sp. and Trichoderma sp. Agar plates enzyme assay had demonstrated that fungal isolates can able to utilize organic compounds which are major components of fruit tissues. This study has provided useful information about the toxigenic fungi associated with local fruits which may affects the human health. Spoiled fruits should be sorted and eliminated to avoid toxins usually associated with the growth of fungi.

REFERENCES 1.

Alexopoulos, C.J., Introductory Mycology, John Wiley and Sons, Inc., New York pp: 229â&#x20AC;&#x201C; 30. (1961). Al-Hindi, R. R., Al-Najada,R.A., and Mohamed, S,A., Isolation and identification of some fruit spoilage fungi: Screening of plant cell wall degrading enzymes. African Journal of Microbiology , 5(4): 443-448 (2011). Barnett, HL, and Hunter, B.B., Illustrated genera of Imperfect Fungi.Burgess Publishing Company, Third edition (1972). Bhale,U.N., Survey of market storage diseases of some important fruits of Osmannabad District (M. S.) India Science Research Reporter 1(2): 88-91 (2011). Das,K., Occurrence of endophytic fungi on sal tree (Shorea robusta G.f.) in forest of Chattisgarh. J. Mycopathological., Res, 49(1): 39-45 (2011). Gadgile,D.P., Kakde,R.B., Rathod,G.M. and Chavan,A.M., Post-harvest fungal diseases of some tropical fruits.Biosci.Disc,. 1(1): 7-

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10 (2010). Garcha,H.S. and Singh,V., Post harvest diseases of fruits in Punjab. Indian Phytopathol. 33(1): 42-47 (1980). Majumdar,V.L. and Pathak, V.N., Incidence of major post harvest diseases of guava fruits in Jaipur markets. Indian Phytopatho. 42: 469 (1989). Malik, B.S., A Laboratory Manual of Veterinary Microbiology, Part III. Pathogenic Bacteriology and Mycology, 4th Ed., pp: 137â&#x20AC;&#x201C; 46 (1996). McClenny, N., Laboratory detection and identification of Aspergillus species by microscopic observation and culture: the traditional approach. Medical Mycology Supplement, 43: S125-S128 (2005). Nelson,S., Rhizopus Rot of Jackfruit. Plant Disease , PD-29 (2005). Rathod, G.M., Survey of Post harvest Fungal diseases of Some fruits from Marathwada regions of Maharashtra, India. Jour. of Ecobiotechnology. 2/6:07-10 (2010).

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Detection of Atrazine and Simazine in Ground Water of Delhi using High Performance Liquid Chromatography with Ultraviolet Detector MOHD ASLAM1, 2, MASOOD ALAM2 and SUMBUL RAIS2* 1

Center of Excellence in Environmental Studies, King Abdulaziz University, Jeddah-21589, Saudi Arabia 2 Department of Applied Sciences and Humanities, Faculty of Engineering and Technology, Jamia Millia Islamia, New Delhi - 110 025, India. http://dx.doi.org/10.12944/CWE.8.2.21 (Received: July 08, 2013; Accepted: August 01, 2013) ABSTRACT Herbicide usage has increased dramatically during the last two decades coinciding with the change in farming practices and increasingly intensive agriculture. This study thus assesses herbicide occurrence in the ground water of Delhi i.e. Atrazine and Simazine herbicide. Liquid-liquid extraction with dichloromethane and methanol as extracting solvents were used. These extracted herbicides were separated and quantified by High Performance Liquid Chromatography (HPLC) with ultraviolet detector. The excellent results were achieved with spiked recoveries of 96.8% and 84.6 % for atrazine and simazine respectively. Analysis shows that the concentration of simazine was higher as compared to atrazine. The results obtained were compared with WHO limit of 0.002 mg/l and USEPA limit of 0.003 mg/l for Atrazine and 0.004 mg/l for Simazine. Highest concentration of atrazine was recorded in the north region of Delhi. Sample from the central Delhi did not reveal contamination from any of the herbicides being monitored. The results indicate that there is need for further work to identify sources and fate of herbicide contaminations. The findings of our investigation contribute to the knowledge of the extent of pollution in the groundwater of Delhi.

Key words: Herbicides, Simazine, Atrazine, Groundwater, HPLC INTRODUCTION Herbicides belong to the class of pesticides that are used to control undesirable or noxious plant growth, generally weeds, in the crop production. These are also used in non-crop areas, where it is necessary to limit the plant growth 1. They are, therefore, also called weed killers. Herbicide usage has increased dramatically during the last two decades coinciding with the change in farming practices and increasingly intensive agriculture2. Herbicides show a wide range of beneficial effects such as improving the plant health, maintaining agro-ecosystems, food supply and other economical advantages3. After application of herbicide on target weeds, the active ingredient is gradually lost as a result of breakdown, evaporation and leaching. The herbicide residue is the amount that remains on

the field after application and usage4. As some herbicides have long residual activity and they persist in the environment for long time. Others have low residual activity and disappear from the environment and produce low residual concentrations5. The identification and quantification of environmental pollutants are important in determining the extent of exposure to these compounds and in evaluating the hazard to humans and wildlife. Environmental pollution by pesticide residues is a major environmental concern due to their extensive use in agriculture and public health programs6. The extensive use of herbicides in agriculture and the high persistence of many of them have required rigorous control of environmental contamination, especially of ground water and drinking water sources 7. Pesticide residues above the tolerance limits (MRL) are a cause of great concern globally as well as nationally. The intensive application of herbicides has resulted

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in the contamination of the atmosphere, ground and waste waters, agricultural products such as wheat, corn, fruits, vegetables, etc. and biological systems8. Pesticides monitoring of water is also possible with rapid and simple methods that use less sophisticated instruments which still provide reliable identification of analytes9. Thermo labile or non-volatile herbicides can be determined only by liquid chromatographic methods such as thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC). Reversed-phase HPLC is widely used in analyses of pesticides with high polarity, low volatility and thermal instability. Because of its higher sensitivity HPLC has been widely applied in the measurement of herbicide residues. Where an MS detector is not available an ultraviolet (UV) or photodiode array detector (PDA) is frequently employed10, 11. Liquid-liquid extraction is frequently used for the isolation of pesticides from water samples and dichloromethane is the most common solvent because it is capable of extracting compounds having a wide range of polarities while its volatility makes sample concentration easy12. The main chemical classes of herbicides include, triazine derivatives containing three heterocyclic nitrogen atoms in the ring structure (atrazine, simazine, etc. as shown in Fig. 1) Atrazine (6-chloro-N2-ethyl-N4-isopropyl1,3,5-triazine-2,4-diamine) is one of the most used pesticides worldwide 13, 14 for pre and post emergence weed control amongst crops of corn, wheat, barley and sorghum. A large amount of applied atrazine and its degradation products remain in the soil even after 16 months, which suggest its potential to contaminate groundwater15. It can also be said that because of their relatively high water solubility symmetric triazine herbicides are agrochemical agents with a potentially high risk of leaching into surface and ground waters16, 17. The Half- life of Atrazine was determined to be approximately 223 days18. According to USEPA the Potential Health Effects from long-term exposure above the MCL (unless specified as short-term) by atrazine is on Cardiovascular system and is also responsible for reproductive problems.

Simazine (6-chloro-N,N’-diethy1(1,3,5)triazine-2,4-diamine) is one of the most popular photosynthesis-inhibiting herbicides. It is used in many countries to kill broad-leaved weeds and also to control vegetation and algae in farm ponds, fish hatcheries, swimming pools, fountains, ornamental fish ponds & water-recirculating cooling towers. Although EU directives have banned the use of simazine on non-cropped land, its use is still permitted on cropped land and in ornamental water (ponds, aquariums)19. It affects the blood on LongTerm Exposure20. MATERIALS AND METHODS Groundwater samples were collected from Delhi. The extraction procedure was undertaken within 72 h. The organic solvents, acetonitirile, methanol, methylenechloride and water, used were HPLC grade and were purchased from E. Merck. Pesticide standards were obtained from Accustandards with a purity of 9599%. All solvents were filtered through Millipore membrane filters (polysulfone membrane with 0.45 µm pore size) before using as mobile phase. The samples were filtered using Millipore syringe filters (polysulfone membrane with 0.45 µm pore size) before injecting in the column. Anhydrous sodium sulfate for the residue analysis, 60-100 mesh was maintained at 300ºC overnight and stored in desiccators till used Individual standard stock solutions of Atrazine and Simazine containing 1mg/ml in methanol were prepared and stored at 4ºC. After the extraction and cleanup procedure, samples were stored in glass container at the recommended temperature. Herbicides were extracted thrice from the groundwater sample (1000 ml) using liquid-liquid partitioning into dichloromethane (50 ml). After extraction, the supernatant was evaporated to dryness and redissolved in 5 ml of Methanol. All samples were cleaned up by passing through anhydrous sodium sulfate (pretreated at 300°C) and eluted with 50 ml methanol. The organic phase thus obtained was evaporated to dryness in a rotary vaccum evaporator completely at a temperature of 40-45°C and then dissolved in methanol for HPLC analysis.

ASLAM et al., Curr. World Environ., Vol. 8(2), 323-329 (2013) Perkin Elmer High Performance Liquid Chromatography (isocratic) having Ultraviolet detector, integrated with Totalchrom software. Stainless steel analytical column Spheri-10 Reverse Phase C18 of 250x4.6 mm i.d., partical size-10µm was used. The samples were injected manually through a Rheodyne injector. Working conditions for HPLC were as follows: The Eluent solvent was acetonitrile/water (60:40, v/v) at Flow rate 1ml min -1, and the injection volume and detection wavelength were 20µl and 235 nm, respectively. The identification of target pesticides were accomplished on the basis of the retention times of the analytes. RESULTS AND DISCUSSION Contamination of surface, ground and drinking water by the studied herbicides has been reported in many countries 1, 20, 21, 22, 23 .The compounds are separated with good resolution and sharp peak by gradient HPLC using a simple mobile phase containing acetonitrile:water (60:40, v/v). The extraction procedure employed resulted recoveries of 96.8% and 84.6 % for atrazine and simazine respectively. Several mobile phase flow rates (0.5 – 2 ml/min) were evaluated. The best separation was achieved using a flow rate of 1.0 ml/min. Fig. 2a & 2b shows the chromatogram referring to HPLC analysis of atrazine and simazine herbicides respectively. Fig. 3 is the chromatogram obtained by analyzing analytical standard where as spiked water chromatogram is shown in Fig. 4. Fig. 5

represents the chromatograms for the water samples from the region of interest (Delhi). Analysis of the results on table 2 shows that the concentration of simazine was higher as compared to atrazine. Maximum Contaminant Level Goal (MCLG), the level of a contaminant in drinking water below which there is no known or expected risk to health, allow for a margin of safety and are non-enforceable public health goals. Maximum Contaminant Level (MCL) is however the highest level of a contaminant that is allowed in drinking water. The MCLG and MCL values for Atrazine and Simazine are 0.003 and 0.004 mg/l respectively24. In the present study, highest concentration of atrazine was recorded in the north region of Delhi. Sample from the central Delhi did not reveal contamination from any of the herbicides being monitored. The atrazine was detected in 45% water samples analysed where as 35 % samples exceeded the WHO and USEPA limit. Simazine was detected in 85% analysed samples with 50% samples exceeding the limit according to USEPA and 55% exceeding the WHO limit (Table 2). The total mean concentrations of atrazine and simazine ranged from 0.00072 to 0.0173 mg/l and 0.00091 to 0.04097 mg/l respectively. The findings of our investigation contribute to the knowledge of the extent of pollution in the groundwater of Delhi. The total mean concentration of atrazine ranged from 0.00072 to 0.0173 mg/l where as 0.00091 to 0.04097 mg/l are recorded as the mean concentration of simazine. It is important to monitor the pesticides and see whether they have caused contamination in the hydrological system

Table 1:Physicochemical properties of atrazine and simazinea Property

Atrazine Value

Simazine Value

Mol. Wt. Melting point Density Water solubility pKa (Acid dissociation constant) Log Kow (Log octanol–water partition coefficient) Vapour pressure

215.7 175–177 °C 1.187 g/cm3 at 20 °C 33 mg/l at 20 °C 1.70 (base)

201.72 25–227 °C 1.302 g/cm3 at 20 °C 6.2 mg/l at 20 °C 1.62 (base)

2.5 40 × 10"6 Pa at 20 °C

2.1 8.1 × 10-4 Pa at 20 °C

data obtained from Tran et al., 2007

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Table 2. Herbicide concentrations in the water samples of Delhi with statistical data Sample No.

Atrazine (ppm)

Simazine (ppm)

Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10 Sample 11 Sample 12 Sample 13 Sample 14 Sample 15 Sample 16 Sample 17 Sample 18 Sample 19 Sample 20 Average Maximum Minimum Std Deviation Average Deviation Variance population Median Mode USEPA Limit WHO Limit % of samples exceeding USEPA limit % of samples exceeding WHO limit

ND ND 0.0098 0.017316 0.00098 0.00072 0.00715 ND 0.010651 ND 0.009315 ND 0.00462 ND ND ND 0.00711 ND ND ND 0.0033831 0.017316 0 0.00508707 0.00422803 2.45844E-05 0 0 0.003 ppm 0.002 ppm 35 35

0.004326 0.022492 0.000912 0.0098 0.004008 0.00154 0.0014 ND 0.0106 ND 0.006255 ND 0.010714 0.022415 0.040979 0.001722 0.0017 0.013587 0.015409 0.009714 0.00887865 0.040979 0 0.010350463 0.007580215 0.000101775 0.0052905 0 0.004 ppm 0.002 ppm 50 55

ND : Not Detected

Fig. 1: Structure of Atrazine and Simazine

ASLAM et al., Curr. World Environ., Vol. 8(2), 323-329 (2013)

Fig. 2(a): HPLC Chromatogram obtained by analyzing Atrazine Standard.

Fig. 2(b): HPLC Chromatogram obtained by analyzing Simazine Standard

Fig. 3: HPLC Chromatogram obtained by analyzing Standard Simazine & Atrazine

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Fig. 4: HPLC Chromatogram obtained by analyzing Spiked water Sample

Fig. 5: HPLC Chromatogram a) Showing Atrazine concentration more than Simazine. b) Showing Simazine concentration more than Atrazine. c) Showing no peak in the interested area this will also help to take necessary actions in minimising the chances of further deterioration and

prevent exposure of large population of Delhi from health hazards due to chemical contamination.

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Guzzella L, Pozzoni F and Giuliano G., Herbicide contamination of suficial groundwater in Northern Italy, Environ Poll, 142: 344-353 (2006). Readman J. W, Albanis T. A, Barcelo D, Galassis S, Tronczynski J and Gabrielides G.P., Herbicide contamination of Medeterranean Estuarine waters: Results

from a MED POL pilot survey, Marine Poll. Bulletin, 26(11): 613-619 (1993). Cserhati T, Forgacs E, Deyl Z, Miksik I and Eckhardt A., Chromatographic determination of herbicide residues in various matrices. Biomed. Chromatogr, 18: 350-359 (2004). Afful S., Thin layer chromatographic studies

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