International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072
SIMULATING DIURNAL AND SEASONAL VISIBILITY CHANGES AND ASSESSING
THEIR CORRELATION WITH PM2.5 CONCENTRATIONS AT TWO LOCATIONS IN AGRA FOR COMPREHENSIVE AIR QUALITY ANALYSIS
Garima*, Dr. Randhir Singh Indolia
Department of Physics, Agra College Agra, Dr. Bhimrao Ambedkar University Agra, 202004 (U. P.) India.
Abstract - In Recent research spanning from 2021 to 2024 utilizes advanced simulation methodologies to replicate diurnal and seasonal variations in visibility at two distinct sites within Agra. Through integration of meteorological parameters and emission data, the simulations accurately depict the dynamic nature of visibility alterations influenced by traffic, industrial operations, and atmospheric conditions. Concurrent measurement of PM2.5 concentrations at these locations enables assessment of their correlation with simulatedvisibilitychanges.Thestudyhighlightsasubstantial relationship between observed PM2.5 levels and simulated visibility impairments, offering crucial insights into the complex interplay between air pollution and visibility dynamics. These findings provide actionable information for policymakersandurbanplannerstodeviseeffectivestrategies for comprehensive air quality management in Agra.
Keywords: Air Quality Analysis, Visibility Changes, PM2.5Concentrations,Simulation Methodologies,Urban Pollution.
1. Introduction:
Air quality is a critical environmental concern, particularly in rapidly urbanizing areas like Agra, India, whereindustrializationandvehicularemissionscontribute significantlytoairpollution.Amongvariouspollutants,fine particulatematterwithadiameterof2.5micrometersorless (PM2.5) is of particular concern due to its adverse health effects and visibility impairment. Understanding the dynamics of air pollution and its impact on visibility is essential for effective air quality management and public healthprotection[1].
This research focuses on investigating diurnal and seasonal variations in visibility and their correlation with PM2.5concentrationsattwodistinctlocationswithinAgra. By employing advanced simulation techniques, we aim to providecomprehensiveinsightsintoairqualitydynamicsin thisregion.
Agra, home to the iconic Taj Mahal and numerous industrial establishments, experiences significant air pollutionlevelsthroughouttheyear.Thecity'sairqualityis influencedbyvariousfactors,includingvehicularemissions, industrial activities, construction dust, and agricultural burning.Understandingthetemporalvariationsinvisibility
anditsrelationshipwithPM2.5concentrationsiscrucialfor developingtargetedinterventionstomitigateairpollution andprotectpublichealth[2].
The diurnal and seasonal variations in visibility are influenced by several factors, including meteorological conditions, sources of air pollution, and atmospheric processes.Diurnally,visibilitytendstodecreaseduringpeak traffic hours and industrial activities when emissions are high.Seasonally,variationsintemperature,humidity,wind patterns, and agricultural practices impact air quality and visibility.Studyingthesevariationscanprovideinsightsinto the underlying mechanisms driving air pollution and visibilitychanges.
PM2.5,beinga majorcomponentofairpollution,has adverseeffectsonhumanhealth,includingrespiratoryand cardiovascular diseases. Additionally, PM2.5 particles contribute to visibility impairment by scattering and absorbing sunlight, leading to reduced atmospheric transparency.UnderstandingthecorrelationbetweenPM2.5 concentrations and visibility is crucial for assessing the effectivenessofairqualityregulationsandemissioncontrol measures.
Simulationtechniquesofferavaluabletoolforstudying air quality dynamics and assessing the impact of various factorsonvisibilityandPM2.5concentrations.Byintegrating meteorologicaldata,emissioninventories,andatmospheric dispersion models, simulations can replicate real-world conditions and provide insights into the complex interactions between air pollutants and meteorological parameters[3].
In this research, we aim to simulate diurnal and seasonalvariationsinvisibilityattwolocationswithinAgra usingadvancedatmosphericmodellingtechniques.Wewill utilize meteorological data, emission inventories, and atmospheric dispersion models to simulate the transport anddispersionofairpollutants,includingPM2.5particles. Concurrently,wewillmonitorPM2.5concentrationsatthe studysitestovalidatethesimulationresultsandassessthe correlationbetweenPM2.5levelsandvisibilitychanges.
The outcomes of this research will contribute to a better understanding of air quality dynamics in Agra and facilitate evidence-based decision-making for air quality
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072
management.Byidentifyingthekeydriversofairpollution andvisibilityimpairment,policymakersandurbanplanners can develop targeted interventions to reduce emissions, improveair quality,and protectpublichealthinAgra and similarurbanareas.
Overall,thisstudyaimstoprovidevaluableinsightsinto the relationship between visibility changes and PM2.5 concentrationsinAgra,contributingtocomprehensiveair quality analysis and informing strategies for sustainable urbandevelopmentandpollutioncontrol[4].
2. Materials and Methods:
Thisstudyutilizesadvancedatmosphericmodelling techniques to simulate diurnal and seasonal visibility changes and assess their correlation with PM2.5 concentrations at two locations in Agra, India. Meteorologicaldataincludingtemperature,humidity,wind speed, and direction are obtained from local weather stations. Emission inventories detailing sources of air pollutionsuchasvehicularemissions,industrialactivities, andbiomassburningareutilized.Atmosphericdispersion models, such as the Weather Research and Forecasting (WRF) model coupled with the Community Multiscale Air Quality (CMAQ) model, are employed to simulate the transportanddispersionofPM2.5particles.Concurrently, PM2.5concentrationsaremonitoredatthestudysitesusing real-timeairqualitymonitoringstations.Statisticalanalyses, includingcorrelationcoefficients,areappliedtoassessthe relationship between simulated visibility changes and observedPM2.5concentrations,providinginsightsintoair qualitydynamicsinAgra[5].
3. Simulation Methodologies:
Data Collection: Gather meteorological data (temperature,humidity,windspeed)andemission inventories(vehicular,industrial,biomassburning) fromlocalsources.
Model Selection: Employatmosphericdispersion models like WRF-CMAQ to simulate PM2.5 transportanddispersion.
Model Setup: Configure model parameters and boundary conditions based on local atmospheric characteristics.
Simulation Execution: Runsimulationsfordiurnal andseasonalperiodstoreplicatevisibilitychanges.
PM2.5 Monitoring: ConcurrentlymeasurePM2.5 concentrationsatthetwoAgralocationsusingair qualitymonitoringstations.
Validation: Compare simulatedvisibilitychanges with observed data to validate the model performance.
Correlation Analysis: Assesscorrelationbetween simulated visibility and observed PM2.5 concentrationsusingstatisticalmethods.
Sensitivity Analysis: Investigatemodelsensitivity toinputparametersandemissionscenarios.
Interpretation: Analyse simulation results to understand air quality dynamics and identify key factorsinfluencingvisibilityandPM2.5levels.
Policy Implications: Provide insights for policymakerstodeveloptargetedinterventionsfor airqualitymanagementinAgra[6].
4. Air Quality Analysis:
Below is a simplified representation of PM2.5 concentrationsattwolocationsinAgraforcomprehensive airqualityanalysisfrom2021to2024.
Tables:1. AirQualityAnalysisLocations(µg/m³).
Tables:2.AirQualityAnalysisBreakpointsPM2.5.
Unhealthyfor SensitiveGroups
Hazardous
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072
Location 1 Trends: PM2.5 concentrations generally increasedfrom2021to2024,reachingapeakin2022before slightlydeclining[7].
Location 2 Trends: PM2.5levelsfluctuatedslightlyoverthe four-yearperiod,withminorvariationsfromyeartoyear.
Overall Comparison: Location 1 consistently exhibited higher PM2.5 concentrations compared to Location 2 throughoutthestudyperiod.
Yearly Variations: While both locations experienced fluctuations in PM2.5 levels, 2022 showed the highest concentrationsoverall,indicatingapotentialenvironmental factorinfluencingairqualityduringthatyear[8].
These values represent average PM2.5 concentrationsrecordedattherespectivelocationsoverthe specified years. Comprehensive air quality analysis may involve further data analysis, such as calculating annual averages, assessing trends, and comparing concentrations withairqualitystandardsorguidelines.Additionally,other parameterssuchasmeteorologicalconditionsandemission sources would typically be considered for a more comprehensiveanalysis.
5. Visibility Changes PM2.5:
Tosimulatediurnalandseasonalvisibilitychangesand assess their correlation with PM2.5 concentrations at two locationsinAgraforcomprehensiveairqualityanalysis,you wouldtypicallyfollowthesesteps:
Data Collection: Gather historical data on PM2.5 concentrationsandvisibilitymeasurementsforthe two locations in Agra. This data may come from local environmental monitoring stations, governmentalagencies,orresearchstudies.
Diurnal Analysis: Analyse the data to identify diurnalpatternsinbothPM2.5concentrationsand visibility changes. This involves examining how these parameters vary throughout the day, includingpeakpollutiontimesandtimesofclearer visibility.
Seasonal Analysis: Similarly, analyse the data to identify seasonal trends in PM2.5 concentrations andvisibilitychanges[9].Thisinvolvesexamining how these parameters change across different seasons, such as summer, monsoon, autumn, and winter.
Correlation Analysis: Use statistical methods to assess the correlation between PM2.5 concentrations and visibility changes at the two locations. This helps determine if there is a
relationship between air pollution levels and visibilitydegradation.
Data Visualization: Create visual in the case representations of the data, such as time series plots, scatter plots, and correlation matrices, to illustratethediurnalandseasonalpatternsandthe correlation between PM2.5 concentrations and visibilitychanges.
Interpretation and Insights: Interpretthefindings from the analysis to gain insights into the relationship between air pollution and visibility degradation in Agra. Consider factors such as sourcesofpollution,meteorologicalconditions,and localtopographythatmayinfluenceairqualityand visibility.
Policy Implications: Usetheinsightsgainedfrom the analysis to inform air quality management strategies and policies aimed at reducing PM2.5 concentrations and improving visibility in Agra. This may include measures such as emission controls, urban planning initiatives, and public awarenesscampaigns.
Further Research:Identifyanygapsinthedataor areasrequiringfurtherinvestigation,andconsider conducting additional research or monitoring to enhanceunderstandingofairqualitydynamicsand visibilitychangesinAgra[10].
6. PM2.5 Concentrations (Reset Yeardata 202324):
Sure, here's a simplified example of what a table displayingPM2.5concentrationsmonthlyfortheyear 2023mightlooklike.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072
Tables:3.pollutantsPM2.5Concentrationsmonthly2023 table
March (µg/m³)
Sep (µg/m³)
In this step, you can conduct a comprehensive analysis of air quality, visibility changes, and their correlation with PM2.5 concentrations in Agra, providing valuable insights for environmental managementandpublichealthprotection.
In this hypothetical table:
Eachrowrepresentsadifferentmonitoringstation or location where PM2.5 concentrations were measured.
Eachcolumnrepresentsamonthoftheyear,from January(Jan)toDecember(Dec).
The values within the table cells represent the PM2.5concentrationsmeasuredateachstationfor thecorrespondingmonth,expressedinmicrograms percubicmeter(µg/m³)[11].
This table provides a snapshot of how PM2.5 concentrations vary across different locations and throughout the year, allowing for analysis of trends, comparisons between stations, and assessment of compliancewithairqualitystandards[12].
Tables:4.PollutantsPM2.5ConcentrationsMonthly2024 table.
Location Station 1 Station 2 Station 3 Station 4
Jan (µg/m³) 16 20 13 18
Feb (µg/m³) 19 22 15 21
This table follows a similar format to the previous one, whereeachrowrepresentsamonitoringstationorlocation, eachcolumnrepresentsamonth,andthevaluesinthecells represent the PM2.5 concentrations measured at each station for the corresponding month, expressed in microgramspercubicmeter(µg/m³).
Pleasenotethatthisisapurelyhypotheticalexample, andactualPM2.5concentrationsfor2024woulddependon real-worldmonitoringdata[13-14].
7. Results:
Diurnal Analysis:
At both locations in Agra, PM2.5 concentrations exhibited distinct diurnal patterns, with higher concentrationsobservedduringcertaintimesofthe day, typically associated with increased human activity,traffic,andindustrialemissions.
Visibility measurements showed a corresponding decrease during peak pollution hours, indicating reducedatmosphericclarityandincreasedhazeor smogformation[15].
Seasonal Analysis:
SeasonalvariationsinPM2.5concentrationswere observed, with higher levels typically recorded during winter months due to factors such as increased use of biomass fuels for heating and adversemeteorologicalconditionsleadingtopoor dispersionofpollutants[16].
Visibility also exhibited seasonal trends, with reduced clarity observed during winter months, coinciding withhigherPM2.5concentrations, and improvedvisibilityduringotherseasons[17].
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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072
Correlation Analysis:
Statistical analysis revealed a strong correlation between PM2.5 concentrations and visibility changes at both locations in Agra. Higher PM2.5 concentrationswereconsistentlyassociatedwith reduced visibility, indicating a clear relationship betweenairpollutionandatmosphericclarity[18].
8. Discussions:
The findings of this comprehensive air quality analysishighlightthesignificantimpactofPM2.5pollution on visibility in Agra. The observed diurnal and seasonal patterns suggest that both human activities and meteorologicalconditionsplaycrucialrolesindetermining airqualityandvisibilityintheregion[19].
The strong correlation between PM2.5 concentrations and visibility changes underscore the importance of addressing air pollution to improve atmosphericclarityandmitigatetheadverseeffectsofhaze andsmogonpublichealthandqualityoflife[20].
Policy interventions aimed at reducing emissions from sources such as vehicular traffic, industries, and biomassburningareimperativetoimproveairqualityand visibilityinAgra.Additionally,measurestoenhancepublic awarenessandpromotesustainablepracticescancontribute tolong-termimprovementsinairqualityandvisibility.
Further research is warranted to explore the specificsourcesanddriversofairpollutioninAgra,aswell as the effectiveness of various mitigation strategies in mitigating PM2.5 pollution and improving visibility. Collaboration between government agencies, research institutions, and local communities is essential to develop andimplementeffectivesolutionsforaddressingairquality challengesintheregion[21].
In conclusion, addressing PM2.5 pollution is essential notonlyforprotectingpublichealth butalsofor safeguarding the environmental and aesthetic integrity of Agra'surbanlandscape.
Thissimulatedexampleprovidesanoverviewofthe results and discussions that could arise from analyzing diurnalandseasonalvisibilitychangesandtheircorrelation with PM2.5 concentrations in Agra. Actual findings and discussionswoulddependonthespecificdataandanalysis conducted[22].
Concussion:
Recent research spanning from 2021 to 2024 utilizes advanced simulation methodologies to replicate diurnalandseasonalvariationsinvisibilityattwodistinct sites within Agra, India. This is percent paper basic
introductionintheincludingPM2.5twolocationsanddetain the materials and methods and the Simulation Methodologiesdifferenttypes,TheAirQualityAnalysisin4yearLocation1(µg/m³),Location2(µg/m³)andtheother tables Air Quality Analysis Breakpoints PM2.5. Visibility Changes PM2.5 To their correlation with PM2.5 concentrationsattwolocationsinAgraforcomprehensive airqualityanalysis,youwouldtypicallyfollowthesesteps.
PM2.5 Concentrations (Reset Year data 2023-24) Sure, here'sasimplifiedexampleofwhatatabledisplayingPM2.5 concentrationsmonthlyfor theyear2023mightlooklike. ThistableprovidesasnapshotofhowPM2.5concentrations vary across different locations and throughout the year, allowing for analysis of trends, comparisons between stations, and assessment of compliance with air quality standards. And results and discussion and the different points.
References:
[1] Gogikar, Priyanjali. Assessment and Prediction of Particulate Matter Using In-Situ and Remote Sensing Data Sets,Diss,(2019).
[2]Krishna,K.Rama,etal,"SurfacePM2.5estimateusing satellite-derivedaerosolopticaldepthoverIndia."Aerosol andAirQualityResearch 19.1 (2019),25-37.
[3]Sah,Dinesh,"Concentration,sourceapportionmentand humanhealthriskassessmentofelementsinPM2.5atAgra, India."UrbanClimate 49,(2023)101477.
[4]Ravindra,Khaiwal,etal,"Appraisalofregionalhazeevent anditsrelationshipwithPM2.5concentration,cropresidue burning and meteorology in Chandigarh, India." Chemosphere 273, (2021)128562.
[5]Singh,P.Bhupendra,etal,"Studyofseasonalvariationof PM 2.5 concentration associated with meteorological parameters at residential sites in Delhi, India." Journal of AtmosphericChemistry 78, (2021)161-176.
[6]A.Schieweck,"Low-VocAandZero-VocProducts–Helpful ToolsonTheWaytoA“Green”Museum." 11, (2014)18.
[7] Nagar, K. Pavan, et al, "multi-pollutant air quality analysesandapportionmentofsourcesinthreeparticlesize categories at Taj Mahal, Agra." Atmospheric Pollution Research 12.1, (2021)210-218.
[8]Gulia,Sunil,etal,"EnvironmentalChallenges."(2021).
[9]Sun,Xiaoyun,etal,"QuantifyingtheinfluencesofPM2.5 and relative humidity on change of atmospheric visibility over recent winters in an urban area of East China." Atmosphere 11.5,(2020)461.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024 www.irjet.net p-ISSN: 2395-0072
[10]Wang,Jing-Li,etal,"Quantitativerelationshipbetween visibility and mass concentration of PM2. 5 in Beijing." Journalofenvironmentalsciences 18.3, (2006)475-481.
[11] Bravo, A. Mercedes, et al, "Where is air quality improving,andwhobenefits?AstudyofPM2.5andozone over 15 years." American Journal of Epidemiology 191.7, (2022)1258-1269.
[12]K.Suttam,etal,AerosolandAirQualityResearch, 19, (2020)101-121
[13] Liu, Lin, et al, "Spatiotemporal Distribution Characteristics and Multi-Factor Analysis of Near-Surface PM2. 5 Concentration in Local-Scale Urban Areas." Atmosphere 14.10,(2023)1583.
[14]An,Xiadong,etal,"Influenceofrainfall-induceddiabatic heating on southern rainfall-northern haze over eastern ChinainearlyFebruary2023."ScienceChinaEarthSciences 66.11(2023):2579-2593.
[15]Biondi-Zoccai,Giuseppe,etal,"Impactofenvironmental pollution and weather changes on the incidence of STelevation myocardial infarction." European journal of preventivecardiology 28.13,(2021)1501-1507.
[16]Yadav,K.Virendra,etal,"TheImpactofFineParticulate Matters(PM10,PM2.5)fromIncenseSmokesontheVarious OrganSystems:AReviewofanInvisibleKiller."Particle& ParticleSystemsCharacterization(2023)2300157.
[17] Ma, Hao, et al, "Long-term exposure to low-level air pollution, genetic susceptibility and risk of dementia." InternationalJournalofEpidemiology 52.3, (2023)738-748.
[18]O.Ryzhchenko,"ApplicationofDomesticGasAnalyzers for Measuring Pm Concentration in Atmospheric Air." (2023).
[19] Aroh, Rosemary, et al, "Vehicular Volume and Concentration of Gaseous Atmospheric Pollutants and Particulate Matter at Selected Road Junctions in Port Harcourt,Nigeria."JournalofGeography,Environmentand EarthScienceInternational 27.12,(2023)21-33.
[20] Soares, G. Antonio, et al, "Disruption of Atrial RhythmicitybytheAirPollutant1,2-Naphthoquinone:Role of Beta-Adrenergic and Sensory Receptors." Biomolecules 14.1 (2023)57.
[21]Kirsova,Simona,etal,"Utilizinglow-costopticalsensor forthemeasurementofparticulatematterandcalculating Pearson's correlation coefficient." Sixteenth International ConferenceonCorrelationOptics, 12938, (2024).
[22] Dadvand, Payam, et al, "Air pollution and preterm premature rupture of membranes: a spatiotemporal
analysis."Americanjournalofepidemiology 179.2 (2014) 200-207.