Abstract
The variation in particulate mass and particulate types (PM2.5 and PM10) with respect to local/regional meteorology was analyzed from January to December 2014 (n = 104) for an urban location over the middle Indo-Gangetic Plain (IGP). Both coarser (mean ± SD; PM10 161.3 ± 110.4 μg m−3, n = 104) and finer particulates (PM2.5 81.78 ± 66.4 μg m−3) revealed enormous mass loading with distinct seasonal effects (range: PM10 12–535 μg m−3; PM2.5 8–362 μg m−3). Further, 56% (for PM2.5) to 81% (for PM10) of monitoring events revealed non-attainment national air quality standard especially during winter months. Particulate types (in terms of PM2.5/PM10 0.49 ± 0.19) also exhibited temporal variations with high PM2.5 loading particularly during winter (0.62) compared to summer months (0.38). Local meteorology has clear distinguishing trends in terms of dry summer (March to June), wet winter (December to February), and monsoon (July to September). Among all the meteorological variables (average temperature, rainfall, relative humidity (RH), wind speed (WS)), temperature was found to be inversely related with particulate loading (rPM10 −0.79; rPM2.5 −0.87) while RH only resulted a significant association with PM2.5 during summer (rPM10 0.07; rPM2.5 0.55) and with PM10 during winter (rPM10 0.53; rPM2.5 0.24). Temperature, atmospheric boundary layer (ABL), and RH were cumulatively recognized as the dominant factors regulating particulate concentration as days with high particulate loading (PM2.5 >150 μg m−3; PM10 >260 μg m−3) appeared to have lower ABL (mean 660 m), minimum temperature (<22.6 °C), and high RH (∼79%). The diurnal variations of particulate ratio were mostly insignificant except minor increases during night having a high wintertime ratio (0.58 ± 0.07) over monsoon (0.34 ± 0.05) and summer (0.30 ± 0.07). Across the region, atmospheric visibility appeared to be inversely associated with particulate (rPM2.5 −0.84; rPM10 −0.79) for all humid conditions, while at RH ≥80%, RH appeared as the most dominant factor in regulating visibility compared to particulate loading. The Lagrangian particle dispersion model was further used to identify possible regions contributing particulate loading through regional/transboundary movement.
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Acknowledgements
Present submission is financially supported by University Grants Commission, New Delhi (F. No. 41-1111/2012, SR), and the Science and Engineering Research Board, Department of Science and Technology, New Delhi (F. No. SR/FTP/ES-52/2014). Meteorological data from wunderground.com is acknowledged. Ground level particulate data and meteorological data at Varanasi were courtesy of the Central Pollution Control Board and the Indian Meteorological Department, respectively. Authors also acknowledge the NOAA-ARL for the HYSPLIT transport model and the NCEP/NCAR Reanalysis team for providing synoptic meteorological data. The guidance and cooperation provided by the Director, IESD-BHU, is also acknowledged.
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Murari, V., Kumar, M., Mhawish, A. et al. Airborne particulate in Varanasi over middle Indo-Gangetic Plain: variation in particulate types and meteorological influences. Environ Monit Assess 189, 157 (2017). https://doi.org/10.1007/s10661-017-5859-9
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DOI: https://doi.org/10.1007/s10661-017-5859-9