Variations in particulate matter over Indo-Gangetic Plains and Indo-Himalayan Range during four field campaigns in winter monsoon and summer monsoon: Role of pollution pathways

Abstract

Both in-situ and space-borne observations reveal an extremely high loading of particulates over the Indo-Gangetic Plains (IGP), all year around. With a burgeoning population and combustion sources (fossil fuels (FFs) and biofuels (BFs)) in close proximity to each other, the IGP is widely regarded as a hotspot for anthropogenic aerosol emission in South Asia. The deteriorating air quality over this region, particularly during winters, is a cause of major concern, since the pollutants undergo long range transport from their source regions to the Indo-Himalayan Range (IHR), Bay of Bengal (BoB) and other remote areas, polluting their pristine atmospheric conditions. Seasonal reversal in winds over the Indian mainland leads to an outflow of continental pollutants into the BoB during winters and a net advection of desert dust aerosols into the IGP from southwest Asia (SW-Asia), northwest India (NW-India) and northern Africa (N-Africa) during summers. Through the course of this study, four observational campaigns were conducted for sampling the ambient PM2.5 and PM10 during winter and summer seasons of 2014-2015, at multiple locations (18 sites) in the IGP, IHR, and semi-arid/arid sites towards their south and west, in order to accurately determine the inter-seasonal and inter-annual changes in the aerosol loading at the sites. We have also utilized data from Moderate Resolution Imaging Spectroradiometer (MODIS) on-board Earth Observing System (EOS) Terra satellite for estimating the columnar Aerosol Optical Depth at 550 nm (AOD(550)) and data from EOS Terra and Aqua satellites for discovering openly burning fires in the vicinity of sampling sites. Determination of the major source regions and key transport pathways during both seasons have also been attempted, using back-trajectory cluster analyses, as well as receptor models such as PSCF and CWT. (C) 2017 Elsevier Ltd. All rights reserved.