A Satellite-Based High-Resolution (1-Km) Ambient Pm2.5 Database For India Over Two Decades (2000-2019): Applications For Air Quality Management

REMOTE SENSING(2020)

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摘要
Fine particulate matter (PM2.5) is a major criteria pollutant affecting the environment, health and climate. In India where ground-based measurements of PM2.5 is scarce, it is important to have a long-term database at a high spatial resolution for an efficient air quality management plan. Here we develop and present a high-resolution (1-km) ambient PM2.5 database spanning two decades (2000-2019) for India. We convert aerosol optical depth from Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved by Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm to surface PM2.5 using a dynamic scaling factor from Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) data. The satellite-derived daily (24-h average) and annual PM2.5 show a R-2 of 0.8 and 0.97 and root mean square error of 25.7 and 7.2 mu g/m(3), respectively against surface measurements from the Central Pollution Control Board India network. Population-weighted 20-year averaged PM2.5 over India is 57.3 mu g/m(3) (5-95 percentile ranges: 16.8-86.9) with a larger increase observed in the present decade (2010-2019) than in the previous decade (2000 to 2009). Poor air quality across the urban-rural transact suggests that this is a regional scale problem, a fact that is often neglected. The database is freely disseminated through a web portal 'satellite-based application for air quality monitoring and management at a national scale' (SAANS) for air quality management, epidemiological research and mass awareness.
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关键词
PM2.5, MAIAC, AOD, India, air quality
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