A Satellite-Based High-Resolution (1-km) Ambient PM2.5 Database for India over Two Decades (2000–2019): Applications for Air Quality Management

Sagnik Dey,Fahad Imam,V K Shukla,Palak Balyan,Kunal Bali,Prashant Gargava,Bhavesh Purohit,Kuldeep Dixit,Alok Kumar,Dilip Ganguly,Sourangsu Chowdhury

doi:10.3390/rs12233872

Abstract

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 R2 of 0.8 and 0.97 and root mean square error of 25.7 and 7.2 μg/m3, respectively against surface measurements from the Central Pollution Control Board India network. Population-weighted 20-year averaged PM2.5 over India is 57.3 μg/m3 (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.

Highlights

Exposure to ambient fine particulate matter (PM2.5) is one of the leading causes of health burden in India [1,2]
We examine the product over India (Figure A2) and find that Moderate Resolution Imaging Spectroradiometer (MODIS)–Multiangle Implementation of Atmospheric Correction (MAIAC) aerosol optical depth (AOD) at 550 nm shows a statistically significant (p < 0.05) correlation and root mean square error (RMSE) of 0.13 with AOD from Aerosol Robotic Network (AERONET) [23] sites in India
We find that MERRA-2 and AERONET AOD show a statistically significant (p < 0.05 for N = 4546) R2 of 0.71 (Figure A3) with a RMSE similar to that of MAIAC AOD

Summary

Introduction

Exposure to ambient fine particulate matter (PM2.5) is one of the leading causes of health burden in India [1,2]. The rising ambient PM2.5 concentration [3,4] and its staggering health burden [5,6] led the Government of India to launch the National Clean Air Program (NCAP) in early 2018. Though the NCAP addressed air pollution as a national scale problem, its focus on the urban centres essentially fails to recognize the air quality status in the rural areas. This is reflected in the ground-based monitoring network maintained by the Central Pollution Control Board (CPCB) with all of the 230+ continuous and 650+ manual monitoring sites (www.cpcb.nic.in) deployed in the urban centres. The population-weighted distance to the nearest monitoring site in India is estimated to be 80 km [7]

Methods

Results

Discussion

Conclusion