Five-year Ground-based Observation Trend of PM2.5 and PM10, and Comparison with MERRA-2 Data over India

Abstract

A comprehensive analysis of pollutant’s trend and their measurement techniques are crucial for evaluating the air quality, and thereby helpful in formulating better control policies. In this report, we summarise ground based PM_2.5 and PM₁₀ data report in India (2015–2019). The important points discussed here are: (i) review of the ground-based data of PM_2.5 and PM₁₀ and the techniques used, (ii) mapping of the data over India with spatial and temporal distribution so that better understanding on PM pollution level can be made, (iii) identifying the technological gaps in measurement of PM concentration in India, and (iv) evaluation of MERRA-2’s (Modern-Era Retrospective Analysis for Research and Applications, Version 2) simulation of PM_2.5 against surface measurements in India to better understand biases for spatial and seasonal distribution, and then (v) suggestions for better PM measurement protocols, policies and metrological aspects for both measurement and control policies. It is observed that the amount of ground data on ambient monitoring of fine PM is insufficient and has several inconsistencies which require adequate attention. In India, not much work has been done on developing certified reference materials, traceable standards and calibration facility for particulate matter measurement which is a crucial step to ensure quality checks. Further, the comparison of MERRA-2 and ground PM_2.5 concentrations revealed huge discrepancies with underestimating PM_2.5 measurements in highly polluted regions like the Indo-Gangetic plain, especially during winter when pollution load was high. Better PM_2.5 agreement was found in summer and monsoon season, based on performance statistics explained in this paper. Inconsistencies between MERRA-2 and ground PM_2.5 are partly due to few limitations in MERRA-2 reanalysis method which are discussed in this paper, apart from several issues in ground-based observation. The aim of this review and comparison is to highlight such issues and give more attention to the importance of data quality assurance for effective air quality management. The present study may be helpful for the researchers in evaluating and choosing appropriate reanalysis products for their future studies.