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  • 标题:Evaluation of PM2.5 Surface Concentrations Simulated by NASA’s MERRA Version 2 Aerosol Reanalysis over India and its Relation to the Air Quality Index
  • 本地全文:下载
  • 作者:Chimurkar D. Navinya ; V Vinoj ; Satyendra K Pandey
  • 期刊名称:Aerosol and Air Quality Research
  • 印刷版ISSN:1680-8584
  • 出版年度:2020
  • 卷号:20
  • 期号:6
  • 页码:1329-1339
  • DOI:10.4209/aaqr.2019.12.0615
  • 语种:English
  • 出版社:Chinese Association for Aerosol Research in Taiwan
  • 摘要:The PM2.5 (particulate matter with a diameter ≤ 2.5 µm), an essential component of air pollution, is closely linked to adverse effects on human health, including premature mortality following prolonged exposure. However, limited surface measurement and the lack of monitoring with adequate spatial resolution hamper studies related to air pollution and its impact on various societally relevant issues. More recently, the National Aeronautics and Space Administration (NASA)’s Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) has begun estimating the global distribution of PM2.5 mass concentrations at high spatio-temporal resolutions, but the limitations of the applied estimation methodologies must be carefully evaluated in order to understand their strengths and weaknesses. This study assesses MERRA-2’s PM2.5 results by comparing them with ground-based measurements conducted at 20 stations across the Indian region between 2015 and early 2018. Our analysis shows that MERRA-2 generally underestimates the PM2.5 in terms of both the mass concentration and the number of exceedance days. While the Central Pollution Control Board (CPCB) measured exceedances of the national ambient air quality standards (NAAQS) on 34% of the days, MERRA-2’s prediction was only 11%, and its estimate of the annual average PM2.5 concentration across all of the sites was also negatively biased, by ~27 µg m–3. Correlations of 0.96 and 0.6 were found between the estimates and the measurements for the monthly and the daily averaged concentrations, respectively; these numbers can be dramatically improved by applying a simple bias correction. Overall, our evaluation reveals that MERRA-2’s raw estimates of PM2.5 on a monthly time scale or longer are helpful in long-term air quality studies.
  • 关键词:PM2.5; CPCB; MERRA-2; Air pollution; Aerosols; Evaluation.
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