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  1. Article ; Online: Addressing Biases in Ambient PM

    Katoch, Varun / Kumar, Alok / Imam, Fahad / Sarkar, Debajit / Knibbs, Luke D / Liu, Yang / Ganguly, Dilip / Dey, Sagnik

    Environmental science & technology

    2023  Volume 57, Issue 48, Page(s) 19190–19201

    Abstract: ... Ambient ... ...

    Abstract Ambient PM
    MeSH term(s) Particulate Matter/analysis ; Air Pollution/analysis ; Environmental Monitoring/methods ; Aerosols/analysis ; Bias ; India ; Air Pollutants/analysis
    Chemical Substances Particulate Matter ; Aerosols ; Air Pollutants
    Language English
    Publishing date 2023-11-13
    Publishing country United States
    Document type Journal Article
    ISSN 1520-5851
    ISSN (online) 1520-5851
    DOI 10.1021/acs.est.3c03355
    Database MEDical Literature Analysis and Retrieval System OnLINE

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

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

    Remote Sensing. 2020 Nov. 26, v. 12, no. 23

    2020  

    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 ... ...

    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.
    Keywords Internet ; administrative management ; aerosols ; air quality ; algorithms ; climate ; databases ; depth ; environment ; mass ; moderate resolution imaging spectroradiometer ; monitoring ; particulates ; pollutants ; pollution control ; remote sensing ; research ; retrospective studies ; satellites ; India
    Language English
    Dates of publication 2020-1126
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    Note NAL-light
    ZDB-ID 2513863-7
    ISSN 2072-4292
    ISSN 2072-4292
    DOI 10.3390/rs12233872
    Database NAL-Catalogue (AGRICOLA)

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