Air pollution scenario over Pakistan: Characterization and ranking of extremely polluted cities using long-term concentrations of aerosols and trace gases

REMOTE SENSING OF ENVIRONMENT

卷:264

Article

Bilal, Muhammad¹  Mhawish, Alaa¹  Nichol, Janet E.²  Qiu, Zhongfeng¹  Nazeer, Majid³  Ali, Md Arfan¹  de Leeuw, Gerrit^4,5,6,7  Levy, Robert C.⁸  Wang, Yu¹  Chen, Yang⁹  Wang, Lunche¹⁰  Shi, Yuan¹¹  Bleiweiss, Max P.¹²  Mazhar, Usman¹³  Atique, Luqman¹⁴  Ke, Song¹⁵ 

[1] Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Lab Environm Remote Sensing LERS, Nanjing 210044, Peoples R China

[2] Univ Sussex, Sch Global Studies, Dept Geog, Brighton BN1 9RH, E Sussex, England

[3] East China Univ Technol, Key Lab Digital Land & Resources, Nanchang 330013, Jiangxi, Peoples R China

[4] Royal Netherlands Meteorol Inst KNMI, R&D Satellite Observat, NL-3730 AE De Bilt, Netherlands

[5] Nanjing Univ Informat Sci & Technol, Sch Atmospher Phys, Nanjing 210044, Peoples R China

[6] Chinese Acad Sci AirCAS, Aerosp Informat Res Inst, 20 Datun Rd, Beijing 100101, Peoples R China

[7] Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou 221116, Jiangsu, Peoples R China

[8] NASA, Goddard Space Flight Ctr, Climate & Radiat Lab, Greenbelt, MD USA

[9] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China

[10] China Univ Geosci, Sch Earth Sci, Lab Crit Zone Evolut, Wuhan 430074, Peoples R China

[11] Chinese Univ Hong Kong, Inst Future Cities, Hong Kong, Peoples R China

[12] New Mexico State Univ, Dept Entomol Plant Pathol & Weed Sci, Las Cruces, NM 88003 USA

[13] Zhejiang Univ, Sch Earth Sci, Hangzhou 310027, Peoples R China

[14] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China

[15] Geol Survey Jiangsu Prov, Nanjing 210018, Peoples R China

关键词: MODIS;    AOD;    CAMS;    MERRA-2;    PM1;    PM2.5;    PM10;    OMI;    NO2;    SO2;    PSCF;    Pakistan;   

DOI  :  10.1016/j.rse.2021.112617

来源: Elsevier

【 摘 要 】

Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectmradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used.For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan's entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 mu g/m(3), over all Pakistan from 2003 to 2020.This value exceeds Pakistan's National Environmental Quality Standards (Pak-NEQS, i.e., <15 mu g/m(3) annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 < 35 mu g/m(3)).The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan's air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries.Statistically significant positive (increasing) trends in PM1, PM2. 5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in similar to 89%, similar to 67%, similar to 48%, 91%, and similar to 88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.

【 授权许可】

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