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Incorporating long-term satellite-based aerosol optical depth, localized land use data, and meteorological variables to estimate ground-level PM2.5 concentrations in Taiwan from 2005 to 2015.
Environ Pollut. 2018 Jun; 237:1000-1010.EP

Abstract

Satellite-based aerosol optical depth (AOD) is now comprehensively applied to estimate ground-level concentrations of fine particulate matter (PM2.5). This study aimed to construct the AOD-PM2.5 estimation models over Taiwan. The AOD-PM2.5 modeling in Taiwan island is challenging owing to heterogeneous land use, complex topography, and humid tropical to subtropical climate conditions with frequent cloud cover and prolonged rainy season. The AOD retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites were combined with the meteorological variables from reanalysis data and high resolution localized land use variables to estimate PM2.5 over Taiwan island from 2005 to 2015. Ten-fold cross validation was carried out and the residuals of the estimation model at various locations and seasons are assessed. The cross validation (CV) R2 based on monitoring stations were 0.66 and 0.66, with CV root mean square errors of 14.0 μg/m3 (34%) and 12.9 μg/m3 (33%), respectively, for models based on Terra and Aqua AOD. The results provided PM2.5 estimations at locations without surface stations. The estimation revealed PM2.5 concentration hotspots in the central and southern part of the western plain areas, particularly in winter and spring. The annual average of estimated PM2.5 concentrations over Taiwan consistently declined during 2005-2015. The AOD-PM2.5 model is a reliable and validated method for estimating PM2.5 concentrations at locations without monitoring stations in Taiwan, which is crucial for epidemiological study and for the assessment of air quality control policy.

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Publisher Full Text (DOI)

Authors+Show Affiliations

Jung CR
Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung, Taiwan.
Hwang BF
Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung, Taiwan; Department of Occupational Therapy, College of Medical and Health Science, Asia University, Taichung, Taiwan.
Chen WT
Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan. Electronic address: weitingc@ntu.edu.tw.

MeSH

AerosolsAir PollutantsAir PollutionEnvironmental MonitoringMeteorologyParticulate MatterSatellite ImagerySeasonsTaiwan

Pub Type(s)

Journal Article

Language

eng

PubMed ID

29157969

Citation

Jung, Chau-Ren, et al. "Incorporating Long-term Satellite-based Aerosol Optical Depth, Localized Land Use Data, and Meteorological Variables to Estimate Ground-level PM2.5 Concentrations in Taiwan From 2005 to 2015." Environmental Pollution (Barking, Essex : 1987), vol. 237, 2018, pp. 1000-1010.
Jung CR, Hwang BF, Chen WT. Incorporating long-term satellite-based aerosol optical depth, localized land use data, and meteorological variables to estimate ground-level PM2.5 concentrations in Taiwan from 2005 to 2015. Environ Pollut. 2018;237:1000-1010.
Jung, C. R., Hwang, B. F., & Chen, W. T. (2018). Incorporating long-term satellite-based aerosol optical depth, localized land use data, and meteorological variables to estimate ground-level PM2.5 concentrations in Taiwan from 2005 to 2015. Environmental Pollution (Barking, Essex : 1987), 237, 1000-1010. https://doi.org/10.1016/j.envpol.2017.11.016
Jung CR, Hwang BF, Chen WT. Incorporating Long-term Satellite-based Aerosol Optical Depth, Localized Land Use Data, and Meteorological Variables to Estimate Ground-level PM2.5 Concentrations in Taiwan From 2005 to 2015. Environ Pollut. 2018;237:1000-1010. PubMed PMID: 29157969.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Incorporating long-term satellite-based aerosol optical depth, localized land use data, and meteorological variables to estimate ground-level PM2.5 concentrations in Taiwan from 2005 to 2015. AU - Jung,Chau-Ren, AU - Hwang,Bing-Fang, AU - Chen,Wei-Ting, Y1 - 2017/11/20/ PY - 2017/04/02/received PY - 2017/11/04/revised PY - 2017/11/05/accepted PY - 2017/11/22/pubmed PY - 2018/7/12/medline PY - 2017/11/22/entrez KW - Aerosol optical depth KW - Fine particulate matter KW - Land use KW - Meteorological variables KW - PM(2.5) SP - 1000 EP - 1010 JF - Environmental pollution (Barking, Essex : 1987) JO - Environ Pollut VL - 237 N2 - Satellite-based aerosol optical depth (AOD) is now comprehensively applied to estimate ground-level concentrations of fine particulate matter (PM2.5). This study aimed to construct the AOD-PM2.5 estimation models over Taiwan. The AOD-PM2.5 modeling in Taiwan island is challenging owing to heterogeneous land use, complex topography, and humid tropical to subtropical climate conditions with frequent cloud cover and prolonged rainy season. The AOD retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites were combined with the meteorological variables from reanalysis data and high resolution localized land use variables to estimate PM2.5 over Taiwan island from 2005 to 2015. Ten-fold cross validation was carried out and the residuals of the estimation model at various locations and seasons are assessed. The cross validation (CV) R2 based on monitoring stations were 0.66 and 0.66, with CV root mean square errors of 14.0 μg/m3 (34%) and 12.9 μg/m3 (33%), respectively, for models based on Terra and Aqua AOD. The results provided PM2.5 estimations at locations without surface stations. The estimation revealed PM2.5 concentration hotspots in the central and southern part of the western plain areas, particularly in winter and spring. The annual average of estimated PM2.5 concentrations over Taiwan consistently declined during 2005-2015. The AOD-PM2.5 model is a reliable and validated method for estimating PM2.5 concentrations at locations without monitoring stations in Taiwan, which is crucial for epidemiological study and for the assessment of air quality control policy. SN - 1873-6424 UR - https://www.unboundmedicine.com/medline/citation/29157969/Incorporating_long_term_satellite_based_aerosol_optical_depth_localized_land_use_data_and_meteorological_variables_to_estimate_ground_level_PM2_5_concentrations_in_Taiwan_from_2005_to_2015_ DB - PRIME DP - Unbound Medicine ER -