The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth

Satellite aerosol retrievals have been a popular alternative to monitoring the surface-based PM2.5 concentration due to their extensive spatial and temporal coverage. Satellite-derived PM2.5 estimations strongly rely on an accurate representation of the relationship between ground-level PM2.5 and sa...

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Main Authors: He, Qingqing, Wang, Mengya, Yim, Steve Hung Lam
Other Authors: Asian School of the Environment
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/161483
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1614832023-02-28T16:39:57Z The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth He, Qingqing Wang, Mengya Yim, Steve Hung Lam Asian School of the Environment Lee Kong Chian School of Medicine (LKCMedicine) Engineering::Environmental engineering Optical Depth Particulate Matter Satellite aerosol retrievals have been a popular alternative to monitoring the surface-based PM2.5 concentration due to their extensive spatial and temporal coverage. Satellite-derived PM2.5 estimations strongly rely on an accurate representation of the relationship between ground-level PM2.5 and satellite aerosol optical depth (AOD). Due to the limitations of satellite AOD data, most studies have examined the relationship at a coarse resolution (i.e., ≥10km) thus, more effort is still needed to better understand the relationship between "in situ"PM2.5 and AOD at finer spatial scales. While PM2.5 and AOD could have obvious temporal variations, few studies have examined the diurnal variation in their relationship. Therefore, considerable uncertainty still exists in satellite-derived PM2.5 estimations due to these research gaps. Taking advantage of the newly released fine-spatial-resolution satellite AOD data derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm and real-time ground aerosol and PM2.5 measurements, this study explicitly explored the relationship between PM2.5 and AOD as well as its plausible impact factors, including meteorological parameters and topography, in mainland China during 2019, at various spatial and temporal scales. The coefficient of variation, the Pearson correlation coefficient and the slope of the linear regression model were used. Spatially, stronger correlations mainly occurred in northern and eastern China, and the linear slope was larger on average in northern inland regions than in other areas. Temporally, the PM2.5-AOD correlation peaked at noon and in the afternoon, and reached a maximum in winter. Simultaneously, considering relative humidity (RH) and the planetary boundary layer height (PBLH) in the relationship can improve the correlation, but the effect of RH and the PBLH on the correlation varied spatially and temporally with respect to both strength and direction. In addition, the largest correlation occurred at 400-600m primarily in basin terrain such as the Sichuan Basin, the Shanxi-Shaanxi basins and the Junggar Basin. MAIAC 1km AOD can better represent the ground-level fine particulate matter in most domains with exceptions, such as in very high terrain (i.e., Tibetan Plateau) and northern central China (i.e., Qinghai and Gansu). The findings of this study have useful implications for satellite-based PM2.5 monitoring and will further inform the understanding of the aerosol variation and PM2.5 pollution status of mainland China. Published version This research was funded by the Vice-Chancellor’s Discretionary Fund of The Chinese University of Hong Kong (grant no. 4930744), the Dr. Stanley Ho Medicine Development Foundation (grant no. 8305509) and the National Natural Science Foundation of China (grant no. 41901324). 2022-09-05T08:21:54Z 2022-09-05T08:21:54Z 2021 Journal Article He, Q., Wang, M. & Yim, S. H. L. (2021). The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth. Atmospheric Chemistry and Physics, 21(24), 18375-18391. https://dx.doi.org/10.5194/acp-21-18375-2021 1680-7316 https://hdl.handle.net/10356/161483 10.5194/acp-21-18375-2021 2-s2.0-85122016422 24 21 18375 18391 en Atmospheric Chemistry and Physics © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Environmental engineering
Optical Depth
Particulate Matter
spellingShingle Engineering::Environmental engineering
Optical Depth
Particulate Matter
He, Qingqing
Wang, Mengya
Yim, Steve Hung Lam
The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth
description Satellite aerosol retrievals have been a popular alternative to monitoring the surface-based PM2.5 concentration due to their extensive spatial and temporal coverage. Satellite-derived PM2.5 estimations strongly rely on an accurate representation of the relationship between ground-level PM2.5 and satellite aerosol optical depth (AOD). Due to the limitations of satellite AOD data, most studies have examined the relationship at a coarse resolution (i.e., ≥10km) thus, more effort is still needed to better understand the relationship between "in situ"PM2.5 and AOD at finer spatial scales. While PM2.5 and AOD could have obvious temporal variations, few studies have examined the diurnal variation in their relationship. Therefore, considerable uncertainty still exists in satellite-derived PM2.5 estimations due to these research gaps. Taking advantage of the newly released fine-spatial-resolution satellite AOD data derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm and real-time ground aerosol and PM2.5 measurements, this study explicitly explored the relationship between PM2.5 and AOD as well as its plausible impact factors, including meteorological parameters and topography, in mainland China during 2019, at various spatial and temporal scales. The coefficient of variation, the Pearson correlation coefficient and the slope of the linear regression model were used. Spatially, stronger correlations mainly occurred in northern and eastern China, and the linear slope was larger on average in northern inland regions than in other areas. Temporally, the PM2.5-AOD correlation peaked at noon and in the afternoon, and reached a maximum in winter. Simultaneously, considering relative humidity (RH) and the planetary boundary layer height (PBLH) in the relationship can improve the correlation, but the effect of RH and the PBLH on the correlation varied spatially and temporally with respect to both strength and direction. In addition, the largest correlation occurred at 400-600m primarily in basin terrain such as the Sichuan Basin, the Shanxi-Shaanxi basins and the Junggar Basin. MAIAC 1km AOD can better represent the ground-level fine particulate matter in most domains with exceptions, such as in very high terrain (i.e., Tibetan Plateau) and northern central China (i.e., Qinghai and Gansu). The findings of this study have useful implications for satellite-based PM2.5 monitoring and will further inform the understanding of the aerosol variation and PM2.5 pollution status of mainland China.
author2 Asian School of the Environment
author_facet Asian School of the Environment
He, Qingqing
Wang, Mengya
Yim, Steve Hung Lam
format Article
author He, Qingqing
Wang, Mengya
Yim, Steve Hung Lam
author_sort He, Qingqing
title The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth
title_short The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth
title_full The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth
title_fullStr The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth
title_full_unstemmed The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth
title_sort spatiotemporal relationship between pm2.5 and aerosol optical depth in china: influencing factors and implications for satellite pm2.5 estimations using maiac aerosol optical depth
publishDate 2022
url https://hdl.handle.net/10356/161483
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