A novel framework for decomposing PM2.5 variation and demographic change effects on human exposure using satellite observations

Changqing Lin; Alexis K.H. Lau; Xiang Qian Lao; Jimmy C.H. Fung; Xingcheng Lu; Zhiyuan Li; Jun Ma; Chengcai Li; Andromeda H.S. Wong

doi:10.1016/j.envres.2020.109120

A novel framework for decomposing PM_2.5 variation and demographic change effects on human exposure using satellite observations

Changqing Lin
, Alexis K.H. Lau^*
, Xiang Qian Lao
, Jimmy C.H. Fung
, Xingcheng Lu
, Zhiyuan Li
, Jun Ma
, Chengcai Li
, Andromeda H.S. Wong

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

4 Citations (Scopus)

Abstract

Human exposure to PM_2.5, represented by population-weighted mean PM_2.5 concentration (c_ρ), declines under three conditions: (1) mean PM_2.5 concentration declines, (2) PM_2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM_2.5 observations limits the assessment of human exposure to PM_2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in c_ρ resulting from change in the mean PM_2.5 concentration, spatial difference in PM_2.5 change, and demographic change. In this framework, we decomposed c_ρ into mean PM_2.5 concentration (c₀) and pollution-population-coincidence induced PM_2.5 exposure (PPCE). We then used this framework to decompose the variation in c_ρ over China within three recent Five-Year Plans (FYPs) (2001–2015). The results showed that the decline in c₀ reduced c_ρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM_2.5 change reduced the PPCE and c_ρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of −3.64 μg m⁻³·yr⁻¹ in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and c_ρ (by as much as 0.22 μg m⁻³·yr⁻¹) in all provinces except Taiwan within all three FYPs. The demographic change reduced c_ρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.

Original language	English
Article number	109120
Journal	Environmental Research
Volume	182
Online published	7 Jan 2020
DOIs	https://doi.org/10.1016/j.envres.2020.109120
Publication status	Published - Mar 2020
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Inc.

Funding

This work was supported by the Research Grants Council of Hong Kong Government (Project No. T24/504/17), the Science and Technology Plan Project of Guangdong Province of China (Grant No. 2017A050506003), NSFC/RGC (Grant No. N_HKUST638/19, N_HKUST631/05), and the Fok Ying Tung Graduate School (NRC06/07.SC01). We thank the Hong Kong Environmental Protection Department for providing air-quality monitoring data. The authors declare they have no actual or potential competing financial interests.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 11 Sustainable Cities and Communities

Research Keywords

Human exposure
PM
Public health
Satellite observations
Urbanization

RGC Funding Information

RGC-funded

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10.1016/j.envres.2020.109120

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Cite this

@article{1758fa2bcf854eb5b391e328fda26507,

title = "A novel framework for decomposing PM2.5 variation and demographic change effects on human exposure using satellite observations",

abstract = "Human exposure to PM2.5, represented by population-weighted mean PM2.5 concentration (cρ), declines under three conditions: (1) mean PM2.5 concentration declines, (2) PM2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM2.5 observations limits the assessment of human exposure to PM2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in cρ resulting from change in the mean PM2.5 concentration, spatial difference in PM2.5 change, and demographic change. In this framework, we decomposed cρ into mean PM2.5 concentration (c0) and pollution-population-coincidence induced PM2.5 exposure (PPCE). We then used this framework to decompose the variation in cρ over China within three recent Five-Year Plans (FYPs) (2001–2015). The results showed that the decline in c0 reduced cρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM2.5 change reduced the PPCE and cρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of −3.64 μg m−3·yr−1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and cρ (by as much as 0.22 μg m−3·yr−1) in all provinces except Taiwan within all three FYPs. The demographic change reduced cρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.",

keywords = "Human exposure, PM, Public health, Satellite observations, Urbanization",

author = "Changqing Lin and Lau, \{Alexis K.H.\} and Lao, \{Xiang Qian\} and Fung, \{Jimmy C.H.\} and Xingcheng Lu and Zhiyuan Li and Jun Ma and Chengcai Li and Wong, \{Andromeda H.S.\}",

note = "Publisher Copyright: {\textcopyright} 2020 Elsevier Inc.",

year = "2020",

month = mar,

doi = "10.1016/j.envres.2020.109120",

language = "English",

volume = "182",

journal = "Environmental Research",

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T1 - A novel framework for decomposing PM2.5 variation and demographic change effects on human exposure using satellite observations

AU - Lin, Changqing

AU - Lau, Alexis K.H.

AU - Lao, Xiang Qian

AU - Fung, Jimmy C.H.

AU - Lu, Xingcheng

AU - Li, Zhiyuan

AU - Ma, Jun

AU - Li, Chengcai

AU - Wong, Andromeda H.S.

PY - 2020/3

Y1 - 2020/3

N2 - Human exposure to PM2.5, represented by population-weighted mean PM2.5 concentration (cρ), declines under three conditions: (1) mean PM2.5 concentration declines, (2) PM2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM2.5 observations limits the assessment of human exposure to PM2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in cρ resulting from change in the mean PM2.5 concentration, spatial difference in PM2.5 change, and demographic change. In this framework, we decomposed cρ into mean PM2.5 concentration (c0) and pollution-population-coincidence induced PM2.5 exposure (PPCE). We then used this framework to decompose the variation in cρ over China within three recent Five-Year Plans (FYPs) (2001–2015). The results showed that the decline in c0 reduced cρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM2.5 change reduced the PPCE and cρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of −3.64 μg m−3·yr−1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and cρ (by as much as 0.22 μg m−3·yr−1) in all provinces except Taiwan within all three FYPs. The demographic change reduced cρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.

AB - Human exposure to PM2.5, represented by population-weighted mean PM2.5 concentration (cρ), declines under three conditions: (1) mean PM2.5 concentration declines, (2) PM2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM2.5 observations limits the assessment of human exposure to PM2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in cρ resulting from change in the mean PM2.5 concentration, spatial difference in PM2.5 change, and demographic change. In this framework, we decomposed cρ into mean PM2.5 concentration (c0) and pollution-population-coincidence induced PM2.5 exposure (PPCE). We then used this framework to decompose the variation in cρ over China within three recent Five-Year Plans (FYPs) (2001–2015). The results showed that the decline in c0 reduced cρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM2.5 change reduced the PPCE and cρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of −3.64 μg m−3·yr−1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and cρ (by as much as 0.22 μg m−3·yr−1) in all provinces except Taiwan within all three FYPs. The demographic change reduced cρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.

KW - Human exposure

KW - PM

KW - Public health

KW - Satellite observations

KW - Urbanization

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