Spatio-Temporal Variation-Induced Group Disparity of Intra-Urban NO 2 Exposure

Huizi Wang, Xiao Luo, Chao Liu, Qingyan Fu and Min Yi
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Huizi Wang: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China
Xiao Luo: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China
Chao Liu: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Qingyan Fu: Shanghai Environmental Monitoring Center, Shanghai 200235, China
Min Yi: Shanghai Environmental Monitoring Center, Shanghai 200235, China

IJERPH, 2022, vol. 19, issue 10, 1-21

Abstract: Previous studies on exposure disparity have focused more on spatial variation but ignored the temporal variation of air pollution; thus, it is necessary to explore group disparity in terms of spatio-temporal variation to assist policy-making regarding public health. This study employed the dynamic land use regression (LUR) model and mobile phone signal data to illustrate the variation features of group disparity in Shanghai. The results showed that NO 2 exposure followed a bimodal, diurnal variation pattern and remained at a high level on weekdays but decreased on weekends. The most critical at-risk areas were within the central city in areas with a high population density. Moreover, women and the elderly proved to be more exposed to NO 2 pollution in Shanghai. Furthermore, the results of this study showed that it is vital to focus on land-use planning, transportation improvement programs, and population agglomeration to attenuate exposure inequality.

Keywords: land use regression (LUR); mobile phone signal data; air pollution; population exposure; environmental justice (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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