Spatiotemporal mapping and assessment of daily ground NO2 concentrations in China using high-resolution TROPOMI retrievals

Sensen Wu; Bo Huang; Jionghua Wang; Lijie He; Zhongyi Wang; Zhen Yan; Xiangqian Lao; Feng Zhang; Renyi Liu; Zhenhong Du

doi:10.1016/j.envpol.2021.116456

Spatiotemporal mapping and assessment of daily ground NO₂ concentrations in China using high-resolution TROPOMI retrievals

Environ Pollut. 2021 Jan 8:273:116456. doi: 10.1016/j.envpol.2021.116456. Online ahead of print.

Authors

Sensen Wu¹, Bo Huang², Jionghua Wang³, Lijie He³, Zhongyi Wang⁴, Zhen Yan⁵, Xiangqian Lao⁶, Feng Zhang⁷, Renyi Liu⁷, Zhenhong Du⁷

Affiliations

¹ School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, 310028, China; Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.
² Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong; Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong. Electronic address: bohuang@cuhk.edu.hk.
³ Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.
⁴ School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China.
⁵ Center of Agricultural and Rural Development, School of Public Affairs, Zhejiang University, Hangzhou, 310058, China.
⁶ The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.
⁷ School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, 310028, China.

PMID: 33477063
DOI: 10.1016/j.envpol.2021.116456

Abstract

Nitrogen dioxide (NO₂) is an important air pollutant that causes direct harms to the environment and human health. Ground NO₂ mapping with high spatiotemporal resolution is critical for fine-scale air pollution and environmental health research. We thus developed a spatiotemporal regression kriging model to map daily high-resolution (3-km) ground NO₂ concentrations in China using the Tropospheric Monitoring Instrument (TROPOMI) satellite retrievals and geographical covariates. This model combined geographically and temporally weighted regression with spatiotemporal kriging and achieved robust prediction performance with sample-based and site-based cross-validation R² values of 0.84 and 0.79. The annual mean and standard deviation of ground NO₂ concentrations from June 1, 2018 to May 31, 2019 were predicted to be 15.05 ± 7.82 μg/m³, with that in 0.6% of China's area (10% of the population) exceeding the annual air quality standard (40 μg/m³). The ground NO₂ concentrations during the coronavirus disease (COVID-19) period (January and February in 2020) was 14% lower than that during the same period in 2019 and the mean population exposure to ground NO₂ was reduced by 25%. This study was the first to use TROPOMI retrievals to map fine-scale daily ground NO₂ concentrations across all of China. This was also an early application to use the satellite-estimated ground NO₂ data to quantify the impact of the COVID-19 pandemic on the air pollution and population exposures. These newly satellite-derived ground NO₂ data with high spatiotemporal resolution have value in advancing environmental and health research in China.

Keywords: COVID-19; China; High-resolution; Nitrogen dioxide; Spatiotemporal regression kriging; TROPOMI.