Multiscale spatiotemporal variations of NOx emissions from heavy duty diesel trucks in the Beijing-Tianjin-Hebei region

Shifen Cheng; Beibei Zhang; Yibo Zhao; Peng Peng; Feng Lu

doi:10.1016/j.scitotenv.2022.158753

Multiscale spatiotemporal variations of NO_x emissions from heavy duty diesel trucks in the Beijing-Tianjin-Hebei region

Sci Total Environ. 2023 Jan 1:854:158753. doi: 10.1016/j.scitotenv.2022.158753. Epub 2022 Sep 13.

Authors

Shifen Cheng¹, Beibei Zhang¹, Yibo Zhao¹, Peng Peng¹, Feng Lu²

Affiliations

¹ State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
² State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: luf@lreis.ac.cn.

PMID: 36108863
DOI: 10.1016/j.scitotenv.2022.158753

Abstract

Heavy-duty diesel trucks (HDDTs) cause serious pollution to urban and regional environment. Understanding the spatiotemporal pattern of pollution emissions and its impact factors is the basis for implementing emission reduction measures. However, since the multiscale emission inventory of HDDTs is not currently established, multiscale analysis of these issues is still lacking. Therefore, this study uses massive trajectory data, detailed vehicle specification information and road network information, combined with localized emission factors, to construct a multiscale NO_x emission inventory of HDDTs with high spatiotemporal resolution in the Beijing-Tianjin-Hebei region. Then the multiscale spatiotemporal variations of NO_x emissions are analyzed by using spatial statistical indicators and multiscale geographical weighted regression model. The results show that the NO_x emissions of HDDTs show different spatiotemporal distribution and aggregation characteristics at different scales. Specifically, link-scale emissions are concentrated to a few highways and are dominated by Low-Low cluster. While county-scale and city-scale emissions are concentrated in the eastern plains, mainly in High-High and Low-Low clusters. There are spatial heterogeneity and multiscale effects of socioeconomic and road attribute characteristics on the NO_x emissions from HDDTs. Population density, urbanization rate, proportion of second industry, and proportion of highway affect the NO_x emissions of HDDTs globally, while per capita GDP and road density have local effects. Our results extend the scientific understanding of the multiscale spatiotemporal variations of HDDTs and may provide a scientific basis for the development of targeted emission control measures for HDDTs.

Keywords: Heavy-duty diesel trucks; Multiscale effect; Spatiotemporal patterns; Traffic emissions.