Analysis of traffic-related air pollution using Shanghai road traffic state index

¹ School of Software Engineering, University of Science and Technology of China, 215123, Suzhou, China
² College of Information Engineering, Northwest A&F University, 712100, Yangling, China

^* Corresponding author: chenry@mail.ustc.edu.cn

Abstract

Recently, due to the rapid economic development and the acceleration of urbanization, haze events have occurred frequently in most parts of China, which has attracted widespread attention at home and abroad. This study presents a statistical summary of air pollution concentrations and traffic state indexes from August 2014 to April 2015 in Shanghai, China. We find PM_2.5 concentrations show a remarkable seasonal variability with ``winter > spring > autumn > summer'' in Shanghai. Concentrations of PM_2.5, CO, NO₂, SO₂ are generally higher in winter than in summer due to enhanced anthropogenic and biogenic emissions and unsuitable meteorological conditions for pollution diffusion, contrary to concentrations of O₃. The weekly changes of NO₂ are highly consistent with that of traffic state indexes, suggesting a significant contribution to NO₂ concentrations from road traffic emissions. Two moderate peaks are found in the diurnal variability of concentrations of PM_2.5, CO and NO₂, similar to road traffic indexes, indicating the important contribution of road traffic emissions every day. We find that SO₂, NO₂, CO are the dominant factors contributing to PM_2.5 pollution, where NO₂ and CO are mainly from road traffic emissions. The average annual Spearman correlation coefficient is r = 0.689 (p < 0.01), r = 0.564 (p < 0.01), r = 0.812 (p < 0.01), respectively.