Study on the Spatiotemporal Heterogeneity and Driving Factors of PM2.5 Pollution in Shandong Province during 2014-2020
Wei Jiang 1,2
Ke Du 1
More details
Hide details
School of Water Conservancy and Environment, University of Jinan, Jinan, China
College of Geography and Environment, Shandong Normal University, Jinan, China
Submission date: 2023-04-13
Final revision date: 2023-06-07
Acceptance date: 2023-07-07
Online publication date: 2023-09-04
Publication date: 2023-10-25
Corresponding author
Wei Jiang   

University of Jinan, School of Water Conservancy and Environment, 250000, Jinan, China
Pol. J. Environ. Stud. 2023;32(6):5245–5260
Shandong suffered from severe PM2.5 pollution in recent years as a result of its energy-intensive heavy industry. The initial step in implementing targeted control measures was to identify the main factors affecting PM2.5 concentrations. This paper explored the spatiotemporal characteristics of PM2.5 pollution in Shandong province during 2014-2020 based on observation data of 103 monitoring stations, thereafter, screened out the key natural and social-economical driving factors with the spatial Durbin model (SDM). The findings indicated that between 2014 and 2020, the annual average concentration of PM2.5 in Shandong decreased from 75.32 μg/m3 to 46.46 μg/m3. The monthly variation followed a clear U-shaped pattern and the daily variation followed an N-shaped distribution with peak concentrations at 09:00 and 23:00 respectively. Spatially, cities with high PM2.5 concentration tended to cluster and present high-west and low-east agglomeration characteristic at provincial scale. PM2.5 pollution showed considerable positive spatial autocorrelation and it took an apparent spatial agglomeration pattern in central and western cities. According to the estimates of the spatial Durbin model (SDM), PM2.5 pollution had significant spatial spillover effects in Shandong, and the indirect effects of the same factor were generally greater than the direct effects, indicating that the influence of neighboring cities could not be ignored. Of the multiple factors, socioeconomic factors had a considerably lesser influence on PM2.5 pollution than did natural ones like temperature, relative humidity and wind speed.