Source Apportionment of PM2.5 in Shandong Province, China, During 2017–2018 Winter Heating Season

PM2.5 pollution has become one of the major environmental issues in Shandong Province in recent years. High concentrations of PM2.5 not only reduce atmospheric visibility but also induce respiratory and cardiovascular diseases, and significantly increase health risks. Source apportionment of PM2.5 is important for policy makers to determine control strategies. This study analyzed regional and sectoral PM2.5 sources across 17 Shandong cities during the 2017–2018 winter heating season, which is selected because it is representative of severe air pollution with an average PM2.5 of 65.75 μg/m3 and hourly peak exceeding 250 μg/m3. This air pollution episode aligned with key control policies, where seven major cities implemented steel capacity reduction and coal-to-gas/electric heating, as a baseline for evaluating emission reduction effectiveness. The particulate matter source apportionment technology in the Comprehensive Air Quality Model with extensions (CAMx) was applied to simulate the source contributions to PM2.5 in 17 cities from different regions and sectors including industry, residence, transportation, and coal-burning power plants. The meteorological fields required for the CAMx model were generated using the Weather Research and Forecasting (WRF) model. The results showed that all cities besides Dezhou city in Shandong Province contributed PM2.5 locally, varying from 39% to 53%. The emissions from Hebei province have a large impact on the PM2.5 concentrations in Shandong Province. The non-local industrial and residential sources in Shandong Province accounted for the prominent proportion of local PM2.5 in all cities. The contribution of non-local industrial sources to PM2.5 in Heze City was up to 56.99%. As for Zibo City, the largest contribution of PM2.5 was from non-local residential sources, around 56%. Additionally, the local industrial and residential sources in Jinan and Rizhao cities had relatively more contributions to the local PM2.5 concentrations compared to the other cities in Shandong Province. Finally, the emission reduction effects were evaluated by applying different reduction ratios of local industrial and transportation sources, with decreases in PM2.5 concentrations ranging from 0.2 to 26 µg/m3 in each city.

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Publication Details

Journal
Atmosphere
Published
2026-01-21
DOI
https://doi.org/10.3390/atmos17010112
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
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article

Source Apportionment of PM2.5 in Shandong Province, China, During 2017–2018 Winter Heating Season

Yang Yu, Y. W. LI, Jing He, Fei Tian et al.
Atmosphere
Atmospheric chemistry and aerosols
article

Source Apportionment of PM2.5 in Shandong Province, China, During 2017–2018 Winter Heating Season

Yang Yu, Y. W. LI, Jing He, Fei Tian, Zhongzhi Zhang, Fan Meng, Tao Ma, Yin Zheng, Wei Tang, Xiaohui Du
article en

Abstract

PM2.5 pollution has become one of the major environmental issues in Shandong Province in recent years. High concentrations of PM2.5 not only reduce atmospheric visibility but also induce respiratory and cardiovascular diseases, and significantly increase health risks. Source apportionment of PM2.5 is important for policy makers to determine control strategies. This study analyzed regional and sectoral PM2.5 sources across 17 Shandong cities during the 2017–2018 winter heating season, which is selected because it is representative of severe air pollution with an average PM2.5 of 65.75 μg/m3 and hourly peak exceeding 250 μg/m3. This air pollution episode aligned with key control policies, where seven major cities implemented steel capacity reduction and coal-to-gas/electric heating, as a baseline for evaluating emission reduction effectiveness. The particulate matter source apportionment technology in the Comprehensive Air Quality Model with extensions (CAMx) was applied to simulate the source contributions to PM2.5 in 17 cities from different regions and sectors including industry, residence, transportation, and coal-burning power plants. The meteorological fields required for the CAMx model were generated using the Weather Research and Forecasting (WRF) model. The results showed that all cities besides Dezhou city in Shandong Province contributed PM2.5 locally, varying from 39% to 53%. The emissions from Hebei province have a large impact on the PM2.5 concentrations in Shandong Province. The non-local industrial and residential sources in Shandong Province accounted for the prominent proportion of local PM2.5 in all cities. The contribution of non-local industrial sources to PM2.5 in Heze City was up to 56.99%. As for Zibo City, the largest contribution of PM2.5 was from non-local residential sources, around 56%. Additionally, the local industrial and residential sources in Jinan and Rizhao cities had relatively more contributions to the local PM2.5 concentrations compared to the other cities in Shandong Province. Finally, the emission reduction effects were evaluated by applying different reduction ratios of local industrial and transportation sources, with decreases in PM2.5 concentrations ranging from 0.2 to 26 µg/m3 in each city.

AtmosphereVol. 17(1)
Xinjiang Institute of Engineering (CN), Shandong Academy of Environmental Science (CN), Chinese Research Academy of Environmental Sciences (CN)
Openalex Percentile: Top 85%
Atmospheric chemistry and aerosols
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