Comparative Analysis of PM_2.5 and O₃ Source in Beijing Using a Chemical Transport Model

• Main Authors: Wei Wen, Song Shen, Lei Liu, Xin Ma, Ying Wei, Jikang Wang, Yi Xing, Wei Su
• Format: Article
• Language: English
• Published: MDPI AG 2021-08-01
• Series: Remote Sensing
• Subjects: PM_2.5 components; ozone; source apportionment; regional transport
• Online Access: https://www.mdpi.com/2072-4292/13/17/3457

For many years, Beijing has suffered from severe air pollution. At present, fine particulate matter (PM_2.5) pollution in the winter and ozone (O₃) pollution in the summer constitute serious environmental problems. In this study, the combination of a comprehensive air quality model with particulate matter source apportionment technology (CAMx-PAST) and monitoring data was used for the high-spatial resolution source apportionment of secondary inorganic components (SNA: SO₄²⁻, NO₃⁻, and NH₄⁺) in PM_2.5; their corresponding precursor gases (SO₂, NO₂, and NH₃); and O₃ in the winter and summer over Beijing. Emissions from residents, industry, traffic, agriculture, and power accounted for 54%, 25%, 14%, 5%, and 2% of PM_2.5 in the winter, respectively. In the summer, the emissions from industry, traffic, residents, agriculture, and power accounted for 42%, 24%, 20%, 10%, and 4% of PM_2.5, respectively. The monthly transport ratio of PM_2.5 was 27% and 46% in the winter and summer, respectively. The regional transport of residential and industrial emissions accounted for the highest proportion of PM_2.5. The regional transport of emissions had a significant effect on the SO₄²⁻ and NO₃⁻ concentrations, whereas SO₂ and NO₂ pollution were mainly affected by local emissions, and NH₄⁺ and NH₃ were mainly attributed to agricultural emissions. Industrial and traffic sources were two major emission sectors that contributed to O₃ pollution in Beijing. The monthly transport ratios of O₃ were 31% and 65% in the winter and summer, respectively. The high-spatial resolution regional source apportionment results showed that emissions from Langfang, Baoding, and Tangshan had the greatest impact on Beijing’s air pollution. This work’s methods and results will provide scientific guidance to support the government in its decision-making processes to manage the PM_2.5 and O₃ pollution issues.