Source apportionment and regional transport of PM2.5 during haze episodes in Beijing combined with multiple models

2021 ◽  
pp. 105957
Author(s):  
Lingling Lv ◽  
Peng Wei ◽  
Jingnan Hu ◽  
Yingjun Chen ◽  
Yaopeng Shi
2020 ◽  
Author(s):  
Jiarui Wu ◽  
Naifang Bei ◽  
Yuan Wang ◽  
Xia Li ◽  
Suixin Liu ◽  
...  

Abstract. Accurate identification and quantitative source apportionment of fine particulate matters (PM2.5) provide an important prerequisite for design and implementation of emission control strategies to reduce PM pollution. Therefore, a source-oriented version of the WRF-Chem model is developed in the study to make source apportionment of PM2.5 in the North China Plain (NCP). A persistent and heavy haze event occurred in the NCP from 05 December 2015 to 04 January 2016 is simulated using the model as a case study to quantify PM2.5 contributions of local emissions and regional transport. Results show that local and non-local emissions contribute 36.3 % and 63.7 % of the PM2.5 mass in Beijing during the haze event on average. When Beijing's air quality is excellent or good in terms of hourly PM2.5 concentrations, local emissions dominate the PM2.5 mass with contributions exceeding 50 %. However, when the air quality is severely polluted, the PM2.5 contribution of non-local emissions is around 75 %. The non-local emissions also dominate the Tianjin's air quality, with average PM2.5 contributions exceeding 70 %. The PM2.5 level in Hebei and Shandong is generally controlled by local emissions, but in Henan, local and non-local emissions play an almost equivalent role in the PM2.5 level, except when the air quality is severely polluted, with non-local PM2.5 contributions of over 60 %. Additionally, the primary aerosol species are generally dominated by local emissions with the average contribution exceeding 50%. However, the source apportionment of secondary aerosols shows more evident regional characteristics. Therefore, except cooperation with neighboring provinces to carry out strict emission mitigation measures, reducing primary aerosols constitutes the priority to alleviate PM pollution in the NCP, especially in Beijing and Tianjin.


2021 ◽  
Vol 21 (3) ◽  
pp. 2229-2249
Author(s):  
Jiarui Wu ◽  
Naifang Bei ◽  
Yuan Wang ◽  
Xia Li ◽  
Suixin Liu ◽  
...  

Abstract. Accurate identification and quantitative source apportionment of fine particulate matter (PM2.5) provide an important prerequisite for design and implementation of emission control strategies to reduce PM pollution. Therefore, a source-oriented version of the WRF-Chem model is developed in the study to conduct source apportionment of PM2.5 in the North China Plain (NCP). A persistent and heavy haze event that occurred in the NCP from 5 December 2015 to 4 January 2016 is simulated using the model as a case study to quantify PM2.5 contributions of local emissions and regional transport. Results show that local and nonlocal emissions contribute 36.3 % and 63.7 % of the PM2.5 mass in Beijing during the haze event on average. When Beijing's air quality is excellent or good in terms of hourly PM2.5 concentrations, local emissions dominate the PM2.5 mass, with contributions exceeding 50 %. However, when the air quality is severely polluted, the PM2.5 contribution of nonlocal emissions is around 75 %. Nonlocal emissions also dominate Tianjin's air quality, with average PM2.5 contributions exceeding 65 %. The PM2.5 level in Hebei and Shandong is generally controlled by local emissions, but in Henan, local and nonlocal emissions play an almost equivalent role in the PM2.5 level, except when the air quality is severely polluted, with nonlocal PM2.5 contributions of over 60 %. Additionally, the primary aerosol species are generally dominated by local emissions, with the average contribution exceeding 50 %. However, the source apportionment of secondary aerosols shows more evident regional characteristics. Therefore, except for cooperation with neighboring provinces to carry out strict emission mitigation measures, reducing primary aerosols is a priority to alleviate PM pollution in the NCP, especially in Beijing and Tianjin.


2021 ◽  
Vol 13 (17) ◽  
pp. 3457
Author(s):  
Wei Wen ◽  
Song Shen ◽  
Lei Liu ◽  
Xin Ma ◽  
Ying Wei ◽  
...  

For many years, Beijing has suffered from severe air pollution. At present, fine particulate matter (PM2.5) 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 PM2.5; 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 PM2.5 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 PM2.5, respectively. The monthly transport ratio of PM2.5 was 27% and 46% in the winter and summer, respectively. The regional transport of residential and industrial emissions accounted for the highest proportion of PM2.5. 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 PM2.5 and O3 pollution issues.


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