Insights into particulate matter pollution in the North China Plain during wintertime: local contribution or regional transport?

Abstract

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.

Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data

“…A meta-analysis of multiple cases of heavy haze episodes from 2013 to 2020 (population-weighted mean PM 2.5 = 155.6 μg/m 3 ) illustrates that SIA fractions varied from 39.8% to 49.8%, with an average of 45.9%, of which NO 3 – and SO 4 2– were the two dominant components, accounting for 18.2% and 16.2% of the total PM 2.5 mass, respectively (Table S5). This suggests the important role of these two PM 2.5 components in regional pollution due to intensive anthropogenic emissions . The continuous growth of SIA fractions (slope = 1.46%, R 2 = 0.87) became the main driver for winter haze in the NCP.…”

“…This suggests the important role of these two PM 2.5 components in regional pollution due to intensive anthropogenic emissions. 86 The continuous growth of SIA fractions (slope = 1.46%, R 2 = 0.87) became the main driver for winter haze in the NCP. In particular, NO 3 − (slope = 0.96%, R 2 = 0.72) became increasingly prominent over SO 4 2− (slope = 0.17%, R 2 = 0.18), with their rapid rises proving to be the key factors for the explosive growth of PM 2.5 pollution.…”

Measurement report: Spatiotemporal and policy-related variations of PM<sub>2.5</sub> compositions and sources during 2015–2019 at multisite of a Chinese megacity

“…According to previous studies, NO3 -, SO4 2and NH4 + are indicative species of secondary reactions (Richard et al, 2011;Wu et al, 2021). Consequently, factor 4 represented the secondary particle source, contributing 39.7% of PM2.5.…”

Spatial variability of air pollutants in a megacity characterized by mobile measurements: Chemical homogeneity under haze conditions

“…The similar chemical composition across the city is consistent with the understanding of haze evolution in NCP during which regional transport becomes a main contributor to the PM pollution in Beijing. Over 60% of the PM1 and PM2.5 mass in Beijing can be contributed by regional transport during the winter haze episodes (Sun et al, 2014;Wu et al, 2021). The similar particle composition may suggest a chemical homogeneity on the megacity scale, and the north-south difference in mass concentration is perhaps driven by the differences in atmospheric dilution on the intracity scale (Sun et al, 2016;Chen et al, 2020).…”