Abstract

Haze is a majorly disastrous type of weather in China, especially central and eastern of China. The development of haze is mainly caused by highly concentrated fine particles (PM2.5) on a regional scale. Here, we present the results from an autumn and winter study conducted from 2013 to 2020 in seven highly polluted areas (27 representative stations) in central and eastern China to analyze the growth mechanism of PM2.5. At the same time, taking Beijing Station as an example, the characteristics of aerosol composition and particle size in the growth phase are analyzed. Taking into account the regional and inter-annual differences of fine particles (PM2.5) distribution, the local average PM2.5 growth value of the year is used as the boundary value for dividing slow, rapid, and explosive growth (only focuses on the hourly growth rate greater than 0). The average value of PM2.5 in the autumn and winter of each regional representative station shows a decreasing trend as a whole, especially after 2017, whereby the decreasing trend was significant. The distribution value of +ΔPM2.5 (PM2.5 hourly growth rate) in the north of the Huai River is lower than that in the south of the Huai River, and both of the +ΔPM2.5 after 2017 showed a significant decreasing trend. The average PM2.5 threshold before the explosive growth is 70.8 µg m−3, and the threshold that is extremely prone to explosive growth is 156 µg m−3 to 277 µg m−3 in north of the Huai River. For the area south of the Huai River, the threshold for PM2.5 explosive growth is relatively low, as a more stringent threshold also puts forward stricter requirements on atmospheric environmental governance. For example, in Beijing, the peak diameters gradually shift to larger sizes when the growth rate increases. The number concentration increasing mainly distributed in Aitken mode (AIM) and Accumulation mode (ACM) during explosive growth. Among the various components of submicron particulate matter (PM1), organic aerosol (OA), especially primary OA (POA), have become one of the most critical components for the PM2.5 explosive growth in Beijing. During the growth period, the contribution of secondary particulate matter (SPM) to the accumulated pollutants is significantly higher than that of primary particulate matter (PPM). However, the proportion of SPM gradually decreases when the growth rate increases. The contribution of the PPM can reach 48% in explosive growth. Compared to slow and rapid growth, explosive growth mainly occurs in the stable atmosphere of higher humidity, lower pressure, lower temperature, small winds, and low mixed layers.

Highlights

  • The study by Zhang et al [14] shows that the unfavorable weather elements in the winter of Beijing-Tianjin-Hebei can cause the PM2.5 concentration to increase by about 40% to 100% compared with other seasons

  • 2.5 mass concentration in the autumn average daily moderate pollution stipulated by the Ministry of Environmental Protection and winter (October of the current year to February of the following year) of 2013–2020 of the People’s Republic of China), and 87% of statistical values exceed 75 μg m−3

  • The highest average value areas where PM2.5 concentration is relatively high in China

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Summary

Introduction

Zhong et al [27] conducted a study of 28 pollution episodes in Beijing from 2013 to 2017 and concluded that a threshold value for PM2.5 explosive growth is 100 μg m−3 in Beijing. This threshold, the positive feedback from aerosols to near-ground radiative cooling to anomalous inversion is effectively triggered. Ground-based PM2.5 observation data and meteorological element data are used to discuss the thresholds and year-on-year changes of PM2.5 in several major polluted areas in China from 2013 to 2020 under three growth mechanisms (slow, rapid, and explosive). At the same time, using the PM chemical composition and particle size distribution data, the contribution of PM composition and size distribution at different rates of pollutant cumulative stage is analyzed

Materials and Methods
Results and Discussion
Average Distribution of PM
Chemical
Conclusions
A Reliability
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