Abstract
Abstract. Strict emission controls were implemented in Beijing and adjacent provinces to ensure good air quality during the 2015 China Victory Day parade. Here, we conducted synchronous measurements of submicron aerosols (PM1) at ground level and 260 m on a meteorological tower by using a high-resolution aerosol mass spectrometer and an aerosol chemical speciation monitor, respectively, in Beijing from 22 August to 30 September. Our results showed that the average PM1 concentrations are 19.3 and 14.8 µg m−3 at ground level and 260 m, respectively, during the control period (20 August–3 September), which are 57 and 50 % lower than those after the control period (4–30 September). Organic aerosols (OAs) dominated PM1 during the control period at both ground level and 260 m (55 and 53 %, respectively), while their contribution showed substantial decreases (∼ 40 %) associated with an increase in secondary inorganic aerosols (SIAs) after the parade, indicating a larger impact of emission controls on SIA than OA. Positive matrix factorization of OA further illustrated that primary OA (POA) showed similar decreases as secondary OA (SOA) at both ground level (40 % vs. 42 %) and 260 m (35 % vs. 36 %). However, we also observed significant changes in SOA composition at ground level. While the more oxidized SOA showed a large decrease by 75 %, the less oxidized SOA was comparable during (5.6 µg m−3) and after the control periods (6.5 µg m−3). Our results demonstrated that the changes in meteorological conditions and PM loadings have affected SOA formation mechanisms, and the photochemical production of fresh SOA was more important during the control period. By isolating the influences of meteorological conditions and footprint regions in polluted episodes, we found that regional emission controls on average reduced PM levels by 44–45 %, and the reductions were close among SIA, SOA and POA at 260 m, whereas primary species showed relatively more reductions (55–67 %) than secondary aerosol species (33–44 %) at ground level.
Highlights
Beijing, the capital of China, with ∼ 21.71 million people in the metropolitan area (Beijing Municipal Bureau of Statistics, http://www.bjstats.gov.cn/tjsj/yjdsj/rk/ 2015/201603/t20160317_339143.html), has been suffering from severe air pollution during the past decade
Back-trajectory analysis showed that high PM1 mass concentrations were often associated with air masses from the south and southwest, and the composition was characterized by high fractions of oxidized OA and secondary inorganic aerosols (SIAs are a combination of sulfate, nitrate and ammonium), whereas primary species emitted from local sources were the dominant contributors during clean events (Huang et al, 2010; Sun et al, 2010, 2012; Zhang et al, 2015a)
The sampling site is located at the tower branch of the Institute of Atmospheric Physics (IAP), CAS (39◦58 28 N, 116◦22 16 E; 49 m.a.s.l.), which is a typical urban site that is subject to influences from local traffic and cooking emissions nearby
Summary
The capital of China, with ∼ 21.71 million people in the metropolitan area (Beijing Municipal Bureau of Statistics, http://www.bjstats.gov.cn/tjsj/yjdsj/rk/ 2015/201603/t20160317_339143.html), has been suffering from severe air pollution during the past decade Results showed that stagnant meteorological conditions, local emissions, regional transport and secondary production were four major factors leading to the formation of severe haze episodes in Beijing in winter (Sun et al, 2014; Zhang et al, 2014; Liu et al, 2016). Secondary species showed substantial reductions at ground level, ranging from 35 to 69 %, yet the reductions in primary species were much smaller (Xu et al, 2015) These studies highlight the importance of regional emission controls in decreasing secondary aerosol precursors, and suppressing the formation of secondary aerosols, yet a more strict local emission control is needed. The sources of aerosol particle species during and after the control period were investigated with FLEXPART analysis and bivariate polar analysis
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