ACPD Atmospheric Chemistry and Physics Discussions ACPD 1680-7375 Copernicus GmbH Göttingen, Germany 10.5194/acpd-11-33465-2011 The impact of circulation patterns on regional transport pathways and air quality over Beijing and its surroundings Zhang J. P. 1 Zhu T. 2 Zhang Q. H. 1 Li C. C. 1 Shu H. L. 1 Ying Y. 1 Dai Z. P. 3 Liu X. Y. 1 Liang A. M. 4 Shen H. X. 4 Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China Shenzhen Academy of Environmental Science, Shenzhen, 518001, China Meteorological Center of North China Air Traffic Management Bureau of CAAC, Beijing, 100621, China 19 12 2011 11 12 33465 33509 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys-discuss.net/11/33465/2011/acpd-11-33465-2011.html The full text article is available as a PDF file from http://www.atmos-chem-phys-discuss.net/11/33465/2011/acpd-11-33465-2011.pdf

This study investigated the air pollution characteristics of synoptic-scale circulation in the Beijing megacity, and provided holistic evaluation of the impacts of circulation patterns on air quality during the 2008 Beijing Summer Olympics. Nine weather circulation types (CTs) were objectively identified over the North China region during 2000–2009, using obliquely rotated T-mode principal component analysis (PCA). The resulting CTs were examined in relation to the local meteorology, regional transport pathways, and air quality parameters, respectively. The FLEXPART-WRF model was used to calculate 48-h backward plume trajectories for each CT. Nine CTs were characterized, with distinct local meteorology and air mass origins. CT 1 (high to the west with a strong pressure gradient) was characterized by a northwestern origin, with the smallest local and southeasterly air mass sources, and CT 6 (high to the northwest) had air mass sources mostly from the north and east. In contrast, CTs 5, 8, and 9 (unique, high to the east, and low to the northwest, respectively) were characterized by southern and southeastern trajectories, which indicated a greater influence of high pollutant emission sources. In turn, poor air quality in Beijing (high loadings of PM<sub>10</sub>, BC, SO<sub>2</sub>, NO<sub>2</sub>, O<sub>3</sub>, AOD, and low visibility) was associated with these CTs. Good air quality in Beijing was associated with CTs 1 and 6. The average visibilities (with ±1 σ) in Beijing for CTs 1 and 6 during 2000–2009 were 18.5 ± 8.3 km and 14.3 ± 8.5 km, respectively. In contrast, poor visibility values of 6.0 ± 3.5 km, 6.6 ± 3.7 km, and 6.7 ± 3.6 km were found in CTs 5, 8, and 9, respectively. The mean concentrations of PM<sub>10</sub> for CTs 1, 6, 5, 8, and 9 during 2005–2009 were 90.3 ± 76.3 μg m<sup>−3</sup>, 111.7 ± 89.6 μg m<sup>−3</sup>, 173.4 ± 105.8 μg m<sup>−3</sup>, 158.4 ± 90.0 μg m<sup>−3</sup>, and 151.2 ± 93.1 μg m<sup>−3</sup>, respectively. <br><br> Analysis of the relationship between circulation pattern and air quality during the emission control period suggests that CTs are the primary drivers of day-to-day variations in pollutant concentrations over Beijing and its vicinity. During the Olympics period, the frequency of CT 6 was twice that of the mean in August from 2000 to 2009. This CT had northerly transport pathways and favorable meteorological conditions (e.g. frequent precipitation) for clean air during the Olympics. Assuming that relationships between CTs and air quality parameters in the same season (month) were constant in different years, the relative contributions of synoptic circulation to decreases in PM<sub>10</sub>, BC, SO<sub>2</sub>, NO<sub>2</sub>, CO, AOD, and horizontal light extinction during the Olympics were estimated as 19 ± 14%, 18 ± 13%, 41 ± 36%, 12 ± 7%, 19 ± 11%, 25 ± 28%, and 50 ± 46%, respectively.

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