ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-12-5031-2012 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 Wang X. 1 Liu X. Y. 1 Liang A. M. 4 Shen H. X. 4 Yi B. Q. 5 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 Department of Atmospheric Sciences, Texas A & M University, College Station, TX 77845, USA 07 06 2012 12 11 5031 5053 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.net/12/5031/2012/acp-12-5031-2012.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/12/5031/2012/acp-12-5031-2012.pdf

This study investigated the air pollution characteristics of synoptic-scale circulation in the Beijing megacity, and provided quantitative 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. Each CT was characterized with distinct local meteorology and air mass origin. CT 1 (high pressure to the west with a strong pressure gradient) was characterized by a northwestern air mass origin, with the smallest local and southeasterly air mass sources, and CT 6 (high pressure to the northwest) had air mass sources mostly from the north and east. On the contrary, CTs 5, 8, and 9 (weak pressure field, high pressure to the east, and low pressure 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>, NO<sub>x</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&sigma;) 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, low 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 are fixed 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>, NO<sub>x</sub>, CO, and horizontal light extinction during the Olympics were estimated as 19 ± 14%, 18 ± 13%, 41 ± 36%, 12 ± 7%, 10 ± 5%, 19 ± 11%, and 54 ± 25%, respectively.

 References Aiken, A. C., de Foy, B., Wiedinmyer, C., DeCarlo, P. F., Ulbrich, I. M., Wehrli, M. N., Szidat, S., Prevot, A. S. H., Noda, J., Wacker, L., Volkamer, R., Fortner, E., Wang, J., Laskin, A., Shutthanandan, V., Zheng, J., Zhang, R., Paredes-Miranda, G., Arnott, W. P., Molina, L. T., Sosa, G., Querol, X., and Jimenez, J. L.: Mexico city aerosol analysis during MILAGRO using high resolution aerosol mass spectrometry at the urban supersite (T0) – Part 2: Analysis of the biomass burning contribution and the non-fossil carbon fraction, Atmos. Chem. Phys., 10, 5315–5341, http://dx.doi.org/10.5194/acp-10-5315-2010doi:10.5194/acp-10-5315-2010, 2010. An, X., Zhu, T., Wang, Z., Li, C., and Wang, Y.: A modeling analysis of a heavy air pollution episode occurred in Beijing, Atmos. Chem. Phys., 7, 3103–3114, http://dx.doi.org/10.5194/acp-7-3103-2007doi:10.5194/acp-7-3103-2007, 2007. Ashbaugh,~L L., Malm,~W C., and Sadeh,~W Z.: A~residence time probability analysis of sulfur concentrations at Grand Canyon National Park, Atmos. Environ., 19, 1263–1270, 1985. Atkinson, R. W., Fuller, G. W., Anderson, H. R., Harrison, R. M., and Armstrong, B.: Urban ambient particle metrics and health: a time-series analysis, Epidemiology, 21, 501–511, 2010. Bardossy,~A., Duckstein,~L., and Bogardi,~I.: Fuzzy rule based classification of atmospheric circulation patterns, Int J. Climatol., 15, 1087–1097, 1995. Bäumer,~D., Vogel,~B., Versick,~S., Rinke,~R., Möhler,~O., and Schnaiter,~M.: Relationship of visibility, aerosol optical thickness and aerosol size distribution in an ageing air mass over South-West Germany, Atmos. Environ., 42, 989–998, 2008. Bernaards,~C A. and Jennrich,~R I.: Gradient projection algorithms and software for arbitrary rotation criteria in factor analysis, Educ. Psychol. Meas., 65, 770–790, 2005. Brinkmann,~W.: Application of non-hierarchically clustered circulation components to surface weather conditions: Lake Superior Basin winter temperatures, Theor. Appl. Climatol., 63, 41–56, 1999. Cavazos,~T.: Using self-organizing maps to investigate extreme climate events: an application to wintertime precipitation in the Balkans,~J. Climate, 13, 1718–1732, 2000. Chan,~C K. and Yao,~X.: Air pollution in mega cities in China, Atmos. Environ., 42, 1–42, 2008. Chen, D. S., Cheng, S. Y., Liu, L., Chen, T., and Guo, X. R.: An integrated MM5-CMAQ modeling approach for assessing trans-boundary PM10 contribution to the host city of 2008 Olympic summer games-Beijing, China, Atmos. Environ., 41, 1237–1250, doi:10.1016/j.atmosenv.2006.09.045, 2007. Chen,~F., Tewari,~M., Kusaka,~H., and Warner,~T.: Current status of urban modeling in the community Weather Research and Forecast (WRF) model, paper presented at Joint Session with Sixth Symposium on the Urban Environment and AMS Forum: Managing our Physical and Natural Resources: Successes and Challenges, the 86th AMS Annual Meeting, AMS, Atlanta, Georgia, 28 January–3 February, 2006. Cheng,~W L., Pai,~J L., Tsuang,~B J., and Chen,~C L.: Synoptic patterns in relation to ozone concentrations in West-Central Taiwan, Meteorol. Atmos. Phys., 78, 11–21, 2001. Cheng,~X. and Wallace,~J M.: Cluster analysis of the Northern Hemisphere wintertime 500-hPa height field: spatial patterns,~J. Atmos. Sci., 50, 2674–2696, 1993. Cheng, Y. F., Heintzenberg, J., Wehner, B., Wu, Z. J., Su, H., Hu, M., and Mao, J. T.: Traffic restrictions in Beijing during the Sino-African Summit 2006: aerosol size distribution and visibility compared to long-term in situ observations, Atmos. Chem. Phys., 8, 7583–7594, http://dx.doi.org/10.5194/acp-8-7583-2008doi:10.5194/acp-8-7583-2008, 2008. Chen,~Z., Cheng,~S., Li,~J., Guo,~X., Wang,~W., and Chen,~D.: Relationship between atmospheric pollution processes and synoptic pressure patterns in Northern China, Atmos. Environ., 42, 6078–6087, 2008. Chou, C. C. K., Tsai, C.-Y., Shiu, C.-J., Liu, S. C., and Zhu, T.: Measurement of NO$_\textrmy$ during Campaign of Air Quality Research in Beijing 2006 (CAREBeijing-2006): Implications for the ozone production efficiency of NO$_\textrmx$, J. Geophys. Res., 114, D00G01, http://dx.doi.org/10.1029/2008jd010446doi:10.1029/2008jd010446, 2009. Chou, C. C.-K., Tsai, C.-Y., Chang, C.-C., Lin, P.-H., Liu, S. C., and Zhu, T.: Photochemical production of ozone in Beijing during the 2008 Olympic Games, Atmos. Chem. Phys., 11, 9825–9837, http://dx.doi.org/10.5194/acp-11-9825-2011doi:10.5194/acp-11-9825-2011, 2011. Chu, D. A., Kaufman, Y. J., Zibordi, G., Chern, J. D., Mao, J., Li, C., and Holben, B. N.: Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS), J. Geophys. Res., 108, 4661, http://dx.doi.org/10.1029/2002jd003179doi:10.1029/2002jd003179, 2003. Compagnucci,~R H. and Richman,~M B.: Can principal component analysis provide atmospheric circulation or teleconnection patterns?, Int J. Climatol., 28, 703–726, 2008. Comrie,~A C. and Yarnal,~B.: Relationships between synoptic-scale atmospheric circulation and ozone concentrations in metropolitan Pittsburgh, Pennsylvania, Atmos. Environ., 26, 301–312, 1992. de Foy, B., Clappier, A., Molina, L. T., and Molina, M. J.: Distinct wind convergence patterns in the Mexico City basin due to the interaction of the gap winds with the synoptic flow, Atmos. Chem. Phys., 6, 1249–1265, http://dx.doi.org/10.5194/acp-6-1249-2006doi:10.5194/acp-6-1249-2006, 2006. de Foy, B., Zavala, M., Bei, N., and Molina, L. T.: Evaluation of WRF mesoscale simulations and particle trajectory analysis for the MILAGRO field campaign, Atmos. Chem. Phys., 9, 4419–4438, http://dx.doi.org/10.5194/acp-9-4419-2009doi:10.5194/acp-9-4419-2009, 2009. de Foy, B., Burton, S. P., Ferrare, R. A., Hostetler, C. A., Hair, J. W., Wiedinmyer, C., and Molina, L. T.: Aerosol plume transport and transformation in high spectral resolution lidar measurements and WRF-Flexpart simulations during the MILAGRO Field Campaign, Atmos. Chem. Phys., 11, 3543–3563, http://dx.doi.org/10.5194/acp-11-3543-2011doi:10.5194/acp-11-3543-2011, 2011. Dockery, D. W. and Pope, C. A.: Acute respiratory effects of particulate air pollution, Annu. Rev. Publ. Health, 15, 107–132, 1994. Downs, S. H., Schindler, C., Liu, L. J. S., Keidel, D., Bayer-Oglesby, L., Brutsche, M. H., Gerbase, M. W., Keller, R., Kunzli, N., and Leuenberger, P.: Reduced exposure to PM$_10$ and attenuated age-related decline in lung function, New Engl. J. Med., 357, 2338–2347, 2007. Dudhia,~J.: Numerical study of convection observed during the winter monsoon experiment using a~mesoscale two-dimensional model,~J. Atmos. Sci., 46, 3077–3107, 1989. Eck, T., Holben, B., Reid, J., Dubovik, O., Smirnov, A., O'neill, N., Slutsker, I., and Kinne, S.: Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols, J. Geophys. Res., 104, 31333–31349, 1999. Engel-Cox, J. A., Holloman, C. H., Coutant, B. W., and Hoff, R. M.: Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality, Atmos. Environ., 38, 2495–2509, 2004. Fang,~M., Chan,~C K., and Yao,~X.: Managing air quality in a~rapidly developing nation: China, Atmos. Environ., 43, 79–86, 2009. Fast,~J D. and Easter,~R C.: A~Lagrangian particle dispersion model compatible with WRF, in: 7th WRF User's Workshop, NCAR, P6-02, 19–22 June, Boulder, Colorado, 2006. Fleming, Z. L., Monks, P. S., and Manning, A. J.: Review: Untangling the influence of air-mass history in interpreting observed atmospheric composition, Atmos. Res., 104, 1–39, 2012. Gao, Y., Liu, X., Zhao, C., and Zhang, M.: Emission controls versus meteorological conditions in determining aerosol concentrations in Beijing during the 2008 Olympic Games, Atmos. Chem. Phys., 11, 12437–12451, http://dx.doi.org/10.5194/acp-11-12437-2011doi:10.5194/acp-11-12437-2011, 2011. Gong,~X. and Richman,~M B.: On the application of cluster analysis to growing season precipitation data in North America east of the Rockies,~J. Climate, 8, 897–931, 1995. He, Q., Li, C., Tang, X., Li, H., Geng, F., and Wu, Y.: Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China, Remote Sens. Environ., 114, 1649–1661, 2010. He,~X., Li,~C C., Lau,~A K H., Deng,~Z Z., Mao,~J T., Wang,~M H., and Liu,~X Y.: An intensive study of aerosol optical properties in Beijing urban area, Atmos. Chem. Phys., 9, 8903–8915, http://dx.doi.org/10.5194/acp-9-8903-2009doi:10.5194/acp-9-8903-2009, 2009. Hewitson,~B. and Crane,~R.: Self-organizing maps: applications to synoptic climatology, Clim. Res., 22, 13–26, 2002. Highwood,~E J. and Kinnersley,~R P.: When smoke gets in our eyes: the multiple impacts of atmospheric black carbon on climate, air quality and health, Environ. Int., 32, 560–566, 2006. Holben, B., Eck, T., Slutsker, I., Tanre, D., Buis, J., Setzer, A., Vermote, E., Reagan, J., Kaufman, Y., and Nakajima, T.: AERONET – A federated instrument network and data archive for aerosol characterization, Remote Sens. Environ., 66, 1–16, 1998. Hong,~S Y., Dudhia,~J., and Chen,~S H.: A~revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation, Mon. Weather Rev., 132, 103–120, 2004. Huth,~R.: An example of using obliquely rotated principal components to detect circulation types over Europe, Meteorol Z., 2, 285–293, 1993. Huth,~R.: Properties of the circulation classification scheme based on the rotated principal component analysis, Meteorol. Atmos. Phys., 59, 217–233, 1996a. Huth,~R.: An intercomparison of computer-assisted circulation classification methods, Int J. Climatol., 16, 893–922, 1996b. Huth,~R.: A~circulation classification scheme applicable in GCM studies, Theor. Appl. Climatol., 67, 1–18, 2000. Huth,~R., Beck,~C., Philipp,~A., Demuzere,~M., Ustrnul,~Z., Cahynová,~M., Kysel\'y,~J., and Tveito,~O E.: Classifications of atmospheric circulation patterns, Ann NY Acad. Sci., 1146, 105–152, 2008. Jacobeit,~J.: Classifications in climate research, Phys. Chem. Earth, 35, 411–421, 2010. Janji$\acute\textrmc$,~Z I.: Nonsingular implementation of the Mellor–Yamada level 2.5 scheme in the NCEP Meso model, Office Note #437, National Center for Environmental Prediction, 2001. Jansen,~K L., Larson,~T V., Koenig,~J Q., Mar,~T F., Fields,~C., Stewart,~J., and Lippmann,~M.: Associations between health effects and particulate matter and black carbon in subjects with respiratory disease, Environ. Health Persp., 113, 1741–1746, 2005. Jiang,~N., Hay,~J., and Fisher,~G.: Synoptic weather types and morning rush hour nitrogen oxides concentrations during Auckland winters, Weather Clim., 25, 43–69, 2005. Jiménez, P. A., González-Rouco, J. F., García-Bustamante, E., Navarro, J., Montávez, J. P., de Arellano, J. V.-G., Dudhia, J., and Muñoz-Roldan, A.: Surface Wind Regionalization over Complex Terrain: Evaluation and Analysis of a High-Resolution WRF Simulation, J. Appl. Meteorol. Clim., 49, 268–287, http://dx.doi.org/10.1175/2009jamc2175.1doi:10.1175/2009jamc2175.1, 2010. Jiménez, P., González-Rouco, J., Montávez, J., García-Bustamante, E., Navarro, J., and Dudhia, J.: Analysis of the long-term surface wind variability over complex terrain using a high spatial resolution WRF simulation, Clim. Dyn., 1–14, 2012. Kahl,~J D. and Samson,~P J.: Uncertainty in trajectory calculations due to low resolution meteorological data,~J. Clim. Appl. Meteorol., 25, 1816–1831, 1986. Kain,~J S.: The Kain Fritsch convective parameterization: an update,~J. Appl. Meteorol., 43, 170–181, 2004. Kalkstein,~L S. and Corrigan,~P.: A~synoptic climatological approach for geographical analysis: assessment of sulfur dioxide concentrations, Ann. Assoc. Am. Geograph., 76, 381–395, 1986. Kaufman, Y. J. and Tanré, D.: Algorithm for remote sensing of tropospheric aerosol from MODIS, NASA MODIS Algorithm Theoretical Basis Document, Goddard Space Flight Center, 85, 1998. Levy, I., Mahrer, Y., and Dayan, U.: Coastal and synoptic recirculation affecting air pollutants dispersion: A numerical study, Atmos. Environ., 43, 1991, 2009. Levy, R., Remer, L., Martins, J., Kaufman, Y., Plana-Fattori, A., Redemann, J., and Wenny, B.: Evaluation of the MODIS aerosol retrievals over ocean and land during CLAMS, J. Atmos. Sci., 62, 974–992, 2005. Li, B., Yuan, H., Feng, N., and Tao, S.: Comparing MODIS and AERONET aerosol optical depth over China, Int. J. Remote Sens., 30, 6519-6529, 2009. Li,~C., Mao,~J., Lau,~A., Yuan,~Z., Wang,~M., and Liu,~X.: Application of MODIS satellite products to the air pollution research in Beijing, Sci. China Ser. D, 48, 209–219, 2005. Li, P., Li, X., Yang, C., Wang, X., Chen, J., and Collett, J. L.: Fog water chemistry in Shanghai, Atmos. Environ., 45, 4034, 2011. Lin, J. C., Brunner, D., and Gerbig, C.: Studying atmospheric transport through Lagrangian models, Eos Trans. AGU, 92, http://dx.doi.org/10.1029/2011eo210001doi:10.1029/2011eo210001, 2011.Liu, P., Zhao, C., Zhang, Q., Deng, Z., Huang, M., Ma, X., and Tie, X.: Aircraft study of aerosol vertical distributions over Beijing and their optical properties, Tellus B, 61, 756–767, http://dx.doi.org/10.1111/j.1600-0889.2009.00440.xdoi:10.1111/j.1600-0889.2009.00440.x, 2009. Lin,~W., Zhu,~T., Huang,~W., Hu,~M., Brunekreef,~B., Zhang,~Y., Liu,~X., Cheng,~H., Gehring,~U., Li,~C., and Tang,~X.: Acute respiratory inflammation in children and black carbon in ambient air before and during the 2008 Beijing Olympics, Environ. Health Persp., 119, 1507–1512, http://dx.doi.org/10.1289/ehp.1103461doi:10.1289/ehp.1103461, 2011. Liu, P., Zhao, C., Zhang, Q., Deng, Z., Huang, M., Ma, X., and Tie, X.: Aircraft study of aerosol vertical distributions over Beijing and their optical properties, Tellus B, 61, 756–767, doi:10.1111/j.1600-0889.2009.00440.x, 2009. Liu, P., Zhao, C., Göbel, T., Hallbauer, E., Nowak, A., Ran, L., Xu, W., Deng, Z., Ma, N., and Mildenberger, K.: Hygroscopic properties of aerosol particles at high relative humidity and their diurnal variations in the North China Plain, Atmos. Chem. Phys, 11, 3479–3494, 2011. Lo, J. C.-F., Yang, Z.-L., and Pielke, R. A., Sr.: Assessment of three dynamical climate downscaling methods using the Weather Research and Forecasting (WRF) model, J. Geophys. Res., 113, D09112, http://dx.doi.org/10.1029/2007jd009216doi:10.1029/2007jd009216, 2008. Lund,~I.: Map-pattern classification by statistical techniques,~J. Appl. Meteorol., 2, 56–65, 1963. Magari, S. R., Hauser, R., Schwartz, J., Williams, P. L., Smith, T. J., and Christiani, D. C.: Association of heart rate variability with occupational and environmental exposure to particulate air pollution, Circulation, 104, 986, 2001. McGregor,~G R. and Bamzelis,~D.: Synoptic typing and its application to the investigation of weather air pollution relationships, Birmingham, United Kingdom, Theor. Appl. Climatol., 51, 223–236, 1995. Mijling,~B.: Reductions of NO<sub>2</sub> detected from space during the 2008 Beijing Olympic Games, Geophys. Res. Lett., 36, L13801, http://dx.doi.org/10.1029/2009GL038943doi:10.1029/2009GL038943, 2009. Molina, M. J. and Molina, L. T.: Megacities and atmospheric pollution, J. Air Waste Manage. Assoc, 54, 644–680, 2004. Mlawer,~E J., Taubman,~S J., Brown,~P D., Iacono,~M J., and Clough,~S A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a~validated correlated-k model for the longwave,~J. Geophys. Res., 102, 16663–16682, http://dx.doi.org/10.1029/97JD00237doi:10.1029/97JD00237, 1997. Müller,~G V., Compagnucci,~R., Nuñez,~M N., and Salles,~A.: Surface circulation associated with frost in the wet pampas, Int J. Climatol., 23, 943–961, 2003. Pagano,~L E., Sims,~A P., and Boyles,~R P.: A~comparative study between FLEXPART-WRF and HYSPLIT in an operational setting: analysis of fire emissions across complex geography using WRF, M.Sc. Thesis, North Carolina State University, Raleigh, North Carolina, 2010. Pan, Z., Takle, E., Gutowski, W., and Turner, R.: Long Simulation of Regional Climate as a Sequence of Short Segments, Mon. Weather Rev., 127, 308–321, 1999. Patel,~M M., Chillrud,~S N., Correa,~J C., Hazi,~Y., Feinberg,~M., Kc,~D., Prakash,~S., Ross,~J M., Levy,~D., and Kinney,~P L.: Traffic-related particulate matter and acute respiratory symptoms among New York City Area adolescents, Environ. Health Persp., 118, 1338–1343, http://dx.doi.org/10.1289/ehp.0901499doi:10.1289/ehp.0901499, 2010. Philipp,~A., Bartholy,~J., Beck,~C., Erpicum,~M., Esteban,~P., Fettweis,~X., Huth,~R., James,~P., Jourdain,~S., and Kreienkamp,~F.: COST733CAT-a~database of weather and circulation type classifications, Phys. Chem. Earth, 35, 360–373, 2010. Pope Iii, C. A. and Dockery, D. W.: Health effects of fine particulate air pollution: lines that connect, J. Air Waste Manage., 56, 709–742, 2006. Quan, J., Zhang, Q., He, H., Liu, J., Huang, M., and Jin, H.: Analysis of the formation of fog and haze in North China Plain (NCP), Atmos. Chem. Phys. Discuss., 11, 11911–11937, http://dx.doi.org/10.5194/acpd-11-11911-2011doi:10.5194/acpd-11-11911-2011, 2011. Ramanathan, V. and Carmichael, G.: Global and regional climate changes due to black carbon, Nat. Geosci., 1, 221–227, 2008. Richman,~M B.: Obliquely rotated principal components: an improved meteorological map typing technique?,~J. Appl. Meteorol., 20, 1145–1159, 1981. Shahgedanova,~M., Burt,~T., and Davies,~T.: Synoptic climatology of air pollution in Moscow, Theor. Appl. Climatol., 61, 85–102, 1998. Sloane,~C S.: Summertime visibility declines: meteorological influences, Atmos. Environ., 17, 763–774, 1983. Sloane,~C S.: Meteorologically adjusted air quality trends: visibility, Atmos. Environ., 18, 1217–1229, 1984. Smirnov, A., Holben, B., Eck, T., Dubovik, O., and Slutsker, I.: Cloud-screening and quality control algorithms for the AERONET database, Remote Sens. Environ., 73, 337–349, 2000. Stohl,~A.: Computation, accuracy and applications of trajectories~–~a~review and bibliography, Atmos. Environ., 32, 947–966, 1998. Stohl,~A., Hittenberger,~M., and Wotawa,~G.: Validation of the Lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data, Atmos. Environ., 32, 4245–4264, 1998. Stohl,~A., Forster,~C., Frank,~A., Seibert,~P., and Wotawa,~G.: Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461–2474, http://dx.doi.org/10.5194/acp-5-2461-2005doi:10.5194/acp-5-2461-2005, 2005. Sun,~Y., Wang,~Y., and Zhang,~C.: Vertical observations and analysis of PM$_2.5$, O<sub>3</sub>, and NO$_\textrmx$ at Beijing and Tianjin from towers during summer and autumn 2006, Adv. Atmos. Sci., 27, 123–136, 2010. Tang,~G., Li,~X., Wang,~Y., Xin,~J., and Ren,~X.: Surface ozone trend details and interpretations in Beijing, 2001–2006, Atmos. Chem. Phys., 9, 8813–8823, http://dx.doi.org/10.5194/acp-9-8813-2009doi:10.5194/acp-9-8813-2009, 2009. Vucetic, S., Han, B., Mi, W., Li, Z., and Obradovic, Z.: A Data-Mining Approach for the Validation of Aerosol Retrievals, Geosci. Remote Sens. Lett., IEEE, 5, 113-117, 2008. Wang, B., Shao, M., Lu, S. H., Yuan, B., Zhao, Y., Wang, M., Zhang, S. Q., and Wu, D.: Variation of ambient non-methane hydrocarbons in Beijing city in summer 2008, Atmos. Chem. Phys., 10, 5911–5923, http://dx.doi.org/10.5194/acp-10-5911-2010doi:10.5194/acp-10-5911-2010, 2010. Wang, C.: A modeling study on the climate impacts of black carbon aerosols, J. Geophys. Res., 109, D03106, http://dx.doi.org/10.1029/2003jd004084doi:10.1029/2003jd004084, 2004. Wang,~M., Zhu,~T., Zheng,~J., Zhang,~R Y., Zhang,~S Q., Xie,~X X., Han,~Y Q., and Li,~Y.: Use of a mobile laboratory to evaluate changes in on-road air pollutants during the Beijing 2008 Summer Olympics, Atmos. Chem. Phys., 9, 8247–8263, http://dx.doi.org/10.5194/acp-9-8247-2009doi:10.5194/acp-9-8247-2009, 2009. Wang, M., Zhu, T., Zhang, J. P., Zhang, Q. H., Lin, W. W., Li, Y., and Wang, Z. F.: Using a mobile laboratory to characterize the distribution and transport of sulfur dioxide in and around Beijing, Atmos. Chem. Phys., 11, 11631–11645, doi:10.5194/acp-11-11631-2011, 2011. Wang,~S., Zhang,~J., Zeng,~X., Zeng,~Y., Wang,~S., and Chen,~S.: Association of traffic-related air pollution with children's neurobehavioral functions in Quanzhou, China, Environ. Health Persp., 117, 1612–1618, http://dx.doi.org/10.1289/ehp.0800023doi:10.1289/ehp.0800023, 2009. Wang,~S., Zhao,~M., Xing,~J., Wu,~Y., Zhou,~Y., Lei,~Y., He,~K., Fu,~L., and Hao,~J.: Quantifying the air pollutants emission reduction during the 2008 Olympic Games in Beijing, Environ. Sci. Technol., 44, 2490–2496, 2010. Wang,~T., Nie,~W., Gao,~J., Xue,~L K., Gao,~X M., Wang,~X F., Qiu,~J., Poon,~C N., Meinardi,~S., Blake,~D., Wang,~S L., Ding,~A J., Chai,~F H., Zhang,~Q Z., and Wang,~W X.: Air quality during the 2008 Beijing Olympics: secondary pollutants and regional impact, Atmos. Chem. Phys., 10, 7603–7615, http://dx.doi.org/10.5194/acp-10-7603-2010doi:10.5194/acp-10-7603-2010, 2010. Wang,~Y., Hao,~J., McElroy,~M B., Munger,~J W., Ma,~H., Chen,~D., and Nielsen,~C P.: Ozone air quality during the 2008 Beijing Olympics: effectiveness of emission restrictions, Atmos. Chem. Phys., 9, 5237–5251, http://dx.doi.org/10.5194/acp-9-5237-2009doi:10.5194/acp-9-5237-2009, 2009. %Wang, Y., Konopka, P., Liu, Y., Chen, H., Müller, R., Plöger, F., %Riese, M., Cai, Z., and Lü, D.: Tropospheric ozone trend over Beijing %from 2002–2010: ozonesonde measurements and modeling analysis, Atmos. Chem. %Phys. Discuss., 12, 11175-11199, http://dx.doi.org/10.5194/acpd-12-11175-2012doi:10.5194/acpd-12-11175-2012, 2012. Wang, Y., Konopka, P., Liu, Y., Chen, H., Müller, R., Plöger, F., Riese, M., Cai, Z., and Lü, D.: Tropospheric ozone trend over Beijing from 2002–2010: ozonesonde measurements and modeling analysis, Atmos. Chem. Phys. Discuss., 12, 11175–11199, http://dx.doi.org/10.5194/acpd-12-11175-2012doi:10.5194/acpd-12-11175-2012, 2012. Wehner, B., Birmili, W., Ditas, F., Wu, Z., Hu, M., Liu, X., Mao, J., Sugimoto, N., and Wiedensohler, A.: Relationships between submicrometer particulate air pollution and air mass history in Beijing, China, 2004–2006, Atmos. Chem. Phys., 8, 6155–6168, http://dx.doi.org/10.5194/acp-8-6155-2008doi:10.5194/acp-8-6155-2008, 2008. Wei,~P., Cheng,~S., Li,~J., and Su,~F.: Impact of boundary-layer anticyclonic weather system on regional air quality, Atmos. Environ., 45, 2453–2463, http://dx.doi.org/10.1016/j.atmosenv.2011.01.045doi:10.1016/j.atmosenv.2011.01.045, 2011. Witte,~J., Schoeberl,~M., Douglass,~A., Gleason,~J., Krotkov,~N., Gille,~J., Pickering,~K., and Livesey,~N.: Satellite observations of changes in air quality during the 2008 Beijing Olympics and Paralympics, Geophys. Res. Lett., 36, L17803, http://dx.doi.org/10.1029/2009gl039236doi:10.1029/2009gl039236, 2009. Xia, X., Chen, H., Wang, P., Zhang, W., Goloub, P., Chatenet, B., Eck, T., and Holben, B.: Variation of column-integrated aerosol properties in a Chinese urban region, J. Geophys. Res., 111, D05204, http://dx.doi.org/10.1029/2005JD006203doi:10.1029/2005JD006203, 2006. Yarnal,~B.: Synoptic climatology in environmental analysis: a~primer, Belhaven Press, London, 1993. Žagar, N., Žagar, M., Cedilnik, J., Gregori$\checkc$, G., and Rakovec, J.: Validation of mesoscale low-level winds obtained by dynamical downscaling of ERA40 over complex terrain, Tellus A, 58, 445–455, http://dx.doi.org/10.1111/j.1600-0870.2006.00186.xdoi:10.1111/j.1600-0870.2006.00186.x, 2006. Zhang, Q. H., Zhang, J. P., and Xue, H. W.: The challenge of improving visibility in Beijing, Atmos. Chem. Phys., 10, 7821–7827, http://dx.doi.org/10.5194/acp-10-7821-2010doi:10.5194/acp-10-7821-2010, 2010. Zhang, Q., Streets, D. G., Carmichael, G. R., He, K. B., Huo, H., Kannari, A., Klimont, Z., Park, I. S., Reddy, S., Fu, J. S., Chen, D., Duan, L., Lei, Y., Wang, L. T., and Yao, Z. L.: Asian emissions in 2006 for the NASA INTEX-B mission, Atmos. Chem. Phys., 9, 5131–5153, http://dx.doi.org/10.5194/acp-9-5131-2009doi:10.5194/acp-9-5131-2009, 2009. Zhang,~J., Mauzerall,~D L., Zhu,~T., Liang,~S., Ezzati,~M., and Remais,~J V.: Environmental health in China: progress towards clean air and safe water, The Lancet, 375, 1110–1119, 2010. Zhang,~X., Wang,~Y., Lin,~W., Zhang,~Y., Zhang,~X., Zhao,~P., Yang,~Y., Wang,~J., Hou,~Q., and Che,~H.: Changes of atmospheric composition and optical properties over BEIJING-2008 Olympic monitoring campaign, B. Am. Meteorol. Soc., 90, 1633–1651, 2009. Zhu, C., Wang, B., and Qian, W.: Why do dust storms decrease in northern China concurrently with the recent global warming?, Geophys. Res. Lett., 35, L18702, http://dx.doi.org/10.1029/2008gl034886doi:10.1029/2008gl034886, 2008.