Environmental Science and Pollution Research

, Volume 23, Issue 5, pp 4509–4521 | Cite as

Impact of emission control on PM2.5 and the chemical composition change in Beijing-Tianjin-Hebei during the APEC summit 2014

  • Wei Wen
  • Shuiyuan Cheng
  • Xufeng Chen
  • Gang Wang
  • Song Li
  • Xiaoqi Wang
  • Xiaoyu Liu
Research Article


The success of the emission reduction measures undertaken by authorities in the Asia-Pacific Economic Cooperation summit 2014 demonstrated that the Beijing-Tianjin-Hebei air quality can be improved by introducing integrated emission reduction measures. This paper combines observation data, emission reduction measures, and air quality simulations that were applied before, during, and after the emission control measure implement to analyze the chemical composition change and relationship between emissions and concentrations of pollutants in region. The 24-h PM2.5 samples were collected in the city Beijing, Shijiazhuang, and Tangshan during the period of 20 October to 25 November, 2014. The total PM2.5 mass was measured. PM2.5 samples were used for the analysis of inorganic elements, selected ions, and organic carbon (OC) and element carbon (EC). PM2.5 concentrations during the emission control period were decreased. Total PM2.5 concentrations were reduced by 54, 26, and 39 % when compared to non-emission control period in Beijing, Shijiazhuang, and Tangshan. The average element concentrations were reduced significantly by 75 % in Beijing, 37 % in Shijiazhuang, and 36 % in Tangshan. After the Asia-Pacific Economic Cooperation (APEC) conference, the average element concentration increased. At both cities, the concentration secondary water-soluble ions, primary carbon, and element carbon were reduced. However, the concentration of secondary carbon species increased in Beijing due to photochemical oxidants change. More stringent control of regional emissions will be needed for significant reductions of fine particulate pollution in the region to continue to improve air quality.


AEPC summit PM2.5 emission control Chemical composition Emission control assessment 



This research was supported by the Natural Sciences Foundation of China, the Ministry of Environmental Protection Special Funds for Scientific Research on Public Causes (Nos. 201409006 and 201409007), the “Beijing Science and Technology Project” of the Beijing Municipal Science and Technology Commission (No. Z141108001314048). The authors are grateful to the editors and the anonymous reviewers for their insightful comments.


  1. Beijing Municipal Environmental Protection Bureau (2014) Air pollution prevention and control (action plan). Accessed 1 Jan. 2015
  2. Binkowski FS, Roselle SJ (2003) Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component 1. Model description. J Geophys Res 108:4183. doi: 10.1029/2001JD001409, D6 CrossRefGoogle Scholar
  3. Bureau of Statistics of Beijing (2012) Beijing Statistical Yearbook 2012. China Statistical Press, BeijingGoogle Scholar
  4. Bureau of Statistics of Shijiazhuang (2012) Shijiazhuang Statistical Yearbook 2012. China Statistical Press, BeijingGoogle Scholar
  5. Bureau of Statistics of Tangshan (2012) Tangshan Statistical Yearbook 2012. China Statistical Press, BeijingGoogle Scholar
  6. Castro LM, Pio CA, Harrison RM, Smith DJT (1999) Carbonaceous aerosol in urban and rural European atmospheres: estimation of secondary organic carbon concentrations. Atmos Environ 33:2771–2781CrossRefGoogle Scholar
  7. Chen F, Dudhia J (2001) Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev 129:569–585CrossRefGoogle Scholar
  8. Cheng SY, Zhou Y, Li JB, Lang JL, Wang HY (2012) A new statistical modeling and optimization framework for establishing high-resolution PM10 emission inventory I Stepwise regression model development and application. Atmos Environ 60:613–622CrossRefGoogle Scholar
  9. China National Environmental Monitoring Center (2014) The real time of city air quality publishing platform. Accessed 2 Jan. 2015
  10. China State Council (2013) Air pollution prevention and control (action plan). Accessed 2 Jan. 2015
  11. Chow JC, Watson JG, Lu ZQ (1996) Descriptive analysis of PM2.5 and PM10 at regionally representative locations during SJVAQS/PAUSPEX. Atmos Environ 30:2079–2112CrossRefGoogle Scholar
  12. Cohan DS, Napelenok SL (2011) Air quality response modeling for decision support. Atmos Chem Phys 2:407–425Google Scholar
  13. Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a Mesoscale two-dimensional model. J Atmos Sci 46:3077–3107CrossRefGoogle Scholar
  14. Fu XX, Wang XM, Guo H, Cheung KL, Ding X, Zhao XY, He QF, Gao B, Zhang Z, Liu TY, Zhang YL (2014) Trends of ambient fine particles and major chemical components in the Pearl River Delta region: observation at a regional background site in fall and winter. Sci Total Environ 497:274–281CrossRefGoogle Scholar
  15. Gu JX, Bai ZP, Li WF, Wu LP, Liu AX, Dong HY, Xie YY (2011) Chemical composition of PM2.5 during winter in Tianjin, China. Particuology 9:215–221CrossRefGoogle Scholar
  16. He KB, Yang FM, Duan FD, Ma YL (2011) Particulate matter and regional air pollution. Science press, Beijing, China, pp 223–226Google Scholar
  17. Hong SY, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341CrossRefGoogle Scholar
  18. Kain JS (2004) The Kain-Fritsch convective parameterization: an update. J Appl Meteorol Climatol 43:170–181CrossRefGoogle Scholar
  19. Kim KW, Kim YJ, Oh SJ (2001) Visibility impairment during Yellow Sand periods in the urban atmosphere of Kwangju, Korea. Atmos Environ 35:5157–5167CrossRefGoogle Scholar
  20. Lang JL, Cheng SY, Li JB, Chen DS, Zhou Y, Wei X (2013) A monitoring and modeling study to investigate regional transport and characteristics of PM2.5 pollution. Aerosol Air Qual Res 13:943–956. doi: 10.4209/aaqr.2012.09.0242 Google Scholar
  21. Liu XH, Zhang Y, Cheng SH, Xing J, Zhang QA, Streets DG, Jang C, Wang WX, Hao JM (2010a) Understanding of regional air pollution over China using CMAQ, part I performance evaluation and seasonal variation. Atmos Environ 44:2415–2426CrossRefGoogle Scholar
  22. Liu XH, Zhang Y, Xing J, Zhang QA, Wang K, Streets DG, Jang C, Wang WX, Hao JM (2010b) Understanding of regional air pollution over China using CMAQ, part II. Process analysis and sensitivity of ozone and particulate matter to precursor emissions. Atmos Environ 44:3719–3727CrossRefGoogle Scholar
  23. Liu H, Wang XM, Zhang JP, He KB, Wu Y, Xu JY (2013) Emission controls and changes in air quality in Guangzhou during the Asian Games. Atmos Environ 76:81–93CrossRefGoogle Scholar
  24. Manktelow PT, Mann GW, Carslaw KS, Spracklen DV, Chipperfield MP (2007) Regional and global trends in sulfate aerosol since the 1980s. Geophys Res Lett 34, DOI: 10.1126/science.1204531Google Scholar
  25. Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res-Atmos 102:16663–16682Google Scholar
  26. Okuda T, Matsuura S, Yamaguchi D, Umemura T, Hanada E, Orihara H, Tanaka S, He KB, Ma YL, Cheng Y, Liang LL (2011) The impact of the pollution control measures for the 2008 Beijing Olympic Games on the chemical composition of aerosols. Atmos Environ 45:2789–2794CrossRefGoogle Scholar
  27. Provincial Government of HeBei (2013) Air pollution prevention and control (action plan).
  28. Querol X, Viana M, Alastuey A, Amato F, Moreno T (2007) Source origin of trace elements in PM from regional background, urban and industrial sites of Spain. Atmos Environ 41:7219–7231CrossRefGoogle Scholar
  29. The Government of Beijing (2013) Five-year clean air action plan (2013-2017). Accessed 2 Jan. 2015
  30. U.S. Environment Protection Agency (2007) EPA-454/B-07-002. Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional HazeGoogle Scholar
  31. Wang T, Nie W, Gao J, Xue LK, Gao XM, Wang XF, Qiu J, Poon CN, Meinardi S, Blake D, Wang SL, Ding AJ, Chai FH, Zhang QZ, Wang WX (2010) Air quality during the 2008 Beijing Olympics: secondary pollutants and regional impact. Atmos Chem Phys 10:7603–7615CrossRefGoogle Scholar
  32. Wang G, Cheng SY, Li JB, Lang JL, Wen W (2015) Source apportionment and seasonal variation of PM2.5 carbonaceous aerosol in the Beijing-Tianjin-Hebei Region of China. Environ Monit Assess 187(143):1–13CrossRefGoogle Scholar
  33. Yuan H, Zhuang GS, Li J, Wang ZF (2008) Mixing of mineral with pollution aerosols in dust season in Beijing: revealed by source apportionment study. Atmos Environ 42:2141–2157CrossRefGoogle Scholar
  34. Zhang HL, Li JY, Ying Q, Yu JZ, Wu D, Cheng Y, He KB, Jiang JK (2012) Source apportionment of PM2.5 nitrate and sulfate in China using a source-oriented chemical transport model. Atmos Environ 62:228–242CrossRefGoogle Scholar
  35. Zhang Y, Olsen KM, Wang K (2013) Fine scale modeling of agricultural air quality over the Southeastern United States using two air quality models. Part I. Application and evaluation. Aerosol Air Qual Res 13:1231–1252Google Scholar
  36. Zhou Y, Cheng SY, Liu L, Chen DS (2012) A coupled MM5-CMAQ modeling system for assessing effects of restriction measures on PM10 pollution in Olympic City of Beijing, China. J Environ Inform 19(2):120–127Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Wei Wen
    • 1
    • 2
  • Shuiyuan Cheng
    • 1
    • 3
  • Xufeng Chen
    • 4
  • Gang Wang
    • 1
  • Song Li
    • 1
  • Xiaoqi Wang
    • 1
  • Xiaoyu Liu
    • 1
  1. 1.College of Environmental and Energy EngineeringBeijing University of TechnologyBeijingPeople’s Republic of China
  2. 2.Environmental Meteorology Forecast Center of Beijing-Tianjin-HebeiChinese Meteorological AdministrationBeijingChina
  3. 3.Collaborative Innovation Center of Electric VehiclesBeijingChina
  4. 4.Tangshan Environmental Monitoring StationTangshanChina

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