Advertisement

Environmental Chemistry Letters

, Volume 16, Issue 3, pp 1117–1127 | Cite as

Residential emissions predicted as a major source of fine particulate matter in winter over the Yangtze River Delta, China

  • Yujie Wu
  • Peng Wang
  • Shaocai Yu
  • Liqiang Wang
  • Pengfei Li
  • Zhen Li
  • Khalid Mehmood
  • Weiping Liu
  • Jian Wu
  • Eric Lichtfouse
  • Daniel Rosenfeld
  • John H. Seinfeld
Original Paper
  • 240 Downloads

Abstract

Air pollution is an increasingly critical health issue responsible for numerous diseases and deaths worldwide. In China, to address severe air pollution in the Yangtze River Delta region, the local government has formulated Five-Year Plans to set the road map for air pollution control by phased targets in 2020, but the effectiveness of these policies is still uncertain. There is therefore a need for accurate prediction of control strategies. Here we present a computational evaluation of the predicted effectiveness of four emission control strategies: normal or enhanced emission reduction for industry and power plants, and normal or enhanced emission reduction for industry, power plants and transportation, designed on the basis of policies of the 13th Five-Year Plans. Effectiveness was tested on concentrations of PM2.5, e.g., particulate matter with aerodynamic diameter less than 2.5 μm, using the two-way coupled Weather Research and Forecasting—Community Multiscale Air Quality (WRF-CMAQ) model. Results show that by implementing the four emission control strategies, only Hangzhou with the strictest emission controls in four main cities (Hangzhou, Hefei, Nanjing and Shanghai) can meet the 20% reduction goals of PM2.5 concentrations in the 13th Five-Year Plan, indicating that current policies are not sufficient to control the severe air pollution in the Yangtze River Delta region. Sensitivity tests show that residential emissions have the highest contributions to the PM2.5 concentrations in January in the four main cities of Hangzhou, Hefei, Nanjing and Shanghai, followed by agriculture, industry, transportation and power plants. Predicted annual mean reduction percentages for PM2.5 are the highest in Hangzhou, from − 9.7 to − 20.1%, followed by Nanjing, from − 8.2 to − 18.7%, Shanghai, from − 7.4 to − 15.8%, and Hefei, from − 6.1 to − 13.8%. This finding highlights the predominance of residential emissions, which should be better controlled, notably coal burning. By comparison, predicted annual contributions of regional transport and natural sources to mean PM2.5 concentrations in four cities range from 29.2 to 36.6%. Overall, a major finding is that residential sources are of comparable importance to industrial, power plant and transportation sources to PM2.5 concentrations, especially for winter. This information will help governments of other regions of China, as well as other developing countries, to formulate more appropriate emission control strategies where coal is used for heating and cooking purposes in the developing countries.

Keywords

Emission reductions WRF-CMAQ Scenario analysis Yangtze River Delta 

Notes

Acknowledgments

This work was partially supported by the Department of Science and Technology of China (No. 2016YFC0202702; No. 2014BAC22B06) and National Natural Science Foundation of China (No. 21577126). This work was also supported by the Joint NSFC–ISF Research Program (No. 41561144004), jointly funded by the National Natural Science Foundation of China and the Israel Science Foundation. Part of this work was also supported by the “Zhejiang 1000 Talent Plan” and Research Center for Air Pollution and Health in Zhejiang University.

References

  1. Burr MJ, Zhang Y (2011) Source apportionment of fine particulate matter over the Eastern U.S. Part I: source sensitivity simulations using CMAQ with the Brute Force method. Atmos Pollut Res 2(3):300–317.  https://doi.org/10.5094/apr.2011.036 CrossRefGoogle Scholar
  2. Eder B, Yu SC (2006) A performance evaluation of the 2004 release of Models-3 CMAQ. Atmos Environ 40:4811–4824.  https://doi.org/10.1016/j.atmosenv.2005.08.045 CrossRefGoogle Scholar
  3. Fu X, Wang SX, Cheng Z, Xing J, Zhao B, Wang JD, Hao JM (2014) Source, transport and impacts of a heavy dust event in the Yangtze River Delta, China, in 2011. Atmos Chem Phys 14(3):1239–1254.  https://doi.org/10.5194/acp-14-1239-2014 CrossRefGoogle Scholar
  4. Gao Y, Zhang MG (2012) Sensitivity analysis of surface ozone to emission controls in Beijing and its neighboring area during the 2008 Olympic Games. J Environ Sci 24:50–61.  https://doi.org/10.1016/S1001-0742(11)60728-6 CrossRefGoogle Scholar
  5. Guenther AB, Jiang X, Heald CL, Sakulyanontvittaya T, Duhl T, Emmons LK, Wang X (2012) The model of emissions of gases and aerosols from nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions. Geosci Model Dev 5(6):1471–1492.  https://doi.org/10.5194/gmd-5-1471-2012 CrossRefGoogle Scholar
  6. Hong YW, Chen JS, Deng JJ, Tong L, Xu LL, Niu ZC, Yin LQ, Chen YT, Hong ZY (2016) Pattern of atmospheric mercury speciation during episodes of elevated PM2.5 levels in a coastal city in the Yangtze River Delta, China. Environ Pollut 218:259–268.  https://doi.org/10.1016/j.envpol.2016.06.073 CrossRefGoogle Scholar
  7. Hu JL, Wu L, Zheng B, Zhang Q, He KB, Chang Q, Li XH, Yang FM, Ying Q, Zhang HL (2015) Source contributions and regional transportation of primary particulate matter in China. Environ Pollut 207:31–42.  https://doi.org/10.1016/j.envpol.2015.08.037 CrossRefGoogle Scholar
  8. Huang K, Zhuang G, Lin Y, Fu JS, Wang Q, Liu T, Zhang R, Jiang Y, Deng C, Fu Q, Hsu NC, Cao B (2012) Typical types and formation mechanisms of haze in an Eastern Asia megacity, Shanghai. Atmos Chem Phys 12:105–124.  https://doi.org/10.5194/acp-12-105-2012 CrossRefGoogle Scholar
  9. Huang ZJ, Ou JM, Zheng JY, Yuan ZB, Yin SS, Chen DH, Tan HB (2016) Process contributions to secondary inorganic aerosols during typical pollution episodes over the Pearl River Delta region, China. Aerosol Air Qual Res 16:2129–2144.  https://doi.org/10.4209/aaqr.2015.12.0668 CrossRefGoogle Scholar
  10. Li PF, Wang LQ, Guo P, Yu SC, Mehmood K, Wang S, Liu WP, Seinfeld JH, Zhang Y, Wong DC, Alapaty K, Pleim J, Mathur R (2017) High reduction of ozone and particulate matter during the 2016 G-20 summit in Hangzhou by forced emission controls of industry and traffic. Environ Chem Lett 15:709–715.  https://doi.org/10.1007/s10311-017-0642-2 CrossRefGoogle Scholar
  11. Liu HR, Liu C, Xie ZQ, Li Y, Huang X, Wang SS, Xu J, Xie PH (2016) A paradox for air pollution controlling in China revealed by “APEC Blue”. Sci Rep 6:34408.  https://doi.org/10.1038/srep34408 CrossRefGoogle Scholar
  12. Lu C, Yao T, Fung JC, Lin CQ (2016) Estimation of health and economic costs of air pollution over the Pearl River Delta region in China. Sci Total Environ 566:134–143.  https://doi.org/10.1016/j.scitotenv.2016.05.060 CrossRefGoogle Scholar
  13. Mehmood K, Chang SC, Yu SC, Wang LQ, Li PF, Li Z, Liu WP, Rosenfeld D, Seinfeld JH (2018) Spatial and temporal distributions of air pollutant emissions from open crop straw and biomass burnings in China from 2002 to 2016. Environ Chem Lett 16:301–309.  https://doi.org/10.1007/s10311-017-0675-6 CrossRefGoogle Scholar
  14. Ministry of Environmental Protection of China (2014) 2013 China environmental state bulletin. http://www.zhb.gov.cn/hjzl/zghjzkgb/lssj/2013nzghjzkgb. Accessed 30 Mar 2018
  15. Morrison H, Thompson G, Tatarskii V (2009) Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: comparison of one- and two-moment schemes. Mon Weather Rev 137:991–1007.  https://doi.org/10.1175/2008MWR2556.1 CrossRefGoogle Scholar
  16. National Bureau of Statistics of China (2014) China Statistical Yearbook 2014. http://www.stats.gov.cn/tjsj/ndsj/2014/indexeh.htm. Accessed 30 Mar 2018
  17. Pleim JE (2007) A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: model description and testing. J Appl Meteorol Clim 46:1383–1395.  https://doi.org/10.1175/JAM2539.1 CrossRefGoogle Scholar
  18. Skamarock WC (2005) Why is there more than one dynamical core in WRF? A technical perspective. http://www2.mmm.ucar.edu/people/skamarock/Papers/one_core_2005.pdf. Accessed 30 Mar 2018
  19. State Council of China (2012) 12th Five year plan for air pollution prevention and control in key regions. http://www.gov.cn/gongbao/content/2013/content_2344559.htm. Accessed 30 Mar 2018
  20. State Council of China (2013) Action plan for air pollution prevention and control. http://zfs.mep.gov.cn/fg/gwyw/201309/t20130912_260045.shtml. Accessed 30 Mar 2018
  21. Sun Y, Wang Z, Wild O, Xu WQ, Chen C, Fu Q, Du W, Zhou LB, Zhang Q, Han TT, Wang QQ, Pan XL, Zheng HT, Li J, Guo XF, Liu JG, Worsnop DR (2016) “APEC Blue”: secondary aerosol reduction from emission control in Beijing. Sci Rep 6:20668.  https://doi.org/10.1038/srep20668 CrossRefGoogle Scholar
  22. Wang LT, Wei Z, Yang J, Zhang Y, Zhang FF, Su J, Meng CC, Zhang Q (2014a) The 2013 severe haze over southern Hebei, China: model evaluation, source apportionment, and policy implications. Atmos Chem Phys 14:3151–3173.  https://doi.org/10.5194/acp-14-3151-2014 CrossRefGoogle Scholar
  23. Wang DX, Hu JL, Xu Y, Lv D, Xie XY, Kleeman M, Xing J, Zhang HL, Ying Q (2014b) Source contributions to primary and secondary inorganic particulate matter during a severe winter-time PM2.5 pollution episode in Xi’an, China. Atmos Environ 97:182–194.  https://doi.org/10.1016/j.atmosenv.2014.08.020 CrossRefGoogle Scholar
  24. Wang LQ, Li PF, Yu SC, Mehmood K, Li Z, Chang SC, Liu WP, Rosenfeld D, Flagan RC, Seinfeld JH (2018) Predicted impact of thermal power generation emission control measures in the Beijing-Tianjin-Hebei region on air pollution over Beijing, China. Sci Rep 8:934.  https://doi.org/10.1038/s41598-018-19481-0 CrossRefGoogle Scholar
  25. Wong DC, Pleim J, Mathur R, Binkowski F, Otte T, Gilliam R, Pouliot G, Xiu A, Young JO, Kang D (2012) WRF-CMAQ two-way coupled system with aerosol feedback: software development and preliminary results. Geosci Model Dev 5:299–312.  https://doi.org/10.5194/gmd-5-299-2012 CrossRefGoogle Scholar
  26. Xing J, Zhang Y, Wang SX, Liu XH, Cheng SH, Zhang Q, Chen YS, Streets DG, Jang C, Hao JM, Wang WX (2011) Modeling study on the air quality impacts from emission reductions and a typical meteorological conditions during the 2008 Beijing Olympics. Atmos Environ 45:1786–1798.  https://doi.org/10.1016/j.atmosenv.2011.01.025 CrossRefGoogle Scholar
  27. Yan RC, Yu SC, Zhang QY, Li PF, Wang S, Chen BX, Liu WP (2015) A heavy haze episode in Beijing in February of 2014: characteristics, origins and implications. Atmos Pollut Res 6:867–876.  https://doi.org/10.5094/APR.2015.096 CrossRefGoogle Scholar
  28. Yarwood G, Rao S, Yocke M, Whitten GZ (2005) Final report updates to the carbon bond chemical mechanism: CB05. Rep. RT-04-00675, 246 pp., Yocke and Co., Novato, California. http://www.camx.com/publ/pdfs/CB05_Final_Report_120805.pdf. Accessed 30 Mar 2018
  29. Yu SC, Mathur R, Pleim J, Wong D, Gilliam R, Alapaty K, Zhao C, Liu X (2014a) Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF-CMAQ: model description, development, evaluation and regional analysis. Atmos Chem Phys 14(20):11247–11285.  https://doi.org/10.5194/acp-14-11247-2014 CrossRefGoogle Scholar
  30. Yu SC, Zhang QY, Yan RC, Wang S, Li PF, Chen BX, Liu WP, Zhang XY (2014b) Origin of air pollution during a weekly heavy haze episode in Hangzhou, China. Environ Chem Lett 12:543–550.  https://doi.org/10.1007/s10311-014-0483-1 CrossRefGoogle Scholar
  31. Zhao PS, Dong F, He D, Zhao XJ, Zhang XL, Zhang WZ, Yao Q, Liu HY (2013) Characteristics of concentrations and chemical compositions for PM2.5 in the region of Beijing, Tianjin, and Hebei, China. Atmos Chem Phys 13:4631–4644.  https://doi.org/10.5194/acp-13-4631-2013 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Yujie Wu
    • 1
    • 2
  • Peng Wang
    • 1
    • 2
  • Shaocai Yu
    • 1
    • 2
    • 3
  • Liqiang Wang
    • 1
    • 2
  • Pengfei Li
    • 1
    • 2
  • Zhen Li
    • 1
    • 2
  • Khalid Mehmood
    • 1
    • 2
  • Weiping Liu
    • 1
    • 2
  • Jian Wu
    • 4
  • Eric Lichtfouse
    • 5
  • Daniel Rosenfeld
    • 6
  • John H. Seinfeld
    • 3
  1. 1.Research Center for Air Pollution and Health, College of Environmental and Resource SciencesZhejiang UniversityHangzhouPeople’s Republic of China
  2. 2.Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource SciencesZhejiang UniversityHangzhouPeople’s Republic of China
  3. 3.Division of Chemistry and Chemical EngineeringCalifornia Institute of TechnologyPasadenaUSA
  4. 4.Institute of Environmental Science Research and Design Institute of Zhejiang ProvinceHangzhouPeople’s Republic of China
  5. 5.CEREGE, Aix-Marseille Univ, CNRS, Coll France, CNRS, INRA, IRD, Europole Mediterraneen de l’ArboisAix en ProvenceFrance
  6. 6.Institute of Earth Sciences, The Hebrew University of JerusalemJerusalemIsrael

Personalised recommendations