Responses of PM2.5 and O3 concentrations to changes of meteorology and emissions in China Academic Article uri icon

abstract

  • Tremendous efforts have been made to reduce the severe air pollution in China since 2013. However, the annual and peak fine particulate matter (PM2.5) concentrations during severe events in winter did not always reduce as expected. This is partially due to the inter-annual variation of meteorology, which affects the emission, transport, transformation, and deposition processes of air pollutants. In this study, the responses of PM2.5 and ozone (O3) concentrations to changes in emission and meteorology from 2013 to 2015 were investigated based on ambient measurements and the Community Multi-Scale Air Quality (CMAQ) model simulations with anthropogenic emissions. It is found that emission reductions in 2014 and 2015 effectively reduced PM2.5 concentrations by 23.9 and 43.5 μg/m3, respectively, but was partially counteracted by unfavorable meteorology. The negative effects from unfavorable meteorology were significant in extreme pollution events. For example, in December 2015, unfavorable meteorology caused a great increase (90 μg/m3) of PM2.5 in Beijing. Reduction of primary PM and gaseous precursors led to 13.4 and 16.5 ppb increase of O3-8 h daily concentrations in the summertime in 2014 and 2015 in comparison of 2013, which was likely caused by the increase of solar actinic flux due to PM reduction. In addition, reduction of nitrogen oxides (NOx) emissions in areas with negative NOx-O3 sensitivity could lead to an increase of O3 formation when the reduction of volatile organic compounds (VOCs) was not sufficient. This unintended enhanced O3 formation could also lead to higher O3 in downwind areas. This study emphasizes the role of meteorology in pollution control, validates the effectiveness of PM2.5 control measures in China, and highlights the importance of appropriate joint reduction of NOx and VOCs to simultaneously decrease O3 and PM2.5 for higher air quality.

author list (cited authors)

  • Wang, P., Guo, H., Hu, J., Kota, S. H., Ying, Q. i., & Zhang, H.

citation count

  • 53

publication date

  • January 2019