Abstract

Abstract. To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

Highlights

  • Air pollution poses serious health risks to human populations and is one of the most important global environmental problems

  • During the pollution control periods of Asia-Pacific Economic Cooperation Forum (APEC) 2014 and the Victory Parade 2015, the concentrations of air pollutants except ozone decreased dramatically compared with the concentrations during non-control periods, accompanied by meteorological conditions favorable for pollutant dispersal

  • If including the nonlinear relationship between meteorological parameters and air pollutant concentrations, generalized linear regression model (GLM) based only on meteorological parameters could provide a good explanation of the variation of pollutant concentrations, with adjusted R2 values mostly larger than 0.7

Read more

Summary

Introduction

Air pollution poses serious health risks to human populations and is one of the most important global environmental problems. To ensure satisfactory air quality in Beijing during the two most recent events, the Asia-Pacific Economic Cooperation Forum (APEC) 2014 and the 2015 China Victory Day Parade (Victory Parade 2015), the Chinese central government and the local government of Beijing, together with its surrounding provinces, implemented comprehensive air pollution control strategies. These two events provide a good opportunity to evaluate the effectiveness of air pollution control strategies

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call