Abstract
Severe and persistent haze pollution involving fine particulate matter (PM2.5) concentrations reaching unprecedentedly high levels across many cities in China poses a serious threat to human health. Although mandatory temporary cessation of most urban and surrounding emission sources is an effective, but costly, short-term measure to abate air pollution, development of long-term crisis response measures remains a challenge, especially for curbing severe urban haze events on a regular basis. Here we introduce and evaluate a novel precision air pollution control approach (PAPCA) to mitigate severe urban haze events. The approach involves combining predictions of high PM2.5 concentrations, with a hybrid trajectory-receptor model and a comprehensive 3-D atmospheric model, to pinpoint the origins of emissions leading to such events and to optimize emission controls. Results of the PAPCA application to five severe haze episodes in major urban areas in China suggest that this strategy has the potential to significantly mitigate severe urban haze by decreasing PM2.5 peak concentrations by more than 60% from above 300 μg m−3 to below 100 μg m−3, while requiring ~30% to 70% less emission controls as compared to complete emission reductions. The PAPCA strategy has the potential to tackle effectively severe urban haze pollution events with economic efficiency.
Highlights
China’s unprecedented urbanization has been accompanied by an increase in the level of air pollution, which has been estimated to lead to 2.5 million premature deaths annually[1,2,3,4]
Good air quality was achieved for several large international events, such as the 2008 Beijing Olympics, 2010 Shanghai Expo, 2014 Beijing Asia-Pacific Economic Cooperation (APEC) Summit, 2015 Beijing Grand Military Parade, and the 2016 G20 Hangzhou Summit, as a result of stringent urban and regional emission control measures enacted in anticipation of these events[23,24,25,26,27]
The essential idea of the precision air pollution control approach (PAPCA) is to predict the advent of extreme pollutant concentrations using a comprehensive 3-D air quality model in conjunction with a hybrid trajectory-receptor model to calculate so-called Concentration Weighted Trajectory (CWT) values which can pinpoint the emission areas that are predicted to contribute most significantly to a pending severe urban haze event
Summary
The essential idea of the PAPCA is to predict the advent of extreme pollutant concentrations using a comprehensive 3-D air quality model in conjunction with a hybrid trajectory-receptor model to calculate so-called Concentration Weighted Trajectory (CWT) values which can pinpoint the emission areas that are predicted to contribute most significantly to a pending severe urban haze event. For case 1 with emission controls from 50% vehicles and 75% industries, the mean PM2.5 concentration for the severe haze periods in Beijing (from 22:00 on October 26 to 16:00 on October 28, 2103), Beijing (from 9:00 on January 24 to 3:00 on January 26, 2017), Shanghai (from 10:00 on December 1 to 14:00 on December 3), and Xian (from 9:00 on December 16 to 14:00 on December 25) decreased from 203.0 μg m−3 to 95.7 μg m−3, 245.9 μg m−3 to 166.1 μg m−3, 172.1 μg m−3 to 71.0 μg m−3, and 347.9 μg m−3 to 174.4 μg m−3, respectively. Not primarily responsible for the severe haze episode, as even when emissions in each city are totally curtailed, mean PM2.5 concentrations in Beijing (2013 case), Beijing (2017 case), Shanghai, Hangzhou and Xian are predicted to be reduced only by 11.1%, 7%, 22.0%, 21.5% and 22.6%, respectively (Figs 4 and S1d and Tables 2 and S7).
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