AI Summary & Key Takeaways
AI InsightAll these results suggest that strict emission control measures push down thepollution level effectively, and more observed data with long time could improve the accuracy of evaluationresults.
📌 3 Key Takeaways
Özet
Several statistical methods are performed in this study to evaluate the effect of emission control measureson particulate matter (PM) concentrations during the 2014 AsiaePacific Economic Cooperation(APEC) Summit held in Beijing. The concentration of PM2.5 is reduced by 30%, 38% on a year-on-year andmonth-on-month basis during the APEC emission control period while PM10 reducing by 41% and 26%respectively. Considering from the impacts of the weather circulation types, PM2.5 and PM10 are bothreduced by 34%.ANN model is considered to be appropriate with the ability of characterising non-linear phenomena. Inthis work an ANN model is built to predict the daily averaged PM concentrations. Comparing theobserved PM concentrations and the predicted value which are forecasted by ANN model on conditionthat no emission control measures were carried out during the APEC, the reductions for PM2.5 and PM10are 24%, 28% respectively. All these results suggest that strict emission control measures push down thepollution level effectively, and more observed data with long time could improve the accuracy of evaluationresults. More stringent controls of regional emissions should be lasted for the continuous improvementsof air quality in Beijing-Tianjin-Hebei region.