The evaluation of emission control to PM concentration during Beijing APEC in 2014
作者： Ruipeng Li , Hongjun Mao , Lin Wu , Jianjun He , Peipei Ren
DOI: 10.1016/J.APR.2015.10.010
关键词:
摘要: Abstract Several statistical methods are performed in this study to evaluate the effect of emission control measures on particulate matter (PM) concentrations during 2014 Asia–Pacific Economic Cooperation (APEC) Summit held Beijing. The concentration PM 2.5 is reduced by 30%, 38% a year-on-year and month-on-month basis APEC period while 10 reducing 41% 26% respectively. Considering from impacts weather circulation types, both 34%. ANN model considered be appropriate with ability characterising non-linear phenomena. In work an built predict daily averaged concentrations. Comparing observed predicted value which forecasted condition that no were carried out APEC, reductions for 24%, 28% All these results suggest strict push down pollution level effectively, more data long time could improve accuracy evaluation results. More stringent controls regional emissions should lasted continuous improvements air quality Beijing-Tianjin-Hebei region.
sci-hub.se 参考文章(28)
Kan Huang, Xingying Zhang, Yanfen Lin, The “APEC Blue” phenomenon: Regional emission control effects observed from space Atmospheric Research. ,vol. 164, pp. 65- 75 ,(2015) , 10.1016/J.ATMOSRES.2015.04.018
Kevin Swingler, Applying Neural Networks: A Practical Guide ,(1996)
Mehmet Akyüz, Hasan Çabuk, Meteorological variations of PM2.5/PM10 concentrations and particle-associated polycyclic aromatic hydrocarbons in the atmospheric environment of Zonguldak, Turkey. Journal of Hazardous Materials. ,vol. 170, pp. 13- 21 ,(2009) , 10.1016/J.JHAZMAT.2009.05.029
Xiao Feng, Qi Li, Yajie Zhu, Junxiong Hou, Lingyan Jin, Jingjie Wang, Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation Atmospheric Environment. ,vol. 107, pp. 118- 128 ,(2015) , 10.1016/J.ATMOSENV.2015.02.030
Lovro Hrust, Zvjezdana Bencetić Klaić, Josip Križan, Oleg Antonić, Predrag Hercog, Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations Atmospheric Environment. ,vol. 43, pp. 5588- 5596 ,(2009) , 10.1016/J.ATMOSENV.2009.07.048
Z.F. Cai, L.X. Zhang, B. Zhang, Z.M. Chen, Emergy-based analysis of Beijing–Tianjin–Tangshan region in China Communications in Nonlinear Science and Numerical Simulation. ,vol. 14, pp. 4319- 4331 ,(2009) , 10.1016/J.CNSNS.2009.03.009
M.W Gardner, S.R Dorling, Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences Atmospheric Environment. ,vol. 32, pp. 2627- 2636 ,(1998) , 10.1016/S1352-2310(97)00447-0
Jianlin Hu, Yungang Wang, Qi Ying, Hongliang Zhang, Spatial and temporal variability of PM2.5 and PM10 over the North China Plain and the Yangtze River Delta, China Atmospheric Environment. ,vol. 95, pp. 598- 609 ,(2014) , 10.1016/J.ATMOSENV.2014.07.019
Jianjun He, Ye Yu, Na Liu, Suping Zhao, Numerical model-based relationship between meteorological conditions and air quality and its implication for urban air quality management International Journal of Environment and Pollution. ,vol. 53, pp. 265- ,(2013) , 10.1504/IJEP.2013.059921
Xiao-Ming Hu, ZhiQiang Ma, Weili Lin, Hongliang Zhang, Jianlin Hu, Ying Wang, Xiaobin Xu, Jose D. Fuentes, Ming Xue, Impact of the Loess Plateau on the atmospheric boundary layer structure and air quality in the North China Plain: A case study Science of The Total Environment. ,vol. 499, pp. 228- 237 ,(2014) , 10.1016/J.SCITOTENV.2014.08.053