不同时刻污染减排对北京市PM2.5浓度的影响

利用空气质量模式Model-3/CMAQ及京津冀地区高分辨率排放源清单,针对有代表性的污染时段(2012年2月7~16日),设置了5种不同时刻的减排方案(在污染峰值提前4d、提前3d、提前2d、提前1d及当天减排),对比在同样的减排比例下,不同时刻开始减排的效果差异.研究发现,提前采取减排控制措施比污染峰值当天开始减排对降低PM2.5浓度的影响更为明显,而且提前采取应急减排的时间越早,PM2.5浓度下降越明显.提前1d、2d、3d减排海淀站和城六区峰值浓度下降率分别为23%和22%、31%和30%、39%和38%,均明显高于当天减排的峰值浓度下降率10%和9%.但随着提前天数的增加,PM2.5峰值浓度进一步下降的幅度越来越小,减排效益较之前显著降低.提前4d减排海淀站和城六区峰值浓度下降率分别为40%和39%,提前4d减排和提前3d减排对降低污染峰值日PM2.5浓度的效果已没有太大差别.同时针对另一个污染时段(2012年1月11~20日)进行了相似的敏感性试验,得出了类似的结论.因此,针对某些污染事件的应急减排,综合考虑减排成本和减排效果,根据气象条件的预报,在可能引起重污染事件的不利气象条件来临时提前2~3d采取减排措施效果最好,既能有效降低PM2.5浓度,也可以避免因盲目长时间减排造成的成本过大.

Effects of emission-sources reduction at different time points on PM2.5 concentration over Beijing Municipality

The Models-3Community Multi-scale Air Quality (CMAQ) Modeling system with a high resolution inventory data over Beijing-Tianjin-Hebei area was used to investigate the effects on PM2.5 concentrations over Beijing of emission-sources reduction, with the same reduction rate at 5different time points: 4 days, 3 days, 2 days, 1 day and 0 day in advance of the most polluted day. Simulations were made for a representative air pollution episode (Feb 7th~16th, 2012), in which Feb 13th was found to be the most polluted day. The results show that the PM2.5 concentration was likely to decline more significantly if emission-sources reduction measures were taken before the most polluted day than were taken on the most polluted day. In addition, the earlier emission-sources reduction measures were taken, the more significantly the PM2.5 concentration would decline. Reducing emission-sources 1 day, 2 days, 3 days ahead of the most polluted day led to declination of the peak value of PM2.5 concentration at the Haidian station by 23%, 31%, and 39%, and in urban Beijing by 22%, 30%, and 38%, respectively. However, as the number of days ahead of the most polluted day (Feb 13th) to take reduction measures increased further, the additional decrease of the peak PM2.5 concentration became smaller, thus the emission-sources reduction benefits became less effective. The peak PM2.5 concentration would decrease by 40% and 39% at Haidian station and urban Beijing if the reduction measures were taken 4 days before the most polluted day, which shows almost no improvement compared with those 3days in advance. Similar results were obtained in simulations for another pollution episode (Jan 11th~20th, 2012). For controlling severe air pollution, both reduction costs and benefits should be considered. Our study indicates that the most effective way of emission-sources reduction is to take reduction actions 2~3days ahead of the possible severe pollution event, which can be obtained from meteorological condition prediction. In this way, substantial decrease of the peak PM2.5 concentration can be achieved with less cost for implementing the reduction measures.