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中文摘要：
利用第三代区域空气质量模式CMAQ（Community Multiscale Air Quality）及京津冀地区高分辨的污染源排放清单,基于2011年、2012年和2013年秋冬季美国国家环境预报中心全球再分析资料的气象条件分析,选取2012年10月1日至12月30日作为代表性时段,模拟了PM2.5的浓度变化趋势,同时根据《京津冀及周边地区落实大气污染防治行动计划实施细则》和2012年到2017年污染源减排控制目标,进行了减排效果评估分析.结果显示,模式系统能较好捕捉PM2.5浓度的变化趋势,海淀站和上甸子站观测与模拟值的相关系数分别为0.71和0.63.主要污染源和污染物排放量削减30%～40%后,北京市PM2.5浓度发生了明显降低,海淀站、上甸子站和城六区的平均浓度下降率分别为（24.9±2.3）%,（20.2±2.7）%和（24.8±2.1）%.如果严格执行《京津冀及周边地区落实大气污染防治行动计划实施细则》,在气象条件和2012年相似情况下,到2017年,北京市城区PM2.5年均浓度控制在60μg/m^3内的防治目标可以实现.
英文摘要：
The models-3 community multiscale air quality（CMAQ） Modeling System was used to simulate PM2.5concentrations in Beijing with the application of a high-resolution emission inventory for Beijing-Tianjin-Hebei Region in North China Plain. Based on the reanalysis of meteorological data derived from the national centersfor environmental prediction（NCEP） final analysis（FNL）, in the autumn and winter of 2011, 2012, and 2013, we have chosen a representative period, October 1st to December 30 th of 2012,for baseline simulation. According to the implementing measures for air pollution prevention and control action plans in Beijing-Tianjin-Hebei and surrounding area（hereinafter referred to as the measures） and Emission Source Control Target for the five-year period（2012～2017）, we formulated an emission control scenario to evaluate the improvements in air quality with the comparison to baseline simulation. The modeling system well captured the temporal trend of PM2.5 concentrations,with a correlation coefficient of 0.71 and 0.63 betweenmodeled and measured PM2.5 daily average concentrationsat Haidian and Shangdianzi, respectively. After 30～40% reduction of emissions for main pollutants in the Beijing-Tianjin-Hebei Region, PM2.5 average concentrations in Haidian, Shangdianzi, and urban area deceased by（24.9±2.3）%,（20.2±2.7）%, and（24.8±2.1）%, respectively. If the measures were strictly implemented and the meteorological conditions were similar with those in 2012, the goal of reducing PM2.5 annual mean concentration to 60μg/m3 could be reached in 2017.
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