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研究报告

The spatial optimization of the PM₁₀ emission in Beijing and its verification by the numerical model

基金项目：城市气象科学研究基金(No.UMRF201003);国家高技术研究发展计划项目(No.2010AA012305);国家自然科学基金(No.40905063)

摘要：采用大气污染排放处理模型SMOKE,整合东亚区域排放清单及北京本地大气污染排放数据,结合人口、路网等地理信息数据,处理获得较高空间分辨率的网格化排放源,通过嵌套网格空气质量模式(NAQPMS)模拟验证表明,排放更新后,模式对2006年8月PM₁₀小时浓度模拟效果显著提高.市区各站点平均偏差MB由-87.4~-43.2μg·m^-3改善为-31.0~13.4μg·m^-3;市区平均的MB由-57.3μg·m^-3显著改善为-5.9μg·m^-3,约束条件更为严格的平均误差ME由66.6μg·m^-3下降到43.6μg·m^-3;各站点模拟-实测两倍因子百分比FAC2从17%~43%上升到44%~70%,市区平均的FAC2更是达到74%;除郊区定陵站外,市区各站点归一标准均方误差NMSE从1.030~3.447下降到0.370~0.867,市区平均NMSE由1.311下降到0.303.

Abstract：The sparse matrix operator kernel emissions (SMOKE) model is applied to improve the emissions process and provide the high resolution model-ready emissions for the PM₁₀ simulation of the nested air quality prediction modeling system (NAQPMS).The regional emissions in East Asia from TRACE-P/INTEX-B and the local sources emissions database in North China are included and spatially allocated based on related spatial factor such as the population data and the road length density for the high resolution emissions.The model performance of PM₁₀ simulation has improved obviously after emission process updated in August 2006.The mean bias (MB) of the simulation on the urban sites reduced greatly from-87.4~-43.2 μg·m^-3 to-31.0~13.4 μg·m^-3,with the averaged bias from-57.3 μg·m^-3 to-5.9 μg·m^-3;and the mean error (ME) decreased from 66.6 μg·m^-3 to 43.6 μg·m^-3.The fraction of prediction within a factor of two of observation (FAC2) increased from 17%~43% to 44%~70%,and the averaged FAC2 of PM₁₀ on the urban sites reached 74%.Except for the suburban station Dingling,the normalized mean square errors (NMSE) on the urban sites decreased from 1.030~3.447 to 0.370~0.867,with the average from 1.311 to 0.303.