基于POI兴趣点的排放清单空间分配方法

摘要

POI (Points of interest) describes the type, location and other information of engineering and servicing facilities. POI data has the characteristics of easy access, strong timeliness and high accuracy. It is an important part of navigation electronic maps, and has a widely application prospects in urban planning. This study established a method to allocate area emissions (residential, agriculture and transportation source, etc.) basing on POI data (such as residential and commercial enterprises, animal husbandry and fishery enterprises, parking lot and other transportation facilities). Using the method, Beijing's MEIC inventory was allocated to 3km×3km and 1km×1km spatial resolution, and CMAQ model was applied to test accuracy of allocated inventory. The result show that, using POI data to spatial allocate emission inventory can more effectively reflect the spatial distribution characteristics of the emission source. The simulation results of CMAQ model show that after using POI data to allocate Beijing's MEIC inventory, the NMB and NME between monitoring data and simulated data are reduced about 30% and 10%, respectively.%基于商业住宅、农林牧渔企业、交通设施等类型的城市设施兴趣点(POI)数据建立了针对居民生活源、农业源、交通源等非点源的排放清单分配方法.以北京市为例,基于2015年高德地图的POI数据对清华大学MEIC排放清单进行了3km×3km及1km×1km的高空间分辨率分配,并基于分配后的排放清单,采用CMAQ空气质量模式对2015年1月5个市内监测站点PM2.5的模拟值及监测数据进行对比,以检验该分配方法的准确性.结果表明,利用POI数据进行空间分配可以更加有效地反映出排放源的空间分布特征;CMAQ空气质量模式模拟结果中,采用该方法分配后的排放清单较直接面积插值的排放清单标准化平均偏差(NMB)降低40%左右,标准化平均误差(NME)降低10%左右.