• 关键词：京津冀  国家干线公路  交通污染物  核密度分析  空间分布

• 基金项目：中央在京高校重大成果转化项目

• 李海萍
• 中国人民大学环境学院, 北京 100872

• 赵颖
• 中国人民大学环境学院, 北京 100872

• 傅毅明
• 中国人民大学环境学院, 北京 100872

• 摘要：以国家干线公路交通量信息和单车排放因子为基础，基于GIS的路网线性参考系统，采用动态分段技术和核密度分析方法，从路段、污染物和车型这3个层次对2014年京津冀国家干线公路交通污染排放强度的空间差异进行分析.结果表明，车流量、车型构成和路网布局是引起排放强度空间分布差异的主要因素，排放强度高的路段集中在路网密度大且公路使用率高的京津地区，中小客车和特大货车对污染物排放强度影响显著.因使用燃料和车型的不同，NO_x、PM₁₀和PM_2.5排放强度分布大体一致，HC、CO空间分布更为相似.此外，经济发展水平、产业结构特征也是重要影响因素.北京除特大货车和集装箱以外的其他车型排放强度均很高，天津货车和客车排放强度均较高，河北货车排放强度高于客车.

• Abstract：A linear reference road network system is constructed under GIS environment. Kernel density analysis method and dynamic segmentation technology were used to estimate the emission intensity of air pollutants from national trunk highway in Beijing-Tianjin-HeBei (BTH) based on traffic flows of 2014 and vehicle emission factors. The variation of spatial distribution of air pollutants emission was characterized at three levels: road segments, pollutants and vehicle composition. The results show that traffic flows, vehicle composition and road network layout are the main factors that affect the spatial distribution of on-road vehicular emission. Roads within Beijing-Tianjin area have high pollutants discharge intensity because of its densely road network and heavy traffic flows. Passenger cars and heavy duty trucks have remarkable influences on the intensity of pollutants emission. Because of the differences among fuels and vehicle types, spatial distribution of pollutants such as NO_x, PM₁₀ and PM_2.5 were similar to each other; and CO was more consistent with HC. Besides, economic development level and industrial structure characteristics also have great impacts on spatial distribution of vehicle pollutants emission intensity. All vehicles except heavy trucks and containers have high emission intensity in Beijing area. In Tianjin, both trucks and buses have high emission intensity. While in Hebei, trucks have higher emission intensity than passenger cars.

• Key words：Beijing-Tianjin-Hebei  national trunk highways  vehicle pollutants  kernel density analysis  spatial distribution

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