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杭州市机动车污染物排放清单的建立
引用本文:王孝文,田伟利,张清宇.杭州市机动车污染物排放清单的建立[J].中国环境科学,2012,32(8):1368-1374.
作者姓名:王孝文  田伟利  张清宇
作者单位:1. 浙江大学环境与资源学院,浙江杭州,310058
2. 杭州合一环境科技有限公司 浙江杭州310027
摘    要:基于调研的基础数据,运用修正后的IVE排放模型及GIS系统建立了杭州市2010年1km×1km的高时空分辨率的机动车排放清单.结果表明,2010年杭州市机动车污染物CO、HC、NOx、PM的年排放量分别为44.06,2.31,4.43,0.65万t,主要来自线源道路的排放.各车型污染物分担率各不相同,汽油乘用车和公交车排放CO和HC最大,柴油重型货车和公交车是NOx和PM排放的主要来源,两种燃油下的机动车排放差异十分明显.机动车污染排放与路网密集程度及道路长度密切相关,因此西湖区和江干区排放总量远远高出其他区域.机动车各污染物排放强度空间分布均呈现由城市中心向城市边缘的递减趋势,各污染物中心城区排放量占总排量的70%以上.机动车污染物排放日变化十分明显,与人群出行规律有极大的相关性.

关 键 词:机动车中观排放清单  排放量分担率  时空分布  
收稿时间:2011-12-30;

Development of motor vehicles emission inventory in Hangzhou
WANG Xiao-wen , TIAN Wei-li , ZHANG Qing-yu.Development of motor vehicles emission inventory in Hangzhou[J].China Environmental Science,2012,32(8):1368-1374.
Authors:WANG Xiao-wen  TIAN Wei-li  ZHANG Qing-yu
Institution:1 (1.College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; 2.Hangzhou Heyi Environmental Technology Company, Hangzhou 310027, China)
Abstract:The vehicular emission inventories with high temporal and spatial resolution of 1km×1km were developed using modified IVE model and GIS technique based on a series of investigations in Hangzhou in 2010. The results showed that the emissions of CO, HC, NOx and PM were 440.6, 23.1, 44.3, 6.5kt respectively, principally from line-road sources emission. There are significant differences in the emission contributions among different vehicle types. Gasoline passenger cars and buses contributed most to the emission of CO and HC. While diesel heavy-duty trucks and buses were the major NOx and PM contributors. At the same time, the ratio of diesel vs. gasoline showed significant effects on pollutant emissions. Vehicle emissions closely related with the intensity and length of road networks which made the emissions in Xihu and Jianggan districts were much more than other four districts. Vehicles spatial distributions showed that the vehicles emissions decreased gradually from urban core to surrounding areas. Emission in city center contributed more than 70 percent to total vehicles emissions. The temporal variation trends varied apparently which were well consistent with the characteristics of people’s activities.
Keywords:Bottom-up vehicular emission  contribution rates  temporal and spatial distributions
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