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区县尺度机动车高分辨率排放清单建立方法及应用
摘要点击 2346  全文点击 743  投稿时间:2017-09-10  修订日期:2017-10-24
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中文关键词  区县尺度  机动车尾气  排放清单  车流量  高分辨率
英文关键词  county scale  motor vehicle exhaust  emission inventory  traffic flow  high resolution
作者单位E-mail
樊守彬 北京市环境保护科学研究院, 北京 100037
国家城市环境污染控制工程技术研究中心, 北京 100037 
fanshoubin@163.com 
郭津津 北京市环境保护科学研究院, 北京 100037  
李雪峰 北京市环境保护科学研究院, 北京 100037
国家城市环境污染控制工程技术研究中心, 北京 100037 
lixuefeng@cee.cn 
中文摘要
      提出了一种基于现场调查和卫片解译建立区县尺度机动车行驶里程(VKT)数据库和尾气排放高分辨率排放清单的方法,以北京市通州区为例进行了应用和排放特征分析.分别使用登记注册车辆信息(保有量方法)和实际车流量信息(车流量方法)计算出VKT和对应的各污染物排放量.结果表明,基于保有量方法计算得到的行驶里程比基于车流量方法的结果低约37%,应用实际车流量的计算方法与实际状况更接近.基于保有量的方法低估了小型载客汽车、大型载客汽车和中型载货汽车的行驶里程,高估了轻型载货汽车、重型载货汽车、低速载货汽车和摩托车的行驶里程.基于保有量的计算方法低估了小客车的尾气污染物排放量,低估比例约为51%.对于大客车、轻型载货汽车和中型载货汽车,2种方法计算的排放量差别较小.基于保有量的计算方法高估了重型载货汽车、低速载货汽车和摩托车的排放量的尾气排放量,高估比例分别约为41%、30%、30%.
英文摘要
      This study proposes a method for high-resolution vehicle emission inventories at county scale based on field investigations and Google Earth satellite images, using the Tongzhou district of Beijing as an example for data analysis. VKT and the corresponding emissions of each pollutant were calculated using the number of registered vehicles and the real-time traffic volumes, respectively. The results showed that the mileage calculated based on the method using registered vehicles is about 37% less than that based on real-time traffic volumes, with the latter method providing data closer to the actual situation. The mileage for small passenger cars, large passenger vehicles, and medium-duty trucks were underestimated, and that for light trucks, heavy trucks, low-speed trucks were overestimated based on the registered vehicle method. Emissions from small passenger cars were also underestimated by about 51%, using the registered vehicle method. For emissions of large passenger vehicles, light trucks, and medium-duty trucks, there was less difference between the two methods. Based on the registered vehicle method, emissions of heavy trucks, low-speed trucks, and motorcycles were overestimated by about 41%, 30%, and 30%, respectively.

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