| 基于交通流的成都市高分辨率机动车排放清单建立 |
| 摘要点击 3163 全文点击 1189 投稿时间：2020-02-14 修订日期：2020-03-05 |
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| 中文关键词 交通流 车队结构 交通小区 高分辨率 机动车 排放清单 |
| 英文关键词 traffic flow road vehicle structure traffic-zone high resolution motor vehicle emission inventory |
| 作者 | 单位 | E-mail | | 潘玉瑾 | 四川省生态环境科学研究院, 成都 610041
四川省环境保护移动源污染与控制研究实验室, 成都 610041 | pan_yujin@163.com | | 李媛 | 四川省生态环境科学研究院, 成都 610041
四川省环境保护移动源污染与控制研究实验室, 成都 610041 | | | 陈军辉 | 四川省生态环境科学研究院, 成都 610041
四川省环境保护移动源污染与控制研究实验室, 成都 610041 | 9503062@qq.com | | 石嘉诚 | 四川省生态环境科学研究院, 成都 610041
四川省环境保护移动源污染与控制研究实验室, 成都 610041 | | | 田红 | 成都市机动车排气污染防治技术保障中心, 成都 610041 | | | 张季 | 成都市机动车排气污染防治技术保障中心, 成都 610041 | | | 周敬 | 成都市机动车排气污染防治技术保障中心, 成都 610041 | | | 陈霞 | 成都市机动车排气污染防治技术保障中心, 成都 610041 | | | 刘政 | 四川省生态环境科学研究院, 成都 610041 | | | 钱骏 | 四川省生态环境科学研究院, 成都 610041 | |
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| 中文摘要 |
| 提出一种基于交通流监测数据的道路机动车高分辨率排放清单建立方法，对成都市道路交通流特征进行分析并建立了成都市机动车尾气高分辨率排放清单.结果表明，成都市道路车流量及排放均呈现明显的"双峰"分布，早晚高峰时段机动车通行量占全天的39.85%，车队结构中排放标准以国Ⅳ车为主，车辆类型以小型车为主，燃料类型以汽油车为主；道路机动车SO2、NOx、CO、PM10、PM2.5、BC、OC和VOCs（不含驻车蒸发）日排放量分别为3.89、162.08、324.11、4.79、4.36、1.89、0.78和44.37 t，空间分布整体呈现从城市中心到外围排放强度逐渐降低趋势，时间分布基本呈现"双峰"分布，颗粒物相关指标受货车流量影响较大；NOx、PM10、PM2.5、BC和OC主要来源为大型柴油车，CO主要来源为小型汽油车，其中大型车对NOx的贡献率达80%；基于保有量的计算方法对成都市道路机动车污染物排放存在一定高估，高估比例在1%～30%. |
| 英文摘要 |
| A method for developing a high-resolution emission inventory for road vehicles based on traffic flow monitoring data is proposed in this study. The characteristics of road traffic flow were analyzed and a high-resolution emission inventory of vehicle in Chengdu was established. The results showed that the traffic flow and emissions in Chengdu exhibited an obvious "double peak" distribution, and that the traffic volume of vehicles during peak hours accounted for 39.85% of the total. China IV vehicles, small vehicles, and gasoline vehicles were the main types of road vehicles classified. The daily emissions of SO2, NOx, CO, PM10, PM2.5, BC, OC, and VOCs from road vehicles were 3.89, 162.08, 324.11, 4.79, 4.36, 1.89, 0.78, and 44.37 t, respectively. The overall spatial distribution showed a decreasing trend from the city center to the periphery, and the time distribution essentially presented a "double peak" distribution. The related indicators of particulate matter were greatly affected by the number of trucks. The main source of NOx, PM10, PM2.5, BC, and OC was large diesel vehicles, and the main source of CO was small gasoline vehicles. NOx emissions from large vehicles accounted for up to 80% of the total. The method based on registered vehicles led to an overestimation of the emissions from road vehicles in Chengdu, with a proportion between 1% and 30%. |
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