A high temporal-spatial vehicle emission inventory based on detailed hourly traffic data in a medium-sized city of China

氮氧化物 北京 环境科学 排放清单 污染物 白天 流量(计算机网络) 气象学 道路交通 大气科学 中国 空气质量指数 环境工程 运输工程 地理 工程类 地质学 计算机科学 燃烧 考古 有机化学 化学 计算机安全
作者
Liu Y,Jinling Ma,Li Li,Xiangmin Lin,Weihua Xu,Hui Ding
出处
期刊:Environmental Pollution [Elsevier BV]
卷期号:236: 324-333 被引量:76
标识
DOI:10.1016/j.envpol.2018.01.068
摘要

To improve the accuracy and temporal-spatial resolution for a vehicle emission inventory in a medium-sized city with a strip road network, this study was conducted based on detailed hourly traffic-flow data for each day of 2014, and covered all road types and regions in the city of Foshan. Detailed hourly emission characteristics and sources in five regions were analysed. The results showed that the total vehicle emissions of CO, NOX, VOCs, and PM2.5 were 13.10 × 104, 0.23 × 104, 4.46 × 104, and 0.18 × 104 tons, respectively. Motorcycles (MCs) and light passenger cars (LPCs) were the dominant contributors of CO emissions, while buses and heavy passenger cars (HPCs) were the dominant contributors for NOX. As a whole, the daytime contributions to total emissions were close to 80%, and emissions during the peak periods accounted for almost 40%. Specifically, the hourly emissions of each pollutant on workdays were higher than on non-workdays (maximum up to 64.2%), and for some roads the early peak periods changed significantly from workdays to non-workdays. At expressways, artery roads, and local roads, the daily emission intensities of CO, NOx, and PM2.5 in Foshan were close to or even higher than that of Beijing. On a regional scale, the temporal variation of vehicle emissions on workdays at artery roads of different regions were similar. In addition, the higher emission intensities of CO and VOCs were identified in DaLiang-RongGui (DLRG) and that of NOX and PM2.5 were in Central Region (CR). These results are meaningful for decision-makers to help provide more detailed vehicle pollution control measures in Foshan with a strip road network and only one ring road.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
蓦然回首完成签到,获得积分10
刚刚
1秒前
1秒前
大昌完成签到 ,获得积分10
2秒前
小丽完成签到,获得积分10
2秒前
2秒前
2秒前
迷路冰颜完成签到,获得积分10
3秒前
Kate完成签到,获得积分10
4秒前
馒头发布了新的文献求助10
4秒前
今后应助渡星河采纳,获得10
4秒前
Dai完成签到,获得积分10
4秒前
小麦发布了新的文献求助10
5秒前
哈哈哈哈发布了新的文献求助10
5秒前
5秒前
叶千落完成签到 ,获得积分10
5秒前
蓝天发布了新的文献求助10
6秒前
DX120210165完成签到,获得积分10
6秒前
xmy完成签到,获得积分10
6秒前
冯尔蓝发布了新的文献求助10
6秒前
Arusa完成签到,获得积分10
6秒前
47发布了新的文献求助10
6秒前
7秒前
双峰山完成签到,获得积分10
7秒前
7秒前
8秒前
8秒前
8秒前
李木槿发布了新的文献求助10
8秒前
兴奋代芙完成签到,获得积分10
9秒前
科研通AI6.3应助llll采纳,获得10
9秒前
张奎完成签到,获得积分10
9秒前
在水一方应助skyziy采纳,获得10
9秒前
斯文败类应助jetlee采纳,获得10
10秒前
科研通AI6.4应助唔wu采纳,获得10
10秒前
ySX应助馒头采纳,获得10
10秒前
脑洞疼应助畅快的雁采纳,获得10
11秒前
wm发布了新的文献求助10
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
How to Design and Conduct an Experiment and Write a Lab Report: Your Complete Guide to the Scientific Method (Step-by-Step Study Skills) 333
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6363010
求助须知:如何正确求助?哪些是违规求助? 8176839
关于积分的说明 17230496
捐赠科研通 5417939
什么是DOI,文献DOI怎么找? 2866875
邀请新用户注册赠送积分活动 1844126
关于科研通互助平台的介绍 1691729