基于高分辨率动态排放清单的郑州市机动车排放特征研究

王雯楠; 刘格格; 魏红格; 任歌; 何巍楠; 胡宇鑫; 林鸿; 樊亚辉; 杨耀环

doi:10.13205/j.hjgc.202410012

基于高分辨率动态排放清单的郑州市机动车排放特征研究

doi: 10.13205/j.hjgc.202410012

王雯楠¹,
刘格格^1,2,
魏红格³,
任歌^1,2, ,,
何巍楠^4,5,
胡宇鑫¹,
林鸿^1,2,
樊亚辉³,
杨耀环⁶

1. 郑州计量先进技术研究院, 郑州 450001;
2. 中国计量科学研究院, 北京 100029;
3. 郑州市数字城市运行管理中心, 郑州 450001;
4. 北京交通发展研究院, 北京 100073;
5. 清华大学环境学院, 北京 100084;
6. 郑州大数据发展有限公司, 郑州 450001

基金项目:

中国计量科学研究院基本科研业务费重点领域(AKYZD2207-2)

国家市场监督管理总局技术保障专项项目(2022YJ19)

详细信息

作者简介:
王雯楠(1996-),女,助理工程师,主要研究方向为移动源排放污染分析。wangwennan@zim.ac.cn

通讯作者:
任歌(1988-),女,副研究员,主要研究方向为温室气体和大气污染物监测分析。reng@nim.ac.cn

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出版历程
- 收稿日期: 2023-04-28
- 网络出版日期: 2024-11-30

RESEARCH OF VEHICLE EMISSION CHARACTERISTICS IN ZHENGZHOU BASED ON HIGH-RESOLUTION DYNAMIC EMISSION INVENTORY

WANG Wennan¹,
LIU Gege^1,2,
WEI Hongge³,
REN Ge^{1,2
, ,},
HE Weinan^4,5,
HU Yuxin¹,
LIN Hong^1,2,
FAN Yahui³,
YANG Yaohuan⁶

1. Zhengzhou Institute of Metrology, Zhengzhou 450001, China;
2. National Institute of Metrology, Beijing 100029, China;
3. Zhengzhou Digital City Operation Management Center, Zhengzhou 450001, China;
4. Beijing Transportation Institute, Beijing 100073, China;
5. School of Environment, Tsinghua University, Beijing 100084, China;
6. Zhengzhou Big Data Development Co., Ltd., Zhengzhou 450001, China

摘要

摘要: 为深入了解郑州市机动车污染排放现状,提升移动源污染治理水平,通过融合多源交通大数据,搭建基于路段交通流和本地化排放因子的郑州市路网排放动态测算模型,实现对道路排放的实时测算,建立了小时级、路段级高分辨率道路移动源排放清单。开展郑州市分车型、分环路、行政区、道路类别等机动车排放特征分析,提出机动车污染管控措施建议。结果表明:小客车是CO₂、CO和HC的主要贡献车型,NO_x和PM排放量主要来自货车和大型客车;郑州市机动车CO₂、CO和HC排放主要集中在三环内区域,碳排放量从中心城区至边缘呈逐渐减弱趋势,NO_x和PM排放沿环路呈明显的带状分布;东南部区域机动车污染物排放水平偏高,其中郑东新区和金水区CO₂、CO和HC污染物排放占比超出郑州市区排放量40%,中牟县和新郑市NO_x和PM排放污染较重;快速路类型机动车CO₂排放率高至3.66 t/(km·d),高速路类型NO_x排放强度最大,为0.017 t/(km·d)。研究显示,郑州市可通过优先推动主城区绿色低碳发展和提高货车污染治理水平,推进本市移动源减污降碳协同增效,以切实改善空气质量。
- 郑州市 /
- 路网排放动态测算模型 /
- 实时测算 /
- 高分辨率道路移动源排放清单 /
- 机动车 /
- 典型特征分析
Abstract: To deeply understand the current situation of vehicle emissions in Zhengzhou and improve the level of mobile pollution sources management, a vehicular dynamic emission model based on the traffic flow characteristics and localized emission factors was established by integrating multi-source traffic big data, achieving the real-time calculation of on-road emission. Then a high spatio-temporal resolution on-road emission inventory in Zhengzhou was developed at the hourly and link level. The vehicle emission characteristics were analyzed by vehicle type, ring road, administrative division, and road type, and the measures for vehicle pollution control were proposed. The results showed that passenger cars were the major contributors to CO₂, CO, and HC emissions, while NO_x and PM emissions mainly came from trucks and coaches. The carbon emissions (including CO₂, CO, and HC) in Zhengzhou were mainly concentrated in the area of the 3rd Ring Road, with a gradually decreasing trend from downtown areas to urban fringes. The emissions of NO_x and PM were concentrated in ring roads with distinctive banding distribution. The analysis of the emission characteristics of administrative regions showed that the proportion of CO₂, CO, and HC emissions in Zhengdong New District and Jinshui District was more prominent, and NO_x and PM emissions in Zhongmu County and Xinzheng County were relatively heavier. Additionally, the CO₂ emission rate of urban expressways was as high as 3.66 t/(km·d), and the NO_x emission intensity on highways was the highest, at 0.017 t/(km·d). The research indicated that Zhengzhou could give priority to promoting green and low-carbon development in the downtown area and enhancing the level of truck pollution control, which contributed to the synergy of pollution and carbon emissions reduction from mobile sources and improvement of air quality.
- Zhengzhou /
- vehicular dynamic emission model /
- real-time calculation /
- high spatio-temporal resolution on-road emission inventory /
- vehicles /
- emission characteristics

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