基于GPS数据的重型柴油货车排放时空特征分析

柏洋洋; 何超; 李加强; 赵龙庆; 李菊; 徐加臣; 陈振瑜

doi:10.13205/j.hjgc.202304009

基于GPS数据的重型柴油货车排放时空特征分析

doi: 10.13205/j.hjgc.202304009

柏洋洋^1,2,
何超^1,2,3,
李加强^1,2, ,,
赵龙庆^1,2,
李菊^1,2,
徐加臣^1,2,
陈振瑜^1,2

1. 西南林业大学机械与交通学院, 昆明 650224;
2. 云南省高校高原山区机动车环保与安全重点实验室, 昆明 650224;
3. 德宏职业学院, 云南芒市 678400

基金项目:

云南省高层次人才项目(YNWR-QNBJ-2018-066,YNQR-CYRC-2019-001)

云南省教育厅科学研究基金项目(2020J0418,2022Y578)

详细信息

作者简介:
柏洋洋(1994-),男,硕士研究生,主要研究方向为汽车区域排放。b18795995990@163.com

通讯作者:
李加强(1977-),男,博士,讲师,主要从事汽车能源与排放控制研究。lijiaqiang@swfu.edu.cn

计量
- 文章访问数: 190
- HTML全文浏览量: 14
- PDF下载量: 23
- 被引次数: 0
出版历程
- 收稿日期: 2022-07-09
- 网络出版日期: 2023-05-26
- 刊出日期: 2023-04-01

SPATIOTEMPORAL CHARACTERISTICS ANALYSIS OF HEAVY-DUTY DIESEL TRUCK EMISSIONS BASED ON GPS DATA

BAI Yangyang^1,2,
HE Chao^1,2,3,
LI Jiaqiang^{1,2
, ,},
ZHAO Longqing^1,2,
LI Ju^1,2,
XU Jiachen^1,2,
CHEN Zhenyu^1,2

1. School of Mechanical and Transportation, Southwest Forestry University, Kunming 650224, China;
2. Key Laboratory of Vehicle Environmental Protection and Safety in Plateau Mountain Area of Yunnan Provincial Colleges, Kunming 650224, China;
3. Dehong Vocational College, Mangshi 678400, China

摘要

摘要: 汽车污染已成为中国空气污染的重要来源,而重型柴油货车是汽车大气污染排放的主要贡献者。为揭示重型柴油货车的排放特征,基于高原地区云南省昆明市重型柴油货车GPS点数据,用Python语言提取重型柴油货车在各点轨迹段的平均速度、行驶里程等参数,采用机动车排放模型MOVES,模拟计算研究区域内HC、CO、NO_<em>x、PM_2.5污染物排放量,并通过ArcGIS进一步分析其时空分布特征。结果表明:2021年1月3日昆明市研究区域内重型柴油货车HC、CO、NO_<em>x、PM_2.5的排放量分别为11.7423,39.6386,102.2600,0.9192 kg;时间维度,重型柴油货车在2:00和22:00有明显的排放高峰,受路权及运输行业工作时间的影响;空间维度,排放的分布格局呈明显的空间异质性,受政策驱动的影响且与空间位置的布置密切相关,排放主要分布在汕昆高速、昆石高速及支路、立交交叉口处;区域内重型柴油货车小时平均速度、交通量与其小时排放量有密切关系。因此,可以针对重型柴油货车排放较高的时段和地区,采取必要的治理手段,深入开展污染防治行动,以减少排放,助力"十四五"规划和2035远景目标的实现。
- 重型柴油货车 /
- MOVES /
- 运输排放 /
- GPS数据 /
- 时空特征
Abstract: Automobile pollution has become an important source of air pollution in China, and heavy-duty diesel trucks are the main contributors to automobile air pollution emissions. To reveal the emission characteristics of heavy-duty diesel trucks, based on the GPS point data of heavy-duty diesel trucks in Kunming, Yunnan Province, the average speed and mileage of heavy-duty diesel trucks in each point trajectory section were extracted by Python language. The vehicle emission model MOVES was used to simulate and calculate the emissions of HC, CO, NO_<em>x and PM_2.5 in the study area, and the spatiotemporal characteristics were further analyzed by ArcGIS. The results showed that the emissions of HC, CO, NO_<em>x and PM_2.5 of heavy diesel trucks in the study area of Kunming on January 3, 2021, were 11.7423 kg, 39.6386 kg, 102.2600 kg and 0.9192 kg, respectively. From the time point of view, heavy diesel truck emissions peaked at 2:00 and 22:00, affected by road rights and transportation industry working hours; in space, the distribution pattern of emissions showed obvious spatial heterogeneity, which was policy-driven and closely related to the layout of spatial location. Emissions were mainly distributed at Shankun Expressway, Kunshi Expressway, branches and interchange intersections. The hourly average speed and traffic volume of heavy diesel trucks in the region were closely related to their hourly emissions. Therefore, the relevant government departments should take necessary measures to control the pollution in periods and regions with high emissions of heavy-duty diesel trucks, and carry out in-depth pollution prevention and control actions to reduce emission and help achieve the 14th Five-Year Plan and the 2035 vision of China.
- heavy-duty diesel trucks /
- MOVES /
- transportation emissions /
- GPS data /
- spatiotemporal characteristics

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