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

BAI Yangyang; HE Chao; LI Jiaqiang; ZHAO Longqing; LI Ju; XU Jiachen; CHEN Zhenyu

doi:10.13205/j.hjgc.202304009

Volume 41 Issue 4

Apr. 2023

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BAI Yangyang, HE Chao, LI Jiaqiang, ZHAO Longqing, LI Ju, XU Jiachen, CHEN Zhenyu. SPATIOTEMPORAL CHARACTERISTICS ANALYSIS OF HEAVY-DUTY DIESEL TRUCK EMISSIONS BASED ON GPS DATA[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(4): 63-70,100. doi: 10.13205/j.hjgc.202304009

Citation:

BAI Yangyang, HE Chao, LI Jiaqiang, ZHAO Longqing, LI Ju, XU Jiachen, CHEN Zhenyu. SPATIOTEMPORAL CHARACTERISTICS ANALYSIS OF HEAVY-DUTY DIESEL TRUCK EMISSIONS BASED ON GPS DATA[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(4): 63-70,100. doi: 10.13205/j.hjgc.202304009

Citation:

BAI Yangyang, HE Chao, LI Jiaqiang, ZHAO Longqing, LI Ju, XU Jiachen, CHEN Zhenyu. SPATIOTEMPORAL CHARACTERISTICS ANALYSIS OF HEAVY-DUTY DIESEL TRUCK EMISSIONS BASED ON GPS DATA[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(4): 63-70,100. doi: 10.13205/j.hjgc.202304009

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

doi: 10.13205/j.hjgc.202304009

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

Received Date: 2022-07-09
Available Online: 2023-05-26
Publish Date: 2023-04-01

Abstract

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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References(28)

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