省域高速公路网车辆碳排放量测算方法

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摘要提出一种基于联网收费数据测算省域高速公路碳排放量的方法,通过车辆理论油耗模型,结合车型差异、车辆总质量、汽车运行工况等因素,实现路段级碳排放的精细计算.依托高速公路收费数据,通过数据清洗和聚合,计算路段平均速度,运用TransCAD实现交通分配;运用Python实现Dijkstra算法确定实际行驶路径矩阵,结合路段平均速度和NEDC工况曲线构建汽车行驶工况;通过MOVES数据库反推燃油消耗率来计算油耗并转化为碳排放量;以宁夏回族自治区为例,计算月度省域高速公路碳排放量,并分析碳排放分布特征,通过MOVES、COPERT模拟及对比国家统计局数据发布的各类燃料消耗量,验证测算方法的可行性.结果表明,2019年9月宁夏回族自治区高速公路碳排放总量为21.04万t,客货分布比为1:3.92;5轴及以上的重型货车碳排放量占货车总量的82.34%;乘用车碳排放量占客车总量的83.18%;碳排放量主要集中在连接省会城市和周边地级市的路网干道;模型测算结果较MOVES高出15.86%,较COPERT高出32.16%,与由国家和地方统计部门公布的燃油消费量折算为碳排放量的偏差率仅为4.29%.研究可揭示省域高速公路上各车型的碳排放量及各路段的碳排放分布特征.

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关键词 ：交通运输, 高速公路, 碳排放量测算, 收费数据, 汽车运行工况, 燃油消耗率

Abstract：The paper proposed a model for estimating the carbon emissions of provincial expressway network by toll collection data. In consideration of a theoretical fuel consumption model and the factors such as vehicle type differences, total mass, and vehicle operating conditions, it achieved precise calculation of carbon emissions at the section level. Based on toll collection data, the average speeds of section were calculated through data cleaning and aggregation, and TransCAD was used to achieve traffic allocation. By using PYTHON, the Dijkstra algorithm to determine the actual path matrix was implemented, combining these with the NEDC driving cycle to construct the vehicle driving cycle. It calculated fuel consumption and converted into carbon emissions by inferring specific fuel consumption through the MOVES database. Taking the Ningxia Hui Autonomous Region as a case study, we calculated the monthly carbon emissions of provincial highways and analyzed the distribution characteristics of carbon emissions. The feasibility of the model was verified through MOVES and COPERT simulations and comparison with various fuel consumption data released by the National Bureau of Statistics. The results show that in September 2019, the total carbon emissions of expressways in Ningxia Hui Autonomous Region were 210400 tons, with a passenger vehicle to truck distribution ratio of 1:3.92. Heavy trucks with 5axles or more accounted for 82.34% of the total carbon emissions of trucks. Passenger cars accounted for 83.18% of the total carbon emissions of passenger vehicles. Carbon emissions were mainly concentrated on the road network connecting provincial capital cities and surrounding prefecture level cities. Calculated emissions of the model were 15.86% above those of MOVES and 32.16% above COPERT’s, with a deviation of merely 4.29% from the national and local statistical department’s carbon emission converted by fuel consumption. The paper could reveal the carbon emissions of each vehicle type on provincial expressways, and the distribution characteristics of carbon emissions on each road section.

Key words： transportation expressway carbon emission estimation toll collection data automotive operating conditions specific fuel consumption

收稿日期: 2024-05-25

PACS:

X51

基金资助:国家重点研发计划项目(2023YFB3209803);国家自然科学基金资助项目(52172319,71971138);长安大学中央高校基本科研业务费专项资金资助项目(300102224206)

通讯作者: 孙健,教授,jiansun@chd.edu.cn E-mail: jiansun@chd.edu.cn

作者简介: 闫晟煜(1987-),男,黑龙江绥化人,副教授,博士,主要从事公路运输规划、智慧交通运营研究.发表论文53篇.Leo9574@163.com.

引用本文:

闫晟煜, 王钊龙, 武瑾, 白书铭, 孙健. 省域高速公路网车辆碳排放量测算方法[J]. 中国环境科学, 2024, 44(12): 7095-7104. YAN Sheng-yu, WANG Zhao-long, WU Jin, BAI Shu-ming, SUN Jian. Estimation model of vehicle carbon emission for provincial expressway networks.. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(12): 7095-7104.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2024/V44/I12/7095

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