摘要
为提高机动车排放清单的精度,对清单的空间分配模型进行优化,在模型复杂度与关联因素分析的基础上,对人口密度、国内生产总值(GDP)、交通兴趣点(POI)、坡度等影响因子进行主成分提取,并结合标准路长,提出了基于主成分综合调解系数的多因子空间分配模型,以济南市为例进行验证,结果显示:济南市2021年机动车碳排放总量为1259.9万t;基于构建的空间分配模型,获取了济南市1 km×1 km分辨率的网格化机动车碳排放清单;历下区等济南市中心城区是高排放的热点区域,高速公路与一级公路形成高排放的线状地带。基于空间分配模型与基于标准路长的分配结果相比,高排放区碳排放量更高,低排放区碳排放量更低;前者考虑了坡度,对于地形起伏较大地区的分配结果更合理。基于主成分调解系数的多因子空间分配模型提高了网格化排放清单的空间分辨率和分配结果精度。
To improve the accuracy of the motor vehicle emission inventory,the spatial allocation model of the inventory was optimized.Considering the model complexity and correlation factor analysis,this paper provided a new multi factor spatial allocation model based on principal component mediation coefficients to extract the influencing factors such as population density,GDP,traffic POI and slope,combined the standard road length.Taking Jinan City as an example for verification,the results showed that the total carbon emissions of vehicles in Jinan City in 2021 were 12.599 million tons.Based on the constructed model,a gridding carbon emission inventory of vehicles with a resolution of 1 km ×1 km in Jinan City was obtained.The central urban areas of Jinan City,such as Lixia District,were hot spots for high emissions,and the expressway and first-class roads formed a linear zone with high emissions.The spatial allocation results based on the newly constructed model were higher in high emission areas and lower in low emission areas compared to those based on standard road length allocation,and it took into account the slope,so the distribution results were more reasonable in areas with larger topographic variation.The multi factor spatial allocation model based on principal component mediation coefficients proposed in this paper improved the spatial resolution and the accuracy of allocation results of gridding emission inventories.
作者
王天旻
冯海霞
魏代梅
李永昌
崔纪鹏
宁二伟
WANG Tianmin;FENG Haixia;WEI Daimei;LI Yongchang;CUI Jipeng;NING Erwei(Shandong Transportation Planning and Design Institute Group Co.,Ltd.,Jinan Shandong 250101;School of Transportation and Logistics Engineering,Shandong Jiaotong University,Jinan Shandong 250357)
出处
《环境污染与防治》
CAS
CSCD
北大核心
2023年第10期1338-1342,1351,共6页
Environmental Pollution & Control
基金
国家自然科学基金资助项目(No.52102412)
山东省自然科学基金资助项目(No.ZR2022MG077)
山东省交通运输厅科技计划项目(No.2022B70、No.2022B31)
山东省社会科学规划研究项目(No.22CJJJ31、No.22BLYJ13)
交通运输部规划研究院研究课题(No.20222000496)。
关键词
公路运输
空间分配模型
主成分分析
机动车碳排放清单
高精度
road transport
spatial allocation model
principal component analysis
vehicle carbon emission inventory
high accuracy
