Differential impacts of urbanization characteristics on city-level carbon emissions from passenger transport on road: Evidence from 360 cities in China

被引:20
|
作者
Su, Yongxian [1 ,3 ,4 ]
Wu, Jianping [1 ]
Ciais, Philippe [4 ]
Zheng, Bo [4 ,5 ]
Wang, Yilong [6 ]
Chen, Xiuzhi [2 ]
Li, Xueyan [1 ]
Li, Yong [1 ]
Wang, Yang [7 ]
Wang, Changjian [1 ]
Jiang, Lu [8 ]
Lafortezza, Raffaele [9 ,10 ]
机构
[1] Guangdong Acad Sci, Guangzhou Inst Geog, Guangdong Prov Key Lab Remote Sensing & Geog Infor, Guangdong Open Lab Geospatial Informat Technol & A, Guangzhou 510070, Peoples R China
[2] Sun Yat Sen Univ, Sch Atmospher Sci, Guangdong Prov Key Lab Climate Change & Nat Disast, Guangzhou 510275, Peoples R China
[3] Southern Marine Sci & Engn Guangdong Lab, Guangzhou 511458, Peoples R China
[4] Lab Sci Climat & Environm, UMR CEA CNRS UVSQ 1572, F-91191 Gif Sur Yvette, France
[5] Tsinghua Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China
[6] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
[7] Qinghai Normal Univ, Sch Geog Sci, Xining 810008, Peoples R China
[8] Yunnan Normal Univ, Fac Geog, Kunming 650500, Peoples R China
[9] Univ Bari A Moro, Dept Agr & Environm Sci, Via Amendola 165-A, I-70126 Bari, Italy
[10] Univ Hong Kong, Dept Geog, Centennial Campus,Pokfulam Rd, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Carbon emissions; China; City-level; Driving forces; Passenger transport; Tree-based method; CO2; EMISSIONS; DIOXIDE EMISSIONS; TRAVEL; CONSUMPTION; COMPACTNESS; CONGESTION; POLICIES; INDEX; SHAPE;
D O I
10.1016/j.buildenv.2022.109165
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Although it's well known that the carbon intensity from passenger transport of cities varies widely, few studies assessed the disparities of that in city-level and its underlying factors due to the limited availability of data, and thus developed effective strategies for different types of cities. This study is the first to present a comprehensive inventory of emissions from passenger transport on road for 360 cities in mainland China for 2018, based on the data from 5 transport modes and evaluated by combining distance-based and top-down fuel-based methods. In 2018, passenger transport on road in China emitted 1076 MtC. A large portion of CO2 emissions was identified in the southern and eastern coastal areas and capital cities. GDP, population, and policy were the major factors determining the total CO2 emissions, but not carbon intensity. Clustering analysis of carbon intensity and 9 socioeconomic predictors, using a tree-based regression model, clustered the 360 cities into 6 groups and showed that higher carbon intensities occurred in both affluent city groups with a high active population share and less affluent city groups with a low population density but high density of trip destinations. Forward-and-backward stepwise multiple regression analysis indicated that constructing a compact city is more effective for city groups with a high income and high active population share. Enhancing land-use mixed degree is more critical for city groups with a high income and low active population share, while shortening travel distance by intensifying infrastructure construction is more important for the less affluent city groups.
引用
收藏
页数:12
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