共 51 条
A comparative analysis of the potential of carbon emission reductions from shared micro-mobility
被引:3
作者:
Zhang, Yongping
[1
,2
,3
]
Fu, Wenyan
[1
]
Chao, Hao
[4
]
Mi, Zhifu
[5
]
Kong, Hui
[4
,6
]
机构:
[1] Zhejiang Univ, Sch Publ Affairs, Hangzhou 310058, Peoples R China
[2] Zhejiang Univ, ZJU CMZJ Joint Lab Data Intelligence & Urban Futur, Hangzhou 310058, Peoples R China
[3] Zhejiang Univ, China Inst Urbanizat, Hangzhou 310058, Peoples R China
[4] Xiamen Univ, Sch Architecture & Civil Engn, Xiamen 361005, Peoples R China
[5] UCL, Bartlett Sch Sustainable Construct, London WC1E 7HB, England
[6] Xiamen Univ, Fujian Prov Univ Key Lab Intelligent & Low Carbon, Sch Architecture & Civil Engn, Xiamen 361005, Fujian, Peoples R China
关键词:
Shared micro-mobility;
Bikes;
E;
-bikes;
Environment benefit;
Carbon emissions;
Travel mode substitution;
ENVIRONMENTAL BENEFITS;
BIKES;
CITY;
D O I:
10.1016/j.seta.2024.104088
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Shared micro-mobility systems (SMSs) have recently experienced rapid growth, providing new green mobility options to reduce energy use. To better understand SMS's environmental impact, this paper comparatively examines the potential of carbon emission reductions from dockless shared bikes and e-bikes in three Chinese cities at different economic development stages (i.e., Binjiang, Wucheng and Xiangshan) using massive user-generated trips. Results show that shared bikes and e-bikes in the three cities reduced 41.51 and 31.84 tonnes of CO2 emissions over a week, respectively. The trip-level environmental benefit of shared e-bikes is 155.11 g of CO2, higher than that of shared bikes (132.03 g). Most of the reduced carbon emissions are from substituting driving trips, but shared e-bikes even generate extra carbon emissions by substituting public transit and walking. Patterns of carbon emission reductions show spatiotemporal heterogeneity. Spatially, reduced carbon emissions are concentrated in central areas of Wucheng/Xiangshan and more dispersedly distributed in Binjiang, which is a more economically vibrant city. From a temporal perspective, SMS's carbon reduction patterns are similar to typical temporal usage patterns. The Dining and Shopping trips contribute the most to SMS's carbon reductions in all cities. Binjiang has more carbon emissions reduced from the Transfer and Working trips, and shared bike trips with the Home and Schooling purposes reduced relatively more carbon emissions in Wucheng. Our analysis helps us better understand the environmental impact of SMSs across various urban contexts and inform relevant transport planning to achieve carbon neutrality in cities.
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