Low-carbon futures for Shenzhen’s urban passenger transport: A human-based approach

Document Type

Journal Article

Publication Date


Subject Area

place - urban, place - asia, mode - car, mode - subway/metro, technology - emissions, planning - environmental impact, planning - methods, planning - service improvement, planning - surveys, policy - parking, policy - environment


Traveler behavior, Human-based agent model, Carbon emissions, Energy consumption, Urban transportation policy, Environmental policy


Shenzhen, one of China’s leading cities, has the potential to be a model for achieving China’s ambitious CO2 emission reduction targets. Using data from a travel diary survey in Shenzhen in 2014, we develop a human-based agent model to conduct a scenario study of future urban passenger transport energy consumption and CO2 emissions from 2014 to 2050. Responses to different policy interventions at the individual level are taken into account. We find that with current policies, the carbon emissions of the urban passenger transport sector in Shenzhen will continuously increase without a peak before 2050. Strengthening 21 transport policies will help Shenzhen to peak the carbon emissions by 2030 for passenger transport. Among these policies, the car quota policy and the fuel economy standard are essential for achieving a carbon peak by 2030. In addition, a package of seven policies, including fewer car quotas, a stricter fuel economy standard, raising parking fees, limiting parking supply, increasing EV charging facilities and subway lines, and improving public transport services, is sufficient to peak carbon emissions by 2030, although at an emissions level higher than for the 21 policies.


Permission to publish the abstract has been given by Elsevier, copyright remains with them.


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