Multi-agent based and system dynamics models integrated simulation of urban commuting relevant carbon dioxide emission reduction policy in China

Transportation is a major source of greenhouse gas (GHG) emissions in cities. Multiple strategies including transport management, urban planning and behavioral changes are required to reduce GHG emissions. Considering the urgent need to improve to urban jobs-housing relationship and reduce transport carbon dioxide (CO2) emissions, we propose a complex system model that couples multi-agent based models (ABM) and system dynamics (SD) models to simulate the impact of jobs-housing relationship adjustment policies on CO2 emissions from urban transport. Through simulation of the jobs-housing relationship and comprehensive intelligent simulation of multi-scenario policy schemes, the best optimal combination of schemes is investigated. Results show that the implementation of a single policy and measure can reduce some transport CO2 emissions, but they still rise, and do not reach a peak. To address possible future development of Beijing, three scenarios for transport CO2 emissions reduction were designed, which include Business as usual scenario (BAU), Plan scenario (PS) and Integrated scenario (IS), respectively. Under the IS, carbon intensity could be reduced by 25%-55% compared with 2005, and the environmental economic benefits of each combination scheme were higher than the single measure. Further, we investigated the effects of a reduction in carbon intensity of 65% in 2050 compared to 2005, by simulating 3 different integrated schemes (Combination Scheme Six (CSSI), Combination Scheme Seven (CSSE) and Combination Scheme Eight (CSEI)). This approach showed that CO2 emissions reduction and environmental economic benefits of the CSEI scheme were greater than either of the other two schemes. Therefore, the CSEI scheme is the best optimal development path in an integrated scenario from the long-term goal, and the research results provide decision-making reference and research support for Beijing to achieve low-carbon transportation. (C) 2020 Elsevier Ltd. All rights reserved.