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Highlights • People choose LCT provided high population density and sufficient access to public transit. • Land-use diversity alone was not found to be significant in affecting LCT mode choice. • The proliferation of gated communities reduces connectivity and has a negative effect on LCT. Abstract Developing less auto-dependent urban forms and promoting low-carbon transportation (LCT) are challenges facing our cities. Previous literature has supported the association between neighborhood form and low-carbon travel behaviour. Several studies have attempted to measure neighborhood forms focusing on physical built-environment factors such as population and employment density and socio-economic conditions such as income and race. We find that these characteristics may not be sufficiently fine-grained to differentiate between neighborhoods in Chinese cities. This research assesses characteristics of neighborhood spatial configuration that may influence the choice of LCT modes in the context of dense Chinese cities. Urban-form data from 40 neighborhoods in Chengdu, China, along with a travel behaviour survey of households conducted in 2016, were used to generate several measures of land use diversity and accessibility for each neighborhood. We use principle component analysis (PCA) to group these variables into dimensions that could be used to classify the neighborhoods. We then estimate regression models of low-carbon mode choices such as walking, bicycling, and transit to better understand the significance of these built-environment differences at the neighbourhood level. We find that, first, members of households do choose to walk or bike or take transit to work provided there is relatively high population density and sufficient access to public transit and jobs. Second, land-use diversity alone was not found to be significant in affecting LCT mode choice. Third, the proliferation of gated communities was found to reduce overall spatial connectivity within neighborhoods and had a negative effect on choice of LCT. [ABSTRACT FROM AUTHOR]

• The traditional mixed-use neighborhoods are in need of intensified urban retrofitting projects. • The work-unit could benefit from comprehensive plans rather than patching individual pieces. • The most pressing issue for gated communities is their obsolete spatial functions. • Resettlement housing should provide more opportunities to connect with the rest of the city. Rapid urban expansion in China has created both opportunities and challenges for promoting active transport in urban residential communities. Previous studies have shown that the urban form at the city scale has affected active transport in Chinese cities. However, there is less agreement about how the physical and social variations of neighborhood types should be addressed. This research investigates the four most representative neighborhood types found in Chinese cities: traditional mixed-use, slab block work-unit, gated community, and resettlement housing. Household travel diaries conducted in Chengdu in 2016 were analyzed using binary logistic regressions, supplemented by informal onsite interviews. The findings indicate significant variations in the use and accessibility of active transport in each neighborhood type for non-work trips. This suggests that each neighborhood type may need different strategies for promoting active transport: (1) the traditional mixed-use neighborhoods are in need of intensified urban retrofitting projects to reclaim public open space; (2) the work-unit could benefit from comprehensive plans rather than a patchwork of projects; (3) while opening up gated communities can improve porosity across neighborhoods and promote active transport, the more pressing issue may be their inability to keep up with the transportation needs of the residents; and (4) residents of resettlement housing should have better access to employment using transit and non-motorized modes. [ABSTRACT FROM AUTHOR]

The rapid adoption of on-demand mobility services has brought a challenge in accessing their equity impacts at a regional scale due to the absence of consistent trip data and efficient transportation models. This study shows the potential of integrating synthetic population data and a choice-based optimization model to support large-scale mobility service region design with equity concerns. We propose a decision support tool that specifies budget-constrained optimal service regions for new mobility services under one of several objectives such as minimizing consumer surplus insufficiency. We test using New York State synthetic data and illustrate its application by considering new ride-hailing and microtransit services. The "cost of equity" is measured: under budget level II, each vehicle requires a subsidy of $71.39/day to minimize disparity and $29.86/day to minimize insufficiency. Our findings contribute to the literature by quantifying trade-offs among different services, objectives, and budget levels, thereby supporting funding and resource allocation. [ABSTRACT FROM AUTHOR]

In this study, a bi-level model is developed to quantify the value of orderly electric vehicle (EV) charging in carbon reduction. Specifically, the upper-level model optimizes each EV driver's charging schedule to diminish the total carbon emissions without impacting their travel plans, and the lower-level problem aims to fulfill electricity demands with minimal electricity dispatch cost. Based on real-world operation data obtained from 3,777 battery EVs (BEVs) in Shanghai over 11 months and local power plant data, the total carbon emissions generated by BEVs in Shanghai is calculated as 1,176,637 tons over this period, averaging 73 gCO 2 /km per BEV. By administering charging control to all BEVs in Shanghai, the above emission could be curtailed by 39%. Sensitivity analyses uncover that augmenting battery capacity and integrating wind power can significantly enhance emission reductions, while increasing the flexibility of the power plant might diminish the effectiveness of orderly EV charging. [ABSTRACT FROM AUTHOR]