Transportation and Urban Planning

The Harvard-China Project has long worked on both: 1) air quality impacts of road and now air transport, led by scientists and engineers; and 2) urban planning to reduce transportation demand, led by urban planners in the Harvard Graduate School of Design. In recent years the Project has also developed engineering-based research capacities on transportation decarbonization, especially of light-duty road and air transport modes, as described under Energy Systems

A basis for many urban planning studies has been interdisciplinary household surveys in the city of Chengdu led by the Harvard-China Project and implemented by the Research Center for Contemporary China of Peking University, using RCCC's rigorous geospatial sampling methods to insure inclusion of non-registered migrants. The team completed the most recent interdisciplinary household survey in July 2016. The data were joined with an earlier dataset collected in a nearly identical Harvard-PKU survey in 2005, to cover changes in Chengdu's economy, urbanization, travel behavior, land use, air quality, and environmental health over 11 years. Both the 2005 and 2016 Chengdu surveys collected data for a wide range of research interests, including transportation planning, travel behavior, mobile-source emissions, outdoor and indoor air pollution exposures, health effects of air pollution, and perceptions and valuation of environmental health risk.  The team hopes to return to Chengdu for another household survey when the collaborative research environment allows it, to extend its analyses of changes in urban form, transport options, travel behavior, and popular perceptions over time. 
 
 

Related Publications

Saiwen Zhang, Yiliang Jiang, Shaojun Zhang, and Ernani F Choma. 2024. “Health benefits of vehicle electrification through air pollution in Shanghai, China.” Science of The Total Environment, 914, 1 March 2024, Pp. 169859. Publisher's VersionAbstract
Vehicle electrification has been recognized for its potential to reduce emissions of air pollutants and greenhouse gases in China. Several studies have estimated how national-level policies of electric vehicle (EV) adoption might bring very large environmental and public health benefits from improved air quality to China. However, large-scale adoption is very costly, some regions derive more benefits from large-scale EV adoption than others, and the benefits of replacing internal combustion engines in specific cities is less known. Therefore, it is important for policymakers to design incentives based on regional characteristics – especially for megacities like Shanghai – which typically suffer from worse air quality and where a larger population is exposed to emissions from vehicles. Over the past five years, Shanghai has offered substantial personal subsidies for passenger EVs to accelerate its electrification efforts. Still, it remains uncertain whether EV benefits justify the strength of incentives. The purpose of our study is to evaluate the health and climate benefits of replacing light-duty gasoline vehicles (ICEVs) with battery EVs in the city of Shanghai. We assess health impacts due to ICEV emissions of primary fine particulate matter, NOx, and volatile organic compounds, and to powerplant emissions of NOx and SO2 due to EV charging. We incorporate climate benefits from reduced greenhouse gas emissions based on existing research. We find that the benefit of replacing the average ICEV with an EV in Shanghai is US$6400 (2400-14,700), with health impacts of EVs about 20 times lower than the average ICEV. Larger benefits ensue if older ICEVs are replaced, but replacing newer China ICEVs also achieves positive health benefits. As Shanghai plans to stop providing personal subsidies for EV purchases in 2024, our results show that EVs achieve public health and climate benefits and can help inform policymaking strategies in Shanghai and other megacities.
Yang Zhao, Ziyue Jiang, Xinyu Chen, Peng Liu, Tianduo Peng, and Zhan Shu. 2023. “Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets.” Energy, 285, 15 Dec 2023, Pp. 129465. Publisher's VersionAbstract
The scale-up of urban electric vehicle (EV) fleets, driven by environmental benefits, is resulting in surging aggregate energy demands that may reshape a city's power supply. This paper establishes an integrated data-driven assessment model for investigating the energy use (kWh) patterns and charging load (kW) profiles of urban-scale EV fleets. To this end, urban EV operating and operational datasets are linked with climate data and vehicle specifications. Four vehicle fleet types are distinguished: private, taxi, rental, and business fleets. Statistical models regarding distribution analysis, spectrum analysis, and identical distribution tests are employed to analyze the patterns of driving distances, energy consumption, and shares of active charging EVs. The minute-level changes in charging EV numbers and aggregate charging power are examined to reflect the grid load impact. The results show that private light-duty EVs in Beijing consume an average of 9.1 kWh/day, with more charging activities on Fridays. The primary load peaks of light-duty EVs in Beijing usually occur between 11 p.m. and 1 a.m., attributable chiefly to the private fleet's midnight peak load estimated at 28 % of the total daily charging private EV count multiplied by 5.5 kW/EV. Secondary peaks occur between 8 a.m. and 10 a.m. on weekdays for private fleets, and at 4 p.m. for public fleets. Our work can be extensively used for analyses on transport emissions, urban power supply, infrastructure build-ups, and policymaking.
Zhichang Cai, Chenghe Guan, An Trinh, Bo Zhang, Zhibin Chen, Sumeeta Srinivasan, and Chris Nielsen. 2022. “Satisfaction on self-perceived health of urban residents in Chengdu, China: Gender, age and the built environment.” Sustainability, 14, 40, Pp. 13389. Publisher's VersionAbstract
Self-perceived health is an important factor for assessing urban residents’ satisfaction and quality of life. However, few have comprehensively investigated the impact of demographics, lifestyle and health awareness, indoor environment characteristics, and neighborhood features on self-perceived health. To fill this gap, we designed a framework using multivariable regressions to derive odd rations and to analyze the determinants of self-rated health, stratified into different sub-groups divided by gender, age, and neighborhood types. The study area is Chengdu, one of the most populous cities in western China. The results show that: (1) female respondents reported worse health, with household income level and marital status significantly affecting self-rated health; (2) elderly people reported the worst health, while unique factors affected only younger people (18–29 years old), such as gender, smoking, and indoor environment characteristics; and (3) different types of neighborhoods influence their residents’ perception of health differently due to historical establishment, current population composition, and housing conditions. Our study provides new observations on neighborhood types, while agreeing with previous studies on the influences of gender and age. We contribute to the field by providing a more complex understanding of the mechanism by which people rate their own health, which is important for understanding the satisfaction of urban residents and the built environment in which they live.
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