2016年7月,由Chris P. NIELSEN研究员(哈佛大学中国项目)、James HAMMITT教授(哈佛大学T.H.Chan公共卫生学院)、沈明明和严洁教授(北京大学政府管理学院)领衔,在中国四川省成都市完成了一项跨学科的家庭调研。结合2005年同样由哈佛大学中国项目联合北京大学进行的同类调研的数据,形成了一组涵盖成都的经济、城市化、交通出行习惯、土地使用、空气质量和环境健康的跨越11年的时间序列数据。除了这次对成都市的多层面的调研,哈佛大学中国项目也对交通、土地使用、排放、空气质量和/或健康进行了城市尺度的独立调研。



与Hammitt教授和Nielsen研究员一同进行后续数据分析的合作人员包括哈佛大学中国项目研究员关成贺(哈佛大学设计研究院)、Sumeeta SRINIVASAN教授(塔夫斯大学城市与环境政策与规划系)、王海鲲教授(南京大学环境学院),以及GENG Fangli(哈佛大学 T.H.Chan公共卫生学院)。


Chenghe Guan, Sumeeta Srinivasan, and Chris P. Nielsen. 2019. “Does neighborhood form influence low-carbon transportation in China?” Transportation Research Part D: Transport and Environment, 67, Pp. 406-420. Publisher's VersionAbstract
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.
Chenghe Guan and Richard B. Peiser. 2018. “Accessibility, urban form, and property value: Toward a sustainable urban spatial structure.” Journal of Transport and Land Use, 11, 1, Pp. 1057-1080. Publisher's VersionAbstract
The effects of metro system development and urban form on housing prices highly depend on the spatial temporal conditions of urban neighborhoods. However, scholars have not yet comprehensively examined these interactions at a neighborhood-scale. This study assesses metro access, urban form, and property value at both the district- and neighborhood-level. The study area is Pudong, Shanghai, where metro system development has coincided with rapid urban growth. Two hundred and seventy-nine neighborhoods from 13 districts of Shanghai are randomly selected for the district-level investigation and 31 neighborhoods from Pudong are selected for the neighborhood-level investigation. The analysis of variance shows that metro access is more positively correlated to property price in Pudong than other districts. The Pearson correlation, principle component, and ordinary least square regression analyses show that while accessibility attributes have a positive influence on housing prices, neighborhood characteristics also exhibit a pronounced impact on property price change over time. This study extends our knowledge on how metro system development interacts with landuse efficiency and discusses planning policies that correspond to different stages of development.
Mengyao Han, Bo Zhang, Yuqing Zhang, and Chenghe Guan. 2019. “Agricultural CH4 and N2O emissions of major economies: Consumption-vs. production-based perspectives.” Journal of Cleaner Production, 210, Pp. 276-286. Publisher's VersionAbstract
Agriculture is one of the most important sectors for global anthropogenic methane (CH4) and nitrous oxide (N2O) emissions. While much attention has been paid to production-side agricultural non-CO2 greenhouse gas (ANGHG) emissions, less is known about the emissions from the consumption-based perspective. This paper aims to explore the characteristics of agricultural CH4 and N2O emissions of global major economies by using the latest emission data from the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) and the recently available global multi-regional input-output model from the World Input-Output Database (WIOD). The results show that in 2014, the 42 major economies together accounted for 60.7% and 65.0% of global total direct and embodied ANGHG emissions, respectively. The consumption-based ANGHG emissions in the US, Japan, and the EU were much higher than their production-based emissions, while the converse was true for Brazil, Australia, and India. The global-average embodied ANGHG emissions per capita was 0.7 t CO2-eq, but major developing countries such as China, India, Indonesia and Mexico were all below this average value. We find that the total transfer of embodied ANGHG emissions via international trade was 622.4 Mt CO2-eq, 11.9% of the global total. China was the largest exporter of embodied ANGHG emissions, while the US was the largest importer. Most developed economies were net importers of embodied emissions. Mexico-US, China-US, China-EU, China-Japan, China-Russia, Brazil-EU, India-EU and India-US formed the main bilateral trading pairs of embodied emission flows. Examining consumption-based inventories can be useful for understanding the impacts of final demand and international trade on agricultural GHG emissions and identifying appropriate mitigation potentials along global supply chains.


Summer RA


September 26, 2018

A Harvard Gazette article by Al Powell



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