# 交通与城市环境

2022
Faan Chen, Chris P. Nielsen, Jiaorong Wu, and Xiaohong Chen. 2022. “Examining socio-spatial differentiation under housing reform and its implications for mobility in urban China.” Habitat International, 119, January, Pp. 102498.Abstract
Housing reform in socialist China has incurred considerable restructuring and transformation of urban space and society. Yet its specific socio-spatial outcomes have not been fully investigated from the perspective of housing type at the meso- and micro-levels. This study attempts to fill the gap by examining the nature and magnitude of the consequences of housing reform and the corresponding effects on mobility. Specifically, based on census data and a mobility survey, this paper combines statistical breakdowns and structural equation modeling to capture the socio-spatial differentiation of urban structure resulting from housing reform and its influences on individual vehicle kilometers traveled (VKT) and transportation walking. The results reveal that: (1) different types of housing tend to feature internally homogeneous populations in terms of socio-economic composition and socio-psychological condition, with pronounced social stratification; (2) residents in different types of housing display dramatically different travel styles, with substantial mobility inequities; (3) social differentiation appears to have spatial determinants; in particular spatial segregation contributes to increasing social exclusion; (4) the effects of spatial and social characteristics on mobility are led by housing type; and (5) individual mobility patterns are shaped by the joint influences of spatial and social dimensions of housing differentiation. The findings contribute to further understanding of socio-spatial differentiation in countries with a transitional housing market, suggesting that the design of land-use policies should recognize their social effects and that urban mobility planning practices should deliver sustainability that serves a diverse population, including in particular disadvantaged groups in public and replacement housing. This study serves as a mirror to observe the urban transition compared to other political economies and adds additional richness and diversity to the theoretical debates on the issue of socio-spatial differentiation and empirical evidence on residential and mobility inequities across global contexts.
Haiyang Lin, Caiyun Bian, Yu Wang, Hailong Li, Qie Sun, and Fredrik Wallin. 2022. “Optimal planning of intra-city public charging stations.” Energy, 238, Part C, January, Pp. 121948. Publisher's VersionAbstract
Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs.
2021
Yingying Lyu and Ann Forsyth. 2021. “Planning, Aging, and Loneliness: Reviewing Evidence About Built Environment Effects.” Journal of Planning Literature, August 2021. Publisher's VersionAbstract
Large numbers of people in many countries report being lonely with rates highest among the very old. Does the built environment affect loneliness among older people and if so, how? Using a scoping review, we examined associations between loneliness and built environments at the block, neighborhood, and city scales. The (1) neighborhood environment has received most attention. Research has also examined (2) urban contexts, (3) housing, and (4) transportation access. Findings are mixed with the stronger evidence that local resources, walkability, overall environment quality, housing options, and nearby transportation alternatives can help combat loneliness.
Chenghe Guan, R.B. Peiser, S. Fu, and C. Zhou. 2021. “New towns in China: The Liangzhu story.” In Toward Twenty-First Century New Towns, Peiser, R., and Forsyth, A. Eds. University of Pennsylvania Press.
Chenghe Guan, Jihoon Song, Michael Keith, Bo Zhang, Yuki Akiyama, Liangjun Da, Ryosuke Shibasaki, and Taisei Sato. 2021. “Seasonal variations of park visitor volume and park service area in Tokyo: A mixed-method approach combining big data and field observations.” Urban Forestry & Urban Greening, 58, March 2021, Pp. 126973. Publisher's VersionAbstract
Urban green and open space are important components of achieving the goal of planning sustainable cities, by offering health benefits to urban dwellers and providing socio-economic and environmental benefits to society. Recent literature studied the usage of urban parks, however, few has addressed seasonal fluctuations of park visitor volume, let alone seasonal variations of home-park travel distances and park service areas. This paper not only empirically shows the seasonal variations of park visits but also examines links between the park visit patterns and spatial characteristics of the case parks. Applying spatial analysis methods to location data of over 1 million anonymous mobile phone samples collected from January to December 2011, we analyzed the seasonal variations in six medium-sized urban parks, of which size falls under the category of ‘district parks,’ in central Tokyo. We also conducted content analysis of a Japanese place review website to understand visitor perceptions of the case parks. On the other hand, park spatial characteristics data were collected and summarized through various ways including field observation and satellite image analysis. The results show that (1) while notable seasonal variations of park visitor volume and park service area existed in all case parks, the degree of variation also differed from park to park; (2) spatial characteristics of parks were closely interlinked to seasonal cultural events, to visitor perceptions, and consequently to seasonal fluctuations of the park visit patterns. Lessons learned from the policy perspective include highly diverse user groups visit these medium-sized urban parks than what the typical guidelines assume, and seasonal patterns of their visits considerably vary from park to park, interacting with spatial characteristics of the parks. Hence, the urban park planning process should consider specific and detailed characteristics of parks and allocate resources to respond to dynamic park visit patterns beyond generic guidelines.
Yingying Lyu and Ann Forsyth. 2021. “Attitudes, Perceptions, and Walking Behavior in a Chinese City.” Journal of Transport & Health. Publisher's VersionAbstract

Introduction

An increasing number of walking studies discussed the relationship of walking with attitudes and perceptions. However, the findings were not consistent, and few studies examined the relationship between walking and attitudes to overall mobility and multiple modes. In this paper, we contribute to the debates by exploring the relationship between walking for transport and broad attitudes to urban mobility and transport modes.

Methods

Using a clustered random sample survey conducted in a second-tier city in China (N=1,048), we hypothesized that people with different attitudes have different amounts of walking for transport. Data analysis methods involved descriptive statistics, t-tests, Analysis of Variance (ANOVA), hierarchical logistic models, and hierarchical linear models.

Results

Positive attitudes and perceptions regarding multiple transport modes and related environments were associated with some walking for transport. T-tests indicated that those with different attitudes walked different amounts. Regression models showed that associations between attitudes and odds of people walking varied between genders. Males who perceived bus frequency was not a problem were more likely to walk. Females tended to walk when viewing transportation in the city as convenient. Both findings contribute to the understanding that positive perceptions of overall mobility in the city were associated with higher odds of walking. Meanwhile, among those who did walk, those with positive attitudes towards pedestrian safety crossing streets and those perceiving traffic jams as a problem in their daily trips spent more time walking.

Conclusion

This paper concludes that positive broad attitudes and perceptions of overall mobility and all transport modes are related to more walking activities. A better understanding of such relationships can provide a reference point for urban policies aiming at promoting walking for transport.

Yingying Lyu, Ann Forsyth, and Steven Worthington. 2021. “Built environment and self-rated health: comparing young, middle-aged, and older people in Chengdu, China.” Health Environments Research & Design Journal. Publisher's VersionAbstract
Objectives: This paper explores how the building-scale built environment is associated with self-rated health, examining differences in this association among younger, middle-aged, and older age groups. Features examined included building type, building condition, and sidewalk presence in front of dwellings.
Background: Understanding how the relationships between built environments and health vary across age groups helps to build a healthy environment for all. However, most studies have concentrated on the neighborhood or indoor environment, rather than whole buildings, and few have compared age groups.
Methods: This study analyzed survey data from 1,019 adults living in 40 neighborhoods in Chengdu, China, recruited through a clustered random sampling approach. It used a Bayesian logistic mixed effects model with interaction terms between age group indicators and other variables.
Results: Significant differences exist in the relationships of self-rated health with some environmental and other indicators among age groups. For older people, living in multi-floor buildings, having a household smoker, and undertaking fewer hours of weekly exercise were associated with lower odds of reporting good, very good, or excellent health. These relationships were not identified among middle-aged and younger people. More education was associated with higher odds of reporting better health among older and middle-aged groups.
Conclusions: Older people experience more health-related challenges compared to middle-aged and younger people. However, among the examined built environmental factors, building type was the only significant factor related to self-rated health among older people. To promote health among older people, this study recommends adding elevators in the multi-floor buildings.
Faan Chen, Jiaorong Wu, Xiaohong Chen, and Chris Nielsen. 2021. “Disentangling the impacts of the built environment and self-selection on travel behavior: An empirical study in the context of different housing types.” Cities, 116, September 2021, Pp. 103285. Publisher's VersionAbstract
Due to spatial heterogeneity worldwide, results from studies examining the effect of residential self-selection on travel behavior vary substantially. As a result of housing reform, the unique housing allocation system in China is a prime example of a context where the self-selection effect may conflict with international knowledge. Using a sample of 3836 residents, whom are living in Transit-Oriented Development (TOD) and non-TOD neighborhoods in Shanghai, this study untangles the effects that the built environment and residential self-selection have on travel behavior, in the context of diversified housing types in urban China. Specifically, this paper employs propensity score matching (PSM) to quantitate the relative importance of the built environment itself, verses residential self-selection, in influencing travel behavior for each of the housing types. The results show that the residential self-selection effect in the four types of housing (work-unit, commodity, public, and replacement) accounts for 15.2%, 30.7%, 18.5%, and 5.9% of the total impact on vehicle kilometers traveled (VKT), respectively. These findings expand the international database of point estimates in the relative contribution of self-selection toward the impact on travel behavior across global contexts, providing a comprehensive framework for similar studies on self-selection in other parts of the world.
Haiyang Lin, Caiyun Bian, Yu Wang, Hailong Li, Qie Sun, and Fredrik Wallen. 2021. “Optimal planning of intra-city public charging stations.” Energy, Volume 238, Part C, 1 January 2022, Pp. 121948. Publisher's VersionAbstract
Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs.
2020
Chenghe Guan, Jihoon Song, Michael Keith, Yuki Akiyama, Ryosuke Shibasaki, and Taisei Sato. 2020. “Delineating urban park catchment areas using mobile phone data: A case study of Tokyo.” Computers, Environment and Urban Systems, 81. Publisher's VersionAbstract
Urban parks can offer both physical and psychological health benefits to urban dwellers and provide social, economic, and environmental benefits to society. Earlier research on the usage of urban parks relied on fixed distance or walking time to delineate urban park catchment areas. However, actual catchment areas can be affected by many factors other than park surface areas, such as social capital cultivation, cultural adaptation, climate and seasonal variation, and park function and facilities provided. This study advanced this method by using mobile phone data to delineate urban park catchment area. The study area is the 23 special wards of Tokyo or tokubetsu-ku, the core of the capital of Japan. The location data of over 1 million anonymous mobile phone users was collected in 2011. The results show that: (1) the park catchment areas vary significantly by park surface areas: people use smaller parks nearby but also travel further to larger parks; (2) even for the parks in the same size category, there are notable differences in the spatial pattern of visitors, which cannot be simply summarized with average distance or catchment radius; and (3) almost all the parks, regardless of its size and function, had the highest user density right around the vicinity, exemplified by the density-distance function closely follow a decay trend line within 1-2 km radius of the park. As such, this study used the density threshold and density-distance function to measure park catchment. We concluded that the application of mobile phone location data can improve our understanding of an urban park catchment area, provide useful information and methods to analyze the usage of urban parks, and can aid in the planning and policy-making of urban parks.
Haikun Wang, Xiaojing He, Xinyu Liang, Ernani F. Choma, Yifan Liu, Li Shan, Haotian Zheng, Shaojun Zhang, Chris P. Nielsen, Shuxiao Wang, Ye Wu, and John S. Evans. 2020. “Health benefits of on-road transportation pollution control programs in China.” Proceedings of the National Academy of Sciences, Sept 2020, 201921271. Publisher's VersionAbstract
China started to implement comprehensive measures to mitigate traffic pollution at the end of 1990s, but the comprehensive effects, especially on ambient air quality and public health, have not yet been systematically evaluated. In this study, we analyze the effects of vehicle emission control measures on ambient air pollution and associated deaths attributable to long-term exposures of fine particulate matter (PM2.5) and O3 based on an integrated research framework that combines scenario analysis, air quality modeling, and population health risk assessment. We find that the total impact of these control measures was substantial. Vehicular emissions during 1998–2015 would have been 2–3 times as large as they actually were, had those measures not been implemented. The national population-weighted annual average concentrations of PM2.5 and O3 in 2015 would have been higher by 11.7 μg/m3 and 8.3 parts per billion, respectively, and the number of deaths attributable to 2015 air pollution would have been higher by 510 thousand (95% confidence interval: 360 thousand to 730 thousand) without these controls. Our analysis shows a concentration of mortality impacts in densely populated urban areas, motivating local policymakers to design stringent vehicle emission control policies. The results imply that vehicle emission control will require policy designs that are more multifaceted than traditional controls, primarily represented by the strict emission standards, with careful consideration of the challenges in coordinated mitigation of both PM2.5 and O3 in different regions, to sustain improvement in air quality and public health given continuing swift growth in China’s vehicle population.
Chenghe Guan, Jialin Liu, Sumeeta Srinivasan, Bo Zhang, Liangjun Da, and Chris P. Nielsen. 2020. “The influence of neighborhood types on active transport in China’s growing cities.” Transportation Research Part D: Transport and Environment, 80, 102273. Publisher's VersionAbstract
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.
Chenghe Guan and Ann Forsyth. 2020. “The influence of urban form and socio-demographics on active transport: a 40 neighborhoods study in Chengdu, China.” Journal of Transport and Land Use . Publisher's VersionAbstract
In China a centralized planning culture has created similar neighborhoods across the country. Using a survey of 1,048 individuals conducted in 2016 in Chengdu—located in a carefully conceptualized typology of neighborhood forms—we analyzed the associations between individual and neighborhood characteristics and active or non-motorized transport behavior. Using several multiple logistic and multi-level models, we show how neighborhoods were categorized and the number of categories or neighborhood types affected the magnitude of the associations with active transport but not the direction. People taking non-work trips were more likely to use active compared with motorized modes in all neighborhood types. Neighborhood type was significant in models, but so were many other individual-level variables and infrastructural and locational features such as bike lanes and location near the river. Of the 3-D physical environment variables, floor area ratio (a proxy for density) was only significant in one model for non-work trips. Intersection density and dissimilarity (land use diversity) were only significant in a model for work trips. This study shows that to develop strong theories about the connections between active transport and environments, it is important to examine different physical and cultural contexts and perform sensitivity analyses. Research in different parts of China can help provide a more substantial base for evidence-informed policy-making. Planning and design recommendations related to active transport need to consider how neighborhoods, built environments, and personal characteristics interact in different kinds of urban environments.
Chenghe Guan and Peter Rowe. 2020. “Multi-criteria locational analysis for retail development in small towns.” In The Geography of Mobility, Wellbeing and Development: Understanding China’s Transformations through Big Data, 1st ed., Pp. 220. London: Routledge. Publisher's VersionAbstract

Big data is increasingly regarded as a new approach for understanding urban informatics and complex systems. Today, there is unprecedented data availability, with detailed remote-sensed data on the built environment and rich mineable web-based sources in the form of social media, web mapping, information services and other sources of unstructured "big data".

This book brings together a group of international contributors to consider the geographical implications of mobility, wellbeing and development within and across Chinese cities through location-based big data perspectives. The degree of urban sprawl, productive density and vibrancy can be reflected from location-based social media big data. The challenge is to identify, map and model these relationships to develop cities at different places in the urban hierarchical system that are more sustainable. This edited book aims to tackle these issues through two inter-related geographical scales: inter-city level and intra-city level.

The text is designed for graduate courses in planning, geography, public policy and administration, and for international researchers who are involved in urban and regional economics and economic geography.

2019
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.
Sumeeta Srinivasan, Chenghe Guan, and Chris P. Nielsen. 2019. “Built environment, income and travel behavior: Change in the city of Chengdu 2005-2016.” International Journal of Sustainable Transportation. Publisher's VersionAbstract
In this paper, we look at differences in travel behavior and location characteristics across income in Chengdu, China at two points of time, 2005 and 2016, using household travel surveys. Specifically, we compare changes over time for different income groups for Chengdu in 2005 and 2016. We find that walking or biking remains the most common mode for all income groups but higher-income households appear to have more choices depending on the proximity of their neighborhood to downtown. We also find that both average local and average regional access have worsened since 2005. Furthermore, it appears that there is less economic diversity within neighborhoods in 2016 when compared to 2005, with more locations appearing to have 40% or more of low-, middle-, or high-income households than in the past. Finally, we find that low-income households and older trip makers are more likely to walk or bike and that high-income households are the most likely to own cars and use motorized modes. Built environment characteristics like mixed land use appear to significantly reduce travel time in 2016 but do not result in higher non-motorized transport mode share. We contribute to existing literature by evaluating changes in the relationship of built environment and travel behavior during a period of rapid urbanization and economic growth in a Chinese city.
Haikun Wang, Xi Lu, Yu Deng, Yaoguang Sun, Chris P. Nielsen, Yifan Liu, Ge Zhu, Maoliang Bu, Jun Bi, and Michael B. McElroy. 2019. “China’s CO2 peak before 2030 implied from diverse characteristics and growth of cities.” Nature Sustainability, 2, Pp. 748–754. Publisher's VersionAbstract
China pledges to peak CO2 emissions by 2030 or sooner under the Paris Agreement to limit global warming to 2 °C or less by the end of the century. By examining CO2 emissions from 50 Chinese cities over the period 2000–2016, we found a close relationship between per capita emissions and per capita gross domestic product (GDP) for individual cities, following the environmental Kuznets curve, despite diverse trajectories for CO2 emissions across the cities. Results show that carbon emissions peak for most cities at a per capita GDP (in 2011 purchasing power parity) of around US$21,000 (80% confidence interval: US$19,000 to 22,000). Applying a Monte Carlo approach to simulate the peak of per capita emissions using a Kuznets function based on China’s historical emissions, we project that emissions for China should peak at 13–16 GtCO2 yr−1 between 2021 and 2025, approximately 5–10 yr ahead of the current Paris target of 2030. We show that the challenges faced by individual types of Chinese cities in realizing low-carbon development differ significantly depending on economic structure, urban form and geographical location.
Chenghe Guan, Michael Keith, and Andy Hong. 2019. “Designing walkable cities and neighborhoods in the era of urban big data.” Urban Planning International, 34, 5, Pp. 9-15. Publisher's VersionAbstract
In this paper, we discuss walkable cities from the perspective of urban planning and design in the era of digitalization and urban big data. We start with a brief review on historical walkable cities schemes; followed by a deliberation on what a walkable city is and what the spatial elements of a walkable city are; and a discussion on the emerging themes and empirical methods to measure the spatial and urban design features of a walkable city. The first part of this paper looks at key urban design propositions and how they were proposed to promote walkability. The second part of this paper discusses the concept of walkability, which is fundamental to designing a walkable city. We emphasize both the physical (walkways, adjacent uses, space) and the perceived aspects (safety, comfort, enjoyment), and then we look at the variety of spatial elements constituting a walkable city. The third part of this paper looks at the emerging themes for designing walkable cities and neighborhoods. We discuss the application of urban big data enabled by growing computational powers and related empirical methods and interdisciplinary approaches including spatial planning, urban design, urban ecology, and public health. This paper aims to provide a holistic approach toward understanding of urban design and walkability, re-evaluate the spatial elements to build walkable cities, and discuss future policy interventions.
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.
Jing Cao, Mun S Ho, and Wenhao Hu. 2019. “Energy consumption of urban households in China.” China Economic Review, 58, 101343. Publisher's VersionAbstract
We estimate China urban household energy demand as part of a complete system of consumption demand so that it can be used in economy-wide models. This allows us to derive cross-price elasticities unlike studies which focus on one type of energy. We implement a two-stage approach and explicitly account for electricity, domestic fuels and transportation demand in the first stage and gasoline, coal, LPG and gas demand in the second stage. We find income inelastic demand for electricity and home energy, but the elasticity is higher than estimates in the rich countries. Demand for total transportation is income elastic. The price elasticity for electricity is estimated to be −0.5 and in the range of other estimates for China, and similar to long-run elasticities estimated for the U.S.