Urban Transportation, Land Use, Air Quality, and Health

Yu Deng, Shenghe Liu, Jianming Cai, Xi Lu, and Chris P Nielsen. 2015. “Spatial pattern and evolution of Chinese provincial population: Methods and empirical study.” Journal of Geographical Sciences, 25, 12, Pp. 1507-1520. Publisher's VersionAbstract

China has been experiencing an unprecedented urbanization process. In 2011, China’s urban population reached 691 million with an urbanization rate of 51.27%. Urbanization level is expected to increase to 70% in China in 2030, reflecting the projection that nearly 300 million people would migrate from rural areas to urban areas over this period. At the same time, the total fertility rate of China’s population is declining due to the combined effect of economic growth, environmental carrying capacity, and modern social consciousness. The Chinese government has loosened its “one-child policy” gradually by allowing childbearing couples to have the second child as long as either of them is from a one-child family. In such rapidly developing country, the natural growth and spatial migration will consistently reshape spatial pattern of population. An accurate prediction of the future spatial pattern of population and its evolution trend are critical to key policy-making processes and spatial planning in China including urbanization, land use development, ecological conservation and environmental protection. In this paper, a top-down method is developed to project the spatial distribution of China’s future population with considerations of both natural population growth at provincial level and the provincial migration from 2010 to 2050. Building on this, the spatial pattern and evolution trend of Chinese provincial population are analyzed. The results suggested that the overall spatial pattern of Chinese population will be unlikely changed in next four decades, with the east area having the highest population density and followed by central area, northeast and west area. Four provinces in the east, Shanghai, Beijing, Tianjin and Jiangsu, will remain the top in terms of population density in China, and Xinjiang, Qinghai and Tibet will continue to have the lowest density of population. We introduced an index system to classify the Chinese provinces into three categories in terms of provincial population densities: Fast Changing Populated Region (FCPR), Low Changing Populated Region (LCPR) and Inactive Populated Region (IPR). In the FCPR, China’s population is projected to continue to concentrate in net immigration leading type (NILT) area where receives nearly 99% of new accumulated floating population. Population densities of Shanghai, Beijing, Zhejiang will peak in 2030, while the population density in Guangdong will keep increasing until 2035. Net emigration leading type (NELT) area will account for 75% of emigration population, including Henan, Anhui, Chongqing and Hubei. Natural growth will play a dominant role in natural growth leading type area, such as Liaoning and Shandong, because there will be few emigration population. Due to the large amount of moving-out labors and gradually declining fertility rates, population density of the LCPR region exhibits a downward trend, except for Fujian and Hainan. The majority of the western provinces will be likely to remain relatively low population density, with an average value of no more than 100 persons per km2.

Jieping Li, Joan L Walker, Sumeeta Srinivasan, and William P Anderson. 2010. “Modeling private car ownership in China: Investigating the impact of urban form across mega-cities.” Transportation Research Record , 2193, Pp. 76-84. Publisher's VersionAbstract
The rising prevalence of private cars in the developing world is causing serious congestion and pollution. In China, private cars started to emerge as an important travel mode in the past decade. Prospective research on the relationship between urban form and car ownership is relatively uncommon in the developing world, and China offers a unique study opportunity, given the tremendous increases in private cars and fast-paced urbanization over the past decade. This study investigates the influence of urban form on car ownership as well as the impact of other socioeconomic and demographic factors on private car ownership across megacities in China. Analysis was conducted through the use of data from 36 megacities and two household survey data sets collected in Beijing and the city of Chengdu, China. Ordinary least squares regression and discrete choice models were employed to execute the aggregate and disaggregate analysis of the urban form impact on private car ownership across cities. The statistical model results demonstrate that urban affluence, urban scale, and road infrastructure supply factors have significant positive effects on the city level of private car ownership across cities. Population density calculated at the subdistrict level, however, had a significant negative effect on private car ownership across cities. Households with private cars were found to prefer to live close to urban centers where amenities were readily available. The results provide evidence for urban planners and policy makers.

This paper uses data from the Project's household survey in Chengdu, Sichuan.

Y. Zhao, LP Qiu, RY Xu, FJ Xie, Q. Zhang, YY Yu, C.P. Nielsen, HX Qin, H.K. Wang, XC Wu, WQ Li, and J. Zhang. 2015. “Advantages of city-scale emission inventory for urban air quality research and policy: the case of Nanjing, a typical industrial city in the Yangtze River Delta, China.” Atmospheric Chemistry and Physics, 15, Pp. 12623-12644. Publisher's VersionAbstract

With most eastern Chinese cities facing major air quality challenges, there is a strong need for city-scale emission inventories for use in both chemical transport modeling and the development of pollution control policies. In this paper, a high-resolution emission inventory of air pollutants and CO2 for Nanjing, a typical large city in the Yangtze River Delta, is developed incorporating the best available information on local sources. Emission factors and activity data at the unit or facility level are collected and compiled using a thorough onsite survey of major sources. Over 900 individual plants, which account for 97% of the city's total coal consumption, are identified as point sources, and all of the emission-related parameters including combustion technology, fuel quality, and removal efficiency of air pollution control devices (APCD) are analyzed. New data-collection approaches including continuous emission monitoring systems and real-time monitoring of traffic flows are employed to improve spatiotemporal distribution of emissions. Despite fast growth of energy consumption between 2010 and 2012, relatively small inter-annual changes in emissions are found for most air pollutants during this period, attributed mainly to benefits of growing APCD deployment and the comparatively strong and improving regulatory oversight of the large point sources that dominate the levels and spatial distributions of Nanjing emissions overall. The improvement of this city-level emission inventory is indicated by comparisons with observations and other inventories at larger spatial scale. Relatively good spatial correlations are found for SO2, NOX, and CO between the city-scale emission estimates and concentrations at 9 state-opertated monitoring sites (R = 0.58, 0.46, and 0.61, respectively). The emission ratios of specific pollutants including BC to CO, OC to EC, and CO2 to CO compare well to top-down constraints from ground observations. The inter-annual variability and spatial distribution of NOX emissions are consistent with NO2 vertical column density measured by the Ozone Monitoring Instrument (OMI). In particular, the Nanjing city-scale emission inventory correlates better with satellite observations than the downscaled Multi-resolution Emission Inventory for China (MEIC) does when emissions from power plants are excluded. This indicates improvement in emission estimation for sectors other than power generation, notably industry and transportation. High-resolution emission inventory may also provide a basis to consider the quality of instrumental observations. To further improve emission estimation and evaluation, more measurements of both emission factors and ambient levels of given pollutants are suggested; the uncertainties of emission inventories at city scale should also be fully quantified and compared with those at national scale. 


Joan L Walker, Jieping Li, Sumeeta Srinivasan, and Denis Bolduc. 2010. “Travel demand models in the developing world: Correcting for measurement errors.” Transportation Letters, 2, 4, Pp. 231-243. Publisher's VersionAbstract
While transport modelers in developed countries are accustomed to working with relatively rich datasets including transport networks and land use data, such databases are rarely available in developing countries. However, developing countries such as China with its immense rate of economic growth are, arguably, most in need of demand models. The research addressed in this paper is how to develop mode choice models for planning and policy analysis when high quality level of service data are not available. The research makes use of a 1,001 household travel and activity survey from Chengdu collected by the China Project at Harvard University in 2005. Chengdu has an urban population of over 3 million and a GDP growth rate of over 20% per year. The survey contains a rich array of self-assessed information on available modes and accessibility and also includes a number of attitudinal questions. The approach taken here is to treat level of service as a latent (i.e., unobservable) variable. Measurement equations (from the structural equation model paradigm) are used to infer latent level of service, and these equations are integrated with the mode choice model. Our initial results indicate that models that do not correct for measurement error may significantly underestimate travelers' values of time. The methodological approach employed has potential for improving models estimated with higher quality network data, because it can correct for measurement error that exists, for example, in network-derived level of service variables.

This paper is based on data from the Project's household survey in Chengdu, Sichuan.

Xiannuan Lin and Karen R. Polenske. 1998. “Energy use and air-pollution impacts of China’s transportation growth.” In Energizing China: Reconciling Environmental Protection and Economic Growth, edited by Michael B. McElroy, Chris P Nielsen, Peter Lydon, and eds.. Cambridge, MA: HUCE/Harvard University Press. Publisher's VersionAbstract

As China develops its booming, fossil fuel-powered economy, is it taking lessons from the history of Western industrialization and the unforeseen environmental harms that accompanied it? Given the risks of climate change, is there an imperative, shared responsibility to help China respond to the environmental effects of its coal dependence? By linking global hazards to local air pollution concerns—from indoor stove smoke to burgeoning ground-level ozone—this volume of eighteen studies seeks integrated strategies to address simultaneously a range of harmful emissions. Counterbalancing the scientific inquiry are key chapters on China’s unique legal, institutional, political, and cultural factors in effective pollution control.

Energizing China, the stage-setting publication of an ongoing program of Harvard–China research collaboration, is distinguished by its conceptual breadth and spirit of exchange. Its contributors include twenty-two Western and seventeen Chinese scholars with a disciplinary reach that includes science, public health, engineering, economics, public policy, law, business, and China studies.

Peter Rogers and Sumeeta Srinivasan. 2008. “Comparing sustainable cities—Examples from China, India and the USA.” In Sustainable urban development in China: Wishful thinking or reality?, edited by Marco Keiner. Munster, Germany: Verlagshaus Monsenstein und Vannerdat OHG. Publisher's VersionAbstract
Due to an unprecedented economic
growth, fuelled by a pro-growth policy,
China’s cities are mushrooming.

In the coming years, the mass migration
from rural to urban areas will continue.

The demand for energy and resources will
continue to rise.

China’s cities will increasingly contribute
to global warming and the depletion of
the environment.

The crucial question is: Can urban development
in China become sustainable?
Sumeeta Srinivasan and Peter P. Rogers. 2005. “Travel behavior of low-income residents: Studying two contrasting locations in the city of Chennai, India.” Journal of Transport Geography, 13, 3, Pp. 265-274. Publisher's VersionAbstract
Data on travel behavior in developing countries like India is minimal. This is especially true for the relatively poor residents of urban India. They are dependent on fewer options for transportation and have little choice in terms of employment location given their dependence on walking or bicycles. This is significant in cities like Chennai because employment is highly concentrated in the center of the city. In this study, the results of a survey of 70 households in Chennai were analyzed to estimate statistical models of travel behavior with respect to mode choice and trip frequency. The households were located in two different parts of the city: one group of households lived close to the city center (in a settlement called Srinivasapuram) and the other at the periphery (in a location called Kannagi Nagar). We analyze the differences in travel behavior due to differences in accessibility to employment and services between the two settlement locations. The results indicate that differences in accessibility appear to strongly affect travel behavior. Residents in the centrally located settlement were more likely to use non-motorized modes for travel (walk or bicycle) than the peripherally located residents. It is vital therefore that, policy makers in India consider location of employment in the planning of new housing for low-income households.
Rui Wang. 2011. “Autos, transit and bicycles: Comparing the costs in large Chinese cities.” Transport Policy, 18, 1, Pp. 139-146. Publisher's VersionAbstract
This study compares the full costs of seven passenger modes in the large Chinese cities facing the difficult yet crucial choice among alternative passenger transportation systems. The seven modes are evaluated at varied traffic volumes in hypothetical radial and circumferential commuting corridors. Using detailed estimates of private and social costs, the full cost of each mode is minimized by optimizing infrastructure investment and operation plans. On all corridors and across different scenarios, commuting by one or more forms of bus transit or bicycle costs less than automobile or rail. Nonetheless, in circumferential corridors, rail can be almost as cost-effective as bus under certain conditions, and bicycle can be less cost-effective than bus in some cases. Unlike results from similar studies conducted in the US, automobile commuting does not cost less than bus transportation at low traffic volumes.
Yanxia Zhang, Haikun Wang, Sai Liang, Ming Xu, Qiang Zhang, Hongyan Zhao, and Jun Bi. 2015. “A dual strategy for controlling energy consumption and air pollution in China's metropolis of Beijing.” Energy, 81, 1 March, Pp. 294-303. Publisher's VersionAbstract

It is critical to alleviate problems of energy and air pollutant emissions in a metropolis because these areas serve as economic engines and have large and dense populations. Drivers of fossil fuel use and air pollutants emissions were analyzed in the metropolis of Beijing during 1997-2010. The analyses were conducted from both a bottom-up and a top-down perspective based on the sectoral inventories and structural decomposition analysis (SDA). From a bottom-up perspective, the key energy-intensive industrial sectors directly caused the variations in Beijing's air pollution by means of a series of energy and economic policies. From a top-down perspective, variations in production structures caused increases in most materials during 2000-2010, but there were decreases in PM10 and PM2.5 emissions during 2005-2010. Population growth was found to be the largest driver of energy consumption and air pollutant emissions during 1997-2010. This finding suggests that avoiding rapid population growth in Beijing could simultaneously control energy consumption and air pollutant emissions. Mitigation policies should consider not only the key industrial sectors but also socioeconomic drivers to co-reduce energy consumption and air pollution in China's metropolis.

Xinyu Chen, Xi Lu, Michael B. McElroy, Chris P Nielsen, and Chongqing Kang. 2014. “Synergies of wind power and electrified space heating: A case study for Beijing.” Environmental Science & Technology, 48, 3, Pp. 2016–2024. Publisher's VersionAbstract

Demands for electricity and energy to supply heat are expected to expand by 71% and 47%, respectively, for Beijing in 2020 relative to 2009. If the additional electricity and heat are supplied solely by coal as is the current situation, annual emissions of CO2 may be expected to increase by 59.6% or 99 million tons over this interval. Assessed against this business as usual (BAU) background, the present study indicates that significant reductions in emissions could be realized using wind-generated electricity to provide a source of heat, employed either with heat pumps or with electric thermal storage (ETS) devices. Relative to BAU, reductions in CO2 with heat pumps assuming 20% wind penetration could be as large as 48.5% and could be obtained at a cost for abatement of as little as $15.6 per ton of avoided CO2. Even greater reductions, 64.5%, could be realized at a wind penetration level of 40% but at a higher cost, $29.4 per ton. Costs for reduction of CO2 using ETS systems are significantly higher, reflecting the relatively low efficiency for conversion of coal to power to heat.

Sumeeta Srinivasan. 2010. “Linking travel behavior and location in Chengdu, China: A geographically weighted approach.” Transportation Research Record, 2193, Pp. 85-95. Publisher's VersionAbstract
This study uses geographically weighted regressions and multilevel models to understand the implications of location and attitudinal characteristics for travel behavior in Chengdu, China. In particular, the estimated distance traveled and the mode choice of nonmotorized versus motorized vehicles for work- and school-related trips were examined by using a recent household trip diary data set. The results suggest that location characteristics may be influential in the prediction of travel behavior but cannot be fully captured by simple categorization such as inner ring location versus peripheral location. Variations in travel behavior can be related to socioeconomic and location variables in ways that vary by location in a complex manner. Policy makers should therefore reconsider the role that location and attitudinal implications may play in meeting travel demand in rapidly developing cities like Chengdu.
Yu Deng and Sumeeta Srinivasan. 2016. “Urban land use change and regional access: A case study in Beijing, China.” Habitat International, 51, February, Pp. 103-113. Publisher's VersionAbstract

In the recent past Beijing has experienced rapid development. This growth has been accompanied by many problems including traffic congestion and air pollution. Understanding what stimulates urban growth is important for sustainable development in the coming years. In this paper, we first estimate a binary auto-logistic model of land use change, using physical and socioeconomic characteristics of the location and its access to major centers within the city as predictors. We find that variables determining regional access, like time distance to the city center, the Central Business District (CBD), industrial centers, employment centers, and the transportation system, significantly impact urban land conversion. By using measures of access to predict land use change we believe that we can better understand the planning implications of urban growth not only in Beijing but other rapidly developing cities.

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