# Transportation & Urban Environment

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.
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.

Tao Song, Jian-ming Cai, Teresa Chahine, Hui Xu, and Fang-qu Niu. 2014. “Modeling urban metabolism of Beijing city, China, with coupled system dynamics: Emergy model.” Stochastic Environmental Research and Risk Assessment, 28, 6, Pp. 1511-1524. Publisher's VersionAbstract

Chinese cities are plagued by the rise in resource and energy input and output over the last decade. At the same time, the scale and pace of economic development sweeping across Chinese cities have revived the debate about urban metabolisms, which could be simply seen as the ratio of output to resource and energy input in urban systems. In this study, an emergy (meaning the equivalent solar energy) accounting, sustainable indices of urban metabolisms, and an urban metabolic system dynamics model, are developed in support of the research task on Chinese cities ‘metabolisms and their related policies. The dynamic simulation model used in the paper is capable of synthesizing component-level knowledge into system behavior simulation at an integrated level, which is directly useful for simulating and evaluating a variety of decision actions and their dynamic consequences. For the study case, interactions among a number of Beijing’s urban emergy components within a time frame of 20 years (from 2010 to 2030) are examined dynamically. Six alternative policy scenarios are implemented into the system simulation. Our results indicate that Beijing’s current model of urban metabolism—tertiary industry oriented development mode—would deliver prosperity to the city. However, the analysis also shows that this mode of urban metabolism would weaken urban self-support capacity due primarily to the large share of imported and exported emergy in the urban metabolic system. The keys of improving the efficiency of urban metabolism include the priority on the renewable resource and energy, increase in environmental investment and encouragement on innovative technologies of resource and energy utilization, et al.

Karolin Kokaz and Peter P. Rogers. 2002. “Urban transportation planning for air quality management: Case study of Delhi, India, and role of social and economic costs in welfare maximization of mobility choice.” Transportation Research Record, 1817, Pp. 42-49. Publisher's VersionAbstract
Recent economic expansion and population growth in developing countries have had a big impact on the development of large cities like Delhi, India. Accompanied by Delhi's rapid spatial growth over the last 25 years, urban sprawl has contributed to increased travel. The vehicle fleet projected at current growth rates will result in more than 13 million vehicles in Delhi in 2020. Planning and managing such a rapidly growing transport sector will be a challenge. Choices made now will have effects lasting well into the middle of the century. With such rapid transport growth rates, automobile emissions have become the fastest increasing source of urban air pollution. In India, most urban areas, including Delhi, already have major air pollution problems that could be greatly exacerbated if growth of the transport sector is managed unwisely. The transport plans designed to meet such large increases in travel demand will have to emphasize the movement of people, not vehicles, for a sustainable transportation system. Therefore, a mathematical model was developed to estimate the optimal transportation mix to meet this projected passenger-km demand while satisfying environmental goals, reducing congestion levels, and improving system and fuel efficiencies by exploiting a variety of policy options at the minimum overall cost or maximum welfare from transport. The results suggest that buses will continue to satisfy most passenger transport in the coming decades, so planning done in accordance with improving bus operations is crucial.
Yuxuan Wang, Jiming Hao, Michael B. McElroy, J. William Munger, Hong Ma, Dan Chen, and Chris P Nielsen. 2009. “Ozone air quality during the 2008 Beijing Olympics: Effectiveness of emission restrictions.” Atmospheric Chemistry and Physics, 9, 14, Pp. 5237-5251. Publisher's VersionAbstract
A series of aggressive measures was launched by the Chinese government to reduce pollutant emissions from Beijing and surrounding areas during the Olympic Games. Observations at Miyun, a rural site 100 km downwind of the Beijing urban center, show signiﬁcant decreases in concen-trations of O3, CO, NOy, and SO2 during August 2008, rel-ative to August 2006–2007. The mean daytime mixing ratio of O3 was lower by about 15 ppbv, reduced to 50 ppbv, in August 2008. The relative reductions in daytime SO2, CO, and NOy were 61%, 25%, and 21%, respectively. Changes in SO2 and in species correlations from 2007 to 2008 indicate that emissions of SO2, CO, and NOx were reduced at least by 60%, 32%, and 36%, respectively, during the Olympics. Analysis of meteorological conditions and interpretation of observations using a chemical transport model suggest that although the day-to-day variability in ozone is driven mostly by meteorology, the reduction in emissions of ozone pre-cursors associated with the Olympic Games had a signiﬁ-cant contribution to the observed decrease in O3 during Au-gust 2008, accounting for 80% of the O3 reduction for the month as a whole and 45% during the Olympics Period (8–24 August). The model predicts that emission restrictions such as those implemented during the Olympics can affect O3 far beyond the Beijing urban area, resulting in reductions in boundary layer O3 of 2–10 ppbv over a large region of the North China Plain and Northeastern China.
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.

Tao Song, Jianming Cai, Teresa Chahine, and Yu Deng. 2013. “Urban metabolism model based on the emergy theory: A case study of 31 Chinese cities.” Food, Agriculture and Environment, 11, 3&4, Pp. 2353-2361. Publisher's VersionAbstract

Urban systems, with the overall fluxes of energy, water, material, and wastes, can be modeled with a range of metabolic processes. To quantify the urban metabolism, we use the “emergy” assessment method (all materials and energy are transformed to solar energy equivalents) and then present a group of urban metabolic indicators, which quantify urban metabolic balance, capacity, and outputs to assess a city’s metabolic efficiencies. In this paper, we use 31 Chinese cities as a sample to illustrate how the model can be operated to evaluate the urban metabolism by emergy analysis. Our results indicate that metropolises and coastal cities were more metabolically efficient with higher metabolic balance, capacities, and outputs; but with more external dependency on imported resources. Central and western cities had lower metabolic efficiencies, with a high ratio of non-renewable emergy reliance. Policy implications highlight the need for renewable energy sources and improved management of imported services, goods, and fuels to achieve higher urban resilience and sustainability.

1998. Energizing China: Reconciling Environmental Protection and Economic Growth. 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.

Sumeeta Srinivasan. 2008. “A visual exploration of the accessibility of low income women: Chengdu, China and Chennai, India.” In Gendered Mobilities, edited by Tanu Priya Uteng and Tim Cresswell. Hampshire, UK: Ashgate Publishing. Publisher's VersionAbstract
Being socially and geographically mobile is generally seen as one of the central aspects of women's wellbeing. Alongside health, education and political participation, mobility is indispensable in order for women to reach goals such as agency and freedom. Building on new philosophical underpinnings of 'mobility', whereby society is seen to be framed by the convergence of various mobilities, this volume focuses on the intersection of mobility, social justice and gender. The authors reflect on five highly interdependent mobilities that form and reform social life.
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.

Sumeeta Srinivasan. 2005. “Linking land use and transportation in a rapidly urbanizing context: A study in Delhi, India.” Transportation, 32, 1, Pp. 87-104. Publisher's VersionAbstract
Cities in developing countries like India are facing some of the same concerns that North American cities are: congestion and urban growth. However, there is a sense of urgency in cities like Delhi, India in that this growth is far more rapid as both urbanization and motorization are ongoing processes that have not yet peaked. In this paper, we examine land use change and its relationship with transportation infrastructure and other planning related variables in a spatial context. We estimate land use change models at two different scales from separate data. Cellular automation and Markov models were used to understand change at the regional scale and discrete choice models to predict change at the local level. The results suggest that land use in the Delhi metropolitan area is rapidly intensifying while losing variety. These changes are affected by industrial, commercial and infrastructure location and planners and policy-makers need to better understand the implications of location decisions. We also examine these results in the context of a policy framework for data-based planning that links land use and transportation models for Delhi.
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.

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.