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.

Vehicles have recently overtaken coal to become the largest source of air pollution in urban China. Research on mobile sources of pollution has foundered due both to inaccessibility of Chinese data on health outcomes and strong identifying assumptions. To address these, we collect daily ambulance call data from the Beijing Emergency Medical Center and combine them with an idiosyncratic feature of a driving restriction policy in Beijing that references the last digit of vehicles’ license plate numbers. Because the number 4 is considered unlucky by many in China, it tends to be avoided on license plates. As a result, days on which the policy restricts license plates ending in 4 unintentionally allow more vehicles in Beijing. Leveraging this variation, we find that traffic congestion is indeed 22% higher on days banning 4 and that 24-hour average concentration of NO₂ is 12% higher. Correspondingly, these short term increases in pollution increase ambulance calls by 12% and 3% for fever and heart related symptoms, while no effects are found for injuries. These findings suggest that traffic congestion has substantial health externalities in China but that they are also responsive to policy. 

With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM2.5) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions.

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.