Urban Planning, Low-Carbon Transportation, and Health
An interdisciplinary household survey in the city of Chengdu, led by Chris NIELSEN (Harvard-China Project), James HAMMITT (Harvard T.H. Chan School of Public Health), and SHEN Mingming and YAN Jie (School of Government, Peking University), was completed in July 2016. The data have been joined with an earlier dataset collected in a nearly identical Harvard-China Project-PKU survey in 2005, to cover changes in Chengdu's economy, urbanization, travel behavior, land use, air quality, and environmental health over 11 years. In addition to this multi-faceted research on Chengdu, the Project conducts additional individual studies of transportation, land use, emissions, air quality, and/or health at urban scale.
Both the 2005 and 2016 Chengdu surveys collected data across a wide range of research interests, including transportation planning, travel behavior, mobile-source emissions, outdoor and indoor air pollution exposures, health effects of air pollution, and perceptions and valuation of health risk. Harvard researchers devised the questionnaires and are leading a number of parallel analyses. Covering 2000 households, field implementation of both surveys was led by political scientist Shen, using RCCC's rigorous geospatial sampling methods to insure inclusion of non-registered migrants left out of most social surveys in China.
Joining Hammitt and Nielsen in ongoing analyses of the datasets are China Project research affiliates GUAN ChengHe (Graduate School of Design, Harvard), Sumeeta SRINIVASAN (Department of Urban and Environmental Policy and Planning, Tufts University), WANG Haikun (School of Environment, Nanjing University), and GENG Fangli (Harvard T.H. Chan School of Public Health).
To evaluate the improved emission estimates from online monitoring, we applied the Models-3/CMAQ (Community Multiscale Air Quality) system to simulate the air quality of the Yangtze River Delta (YRD) region using two emission inventories with and without incorporated data from continuous emission monitoring systems (CEMSs) at coal-fired power plants (cases 1 and 2, respectively). The normalized mean biases (NMBs) between the observed and simulated hourly concentrations of SO2, NO2, O3, and PM2.5in case 2 were−3.1 %, 56.3 %,−19.5 %, and−1.4 %, all smaller in absolute value than those in case 1 at 8.2 %, 68.9 %,−24.6 %, and 7.6 %, respectively. The results indicate that incorporation of CEMS data in the emission inventory reduced the biases between simulation and observation and could better reflect the actual sources of regional air pollution. Based on the CEMS data, the air quality changes and corresponding health impacts were quantified for different implementation levels of China's recent “ultra-low” emission policy. If the coal-fired power sector met the requirement alone (case 3), the differences in the simulated monthly SO2, NO2, O3, and PM2.5concentrations compared to those of case 2, our base case for policy comparisons, would be less than 7 % for all pollutants. The result implies a minor benefit of ultra-low emission control if implemented in the power sector alone, which is attributed to its limited contribution to the total emissions in the YRD after years of pollution control (11 %, 7 %, and 2 % of SO2, NOX, and primary particle matter (PM) in case 2, respectively). If the ultra-low emission policy was enacted at both power plants and selected industrial sources including boilers, cement, and iron and steel factories (case 4), the simulated SO2, NO2, and PM2.5concentrations compared to the base case would be 33 %–64 %, 16 %–23 %, and 6 %–22 % lower, respectively, depending on the month (January, April, July, and October 2015). Combining CMAQ and the Integrated Exposure Response (IER) model, we further estimated that 305 deaths and 8744 years of life loss (YLL) attributable to PM2.5exposure could be avoided with the implementation of the ultra-low emission policy in the power sector in the YRD region. The analogous values would be much higher, at 10 651 deaths and 316 562 YLL avoided, if both power and industrial sectors met the ultra-low emission limits. In order to improve regional airquality and to reduce human health risk effectively, coordinated control of multiple sources should be implemented, and the ultra-low emission policy should be substantially expanded to major emission sources in industries other than the power industry.
A striking feature of urban formation has been the deployment of mega-blocks, often on the order of sixteen hectares or more. On the other hand, recent urban policies give strong suggestions for smaller and finer-grained neighborhood block and grid arrangements. This paper explores the transformation of urban block structures in high-density cities beyond spatial conditions of big versus small blocks by emphasizing “place” making through the degree of spatial diversity and flexibility. Using spatial indices of urban block arrangements, road network efficiencies and gradients of transit network accessibility, the assessment on urban neighborhood block structure is applied to territories of central core, suburban and peripheral development in Beijing, Shanghai and Shenzhen at multiple spatial scales. The results show that the overall efficiency and flexibility of urban block structures becomes more a matter of a narrowing of the range of differing block sizes among the three territories and a concomitant higher potential capacity for adaptation to a broader range of development options. Beyond the Chinese context, in high-density cities across the globe, policies on place making should adopt a multi-scale spatial analysis strategy to measure the configuration of the overall urban block structure and guide the transformation of the city.
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.
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.
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.
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.