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Understanding the connections between the built environment and travel mode choice is a major research topic in transportation. However, existing studies usually examine the relationship through trip-based analyses rather than tour-based approaches. A tour consists of multiple trips that originate and end at the same place, which is increasingly considered the more appropriate analysis unit for travel behaviors. Applying a tour-based approach, this study employs random forest to investigate the non-linear impacts of built environment factors and tour attributes on different mode combinations of a tour. We find that tour attributes and connectivity-related variables (e.g., block size and intersection density) have a strong association with the use of active travel modes when their values are within a certain threshold. In addition, capturing mode change behaviors offers more nuanced understanding of how various built environment variables shape people's decision to combine modes in a tour.

China has gone through a rapid process of urbanization, but this has come along with serious environmental problems. Therefore, it has started to develop various eco-cities, low-carbon cities, and other types of sustainable cities. The massive launch of these sustainable initiatives, as well as the higher cost of these projects, requires the Chinese government to invest large sums of money. What financial toolkits can be employed to fund this construction has become a critical issue. Against this backdrop, the authors have selected Sino-Singapore Tianjin Eco-city (SSTEC) and Shenzhen International Low-Carbon City (ILCC) and compared how they finance their construction. Both are thus far considered to be successful cases. The results show that the two cases differ from each other in two key aspects. First, ILCC has developed a model with less financial and other supports from the Chinese central government and foreign governments than SSTEC, and, hence, may be more valuable as a source of inspiration for other similar projects for which political support at the national level is not always available. Second, by issuing bonds in the international capital market, SSTEC singles itself out among various sustainable initiatives in China, while planning the village area as a whole and the metro plus property model are distinct practices in ILCC. In the end, the authors present a generic financing model that considers not only economic returns but also social and environmental impacts to facilitate future initiatives to finance in more structural ways.

China has gone through a rapid process of urbanization, but this has come along with serious environmental problems. Therefore, it has started to develop various eco-cities, low-carbon cities, and other types of sustainable cities. The massive launch of these sustainable initiatives, as well as the higher cost of these projects, requires the Chinese government to invest large sums of money. What financial toolkits can be employed to fund this construction has become a critical issue. Against this backdrop, the authors have selected Sino-Singapore Tianjin Eco-city (SSTEC) and Shenzhen International Low-Carbon City (ILCC) and compared how they finance their construction. Both are thus far considered to be successful cases. The results show that the two cases differ from each other in two key aspects. First, ILCC has developed a model with less financial and other supports from the Chinese central government and foreign governments than SSTEC, and, hence, may be more valuable as a source of inspiration for other similar projects for which political support at the national level is not always available. Second, by issuing bonds in the international capital market, SSTEC singles itself out among various sustainable initiatives in China, while planning the village area as a whole and the metro plus property model are distinct practices in ILCC. In the end, the authors present a generic financing model that considers not only economic returns but also social and environmental impacts to facilitate future initiatives to finance in more structural ways.

AbstractThree methods of calculating evapotranspiration (ET), Penman–Monteith (PM), Makkink (MK) and Priestley–Taylor (PT) equation, were applied to a temperate meadow in Inner Mongolia, China. We compared these methods with eddy covariance (EC) method. The results indicated that a reduction in mean absolute error (MAE) and root mean squared error (RMSE) was achieved for MK and PT methods (45.6–83.0%) when using site‐specific parameters compared with referenced ones, but an increase of 75.9–93.9% for PM method. Intercomparison of three methods through comparison with EC measurements indicated that PT method with site‐specific parameters performed the best to estimate ET, followed by PM method with referenced parameters, and then MK equation with site‐specific parameters (overestimate ET by 8.2, 12.1, 16.5% and 3.4, 12.8, 21.0% respectively for half‐hourly and daily values).

AbstractTo promote the awareness of Priestley–Taylor (PT) model and extend the knowledge of hydrological model under snow, performance of PT model was illustrated by comparing with eddy covariance (EC) measurements over a temperate meadow. The results showed that the mean half‐hourly averages and directly calculated daily value of PT parameter α is 0.47 ± 0.27 and 0.51 ± 0.32, respectively. Vapour pressure deficit VPD is the mainly factor influences α in the snow‐covered period, while soil moisture in the snow‐free period. PT method underestimated evaporation in the whole study period and showed remarkable difference in different phases. It performed best in the snow‐melting phase, better in the presnow phase, worse in the fresh snow phase and worst in the snow‐melted phase. These studies indicated that PT model could be used to estimate evaporation over temperate meadow in dormant season, but utility of a variable PT parameter α during different phases should be considered.