Understanding transport carbon dioxide (CO₂) emission impact factors’ effects is important for the rational planning strategy making in reducing the emissions. This study determines transport emission impact factors’ heterogeneous effects and proposes urban and transport planning strategies in typical developing cities. Quantile regression is applied to overcome the insufficiency of factors’ mean effects and to avoid the biased estimations when the outcome variable is non-normally distributed and heteroscedastic. It is found that, from the low emitters at the 10th quantile to the high emitters at the 90th quantile, transport emissions’ increasing rates are 8.8 times and 79.6 times that of car availability and home-to-center/subcenter distance (HCD/HSD), respectively. When commute distance reaches 5.8 km or farther, and car availability percentage is 41.2% or greater, the effects that metro services have on reducing emissions decrease by 37.8%. Polycentric and satellite city forms can greatly reduce emission increases, which are caused by HCD growth when HCD is more than 10–15 km. According to these findings, the following planning strategies are recommended, including limiting oil-fueled car use to about 40% among the urban residents, forming employment and life circles within a 5–6 km radius, allocating better public transit services around metro stations, providing high service levels of bicycle lanes, pedestrian streets, and greenways to attract more transfers to metros, controlling urban radius within 10–15 km under the monocentric pattern, and fostering polycentric structures and satellite cities when city continuously sprawls. This study can provide empirical evidence and reference value globally.

In the urban traffic research field, taxi detour behavior analysis can be regarded as one of the most crucial and challenging topics accounting for real-world routing network dynamics with complicated external inducement such as “avoiding congestion sections”, “unfamiliarity with road maps” or just “earning more fee under a longer travel path”. We carried out an interdisciplinary research framework to build a more holistic and profound view of the spatio-temporal distribution of the taxi detour behavior at directional road segment (DRS) level. First, a map matching based detour clustering method was proposed to deal with one week of taxi GPS tracing (divided into 3.4 million occupied trips). Then we employed an established multi-layer road index system in Shenzhen, China, to illustrate the spatio-temporal distribution variation of taxi detour features and statistics. Furthermore, three categories of DRS factors related to road structural attributes, traffic dynamics and point-of-interests (POIs) were defined to fit a selected-sample-based binary logit model. Some remarkable findings include: (i) in Shenzhen on average, 23.5 percent of taxi trips made a detour larger than 2.1 kilometers, which could be astonishingly high considering that only a very few trips yielded formal complaints for fraudulent detouring; (ii) both the level of detour intensity and ratio are affected by road features and dynamics in different spatio-temporal interaction patterns.

Exploring key impact factors and their effects on urban residents’ transport carbon dioxide (CO₂) emissions is significant for effective low-carbon transport planning. Researchers face the model uncertainty problem to seek a rational and better explanatory model and the key variables in the model set containing various factors after they are arranged and combined. This paper uses the Bayesian Model Averaging method to solve the above problem, explore the key variables, and determine their relative significance and averaging effects. Beijing, Xi’an, and Wuhan are selected as three case cities for their representation of developing Chinese cities. We found that the initial key factor increasing transport emissions is the high dependence on cars, and the second is the geographical location factor that much more suburban residents suffer longer commuting. Developing satellite city rank first for reducing transport emissions due to more local trips with an average short distance, the second is the metro accessibility, and the third is polycentric form. Key planning strategies and policies are proposed: (i) combining policies of car restriction based on vehicle plate number, encouraging clean fuel cars, a carbon tax on oil uses, and rewarding public transit passengers; (ii) fostering subcenters’ strong industries to develop self-contained polycentric structures and satellite cities, and forming employment and life circle within 5 km radius; and (iii) integrating bus and rail transit services in the peripheral areas and suburbs and increasing the integration level of muti-modes transferring in transport hubs. The findings will offer empirical evidence and reference value in developing cities globally.