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.

Data-driven urban governance increasingly seeks to incorporate the needs of different population groups, yet child-sensitive evidence for public street-space renewal remains limited in older urban districts. Most studies still evaluate environmental conditions through population averages, with insufficient attention to heterogeneous child groups that may require differentiated planning responses. Based on an analytic sample of 314 children retained from 343 usable questionnaire responses collected from children aged 6–12 in the older urban districts of Xi’an, China, this study integrates street-activity characteristics and age- and sex-standardized body mass index (zBMI) using an established person-centered analytical approach. Latent Class Analysis (LCA) was used to identify children’s activity–health profiles, and multinomial logistic regression was used to examine associations between individual, family, and perceived street-environment factors and profile membership. Three profiles were identified: high-activity–healthy, high-intensity active, and low-activity–high-risk. The model-estimated low-activity–high-risk profile represented 35.7% of the analytic sample, and children assigned to this profile reported the lowest perceived safety and convenience. The findings suggest that profile-based analysis may inform child-sensitive street-renewal prioritization. Perceived safety and convenience showed the strongest and most consistent associations with membership in either the high-activity–healthy or high-intensity active profile relative to the low-activity–high-risk profile. These findings are associative and do not establish the effects of street interventions. The study therefore represents a context-specific extension and planning application of established analytical methods.

Adolescent mental health problems have become increasingly prominent, and everyday urban spaces may provide important support for stress relief. Focusing on adolescents aged 12–18 in Xi’an, China, this study examines three frequently used urban spaces: streets, residential communities, and parks. Based on questionnaire data, a multi-group structural equation model was estimated to test the relationships among built environment satisfaction (BES), perceived restorativeness (PR), and restorative outcomes (ROs), as well as their spatial differences. The results show that parks performed best in PR and ROs, followed by residential communities, whereas streets showed the weakest restorative performance. Across all three space types, BES significantly improved PR, and PR further promoted ROs. Parks showed both a significant direct effect and a significant indirect effect through PR, whereas communities and streets mainly relied on the mediating pathway through PR. Taken together, these findings suggest that restorative experiences cannot be explained by space-use intensity alone and are also associated with BES, PR, and space type. The study provides empirical evidence for optimizing everyday urban spaces to support adolescent mental health and socially sustainable urban development.