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This article analyzes the impact of the level of urban polycentricity (UP) on particulate matter emissions from vehicles (PMV) across 102 prefecture-level cities in China between 2011 and 2015. We adopt a spatial panel modeling approach to our measures of UP and PMV, controlling for (possible) intervening effects such as population density and economic output. We observe an inverted U-shaped relationship between both measures: When UP is low, an increase in polycentricity is associated with higher levels of PMV; however, when UP reaches a certain threshold, the increase in polycentricity is associated with a reduction in PMV. We find a similar relationship between economic output and PMV and demonstrate how the effects of population density on PMV consist of two opposite processes that likely offset each other. Nonetheless, jointly, population density and UP have a significant effect on PMV. We use our results to discuss policy implications and identify avenues for further research.

Against the backdrop of current policy discussions in Flanders dealing with differentiated urban development schemes for strategic railway stations, this paper develops an empirical railway station assessment tool. We build on the node-place modeling literature, and more specifically on the tradition of quantitative station assessment models which has emerged from it. First, a series of methodological contributions are proposed in which we suggest strategies to improve the analytical strength of some standard node-place parameters, we broaden the model with temporal variability in accessibility, and we complement the model with a user-based accessibility account. Second, the conceptual model is applied to the case of Flanders and Brussels (the north of Belgium). Drawing on factor and cluster analysis, two intelligible station typologies are produced for both node-place and user-based data. Both typologies are interpreted and complemented with station-specific rose diagrams summarizing a station's accessibility profile. These diagrams reveal insightful and detailed knowledge about station-specific accessibility characteristics, some of which are not captured by standard node-place analyses. Lastly, a more in-depth discussion focusing on five exemplary cases reveals what the results of these analyses may mean for planning practice.