Supporting an integrated transportation infrastructure and public space design: A coupled simulation method for evaluating traffic pollution and microclimate

Traditional urban and transport infrastructure planning that emphasized motorized transport has fractured public space systems and worsened environmental quality, leading to a decrease in active travel. A novel multiscale simulation method for supporting an integrated transportation infrastructure and public space design is presented in this paper. This method couples a mesoscale agent-based traffic prediction model, traffic-related emission calculation, microclimate simulations, and human thermal comfort assessment. In addition, the effects of five urban design strategies on traffic pollution and pedestrian level microclimate are evaluated (i.e., a “two-fold” evaluation). A case study in Beijing, China, is presented utilizing the proposed urban modeling-design framework to support the assessment of a series of transport infrastructure and public space scenarios, including the Baseline scenario, a System-Internal Integration scenario, and two External Integration scenarios. The results indicate that the most effective way of achieving an environmentally- and pedestrian- friendly urban design is to concentrate on both the integration within the transport infrastructure and public space system and the mitigation of the system externalities (e.g., air pollution and heat exhaustion). It also demonstrates that the integrated blue-green approach is a promising way of improving local air quality, micro-climatic conditions, and human comfort

Do drivers of nature visitation vary spatially? The importance of context for understanding visitation of nature areas in Europe and North America

Nature visitation is important, both culturally and economically. Given the contribution of nature recreation to multiple societal goals, comprehending determinants of nature visitation is essential to understand the drivers associated with the popularity of nature areas, for example, to inform land-use planning or site management strategies to maximise benefits. Understanding the factors related to nature, tourism and recreation can support the management of nature areas and thereby, also conservation efforts and biodiversity protection. This study applied a Multiscale Geographically Weighted Regression (MGWR) to quantify the spatially varying influence of different factors associated with nature visitation in Europe and North America. Results indicated that some explanatory variables were stationary for all sites (age 15 to 65, population density (within 25 km), GDP, area, built-up areas, plateaus, and mountains). In contrast, others exhibited significant spatial non-stationarity (locally variable): needle-leaf trees (conifers), trails, travel time, roads, and Red List birds and amphibians. Needle-leaf trees and travel time were found to be negatively significant in Europe. Roads were found to have a significant positive effect in North America. Trails and Red List bird species were found to have a positive effect in both North America and North Europe, with a greater effect in Europe. Red List amphibians was the only spatially variable predictor to have both a positive and negative impact, with selected sites in North America and northern Europe being positive, whereas Iceland and central and southern Europe were negative. The scale of the response-predictor relationship (bandwidth) of these locally variable predictors was smallest for Red List amphibians at 1033 km, with all other spatially variable predictors between 9,558 and 12,285 km. The study demonstrates the contribution that MGWR, a spatially explicit model, can make to support a deeper understanding of processes associated with nature visitation in different geographic contexts