Effects of green roofs’ variations on the regional thermal environment using measurements and simulations in Chongqing,China

In the present work, field measurement and simulation method were employed to investigate the effects of several green roofs variables on regional thermal environment in Chongqing (29°N, 106°E), China. Field experiments were conducted in two typical places. The real influence of green roofs on ambient environment was analyzed and compared with the simulation results. The software ENVI-met was employed to simulate 29 cases with different factors, including green roofs types, vegetation coverage, building height, arrangement position and regional layouts. With the aim to investigate the effect of the green roofs thoroughly, different design factors of green roofs were taken in consideration. From the aspect of cooling effect, it can be found that enclosing layout has the maximum air temperature drop, which is up to 0.5 °C. From the perspective of the uniformity of regional environmental temperature distribution, the regional thermal environment of scattered layout is better than enclosing and array layout as a whole. In addition, with the same vegetation coverage, the effectiveness of air temperature dropping of the whole region differed according to the arrangement position. Centrally arranging the green roofs upwind can effectively reduce the air temperature of the whole region. These findings can be used to improve the regional thermal environment by designing the green roofs reasonably.     

Does pattern matter? Exploring the pathways and effects of urban green space on promoting life satisfaction through reducing air pollution

Urban green space is widely acknowledged to promote public health through multiple pathways. However, there is limited understanding of how the spatial patterns of green space might play different roles in such a process. This study examined potential pathways through which spatial patterns of green space improved people’s life satisfaction (LS) by reducing air pollution. A partial least squares structural equation model was adopted to explore these pathways in sampled urban areas (township) of China (n = 60). Green space spatial patterns were measured using landscape metrics of size, aggregation, fragmentation, and diversity. The results did not show that green space spatial pattern promoted LS by reducing air pollution. However, green space size and fragmentation were negatively associated with air pollution (mainly PM 2.5, PM 10, and NO 2). The pattern of highly densely distributed small green spaces was related to higher LS, as was high diversity of green space type. Simply adopting a fragmented green space pattern to reduce air pollution might be simultaneously associated with reduced LS. This alerts decision-makers and planners to the potential “double-edged sword” effect of optimizing green space structures to improve air quality, which may not yield strongly favorable results due to the impacts that hinder LS.