Despite growing research on green space and health benefits, the body of evidence remains heterogeneous and unclear. A systematic review and meta-analysis of studies of randomized controlled trials (RCTs) with high evidence levels are deemed timely. We searched Scopus, PubMed, Embase, and Web of Science for the literature up to January 2022 and assessed bias using the Cochrane Risk of Bias tool 2.0. We calculated joint impact estimates for each green space exposure assessment technique using random and fixed effects models. Compared to non-green space situations, green space exposure was related to decreased negative feelings, such as fatigue −0.84 (95% CI: −1.15 to −0.54), and increased levels of pleasant emotions, such as vitality 0.85 (95% CI: 0.52 to 1.18). It also lowered physiological indicators, including heart rate levels, by 0.60 (95% CI: −0.90 to −0.31). Effect sizes were large and statistically significant, and the overall quality of the evidence was good. Existing RCTs on greenspace exposure pay insufficient attention to older and adolescent populations, different ethnic groups, different regions, and doses of greenspace exposure interventions. More research is needed to understand how and how much green space investment has the most restorative benefits and guide urban green space planning and renewal.

Dengue fever is an acute mosquito-borne disease that mostly spreads within urban or semi-urban areas in warm climate zones. The dengue-related risk map is one of the most practical tools for executing effective control policies, breaking the transmission chain, and preventing disease outbreaks. Mapping risk at a small scale, such as at an urban level, can demonstrate the spatial heterogeneities in complicated built environments. This review aims to summarize state-of-the-art modeling methods and influential factors in mapping dengue fever risk in urban settings. Data were manually extracted from five major academic search databases following a set of querying and selection criteria, and a total of 28 studies were analyzed. Twenty of the selected papers investigated the spatial pattern of dengue risk by epidemic data, whereas the remaining eight papers developed an entomological risk map as a proxy for potential dengue burden in cities or agglomerated urban regions. The key findings included: (1) Big data sources and emerging data-mining techniques are innovatively employed for detecting hot spots of dengue-related burden in the urban context; (2) Bayesian approaches and machine learning algorithms have become more popular as spatial modeling tools for predicting the distribution of dengue incidence and mosquito presence; (3) Climatic and built environmental variables are the most common factors in making predictions, though the effects of these factors vary with the mosquito species; (4) Socio-economic data may be a better representation of the huge heterogeneity of risk or vulnerability spatial distribution on an urban scale. In conclusion, for spatially assessing dengue-related risk in an urban context, data availability and the purpose for mapping determine the analytical approaches and modeling methods used. To enhance the reliabilities of predictive models, sufficient data about dengue serotyping, socio-economic status, and spatial connectivity may be more important for mapping dengue-related risk in urban settings for future studies.

Traditional shophouse neighbourhoods (TSNs) in southern China respond well to the local hot and humid climate through proper street configurations and the integration of different shading strategies. Investigating the impact of shading strategies and configurations in TSNs on outdoor thermal comfort is valuable for guiding current urban design. Three street canyons in a TSN of Guangzhou with different shading strategies were selected as basic cases for microclimatic measurement in the summer season, i.e., alleys, streets with arcade for pedestrians, and streets with high-density greenery. After validating their simulation models in ENVI-met, five groups of parametric simulations were generated by varying the canyon aspect ratio (CHW), the canyon axis orientation, arcade proportion (AHW), and the tree-covered area (TCA). Using the physiological equivalent temperature (PET) to assess the above results, the correlative impact of different variations on pedestrian’s thermal comfort and their corresponding favourable ranges are summarized. The findings suggest that: (a) only in alleys and arcade streets, the pedestrian-level thermal comfort was significantly influenced by canyon axis orientation. (b) The thermal stress for pedestrians increased dramatically when the CHW was lower than 1.5 in alleys and 0.78 in boulevards (in TCA = 89%), while the CHW higher than 1 indicated a remarkable reduction on the PET for pedestrians in arcades. (c) The pedestrians started losing the protection from shading strategy to thermal stress when the AHW was higher than 1.33 (in canyon with CHW = 1) or the TCA was lower than 33% (in canyon with CHW = 0.78).