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Researchers and city practitioners are paramount stakeholders in creating urban resilience but have diverse and potentially competing views. To understand varying stakeholder perspectives, we conducted a systematic literature content analysis on green infrastructure (GI) and reflective pavement (RP). The analysis shows a United States (US)-based science-practice disconnect in written communication, potentially hindering holistic decision-making. We identified 191 GI and 93 RP impacts, categorized into co-benefits, trade-offs, disservices, or neutral. Impacts were further classified as environmental, social, or economic. The analysis demonstrates that US city practitioners emphasize social and economic co-benefits that may not be fully represented in the scientific discourse. Scientists communicate a broader range of impacts, including trade-offs and disservices, highlighting a nuanced understanding of the potential consequences. Identifying contrasting perspectives and integrating knowledge from various agents is critical in urban climate governance. Our findings facilitate bridging the science-policy disconnect in the US heat mitigation literature.

 

We introduce and demonstrate new measurement and modeling techniques to fully resolve the spatial variation in shortwave and longwave radiant heat transfer in the outdoor environment. We demonstrate for the first time a way to directly resolve the shortwave radiant heat transfer from terrestrial reflected and diffuse sky components along with the standard direct solar radiation using an adapted thermopile array and ray-tracing modeling techniques validated by 6-direction net radiometer. Radiant heat transfer is a major component of heat experienced in cities. It has significant spatial variability that is most easily noticed as one moves between shade and direct solar exposure. But even on a cloudy and warm day the invisible longwave infrared thermal radiation from warm surfaces makes up a larger fraction of heat experienced than that caused by convection with surrounding air. Under warm or hot climate conditions in cities, radiant heat transfer generally accounts for the majority of heat transfer to people. Both the shortwave (visible/solar) and the longwave (infrared/thermal) have significant spatial variation. We demonstrate sensor methods and data analysis techniques to resolve how these radiant fluxes can change the heat experienced by >1 kWm −2 across small distances. The intense solar shortwave radiation is easily recognized outdoors, but longwave is often considered negligible. Longwave radiation from heat stored in urban surfaces is more insidious as it can cause changes invisible to the eye. We show how it changes heat experienced by >200 Wm −2 . These variations are very common and also occur at the scale of a few meters. 

Extreme heat puts tremendous stress on human health and limits people’s ability to work, travel, and socialize outdoors. To mitigate heat in public spaces, thermal conditions must be assessed in the context of human exposure and space use. Mean Radiant Temperature (MRT) is an integrated radiation metric that quantifies the total heat load on the human body and is a driving parameter in many thermal comfort indices. Current sensor systems to measure MRT are expensive and bulky (6-directional setup) or slow and inaccurate (globe thermometers) and do not sense space use. This engineering systems paper introduces the hardware and software setup of a novel, low-cost thermal and visual sensing device (MaRTiny). The system collects meteorological data, concurrently counts the number of people in the shade and sun, and streams the results to an Amazon Web Services (AWS) server. MaRTiny integrates various micro-controllers to collect weather data relevant to human thermal exposure: air temperature, humidity, wind speed, globe temperature, and UV radiation. To detect people in the shade and Sun, we implemented state of the art object detection and shade detection models on an NVIDIA Jetson Nano. The system was tested in the field, showing that meteorological observations compared reasonably well to MaRTy observations (high-end human-biometeorological station) when both sensor systems were fully sun-exposed. To overcome potential sensing errors due to different exposure levels, we estimated MRT from MaRTiny weather observations using machine learning (SVM), which improved RMSE. This paper focuses on the development of the MaRTiny system and lays the foundation for fundamental research in urban climate science to investigate how people use public spaces under extreme heat to inform active shade management and urban design in cities. 

Abstract Cities increasingly recognize the importance of shade to reduce heat stress and adopt urban forestry plans with ambitious canopy goals. Yet, the implementation of tree and shade plans often faces maintenance, water use, and infrastructure challenges. Understanding the performance of natural and non-natural shade is critical to support active shade management in the built environment. We conducted hourly transects in Tempe, Arizona with the mobile human-biometeorological station MaRTy on hot summer days to quantify the efficacy of various shade types. We sampled sun-exposed reference locations and shade types grouped by urban form, lightweight/engineered shade, and tree species over multiple ground surfaces. We investigated shade performance during the day, at peak incoming solar, peak air temperature, and after sunset using three thermal metrics: the difference between a shaded and sun-exposed location in air temperature ( ΔT a ), surface temperature ( ΔT s ), and mean radiant temperature ( ΔT MRT ). ΔT a did not vary significantly between shade groups, but ΔT MRT spanned a 50°C range across observations. At daytime, shade from urban form most effectively reduced T s and T MRT , followed by trees and lightweight structures. Shade from urban form performed differently with changing orientation. Tree shade performance varied widely; native and palm trees were least effective, while non-native trees were most effective. All shade types exhibited heat retention (positive ΔT MRT ) after sunset. Based on the observations, we developed characteristic shade performance curves that will inform the City of Tempe’s design guidelines towards using “the right shade in the right place” and form the basis for the development of microclimate zones (MCSz).