Florian A. Schneider

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.

Urban overheating is an increasing threat to people, infrastructure, and the environment. Common heat mitigation strategies, such as green infrastructure, confront space limitations in current car-centric cities. In 2020, the City of Phoenix, Arizona, piloted a “cool pavement” program using a solar reflective pavement seal on 58 km of residential streets. Comprehensive micrometeorological observations are used to evaluate the cooling potential of the reflective pavement based on three heat exposure metrics—surface, air, and mean radiant temperatures—across three residential reflective pavement-treated and untreated neighborhoods. In addition, the solar reflectivity of reflective pavement is observed over 7 months across eight residential neighborhoods. Results are synthesized with the literature to provide context-based reflective pavement implementation guidelines to mitigate urban overheating where common strategies cannot be applied. The three most important contextual factors to consider for effective implementation include urban location, background climate type, and heat exposure metric of interest.

Urban overheating is an increasing threat to people, infrastructure, and the environment. Common mitigation strategies, such as green infrastructure, face space limitations in current car-centric cities. In 2020, the City of Phoenix, Arizona, piloted a “cool pavement” program using a solar reflective pavement (RP) seal on 58 km of residential streets. Comprehensive micrometeorological observations were used to evaluate the cooling potential of the RP based on three heat exposure metrics––surface, air, and mean radiant temperatures––across three residential RP-treated and untreated neighborhoods. In addition, the solar reflectivity of RP was observed over seven months across eight residential neighborhoods. Results are synthesized with the literature to provide context-based RP implementation guidelines to mitigate urban overheating where common strategies cannot be applied. The three most important contextual factors to consider for effective RP implementation include urban location, background climate type, and heat metric of interest.

Regional land surface temperature (LST) maps derived from remote sensing data are most available to cities to assess and respond to heat. Yet, LST only captures one dimension of urban climate. This study investigates the extent to which remote sensing derived estimates of LST are a proxy for multiple climate variables at hyper-local scales (<10s of meters). We compare remotely sensed estimates of LST (RS-LST) to field and simulated LST, MRT, and air temperature (AT), in a neighborhood in Tucson, Arizona, USA. We find that LST, MRT, and ST follow different diurnal trends masked by RS-LST. We also find that three-dimensional urban design is a better predictor of MRT than two-dimensional land cover and albedo – a known determinant of RS-LST. Shade is a better predictor of both simulated LST and MRT than RS-LST. We conclude that RS-LST is not adequate for guiding heat mitigation at hyper-local scales in cities.

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 nonnatural 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, at peak air temperature, and after sunset using three thermal metrics: the difference between a shaded and sun-exposed location in air temperature (∆ T _a ), surface temperature (∆ T _s ), and mean radiant temperature (∆ T _MRT ). Air temperature did not vary significantly between shade groups, but ∆ T _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 nonnative trees were most effective. All shade types exhibited heat retention (positive ∆ T _MRT ) after sunset. Based on the observations, we developed characteristic shade performance curves that will inform the City of Tempe’s design guidelines toward using “the right shade in the right place” and form the basis for the development of microclimate zones (MCSz).

A global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network Polly^NET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. Polly^NET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the Polly^NET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of Polly^NET to support the establishment of a global aerosol climatology that covers the entire troposphere.