Studies on urban heat island (UHI) have been more than a century after the phenomenon was first discovered in the early 1800s. UHI emerges as the source of many urban environmental problems and exacerbates the living environment in cities. Under the challenges of increasing urbanization and future climate changes, there is a pressing need for sustainable adaptation/mitigation strategies for UHI effects, one popular option being the use of reflective materials. While it is introduced as an effective method to reduce temperature and energy consumption in cities, its impacts on environmental sustainability and large-scale non-local effect are inadequately explored. This paper provides a synthetic overview of potential environmental impacts of reflective materials at a variety of scales, ranging from energy load on a single building to regional hydroclimate. The review shows that mitigation potential of reflective materials depends on a set of factors, including building characteristics, urban environment, meteorological and geographical conditions, to name a few. Precaution needs to be exercised by city planners and policy makers for large-scale deployment of reflective materials before their environmental impacts, especially on regional hydroclimates, are better understood. In general, it is recommended that optimal strategy for UHI needs to be determined on a city-by-city basis, rather than adopting a “one-solution-fits-all” strategy

We propose a new surface exchange scheme coupling the transport of energy and water in urban canopies. The new model resolves the subfacet heterogeneity of urban surfaces, which is particularly useful for capturing surface exchange processes from vegetated urban surfaces, such as lawns or green roofs. We develop detailed urban hydrological models for surfaces consisting of either natural (soil and vegetation) or engineered materials with water‐holding capacity. The coupling of energy and water transport enables us to parametrize surface evaporation from different urban facets including soils, vegetation and water‐holding engineered surfaces. The new coupled model is evaluated using field measurement data obtained through a wireless sensor network deployed over the Princeton University campus. Comparison of model prediction and measured results shows that the proposed surface exchange scheme is able to predict widely varying surface temperatures for each subfacet with good accuracy. Different weather conditions and seasonal variability are found to have insignificant effect on the model performance. The new model is also able to capture the subsurface hydrological processes with reasonable accuracy, particularly for urban lawns. The proposed model is then applied to assess different mitigation strategies of the urban heat island effect.

Warming trends in cities are influenced both by large-scale climate processes and by local-scale urbanization. However, little is known about how surface warming trends of global cities differ from those characterized by weather observations in the rural background. Here, through statistical analyses of satellite land surface temperatures (2002 to 2021), we find that the mean surface warming trend is 0.50 ± 0.20 K·decade⁻¹ (mean ± one S.D.) in the urban core of 2000-plus city clusters worldwide, and is 29% greater than the trend for the rural background. On average, background climate change is the largest contributor explaining 0.30 ± 0.11 K·decade⁻¹ of the urban surface warming. In city clusters in China and India, however, more than 0.23 K·decade⁻¹ of the mean trend is attributed to urban expansion. We also find evidence of urban greening in European cities, which offsets 0.13 ± 0.034 K·decade⁻¹ of background surface warming.