Formulating Operational Mitigation Options and Examining Intra-Urban Social Inequality Using Evidence-Based Urban Warming Effects - Zhu, Yuanhui; Myint, Soe W.; Schaffer-Smith, Danica; Muenich, Rebecca L.; Tong, Daoqin; Li, Yubin (Frontiers in Environmental Science, 2022)
Human-induced climate change is bringing warmer conditions to the Southwestern United States. More extreme urban heat island (UHI) effects are not distributed equally, and often impact socioeconomically vulnerable populations the most. This study aims to quantify how land surface temperature (LST) changes with increasing green vegetation landscapes, identify disparities in urban warming exposure, and provide a method for developing evidence-based mitigation options. ECOSTRESS LST products, detailed land use and land cover (LULC) classes, and socioeconomic variables were used to facilitate the analysis. We examined the relationship between LST and the fractions of LULC and socioeconomic factors in the City of Phoenix, Arizona. A machine learning approach (Random Forest) was used to model LST changes by taking the LULC fractions (scenario-based approaches) as the explanatory variables. We found that vegetation features – trees, grass, and shrubs – were the most important factors mitigating UHI effects during the summer daytime. Trees tended to lower surface temperature more effectively, whereas we observed elevated daytime LST most often near roads. Meanwhile, higher summer daytime temperatures were observed on land with unmanaged soil compared to the built environment. We found that affluent neighborhoods experienced lower temperatures, while low-income communities experienced higher temperatures. Scenario analyses suggest that replacing 50% of unmanaged soil with trees could reduce average summer daytime temperatures by 1.97℃ if the intervention was implemented across all of Phoenix and by 1.43℃ if implemented within the Urban Core only. We suggest that native trees requiring little to no additional water other than rainfall should be considered. Our results highlight existing disparities in UHI impacts under current vegetation conditions and can be used to guide the development of equitable policies for vegetation management to mitigate heat exposure impacts on communities.