An Exploratory Tool for Urban Heat Mitigation

Urban areas worldwide are increasingly impacted by the Urban Heat Island (UHI) effect, posing
significant challenges to public health and urban liveability. This research addresses these
challenges by exploring various urban heat mitigation strategies and developing a calculation
tool to assist urban planners in assessing and implementing mitigation measures in the early
stages of the design process. The study focuses on three primary strategies: Urban Blue (water
based), Urban Green (vegetation-based), and Albedo (reflective materials), providing a
structured approach to reduce urban heat.
Unlike more complex simulation tools like ENVI-met, which can be challenging to use, this
calculation tool is designed to be simple and accessible, supporting urban planners in quickly
evaluating mitigation options. Developed using a Preliminary Evaluation Framework, the tool
integrates environmental and financial criteria, allowing for a straightforward comparison of
different mitigation techniques. A case study was conducted in a high-density urban area with
significant heat retention, demonstrating the tool’s practical applicability. Findings from the
case study indicate that Urban Green strategies, such as tree and hedge plantings, achieved
the highest temperature reduction, with an approximate maximum decrease of 0.71°C. Albedo
interventions also contributed to cooling but were slightly less effective than green solutions.
Urban Green interventions did however require higher investment and maintenance costs.
The study highlights the importance of choosing strategies tailored to site-specific conditions
and financial feasibility. This calculation tool provides urban planners with a customizable,
easy-to-use framework for data-driven decision-making, allowing for early-stage evaluation
and comparison of design alternatives in urban heat mitigation. Its adaptability enables
continuous updates as new data becomes available, making it a resource for managing urban
heat in the long term. Recommendations are offered for further refinement of the tool and
broader testing across diverse urban environments to enhance its scalability and accuracy.