A scaling law for predicting urban trees canopy cooling efficiency.

Area of Science:

• Urban Climatology
• Environmental Science
• Sustainable Urban Planning

Background:

• Urban heat poses significant risks to human health and city sustainability.
• Tree planting is a key nature-based solution for urban heat mitigation.
• Existing cooling efficiency data is limited to small scales, hindering city-wide policy development.

Purpose of the Study:

• To develop a method for predicting the cooling efficiency of urban tree canopy (UTC) at the city scale.
• To investigate the scaling relationship of cooling efficiency (CE) with increasing spatial scale.
• To provide policymakers with tools for setting effective UTC goals.

Main Methods:

• Developed a novel method to analyze the scaling relations of cooling efficiency (CE).
• Examined CE across various spatial scales, from small analytical units to entire cities.
• Validated the power-law scaling across diverse city climates and summer weather conditions.

Main Results:

• Cooling efficiency (CE) follows a power-law relationship as spatial scale increases.
• This power-law scaling was consistent across cities with different climates during summer daylight hours.
• The power-law form proved robust under varying summer weather conditions within cities.

Conclusions:

• The power-law scaling approach enables accurate prediction of CE at the whole-city scale.
• This method offers a valuable tool for urban managers to establish UTC targets for heat mitigation.
• Findings support evidence-based policymaking for enhancing urban sustainability and resilience to heat.