Urban Trees and Air Temperature Changes in Cities

Photo Credit

Anna Pickett

Bicyclists getting ready to collect temperature data. 

New Haven, Connecticut has a diverse climate and experiences precipitation year-round. It is warm and humid in the summers and cold and snowy in the winters.

Urban trees are important for cooling cities like New Haven, especially as temperatures rise because of climate change. Heat-related deaths are a major concern, especially because heat is more deadly than other extreme weather. This research provides a more detailed analysis of the relationship between city trees and heat than previous studies.

Key Findings

• Trees make the biggest difference in nearby air temperatures in the middle of the day, the afternoon, and during the morning on cloudless days, but their effect is smaller at night and on the hottest days.
• Paved surfaces, on the other hand, make things hotter, especially in the evening.
• The cooling effects of trees are mostly consistent and linear; this differs from what has been reported in previous research.
• Research like this provides opportunities for non-scientists to collect useful data.
   

Photo Credit

Mike Alonzo

An old mountain bike gets a new life as a device that measures temperature while on the move.

To understand how urban features affect temperature, researchers used sensors mounted on bicycles. These sensors recorded temperature data along biking routes. They collected data from 156 biking trips in New Haven between June and September in 2019, 2020, and 2021.

To compare the temperatures recorded by the bike-mounted sensors with standard temperatures, the researchers used data from a weather station in a suburban neighborhood. They divided the data into five chunks representing different times of day: morning, mid-day, afternoon, evening, and night. They also filtered the data to focus on the hottest days and analyzed how the temperature relationships varied throughout the day.

The researchers looked at various factors that could influence temperature, such as tree canopy cover, impervious surfaces, elevation, wind, and location. They also added data on cloud cover and measured temperatures with the bike-mounted sensors throughout the day.

The research team used statistical models called Generalized Additive Mixed Models (GAMMs) to analyze the data and account for factors like spatial and temporal autocorrelation. The models showed non-linear relationships between temperature and land cover variables. Finally, they used R and ArcMap software for their analyses and data visualization.

Outcomes

• Understanding the dynamics between heat and trees is crucial for managing urban heat and maintaining livable cities.
• Future research could use more detailed land cover data to better understand the relationships between different types of land cover and air temperature.
• Considering additional factors like pavement type and humidity could provide further insights into urban heat dynamics.