The impact of urban street tree species on air quality and respiratory illness: A spatial analysis of large-scale, high-resolution urban data.

Abstract

Urban trees play a key role in reducing greenhouse gas emissions, cleaning air, promoting physical activity, and improving mental health. However, it is still largely unknown how the density and species of urban street trees may impact local public health. This study demonstrates how open data mining and large-scale spatial data integration can contribute to deeper insights into the effects of urban forestry. We analyze the impact of the spatial distribution of street trees by species in New York City by combining crowd-sourced tree census data - which includes geolocation, species, size, and condition for each of 652,169 street trees - with pollen activity, allergen severity, land use, housing conditions, and neighborhood demographic data. We further integrate neighborhood asthma hospitalization and emergency department visit rates and air quality data (PM2.5) to investigate how street trees impact local air quality and the prevalence of acute respiratory illness. Using a geographically weighted regression model, the results indicate that although a greater concentration of trees contributes to better local air quality, species with severe allergenicity can increase local asthma hospitalization rates in vulnerable populations, controlling for other covariates.