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

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)80-87
Number of pages8
JournalHealth and Place
Volume56
DOIs
StatePublished - Mar 1 2019

Fingerprint

Spatial Analysis
spatial analysis
air quality
illness
Air
air
hospitalization
asthma
housing conditions
local public
data quality
forestry
Hospitalization
Asthma
census
urban forestry
land use
public health
mental health
Forestry

Keywords

  • Civic analytics
  • Environmental health
  • Environmental justice
  • Urban ecology
  • Urban informatics
  • Urban science

ASJC Scopus subject areas

  • Health(social science)
  • Geography, Planning and Development
  • Sociology and Political Science
  • Public Health, Environmental and Occupational Health
  • Life-span and Life-course Studies

Cite this

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title = "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.",
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author = "Yuan Lai and Constantine Kontokosta",
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AB - 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.

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