Assessing the relationship among urban trees, nitrogen dioxide, and respiratory health

Abstract

Modeled atmospheric pollution removal by trees based on eddy flux, leaf, and chamber studies of relatively few species may not scale up to adequately assess landscape-level air pollution effects of the urban forest. A land use regression (LUR) model (R(2) = 0.70) based on NO2 measured at 144 sites in Portland, Oregon (USA), after controlling for roads, railroads, and elevation, estimated every 10 ha (20%) of tree canopy within 400 m of a site was associated with a 0.57 ppb decrease in NO2. Using BenMAP and a 200 m resolution NO2 model, we estimated that the NO2 reduction associated with trees in Portland could result in significantly fewer incidences of respiratory problems, providing a $7 million USD benefit annually. These in-situ urban measurements predict a significantly higher reduction of NO2 by urban trees than do existing models. Further studies are needed to maximize the potential of urban trees in improving air quality.

Keywords: Health impacts; Land use regression; NO(2); Urban forest.