Conifer PM2.5 Deposition and Resuspension in Wind and Rain Events

Abstract

Recent EPA rulings allow State Implementation Plans (SIP) to include new urban tree plantings as a measure of air pollution abatement, creating an urgent need for accurate estimates of pollution removal by trees. Deposition velocities (Vd) of particulates to trees have been reported for a number of species without explicitly recognizing that observed deposition is a net process, the sum of particle deposition and re-suspension. This has implications for atmospheric models that include a separate re-suspension term to estimate PM loading to trees. Wind tunnel tests at 5 m/s wind speed report 2.5% resuspension with a conifer species over a half day (Ould-Dada). However, in the native environment higher wind speeds are suspected to be responsible for the majority of resuspension of PM2.5. In the present study, three conifer species were dosed with KNO3 Dp 2.5 ?m particulates and exposed in a wind tunnel to winds of 6.5, 10, and 13 m/s for 5, 10, or 20 minutes, to determine PM2.5 resuspension rates. Deposition velocities were also determined over a range of PM concentrations. Though the removal of particles from the air is small, re-suspension from Pinus strobus increased from 0% at 6.5 m/s to 20% of the original dose removed at 10 m/s and 50% of the original dose removed at 13 m/s. Taxus cuspidata had low rates of resuspension (20% of the original dose) at all three wind speeds, while Tsuga canadensis had no resuspension. Vd are 0.02 cm/s for Tsuga, 0.01 cm/s for Pinus, and 0.005 for Taxus. Deposition velocity was found to be related to complexity of needle and branch arrangement, and not of total needle surface area as hypothesized. Re-suspension is likely to result from mechanical jarring of needles at high wind speeds rather than direct scouring by the wind. An analysis of wind conditions in upstate New York revealed that wind events of a magnitude sufficient to cause resuspension in Pinus occur 1.25% of the time in January and 0.07% of the time in July. The implications of these findings are: models of pollution removal by urban trees (ie, The Urban Forest Effects Model, UFORE) underestimate the amount of PM2.5 retained by leaves by 50%.