10th International Aerosol Conference
September 2 - September 7, 2018
America's Center Convention Complex
St. Louis, Missouri, USA

Abstract View


The Effectiveness of Roadside Vegetation Barriers as a Near-Road Air Pollution Mitigation Strategy: A Comprehensive Evaluation of the Sensitivity to Leaf Area Density

KHALED HASHAD, K. Max Zhang, Pradeep S. Prathibha, Jay R. Turner, Daniel Fleischer, Cornell University

     Abstract Number: 1600
     Working Group: Control and Mitigation

Abstract
Exposure to near-road air pollution is a widespread public health concern due to its association with adverse health effects as demonstrated by several epidemiological and toxicological studies. While emission control technologies and programs to directly reduce traffic-related air pollution emissions (referred to as “active” mitigation) are vital components of air quality management, considerable research has been carried out to identify, develop and evaluate “passive” mitigation strategies to reduce exposure to near-road air pollutants (PM2.5, ultrafine particles (UFP), black carbon, NOx and others). Vegetative barriers have been shown to be a promising passive strategy, but their effectiveness depends on leaf area density (LAD) which is often ill-characterized. In our study, we employ three independent methods to estimate the LAD of an engineered vegetative barrier planted in the front lawn of the Saint Margaret Mary (SMM) school in Louisville, KY. The barrier lies parallel to the road and consists of small shrubs, forbs, and trees selected to maximize pollutant removal but not adversely affect dispersion. The three LAD estimation methods include direct sampling of tree branches, optical porosity measurement and voxel-level analysis from ground-based LiDAR remote sensing data. The derived LAD profiles from each method are used as inputs to a high-fidelity computational fluids dynamics model to quantify the reduction of near-road pollutant concentrations for the SMM site, evaluated against observational data including UFP number concentration collected during intensive field measurements. This study marks the first comprehensive assessment of LAD sensitivity. The preliminary results from our study reveal the need to reduce uncertainties associated with LAD estimations and are being used to optimize planting strategies for Green Heart project which is a neighborhood-scale greening study being conducted in Louisville.