Using Low-Cost Air Quality Sensor Networks to Improve the Spatial and Temporal Resolution of Concentration Maps.

We present an approach to analyzing fine particulate matter (PM) data from a network of "low cost air quality monitors" (LCAQM) to obtain a finely resolved concentration map. In the approach, based on a dispersion model, we first identify the probable locations of the sources, and then estimate the magnitudes of the emissions from these sources by fitting model estimates of concentrations to corresponding measurements. The emissions are then used to estimate concentrations on a grid covering the domain of interest.

Modeling Dispersion of Emissions from Depressed Roadways.

This paper presents an analysis of data from a wind tunnel (Heist et al., 2009) conducted to study dispersion of emissions from three depressed roadway configurations; a 6 m deep depressed roadway with vertical sidewalls, a 6 m deep depressed roadway with 30° sloping sidewalls, and a 9 m deep depressed roadway with vertical sidewalls. The width of the road at the bottom of the depression is 36 m for all cases.

Reduction of air pollution levels downwind of a road with an upwind noise barrier.

We propose a dispersion model to estimate the impact of a solid noise barrier upwind of a highway on air pollution concentrations downwind of the road. The model, based on data from wind tunnel experiments conducted by Heist et al. (2009), assumes that the upwind barrier has two main effects: 1) it creates a recirculation zone behind the barrier that sweeps the emissions from the highway back towards the wall, and 2) it enhances vertical dispersion and initial mixing.