Abstract
We isolated diurnal timescale contributions to a 6-year hourly radon record and incorporated them in ME-2 as a proxy for changes in atmospheric mixing depth in an attempt to improve the source apportionment of fine atmospheric particulate matter (PM_(2.5)). Results from this radon-based implementation of ME-2 are directly compared with the more traditional ME-2 implementation where wind speed is used, as a proxy for changes in mixing depth. The radon-based version more accurately reproduced daily PM_(2.5) source contributions, as evidenced by better correlations with the results from the corresponding bi-linear model. The versions of ME-2 employed in this study were modified to account for calm wind conditions separately, and a recently updated solution approach was adopted. Source apportionment for the radon-based ME-2 implementation was most successful for the finer, primary emissions (Smoke, Autos, Industry) that are more easily suspended and whose concentrations are more directly tied to changes in atmospheric mixing depth. Incorporation of the diurnal radon signal in ME-2 improved the estimated source strength distributions of the Smoke, Autos and Industry sources with respect to the township of Muswellbrook. It also resulted in a more consistent anti-correlation between these 3 source types and atmospheric mixing depth than for the wind speed case. These results confirm that near surface radon concentration is more closely tied to atmospheric mixing depth (and therefore pollutant concentrations) than wind speed. The measurement site for this study is a small township in a rural setting, with nearby power stations and open-cut coal mines. Consequently, the distribution and characteristics of anthropogenic aerosol sources are very different than for a typical urban or industrial setting. This is reflected in lower correlation between the multi-linear models and the corresponding bi-linear models, indicating that the performance of multi-linear models is affected by the nature of the distribution of sources.
Highlights
Fine aerosols are known to affect the Earth’s radiative balance (e.g., Charlson et al, 1992; Hubert et al, 2003; Jiang et al, 2013) and contribute to adverse health effects (e.g., Dockery et al, 1993; Moloi et al, 2002; Russell and Brunekreef, 2009)
Crawford et al (2013) introduced hourly Radon-222 concentrations observed at Richmond, NSW, to a multi-linear model as a combined proxy for (i) the degree of terrestrial influence on an air mass, and (ii) the degree of dilution in the atmosphere due to the diurnal evolution of the atmospheric boundary layer (ABL)
Evaluation of the Multi-Linear Model To assess the ability of each multi-linear model to reproduce daily PM2.5 source contributions a linear leastsquares regression was performed between columns of the G matrices of the multi-linear model and their corresponding bi-linear model
Summary
Fine aerosols are known to affect the Earth’s radiative balance (e.g., Charlson et al, 1992; Hubert et al, 2003; Jiang et al, 2013) and contribute to adverse health effects (e.g., Dockery et al, 1993; Moloi et al, 2002; Russell and Brunekreef, 2009). Multi-linear models that include other parameters (e.g., speed, wind direction, and temporal factors) have been introduced in ME-2 (Paatero and Hopke, 2002; Kim et al, 2003; Buset et al, 2006).
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