Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6338998 | Atmospheric Environment | 2014 | 7 Pages |
Abstract
An extensive collection of speciated PM2.5 measurements including organic tracers permitted a detailed examination of the emissions from residential wood combustion (RWC) in the southeastern United States over an entire year (2007). The Community Multiscale Air Quality model-based Integrated Source Apportionment Method (CMAQ-ISAM) was used in combination with the U.S. National Emissions Inventory (NEI) to compute source contributions from ten categories of biomass combustion, including RWC. A novel application of the receptor-based statistical model, Unmix, was used to subdivide the observed concentrations of levoglucosan, a unique tracer of biomass combustion. Using the CMAQ-ISAM and Unmix models together, we find that the emission-based RWC contribution to ambient carbonaceous PM2.5 predicted by the model is approximately a factor of two lower than indicated by observations. Recommendations for improving the temporal allocation of the emissions are proposed and tested to show a potential improvement in model RWC predictions, quantified by approximately 15% less bias. Further improvements in the sector predictions could be achieved with a survey-based analysis of detailed RWC emission patterns.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Atmospheric Science
Authors
Sergey L. Napelenok, Ram Vedantham, Prakash V. Bhave, George A. Pouliot, Roger H.F. Kwok,