Abstract
The current study examines predictions of transference ratios and related modeled parameters for oxidized sulfur and oxidized nitrogen using five years (2002–2006) of 12-km grid cell-specific annual estimates from EPA's Community Multiscale Air Quality (CMAQ) model for five selected sub-regions in the eastern US. The monitored oxidized nitrogen species (OxN) considered in the current study includes airborne gaseous nitric acid (HNO3) and particulate nitrate (NO3−), and NO3− ion in precipitation. Modeled airborne OxN accounts for approximately 20% of the modeled airborne concentration of the total reactive oxidized nitrogen (NOY) but is responsible for approximately 80% of the modeled total deposition of NOY. Modeled airborne concentration and total deposition for both oxidized sulfur and OxN tend to be higher than corresponding monitoring-based results, suggesting a need for both model refinement and more comprehensive comparisons with monitoring results. Model estimated annual transference ratios have both spatial variability (grid cell-to-grid cell) and temporal variability (across the five modeled years). Two approaches are explored to investigate the impacts of modeled spatial variability of transference ratios on estimates of regional total deposition. Assuming proportionality rather than equality between cell-specific and regional deposition appears to reduce the impact of modeled spatial variability of transference ratios on estimates of regional total deposition by a substantial margin. The variability of monitored airborne concentration was found to have a noticeable impact on variability in regional total deposition estimated with input from CMAQ. Examination of five years of annual model predictions (along with assumed coefficient of variation (CV) of 10% for the monitored species annual airborne concentration) suggests that in the sub-regions that were considered, most estimates of modeled two-year mean regional total deposition of oxidized sulfur and NOY have CVs that are ≤13.4%. These results also suggest that judicious site selection using air quality model predictions may be employed to optimize representative determinations of regional total deposition. These findings should be considered with caution because they are based almost entirely on modeled annual results (i.e., modeled spatial and modeled temporal variability), and they fail to consider several sources of uncertainty, including discrepancies between model predictions and monitoring results as well as important deposition processes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.