Abstract
Abstract. Data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network are used to estimate organic mass to organic carbon (OM/OC) ratios across the United States by extending previously published multiple regression techniques. Our new methodology addresses common pitfalls of multiple regression including measurement uncertainty, colinearity of covariates, dataset selection, and model selection. As expected, summertime OM/OC ratios are larger than wintertime values across the US with all regional median OM/OC values tightly confined between 1.80 and 1.95. Further, we find that OM/OC ratios during the winter are distinctly larger in the eastern US than in the West (regional medians are 1.58, 1.64, and 1.85 in the great lakes, southeast, and northeast regions, versus 1.29 and 1.32 in the western and central states). We find less spatial variability in long-term averaged OM/OC ratios across the US (90% of our multiyear regressions estimate OM/OC ratios between 1.37 and 1.94) than previous studies (90% fell between 1.30 and 2.10). We attribute this difference largely to the inclusion of EC as a covariate in previous regression studies. Due to the colinearity of EC and OC, we find that up to one-quarter of the OM/OC estimates in a previous study are biased low. Assumptions about OC measurement artifacts add uncertainty to our estimates of OM/OC. In addition to estimating OM/OC ratios, our technique reveals trends that may be contrasted with conventional assumptions regarding nitrate, sulfate, and soil across the IMPROVE network. For example, our regressions show pronounced seasonal and spatial variability in both nitrate volatilization and sulfate neutralization and hydration.
Highlights
Atmospheric measurements have shown that organic mass (OM) is a major component of fine particulate matter (PM2.5), comprising over 50% of ambient PM2.5 in some locations (Jimenez et al, 2009; Murphy et al, 2006; Zhang et al, 2007)
In this paper we develop a nationwide dataset of seasonally- and spatially-varying organic mass to organic carbon (OM/organic carbon (OC)) ratios across the Interagency Monitoring of Protected Visual Environments (IMPROVE) network by extending the methodology of Malm and Hand (2007) while addressing some common pitfalls in multiple regression
This work has helped to develop a robust technique for estimating OM/OC ratios that can be applied to an expansive dataset, such as the IMPROVE monitoring network data
Summary
Atmospheric measurements have shown that organic mass (OM) is a major component of fine particulate matter (PM2.5), comprising over 50% of ambient PM2.5 in some locations (Jimenez et al, 2009; Murphy et al, 2006; Zhang et al, 2007). To achieve mass closure in source testing and ambient particle measurements, an OM/OC ratio (denoted as k and ROC in some earlier literature, Frank, 2006; Malm and Hand, 2007) is often multiplied by measured OC to estimate total OM. This ratio is primarily affected by the oxygen content in the organic aerosol (Pang et al, 2006), hydrogen, nitrogen, and sulfur make small contributions to the NCOM. In recent years a range of techniques have been applied to quantify OM/OC, including gas chromatography/mass spectrometry (GC/MS) (Turpin and Lim, 2001; Yu et al, 2005), high resolution time of flight aerosol mass spectrometry (HR-ToF-AMS) (Aiken et al, 2008; Chan et al, 2010; Sun et al, 2009), Fourier Transform Infrared (FTIR) spectroscopy (Gilardoni et al, 2007; Kiss et al, 2002; Liu et al, 2009; Polidori et al, 2008; Reff et al, 2007; Russell, 2003; Russell et al, 2009), sequential extraction followed by gravimetric weighing and thermal optical measurement of carbon
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