Abstract
Abstract. Peak fitting (PF) and partial least squares (PLS) regression have been independently developed for estimation of functional groups (FGs) from Fourier transform infrared (FTIR) spectra of ambient aerosol collected on Teflon filters. PF is a model that quantifies the functional group composition of the ambient samples by fitting individual Gaussian line shapes to the aerosol spectra. PLS is a data-driven, statistical model calibrated to laboratory standards of relevant compounds and then extrapolated to ambient spectra. In this work, we compare the FG quantification using the most widely used implementations of PF and PLS, including their model parameters, and also perform a comparison when the underlying laboratory standards and spectral processing are harmonized. We evaluate the quantification of organic FGs (alcohol COH, carboxylic COOH, alkane CH, carbonyl CO) and ammonium, using external measurements (organic carbon (OC) measured by thermal optical reflectance (TOR) and ammonium by balance of sulfate and nitrate measured by ion chromatography). We evaluate our predictions using 794 samples collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA) in 2011 and 238 laboratory standards from Ruthenburg et al. (2014) (available at https://doi.org/10.1016/j.atmosenv.2013.12.034). Each model shows different biases. Overall, estimates of OC by FTIR show high correlation with TOR OC. However, PLS applied to unprocessed (raw spectra) appears to underpredict oxygenated functional groups in rural samples, while other models appear to underestimate aliphatic CH bonds and OC in urban samples. It is possible to adjust model parameters (absorption coefficients for PF and number of latent variables for PLS) within limits consistent with calibration data to reduce these biases, but this analysis reveals that further progress in parameter selection is required. In addition, we find that the influence of scattering and anomalous transmittance of infrared in coarse particle samples can lead to predictions of OC by FTIR which are inconsistent with TOR OC. We also find through several means that most of the quantified carbonyl is likely associated with carboxylic groups rather than ketones or esters. In evaluating state-of-the-art methods for FG abundance by FTIR, we suggest directions for future research.
Highlights
Atmospheric aerosol, called particulate matter (PM), is made up of organic compounds, inorganic salts, trace elements, black carbon, and water, among other substances
We focus on the application midinfrared spectroscopy with Fourier transform infrared spectroscopy (FTIR), especially since it can be applied inexpensively and nondestructively to particulate matter collected on widely used polytetrafluoroethylene (PTFE) filters, and its spectrum obtained corresponds to that characterized by its gravimetric mass
We use 794 Interagency Monitoring of PROtected Visual Environments (IMPROVE) network PM2.5 samples and 238 laboratory standard samples reported by Ruthenburg et al (2014), and we focus on the quantification of four organic functional groups and one additional inorganic group which absorbs in the same region: alcohol COH, carboxylic COH (COOH), alkane CH, total carbonyl, and inorganic ammonium NH
Summary
Atmospheric aerosol, called particulate matter (PM), is made up of organic compounds, inorganic salts, trace elements, black carbon, and water, among other substances. Describing organic mass (OM) in terms of FGs has been useful for source apportionment as it captures particular emission characteristics (e.g., hydroxyl groups in marine sprays and biogenic secondary organic aerosol, ketonic carbonyl from burning) as well as atmospheric processes (e.g., carboxylic acid formation from photooxidation) (e.g., Decesari et al, 2007; Russell et al, 2011; Liu, 2014). Recent work has demonstrated the capacity of FG analysis to bridge the gap between molecular speciation and atomic composition obtained by chromatography and mass spectrometry measurements, and chemically explicit model simulations (Ruggeri and Takahama, 2016; Ruggeri et al, 2016). We focus on the application midinfrared (mid-IR) spectroscopy with FTIR, especially since it can be applied inexpensively and nondestructively to particulate matter collected on widely used polytetrafluoroethylene (PTFE) filters, and its spectrum obtained corresponds to that characterized by its gravimetric mass
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