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Abstract
Abstract. Atmospheric particulate matter (PM) is a complex mixture of many different substances and requires a suite of instruments for chemical characterization. Fourier transform infrared (FT-IR) spectroscopy is a technique that can provide quantification of multiple species provided that accurate calibration models can be constructed to interpret the acquired spectra. In this capacity, FT-IR spectroscopy has enjoyed a long history in monitoring gas-phase constituents in the atmosphere and in stack emissions. However, application to PM poses a different set of challenges as the condensed-phase spectrum has broad, overlapping absorption peaks and contributions of scattering to the mid-infrared spectrum. Past approaches have used laboratory standards to build calibration models for prediction of inorganic substances or organic functional groups and predict their concentration in atmospheric PM mixtures by extrapolation. In this work, we review recent studies pursuing an alternate strategy, which is to build statistical calibration models for mid-IR spectra of PM using collocated ambient measurements. Focusing on calibrations with organic carbon (OC) and elemental carbon (EC) reported from thermal–optical reflectance (TOR), this synthesis serves to consolidate our knowledge for extending FT-IR spectroscopy to provide TOR-equivalent OC and EC measurements to new PM samples when TOR measurements are not available. We summarize methods for model specification, calibration sample selection, and model evaluation for these substances at several sites in two US national monitoring networks: seven sites in the Interagency Monitoring of Protected Visual Environments (IMPROVE) network for the year 2011 and 10 sites in the Chemical Speciation Network (CSN) for the year 2013. We then describe application of the model in an operational context for the IMPROVE network for samples collected in 2013 at six of the same sites as in 2011 and 11 additional sites. In addition to extending the evaluation to samples from a different year and different sites, we describe strategies for error anticipation due to precision and biases from the calibration model to assess model applicability for new spectra a priori. We conclude with a discussion regarding past work and future strategies for recalibration. In addition to targeting numerical accuracy, we encourage model interpretation to facilitate understanding of the underlying structural composition related to operationally defined quantities of TOR OC and EC from the vibrational modes in mid-IR deemed most informative for calibration. The paper is structured such that the life cycle of a statistical calibration model for FT-IR spectroscopy can be envisioned for any substance with IR-active vibrational modes, and more generally for instruments requiring ambient calibrations.
Highlights
Airborne particles are made of inorganic salts, organic compounds, mineral dust, black carbon (BC), trace elements, and water (Seinfeld and Pandis, 2016)
We review the current state of the art for quantitative prediction of organic carbon (OC) and elemental carbon (EC) as reported by thermal– optical reflectance (TOR) using Fourier transform infrared (FT-IR) spectroscopy at selected sites of the Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network (Malm and Hand, 2007; Solomon et al, 2014) and the Chemical Speciation Network (CSN) (Solomon et al, 2014)
The FT-IR spectra of particulate matter (PM) are rich in chemical information, and quantitative information such as TOR-equivalent OC and EC can be extracted from it provided that we can find the appropriate combination of training samples and algorithms for extraction
Summary
Airborne particles are made of inorganic salts, organic compounds, mineral dust, black carbon (BC), trace elements, and water (Seinfeld and Pandis, 2016). Gases are measured by FT-IR spectroscopy in an open-path in situ configuration (Russwurm and Childers, 2006) or via extractive sampling into a closed multi-pass cell (Spellicy and Webb, 2006) These techniques have been used to sample urban smog (Pitts et al, 1977; Tuazon et al, 1981; Hanst et al, 1982); smog chambers (Akimoto et al, 1980; Pitts et al, 1984; Ofner, 2011), biomass burning emissions (Hurst et al, 1994; Yokelson et al, 1997; Christian et al, 2004), volcanoes (Oppenheimer and Kyle, 2008), and fugitive gases (Kirchgessner et al, 1993; Russwurm, 1999; U.S EPA, 1998); emission fluxes (Galle et al, 1994; Griffith and Galle, 2000; Griffith et al, 2002); greenhouse gases (Shao and Griffiths, 2010; Hammer et al, 2013; Schütze et al, 2013; Hase et al, 2015); and isotopic composition (Meier and Notholt, 1996; Flores et al, 2017). Synthetic spectra for calibration are generated from a database of absorption line parameters together with simulation of pressure and Doppler broadening and instrumental effects (Griffith, 1996; Flores et al, 2013)
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