scholarly journals Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: sparse methods for statistical selection of relevant absorption bands

2016 ◽  
Vol 9 (7) ◽  
pp. 3429-3454 ◽  
Author(s):  
Satoshi Takahama ◽  
Giulia Ruggeri ◽  
Ann M. Dillner
Keyword(s):  
Infrared Spectra ◽  
Atmospheric Aerosols ◽  
Quantitative Prediction ◽  
Calibration Model ◽  
Vibrational Modes ◽  
Aerosol Composition ◽  
Absorption Bands ◽  
Calibration Models ◽  
Ft Ir ◽  
Selection Of

Abstract. Various vibrational modes present in molecular mixtures of laboratory and atmospheric aerosols give rise to complex Fourier transform infrared (FT-IR) absorption spectra. Such spectra can be chemically informative, but they often require sophisticated algorithms for quantitative characterization of aerosol composition. Naïve statistical calibration models developed for quantification employ the full suite of wavenumbers available from a set of spectra, leading to loss of mechanistic interpretation between chemical composition and the resulting changes in absorption patterns that underpin their predictive capability. Using sparse representations of the same set of spectra, alternative calibration models can be built in which only a select group of absorption bands are used to make quantitative prediction of various aerosol properties. Such models are desirable as they allow us to relate predicted properties to their underlying molecular structure. In this work, we present an evaluation of four algorithms for achieving sparsity in FT-IR spectroscopy calibration models. Sparse calibration models exclude unnecessary wavenumbers from infrared spectra during the model building process, permitting identification and evaluation of the most relevant vibrational modes of molecules in complex aerosol mixtures required to make quantitative predictions of various measures of aerosol composition. We study two types of models: one which predicts alcohol COH, carboxylic COH, alkane CH, and carbonyl CO functional group (FG) abundances in ambient samples based on laboratory calibration standards and another which predicts thermal optical reflectance (TOR) organic carbon (OC) and elemental carbon (EC) mass in new ambient samples by direct calibration of infrared spectra to a set of ambient samples reserved for calibration. We describe the development and selection of each calibration model and evaluate the effect of sparsity on prediction performance. Finally, we ascribe interpretation to absorption bands used in quantitative prediction of FGs and TOR OC and EC concentrations.

scholarly journals Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: sparse methods for statistical selection of relevant absorption bands

2016 ◽  
Author(s):  
Satoshi Takahama ◽  
Giulia Ruggeri ◽  
Ann M. Dillner
Keyword(s):  
Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Atmospheric Aerosols ◽  
Model Building ◽  
Quantitative Prediction ◽  
Calibration Model ◽  
Aerosol Composition ◽  
Absorption Bands ◽  
Calibration Models ◽  
Selection Of

Abstract. We present an evaluation of four algorithms for achieving sparsity in Fourier Transform Infrared Spectroscopy calibration models. Sparse calibration models exclude unnecessary wavenumbers from infrared spectra during the model building process, permitting identification and evaluation of the most relevant vibrational modes of molecules in complex aerosol mixtures required to make quantitative predictions of various measures of aerosol composition. We study two types of models: one which predicts alcohol COH, carboxylic COH, alkane CH, and carbonyl CO functional group (FG) abundances in ambient samples based on laboratory calibration standards, and another which predicts thermal optical reflectance (TOR) organic carbon (OC) and elemental carbon (EC) mass in new ambient samples by direct calibration of infrared spectra to a set of ambient samples reserved for calibration. We describe the development and selection of each calibration model, and evaluate the effect of sparsity on prediction performance. Finally, we ascribe interpretation to absorption bands used in quantitative prediction of FGs and TOR OC and EC concentrations.

scholarly journals Atmospheric particulate matter characterization by Fourier transform infrared spectroscopy: a review of statistical calibration strategies for carbonaceous aerosol quantification in US measurement networks

2019 ◽  
Vol 12 (1) ◽  
pp. 525-567 ◽  
Author(s):  
Satoshi Takahama ◽  
Ann M. Dillner ◽  
Andrew T. Weakley ◽  
Matteo Reggente ◽  
Charlotte Bürki ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Particulate Matter ◽  
Ir Spectroscopy ◽  
Atmospheric Particulate Matter ◽  
Calibration Model ◽  
Vibrational Modes ◽  
Calibration Models ◽  
Ft Ir ◽  
Ft Ir Spectroscopy ◽  
Statistical Calibration

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.

scholarly journals Atmospheric particulate matter characterization by Fourier Transform Infrared spectroscopy: a review of statistical calibration strategies for carbonaceous aerosol quantification in US measurement networks

2018 ◽  
Author(s):  
Satoshi Takahama ◽  
Ann M. Dillner ◽  
Andrew T. Weakley ◽  
Matteo Reggente ◽  
Charlotte Bürki ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Particulate Matter ◽  
Fourier Transform Infrared ◽  
Atmospheric Particulate Matter ◽  
Calibration Model ◽  
Vibrational Modes ◽  
Atmospheric Particulate ◽  
Calibration Models ◽  
Ft Ir ◽  
Statistical Calibration

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 has enjoyed a long history in monitoring gas-phase constituents in the atmospher 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 predicting 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 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: 7 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 6 of the same sites as 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 can be envisioned for any substance with IR-active vibrational modes, and more generally for instruments requiring ambient calibrations.

scholarly journals Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 1: Methods

2019 ◽  
Vol 12 (10) ◽  
pp. 5391-5415 ◽  
Author(s):  
Alexandra J. Boris ◽  
Satoshi Takahama ◽  
Andrew T. Weakley ◽  
Bruno M. Debus ◽  
Carley D. Fredrickson ◽  
...  
Keyword(s):  
Organic Matter ◽  
Functional Groups ◽  
Atmospheric Chemistry ◽  
Functional Group ◽  
Aerosol Composition ◽  
Ir Spectrometry ◽  
Southeastern Us ◽  
Inorganic Species ◽  
Calibration Models ◽  
Ft Ir

Abstract. Comprehensive techniques to describe the organic composition of atmospheric aerosol are needed to elucidate pollution sources, gain insights into atmospheric chemistry, and evaluate changes in air quality. Fourier transform infrared absorption (FT-IR) spectrometry can be used to characterize atmospheric organic matter (OM) and its composition via functional groups of aerosol filter samples in air monitoring networks and research campaigns. We have built FT-IR spectrometry functional group calibration models that improve upon previous work, as demonstrated by the comparison of current model results with those of previous models and other OM analysis methods. Laboratory standards that simulated the breadth of the absorbing functional groups in atmospheric OM were made: particles of relevant chemicals were first generated, collected, and analyzed. Challenges of collecting atmospherically relevant particles and spectra were addressed by including interferences of particle water and other inorganic aerosol constituents and exploring the spectral effects of intermolecular interactions. Calibration models of functional groups were then constructed using partial least-squares (PLS) regression and the collected laboratory standard data. These models were used to quantify concentrations of five organic functional groups and OM in 8 years of ambient aerosol samples from the southeastern aerosol research and characterization (SEARCH) network. The results agreed with values estimated using other methods, including thermal optical reflectance (TOR) organic carbon (OC; R2=0.74) and OM calculated as a difference between total aerosol mass and inorganic species concentrations (R2=0.82). Comparisons with previous calibration models of the same type demonstrate that this new, more complete suite of chemicals has improved our ability to estimate oxygenated functional group and overall OM concentrations. Calculated characteristic and elemental ratios including OM∕OC, O∕C, and H∕C agree with those from previous work in the southeastern US, substantiating the aerosol composition described by FT-IR calibration. The median OM∕OC ratio over all sites and years was 2.1±0.2. Further results discussing temporal and spatial trends of functional group composition within the SEARCH network will be published in a forthcoming article.

Angular Dependence of Diffuse Reflectance Infrared Spectra. Part II: Effect of Polarization

1987 ◽  
Vol 41 (5) ◽  
pp. 791-797 ◽  
Author(s):  
Paul J. Brimmer ◽  
Peter R. Griffiths
Keyword(s):  
Angular Dependence ◽  
Infrared Spectra ◽  
Diffuse Reflectance ◽  
Absolute Intensity ◽  
Absorption Bands ◽  
Reflectance Measurement ◽  
Wire Grid ◽  
Optical Geometry ◽  
Ft Ir ◽  
Diffuse Reflectance Infrared

The magnitude of specular and diffuse Fresnel reflectance from powdered samples was investigated with the use of an FT-IR spectrogoniophotometer with wire-grid polarizers mounted in front of and behind the sample. Specular Fresnel reflectance maintains the polarization of the incoming infrared beam and can therefore be eliminated by crossing the orientation of the second polarizer relative to the first. For neat samples, diffuse Fresnel reflectance was found to be only slightly affected by the presence of the two polarizers. While specular Fresnel reflectance is affected by the optical geometry used in making the reflectance measurement, diffuse Fresnel reflectance is unaffected by optical geometry and can only be eliminated by dilution of the neat sample. For dilute samples, the optical geometry and the orientation of the two polarizers slightly affect the absolute intensity of absorption bands, but do not change relative band intensities or band positions.

Application of Multivariate Calibration Techniques to Quantitative Analysis of Bandpass-Filtered Fourier Transform Infrared Interferogram Data

1997 ◽  
Vol 51 (9) ◽  
pp. 1369-1376 ◽  
Author(s):  
Mutua J. Mattu ◽  
Gary W. Small ◽  
Mark A. Arnold
Keyword(s):  
Fourier Transform ◽  
Quantitative Analysis ◽  
Multivariate Calibration ◽  
Fourier Transform Infrared ◽  
Calibration Model ◽  
Calibration Models ◽  
Background Measurement ◽  
Ft Ir ◽  
Calibration Techniques ◽  
Absorbance Spectra

Multivariate calibration models are developed that allow quantitative analysis of short segments of Fourier transform infrared (FT-IR) interferogram data. Before the interferogram segments are submitted to partial least-squares (PLS) regression analysis, a bandpass digital filter is applied to isolate a narrow range of frequencies that correspond to an absorption band of the target analyte. This adds frequency selectivity to the analysis, thereby overcoming the principal obstacle to the direct use of interferogram data for quantitative analysis. With the optimization of the frequency response function of the filter, as well as the position and length of the interferogram segment employed, calibration models are developed that compare well with those computed with conventional absorbance spectra. This methodology is demonstrated by developing calibration models for determining glucose in an aqueous buffer matrix over the physiologically relevant concentration range of 1–20 mM. Through the use of a time-domain filter designed to isolate the modulated interferogram frequencies corresponding to the glucose C–H combination band at 4400 cm−1, a three-factor PLS calibration model is computed on the basis of interferogram points 601–850. This model is characterized by standard errors of calibration (SEC) and prediction (SEP) of 0.3311 and 0.6950 mM, respectively. The best model obtained in a thorough analysis of the corresponding absorbance spectra was also based on three PLS factors. This model was characterized by values of SEC and SEP of 0.2396 and 0.6115, respectively. In addition to achieving similar calibration and prediction results to the spectral-based model, the interferogram-based method has the advantage of requiring no background measurement of the sample matrix. Furthermore, since the analysis is based on only a 250-point segment of the interferogram, a reduction in the instrumentation and data collection requirements is realized.

scholarly journals Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States, part I: Methods

2019 ◽  
Author(s):  
Alexandra J. Boris ◽  
Satoshi Takahama ◽  
Andrew T. Weakley ◽  
Bruno M. Debus ◽  
Carley D. Fredrickson ◽  
...  
Keyword(s):  
Organic Matter ◽  
Functional Groups ◽  
Atmospheric Chemistry ◽  
Functional Group ◽  
Aerosol Composition ◽  
Ir Spectrometry ◽  
Southeastern Us ◽  
Inorganic Species ◽  
Calibration Models ◽  
Ft Ir

Abstract. Comprehensive techniques to describe the organic composition of atmospheric aerosol are needed to elucidate pollution sources, gain insights into atmospheric chemistry and evaluate changes in air quality. Fourier Transform Infrared absorption (FT-IR) spectrometry can be used to characterize atmospheric organic matter (OM) and its composition via functional groups on aerosol filter samples in air monitoring networks and research campaigns. We have built FT-IR spectrometry functional group calibration models that improve upon previous work. Laboratory standards that simulated the breadth of the absorbing functional groups in atmospheric OM were made: particles of relevant chemicals were first generated, collected, and analyzed. Challenges of collecting atmospherically relevant particles and spectra were addressed by including interferences of particle water and other inorganic aerosol constituents and exploring the spectral effects of inter-molecular interactions. Calibration models of functional groups were then constructed using partial least squares (PLS) regression and the collected laboratory standard data. These models were used to quantify concentrations of five organic functional groups and OM in eight years of ambient aerosol samples from the southeastern aerosol research and characterization (SEARCH) network. The results agreed with values estimated using other methods, including thermal optical reflectance (TOR) organic carbon (OC; R2 = 0.74) and OM calculated as a difference between total aerosol mass and inorganic species concentrations (R2 = 0.82). Comparisons with previous calibration models of the same type demonstrate that this new, more complete suite of chemicals has improved our ability to estimate oxygenated functional group and overall OM concentrations. Calculated characteristic and elemental ratios including OM/OC, O/C and H/C agree with those from previous work in the southeastern US, substantiating the aerosol composition described by FT-IR calibration. The median OM/OC ratio over all sites and years was 2.1 ± 0.2. Further results discussing temporal and spatial trends of functional group composition within the SEARCH network will be published in a forthcoming article.

FT-IR External Reflection Spectroscopy at Brewster's Angle

1992 ◽  
Vol 46 (3) ◽  
pp. 504-509 ◽  
Author(s):  
Yuichi Ishino ◽  
Hatsuo Ishida
Keyword(s):  
Thin Films ◽  
Infrared Spectra ◽  
Polarized Light ◽  
Reflection Spectroscopy ◽  
Absorption Bands ◽  
Nondestructive Technique ◽  
Polymer Substrates ◽  
Optical Effects ◽  
Ft Ir

A nondestructive technique for the measurement of infrared spectra of thick, hard, and dark materials has been studied with the use of external reflection spectroscopy. The distortion of the absorption bands which is due to optical effects can be minimized with the use of parallel polarized light which is incident at Brewster's angle. With this technique, it is impossible to observe over-absorption even if the material has a semi-infinite thickness. Also, this technique can be applied to the study of thin films on polymer substrates.

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