scholarly journals Technical Note: Relating functional group measurements to carbon types for improved model-measurement comparisons of organic aerosol composition

2016 ◽  
Author(s):  
Satoshi Takahama ◽  
Giulia Ruggeri
Keyword(s):  
Organic Carbon ◽  
Functional Group ◽  
Organic Aerosol ◽  
Chem Phys ◽  
Technical Note ◽  
Molecular Structures ◽  
Organic Carbon Content ◽  
Aerosol Composition ◽  
Ft Ir ◽  
Model Measurement

Abstract. Functional group (FG) analysis provides a means by which functionalization in organic aerosol can be attributed to the abundances of its underlying molecular structures. However, performing this attribution requires additional, unobserved details about the molecular mixture to provide constraints in the estimation process. To address this issue, we present an approach for conceptualizing FG measurements of organic aerosol in terms of its functionalized carbon atoms. This reformulation facilitates estimation of mass recovery and biases in popular carbon-centric metrics that describe the extent of functionalization (such as oxygen to carbon ratio, organic mass to organic carbon mass ratio, and mean carbon oxidation state) for any given set of molecules and FGs analyzed. Furthermore, this approach allows development of parameterizations to more precisely estimate the organic carbon content from measured FG abundance. We use simulated photooxidation products of α-pinene secondary organic aerosol previously reported by Ruggeri et al. (Atmos. Chem. Phys., 16, 4401–4422, 2016) and FG measurements by Fourier Transform Infrared (FT-IR) spectroscopy in chamber experiments by Sax et al. (Aerosol Sci. Tech., 39, 822–830, 2005) to infer the relationships among molecular composition, FG composition, and metrics of organic aerosol functionalization. We find that for this simulated system, ~ 80 % of the carbon atoms should be detected by FGs for which calibration models are commonly developed, and ~ 7 % of the carbon atoms are undetectable by FT-IR analysis because they are not associated with vibrational modes in the infrared. Estimated biases due to undetected carbon fraction for these simulations are used to make adjustments in these carbon-centric metrics such that model-measurement differences are framed in terms of unmeasured heteroatoms (e.g., in hydroperoxide and nitrate groups for the case studied in this demonstration). The formality of this method provides framework for extending FG analysis to not only model-measurement but also instrument intercomparisons in other chemical systems.

scholarly journals Technical note: Relating functional group measurements to carbon types for improved model–measurement comparisons of organic aerosol composition

2017 ◽  
Vol 17 (7) ◽  
pp. 4433-4450 ◽  
Author(s):  
Satoshi Takahama ◽  
Giulia Ruggeri
Keyword(s):  
Organic Carbon ◽  
Functional Group ◽  
Organic Aerosol ◽  
Technical Note ◽  
Molecular Structures ◽  
Organic Carbon Content ◽  
Aerosol Composition ◽  
Ft Ir ◽  
Improved Model ◽  
Model Measurement

Abstract. Functional group (FG) analysis provides a means by which functionalization in organic aerosol can be attributed to the abundances of its underlying molecular structures. However, performing this attribution requires additional, unobserved details about the molecular mixture to provide constraints in the estimation process. We present an approach for conceptualizing FG measurements of organic aerosol in terms of its functionalized carbon atoms. This reformulation facilitates estimation of mass recovery and biases in popular carbon-centric metrics that describe the extent of functionalization (such as oxygen to carbon ratio, organic mass to organic carbon mass ratio, and mean carbon oxidation state) for any given set of molecules and FGs analyzed. Furthermore, this approach allows development of parameterizations to more precisely estimate the organic carbon content from measured FG abundance. We use simulated photooxidation products of α-pinene secondary organic aerosol previously reported by Ruggeri et al. (2016) and FG measurements by Fourier transform infrared (FT-IR) spectroscopy in chamber experiments by Sax et al. (2005) to infer the relationships among molecular composition, FG composition, and metrics of organic aerosol functionalization. We find that for this simulated system, ∼ 80 % of the carbon atoms should be detected by FGs for which calibration models are commonly developed, and ∼ 7 % of the carbon atoms are undetectable by FT-IR analysis because they are not associated with vibrational modes in the infrared. Estimated biases due to undetected carbon fraction for these simulations are used to make adjustments in these carbon-centric metrics such that model–measurement differences are framed in terms of unmeasured heteroatoms (e.g., in hydroperoxide and nitrate groups for the case studied in this demonstration). The formality of this method provides framework for extending FG analysis to not only model–measurement but also instrument intercomparisons in other chemical systems.

scholarly journals Predicting ambient aerosol thermal-optical reflectance (TOR) measurements from infrared spectra: organic carbon

2015 ◽  
Vol 8 (3) ◽  
pp. 1097-1109 ◽  
Author(s):  
A. M. Dillner ◽  
S. Takahama
Keyword(s):  
Organic Carbon ◽  
Partial Least Squares Regression ◽  
Functional Group ◽  
Group Composition ◽  
Organic Aerosol ◽  
Least Squares Regression ◽  
Normalized Error ◽  
Ft Ir ◽  
Test Sets ◽  
Absorbance Spectra

Abstract. Organic carbon (OC) can constitute 50% or more of the mass of atmospheric particulate matter. Typically, organic carbon is measured from a quartz fiber filter that has been exposed to a volume of ambient air and analyzed using thermal methods such as thermal-optical reflectance (TOR). Here, methods are presented that show the feasibility of using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE or Teflon) filters to accurately predict TOR OC. This work marks an initial step in proposing a method that can reduce the operating costs of large air quality monitoring networks with an inexpensive, non-destructive analysis technique using routinely collected PTFE filter samples which, in addition to OC concentrations, can concurrently provide information regarding the composition of organic aerosol. This feasibility study suggests that the minimum detection limit and errors (or uncertainty) of FT-IR predictions are on par with TOR OC such that evaluation of long-term trends and epidemiological studies would not be significantly impacted. To develop and test the method, FT-IR absorbance spectra are obtained from 794 samples from seven Interagency Monitoring of PROtected Visual Environment (IMPROVE) sites collected during 2011. Partial least-squares regression is used to calibrate sample FT-IR absorbance spectra to TOR OC. The FTIR spectra are divided into calibration and test sets by sampling site and date. The calibration produces precise and accurate TOR OC predictions of the test set samples by FT-IR as indicated by high coefficient of variation (R2; 0.96), low bias (0.02 μg m−3, the nominal IMPROVE sample volume is 32.8 m3), low error (0.08 μg m−3) and low normalized error (11%). These performance metrics can be achieved with various degrees of spectral pretreatment (e.g., including or excluding substrate contributions to the absorbances) and are comparable in precision to collocated TOR measurements. FT-IR spectra are also divided into calibration and test sets by OC mass and by OM / OC ratio, which reflects the organic composition of the particulate matter and is obtained from organic functional group composition; these divisions also leads to precise and accurate OC predictions. Low OC concentrations have higher bias and normalized error due to TOR analytical errors and artifact-correction errors, not due to the range of OC mass of the samples in the calibration set. However, samples with low OC mass can be used to predict samples with high OC mass, indicating that the calibration is linear. Using samples in the calibration set that have different OM / OC or ammonium / OC distributions than the test set leads to only a modest increase in bias and normalized error in the predicted samples. We conclude that FT-IR analysis with partial least-squares regression is a robust method for accurately predicting TOR OC in IMPROVE network samples – providing complementary information to the organic functional group composition and organic aerosol mass estimated previously from the same set of sample spectra (Ruthenburg et al., 2014).

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.

scholarly journals Predicting ambient aerosol Thermal Optical Reflectance (TOR) measurements from infrared spectra: organic carbon

2014 ◽  
Vol 7 (11) ◽  
pp. 10931-10964
Author(s):  
A. M. Dillner ◽  
S. Takahama
Keyword(s):  
Organic Carbon ◽  
Partial Least Squares Regression ◽  
Functional Group ◽  
Group Composition ◽  
Least Squares Regression ◽  
Normalized Error ◽  
Ft Ir ◽  
Ir Analysis ◽  
Test Sets ◽  
Absorbance Spectra

Abstract. Organic carbon (OC) can constitute 50% or more of the mass of atmospheric particulate matter. Typically, the organic carbon concentration is measured using thermal methods such as Thermal-Optical Reflectance (TOR) from quartz fiber filters. Here, methods are presented whereby Fourier Transform Infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE or Teflon) filters are used to accurately predict TOR OC. Transmittance FT-IR analysis is rapid, inexpensive, and non-destructive to the PTFE filters. To develop and test the method, FT-IR absorbance spectra are obtained from 794 samples from seven Interagency Monitoring of PROtected Visual Environment (IMPROVE) sites sampled during 2011. Partial least squares regression is used to calibrate sample FT-IR absorbance spectra to artifact-corrected TOR OC. The FTIR spectra are divided into calibration and test sets by sampling site and date which leads to precise and accurate OC predictions by FT-IR as indicated by high coefficient of determination (R2; 0.96), low bias (0.02 μg m−3, all μg m−3 values based on the nominal IMPROVE sample volume of 32.8 m−3), low error (0.08 μg m−3) and low normalized error (11%). These performance metrics can be achieved with various degrees of spectral pretreatment (e.g., including or excluding substrate contributions to the absorbances) and are comparable in precision and accuracy to collocated TOR measurements. FT-IR spectra are also divided into calibration and test sets by OC mass and by OM / OC which reflects the organic composition of the particulate matter and is obtained from organic functional group composition; this division also leads to precise and accurate OC predictions. Low OC concentrations have higher bias and normalized error due to TOR analytical errors and artifact correction errors, not due to the range of OC mass of the samples in the calibration set. However, samples with low OC mass can be used to predict samples with high OC mass indicating that the calibration is linear. Using samples in the calibration set that have a different OM / OC or ammonium / OC distributions than the test set leads to only a modest increase in bias and normalized error in the predicted samples. We conclude that FT-IR analysis with partial least squares regression is a robust method for accurately predicting TOR OC in IMPROVE network samples; providing complementary information to the organic functional group composition and organic aerosol mass estimated previously from the same set of sample spectra (Ruthenburg et al., 2014).

scholarly journals Functional group composition of ambient and source organic aerosols determined by tandem mass spectrometry

2010 ◽  
Vol 10 (15) ◽  
pp. 7041-7055 ◽  
Author(s):  
J. Dron ◽  
I. El Haddad ◽  
B. Temime-Roussel ◽  
J.-L. Jaffrezo ◽  
H. Wortham ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Functional Groups ◽  
Mass Spectra ◽  
Functional Group ◽  
Group Composition ◽  
Organic Aerosol ◽  
Tandem Mass ◽  
Wood Combustion ◽  
Alpine Valley ◽  
Aerosol Sources

Abstract. The functional group composition of various organic aerosols (OA) is investigated using a recently developed analytical approach based on atmospheric pressure chemical ionisation-tandem mass spectrometry (APCI-MS/MS). The determinations of three functional groups contents are performed quantitatively by neutral loss (carboxylic and carbonyl groups, R-COOH and R-CO-R´ respectively) and precursor ion (nitro groups, R-NO2) scanning modes of a tandem mass spectrometer. Major organic aerosol sources are studied: vehicular emission and wood combustion for primary aerosol sources; and a secondary organic aerosol (SOA) produced through photooxidation of o-xylene. The results reveal significant differences in the functional group contents of these source aerosols. The laboratory generated SOA is dominated by carbonyls while carboxylics are preponderate in the wood combustion particles. On the other hand, vehicular emissions are characterised by a strong nitro content. The total amount of the three functional groups accounts for 1.7% (vehicular) to 13.5% (o-xylene photooxidation) of the organic carbon. Diagnostic functional group ratios are then used to tentatively discriminate sources of particles collected in an urban background environment located in an Alpine valley (Chamonix, France) during a strong winter pollution event. The three functional groups under study account for a total functionalisation rate of 2.2 to 3.8% of the organic carbon in this ambient aerosol, which is also dominated by carboxylic moieties. In this particular case study of a deep alpine valley during winter, we show that the nitro- and carbonyl-to-carboxylic diagnostic ratios can be a useful tool to discriminate sources. In these conditions, the total OA concentrations are highly dominated by wood combustion OA. This result is confirmed by an organic markers source apportionment approach which assess a wood burning organic carbon contribution of about 60%. Finally, examples of functional group mass spectra of all aerosols under study are presented, and additional perspectives offered by the mass spectra in terms of OA characterisation are discussed.

scholarly journals Determination of the biogenic secondary organic aerosol fraction in the boreal forest by NMR spectroscopy

2012 ◽  
Vol 12 (2) ◽  
pp. 941-959 ◽  
Author(s):  
E. Finessi ◽  
S. Decesari ◽  
M. Paglione ◽  
L. Giulianelli ◽  
C. Carbone ◽  
...  
Keyword(s):  
Nmr Spectroscopy ◽  
Boreal Forest ◽  
Functional Group ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Spectroscopic Techniques ◽  
Aerosol Composition ◽  
Air Masses ◽  
The North ◽  
Aerosol Mass

Abstract. The study investigates the sources of fine organic aerosol (OA) in the boreal forest, based on measurements including both filter sampling (PM1) and online methods and carried out during a one-month campaign held in Hyytiälä, Finland, in spring 2007. Two aerosol mass spectrometers (Q-AMS, ToF-AMS) were employed to measure on-line concentrations of major non-refractory aerosol species, while the water extracts of the filter samples were analyzed by nuclear magnetic resonance (NMR) spectroscopy for organic functional group characterization of the polar organic fraction of the aerosol. AMS and NMR spectra were processed separately by non-negative factorization algorithms, in order to apportion the main components underlying the submicrometer organic aerosol composition and depict them in terms of both mass fragmentation patterns and functional group compositions. The NMR results supported the AMS speciation of oxidized organic aerosol (OOA) into two main fractions, which could be generally labelled as more and less oxidized organics. The more oxidized component was characterized by a mass spectrum dominated by the m/z 44 peak, and in parallel by a NMR spectrum showing aromatic and aliphatic backbones highly substituted with oxygenated functional groups (carbonyls/carboxyls and hydroxyls). Such component, contributing on average 50% of the OA mass throughout the observing period, was associated with pollution outbreaks from the Central Europe. The less oxidized component was enhanced in concomitance with air masses originating from the North-to-West sector, in agreement with previous investigations conducted at this site. NMR factor analysis was able to separate two distinct components under the less oxidized fraction of OA. One of these NMR-factors was associated with the formation of terrestrial biogenic secondary organic aerosol (BSOA), based on the comparison with spectral profiles obtained from laboratory experiments of terpenes photo-oxidation. The second NMR factor associated with western air masses was linked to biogenic marine sources, and was enriched in low-molecular weight aliphatic amines. Such findings provide evidence of at least two independent sources originating biogenic organic aerosols in Hyytiälä by oxidation and condensation mechanisms: reactive terpenes emitted by the boreal forest and compounds of marine origin, with the latter relatively more important when predominantly polar air masses reach the site. This study is an example of how spectroscopic techniques, such as proton NMR, can add functional group specificity for certain chemical features (like aromatics) of OA with respect to AMS. They can therefore be profitably exploited to complement aerosol mass spectrometric measurements in organic source apportionment studies.

scholarly journals Technical Note: Development of chemoinformatic tools to enumerate functional groups in molecules for organic aerosol characterization

2016 ◽  
Vol 16 (7) ◽  
pp. 4401-4422 ◽  
Author(s):  
Giulia Ruggeri ◽  
Satoshi Takahama
Keyword(s):  
Functional Groups ◽  
Chemical Speciation ◽  
Organic Aerosol ◽  
Technical Note ◽  
Carbon Oxidation ◽  
Estimation Model ◽  
Aerosol Composition ◽  
Reduced Representation ◽  
Complete Set ◽  
Chamber Studies

Abstract. Functional groups (FGs) can be used as a reduced representation of organic aerosol composition in both ambient and controlled chamber studies, as they retain a certain chemical specificity. Furthermore, FG composition has been informative for source apportionment, and various models based on a group contribution framework have been developed to calculate physicochemical properties of organic compounds. In this work, we provide a set of validated chemoinformatic patterns that correspond to (1) a complete set of functional groups that can entirely describe the molecules comprised in the α-pinene and 1,3,5-trimethylbenzene MCMv3.2 oxidation schemes, (2) FGs that are measurable by Fourier transform infrared spectroscopy (FTIR), (3) groups incorporated in the SIMPOL.1 vapor pressure estimation model, and (4) bonds necessary for the calculation of carbon oxidation state. We also provide example applications for this set of patterns. We compare available aerosol composition reported by chemical speciation measurements and FTIR for different emission sources, and calculate the FG contribution to the O : C ratio of simulated gas-phase composition generated from α-pinene photooxidation (using the MCMv3.2 oxidation scheme).

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