scholarly journals Biogenic oxidized organic functional groups in aerosol particles from a mountain forest site and their similarities to laboratory chamber products

2010 ◽  
Vol 10 (2) ◽  
pp. 4789-4822 ◽  
Author(s):  
R. E. Schwartz ◽  
L. M. Russell ◽  
S. J. Sjosted ◽  
A. Vlasenko ◽  
J. G. Slowik ◽  
...  
Keyword(s):  
Carboxylic Acid ◽  
Functional Groups ◽  
Functional Group ◽  
Group Composition ◽  
Organic Aerosol ◽  
Anthropogenic Sources ◽  
Forest Site ◽  
Aerosol Composition ◽  
X Ray ◽  
Organic Functional Groups

Abstract. Submicron particles collected at Whistler, British Columbia, at 1020 masl during May and June 2008 on Teflon filters were analyzed by Fourier transform infrared (FTIR) and X-ray fluorescence (XRF) techniques for organic functional groups (OFG) and elemental composition. Organic mass (OM) ranged from less than 0.5 to 3.1μg m−3, with a project mean and standard deviation of 1.3±1.0 μg m−3 and 0.21±0.16 μg m−3 for OM and sulfate, respectively. On average, organic hydroxyl, alkane, and carboxylic acid groups represented 34%, 33%, and 23% of OM, respectively. Ketone, amine and organosulfate groups constituted 6%, 5%, and <1% of the average organic aerosol composition, respectively. Measurements of volatile organic compounds (VOC), including isoprene and monoterpenes from biogenic VOC (BVOC) emissions and their oxidation products (methyl-vinylketone/methacrolein, MVK/MACR), were made using co-located proton transfer reaction mass spectrometry (PTR-MS). We present chemically-specific evidence of OFG associated with BVOC emissions. Positive matrix factorization (PMF) analysis attributed 65% of the campaign OM to biogenic sources, based on the correlations of one factor to monoterpenes and MVK/MACR. The remaining fraction was attributed to anthropogenic sources based on a correlation to sulfate. The functional group composition of the biogenic factor (consisting of 32% alkane, 25% carboxylic acid, 2% organic hydroxyl, 16% ketone, and 6% amine groups) was similar to that of secondary organic aerosol (SOA) reported from the oxidation of BVOCs in laboratory chamber studies, providing evidence that the magnitude and chemical composition of biogenic SOA simulated in the laboratory is similar to that found in actual atmospheric conditions. The biogenic factor OM is also correlated to dust elements, indicating that dust may act as a non-acidic SOA sink. This role is supported by the organic functional group composition and morphology of single particles, which were analyzed by scanning transmission X-ray microscopy near edge X-ray absorption fine structure (STXM-NEXAFS).

scholarly journals Biogenic oxidized organic functional groups in aerosol particles from a mountain forest site and their similarities to laboratory chamber products

2010 ◽  
Vol 10 (11) ◽  
pp. 5075-5088 ◽  
Author(s):  
R. E. Schwartz ◽  
L. M. Russell ◽  
S. J. Sjostedt ◽  
A. Vlasenko ◽  
J. G. Slowik ◽  
...  
Keyword(s):  
Carboxylic Acid ◽  
Functional Groups ◽  
Functional Group ◽  
Group Composition ◽  
Organic Aerosol ◽  
Anthropogenic Sources ◽  
Forest Site ◽  
Aerosol Composition ◽  
X Ray ◽  
Organic Functional Groups

Abstract. Submicron particles collected at Whistler, British Columbia, at 1020 m a.s.l. during May and June 2008 on Teflon filters were analyzed by Fourier transform infrared (FTIR) and X-ray fluorescence (XRF) techniques for organic functional groups (OFG) and elemental composition. Organic mass (OM) concentrations ranged from less than 0.5 to 3.1 μg m−3, with a project mean and standard deviation of 1.3±1.0 μg m−3 and 0.21±0.16 μg m−3 for OM and sulfate, respectively. On average, organic hydroxyl, alkane, and carboxylic acid groups represented 34%, 33%, and 23% of OM, respectively. Ketone, amine and organosulfate groups constituted 6%, 5%, and <1% of the average organic aerosol composition, respectively. Measurements of volatile organic compounds (VOC), including isoprene and monoterpenes from biogenic VOC (BVOC) emissions and their oxidation products (methyl-vinylketone / methacrolein, MVK/MACR), were made using co-located proton transfer reaction mass spectrometry (PTR-MS). We present chemically-specific evidence of OFG associated with BVOC emissions. Positive matrix factorization (PMF) analysis attributed 65% of the campaign OM to biogenic sources, based on the correlations of one factor to monoterpenes and MVK/MACR. The remaining fraction was attributed to anthropogenic sources based on a correlation to sulfate. The functional group composition of the biogenic factor (consisting of 32% alkane, 25% carboxylic acid, 21% organic hydroxyl, 16% ketone, and 6% amine groups) was similar to that of secondary organic aerosol (SOA) reported from the oxidation of BVOCs in laboratory chamber studies, providing evidence that the magnitude and chemical composition of biogenic SOA simulated in the laboratory is similar to that found in actual atmospheric conditions. The biogenic factor OM is also correlated to dust elements, indicating that dust may act as a non-acidic SOA sink. This role is supported by the organic functional group composition and morphology of single particles, which were analyzed by scanning transmission X-ray microscopy near edge X-ray absorption fine structure (STXM-NEXAFS).

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 Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 2: Spatiotemporal Trends

2021 ◽  
Author(s):  
Alexandra J. Boris ◽  
Satoshi Takahama ◽  
Andrew T. Weakley ◽  
Bruno M. Debus ◽  
Stephanie L. Shaw ◽  
...  
Keyword(s):  
Organic Matter ◽  
Carboxylic Acid ◽  
Functional Groups ◽  
Prescribed Burning ◽  
Functional Group ◽  
Aerosol Composition ◽  
Ir Spectrometry ◽  
Spatiotemporal Trends ◽  
Routine Monitoring ◽  
Ft Ir

Abstract. Organic species within atmospheric particles vary widely in molecular structure. The variety of molecules that comprise the aerosol make it rich in information about its sources and chemical lifecycle but also make particulate organic matter (OM) difficult to characterize and quantify. In Part 1 of this pair of papers, we described a direct method for measuring the composition and concentration of OM in aerosol samples that is compatible with routine monitoring of air quality. This method uses Fourier Transform Infrared (FT-IR) spectrometry of filter-based aerosol samples to quantify bonds, or functional groups, that represent the majority of organic composition; summation of these functional groups gives OM. In this paper, functional group composition and OM concentrations are directly measured in eight years of aerosol samples collected at two rural and two urban sites in the Southeastern Aerosol Research and Characterization (SEARCH) network. FT-IR spectrometry with a multivariate calibration is used to quantify the concentrations of aliphatic C-H (aCH), carboxylic acid (COOH), oxalate (oxOCO; representing carboxylates), non-acid and non-oxalate carbonyl (naCO), and alcohol O-H (aCOH) in approximately 3500 filter samples collected every third day from 2009 through 2016. In addition, measurements are made on samples from all days in 2016. A decline in the total OM is observed from 2011 to 2016 that is caused by decreases in the more oxygenated functional groups (carboxylic acid and oxalate) and is attributed to anthropogenic SO2 and/or volatile organic compound (VOC) emissions reductions. The trend in OM composition is consistent with those observed using more time- and labor-intensive analytical techniques. Concurrently, the fractional contributions of aCOH and naCO to OM increased, which might be linked to monoterpene-derived secondary OM, with possible influences from decreasing NOx and/or increasing O3 concentrations. In addition, this work demonstrates that OM to organic carbon (OM / OC) ratios in the Southeast U.S. (SE U.S.) did not appreciably change over the study time period, as a result of these competing functional group contributions to OM. Monthly observations support the sources suggested by these overall trends, including strong biogenic and photo-oxidation influences, while daily samples from 2016 further elucidate the consistent impact of meteorology and biomass burning events on shorter term OM variability, including prescribed burning in the winter/spring and wildfires in the autumn. These shorter-term and spatial observations thus reinforce the results of the broader dataset and serve to evaluate the applicability of FT-IR spectrometry measurement to trends analysis on various timescales relevant to routine monitoring of aerosol composition.

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

2010 ◽  
Vol 10 (4) ◽  
pp. 9253-9289
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 being investigated using a recently developed analytical approach based on atmospheric pressure chemical ionisation-tandem mass spectrometry (APCI-MS/MS). The determinations of the three functional groups' contents are performed quantitatively by neutral loss (carboxylic and carbonyl groups) and precursor ion (nitro groups) 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 photo-oxidation 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 accounted for 1.7% (vehicular) to 13.5% (o-xylene photo-oxidation) of the organic carbon. The diagnostic functional group ratios are then used to tentatively differentiate 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 distinguish the 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 assesses 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 the OA characterisation are discussed.

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 Fog scavenging of organic and inorganic aerosol in the Po Valley

2014 ◽  
Vol 14 (4) ◽  
pp. 4787-4826 ◽  
Author(s):  
S. Gilardoni ◽  
P. Massoli ◽  
L. Giulianelli ◽  
M. Rinaldi ◽  
M. Paglione ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Black Carbon ◽  
Functional Group ◽  
Group Composition ◽  
Organic Aerosol ◽  
Water Soluble ◽  
Carbonaceous Aerosol ◽  
Model Description ◽  
Po Valley ◽  
Scavenging Efficiency

Abstract. The interaction of aerosol with atmospheric water affects the processing and wet removal of atmospheric particles. Understanding such interaction is mandatory to improve model description of aerosol lifetime and ageing. We analyzed the aerosol-water interaction at high relative humidity during fog events in the Po Valley, in the framework of the ARPA-ER Supersite project. For the first time in this area, the changes in particle chemical composition caused by fog are discussed along with changes in particle microphysics. During the experiment, 14 fog events were observed. The average mass scavenging efficiency was 70% for nitrate, 68% for ammonium, 61% for sulfate, 50% for organics, and 39% for black carbon. After fog formation, the interstitial aerosol was dominated by particles smaller than 200 nm Dva (vacuum aerodynamic diameter) and enriched in carbonaceous aerosol, mainly black carbon and water insoluble organic aerosol (WIOA). For each fog event, the size segregated scavenging efficiency of nitrate and organic aerosol (OA) was calculated by comparing chemical species size distribution before and after fog formation. For both nitrate and OA, the size segregated scavenging efficiency followed a sigmoidal curve, with values close to zero below 100 nm Dva and close to 1 above 700 nm Dva. OA was able to affect scavenging efficiency of nitrate in particles smaller than 300 nm Dva. A linear correlation between nitrate scavenging and particle hygroscopicity (κ) was observed, indicating that 44–51% of the variability of nitrate scavenging in smaller particles (below 300 nm Dva) was explained by changes in particle chemical composition. The size segregated scavenging curves of OA followed those of nitrate, suggesting that organic scavenging was controlled by mixing with water-soluble species. In particular, functional group composition and OA elemental analysis indicated that more oxidized OA was scavenged more efficiently than less oxidized OA. Nevertheless, the small variability of organic functional group composition during the experiment did not allow us to discriminate the effect of different organic functionalities on OA scavenging.

scholarly journals Constructing a data-driven receptor model for organic and inorganic aerosol – a synthesis analysis of eight mass spectrometric data sets from a boreal forest site

2019 ◽  
Vol 19 (6) ◽  
pp. 3645-3672 ◽  
Author(s):  
Mikko Äijälä ◽  
Kaspar R. Daellenbach ◽  
Francesco Canonaco ◽  
Liine Heikkinen ◽  
Heikki Junninen ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Organic Aerosol ◽  
Mass Spectrometric ◽  
Chemical Components ◽  
Forest Site ◽  
Aerosol Composition ◽  
Mass Spectrometric Data ◽  
Spectrometric Data ◽  
Aerosol Mass ◽  
Inorganic Aerosol

Abstract. The interactions between organic and inorganic aerosol chemical components are integral to understanding and modelling climate and health-relevant aerosol physicochemical properties, such as volatility, hygroscopicity, light scattering and toxicity. This study presents a synthesis analysis for eight data sets, of non-refractory aerosol composition, measured at a boreal forest site. The measurements, performed with an aerosol mass spectrometer, cover in total around 9 months over the course of 3 years. In our statistical analysis, we use the complete organic and inorganic unit-resolution mass spectra, as opposed to the more common approach of only including the organic fraction. The analysis is based on iterative, combined use of (1) data reduction, (2) classification and (3) scaling tools, producing a data-driven chemical mass balance type of model capable of describing site-specific aerosol composition. The receptor model we constructed was able to explain 83±8 % of variation in data, which increased to 96±3 % when signals from low signal-to-noise variables were not considered. The resulting interpretation of an extensive set of aerosol mass spectrometric data infers seven distinct aerosol chemical components for a rural boreal forest site: ammonium sulfate (35±7 % of mass), low and semi-volatile oxidised organic aerosols (27±8 % and 12±7 %), biomass burning organic aerosol (11±7 %), a nitrate-containing organic aerosol type (7±2 %), ammonium nitrate (5±2 %), and hydrocarbon-like organic aerosol (3±1 %). Some of the additionally observed, rare outlier aerosol types likely emerge due to surface ionisation effects and likely represent amine compounds from an unknown source and alkaline metals from emissions of a nearby district heating plant. Compared to traditional, ion-balance-based inorganics apportionment schemes for aerosol mass spectrometer data, our statistics-based method provides an improved, more robust approach, yielding readily useful information for the modelling of submicron atmospheric aerosols physical and chemical properties. The results also shed light on the division between organic and inorganic aerosol types and dynamics of salt formation in aerosol. Equally importantly, the combined methodology exemplifies an iterative analysis, using consequent analysis steps by a combination of statistical methods. Such an approach offers new ways to home in on physicochemically sensible solutions with minimal need for a priori information or analyst interference. We therefore suggest that similar statistics-based approaches offer significant potential for un- or semi-supervised machine-learning applications in future analyses of aerosol mass spectrometric data.

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).

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