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 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 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 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 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 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 Hydrocarbon-like and oxygenated organic aerosols in Pittsburgh: insights into sources and processes of organic aerosols

2005 ◽  
Vol 5 (5) ◽  
pp. 8421-8471 ◽  
Author(s):  
Q. Zhang ◽  
D. R. Worsnop ◽  
M. R. Canagaratna ◽  
J.-L. Jimenez
Keyword(s):  
Organic Carbon ◽  
Mass Spectra ◽  
Organic Aerosols ◽  
Organic Aerosol ◽  
Particle Formation ◽  
Total Carbon ◽  
New Particle Formation ◽  
Aerosol Mass ◽  
Diurnal Profile ◽  
Mass Concentrations

Abstract. A recently developed algorithm (Zhang et al., 2005) has been applied to deconvolve the mass spectra of organic aerosols acquired with the Aerosol Mass Spectrometer (AMS) in Pittsburgh during September 2002. The results are used here to characterize the mass concentrations, size distributions, and mass spectra of hydrocarbon-like and oxygenated organic aerosol (HOA and OOA, respectively). HOA accounts for 34% of the measured organic aerosol mass and OOA accounts for 66%. The mass concentrations of HOA demonstrate a prominent diurnal profile that peaks in the morning during the rush hour and decreases with the rise of the boundary layer. The diurnal profile of OOA is relatively flat and resembles those of SO42− and NH4+. The size distribution of HOA shows a distinct ultrafine mode that is commonly associated with fresh emissions while OOA is generally concentrated in the accumulation mode and appears to be mostly internally mixed with the inorganic ions, such as SO42− and NH4+. These observations suggest that HOA is likely primary aerosol from local, combustion-related emissions and that OOA is secondary organic aerosol (SOA) influenced by regional contributions. There is strong evidence of the direct correspondence of OOA to SOA during an intense new particle formation and growth event, when condensational growth of OOA was observed. The mass spectrum of OOA of this new particle formation event is very similar to the OOA spectrum of the entire study, which strongly suggests that most OOA during this study is SOA. O3 appears to be a poor indicator for SOA concentration while SO42− is a relatively good surrogate for this dataset. Since the diurnal averages of HOA tightly track those of CO during day time, oxidation/aging of HOA appears to be very small on the time scale of several hours. Based on extracted mass spectra and the likely elemental compositions of major m/z's, the organic mass to organic carbon ratios (OM:OC) of HOA and OOA are estimated at 1.2 and 2.2 μg/μg C, respectively, leading to an average OM:OC ratio of 1.8 for submicron OA in Pittsburgh during September. The C:O ratio of OOA is estimated at 1:0.8. The carbon contents in HOA and OOA calculated accordingly correlate well to primary and secondary organic carbon, respectively, estimated by the OC/EC tracer technique (assuming POC-to-EC ratio=1). In addition, the total carbon concentrations calculated from the AMS data agree well with those measured by the Sunset Laboratory Carbon analyzer (r2=0.87; slope=1.01±0.11).

scholarly journals A Functional Group Oxidation Model (FGOM) for SOA formation and aging

2012 ◽  
Vol 12 (12) ◽  
pp. 32565-32611 ◽  
Author(s):  
X. Zhang ◽  
J. H. Seinfeld
Keyword(s):  
Functional Groups ◽  
Functional Group ◽  
Carbon Number ◽  
Organic Aerosol ◽  
Relative Importance ◽  
Particle Phase ◽  
Carbon Backbone ◽  
Volatile Organic ◽  
Phase Oxidation ◽  
Oxidation Model

Abstract. Secondary organic aerosol (SOA) formation from a volatile organic compound (VOC) involves multiple generations of oxidation that include functionalization and fragmentation of the parent carbon backbone and, likely, particle-phase oxidation and/or accretion reactions. Despite the typical complexity of the detailed molecular mechanism of SOA formation and aging, a relatively small number of functional groups characterize the oxidized molecules that constitute SOA. Given the carbon number and set of functional groups, the volatility of the molecule can be estimated. We present here a Functional Group Oxidation Model (FGOM) that represents the process of SOA formation and aging. The FGOM contains a set of parameters that are to be determined by fitting of the model to laboratory chamber data: total organic aerosol concentration, and O:C and H:C atomic ratios. The sensitivity of the model prediction to variation of the adjustable parameters allows one to assess the relative importance of various pathways involved in SOA formation. An analysis of SOA formation from the high- and low-NOx photooxidation of four C12 alkanes (n-dodecane, 2-methylundecane, hexylcyclohexane, and cyclododecane) using the FGOM is presented, and comparison with the Statistical Oxidation Model (SOM) of Cappa et al. (2012) is discussed.

Sign in / Sign up

Export Citation Format

Share Document