Oxygenated organic functional groups and their sources in single and submicron organic particles in MILAGRO 2006 campaign

Fourier Transform Infrared (FTIR) and X-ray Fluorescence (XRF) were used to measure organic functional groups and elements of submicron particles collected during MILAGRO in March 2006 on three platforms: the Mexico City urban area (SIMAT), the high altitude site at 4010 m (Altzomoni), and the NCAR C130 aircraft. Scanning Transmission X-ray Microscopy (STXM) and Near-Edge X-ray Absorption Fine Structure (NEXAFS) were applied to single particle organic functional group abundance analysis of particles simultaneously collected at SIMAT and C130. Correlations of elemental concentrations showed different groups of source-related elements at SIMAT, Altzomoni, and C130, suggesting different processes affecting the air masses sampled at the three platforms. Cluster analysis resulted in seven distinct clusters of FTIR spectra, with the last three clusters consisting of spectra collected almost exclusively on the C130 platform, reflecting the variety of sources contributing to C130 samples. Positive Matrix Factorization (PMF) of STXM-NEXAFS spectra identified three main factors representing soot, secondary, and biomass burning type spectra. PMF of FTIR spectra resulted in two fossil fuel combustion factors and one biomass burning factor, the former representative of source regions to the northeast and southwest of SIMAT. Alkane, carboxylic acid, amine, and alcohol functional groups were mainly associated with combustion related sources, while non-acid carbonyl groups were likely from biomass burning events. The majority of OM and O/C was attributed to combustion sources, although no distinction between direct emissions and atmospherically processed OM could be identified

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

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 (R-2; 0.96), low bias (0.02 mu g m(-3), the nominal IMPROVE sample volume is 32.8 m(3)), low error (0.08 mu g 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)

An open platform for Aerosol InfraRed Spectroscopy analysis – AIRSpec

AIRSpec is a platform consisting of several chemometric packages developed for analysis of Fourier transform infrared (FTIR) spectra of atmospheric aerosols. The packages are accessible through a browser-based interface, which also generates the necessary input files based on user interactions for provenance management and subsequent use with a command-line interface. The current implementation includes the task of baseline correction, organic functional group (FG) analysis, and multivariate calibration for any analyte with absorption in the mid-infrared. The baseline correction package uses smoothing splines to correct the drift of the baseline of ambient aerosol spectra given the variability in both environmental mixture composition and substrates. The FG analysis is performed by fitting individual Gaussian line shapes for alcohol (aCOH), carboxylic acid (COOH), alkane (aCH), carbonyl (CO), primary amine (aNH2), and ammonium (ammNH) for each spectrum. The multivariate calibration model uses the spectra to estimate the concentration of relevant target variables (e.g., organic or elemental carbon) measured with different reference instruments. In each of these analyses, AIRSpec receives spectra and user choices on parameters for model computation; input files with parameters that can later be used with a command-line interface for batch computation are returned together with diagnostic figures and tables in text format. AIRSpec is built using the open-source software consisting of R and Shiny and is released under the GNU Public License v3. Users can download, modify, and extend the package, or access its functionality through the web application (http://airspec.epfl.ch, last access: 3 April 2019) hosted at the École polytechnique fédérale de Lausanne (EPFL). AIRSpec provides a unified framework by which different chemometric techniques can be shared and accessed, and its underlying suite of packages provides the basic functionality for extending the platform with new types of analyses. For example, basic functionality includes operations for populating and accessing spectra residing in in-memory arrays or relational databases, input and output of spectra and results of computation, and user interface development. Moreover, AIRSpec facilitates the exploratory work, can be used by FTIR spectra acquired with different methods, and can be extended easily with new chemometric packages when they become available. Therefore AIRSpec provides a framework for centralizing and disseminating such algorithms. This paper describes the modular architecture and provides examples of the implemented packages using the spectra of aerosol samples collected on PM2.5 polytetrafluoroethylene (Teflon) filters.</p

Chemical evolution of primary and formation of secondary biomass burning aerosols during daytime and nighttime

Organic matter (OM) can constitute more than half of fine particulate matter (PM) and affect climate and human health. Natural and man-made biomass burning is an important contributor to primary and secondary OM (POA and SOA) with an increasing trend. Aerosol mass spectrometry (AMS) and Fourier transform infrared spectroscopy (FTIR) are two complementary methods of identifying the complex chemical composition of OM in terms of mass fragments and functional groups, respectively. AMS offers a relatively higher temporal resolution compared to FTIR (performed on PTFE filters). However, the interpretation of AMS mass spectra remains complicated due to the extensive molecular fragmentation. In this study, we used collocated AMS and FTIR measurements to better understand the evolution of biomass burning POA and SOA due to different mechanisms of chemical aging (e.g., homogeneous gasphase oxidation and heterogeneous reactions). Primary emissions from wood and pellet stoves were injected into a 10 m3 environmental chamber located at the Center for Studies of Air Qualities and Climate Change (CSTACC) at ICE-HT/FORTH. Primary emissions were aged using hydroxyl and nitrate radicals with atmospherically relevant exposures. PM1 was analyzed by a highresolution time-of-flight (HR-ToF) and was also collected on PTFE filters over 20-minute periods before and after aging for off-line FTIR analysis. AMS and FTIR measurements agreed well with regards to the concentration of OM and some biomass burning tracers (levoglucosan and lignin; Yazdani A., 2020b) and the OM:OC ratio. Chamber wall loss rates were estimated using AMS OM concentration and were used to split the contribution of POA and SOA. The estimated FTIR and AMS spectra of SOA produced by reactions of biomass burning volatile organic compounds (VOCs) with OH were found to have prominent acid signatures. Organonitrates, on the other hand, appeared to be important for SOA produced by the nitrate radical. We found that with continued aging, SOA evolves and becomes similar to the oxygenated OA (OOA) in the atmosphere. We also found that POA composition also evolves with aging. Our estimates show that up to 10 % of POA mass undergoes aging. Biomass burning tracers such as lignin and levoglucosan in addition to hydrocarbons are among the POA compounds that are lost the most in biomass burning POA (up to 6 times more than OM decrease due to chamber wall losses; Fig. 1). This diminution is observed for both semi-volatile (levoglucosan and hydrocarbons) and non-volatile (lignin) POA species, implying the importance of gasparticle partitioning, heterogeneous reactions, and photolysis for POA evolution in the atmosphere. This result can be important since chemical transport models usually do not consider POA heterogeneous reactions. Figure 1. Trends of individual AMS mass fragments (with contribution to OM&gt; 0.3 %) during aging with UV (starting from time zero). All mass fragments have been normalized by their concentration before the with start of aging and corrected for the chamber wall losses. Important mass fragments are shown in color. This work was supported by the project PyroTRACH (ERC- 2016-COG) funded from H2020-EU.1.1. - Excellent Science - European Research Council (ERC), project ID 726165 and funding from the Swiss National Science Foundation (200021_172923). References Yazdani, A., Dudani, N., Takahama, S., Bertrand, A., Prévôt, A. S. H., El Haddad, I., and Dillner, A. M.: Characterization of Primary and Aged Wood Burning and Coal Combustion Organic Aerosols in Environmental Chamber and Its Implications for Atmospheric Aerosols, Atmospheric Chemistry and Physics Discussions, pp. 1– 32

Differentiating between primary and secondary organic aerosols of biomass burning in an environmental chamber with FTIR and AMS

Fine particulate matter (PM) affects visibility, climate and public health. Organic matter (OM), which is hard to characterize due to its complex chemical composition, can constitute more than half of the PM. Biomass burning from residential wood burning, wildfires, and prescribed burning is a major source of OM with an ever-increasing importance. Aerosol mass spectrometry (AMS) and Fourier transform infrared spectroscopy (FTIR) are two complementary methods of identifying the chemical composition of OM. AMS measures the bulk composition of OM with relatively high temporal resolution but provides limited parent compound information. FTIR, carried out on samples collected on Teflon filters, provides detailed functional groupinformation at the expense of relatively low temporal resolution. In this study, we used these two methods to better understand the evolution of biomass burning OM in the atmosphere with aging. For this purpose, primary emissions from wood and pellet stoves were injected into the Center for Studies of Air Qualities and Climate Change (C-STACC) environmental chamber at ICE-HT/FORTH. Primary emissions were aged using hydroxyl and nitrate radicals (with atmospherically relevant exposures) simulating atmospheric day-time and night-time oxidation. A time-of-flight (ToF) AMS reported the composition of non-refractory PM1 every three minutes and PM1 was collected on PTFE filters over 20-minute periods before and after aging for off-line FTIR analysis. We found that AMS and FTIR measurements agreed well in terms of measured OM mass concentration, the OM:OC ratio, and concentration of biomass burning tracers – lignin and levoglucosan. AMS OM concentration was used to estimate chamber wall loss rates which were then used separate the contribution of primary and secondary organic aerosols (POA and SOA) to the aged OM. AMS mass spectra and FTIR spectra of biomass burning SOA and estimates of bulk composition were obtained by this procedure. FTIR and AMS spectra of SOA produced by OH oxidation of biomass burning volatile organic compounds (VOCs) were dominated by acid signatures. Organonitrates, on the other hand, appeared to be important in the SOA aged by the nitrate radical. The spectra from the two instruments also indicated that the signatures of certain compounds such as levoglucosan, lignin and hydrocarbons, which are abundant in biomass burning POA, diminish with aging significantly more than what can be attributed to chamber wall losses. The latter suggests biomass burning POA chemical composition might change noticeably due to heterogeneous reactions or partitioning in the atmosphere. Therefore, the common assumption of stable POA composition is only partially true. In addition, more stable biomass burning tracers should be used to be able to identify highly aged biomass burning aerosols in the atmosphere

Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: systematic intercomparison of calibration methods for US measurement network samples

Peak fitting (PF) and partial least squares (PLS) regression have been independently developed for estimation of functional groups (FGs) from Fourier transform infrared (FTIR) spectra of ambient aerosol collected on Teflon filters. PF is a model that quantifies the functional group composition of the ambient samples by fitting individual Gaussian line shapes to the aerosol spectra. PLS is a data-driven, statistical model calibrated to laboratory standards of relevant compounds and then extrapolated to ambient spectra. In this work, we compare the FG quantification using the most widely used implementations of PF and PLS, including their model parameters, and also perform a comparison when the underlying laboratory standards and spectral processing are harmonized. We evaluate the quantification of organic FGs (alcohol COH, carboxylic COOH, alkane CH, carbonyl CO) and ammonium, using external measurements (organic carbon (OC) measured by thermal optical reflectance (TOR) and ammonium by balance of sulfate and nitrate measured by ion chromatography). We evaluate our predictions using 794 samples collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA) in 2011 and 238 laboratory standards from Ruthenburg et al. (2014) (available at https://doi.org/10.1016/j.atmosenv.2013.12.034). Each model shows different biases. Overall, estimates of OC by FTIR show high correlation with TOR OC. However, PLS applied to unprocessed (raw spectra) appears to underpredict oxygenated functional groups in rural samples, while other models appear to underestimate aliphatic CH bonds and OC in urban samples. It is possible to adjust model parameters (absorption coefficients for PF and number of latent variables for PLS) within limits consistent with calibration data to reduce these biases, but this analysis reveals that further progress in parameter selection is required. In addition, we find that the influence of scattering and anomalous transmittance of infrared in coarse particle samples can lead to predictions of OC by FTIR which are inconsistent with TOR OC. We also find through several means that most of the quantified carbonyl is likely associated with carboxylic groups rather than ketones or esters. In evaluating state-of-the-art methods for FG abundance by FTIR, we suggest directions for future research.</p

Chemical evolution of primary and secondary biomass burning aerosols during daytime and nighttime

Primary emissions from wood and pellet stoves were aged in an atmospheric simulation chamber under daytime and nighttime conditions. The aerosol was analyzed with the online Aerosol Mass Spectrometer (AMS) and offline Fourier transform infrared spectroscopy (FTIR). Measurements using the two techniques agreed reasonably well in terms of the organic aerosol (OA) mass concentration, OA:OC trends, and concentrations of biomass burning markers – lignin-like compounds and anhydrosugars. Based on the AMS, around 15 % of the primary organic aerosol (POA) mass underwent some form of transformation during daytime oxidation conditions after 6–10 hours of atmospheric exposure. A lesser extent of transformation was observed during the nighttime oxidation. The decay of certain semi-volatile (e.g., levoglucosan) and less volatile (e.g., lignin-like) POA components was substantial during aging, highlighting the role of heterogeneous reactions and gas-particle partitioning. Lignin-like compounds were observed to degrade under both daytime and nighttime conditions, whereas anhydrosugars degraded only under daytime conditions. Among the marker mass fragments of primary biomass burning OA (bbPOA), heavy ones (higher m/z) were relatively more stable during aging. The biomass burning secondary OA (bbSOA) became more oxidized with continued aging and resembled those of aged atmospheric organic aerosols. The bbSOA formed during daytime oxidation was dominated by acids. Organonitrates were an important product of nighttime reactions in both humid and dry conditions. Our results underline the importance of changes to both the primary and secondary biomass burning aerosols during their atmospheric aging. Heavier AMS fragments seldomly used in atmospheric chemistry can be used as more stable tracers of bbPOA and in combination with the established levoglucosan marker, can provide an indication of the extent of bbPOA aging

Classification of Multiple Types of Organic Carbon Composition in Atmospheric Particles by Scanning Transmission X-Ray Microscopy Analysis

A scanning transmission X-ray microscope at the Lawrence Berkeley National Laboratory is used to measure organic functional group abundance and morphology of atmospheric aerosols. We present a summary of spectra, sizes, and shapes observed in 595 particles that were collected and analyzed between 2000 and 2006. These particles ranged between 0.1 and 12 mm and represent aerosols found in a large range of geographical areas, altitudes, and times. They include samples from seven different field campaigns: PELTI, ACE-ASIA, DYCOMS II, Princeton, MILAGRO (urban), MILAGRO (C-130), and INTEX-B. At least 14 different classes of organic particles show different types of spectroscopic signatures. Different particle types are found within the same region while the same particle types are also found in different geographical domains. Particles chemically resembling black carbon, humic-like aerosols, pine ultisol, and secondary or processed aerosol have been identified from functional group abundance and comparison of spectra with those published in the literature