Knowledge of the molecular-level chemistry of brown carbon (BrC) is important in reducing the uncertainties in aerosol radiative forcing. Time-resolved ambient PM 2.5 samples were collected during a severe pollution episode in January 2017 over Xi'an, China for a comprehensive nontarget and full scanning of BrC molecules and their absorption properties using electrospray ionization Fourier transform-ion cyclotron resonance mass spectrometry combined with partial least squares regression analysis, which apportioned the overall ultraviolet absorption to individual molecules. The estimated absorption of CHNO and CHNOS molecules exhibited nighttime prevalence, whereas CHOS, CHNS, CHN, CHO, CHS, and CH molecules presented a dynamic trend. Carbon conjugation was positively correlated with estimated absorption by CHO and CHNO molecules, while exhibiting a mixed relationship with CHNOS. Higher nitrogen content was associated with enhanced light-absorption properties of BrC molecules, while higher oxygen and sulfur content appeared to be associated with photobleaching during secondary transformation.Plain Language Summary Individual molecular absorption has significant implications for ambient brown carbon analysis, but existing studies mostly focused on bulk absorption properties for the sample as a whole. A novel method is presented here to evaluate individual brown carbon absorption at the molecular level through high resolution mass spectrometry, and partial least squares regression analysis was applied to PM 2.5 samples collected during a heavy pollution episode in Xi'an, China. Nitrogen-containing compounds were found to be the strongest contributor to brown carbon absorption, especially during the nighttime, while processes involving oxidation and sulfur addition appeared to weaken the molecular absorption. This study bridges the gap between real atmospheric PM 2.5 absorption and knowledge from controlled laboratory studies, which support these findings.
Abstract. 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.
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