Abstract
Abstract. An analytical method coupled to multivariate statistical analysis was developed based on transmission-mode direct analysis in real-time quadrupole time-of-flight mass spectrometry (TM-DART-QTOF-MS) to interrogate lipophilic compounds in seawater samples without the need for desalinization. An untargeted metabolomics approach is addressed here as seaomics and was successfully implemented to discriminate the sea surface microlayer (SML) from the underlying water (ULW) samples (n=22, 10 paired samples) collected during a field campaign at the Cabo Verde islands during September–October 2017. A panel of 11 ionic species detected in all samples allowed sample class discrimination by means of supervised multivariate statistical models. Tentative identification of the species enriched in the SML samples suggests that fatty alcohols, halogenated compounds, and oxygenated boron-containing organic compounds are available at the surface for air–water transfer processes. A subset of SML samples (n=5) were subjected to on-site experiments during the campaign by using a lab-to-field approach to test their secondary organic aerosol (SOA) formation potency. The results from these experiments and the analytical seaomics strategy provide a proof of a concept that can be used for an approach to identifying organic molecules involved in aerosol formation processes at the air–water interface.
Highlights
Oceans act as sinks and sources for gases and aerosol particles
Since the maximum data variance in a Principal component analysis (PCA) model is in the direction of the base of the eigenvectors of the covariance matrix, the largest differences are given by seawater samples that are compared to blanks
Results provided by the t-distributed stochastic neighbor embedding (t-SNE) model (Fig. 2b), which is a nonlinear dimensionality reduction technique, were in agreement with those provided by the linear transformation-based technique of PCA and emphasized the reproducibility of the developed analytical method for seawater sample analysis
Summary
Oceans act as sinks and sources for gases and aerosol particles. The ocean surface chemical composition influences the physicochemical processes occurring at the air–water interface by connecting the ocean biogeochemistry with the atmospheric chemistry in the marine boundary layer (MBL; Donaldson and George, 2012). Untargeted metabolomics attempts to cover the broadest range of detectable compounds in a biological system (Viant et al, 2019), in order to subsequently extract chemical patterns or class fingerprints that can allow for sample classification based on metabolite panels without any a priori hypotheses. Secondary organic aerosol formation potency from the SML interfacial photochemical products was explored during the field campaign by using a lab-to-field approach To our knowledge, this is the first study to apply an untargeted TMDART-QTOF-MS-based seaomics analytical strategy coupled to multivariate statistical analysis to investigate the DOM seawater composition
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