Amino acids in Arctic aerosols

Scalabrin, Elisa; Zangrando, Roberta; Barbaro, Elena; Kehrwald, Natalie; Gabrieli, Jacopo; Barbante, Carlo; Gambaro, Andrea

doi:10.5194/acpd-12-17367-2012

Cited by 5 publications

(8 citation statements)

References 42 publications

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“…Interest in AAs in the atmosphere is partly driven by their important roles in enhancing the ice nucleating ability or cloud condensation nuclei ability of atmospheric particles (Chan et al, ; Szyrmer & Zawadzki, ), which can affect the global climate and the scavenging of air pollutants (Zhang & Anastasio, ). Additionally, AAs may affect the bioavailability of atmospheric organic nitrogen because AAs can be used directly as sources of nitrogen for plants and microorganisms in ecological processes (Mopper & Zika, ; Scalabrin et al, ). Moreover, AAs may influence atmospheric chemistry and the formation of secondary organic aerosols (Bianco et al, ; Haan et al, ; McGregor & Anastasio, ).…”

Section: Introductionmentioning

confidence: 99%

Sources and Transformation Processes of Proteinaceous Matter and Free Amino Acids in PM2.5

et al. 2020

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Amino acids is an important organic nitrogen compound class in aerosol. Its origins and transformation in the atmosphere remain poorly understood. The concentrations of free amino acids (FAAs) and combined amino acids (CAAs) and δ15N values of free and combined Glycine (Gly) in PM2.5 and main emission sources (plant, soil, and aerosol from biomass burning) were investigated from five sampling sites in Nanchang area (Jiangxi Province, China). Our results showed that the composition profiles of CAAs and FAAs were quite different from each other in PM2.5. For CAAs, percentages of individual combined amino acids were different between biomass burning sources and plant or soil sources, and we found that the composition profiles of aerosol CAAs could reflect the contribution of the main emission sources. For FAAs, a predominance of free Gly was observed in aerosol FAAs pool because atmospheric photooxidative processes could increase free Gly and decrease other reactive FAAs. This implied that the composition of aerosol FAAs could not reflect their origins. A strong correlation between δ15NF‐Gly values in aerosols or sources and the δ15NC‐Gly values in their parent CAAs was observed, indicating that the isotope effect associated with Gly transformation in aerosols may be small. Additionally, we found more positive δ15NGly in aerosols emitted by biomass burning, which was likely due to 15N‐depleted amino‐N loss from Gly molecule. The results suggested that δ15NGly values in aerosols might be used to identify biomass burning sources.

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Section: Introductionmentioning

confidence: 99%

Sources and Transformation Processes of Proteinaceous Matter and Free Amino Acids in PM2.5

et al. 2020

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“…Additionally, to gain a more detailed and comprehensive understanding of the suggested surface-assisted desorption/ionization, it is the aim of future work to extend characterization of the energy dependence of the NIR-LDI mechanism to a range of acidic and basic analytes, as well as to other laser wavelengths. Lastly, there is, at present, a limited understanding of the atmospheric aging of nitrogenous organic aerosols due to poor temporal resolution of established off-line methods (Matsumoto and Uematsu 2005;Wedyan and Preston 2008;Miyazaki et al 2011;Scalabrin et al 2012;Laskin et al 2015), underscoring the need for on-line, real-time approaches, such as BP-NIR-LDI-AMS, to complement conventional techniques. Accordingly, BP-NIR-LDI-AMS is being used in conjunction with a custom-built, glass flow reactor to study the heterogenous oxidative processing of PON by ozone, both in the presence and absence of proxies for lipidic, cell-derived materials.…”

Section: Discussionmentioning

confidence: 99%

“…Due to difficulties with fractionation effects in the homogenous nucleation process, namely, the inability to quantify the relative concentrations of multi-component, mixed particles due to differences in analyte vapor pressure, molecular proxies to PON fine-mode particles were generated by pneumatic nebulization of ethanolic solutions of Gly, Ala, Ser, Thr, and Orn. These amino acids have been observed to be abundant in both continental (Zhang and Anastasio 2003) and marine aerosols (Wedyan and Preston 2008;Mandalakis et al 2011;Scalabrin et al 2012), accounting for 37% to 99% of the total amino acid aerosol content. OL, a surrogate for cellular lipidic content that is ubiquitous in the troposphere (Cheng et al 2004;Robinson et al 2006) and is known to form coatings on continental (Tervahattu et al 2005) and marine particulate matter (Tervahattu et al 2002;Kawamura et al 2003), was added to each solution as an internal standard.…”

Section: Aerosol Generationmentioning

confidence: 99%

“…Proteinaceous organic nitrogen (PON), i.e., amino acids and small peptides, presented a logical choice of analyte for these parametric studies, as BP-NIR-LDI-AMS of PON particles, which contain both carboxyl and amine groups, will generate [M¡H] ¡ , [MCH] C , or zwitterionic species, facilitating assessment of the bipolar detection capabilities of the instrument. PON makes a significant contribution to the total nitrogen content in organic aerosols in both continental (Zhang et al 2002a;Zhang and Anastasio 2003;Chan et al 2005;Jaenicke 2005;Laskin et al 2009) and marine regions (Cornell et al 2001;Matsumoto and Uematsu 2005;Wedyan and Preston 2008;Miyazaki et al 2011;Mandalakis et al 2011;Scalabrin et al 2012). It is present in fine-mode particles (i.e., PM 2.5 ) (Cornell et al 2001;Zhang et al 2002a;Zhang and Anastasio 2003), represents a quantitatively substantial component of nitrogen deposition (Duce et al 2008), and is of chief import to biogeochemical nitrogen cycling in terrestrial (Cornell et al 2003;Galloway et al 2008) and aquatic ecosystems (P€ oschl 2005;Duce et al 2008;Miyazaki et al 2011).…”

Section: Introductionmentioning

confidence: 99%

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Characterization of a bipolar near-infrared laser desorption/ionization aerosol mass spectrometer

Kenseth

Petrucci

2016

Aerosol Science and Technology

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A novel method of soft ionization aerosol mass spectrometry (AMS), bipolar near-infrared laser desorption/ionization AMS (BP-NIR-LDI-AMS), has been developed for the on-line, real-time analysis of organic aerosols. Use of a single NIR laser pulse to desorb/ionize aerosols deposited onto an aluminum probe results in minimal analyte fragmentation to produce exclusively intact pseudomolecular ions at [M-H] ¡ for acidic organic analytes and [MCH] C for basic organic analytes. Incorporation of a bipolar mass spectrometer with the NIR-LDI source enables simultaneous detection of acidic and basic species in organic particles. Limits of detection (total particulate mass sampled) for amino acids common to the organic fraction of atmospheric aerosols ranged from 69.1 pg for ornithine to 197 pg for serine on the positive channel, and from 17.0 pg for glycine to 100 pg for ornithine on the negative channel. From studies of the laser energy dependence of the NIR-LDI mechanism, it was found that [M-H] ¡ formation for oleic acid proceeds through simultaneous action of two 1064 nm photons, suggesting a surface-assisted process rather than direct photoionization, for which photon energy is insufficient. For acidic aerosol species, sensitivity was found to increase as a function of analyte acidity, while for basic species, [MCH] C ion signals were detected only in the presence of a labile proton source, with the intensity of the ion signals scaling with the acidity of the proton source. The sensitivity of BP-NIR-LDI-AMS to the amino acids was rationalized in terms of their acidic/basic character, as measured by isoelectric point (pI), with the cationic sensitivity scaling proportionally with pI and the anionic sensitivity scaling inversely with pI.

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“…AAs have been detected in the atmosphere under various contrasted environmental scenarios such as urban area (Barbaro et al, 2011;Di Filippo et al, 2014;Ren et al, 2018;Zhu et al, 2020), background/rural sites (Bianco et al, 2016b;Helin et al, 2017;Samy et al, 2011;Song et al, 2017), marine environment (Mandalakis et al, 2011;Matsumoto and Uematsu, 2005;Triesch et al, 2021;Violaki and Mihalopoulos, 2010) and polar regions (Barbaro et al, 2015;Feltracco et al, 2019;Mashayekhy Rad et al, 2019;Scalabrin et al, 2012). The quantity and type of AAs detected in all the compartments (aerosol particles, cloud water, rainwater) vary over a wide range.…”

Section: Introductionmentioning

confidence: 99%

Free amino acids quantification in cloud water at the puy de Dôme station (France)

Renard¹,

Brissy

Rossi

et al. 2021

Preprint

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Abstract. Eighteen free amino acids (FAAs) were quantified in cloud water sampled at the puy de Dôme station (PUY – France) during 13 cloud events. This quantification has been performed without concentration neither derivatization, using LC-MS and the standard addition method to avoid matrix effects. Total concentrations of FAAs (TCAAs) vary from 1.2 µM to 7.7 µM, Ser (Serine) being the most abundant AA (23.7 % in average) but with elevated standard deviation, followed by Glycine (Gly) (20.5 %), Alanine (Ala) (11.9 %), Asparagine (Asn) (8.7 %), and Leucine/Isoleucine (Leu/I) (6.4 %). The distribution of AAs among the cloud events reveals high variability. TCAA constitutes between 0.5 and 4.4 % of the dissolved organic carbon measured in the cloud samples. AAs quantification in cloud water is scarce but the results agree with the few studies that investigated AAs in this aqueous medium. The environmental variability is assessed through a statistical analysis. This work shows that AAs are correlated with the time spent by the air masses in the boundary layer, especially over the sea surface before reaching the PUY. The cloud microphysical properties fluctuation does not explain the AAs variability in our samples confirming previous studies at PUY. We finally assessed the sources and the atmospheric processes that potentially explain the prevailing presence of certain AAs in the cloud samples. The initial relative distribution of AAs in biological matrices (proteins extracted from bacterial cells or mammalian cells, for example) could explain the dominance of Ala, Gly and Leu/I. AA composition of aquatic organisms (i.e., diatoms species) could also explain the high concentrations of Ser in our samples. The analysis of the AAs hydropathy also indicates a higher contribution of AAs (80 % in average) that are hydrophilic or neutral revealing the fact that other AAs (hydrophobic) are less favorably incorporated into cloud droplets. Finally, the atmospheric aging of AAs has been evaluated by calculating atmospheric lifetimes considering their potential transformation in the cloud medium by biotic or abiotic (mainly oxidation) processes. The most concentrated AAs encountered in our samples present the longest atmospheric lifetimes and the less dominant are clearly efficiently transformed in the atmosphere, potentially explaining their low concentrations. However, this cannot fully explain the relative contribution of several AAs in the cloud samples. This reveals the high complexity of the bio-physico-chemical processes occurring in the multiphasic atmospheric environment.

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Amino acids in Arctic aerosols

Cited by 5 publications

References 42 publications

Sources and Transformation Processes of Proteinaceous Matter and Free Amino Acids in PM2.5

Sources and Transformation Processes of Proteinaceous Matter and Free Amino Acids in PM2.5

Characterization of a bipolar near-infrared laser desorption/ionization aerosol mass spectrometer

Free amino acids quantification in cloud water at the puy de Dôme station (France)

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