Evidence map›Paper›PMID 39514836›Full record

ArticleEnvironmental science & technology2024

Decreasing the Uncertainty in the Comparison of Molecular Fingerprints of Organic Aerosols with H/D Exchange Mass Spectrometry.

Alexander Zherebker, Oliver Babcock, Diana L Pereira, Sara D'Aronco, Daniele Filippi, Lidia Soldà, Vincent Michoud, Aline Gratien, Manuela Cirtog, Christopher Cantrell and 2 more

Abstract read
In one paragraph

Article in Environmental science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Alexander ZherebkerYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom.ORCID 0000-0002-3481-4606
Oliver BabcockYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom.
Diana L PereiraUniversité Paris Cité and Université Paris-Est Créteil, CNRS, LISA, Paris F-75013, France.
Sara D'AroncoYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom.
Daniele FilippiYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom.ORCID 0000-0001-9140-1528
Lidia SoldàDepartment of Chemical Sciences, Università degli Studi di Padova, 35131 Padova, Italy.
Vincent MichoudUniversité Paris Cité and Université Paris-Est Créteil, CNRS, LISA, Paris F-75013, France.
Aline GratienUniversité Paris Cité and Université Paris-Est Créteil, CNRS, LISA, Paris F-75013, France.
Manuela CirtogUniversité Paris Est Creteil and Université Paris Cité, CNRS, LISA, Créteil F-94010, France.
Christopher CantrellUniversité Paris Est Creteil and Université Paris Cité, CNRS, LISA, Créteil F-94010, France.
Paola FormentiUniversité Paris Cité and Université Paris-Est Créteil, CNRS, LISA, Paris F-75013, France.
Chiara GiorioYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom.ORCID 0000-0001-7821-7398

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-resolution mass spectrometry (HRMS) has become an indispensable tool in the characterization of organic aerosols (OA) providing information on air quality, health assessment, climate trends, reactions, and source apportionment. Spectra-derived lists of formulas and their relative abundances are used to compare ambient OA from different sources or to monitor secondary OA formation under controlled laboratory conditions in smog chamber experiments. Various techniques are implemented to visualize common and unique features, series of precursors, and products. The disadvantage of this conventional approach is in associating elemental compositions to specific compounds, while due to several analytical limitations, the structural information remains hidden. We argue that some of the conclusions derived from this data analysis can be misleading. In this study, we applied in-ESI source H/D exchange (HDX), which facilitated enumeration of labile protons in molecules behind elemental compositions of OA. We applied this technique to compare OA from three different locations representing urban, forest, and marine environments and to examine tentative chemical information derived from Kendrick mass defect (KMD) series analysis. Significant discrepancies were found between numbers of labile protons in protogenic functional groups and the stoichiometry of chemical reactions, which are associated with KMD series. Only a portion of chemical pairs matched target stoichiometries, which highlights the existing limitations in environmental applications of conventional formula-based HRMS data interpretation strategies.

Indexed as

AerosolsMass SpectrometryAir PollutantsUncertaintyAerosolsAir Pollutantschemical pairshigh-resolution mass spectrometryisomersKMD serieslabile protonsnontarget analysisstructural descriptor

Identifiers

PMID39514836
PMCPMC11580170

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.