Dataset Information

Intercomparison Between Surrogate, Explicit, and Full Treatments of VSL Bromine Chemistry Within the CAM-Chem Chemistry-Climate Model.

ABSTRACT: Many Chemistry-Climate Models (CCMs) include a simplified treatment of brominated very short-lived (VSL^Br) species by assuming CH₃Br as a surrogate for VSL^Br. However, neglecting a comprehensive treatment of VSL^Br in CCMs may yield an unrealistic representation of the associated impacts. Here, we use the Community Atmospheric Model with Chemistry (CAM-Chem) CCM to quantify the tropospheric and stratospheric changes between various VSL^Br chemical approaches with increasing degrees of complexity (i.e., surrogate, explicit, and full). Our CAM-Chem results highlight the improved accuracy achieved by considering a detailed treatment of VSL^Br photochemistry, including sea-salt aerosol dehalogenation and heterogeneous recycling on ice-crystals. Differences between the full and surrogate schemes maximize in the lowermost stratosphere and midlatitude free troposphere, resulting in a latitudinally dependent reduction of ∼1-7 DU in total ozone column and a ∼5%-15% decrease of the OH/HO₂ ratio. We encourage all CCMs to include a complete chemical treatment of VSL^Br in the troposphere and stratosphere.

SUBMITTER: Fernandez RP

PROVIDER: S-EPMC7988532 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Intercomparison Between Surrogate, Explicit, and Full Treatments of VSL Bromine Chemistry Within the CAM-Chem Chemistry-Climate Model.

Fernandez Rafael P RP Barrera Javier A JA López-Noreña Ana Isabel AI Kinnison Douglas E DE Nicely Julie J Salawitch Ross J RJ Wales Pamela A PA Toselli Beatriz M BM Tilmes Simone S Lamarque Jean-François JF Cuevas Carlos A CA Saiz-Lopez Alfonso A

Geophysical research letters 20210223 4

Many Chemistry-Climate Models (CCMs) include a simplified treatment of brominated very short-lived (VSLBr) species by assuming CH3Br as a surrogate for VSLBr. However, neglecting a comprehensive treatment of VSLBr in CCMs may yield an unrealistic representation of the associated impacts. Here, we use the Community Atmospheric Model with Chemistry (CAM-Chem) CCM to quantify the tropospheric and stratospheric changes between various VSLBr chem ...[more]

PMID: 33776160

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Project description:Abstract The automatic recognition of chemical names and their corresponding database identifiers in biomedical text is an important first step for many downstream text-mining applications. The task is even more challenging when considering the identification of these entities in the article’s full text and, furthermore, the identification of candidate substances for that article’s metadata [Medical Subject Heading (MeSH) article indexing]. The National Library of Medicine (NLM)-Chem track at BioCreative VII aimed to foster the development of algorithms that can predict with high quality the chemical entities in the biomedical literature and further identify the chemical substances that are candidates for article indexing. As a result of this challenge, the NLM-Chem track produced two comprehensive, manually curated corpora annotated with chemical entities and indexed with chemical substances: the chemical identification corpus and the chemical indexing corpus. The NLM-Chem BioCreative VII (NLM-Chem-BC7) Chemical Identification corpus consists of 204 full-text PubMed Central (PMC) articles, fully annotated for chemical entities by 12 NLM indexers for both span (i.e. named entity recognition) and normalization (i.e. entity linking) using MeSH. This resource was used for the training and testing of the Chemical Identification task to evaluate the accuracy of algorithms in predicting chemicals mentioned in recently published full-text articles. The NLM-Chem-BC7 Chemical Indexing corpus consists of 1333 recently published PMC articles, equipped with chemical substance indexing by manual experts at the NLM. This resource was used for the evaluation of the Chemical Indexing task, which evaluated the accuracy of algorithms in predicting the chemicals that should be indexed, i.e. appear in the listing of MeSH terms for the document. This set was further enriched after the challenge in two ways: (i) 11 NLM indexers manually verified each of the candidate terms appearing in the prediction results of the challenge participants, but not in the MeSH indexing, and the chemical indexing terms appearing in the MeSH indexing list, but not in the prediction results, and (ii) the challenge organizers algorithmically merged the chemical entity annotations in the full text for all predicted chemical entities and used a statistical approach to keep those with the highest degree of confidence. As a result, the NLM-Chem-BC7 Chemical Indexing corpus is a gold-standard corpus for chemical indexing of journal articles and a silver-standard corpus for chemical entity identification in full-text journal articles. Together, these resources are currently the most comprehensive resources for chemical entity recognition, and we demonstrate improvements in the chemical entity recognition algorithms. We detail the characteristics of these novel resources and make them available for the community. Database URL: https://ftp.ncbi.nlm.nih.gov/pub/lu/NLM-Chem-BC7-corpus/

Dataset Information

Intercomparison Between Surrogate, Explicit, and Full Treatments of VSL Bromine Chemistry Within the CAM-Chem Chemistry-Climate Model.

Publications

Intercomparison Between Surrogate, Explicit, and Full Treatments of VSL Bromine Chemistry Within the CAM-Chem Chemistry-Climate Model.

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