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Enregistrement W3083297161 · doi:10.5194/acp-21-2125-2021

Evaluating the sensitivity of radical chemistry and ozone formation to ambient VOCs and NO <sub> <i>x</i> </sub> in Beijing

2021· article· en· W3083297161 sur OpenAlexaff
Lisa K. Whalley, Eloise J. Slater, Robert Woodward-Massey, Chunxiang Ye, James Lee, Freya Squires, James R. Hopkins, Rachel E. Dunmore, Marvin Shaw, Jacqueline F. Hamilton, Alastair C. Lewis, Archit Mehra, Stephen D. Worrall, Asan Bacak, Thomas J. Bannan, Hugh Coe, Carl J. Percival, Bin Ouyang, R. L. Jones, Leigh R. Crilley, Louisa J. Kramer, William J. Bloss, Tuan V. Vu, Simone Kotthaus, Sue Grimmond, Yele Sun, Weiqi Xu, Siyao Yue, Lujie Ren, W. Joe F. Acton, C. N. Hewitt, Xinming Wang, Pingqing Fu, Dwayne E. Heard

Notice bibliographique

RevueAtmospheric chemistry and physics · 2021
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueAtmospheric chemistry and aerosols
Établissements canadiensYork University
Organismes subventionnairesNatural Environment Research CouncilChinese Academy of SciencesTsinghua UniversityNational Natural Science Foundation of ChinaUniversity of ManchesterSight Research UK
Mots-clésRadicalChemistryReactivity (psychology)OzoneBox modelNOxEnvironmental chemistryMedicinal chemistryPhotochemistryOrganic chemistryMeteorology

Résumé

récupéré en direct d'OpenAlex

Abstract. Measurements of OH, HO2, complex RO2 (alkene- and aromatic-related RO2) and total RO2 radicals taken during the integrated Study of AIR Pollution PROcesses in Beijing (AIRPRO) campaign in central Beijing in the summer of 2017, alongside observations of OH reactivity, are presented. The concentrations of radicals were elevated, with OH reaching up to 2.8×107moleculecm-3, HO2 peaking at 1×109moleculecm-3 and the total RO2 concentration reaching 5.5×109moleculecm-3. OH reactivity (k(OH)) peaked at 89 s−1 during the night, with a minimum during the afternoon of ≈22s-1 on average. An experimental budget analysis, in which the rates of production and destruction of the radicals are compared, highlighted that although the sources and sinks of OH were balanced under high NO concentrations, the OH sinks exceeded the known sources (by 15 ppbv h−1) under the very low NO conditions (&lt;0.5 ppbv) experienced in the afternoons, demonstrating a missing OH source consistent with previous studies under high volatile organic compound (VOC) emissions and low NO loadings. Under the highest NO mixing ratios (104 ppbv), the HO2 production rate exceeded the rate of destruction by ≈50ppbvh-1, whilst the rate of destruction of total RO2 exceeded the production by the same rate, indicating that the net propagation rate of RO2 to HO2 may be substantially slower than assumed. If just 10 % of the RO2 radicals propagate to HO2 upon reaction with NO, the HO2 and RO2 budgets could be closed at high NO, but at low NO this lower RO2 to HO2 propagation rate revealed a missing RO2 sink that was similar in magnitude to the missing OH source. A detailed box model that incorporated the latest Master Chemical Mechanism (MCM3.3.1) reproduced the observed OH concentrations well but over-predicted the observed HO2 under low concentrations of NO (&lt;1 ppbv) and under-predicted RO2 (both the complex RO2 fraction and other RO2 types which we classify as simple RO2) most significantly at the highest NO concentrations. The model also under-predicted the observed k(OH) consistently by ≈10s-1 across all NOx levels, highlighting that the good agreement for OH was fortuitous due to a cancellation of missing OH source and sink terms in its budget. Including heterogeneous loss of HO2 to aerosol surfaces did reduce the modelled HO2 concentrations in line with the observations but only at NO mixing ratios &lt;0.3 ppbv. The inclusion of Cl atoms, formed from the photolysis of nitryl chloride, enhanced the modelled RO2 concentration on several mornings when the Cl atom concentration was calculated to exceed 1×104atomscm-3 and could reconcile the modelled and measured RO2 concentrations at these times. However, on other mornings, when the Cl atom concentration was lower, large under-predictions in total RO2 remained. Furthermore, the inclusion of Cl atom chemistry did not enhance the modelled RO2 beyond the first few hours after sunrise and so was unable to resolve the modelled under-prediction in RO2 observed at other times of the day. Model scenarios, in which missing VOC reactivity was included as an additional reaction that converted OH to RO2, highlighted that the modelled OH, HO2 and RO2 concentrations were sensitive to the choice of RO2 product. The level of modelled to measured agreement for HO2 and RO2 (both complex and simple) could be improved if the missing OH reactivity formed a larger RO2 species that was able to undergo reaction with NO, followed by isomerisation reactions reforming other RO2 species, before eventually generating HO2. In this work an α-pinene-derived RO2 species was used as an example. In this simulation, consistent with the experimental budget analysis, the model underestimated the observed OH, indicating a missing OH source. The model uncertainty, with regards to the types of RO2 species present and the radicals they form upon reaction with NO (HO2 directly or another RO2 species), leads to over an order of magnitude less O3 production calculated from the predicted peroxy radicals than calculated from the observed peroxy radicals at the highest NO concentrations. This demonstrates the rate at which the larger RO2 species propagate to HO2, to another RO2 or indeed to OH needs to be understood to accurately simulate the rate of ozone production in environments such as Beijing, where large multifunctional VOCs are likely present.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,180
Score d'incertitude au seuil0,647

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,228
Écart entre enseignants0,215 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations179
Publié2021
Routes d'admission1
Résumé présentoui

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