Mexico City aerosol analysis during MILAGRO using high resolution aerosol mass spectrometry at the urban supersite (T0) – Part 2: Analysis of the biomass burning contribution and the modern carbon fraction
Notice bibliographique
Résumé
Abstract. Submicron aerosol was analyzed during the MILAGRO field campaign in March 2006 at the T0 urban supersite in Mexico City with a High-Resolution Aerosol Mass Spectrometer (AMS) and complementary instrumentation. Positive Matrix Factorization (PMF) of high resolution AMS spectra identified a biomass burning OA (BBOA) component, which includes several large plumes that appear to be from forest fires within the region. Here, we show that the AMS BBOA concentration at T0 correlates with fire counts in the vicinity of Mexico City and that most of the BBOA variability is captured when the FLEXPART model is used for the dispersion of fire emissions as estimated from satellite fire counts. The resulting FLEXPART fire impact index correlates well with the observed BBOA, CH3CN, levoglucosan, and potassium, indicating that wildfires in the region surrounding Mexico City are the dominant source of BBOA at T0 during MILAGRO. The impact of distant BB sources such as the Yucatan is small during this period. All fire tracers are correlated, with BBOA and levoglucosan showing little background, acetonitrile having a well-known tropospheric background of ~100–150 ppt, and PM2.5 potassium having a background of ~160 ng m−3 (two-thirds of its average concentration), which does not appear to be related to BB sources. We define two high fire periods based on satellite fire counts and predicted fire impacts. We then compare these periods with a low fire period when the impact of regional fires is about a factor of 5 smaller. Fire tracers are very elevated in the high fire periods whereas tracers of urban pollution do not change between these periods. Dust is also elevated during the high BB period but this appears to be coincidental due to the drier conditions and not driven by direct dust emission from the fires. The AMS oxygenated OA factor (OOA, mostly secondary OA or SOA) does not show an increase during the fire periods or a correlation with fire counts, FLEXPART-predicted fire impacts or fire tracers, indicating that it is dominated by urban and/or regional sources and not by the fires near the MCMA. A new 14C aerosol dataset is presented. Both this new and a previously published dataset of 14C analysis suggest a similar BBOA contribution as the AMS and chemical mass balance (CMB), resulting in 15% higher modern carbon during the high vs. low regional fire periods. The new dataset has ~15% more fossil carbon on average than the previously published one, and possible reasons for this discrepancy are discussed. During the low regional fire period, 37% of organic carbon (OC) and 30% total carbon (TC) are from modern sources, suggesting the importance of urban and regional modern carbon sources other than the fires, such as food cooking and regional biogenic SOA. Overall, the fires from the region near the MCMA are estimated to contribute 15–23% of the OA and 7–9% of the fine PM at T0 during MILAGRO, and 2–3% of the fine PM as an annual average. The 2006 MCMA emissions inventory contains a substantially lower impact of the forest fire emissions, although a fraction of these emissions occur just outside of the MCMA inventory area. The ambient BBOA/ΔCH3CN ratio is much higher in the afternoon when the wildfires are most intense than during the rest of the day, which may explain some disagreements between BB impacts from afternoon aircraft flights and those from 24-h ground measurements. Finally, we show that there are large differences in the contributions of the different OA components to the surface concentrations vs. the integrated column amounts.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».