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Record W4254070791 · doi:10.5194/acpd-9-24085-2009

Chemical evolution of volatile organic compounds in the outflow of the Mexico City Metropolitan area

2009· preprint· en· W4254070791 on OpenAlexaff
Eric C. Apel, L. K. Emmons, Thomas Karl, F. Flocke, Alan J. Hills, S. Madronich, J. Lee‐Taylor, Alan Fried, P. Weibring, J. Walega, Dirk Richter, Xuexi Tie, L. Mauldin, T. Campos, B. C. Sive, L. I. Kleinman, Stephen Springston, R. A. Zaveri, John Ortega, P. B. Voss, D. R. Blake, A. K. Baker, C. Warneke, D. Welsh-Bon, J. A. de Gouw, J. Zheng, R. Zhang, J. Rudolph, W. Junkermann, D. D. Riemer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsYork University
FundersNational Center for Atmospheric ResearchNational Science Foundation
KeywordsWeather Research and Forecasting ModelMorningDaytimePlumeSunriseAtmospheric sciencesEnvironmental scienceReactivity (psychology)OutflowOzoneMetropolitan areaBoundary layerPlanetary boundary layerVolatile organic compoundDiurnal cycleClimatologyMeteorologyChemistryGeographyGeologyPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract. The volatile organic compound (VOC) distribution in the Mexico City Metropolitan Area (MCMA) and its evolution as it is uplifted and transported out of the MCMA basin was studied during the 2006 MILAGRO/MIRAGE-Mex field campaign. The results show that in the morning hours in the city center, the VOC distribution is dominated by non-methane hydrocarbons (NMHCs) but with a substantial contribution from oxygenated volatile organic compounds (OVOCs), predominantly from primary emissions. Alkanes account for a large part of the NMHC distribution in terms of mixing ratios. In terms of reactivity, NMHCs also dominate overall, especially in the morning hours. However, in the afternoon, as the boundary layer lifts and air is mixed and aged within the basin, the distribution changes as secondary products are formed. The WRF-Chem (Weather Research and Forecasting with Chemistry) model and MOZART (Model for Ozone and Related chemical Tracers) were able to reproduce the general features of the daytime cycle of the VOC OH reactivity distribution showing that NMHCs dominate the distribution except in the afternoon hours and that the VOC OH reactivity peaks in the early morning due to high morning emissions from the city into a shallow boundary layer. The WRF-Chem and MOZART models showed higher reactivity than the experimental data during the nighttime cycle, perhaps indicating problems with the modeled nighttime boundary layer height. In addition, a plume was studied in which air was advected out of the MCMA and intercepted downwind with the DOE G1 on 18~March and the NCAR C130 one day later on 19~March. A number of identical species measured aboard each aircraft gave insight into the chemical evolution of the plume as it aged and was transported as far as 1000 km downwind. Ozone and many OVOCs were photochemically produced in the plume. The WRF-Chem and MOZART models were used to examine the spatial and temporal extent of the 19~March plume and to help interpret the OH reactivity in the downwind plume. The model results generally showed good agreement with experimental results for the total VOC OH reactivity downwind and gave insight into the distributions of VOC chemical classes downwind. A box model with detailed gas phase chemistry (NCAR Master Mechanism), initialized with concentrations observed at one of the ground sites in the MCMA, was used to examine the expected evolution of specific VOCs over a 1–2~day period. The models clearly supported the experimental evidence for NMHC oxidation leading to the formation of OVOCs downwind, which then become the primary fuel for ozone production far away from the MCMA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.214
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2009
Admission routes1
Has abstractyes

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