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Record W3205286595

Discerning Trends in Wintertime Reactive Chlorine Chemistry And Air Quality

2020· article· en· W3205286595 on OpenAlexaboutno aff
A. A. Angelucci, Trevor C. VandenBoer, C. Young

Bibliographic record

VenueYork University Digital Library (York University) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality Monitoring and Forecasting
Canadian institutionsnot available
Fundersnot available
KeywordsChlorineAir quality indexChemistryEnvironmental scienceEnvironmental chemistryMeteorologyGeographyOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Reactive chlorine species (Cl*) are crucial to atmospheric chemistry, impacting oxidative cycles, pollutant formation, and air quality. However, their behavior, particularly in urban winter environments, remains underexplored. This thesis investigates the sources, transformations, and impacts of reactive chlorine in urban settings using high-time-resolution measurements, size-resolved aerosol analysis, and advanced modeling techniques. High-time-resolution measurements of hydrogen chloride (HCl) were conducted in coastal (St. John’s, NL) and continental (Toronto, ON) regions. In the coastal environment, HCl variability was influenced by photochemical and acid displacement processes, while in Toronto, direct emissions dominated, with road salting contributing to particulate chloride but not directly to HCl production. Simulations using GEOS-Chem captured coastal variability but significantly underestimated urban HCl levels, indicating the complexity of urban chlorine sources. Size-resolved aerosol analysis during road salt application revealed that chloride levels in urban aerosols were similar to marine environments, with road salt-derived chloride redistributed into finer aerosol modes. These findings suggest that acid displacement and heterogeneous reactions play a critical role in sustaining HCl production over time. Simulations with the E-AIM model underscored the need for improved representation of ammonia and ammonium chloride chemistry to predict HCl partitioning more accurately. Indoor sources, particularly chloramines (NH₂Cl, NHCl₂) from hypochlorite-based cleaning products, were identified as significant outdoor contributors to reactive chlorine budgets. These sources were found to rival smaller industrial emissions. Mobile and vertical gradient measurements quantified spatial variability in HCl emissions, highlighting the influence of local meteorological conditions on HCl fluxes and deposition. These findings advance our understanding of urban chlorine chemistry, providing insights into sources, transformations, and their implications for air quality and atmospheric models.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.187
Teacher spread0.165 · 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 teacher head, not a consensus.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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