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Record W2082641979 · doi:10.5194/acp-12-5367-2012

Projections of mid-century summer air-quality for North America: effects of changes in climate and precursor emissions

2012· article· en· W2082641979 on OpenAlexafffund
James T. Kelly, Paul A. Makar, David A. Plummer

Bibliographic record

VenueAtmospheric chemistry and physics · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsGolder Associates (Canada)Environment and Climate Change Canada
FundersClean Air Regulatory Agenda
KeywordsEnvironmental scienceClimate changeAir quality indexClimate modelClimatologyCurrent (fluid)PrecipitationRepresentative Concentration PathwaysOzoneAtmospheric sciencesGeneral Circulation ModelMeteorologyGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract. Ten year simulations of North American current and future air-quality were carried out using a regional air-quality model driven by a regional climate model, in turn driven by a general circulation model. Three separate summer scenarios were performed: a scenario representing the years 1997 to 2006, and two SRES A2 climate scenarios for the years 2041 to 2050. The first future climate scenario makes use of 2002 anthropogenic precursor emissions, and the second applied emissions scaling factors derived from the IPCC Representative Concentration Pathway 6 (RCP 6) scenario to estimate emissions for 2050 from existing 2020 projections. Ten-year averages of ozone and PM2.5 at North American monitoring network stations were used to evaluate the model's current chemical climatology. The model was found to have a similar performance for ozone as when driven by an operational weather forecast model. The PM2.5 predictions had larger negative biases, likely resulting from the absence of rainwater evaporation, and from sub-regional negative biases in the surface temperature fields, in the version of the climate model used here. The differences between the two future climate simulations and the current climate simulation were used to predict the changes to air-quality that might be expected in a future warmer climate, if anthropogenic precursor emissions remain constant at their current levels, versus if the RCP 6 emissions controls were adopted. Metrics of concentration, human health, and ecosystem damage were compared for the simulations. The scenario with future climate and current anthropogenic emissions resulted in worse air-quality than for current conditions – that is, the effect of climate-change alone, all other factors being similar, would be a worsening of air-quality. These effects are spatially inhomogeneous, with the magnitude and sign of the changes varying with region. The scenario with future climate and RCP 6 emissions for 2050 resulted in an improved air-quality, with decreases in key pollutant concentrations, in acute human mortality associated with air-pollution, and in sulphur and ozone deposition to the ecosystem. The positive outcomes of the RCP 6 emissions reductions were found to be of greater magnitude than the negative outcomes of climate change alone. The RCP 6 scenario however resulted in an increase in the deposition of nitrogen, as a result of increased ammonia emissions expected in that scenario, compared to current ammonia emissions levels. The results of the study raise the possibility that simultaneous reductions of greenhouse gases and air pollution precursors may further reduce air pollution levels, with the added benefits of an immediate reduction in the impacts of air pollution on human and ecosystem health. Further scenarios to investigate this possibility are therefore recommended.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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 designSimulation or modeling
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

Citations68
Published2012
Admission routes2
Has abstractyes

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