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Record W4245814920 · doi:10.5194/acpd-12-18243-2012

Global and regional emissions estimates for HCFC-22

2012· preprint· en· W4245814920 on OpenAlexaboutno aff
Eri Saikawa, Matthew Rigby, Ronald G. Prinn, S. A. Montzka, B. R. Miller, L. J. M. Kuijpers, P. J. Fraser, Martin K. Vollmer, Takuya Saito, Yoko Yokouchi, Christina M. Harth, Jens Mühle, Ray F. Weiss, Peter K. Salameh, J. Kim, S. Li, S. Park, K.‐R. Kim, Dickon Young, Simon O’Doherty, Peter G. Simmonds, Archie McCulloch, Paul B. Krummel, L. P. Steele, Chris Lunder, Ove Hermansen, Michela Maione, Jgor Arduini, Bo Yao, Lingxi Zhou, H. J. Wang, James W. Elkins, B. D. Hall

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersClimate Program OfficeNational Oceanic and Atmospheric AdministrationChina Meteorological AdministrationNational Research Foundation of KoreaAustralian GovernmentCommonwealth Scientific and Industrial Research OrganisationDepartment for Environment, Food and Rural Affairs, UK GovernmentNational Aeronautics and Space Administration
KeywordsMontreal ProtocolEnvironmental scienceNorthern HemisphereGreenhouse gasRefrigerantSouthern HemisphereFreonAtmospheric sciencesClimatologyTroposphereOzone depletionMeteorologyOzoneOzone layerGeographyOceanographyChemistryEngineeringGeology

Abstract

fetched live from OpenAlex

Abstract. HCFC-22 (CHClF_2, chlorodifluoromethane) is an ozone-depleting substance (ODS) as well as a significant greenhouse gas (GHG). HCFC-22 has been used widely as a refrigerant fluid in cooling and air-conditioning equipment since the 1960s, and it has also served as a traditional substitute for some chlorofluorocarbons (CFCs) controlled under the Montreal Protocol. A low frequency record on tropospheric HCFC-22 since the late 1970s is available from measurements of the Southern Hemisphere Cape Grim Air Archive (CGAA) and a few Northern Hemisphere air samples (mostly from Trinidad Head) using the Advanced Global Atmospheric Gases Experiment (AGAGE) instrumentation and calibrations. Since the 1990s high-frequency, high-precision, in situ HCFC-22 measurements have been collected at these AGAGE stations. Since 1992, the Global Monitoring Division of the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) has also collected flasks on a weekly basis from remote sites across the globe and analyzed them for a suite of halocarbons including HCFC-22. Additionally, since 2006 flasks have been collected approximately daily at a number of tower sites across the US and analyzed for halocarbons and other gases at NOAA. All results show an increase in the atmospheric mole fractions of HCFC-22, and recent data show a growth rate of approximately 4% per year, resulting in an increase in the background atmospheric mole fraction by a factor of 1.7 from 1995 to 2009. Using data on HCFC-22 consumption submitted to the United Nations Environment Programme (UNEP), as well as an existing bottom-up emissions estimate, we first create globally-gridded a priori HCFC-22 emissions over the 15 yr since 1995. We then use the three-dimensional chemical transport model, Model for Ozone and Related Chemical Tracers version 4 (MOZART v4) and a Bayesian inverse method to estimate global as well as regional annual emissions. Our inversion indicates that the global HCFC-22 emissions have an increasing trend between 1995 and 2009. We further find a surge in HCFC-22 emissions in 2009 from developing countries in Asia – the largest emitting region including China and India. Globally, substantial emissions continue despite current phase-out of production and consumption in developed countries.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.033
GPT teacher head0.272
Teacher spread0.239 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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