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Record W4313579995 · doi:10.5194/essd-15-75-2023

Version 2 of the global catalogue of large anthropogenic and volcanic SO <sub>2</sub> sources and emissions derived from satellite measurements

2023· article· en· W4313579995 on OpenAlexaff
Vitali Fioletov, C. A. McLinden, Debora Griffin, Ihab Abboud, N. A. Krotkov, Peter Leonard, Can Li, Joanna Joiner, Nicolas Theys, Simon Carn

Bibliographic record

VenueEarth system science data · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersEarth Sciences DivisionGoddard Space Flight CenterNational Aeronautics and Space Administration
KeywordsOzone Monitoring InstrumentSatelliteEnvironmental scienceEmission inventoryVolcanoTotal Ozone Mapping SpectrometerMeteorologyTrace gasTroposphereAtmospheric sciencesRemote sensingOzoneGeologyGeographyOzone layerAir quality indexPhysics

Abstract

fetched live from OpenAlex

Abstract. Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI), Ozone Mapping and Profiler Suite (OMPS), and TROPOspheric Monitoring Instrument (TROPOMI) satellite spectrometers were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources releasing from about 10 kt yr−1 to more than 4000 kt yr−1 of SO2, that have been identified and grouped by country and primary source origin: volcanoes (106 sources); power plants (477); smelters (74); and sources related to the oil and gas industry (102). There are several major improvements compared to the original catalogue: it combines emissions estimates from three satellite instruments instead of just OMI, uses a new version 2 of the OMI and OMPS SO2 dataset, and updated consistent site-specific air mass factors (AMFs) are used to calculate SO2 vertical column densities (VCDs). The newest TROPOMI SO2 data processed with the Covariance-Based Retrieval Algorithm (COBRA), used in the catalogue, can detect sources with emissions as low as 8 kt yr−1 (in 2018–2021) compared to the 30 kt yr−1 limit for OMI. In general, there is an overall agreement within ±12 % in total emissions estimated from the three satellite instruments for large regions. For individual emission sources, the spread is larger: the annual emissions estimated from OMI and TROPOMI agree within ±13 % in 50 % of cases and within ±28 % in 90 % of cases. The version 2 catalogue emissions were calculated as a weighted average of emission estimates from the three satellite instruments using an inverse-variance weighting method. OMI, OMPS, and TROPOMI data contribute 7 %, 5 %, and 88 % to the average, respectively, for small (<30 kt yr−1) sources and 33 %, 20 %, and 47 %, respectively, for large (>300 kt yr−1) sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years. The version 2 of the global catalogue has been posted at the NASA global SO2 monitoring website (https://doi.org/10.5067/MEASURES/SO2/DATA406, Fioletov et al., 2022).

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.009

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 head0.028
GPT teacher head0.241
Teacher spread0.213 · 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

Citations56
Published2023
Admission routes1
Has abstractyes

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