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Record W2156033499 · doi:10.1039/b502128f

Global partitioning of NOx sources using satellite observations: Relative roles of fossil fuel combustion, biomass burning and soil emissions

2005· article· en· W2156033499 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFaraday Discussions · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsDalhousie University
FundersGoddard Space Flight CenterHarvard UniversityNational Aeronautics and Space Administration
KeywordsCombustionNOxEmission inventoryEnvironmental scienceFossil fuelAtmospheric sciencesBiomass burningBiomass (ecology)A priori and a posterioriBiofuelMeteorologyClimatologyAerosolAir quality indexChemistryGeographyGeologyWaste managementEngineering

Abstract

fetched live from OpenAlex

We use space-based observations of NO2 columns from the Global Ozone Monitoring Experiment (GOME) to derive monthly top-down NOx emissions for 2000 via inverse modeling with the GEOS-CHEM chemical transport model. Top-down NOx sources are partitioned among fuel combustion (fossil fuel and biofuel), biomass burning and soils by exploiting the spatio-temporal distribution of remotely sensed fires and a priori information on the location of regions dominated by fuel combustion. The top-down inventory is combined with an a priori inventory to obtain an optimized a posteriori estimate of the relative roles of NOx sources. The resulting a posteriori fuel combustion inventory (25.6 TgN year(-1)) agrees closely with the a priori (25.4 TgN year(-1)), and errors are reduced by a factor of 2, from +/- 80% to +/- 40%. Regionally, the largest differences are found over Japan and South Africa, where a posteriori estimates are 25% larger than a priori. A posteriori fuel combustion emissions are aseasonal, with the exception of East Asia and Europe where winter emissions are 30-40% larger relative to summer emissions, consistent with increased energy use during winter for heating. Global a posteriori biomass burning emissions in 2000 resulted in 5.8 TgN (compared to 5.9 TgN year(-1) in the a priori), with Africa accounting for half of this total. A posteriori biomass burning emissions over Southeast Asia/India are decreased by 46% relative to a priori; but over North equatorial Africa they are increased by 50%. A posteriori estimates of soil emissions (8.9 TgN year(-1)) are 68% larger than a priori (5.3 TgN year(-1)). The a posteriori inventory displays the largest soil emissions over tropical savanna/woodland ecosystems (Africa), as well as over agricultural regions in the western U.S. (Great Plains), southern Europe (Spain, Greece, Turkey), and Asia (North China Plain and North India), consistent with field measurements. Emissions over these regions are highest during summer at mid-latitudes and during the rainy season in the Tropics. We estimate that 2.5-4.5 TgN year(-1) are emitted from N-fertilized soils, at the upper end of previous estimates. Soil and biomass burning emissions account for 22% and 14% of global surface NOx emissions, respectively. We infer a significant role for soil NOx emissions at northern mid-latitudes during summer, where they account for nearly half that of the fuel combustion source, a doubling relative to the a priori. The contribution of soil emissions to background ozone is thus likely to be underestimated by the current generation of chemical transport 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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.244
Teacher spread0.218 · 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