Aerosol size distribution and radiative forcing response to anthropogenically driven historical changes in biogenic secondary organic aerosol formation
Bibliographic record
Abstract
Abstract. Emissions of biogenic volatile organic compounds (BVOCs) have changed in the past millennium due to changes in land use, temperature, and CO2 concentrations. Recent reconstructions of BVOC emissions have predicted that global isoprene emissions have decreased, while monoterpene and sesquiterpene emissions have increased; however, all three show regional variability due to competition between the various influencing factors. In this work, we use two modeled estimates of BVOC emissions from the years 1000 to 2000 to test the effect of anthropogenic changes to BVOC emissions on secondary organic aerosol (SOA) formation, global aerosol size distributions, and radiative effects using the GEOS-Chem-TOMAS (Goddard Earth Observing System; TwO-Moment Aerosol Sectional) global aerosol microphysics model. With anthropogenic emissions (e.g., SO2, NOx, primary aerosols) turned off and BVOC emissions changed from year 1000 to year 2000 values, decreases in the number concentration of particles of size Dp > 80 nm (N80) of > 25% in year 2000 relative to year 1000 were predicted in regions with extensive land-use changes since year 1000 which led to regional increases in the combined aerosol radiative effect (direct and indirect) of > 0.5 W m−2 in these regions. We test the sensitivity of our results to BVOC emissions inventory, SOA yields, and the presence of anthropogenic emissions; however, the qualitative response of the model to historic BVOC changes remains the same in all cases. Accounting for these uncertainties, we estimate millennial changes in BVOC emissions cause a global mean direct effect of between +0.022 and +0.163 W m−2 and the global mean cloud-albedo aerosol indirect effect of between −0.008 and −0.056 W m−2. This change in aerosols, and the associated radiative forcing, could be a largely overlooked and important anthropogenic aerosol effect on regional climates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".