Regulations Concerning Agriculture and Air Pollution
Bibliographic record
Abstract
The main issues related to the atmospheric pollution are the stratospheric ozone depletion, the transboundary air pollution, the troposphere air quality and the climate change. The three last decades have seen the birth of several measures for the atmosphere safeguard. Agricultural activities play a key role in determining, preventing and mitigating atmospheric pollution. The emission to atmosphere of different ozone-depleting substances is regulated by the Montreal Protocol. The role of agriculture activity in ozone depletion is linked to the utilization of methyl bromide as soil sterilant and to the emission of nitrogen oxides and nitrous oxide, from agricultural soils. The Convention on long-range transboundary air pollution regulates the emission of several pollutants, i.e. sulphur dioxide, nitrogen oxides, ammonia, non methane volatile organic compounds, carbon monoxide, heavy metals, persistent organic pollutants, and tropospheric ozone. The agriculture sector is responsible for a large part of the emissions of ammonia and nitrogen oxides, mainly through manure management and nitrogen fertilization, and of most persistent organic pollutants, largely used in the past as insecticides and fungicides. The increase of the greenhouse gases (GHGs) concentration in the atmosphere is under the control of the Kyoto Protocol. Agriculture accounts for 59-63% of global non-CO2 GHGs emissions but at the same time it contributes to the atmospheric CO2 concentration stabilisation through the substitution of fossil fuels by biofuels and the sequestration of C in soil and vegetal biomass. In this paper we provide an outline of the numerous scientific and legislative initiatives aimed at protecting the atmosphere, and we analyse in detail the agriculture sector in order to highlight both its contribution to atmospheric pollution and the actions aimed at preventing and mitigating it.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.012 |
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".