Macroeconomic impacts of reducing greenhouse gas emissions from Canadian agriculture
Notice bibliographique
Résumé
Abstract Canada's commitment under the Kyoto Protocol is to reduce its greenhouse gas (GHG) emissions by 6% of its 1990 levels. Each industrial sector is investigating alternative technologies, production and management practices that can decrease their GHG emissions. The macroeconomic impacts of four mitigation strategies to reduce GHG emissions from Canada's agriculture sectors were measured using an input-output model. The size of the GHG reduction from each mitigation strategy depended on whether agricultural soils were included as a carbon (C) sink. Including agricultural soils as a C sink impacts on the absolute amount of GHG emissions that must be reduced and the relative importance of the various mitigation strategies. This will be a key factor in policy development. Only one strategy, improving forage quality by 15%, had positive macroeconomic impacts in all situations. It was projected that this strategy would increase industrial output by $106.97 M (M = million; all $ Canadian), gross domestic product at factor cost (GDP) by $45.51 M and employment by 689 jobs. This strategy decreased GHG emissions by 0.07% below the ‘business as usual’ (BAU) situation when sinks were included. Increasing the adoption of zero-till farming had a positive macroeconomic impact only when the industrial sector effects were included. However, when household and industrial-sector impacts were combined, the results were decreases in industrial output of $286.90 M, GDP of $55.98 M and employment by 769 jobs. The mitigation strategy decreased GHG emissions by 3.06% below the BAU situation when sinks were included in the estimate. Improved soil nutrient management through more efficient use of N fertilizer had a negative net impact on the economy. This mitigation strategy had a direct impact on the agriculture and the fertilizer sectors, resulting in net decreases in industrial output of $70.76 M, GDP of $43.38 M and employment of 518 jobs. It was estimated that this mitigation strategy would decrease GHG emissions by 1.37% below the BAU situation. The last mitigation strategy was a permanent plant cover program. This generated the largest negative impact on the economy. It was projected to decrease industrial output by $1192.63 M, GDP by $392.17 M and employment by 6155 jobs. The strategy decreased GHG emissions by 1.73% below the BAU situation.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».