Emissions analysis of controlled environment agriculture in the Canadian Arctic
Notice bibliographique
Résumé
Evidence presented in previous studies show that far-north Canadian populations face significant food security challenges, including quality, price, and availability of fresh fruits and vegetables. To target some of these challenges, several methods of protected agriculture have been attempted in recent years in high latitude locations in Canada. Although many studies show that it is feasible to produce quality fruits and vegetables in Controlled Environment Agriculture (CEA) facilities in the Arctic, there are concerns about the energy emissions from operating such facilities. The high energy demand of CEA facilities and the high dependence on fossil fuels in the Canadian Arctic are factors that must be considered from a greenhouse gas emissions perspective. Thus, the objective of this study is to estimate the carbon dioxide equivalent emissions associated with the production of fruits and vegetables in a CEA facility located in the Canadian Arctic. Specifically, this study aims to answer the following research question: what is the relative quantity of greenhouse gases emitted for produce grown locally in the Arctic in a CEA facility compared to produce transported in from southern Canada? The carbon dioxide equivalent footprint of produce cultivated in southern Canada was quantified based on previous studies and the emissions of air transportation of food were estimated based on two transportation paths from southern Canada to locations in the Canadian Arctic. The emissions associated with food produced in the Arctic were estimated based on modelling of the energy use of a CEA facility located in Cambridge Bay, Nunavut. Considering that the production of fruits and vegetables varies significantly depending on the type of produce and the referenced study, three different yield values (low, high, and average production) were selected for performing a sensitivity analysis of the total CEA emissions. Cases of on-site renewable energy for CEA at increasing scales were modelled and compared to a baseline model with no renewable generation. The results of this study indicate that emissions from produce grown locally in the Arctic in a CEA facility could be at least eight times that of the emissions associated with products shipped from southern Canada if no local renewable generation is used. Several factors could change this result – the use of renewable energy resources and more efficient production practices would reduce the emissions associated with CEA in these locations. Further, the transportation analysis did not look at the most extreme routes, such as the northernmost communities, which would increase the transportation carbon dioxide equivalent emissions, although likely only by a factor of two or three at most. While the societal needs for the supply of fresh food is more complex than just examining the related greenhouse gas emissions, this study indicates that until there is a significant proportion of renewable energy readily available in Canadian Arctic locations, CEA operated in these locations would likely result in significantly higher emissions per mass of food produced than air transport of food from lower latitude locations.
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Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».