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Enregistrement W7135884709

Geothermal energy in agrifood systems

2025· report· en· W7135884709 sur OpenAlexafffund
Mark Palmer, Ulrich Ofterdinger, Omaira Bernadett Avila Rostant, Dionne O. Clarke-Harris, Apolonio Aguilar, Egbert Irving, Joyanne De Four-Babb

Notice bibliographique

RevueResearch Portal (Queen's University Belfast) · 2025
Typereport
Langueen
Domaine
Thématique
Établissements canadiensQueen's University
Organismes subventionnairesQueen's UniversityQueen's University Belfast
Mots-clésClimate changeGeothermal energyExtreme weatherResource (disambiguation)Work (physics)Global warmingPeninsulaRenewable energyGeothermal gradient
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The Caribbean Community (Caricom) region is vulnerable to climate change. Located beneath Mexico’s Yucatan Peninsula and adjacent to the warmest basin of water on planet earth – the Gulf of Mexico – Belize showcases and exemplifies climate variability in weather extreme terms - significant rainfall, flash floods, heatwaves, drought and flooding. Like other countries in the wider region, the blunt reality is that Belize is facing new climate change pressures and challenges. These corollary test existing capabilities of whole business sectors, energy infrastructures and food systems. Nowhere is this impact more acutely felt than in the agrifood sector – agrifood systems – for example in the production and processing of chilli peppers, bananas, citrus fruits, sugar beet, coconuts, nuts and seafoods. Persistent and frequent tropical storms and hurricanes impact business economics, growing conditions and the cost of energy and security. However, adapting to what is happening and understanding what possibilities are open to agrifood producers and processors, can place their destiny in their own hands. This adaptation is difficult. But it is essential. For us, co-organising Geothermal Week Belize afforded us the opportunity to better understand if geothermal energy resources (non-volcano) and technologies might be appropriate in small business conditions in agrifood systems in Belize. Toward this end, we aimed to combine local knowledge of ‘on the ground realities’ of what might work (or not) in climate variability conditions, while also collaborating with multiple agrifood stakeholders in Belize. Co-organising Geothermal Week Belize afforded us the opportunity to, (i) better understand the synergies of regional dynamics, (ii) embrace a listening-mode for understanding and learning, (iii) gain insights into the small to medium agricultural producer and processer communities, (iv) understand how communities can be sustainable from local resources for local needs and, (v) eschew large-scale systems change thinking. Our work nudges forward four questions with agrifood stakeholders in Belize: 1)What issues are faced by agrifood communities in Belize? 2)How might geothermal resources and technologies benefit the agrifood system in Belize? 3)How might agrifood businesses adapt to climate variability, become more energy efficient and sustainable? 4)How might R&D projects be realised ‘on the ground’ in Belize so that the agrifood communities can see and understand geothermal energy working? Informed and assisted by sector-specific insights by members of the Caribbean Agricultural Research and Development Institute (CARDI) and also by local knowledge from the University of Belize, this report reflects the work undertaken and that is captured in the title of ‘Exploring the Future of Geothermal Energy in the Agrifood Sector’ of our activities during the week of 4th and 7th of November 2024 at the University of Belize, Belmopan, Belize. A week of activities generated a range of conversations with agrifood production and processing stakeholders. These are reported on here in eight sections: (i) prefatory, (ii) prospectivity, (iii) potentiality, (iv) projectivity, (v) inter-country semiotic reflectivity, (vi) nature-inspired adaptation, (vii) formativity, and (viii) conclusions. Geothermal Week Belize establishes an initial baseline view of what is and what is not relevant in the specifics of agrifood system in Belize. A preliminary baseline assessment is that geothermal technologies, thus far, have had a negligible effect on how the energy and agrifood sector function in Belize. A baseline synopsis from our stakeholder engagement indicates that there is a perceived need for more understanding, more adaptation, with more measures to reduce the energy costs in production and processing in the Belize agrifood sector. Moreover, the baseline assessment points to a perceived need for understanding further how geothermal technologies can enhance controlled environment agriculture (CEA) systems and maximize efficiency, reduce costs and resource use, and increase crop yields by providing optimal growing conditions year-round. Also, there is a perceived need for geothermal cooling equipment solutions in controlled environment agriculture (CEA) systems and the built environment more generally. From technology coupling point of view, an important geothermal energy coupling is with optimisation technology, including artificial intelligence-led systems for controlled environment agriculture (CEA), smart agriculture building designs and synergistic solar-thermal technology interfaces. In sum, this baseline work brings into view the perceived need for small-scale, affordable, energy-efficient, environmentally sustainable, and locally autonomous geothermal R&D projects in Belize. Working towards developing an R&D project at the University of Belize’s Central Farm campus would provide practical small steps for agrifood community demonstration and which may one day be more portable across the agrifood system.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,141
Score d'incertitude au seuil0,281

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0030,002
Communication savante0,0040,002
Science ouverte0,0000,002
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,000

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.

Tête enseignante Opus0,034
Tête enseignante GPT0,301
Écart entre enseignants0,267 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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