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Enregistrement W6948073092 · doi:10.4224/40003324

Hydrogen: large-scale deployment and export

2024· report· en· W6948073092 sur OpenAlexaffvenueabout

Notice bibliographique

RevueNPARC · 2024
Typereport
Langueen
Domaine
Thématique
Établissements canadiensNational Research Council Canada
Organismes subventionnairesnon disponible
Mots-clésSoftware deploymentLegislationClearingConfusionGreenhouse gasPort (circuit theory)Natural resource

Résumé

récupéré en direct d'OpenAlex

Many countries, including Canada, have released hydrogen strategies that require measures that would reduce the greenhouse gases (GHG) emissions to the defined decarbonization targets by 2050. To achieve these climate goals, barriers within the regulatory frameworks must be addressed and substantial infrastructure must be developed. This includes the establishment or adoption of codes and standards across the hydrogen value chain where gaps currently exist in addition to alterations to the existing ports or even developing new terminals for hydrogen export. Canada is positioned as a potential hydrogen exporter due to its abundant natural resources like water and wind. To understand and overcome the regulatory challenges related to hydrogen, Natural Resources Canada (NRCan) tasked NRC to conduct a comprehensive gap analysis to examine both domestic and international regulatory landscapes. The study first identified that the regulatory framework governing large-scale hydrogen deployment and export projects in Canada primarily stems from environmental legislation at various governmental levels. Depending on project scale and scope, activities such as altering bodies of water or clearing forests may trigger environmental assessments. However, the intersection of federal, provincial, and municipal jurisdictions, as well as port authorities, often leads to confusion and project delays. To address this, establishing a single authority in each province to streamline permitting processes and provide guidance on project requirements is crucial. While there are almost no gaps in the majority of infrastructure components of large-scale projects, such as pressurized, fire, electrical and piping systems, there are gaps in minor details like selecting hydrogen-specific detectors, which may pose challenges. In such cases, project proponents can refer to international standards and provincial authorities for guidance to ensure project safety. A regulatory pathway to prioritize hydrogen-related standards is recommended for timely adaptation and safe execution of projects. On the international level, the EU is committed to hydrogen to lower GHG emissions to meet its rigorous climate goals and has political aspiration of achieving an annual production of 20 million tons of renewable hydrogen available to the EU by 2030 (with 10 million tons of domestically produced hydrogen and up to 10 million tons of imported hydrogen). This offers Canada a significant chance to become a net exporter of hydrogen. For the EU to realize its aspirations, it will require a robust infrastructure, support mechanisms, and a cohesive regulatory framework. Challenges like global regulatory discrepancies, insufficient economic support for the development of infrastructure, and permitting issues all contribute to delays in implementation of hydrogen within the desired timeframe. To minimize investment loss and additional capital expenditure, the current regulatory systems and port infrastructure for liquified natural gas (LNG) or ammonia can potentially be repurposed and adapted for the handling and distribution of liquefied hydrogen. While regulations, codes and standards pose challenges, other more immediate barriers were also identified in this study. The environmental assessments, lengthy and complex permit acquisition processes, and high energy demands are some of more immediate obstacles for large-scale hydrogen projects. It was also revealed as part of the study that challenges related to power supply, water resource management, and emergency response protocols for hydrogen ship-spills require urgent attention. Harmonizing certification schemes globally is essential to ensure transparent approval of hydrogen's carbon intensity across its value chain and creating the demand in the market for its use. Many certification schemes are currently available in the market. However, each scheme varies in terms of lifecycle boundaries and carbon intensity thresholds. The discrepancies in the certification scheme s makes their international use challenging. While ammonia is considered as an alternative for hydrogen export, challenges associated with the energy required for the ‘cracking’ process to convert it to hydrogen and the potent greenhouse gas emissions such as N2O and NOx could counteract the intended climate benefits and lead to degradation of air quality over time. Power-to-X technologies offer significant potential for carbon footprint reduction across industry and mobility sectors. Although the gap in specific regulations codes and standards for power-to-x seems to be bigger, the existing RCS for non-synthetic counterpart fuels can be a framework for implementing these. Finally, effective engagement with Indigenous communities during large-scale hydrogen infrastructure projects development is critical. Project proponents must proactively involve and consult with affected indigenous groups where the engagement is not possible through the Environmental Assessment (EA) process. Maintaining meaningful dialogue and collaboration with the indigenous communities helps to respect Aboriginal or Treaty Rights, build mutually beneficial relationships and mitigate potential conflicts. In summary, to realize the full potential of hydrogen as a clean energy solution, the regulatory barriers must be removed by clarifying the applicable permits and regulations. To expedite the implementation, the existing infrastructure and certification schemes can be leveraged. Additionally, careful planning of critical resources such as water, wind, and tidal energy, along with their associated systems like transmission grids capacity, is essential to address future challenges.

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)0,002
score de la tête « metaresearch » (Gemma)0,002
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: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,554
Score d'incertitude au seuil0,898

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0020,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,030
Tête enseignante GPT0,298
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
GenreEmpirique

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
Publié2024
Routes d'admission3
Résumé présentoui

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