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Record W6948073092 · doi:10.4224/40003324

Hydrogen: large-scale deployment and export

2024· report· en· W6948073092 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2024
Typereport
Languageen
Field
Topic
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSoftware deploymentLegislationClearingConfusionGreenhouse gasPort (circuit theory)Natural resource

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.030
GPT teacher head0.298
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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