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Record W7133277320

Canadian ports International Maritime Organization ship engine tier forecasts 2015-2050

2020· other· en· W7133277320 on OpenAlexaboutno aff

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPort (circuit theory)Diesel fuelService (business)Diesel engineMilestoneNitrogen oxidesEngine room
DOInot available

Abstract

fetched live from OpenAlex

The International Maritime Organization (IMO) has established progressively more stringent diesel engine standards for oxides of nitrogen (NOx) emissions from ocean-going vessels (OGVs, or ships), which are based on a ship’s keel-laid date (KLD) and when a Nitrogen Emissions Control Area (NECA) comes into force. Ships built on or after specific KLD milestone dates are required to meet the engine standards in place at that time, and as a result, newer ships are significantly cleaner than older ones. Under IMO MARPOL Annex VI Regulation 13, if a ship undergoes a major conversion (involving the replacement of a marine diesel engine with a non-identical marine diesel engine), the standards at the time of replacement will apply. For a vessel transiting the North American NECA, the NOx Tier III standard would be applicable. Importantly, there are no further requirements for existing vessels to meet the more stringent engine standards nor are there requirements for shipping lines to deploy cleaner IMO Tier III vessels (existing or new builds) to a NECA. Thus, the actual emissions benefits remain uncertain without a better understanding of the four Canadian ports fleet engine mix, now and forecasted into the future. Using IHS Markit (third-party) activity data and ship parameter data, this report analyzes the current fleet composition with respect to IMO engine tiers calling four Canadian ports: Vancouver, Prince Rupert, Montréal, and Halifax. This report also forecasts how long the current world fleet can service future calls for each port before being exhausted and replaced by Tier III ships, which are ships with keels laid on or after 1 January 2016. These engines use aftertreatment technologies to meet an emission limit of 3.4 grams of NOx per kilowatt-hour or better, which are more than 90% cleaner with respect to NOx compared to Tier I ships. This report has identified the following: Just 0.5% of the 2019 ship calls to the four Canadian ports were IMO Tier III, a slower-than-expected deployment compared to previous generations of engines. Ship owners laid an unprecedented number of keels in 2015, leading up to and just prior to the Tier III deadline and many of these keels still have not been constructed. Since 2005, more than 1,000 keels laid still have not been built, and roughly 70% of these ships will be grandfathered from the Tier III standard. This backlog of pre-Tier III ships has delayed deployment of the cleanest Tier III vessels. A scenario forecast found that for the four Canadian ports and associated vessel types, Tier III ships are not expected to comprise a substantial part of the fleet until the mid- to late-2040s with the earliest dates in the mid-2030s for only a few vessel types. This report also has identified significant challenges with using third-party data, rather than data from ports themselves, to conduct such analyses and recommends further study with port-specific call data and vessel forecasts.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.006
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.009

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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 designSimulation or modeling
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
Published2020
Admission routes1
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaFrench-language works237,207