Evaluation of NOx tier III regulations on shipping emissions in Canada: air quality modeling simulations
Bibliographic record
Abstract
This study assesses the impact of implementing the NOx Tier III regulations over the Canadian waters on air quality in coastal regions of Canada, based on a series of numerical simulations using the Canadian air quality prediction model, GEM-MACH.The International Maritime Organization (IMO) established diesel engine standards for nitrogen oxides (NOx) emissions from ocean-going vessels (OGVs), or ships under MARPOL Annex VI Regulation 13.Under this regulation, if a ship with keel laid on or after 1 January 2016 is transiting the North American Emission Control Area (ECA), the NOx Tier III standard would be applicable.The IMO Tier III NOx standards are the strictest of the tier standards, requiring 3.4 grams NOx/kWh for slow-speed marine propulsion engines and less for auxiliary engines.The standards were designed to significantly reduce NOx emissions compared to pre-tier engines (Tier 0), Tier I, and Tier II engines.In 2009, Canada and the United States submitted a proposal (MEPC 59/6/5) to the IMO to designate an ECA for nitrogen oxides, sulphur oxides, and particulate matter for specified portions of the United States and Canadian coastal waters (North America).In the analysis for this proposal, it was assumed that about one-third of the total fleet is expected to be compliant with Tier III standards in the 2020 performance scenario.It was estimated that the emission reductions associated with the ECA designation would be substantial, including a 23% NOx emission reduction in the 2020 ECA scenario compared to the baseline scenario.In 2020, Environment and Climate Change Canada (ECCC) contracted Starcrest Consulting Group, LLC to conduct a study to investigate the keel laid date issue under the IMO.The study found that only 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.In this study, ECCC carried out a modelling analysis on impact of implementation of the IMO NOx Tier III standards within Canadian waters on air quality, using the ECCC's air quality prediction model, GEM-MACH.Three scenarios were considered: current (1%), partial (30%), and full (100%) compliance with the NOx Tier III standards.Following the air quality modelling analysis, Health Canada (HC) conducted a health impact analysis under the three NOx Tier III compliance scenarios.The summary of the health impact analysis is attached (in Appendix) as a companion to this report. The 2019 Canadian marine shipping emission inventory and NOx Tier III compliance scenariosThe 2019 marine vessels emissions inventory was generated using the Marine Emissions Inventory Tool (MEIT) platform developed by the Cross Sectoral Energy Division (CSED) of ECCC.It is based on vessel movement data for 2019 within Canadian waters.The Canadian waters include the Arctic, the St. Lawrence Seaway transit to the Great Lakes, and the West and East coasts.Table E1 shows the estimated 2019 annual total marine shipping emissions within the Canadian waters by vessel category, fuel type, and activity.The 2019 annual total NOx emissions from marine ships traveling in the Canadian waters is estimated at 191,445 tonnes, which includes the consideration for 1% of ships in compliance with the NOx Tier III standard.The 2019 Canadian marine sector NOx emissions constitute to 10% of the national total anthropogenic NOx emissions from all sectors.v Table E1 2019 Marine shipping emissions from the vessels traveling in Canadian waters by vessel group (C2, C3), fuel type (ULSD, MDO, HFO), and activity (berthed, anchored, underway) Vessel group Activity Fuel type NOX SO2 CO CO2 VOC CH4 N2O PM2.5 PM10 Black Carbon C2 Berthed ULSD 3,061
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".