Analysis of Ship Traffic and Ship Accidents in the Canadian and Global Arctic
Bibliographic record
Abstract
In the Canadian Arctic, ship traffic has been increasing at the same time as sea ice has been declining over the past decade-plus. The decrease in sea ice has been associated with trends in warm weather and atmospheric conditions in the summer seasons, which are expected to continue. Thus, it is anticipated that ship traffic will also continue to grow, as areas in the Arctic, including the Northwest Passage (NWP) and Northern Sea Route (NSR) experience less and less sea ice. The appeal of the opening of these major Arctic shipping routes, is that these routes are shorter in distance for commercial ships on international voyages in comparison to traditional routes that travel through the Panama and Suez Canals. Assuming safe and smooth sailing a shorter route can be beneficial monetarily for commercial shipping companies and as a result for other economic sectors reliant on the efficient shipment of goods. However, a major concern associated with the anticipated increase in Arctic ship traffic is the potential for an increase in the number and severity of maritime navigational related accidents. Thus, the overall aim of this thesis is to quantify recent historic links between ship traffic, sea ice, ship accidents, and accident rates within the Canadian Arctic as well as the global Arctic. There are three specific objectives including to: 1. Conduct a comparative statistical analysis between two ship traffic databases (NORDREG and AIS) within the Canadian Arctic to evaluate datasets strengths and weaknesses; 2. Use the best available data (see objective 1) to examine the statistical associations and trends for ship traffic, ship accidents, accident rates, and sea-ice extent within the Canadian Arctic during the shipping-season from 1990 to 2019; and 3. Derive and compare recent ship traffic accident rates to determine if statistical trends from 2012 to 2019 exist for ships across the global Arctic. Results of the study show that both NORDREG and AIS data is useful in understanding shipping traffic trends in Arctic Canada over time and that each dataset is effective depending on the temporal period of interest (Objective 1). NORDREG data is most effective for identifying ship positioning before 2012 (+106,811 more nm sailed per matched unique vessels and +9 overall unique vessels from NORDREG) and from 2012 onwards AIS is more accurate, highlighted by the year of 2018 (+84,149 more nm sailed and +169 unique vessels from AIS). Using available data sources from 1990 to 2019, it was revealed that although commercial and non-commercial ship traffic is increasing across in Arctic Canada, the total number of accidents and overall accident rate for commercial vessels has declined, whereas they have increased for non-commercial ships (Objective 2). There are significant positive trends in overall ship traffic for all ship types (+9,275 nm yr⁻¹), commercial ships (+5,011 nm yr⁻¹) and non-commercial ships (+4,658 nm yr⁻¹). Whereas there have been significant negative trends in ship accidents for commercial ships (-0.06 accidents yr⁻¹), ship accident rates, for all ship types (-6.31E-07 accidents/nm yr⁻¹). Sea ice extent at the monthly level during the shipping season has been significantly decreasing (-3,193 km² mo⁻¹). Results also indicate that there are significant negative correlations between monthly ship traffic and sea ice extent, for all ship types (-0.50), commercial ships (-0.49), and non-commercial ships (-0.48). At the global scale, ship traffic is increasing while ship accident rates are decreasing (Objective 3). For the global Arctic there are positive statistically significant trends for all ship traffic (+2.655 million nm yr⁻¹), commercial ships (+1.598 million nm yr⁻¹), and non-commercial ships (+1.446 million nm yr⁻¹); where there are statistically significant annual decreases in ship accident rates for all ships (-3.64E-07 ship accidents/nm yr⁻¹), commercial ships (-9.39E-07 ship accidents/nm yr⁻¹), and non-commercial ships (-1.19E-07 ship accidents/nm yr⁻¹). At the country level, ship traffic associated to Russia, Norway, and Iceland contributes the most to global increase for both commercial and non-commercial ships. Norway has the largest statistically significant negative trend for all ship and commercial ship accident rates. Future research should focus around expanding on the analytical approach taken for objective 3, as more years of AIS data become available, as currently, the focus is on a shorter time-period (2012 to 2019). Given that incident rates are low globally, for high impacts (i.e., large spills), working with a long time series allows for considering more incidents. It would also be beneficial to perform an analysis that determines if there are statistical associations between yearly accident rates and sea ice extent in the global Arctic, as well as for each country within the Arctic. This information can help to answer questions around ship safety in the global Arctic, specifically: (a) Has the shipping become safer (e.g., less accidents per distance sailed) for the global Arctic and the countries within the Arctic? (b) Are there statistical associations between sea ice extent and accident rates within the global Arctic and the countries within the Arctic? (c) Are there countries associated with a higher incident rate compared to others? This information would help target measures to specific country ships that may be less safe for navigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".