Oil spill risk assessment for a Single Buoy Mooring terminal in the Port of Taranto (Southern Italy)
Bibliographic record
Abstract
<p>Being situated in a semi-enclosed Mediterranean lagoon, the Port of Taranto represents a transport, industrial and commercial hub, where the port infrastructure, a notorious steel plant, oil refinery and naval shipyards coexist with highly-dense urban zone, recreation facilities, mussel farms, and vulnerable environmental sites. A Single Buoy Mooring in the center of the Mar Grande used by tankers and subsea pipeline that takes oil directly from tanker to refinery are assumed to stay at risk of accidental oil spills, despite significant progress in technology and prevention.</p><p>The oil spill model MEDSLIK-II (http://medslik-ii.org) coupled to the high resolution Southern Adriatic Northern Ionian coastal Forecasting System (SANIFS http://sanifs.cmcc.it Federico et al., 2017) is used to model hypothetical oil spill scenarios in stochastic mode. 15,000+ hypothetical individual spills are generated from randomly selected start locations: 50% from a buoy and 50% along the subsea pipeline 2018–2020. Individual spill scenario is based on a real crude oil spill caused by a catastrophic pipeline failure happened in Genoa in April 2016 (Vairo et al., 2017). The model outputs are processed statistically to represent quantitively: (1) timing of the oil drift; (2) hazard maps in probability terms at the sea surface and on the coastline; (3) oil mass balance; (4) local-zone contamination assessment.</p><p>The simulations reveal that around 48% of the spilled oil will evaporate during the first 8 hours after the accident. Being transported by highly variable currents and waves, the rest is additionally exposed to multiply reflections from sea walls and concrete wharfs that dominate in the study area. As a result, the oil will be dispersed almost isotropically in the Mar Grande, indicating a rather moderate or small level of concentrations over the minimum threshold values (French McCay, 2016).</p><p>We have concluded that at a probability of 50%, the first oil beaching event will happen within 14 hours after the accident. The most contaminated areas are predicted on and around the nearest Port berths, on the coastlines of the urban area and on the tips of the breakwaters that frame the Mar Grande openings. The remote areas of the West Port and Mar Piccolo are expected to be the least contaminated ones.</p><p>Results are applicable to contingency planning, ecological risk assessment, cost-benefit analysis, and education.</p><p>This work is conducted in the framework of the IMPRESSIVE project (#821922) co-funded by the European Commission under the H2020 Programme.</p><p>References</p><p>Federico, I., Pinardi, N., Coppini, G., Oddo, P., Lecci, R., Mossa, M., 2017. Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas. Nat. Hazards Earth Syst. Sci., 17, 45–59, doi: 10.5194/nhess-17-45-2017.</p><p>French McCay, D., 2016. Potential effects thresholds for oil spill risk assessments. Proc. of the 39 AMOP Tech. Sem., Environment and Climate Change Canada, Ottawa, ON, 285–303.</p><p>Vairo, T., Magrì, S., Qualgliati, M., Reverberi, A.P., Fabiano, B., 2017. An oil pipeline catastrophic failure: accident scenario modelling and emergency response development. Chem. Eng. Trans., 57, 373–378, doi: 10.3303/CET1757063.</p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".