A simple rapid approach using coupled multivariate statistical methods, GIS and trajectory models to delineate areas of common oil spill risk

Guillen, George J.; Rainey, Gail; Morin, Mario

doi:10.1016/j.jmarsys.2003.11.006

Cited by 35 publications

(19 citation statements)

References 2 publications

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“…Enrichment factors for the fine sediment fraction (Galloway 1979) have been calculated for each metal to evaluate whether the metal concentrations can be considered as part of natural background or not. Extensive statistical analysis using ratio matching technique (Anders 1972;Poulton 1989;Villaescusa-Celaya et al 2000), hierarchical clustering, minimum spanning tree and principal component analysis have been performed on analytical data to assess the geographical distribution of pollutants and their relationships (Villaescusa-Celaya et al 2000;Ruiz 2001;Guillen et al 2004). …”

Section: Introductionmentioning

confidence: 99%

Distribution of Heavy Metals in Marine Sediments of Palermo Gulf (Sicily, Italy)

Tranchina

Basile

Brai

et al. 2008

Water Air Soil Pollut

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Concentrations of Cr, Cu, Hg, Pb and Zn have been measured, by atomic absorption spectrophotometry, in the fine fraction (<63 μm) of surface sediments collected in 30 sites in the Palermo Gulf (Sicily, Italy) in order to assess the levels and the spatial distribution of these elements. Enrichment factors calculated with respect to clean areas have been considered to discriminate between levels due to background or to pollution contributions. The sampling stations, which form a grid inside these areas, are characterized by geographic proximity and by the presence of pollution sources. Ratio matching technique along with hierarchical clustering, minimum spanning tree and principal component analysis have been used for the statistical analysis of data, allowing to better describe the spatial distribution of metal levels. Our work allowed to assess the anthropogenic contribution to the pollution of the area under investigation through industrial and domestic wastes, presence of an harbour area and river inflow.

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Section: Introductionmentioning

confidence: 99%

Distribution of Heavy Metals in Marine Sediments of Palermo Gulf (Sicily, Italy)

Tranchina

Basile

Brai

et al. 2008

Water Air Soil Pollut

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“…3, defining the north direction as positive). Wind speed less than 3 m/s will also induce dark areas in SAR (Synthetic Aperture Radar) image, which were likely to affect the accurate detection of oil spill by remote sensing method [23,24]. Hence it further resulted in less validation of oil spill simulation.…”

Section: Resultsmentioning

confidence: 99%

Modelling of oil spill trajectory for 2011 Penglai 19-3 coastal drilling field, China

Liu

Guo

et al. 2015

Applied Mathematical Modelling

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“…Using Lagrangian passive tracer transport simulations Chrastansky and Callies (2009) analyzed the effects of chronic oil pollution along the German North Sea coast. Guillen et al (2004) used the Oil Spill Risk Analysis model to identify areas at risk from oil spills in the Gulf of Mexico. Deng et al (2013b) conducted sixteen simulation experiments for four potential oil spills linked to offshore oil drilling fields in the Chinese Bohai Sea.…”

Section: Introductionmentioning

confidence: 99%

Assessing pollution-related effects of oil spills from ships in the Chinese Bohai Sea

Liu

Guo

Wang

et al. 2016

Marine Pollution Bulletin

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An analysis of the effects of potential oil spills will provide data in support of decisions related to improving the response to oil spills and its emergency management. We selected the Chinese Bohai Sea, especially the Bohai Strait, as our investigation region to provide an assessment of the effects of pollution from ship-related oil spills on adjacent coastal zones. Ship-related accidents are one of the major factors causing potential oil spills in this area. A three dimensional oil transport and transformation model was developed using the Estuary, Coastal, and Ocean Model. This proposed model was run 90 times and each run lasted for 15 days to simulate the spread and weathering processes of oil for each of four potential spill sites, which represented potential sites of ship collisions along heavy traffic lanes in the Bohai Sea. Ten neighboring coastal areas were also considered as target zones that potentially could receive pollutants once oil spilled in the study areas. The statistical simulations showed that spills in winter were much worse than those in summer; they resulted in very negative effects on several specific target zones coded Z7, Z8, Z9, and Z10 in this paper. In addition, sites S3 (near the Penglai city) and S4 (near the Yantai city) were the two most at-risk sites with a significantly high probability of pollution if spills occurred nearby during winter. The results thus provided practical guidelines for local oil spill prevention, as well as an emergency preparedness and response program.

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A simple rapid approach using coupled multivariate statistical methods, GIS and trajectory models to delineate areas of common oil spill risk

Cited by 35 publications

References 2 publications

Distribution of Heavy Metals in Marine Sediments of Palermo Gulf (Sicily, Italy)

Distribution of Heavy Metals in Marine Sediments of Palermo Gulf (Sicily, Italy)

Modelling of oil spill trajectory for 2011 Penglai 19-3 coastal drilling field, China

Assessing pollution-related effects of oil spills from ships in the Chinese Bohai Sea

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