The Experts below are selected from a list of 12264 Experts worldwide ranked by ideXlab platform

Ming Yang - One of the best experts on this subject based on the ideXlab platform.

  • an operational risk analysis tool to analyze Marine Transportation in arctic waters
    Reliability Engineering & System Safety, 2018
    Co-Authors: Bushra Khan, Faisal Khan, Brian Veitch, Ming Yang
    Abstract:

    Abstract The Arctic Ocean has drawn major attention in recent years due to its rich natural resources and shorter navigational routes. Arctic development and Transportation involve significant risk caused by the unique features of this region, such as ice, severe operating conditions, unpredictable climatic changes, and remoteness. Considering the high degree of uncertainty in the performance of vessel operating systems and humans, robust risk analysis and management tools are required to provide decision-support to prevent accidents and ensure safety at sea. This paper proposes an Object-Oriented Bayesian Network model to dynamically predict ship-ice collision probability based on navigational and operational system states, weather and ice conditions, and human error. The model, when integrated with potential consequences, may help estimate risk. A case study related to oil tanker navigation on the Northern Sea Route (NSR) is used to show the application of the proposed model to predict oil tanker collision with sea ice.

Michele Torregrossa - One of the best experts on this subject based on the ideXlab platform.

  • oil degrading bacteria from a membrane bioreactor bf mbr system for treatment of saline oily waste isolation identification and characterization of the biotechnological potential
    International Biodeterioration & Biodegradation, 2016
    Co-Authors: Simone Cappello, Anna Volta, Santina Santisi, Claudia Morici, Giuseppe Mancini, Paola Quatrini, Maria Genovese, Michail M Yakimov, Michele Torregrossa
    Abstract:

    A collection of forty-two (42) strains was obtained during microbiological screening of a Membrane Bioreactor (MBR) system developed for the treatment of saline oily waste originated from Marine Transportation. The diversity of the bacterial collection was analyzed by amplification and sequencing of the 16S rRNA gene. Taxonomic analysis showed high level of identity with recognized sequences of seven (7) distinct bacterial genera (Alcanivorax, Erythrobacter, Marinobacter, Microbacterium, Muricauda, Rhodococcus and Rheinheimera). The biotechnological potential of the isolates was screened considering an important factor such as the biosurfactant production. In particular fourteen (14) biosurfactant producing bacteria were selected and further tested, for growth on crude oil and hydrocarbon degradation. Data obtained from this study confirmed the high activity of bacteria related to genera Alcanivorax (isolates MBR-B11 and MBR-G10), Rheinheimera (isolates MBR-H02 and MBR-H05), Rhodococcus (isolates MBR-F04 and MBR-G05) and Muricauda (isolate MBR-G04) and underline the possible application of these bacteria in remediation of saline oily waste water.

  • biological approaches to the treatment of saline oily waste waters originated from Marine Transportation
    Chemical engineering transactions, 2012
    Co-Authors: Giuseppe Mancini, Simone Cappello, M M Yakimov, A Polizzi, Michele Torregrossa
    Abstract:

    Oily wastewater generated, in amounts of millions of tons per year, by ships mainly in engine-rooms (bilge waters) and by washing oil tanks (slops) create a major disposal problem throughout the world because of the persistence and accumulation of xenobiotic compounds in the environment. The high salinity levels (up to 25.000 p.p.m.) and the pollutants concentration limit the chances of discharge into the sewer systems and address the disposal of these waste(water)s to the sea. Tightening effluent regulations and consequent high energy and management costs has generated interest in the introduction of biological phases in the treatment of these wastewater. The objectives of this study were to evaluate the feasibility of using biological processes with purposely acclimated microorganism for the treatment of high salinity oily wastewaters (slops). Specifically both the bio-regeneration of the exhaust Granular Activated Carbons (GAC), loaded with a mixture of compounds occurring in slops, and a BioFilm Membrane BioReactor (BF-MBR) application were examined. Results proved the feasibility of using salt-adapted micro-organisms capable of degrading the main pollutants contained in slops.

Aaron T Gulliver - One of the best experts on this subject based on the ideXlab platform.

  • well to propeller environmental assessment of natural gas as a Marine Transportation fuel in british columbia canada
    Energy Reports, 2020
    Co-Authors: Babak Manouchehrinia, Zuomin Dong, Aaron T Gulliver
    Abstract:

    Abstract This paper examines the environmental impact of Natural Gas (NG) as a Transportation fuel, particularly for Marine Transportation use. The aim is to provide a systematic evaluation of Greenhouse Gas (GHG) emissions in the upstream fuel supply chain of NG fuel in British Columbia (BC), Canada. The recent introduction of Liquefied Natural Gas (LNG) fuel for ferry operations in western Canada presents a major step towards the large-scale adoption of NG as a cleaner and lower-cost fuel. This makes a systematic approach for accurate Lifecycle Assessment (LCA) of GHG emissions for the NG/LNG fuel more important and urgent. An analysis using operation and fuel consumption data from vessels with different engine technologies and types of fuel shows that the diesel cycle NG engine will produce 2% less CO 2e emissions in comparison to the low sulphur petroleum diesel engine, while other NG engine technologies, such as the lean-burn Otto cycle engine or dual-fuel gas engine, will result in 4% higher CO 2e emissions. This study clears doubts on well-to-pump (WTP) NG emissions, supports the wide adoption of NG fuel and promotes further pump-to-propeller (PTP) emission improvements in Marine propulsion.

James J. Corbett - One of the best experts on this subject based on the ideXlab platform.

  • Pollution Tradeoffs for Conventional and Natural Gas-Based Marine Fuels
    Sustainability, 2019
    Co-Authors: James J. Winebrake, James J. Corbett, Fatima Umar, Daniel Yuska
    Abstract:

    This paper presents a life-cycle emissions analysis of conventional and natural gas-based Marine Transportation in the United States. We apply a total fuel cycle—or “well-to-propeller”—analysis that evaluates emissions along the fuel production and delivery pathway, including feedstock extraction, processing, distribution, and use. We compare emissions profiles for methanol, liquefied natural gas, and low sulfur Marine fuel in our analysis, with a focus on exploring tradeoffs across the following pollutants: greenhouse gases, particulate matter, sulfur oxides, and nitrogen oxides. For our greenhouse gas analysis, we apply global warming potentials that consider both near-term (20-year) and long-term (100-year) climate forcing impacts. We also conduct uncertainty analysis to evaluate the impacts of methane leakage within the natural gas recovery, processing, and distribution stages of its fuel cycle. Our results indicate that natural-gas based Marine fuels can provide significant local environmental benefits compared to distillate fuel; however, these benefits come with a near-term—and possibly long-term—global warming penalty, unless such natural gas-based fuels are derived from renewable feedstock, such as biomass. These results point to the importance of controlling for methane leaks along the natural gas production process and the important role that renewable natural gas can play in the shipping sector. Decision-makers can use these results to inform decisions related to increasing the use of alternative fuels in short sea and coast-wise Marine Transportation systems.

  • regional economic and environmental analysis as a decision support for Marine spatial planning in xiamen
    Marine Policy, 2015
    Co-Authors: James J. Corbett, Wei Huang, Di Jin
    Abstract:

    Abstract The study explores the environmental input–output (EIO) model as a decision-support tool for Marine spatial planning at the regional level. Using empirical data, an EIO model is developed to examine the economic and environmental impacts associated with two leading ocean industries in Xiamen. Results of the study show that, under select economic and environmental scenarios, waterfront tourism is generally preferable to Marine Transportation in terms of unit environmental and resource effects. Thus, it is more beneficial for the region to promote the growth of the waterfront tourism sector.

  • Energy use and emissions from Marine vessels: a total fuel life cycle approach.
    Journal of The Air & Waste Management Association, 2012
    Co-Authors: James J. Winebrake, James J. Corbett, Patrick E. Meyer
    Abstract:

    Abstract Regional and global air pollution from Marine Transportation is a growing concern. In discerning the sources of such pollution, researchers have become interested in tracking where along the total fuel life cycle these emissions occur. In addition, new efforts to introduce alternative fuels in Marine vessels have raised questions about the energy use and environmental impacts of such fuels. To address these issues, this paper presents the Total Energy & Emissions Analysis for Marine Systems (TEAMS) model. TEAMS can be used to analyze total fuel life cycle emissions and energy use from Marine vessels. TEAMS captures “well-to-hull” emissions, that is, emissions along the entire fuel pathway, including extraction, processing, distribution, and use in vessels. TEAMS conducts analyses for six fuel pathways: (1) petroleum to residual oil, (2) petroleum to conventional diesel, (3) petroleum to low-sulfur diesel, (4) natural gas to compressed natural gas, (5) natural gas to Fischer-Tropsch diesel, and (6...

Faisal Khan - One of the best experts on this subject based on the ideXlab platform.

  • Marine Transportation risk assessment using bayesian network application to arctic waters
    Ocean Engineering, 2018
    Co-Authors: Alamin Baksh, Rouzbeh Abbassi, Vikram Garaniya, Faisal Khan
    Abstract:

    Maritime Transportation poses risks regarding possible accidents resulting in damage to vessels, crew members and to the ecosystem. The safe navigation of ships, especially in the Arctic waters, is a growing concern to maritime authorities. This study proposes a new risk model applicable to the Northern Sea Route (NSR) to investigate the possibility of Marine accidents such as collision, foundering and grounding. The model is developed using Bayesian Network (BN). The proposed risk model has considered different operational and environmental factors that affect shipping operations. Historical data and expert judgments are used to estimate the base value (prior values) of various operational and environmental factors. The application of the model is demonstrated through a case study of an oil-tanker navigating the NSR. The case study confirms the highest collision, foundering and grounding probabilities in the East Siberian Sea. However, foundering probabilities are very low in all five regions. By running uncertainty and sensitivity analyses of the model, a significant change in the likelihood of the occurrence of accidental events is identified. The model suggests ice effect as a dominant factor in accident causation. The case study illustrates the priority of the model in investigating the operational risk of accidents. The estimated risk provides early warning to take appropriate preventive and mitigative measures to enhance the overall safety of shipping operations.

  • an operational risk analysis tool to analyze Marine Transportation in arctic waters
    Reliability Engineering & System Safety, 2018
    Co-Authors: Bushra Khan, Faisal Khan, Brian Veitch, Ming Yang
    Abstract:

    Abstract The Arctic Ocean has drawn major attention in recent years due to its rich natural resources and shorter navigational routes. Arctic development and Transportation involve significant risk caused by the unique features of this region, such as ice, severe operating conditions, unpredictable climatic changes, and remoteness. Considering the high degree of uncertainty in the performance of vessel operating systems and humans, robust risk analysis and management tools are required to provide decision-support to prevent accidents and ensure safety at sea. This paper proposes an Object-Oriented Bayesian Network model to dynamically predict ship-ice collision probability based on navigational and operational system states, weather and ice conditions, and human error. The model, when integrated with potential consequences, may help estimate risk. A case study related to oil tanker navigation on the Northern Sea Route (NSR) is used to show the application of the proposed model to predict oil tanker collision with sea ice.