Quantitative Pollution Spill Risk Assessment: Using A Gis-Based System

Federal and State agencies have recently advocated risk-based analysis as a mechanism for advancing regulatory reform and safety determination in marine systems. the present investigation promotes this objective through the development of risk-based environmental planning strategies for oil spill contingency plans. This alternative approach to contingency planning departs from conventional methodology by employing quantitative risk assessment methods to identify hazardous oil spill zones and sensitive environmental areas, R_o and R_e respectively. the product of this conversion is referenced on a single “Risk” layer within a Geographic Information System (GIS) framework allowing coastal managers to evaluate natural resource data with associated elements of oil spill risk. As a new tool for coastal pollution management, risk-based environmental planning strategies have shown potential for evolving more efficient oil spill contingency plans.     

Optimising reverse logistics network to support policy-making in the case of Electrical and Electronic Equipment

Due to the rapid growth of Waste Electrical and Electronic Equipment (WEEE) volumes, as well as the hazardousness of obsolete electr(on)ic goods, this type of waste is now recognised as a priority stream in the developed countries. Policy-making related to the development of the necessary infrastructure and the coordination of all relevant stakeholders is crucial for the efficient management and viability of individually collected waste. This paper presents a decision support tool for policy-makers and regulators to optimise electr(on)ic products’ reverse logistics network. To that effect, a Mixed Integer Linear Programming mathematical model is formulated taking into account existing infrastructure of collection points and recycling facilities. The applicability of the developed model is demonstrated employing a real-world case study for the Region of Central Macedonia, Greece. The paper concludes with presenting relevant obtained managerial insights.     

On the optimal design of the disassembly and recovery processes

This paper tackles the problem of the optimal design of the recovery processes of the end-of-life (EOL) electric and electronic products, with a special focus on the disassembly issues. The objective is to recover as much ecological and economic value as possible, and to reduce the overall produced quantities of waste. In this context, a medium-range tactical problem is defined and a novel two-phased algorithm is presented for a remanufacturing-driven reverse supply chain. In the first phase, we propose a multicriteria/goal-programming analysis for the identification and the optimal selection of the most ‘desirable’ subassemblies and components to be disassembled for recovery, from a set of different types of EOL products. In the second phase, a multi-product, multi-period mixed-integer linear programming (MILP) model is presented, which addresses the optimization of the recovery processes, while taking into account explicitly the lead times of the disassembly and recovery processes. Moreover, a simulation-based solution approach is proposed for capturing the uncertainties in reverse logistics. The overall approach leads to an easy-to-use methodology that could support effectively middle level management decisions. Finally, the applicability of the developed methodology is illustrated by its application on a specific case study.     

Quantitative Pollution Spill Risk Assessment: Using A Gis-Based System

Federal and State agencies have recently advocated risk-based analysis as a mechanism for advancing regulatory reform and safety determination in marine systems. the present investigation promotes this objective through the development of risk-based environmental planning strategies for oil spill contingency plans. This alternative approach to contingency planning departs from conventional methodology by employing quantitative risk assessment methods to identify hazardous oil spill zones and sensitive environmental areas, R_o and R_e respectively. the product of this conversion is referenced on a single “Risk” layer within a Geographic Information System (GIS) framework allowing coastal managers to evaluate natural resource data with associated elements of oil spill risk. As a new tool for coastal pollution management, risk-based environmental planning strategies have shown potential for evolving more efficient oil spill contingency plans.