WEEE management in Europe and China – A comparison

Salhofer, Stefan; Steuer, Benjamin; Beigl, Peter

doi:10.1016/j.wasman.2015.11.014

Cited by 138 publications

(93 citation statements)

References 20 publications

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“…WEEE contains both hazardous and precious components, and is a rapidly growing waste stream [3][4][5]. The responsible collection and recycling of WEEE reduces environmental harm [6,7] and facilitates the recovery of valuable materials [8][9][10], including rare earth elements and other critical raw materials (e.g., indium and gallium) that are of vital importance for modern economies [11][12][13][14]. The recycling of WEEE is a complex task requiring an effective technical infrastructure and managerial framework [15,16], and it has potential to generate significant economic wealth from recovered rare and important metals [12,17,18].…”

Section: Introductionmentioning

confidence: 99%

The Link between e-Waste and GDP—New Insights from Data from the Pan-European Region

Kusch

Hills

2017

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Waste electrical and electronic equipment (WEEE) is difficult to sustainably manage. One key issue is the challenge of planning for WEEE flows as current and future quantities of waste are difficult to predict. To address this, WEEE generation and gross domestic product (GDP) data from 50 countries of the pan-European region were assessed. A high economic elasticity was identified, indicating that WEEE and GDP are closely interlinked. More detailed analyses revealed that GDP at purchasing power parity (GDP PPP) is a more meaningful measure when looking at WEEE flows, as a linear dependency between WEEE generation and GDP PPP was identified. This dependency applies to the whole region, regardless of the economic developmental stage of individual countries. In the pan-European region, an increase of 1000 international $ GDP PPP means an additional 0.5 kg WEEE is generated that requires management.

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Section: Introductionmentioning

confidence: 99%

The Link between e-Waste and GDP—New Insights from Data from the Pan-European Region

Kusch

Hills

2017

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“…where Γ and Ψ controls the size of the uncertainty sets, and can be represented as: Ψ ≤ Γ ≤ Ψ|J i |. When the formulation of uncertainty set U is as shown in constraint (7), the robust counterpart, constraint (6), will be converted into:…”

Section: Robust Optimizationmentioning

confidence: 99%

“…Hence, we calculate the payoff table (Table 2) by individually optimizing each objective function while calculating the value of another objective in the deterministic case. After obtaining the payoff table, we divide the ranges of the objective functions into four equal intervals, and five grid points are utilized (i.e., [6][7][8][9][10] as the values of ε 2 .…”

Section: Multi-objective Solution Mechanismmentioning

confidence: 99%

“…In 2002, the Waste Electrical and Electronic Equipment (WEEE) Directive [4,5], which is the first developed by the European Union, obliges original equipment manufacturers (OEMs) to collect scrapped products for subsequent recycling or reuse. Subsequently, similar policies are published in other countries such as the United States and China [6,7]. The incentive from customers also • A mixed integer programming (MIP) model is developed to design a CLSCN in which all three aspects of sustainability (i.e., economic, environmental, and social) are optimized concurrently.…”

Section: Introductionmentioning

confidence: 99%

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A Robust Fuzzy Optimization Model for Closed-Loop Supply Chain Networks Considering Sustainability

Zhang

Zhao

et al. 2019

Sustainability

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Supply chain network design (SCND) is an important strategic decision determining the structure of each entity in the supply chain, which has an important impact on the long-term development of a company. An efficient and effective supply chain network is of vital importance for improving customer satisfaction, optimizing the allocation of resources, and increasing profitability. The environmental concerns and social responsibility awareness of the whole society have spurred researchers and managers to design sustainable supply chains (SSCs) integrating the economic, environmental, and social factors. In addition, the innate uncertainty of the SCND problem requires an integrated method to cope. In this regard, this study develops a multi-echelon multi-objective robust fuzzy closed-loop supply chain network (CLSCN) design model under uncertainty including all three dimensions of sustainability. This model considers the total cost minimization, carbon caps, and social impact maximization concurrently to realize supply chain sustainability, and is able to make a balance between the conflicting multiple objectives. Meanwhile, the uncertainty of the parameters is divided into two categories and addressed with two approaches: the first category is missed working days related to social impact, which is solved by the fuzzy membership theory; the second category is the demand and remanufacturing rate, which is settled by a robust optimization method. To validate the ability and applicability of the model and solution approach, a numerical example is conducted and solved using ILOG CPLEX. The result shows that the supply chain network structure and the value of the optimization objectives will change when considering sustainability and different degrees of uncertainty. This will enable supply chain managers to reduce the environmental impact and enhance the social benefits of their supply chain activities, and design a more stable supply chain to better cope with the influence of uncertainty.

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“…Equation (4) ensures the capacity requirement of regional collection center is fulfilled in each scenario. Equations (5)- (10) are the flow balance constraints of the second-level transportation. Equation (11) guarantees the capacity of recycling plant is not exceeded in each scenario.…”

Section: Qtr S L Pmmentioning

confidence: 99%

A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE)

Solvang

2016

Sustainability

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Today, the increased public concern about sustainable development and more stringent environmental regulations have become important driving forces for value recovery from end-of-life and end-of use products through reverse logistics. Waste electrical and electronic equipment (WEEE) contains both valuable components that need to be recycled and hazardous substances that have to be properly treated or disposed of, so the design of a reverse logistics system for sustainable treatment of WEEE is of paramount importance. This paper presents a stochastic mixed integer programming model for designing and planning a generic multi-source, multi-echelon, capacitated, and sustainable reverse logistics network for WEEE management under uncertainty. The model takes into account both economic efficiency and environmental impacts in decision-making, and the environmental impacts are evaluated in terms of carbon emissions. A multi-criteria two-stage scenario-based solution method is employed and further developed in this study for generating the optimal solution for the stochastic optimization problem. The proposed model and solution method are validated through a numerical experiment and sensitivity analyses presented later in this paper, and an analysis of the results is also given to provide a deep managerial insight into the application of the proposed stochastic optimization model.

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WEEE management in Europe and China – A comparison

Cited by 138 publications

References 20 publications

The Link between e-Waste and GDP—New Insights from Data from the Pan-European Region

The Link between e-Waste and GDP—New Insights from Data from the Pan-European Region

A Robust Fuzzy Optimization Model for Closed-Loop Supply Chain Networks Considering Sustainability

A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE)

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