LCA and Linear Programming for the Environmental Optimization of Waste Management Systems: A Simulation

Tascione, Valentino; Mosca, Raffaele; Raggi, Andrea

doi:10.1007/978-3-319-03826-1_2

Cited by 2 publications

(8 citation statements)

References 3 publications

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“…This study calculated CF as described in the literature (Table II). Since some models are inapplicable to the interior design industry in Taiwan, this investigation presented a model based on the models and parameters developed by Benjaafar et al (2013), Pishvaee et al (2009), Chen et al (2013), and Tascione et al (2014). The model proposed by Tascione et al (2014) not only calculates the carbon emission but also other gases.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The authors also discussed the decision to minimize the carbon emission. Tascione et al (2014) analyzed the carbon emission of the delivery of waste. CF helps a company to understand how RL can protect the environment.…”

Section: Introductionmentioning

confidence: 99%

“…In summary, this study calculates the CF of RL and designs a model based on carbon emissions data for RL in the interior design sector as reported in the research works of Benjaafar et al (2013), Chen et al (2013), and Pishvaee et al (2009, 2010). The model of Tascione et al (2014) not only discussed the carbon emissions, but also methane and nitrogen oxide emissions. In this study, the model developed in Tascione et al (2014) was only used to calculate carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

“…The model of Tascione et al (2014) not only discussed the carbon emissions, but also methane and nitrogen oxide emissions. In this study, the model developed in Tascione et al (2014) was only used to calculate carbon emissions. In sum, this study surveyed 40 participants in the reverse flow of the interior design industry in the north and mid-south of Taiwan.…”

Section: Introductionmentioning

confidence: 99%

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Carbon footprint model for reverse logistics of waste disposal in interior design industry

Liang

Lee

2018

APJML

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Purpose Due to the increasing awareness of the need to protect the environment, reverse logistics (RL) is being promoted to improve the ecological sustainability of production. RL can lower the costs of waste disposal, increase market competitiveness, and maintain a good corporate image. Hence, modern companies are focusing on environmental protection to demonstrate social responsibility. According to the OECD report of 2003, buildings consume 32 percent of resources, 12 percent of water, and 40 percent of energy worldwide, and the building waste comprises almost 40 percent of the all waste in the world. Therefore, controlling waste from the interior design sector may help slow global warming. This paper aims to discuss these issues. Design/methodology/approach This investigation models the current and new RL of disposing interior design waste in Taiwan. Modeling the carbon footprint (CF) of disposing interior design waste can help companies be aware of the environmental impact of disposing of waste, and how to improve it through RL. This investigation models the CFs of disposing interior design waste based on studies from Benjaafar et al. (2013), Pishvaee et al. (2009, 2010), and Tascione et al. (2014). Findings Analytical results showed that the RL significantly decreases the environmental impact of wastes. Companies can control carbon emission through the findings of this study and find how to improve their recycling process through RL. Research limitations/implications This study used the model proposed by Tascione et al. (2014) to develop an RL model for Taiwan. Whereas most studies in the literature analyze the carbon emissions from the comparison between cost and benefit, this study considered the logistics for the whole lifecycle of a product. The analytical results of this study reveal that that RL can reduce the environmental impact of wastes. This case study is the first to obtain results that can be extended to other countries. This study also reveals the importance of recycling plants that can process demolition waste for reuse. Originality/value This is the first study to model the RL based on literatures. The findings of this study can be extended to other cases.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Carbon footprint model for reverse logistics of waste disposal in interior design industry

Liang

Lee

2018

APJML

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“…Previously, numbers of MSW-management models were developed by using linear programming (LP) methods [6][7][8][9][10][11][12]. For example, Anderson and Nigam [6] firstly proposed an optimization model for a solid waste management system.…”

Section: Introductionmentioning

confidence: 99%

FCVLP: A Fuzzy Random Conditional Value-at-Risk-Based Linear Programming Model for Municipal Solid Waste Management

Wang

Kong

Zhao

et al. 2019

Climate

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A fuzzy random conditional value-at-risk-based linear programming (FCVLP) model was proposed in this study for dealing with municipal solid waste (MSW) management problems under uncertainty. FCVLP improves upon the existing fuzzy linear programming and fuzzy random conditional value-at-risk methods by allowing analysis of the risks of violating constraints that contain fuzzy parameters. A long-term MSW management problem was used to illustrate the applicability of FCVLP. The optimal feasibility solutions under various significance risk levels could be generated in order to analysis the trade-offs among the system cost, the feasibility degree of capacity constraints, and the risk level of waste-disposal-demand constraints. The results demonstrated that (1) a lower system cost may lead to a lower feasibility of waste-facility-capacity constraint and a higher risk of waste-disposal-demand constraint; (2) effects on system cost from vague information in incinerator capacity inputs would be greater than those in landfill capacity inputs; (3) the total allowable waste allocation would vary significantly because of the variations of risk levels and feasibility degrees. The proposed FCVLP method could be used to identify optimal waste allocation scenarios associated with a variety of complexities in MSW management systems.

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LCA and Linear Programming for the Environmental Optimization of Waste Management Systems: A Simulation

Cited by 2 publications

References 3 publications

Carbon footprint model for reverse logistics of waste disposal in interior design industry

Carbon footprint model for reverse logistics of waste disposal in interior design industry

FCVLP: A Fuzzy Random Conditional Value-at-Risk-Based Linear Programming Model for Municipal Solid Waste Management

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