Biofuel supply chain design from Coffee Cut Stem under environmental analysis

Duarte, Alexandra Eugenia; Sarache, William; Costa, Yasel

doi:10.1016/j.energy.2016.01.076

Cited by 42 publications

(11 citation statements)

References 33 publications

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“…These applications consume only a fraction of the resources available [2]. Another portion is burned in cookstoves, in open fields or disposed on land until decomposition, deriving in health and environmental problems [11], still remaining untapped or inefficiently used [2,8,[10][11][12][13][14][15].…”

Section: International Context Of Coffee Productionmentioning

confidence: 99%

The potential of coffee stems gasification to provide bioenergy for coffee farms: a case study in the Colombian coffee sector

García-Freites

Welfle

Lea‐Langton

et al. 2019

Biomass Conv. Bioref.

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The coffee industry constitutes an important part of the global economy. Developing countries produce over 90% of world coffee production, generating incomes for around 25 million smallholder farmers. The scale of this industry poses a challenge with the generation of residues along with the coffee cultivation and processing chain. Coffee stems, obtained after pruning of coffee trees, are one of those abundant and untapped resources in the coffee supply chain. Their high lignocellulosic content, the low calorific value ranging between 17.5 and 18 MJ kg −1 and the low ash content make them a suitable solid fuel for thermochemical conversion, such as gasification. This research evaluates the feasibility of using these residues in small-scale downdraft gasifiers coupled to internal combustion engines for power and low-grade heat generation, using process modelling and the Colombian coffee sector as a case study. The producer gas properties (5.6 MJ Nm −3) and the gasifier's performance characteristics suggest that this gas could be utilized for power generation. A cogeneration system efficiency of 45.6% could be attainable when the system's low-grade heat is recovered for external applications, like in the coffee drying stage. An analysis of the energy demand and coffee stems availability within the Colombian coffee sector shows that the biomass production level in medium-to large-scale coffee farms is well matched to their energy demands, offering particularly attractive opportunities to deploy this bioenergy system. This work assesses the feasibility of providing coffee stem-sourced low-carbon energy for global coffee production at relevant operating scales in rural areas. Keywords Gasification. Coffee residues. Process modelling. Power and heat generation. Coffee sector. Energy demand Abbreviations CHP Combined heat and power CGE Cold gas efficiency daf Dry ash-free composition d.b. Dry-basis composition ER Equivalence ratio HGE Hot gas efficiency ICE Internal combustion engine LI Low income LMI Low-middle income LHV Low heating value MC Moisture content UMI Upper-middle income * Samira Garcia-Freites

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Section: International Context Of Coffee Productionmentioning

confidence: 99%

The potential of coffee stems gasification to provide bioenergy for coffee farms: a case study in the Colombian coffee sector

García-Freites

Welfle

Lea‐Langton

et al. 2019

Biomass Conv. Bioref.

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“…They addressed centralized and decentralized rubber-seed-processing facilities and showed that the selection of the rubber-processing plant is dependent on the volume of feedstock. Assessment of cost, energy, life cycle, and greenhouse-gas emissions from the forest-biomass harvesting and transportation stages have been studied by Zhang et al 24 and Zhang et al 25 Duarte et al 26 proposed a mathematical model to simultaneously optimize economic and environmental objectives in a bioethanol-SC network. They considered cut-coffee-stem feedstock for bioethanol production.…”

Section: Related Workmentioning

confidence: 99%

Application of Fuzzy Optimization to Bioenergy-Supply-Chain Planning under Epistemic Uncertainty: A New Approach

Babazadeh

2019

Ind. Eng. Chem. Res.

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Recently, finding sustainable solutions to deal with the environmental and social problems emerging from the combustion of fossil fuels in the transportation sector has attracted much interest. This paper proposes an integrated, multiperiod, mixed-integer, nonlinear programming model to design a biodiesel supply-chain network under uncertainty. To deal with the uncertainty of the parameters of the proposed model, a novel formulation of a possibilistic programming model based on possibilistic mean and absolute deviation of fuzzy numbers is proposed. The proposed model, called the possibilistic mean–absolute deviation model, utilizes not only the advantages of previous possibilistic programming methods, such as simultaneously handling the uncertainty and the flexibility in goals and constraints, but also balances mean and risk values of an objective function, including uncertain coefficients according to Decision-Maker’s (DM) preferences. A real case study is conducted in Iran to evaluate the performance and efficiency of the proposed model. The proposed approach has better performance than a pure possibilistic programming model, and its results are justified by the robust possibilistic programming approaches.

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“…They incorporated this social benefit into a multi-objective MILP model so as to maximize the social benefit, net present value, and greenhouse gas emission potential saving of the supply chain. In order to determine the optimal design of a sustainable biofuel supply chain from coffee cut stem, Duarte et al [31] proposed an MILP model in which a global objective function in terms of economic benefits and positive environmental balance is maximized. A number of researchers have coped with the uncertainty of the parameters in BSCND models.…”

Section: Literature Reviewmentioning

confidence: 99%

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

Babazadeh

Ghaderi

Pishvaee

2019

Computers & Chemical Engineering

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This paper proposes a possibilistic programming model in order to design a second-generation biodiesel supply chain network under epistemic uncertainty of input data. The developed model minimizes the total costs of the supply chain from supply centers to the biodiesel and glycerin consumer centers. Waste cooking oil and Jatropha plants, as non-edible feedstocks, are considered for biodiesel production. To cope with the epistemic uncertainty of the parameters, a credibility-based possibilistic programming approach is employed to convert the original possibilistic programming model into a crisp counterpart. An accelerated benders decomposition algorithm using efficient acceleration mechanisms is devised to deal with the computational complexity of solving the proposed model in an efficient manner. The performance of the proposed possibilistic programming model and the efficiency of the developed accelerated benders decomposition algorithm are validated by performing a computational analysis using a real case study in Iran.

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Biofuel supply chain design from Coffee Cut Stem under environmental analysis

Cited by 42 publications

References 33 publications

The potential of coffee stems gasification to provide bioenergy for coffee farms: a case study in the Colombian coffee sector

The potential of coffee stems gasification to provide bioenergy for coffee farms: a case study in the Colombian coffee sector

Application of Fuzzy Optimization to Bioenergy-Supply-Chain Planning under Epistemic Uncertainty: A New Approach

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

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