Managing the moisture content of wood biomass for the optimisation of Ireland's transport supply strategy to bioenergy markets and competing industries

Sosa, Amanda; Acuña, Mauricio; McDonnell, Kevin; Devlin, Ger

doi:10.1016/j.energy.2015.04.032

Cited by 32 publications

(15 citation statements)

References 36 publications

(50 reference statements)

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“…A fall in MC from 55% to 40% resulted in lower total transportation costs in all the biomass facility location scenarios analyzed. This confirms the results from previous studies, which have identified MC as one of the most important factors affecting the calorific value and transportation costs in biomass supply chains [49][50][51][52][53][54][55]. Thus, MC and transport distance constitute the factors with the major impacts on the biomass transportation efficiency from harvesting sites to biomass facilities [46,56].…”

Section: Biomass Supply Chain Costs In Tasmaniasupporting

confidence: 88%

Optimizing the Location of Biomass Energy Facilities by Integrating Multi-Criteria Analysis (MCA) and Geographical Information Systems (GIS)

Woo

Acuña

Moroni

et al. 2018

Forests

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Internationally forest biomass is considered to be a valuable renewable energy feedstock. However, utilization of forest harvesting residues is challenging because they are highly varied, generally of low quality and usually widely distributed across timber harvesting sites. Factors related to the collection, processing and transport impose constraints on the economic viability of residue utilization operations and impact their supply from dispersed feedstock locations. To optimize decision-making about suitable locations for biomass energy plants intending to use forest residues, it is essential to factor in these supply chain considerations. This study conducted in Tasmania, Australia presents an investigation into the integration of Multi-criteria analysis (MCA) and Geographical Information systems (GIS) to identify optimal locations for prospective biomass power plants. The amount of forest harvesting biomass residues was estimated based on a non-industrial private native resource model in Tasmania (NIPNF). The integration of MCA and a GIS model, including a supply chain cost analysis, allowed the identification and analysis of optimal candidate locations that balanced economic, environmental, and social criteria within the biomass supply. The study results confirm that resource availability, land use and supply chain cost data can be integrated and mapped using GIS to facilitate the determination of different sustainable criteria weightings, and to ultimately generate optimal candidate locations for biomass energy plants. It is anticipated that this paper will make a contribution to current scientific knowledge by presenting innovative approaches for the sustainable utilization of forest harvest residues as a resource for the generation of bioenergy in Tasmania.

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Section: Biomass Supply Chain Costs In Tasmaniasupporting

confidence: 88%

Optimizing the Location of Biomass Energy Facilities by Integrating Multi-Criteria Analysis (MCA) and Geographical Information Systems (GIS)

Woo

Acuña

Moroni

et al. 2018

Forests

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“…The constraints of topography and other factors are not considered. (7) There are no quantitative restrictions on the tools and equipment used for harvesting, processing, and transportation, and the efficiency of use has no effect on green job hours, economic costs, or CO 2 emissions. (8) The daily wages of labor in different supply links are consistent.…”

Section: Model Assumptionsmentioning

confidence: 99%

“…Some studies have focused on the optimization of the economic benefits of the raw material supply chain. Because economic benefits can be represented by the cost of the raw material supply chain [7][8][9], these optimization strategies primarily focus on supply chain costs. Specifically, Sara et al (2004) analyzed the raw material procurement costs, storage costs, storage losses, transportation costs, and other aspects to determine how to reduce the supply chain cost of the raw materials for forest biomass power generation [10].…”

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confidence: 99%

Optimizing the Raw Material Supply Chain of the Wood Biomass Power Generation Industry for Different Stakeholders’ Benefits: An Analysis of Inner Mongolia, China

et al. 2020

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A large number of sand shrubs have been planted in western China, especially in Inner Mongolia. Sand shrubs produce a large amount of stump residue, and wood biomass power generation enterprises that use stump residue as raw materials have emerged in Wushen Banner and other areas. In this paper, the Mixed Integer Linear Programming (MILP) model is used to optimize the raw material supply chain of forest biomass power generation enterprises. Optimizations with different objectives represent the choices of different stakeholders. The optimization results are listed as follows. (1) The self-issuance behavior of enterprises is inconsistent with the enterprise behavior required by social planners; (2) When social planners only pay attention to environmental benefits, the utilization rate of raw materials in towns located far from a power plant will be greatly reduced, which is not conducive for the reuse of stump residue; (3) When social planners consider economic, environmental, and social benefits simultaneously, the utilization rate of raw materials in each town will be significantly improved, resources will be effectively utilized, and certain economic benefits will be realized; (4) It is possible to reduce the difficulty of achieving optimization goals by promoting industrial development and encouraging technological progress.

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“…Raw biomass usually has low energetic density, which causes it to lose competitiveness with fossil fuels (Sosa et al, 2015). To reduce this characteristic, the thermochemical conversion of biomass can be a viable alternative.…”

Section: Introduction and Objectivesmentioning

confidence: 99%

Impact of Wood Moisture in Charcoal Production and Quality

et al. 2020

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The charcoal production when performed in woods with high moisture content negatively impacts the pyrolysis and causes an increase of greenhouse emissions. The aim of this study was to investigate the effects of moisture on the production and quality of charcoal for the pig iron industry. The slow pyrolysis of Eucalyptus sp. was carried out in four different wood moistures, 0, 20, 40 and 60% (dry base). The charcoal and gas yield decreased according to the increase of wood moisture. On the other hand, the bio-oil yield and charcoal friability increased along with the moisture content. The proximate analysis, bulk density and higher heating value of the charcoal were not influenced by the moisture content. The use of wood with moisture content below 20% in the production of charcoal is an alternative to improve productivity, contributing for the economic sustanainability of this sector.

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Managing the moisture content of wood biomass for the optimisation of Ireland's transport supply strategy to bioenergy markets and competing industries

Cited by 32 publications

References 36 publications

Optimizing the Location of Biomass Energy Facilities by Integrating Multi-Criteria Analysis (MCA) and Geographical Information Systems (GIS)

Optimizing the Location of Biomass Energy Facilities by Integrating Multi-Criteria Analysis (MCA) and Geographical Information Systems (GIS)

Optimizing the Raw Material Supply Chain of the Wood Biomass Power Generation Industry for Different Stakeholders’ Benefits: An Analysis of Inner Mongolia, China

Impact of Wood Moisture in Charcoal Production and Quality

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