Bioenergy Decision Support Systems: Worth the Effort?

Wright, Daniel G.; Dey, Prasanta Kumar; Brammer, John; Hunt, Phil

doi:10.3384/ecp110579

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…Furthermore, there is a gap between existing Decision Support Systems (DSS) for management/monetary evaluation of forests and the requirements of end-users (Wright et al 2011). Bagstad et al (2013) completed a detailed literature review of existing DSS for assessing, quantifying, modeling, valuing and/or mapping ES.…”

Section: Introductionmentioning

confidence: 99%

A Decision Support System for trade-off analysis and dynamic evaluation of forest ecosystem services

Sacchelli¹

2018

iForest

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This paper presents an open-source Decision Support System (DSS) able to quantify the economic value of forest ecosystem services and their dynamic trade-offs. Provisioning, regulation and support services, as well as cultural services, can be evaluated by the model. Best management forestry practices can be identified by optimizing specific objective functions, e.g., maximizing the economic value or identifying the ideal rotation period. The model was applied to a silver fir (Abies alba Mill.) stand in central Italy as a case study. Results show the importance of economic parameters (e.g., discount rate) and management practices (e.g., presence/absence of silvicultural thinning) in defining forest values. The main strengths and weaknesses of the DSS are discussed in light of its potential for application in the sector of Payment for Ecosystem Services.

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Section: Introductionmentioning

confidence: 99%

A Decision Support System for trade-off analysis and dynamic evaluation of forest ecosystem services

Sacchelli¹

2018

iForest

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“…More recently, Yue and Yang (2007) expand DSS to incorporate costs, incentives, and return on investment for renewable energy in Taiwan. Addressing the practical relevance of bioenergy DSS, Wright et al (2011) found that 23.1 percent of their sample of bioenergy DSS had high practical applicability. If the main objective of developing a DSS is to help arrive at better decision-making, perhaps the practical application has to be an important characteristic.…”

Section: Dss Modelmentioning

confidence: 99%

Energy security for rural communities in the developing world

Blahnik

McGillivray

Prasad

et al. 2013

Int J of Energy Sector Man

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Purpose – The purpose of this paper is to demonstrate the viability of using bamboo hybrid fencing fertigated with grey water as a means of providing energy to rural communities in developing countries. Design/methodology/approach – The paper establishes such returns by developing a decision support system (DSS) model populated with parameters obtained from literature and field data. The DSS allows for a sensitivity analysis that examines the robustness of the hybrid bio-fencing under varying scenarios and the interactions among species, management, and technological variables. Findings – Critical variables identified include the technological efficiency, number of clumps per m2 planted and the influence of grey water on growth rates. Practical implications – In the developing countries, uncertainty abounds in rural “green” interventions. Such uncertainties can be quite problematic especially for marginal communities. This research provides developmental agents with the ability to derive specific economic and environmental returns by making decisions related to species type, managerial methods, grey water treatment and energy conversion technologies. The hybrid fencing provides villagers with security without depleting scarce resources for brick and mortar (“pukka”) walls. Furthermore, the hybrid bio-fencing provides significant positive energy and financial returns. Originality/value – The research demonstrates how green ventures can be audited across multiple dimensions of sustainability including economic, environmental and energy. The DSS developed here is a powerful tool as it not only provides an energy audit, but also simultaneously displays economic returns.

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“…In addition, even though several attempts for bioenergy chain optimization have been carried out (De Meyer et al, 2014), the implementation of a holistic analysis of impacts in local and global perspective and for current and future processes is a difficult task to define. Moreover, as affirmed by Wright et al (2011), a disparity between the existing model-oriented bio-energy DSS functions and what practitioners desire, exists. Lastly, it must be not forgotten that the agro-forestry territory is a mixed public/private good with a relevant production of social externalities (landscape, habitat for wildlife, etc.…”

Section: Introductionmentioning

confidence: 99%

Environmental and social sustainability and supply chain efficiency in the production of biomass energy

Sottini¹,

Bernetti²,

Cipollaro³

et al. 2015

Atti Del Secondo Congresso Internazionale Di Selvicoltura = Proceedings of the Second International Congress of Silviculture

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The aim of the paper is to present a coordinated framework of the researches conducted by GESAAF -Department of the University of Florence, with a specific regard to the environmental and socioeconomic sustainability of supply energy chains and local energy districts. The common feature of the researches is to provide a planning decision support able to considering the geographic variability of ecological, environmental and social characteristics of the territory. Modellisation of the analysed system was developed applying operational research based on multi-objective spatial analysis and optimization procedures. Conventional financial indicators and parameters to assess the best logistics of the chain were depicted in the evaluation. In addition, the researches introduced innovative performance indicators, such as the potential positive and/or negative impacts on ecosystem services, the trade-off between the production of residues for energy purposes and other wooded assortments and the analysis of acceptance of biomass plant by local stakeholders and the local community. Moreover, SensorWebEnergy technologies and computing platforms were developed not only to ensure the dissemination of technologies, results and technical and management experiences of supply chains, but also to ensure a constant monitoring of the production activities of the bioenergy chain. In other terms, Decision Support Systems, which are able to auto-calibrate in relation to the evolution of environmental, logistics and managerial parameters of the supply chains, were implemented.Keywords: wood-energy chain, sustainability, operational research, decision support systems. Parole chiave: filiera legno-energia, sostenibilità, ricerca operativa, sistemi di supporto alle decisioni.http://dx.doi.org/10.4129/2cis-va-env

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Bioenergy Decision Support Systems: Worth the Effort?

Cited by 4 publications

References 17 publications

A Decision Support System for trade-off analysis and dynamic evaluation of forest ecosystem services

A Decision Support System for trade-off analysis and dynamic evaluation of forest ecosystem services

Energy security for rural communities in the developing world

Environmental and social sustainability and supply chain efficiency in the production of biomass energy

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