Abstract: This paper assesses unintentional interference between different public policies promoting energy efficiency and renewable energy. The paper develops a methodology to study the interference by analysing the economic and technical behaviour of a hybrid energy system. The hybrid energy system in this case consists of an existing cogeneration unit extended with a new installation of thermal solar panels. This puts two complementary heating technologies in juxtaposition. The two technologies are supported with distinct regional support instruments in each region. The design and operation of the energy system is optimised from the point of view of the investor according to the different support instruments. The optimal configuration is analysed as well as its effect on reduced CO2-emissions during the lifetime of the project. The methodology is applied to a case-study for two neighbouring regions, the Netherlands and Flanders. The policies in the Netherlands show a beneficial synergy. In Flanders, the hybrid energy system is not interesting, indicating unbalanced high support for cogeneration in this case. From the point of view of the authorities, a more balanced regional policy as in the Netherlands provides a larger CO2-emission reduction for a smaller cost. (C) 2012 Elsevier Ltd. All rights reserved.

Abstract: Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.

Abstract: Transition projects have been implemented for Flemish agriculture since 2003, but these did not enable a transformation of the agricultural sector. This paper looks at pre-transition scenarios that have been collectively designed by stakeholders of the agricultural sector in 2002. These foresaw decreases in the regional animal stocks in Flanders. However, the real evolution of the sector did not reveal such a decrease. It is assumed that the individual adaptive behaviour of farmers can explain the unexpected stability of the Flemish agricultural sector. A detailed agent-based model has been built to replicate the past evolution, accounting for structural diversity of farmers, heterogeneity in behaviour, and natural resource constraints. The results indicate that different forms of rigidity in the individual behaviour of farmers slow down the adaptation of the agricultural sector. Future transition scenarios should account for these elements in order not to overestimate the speed of change in the sector. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Innovative bioenergy projects show a growing diversity in biomass pathways, transformation technologies and end-products, leading to complex new processes. Existing energy-based indicators are not designed to include multiple impacts and are too constrained to assess the sustainability of these processes. Alternatively, indicators based on exergy, a measure of “qualitative energy”, could allow a more holistic view. Exergy is increasingly applied in analyses of both technical and biological processes. But sustainability assessments including exergy calculations, are not very common and are not generally applicable to all types of impact. Hence it is important to frame the use of exergy for inclusion in a sustainability assessment. This paper reviews the potentials and the limitations of exergy calculations, and presents solutions for coherent aggregation with other metrics. The resulting approach is illustrated in a case study. Within the context of sustainability assessment of bioenergy, exergy is a suitable metric for the impacts that require an ecocentric interpretation, and it allows aggregation on a physical basis. The use of exergy is limited to a measurement of material and energy exchanges with the sun, biosphere and lithosphere. Exchanges involving services or human choices are to be measured in different metrics. This combination provides a more inclusive and objective sustainability assessment, especially compared to standard energy- or carbon-based indicators. Future applications of this approach in different situations are required to clarify the potential of exergy-based indicators in a sustainability context. (C) 2013 Elsevier Inc. All rights reserved.

Abstract: Being confronted with increasing and expanding urbanisation and the loss of natural green spaces, our living environment is threatened more and more by the effects of global climate change. Green infrastructure is often thought of as the solution to increase climate resilience and reinforce the quality of the lived environment simultaneously. While the benefits, or ecosystem services, that are generated through green infrastructure have been studied intensively, forces that influence green infrastructure decision-making have been far less subjected to thorough research. In this study a discrete choice experiment was conducted with local decision makers in Flemish municipalities to reveal crucial factors in the decision process applied to green infrastructure projects. Flanders is one of the most densely built regions in Europe, stressing the urgency to understand local spatial decision factors to guarantee green space. 568 decision makers active in the local administration of 235 Flemish municipalities participated in the experiment, set in a hypothetical neighbourhood park. Every choice alternative exists of five attributes: investment cost, maintenance cost, deferred investment, recreational value, and climate impact. We find that barriers hampering Flemish munipalities' GI implementation, differ over size of the municipality: smallers municipalities are more affected by knowledge gaps, while larger municipalities are experiencing prioritization issues. Results from hierarchical Bayes choice models indicate that municipal decisions on green infrastructure are highly – almost solely -cost-driven, rarely consider the full range of benefits, and centre around short-term and immediate arguments. Moreover, interaction models reveal that a municipalities' financial result is a key determinant of its willingness to invest in public greening and consider long term benefits, suggesting that GI is a luxury good. The results expose some of the heuristics in GI decision making and can be used to inform higher authorities on ways to overcome barriers towards informed decision-making and to facilitate GI investment.

Abstract: Environmental effects and natural resources depletion associated with agriculture production affect the agriculture response to climate change. Traditional cross-sectional climate response models ignore this requirement. This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. We correct farm income by accounting for resources (energy, fertilisers, pesticides, and water) use intensity and calculate the sustainable value for a sample of 9497 specialized field crop farms. Compared with the traditional Ricardian method, the marginal effects of temperature remain positive (but less positive) in Northern countries, while it leads to less damages in Southern countries when net revenue and farms? sustainable values are used as dependent variables. Accounting for the environmental effects and depletion of natural capital improves the ability of the Ricardian method to estimate agriculture climate response functions in the long run.

Abstract: An important issue in biodiversity valuation is gaining a better understanding of how biodiversity conservation affects economic activities and human welfare. Quantifying the economic benefits of biodiversity for human well-being is not straightforward. Here, we expand the ecosystem service cascade by (i) attributing a methodology to the different steps of the cascade to assess the effects of changes in functional group diversity on economic activities; (ii) including multiple attributes for defining functional diversity and (iii) integrating a dynamic ecological model simulating complex interactions and feedbacks between species with an economic model assessing the effects of changes in functional group diversity for gross revenues. The stepwise methodological framework integrates a production function approach with a market price-based approach in order to investigate the indirect use value of functional group diversity based on the ecological role of species in the ecosystem. The methodology is applied to estimate the relationship between the gross economic value of Chinook salmon (Pacific Northwest, United States) and the diversity of freshwater macroinvertebrates. The results of our analysis emphasize the importance of biological diversity for sustaining ecosystem goods and services. The analysis provides a tractable framework for quantitatively exploring the economic consequences of changes in functional group diversity.

Abstract: The Sustainable Value approach integrates the efficiency with regard to environmental, social and economic resources into a monetary indicator. It gained significant popularity as evidenced by diverse applications at the corporate level. However, its introduction as a measure adhering to the strong sustainability paradigm sparked an ardent debate. This study explores its validity as a macroeconomic strong sustainability measure by applying the Sustainable Value approach to the EU-15 countries. Concretely, we assessed environmental, social and economic resources in combination with the GDP for all EU-15 countries from 1995 to 2006 for three benchmark alternatives. The results show that several countries manage to adequately delink resource use from GDP growth. Furthermore, the remarkable difference in outcome between the national and EU-15 benchmark indicates a possible inefficiency of the current allocation of national resource ceilings imposed by the European institutions. Additionally, by using an effects model we argue that the service degree of the economy and governmental expenditures on social protection and research and development are important determinants of overall resource efficiency. Finally, we sketch out three necessary conditions to link the Sustainable Value approach to the strong sustainability paradigm. (C) 2011 Elsevier B.V. All rights reserved.

Abstract: A major objective of European agricultural policy is to have a sustainable and efficient farming sector that is applying environmentally-friendly production methods. Policy makers aim to combine a strong economic performance and a sustainable use of natural resources. Therefore, it is important to measure and to assess farm sustainability. For a large dataset of Flemish dairy farms, a valuation method that is based on the concept of opportunity costs is used to calculate and analyze differences among the sample farms with respect to the creation of sustainable value. But more important than measuring the creation of sustainable value is to analyze differences in sustainable efficiency. Therefore, sustainable efficiency measures are calculated and differences in sustainable efficiency are explained. Using panel data, an effect model captures the determinants of sustainable efficiency of the studied farms. The empirical model shows that, in general, larger farms have a higher sustainable efficiency. Also farmer's age and dependency on support payments proved to be determining characteristics for observed differences in sustainable efficiency.

Abstract: The bioeconomy is a shared vision for a future European industry entirely based on organic matter. Authorities support this technological development with subsidies and policies stimulating R&D. One major limitation for the bioeconomy is that R&D and industrial growth require the continuous availability of biomass as a primary resource. This resource dependence is already present during the formative years of new biobased innovations and influences the pilot and demonstration phase of the development. Traditionally, it is assumed that public support for pilot and demonstration initiatives may overcome this hurdle. In this paper, we investigate how this resource constraint limits the effectiveness of bioeconomy policies. The future development of the biobased sector is simulated including the inherent dependence of industrial activity on biomass. We simulate the future growth and technological diversity of an emerging biotechnological sector: the sector of manure transformation in Belgium. The paper reports the evolutions for three policy scenarios. The model explicitly accounts for endogenous innovation and knowledge transfer mechanisms. The results show that policies may have an important impact on the sector structure in the long run, but the sector growth remains ultimately constrained by the availability of inputs. So bioeconomy policies to promote innovation will be less effective, unless mechanisms are included to alleviate the resource constraint.

Abstract: Phytoremediation could be a sustainable remediation alternative for conventional remediation technologies. However, its implementation on a commercial scale remains disappointing. To emphasize its sustainability, this paper examines whether and how the potential economic benefit of CO2 abatement for different crops used for phytoremediation or sustainable land management purposes could promote phytotechnologies. Our analysis is based on a case study in the Campine region, where agricultural soils are contaminated with mainly cadmium. We use Life Cycle Analysis to show for the most relevant crops (willow (Salix spp), energy maize (Zea mays), and rapeseed (Brassica napus)), that phytoremediation, used for renewable energy production, could abate CO2. Converting this in economic numbers through the Marginal Abatement Cost of CO2 ( 20 ton−1) we can integrate this in the economic analysis to compare phytoremediation crops among each other, and phytoremediation with conventional technologies. The external benefit of CO2 abatement when using phytoremediation crops for land management ranges between 55 and 501 per hectare. The purpose of these calculations is not to calculate a subsidy for phytoremediation. There is no reason why one would prefer phytoremediation crops for renewable energy production over normal biomass. Moreover, subsidies for renewable energy already exist. Therefore, we should not integrate these numbers in the economic analysis again. However, these numbers could contribute to making explicit the competitive advantage of phytoremediation compared to conventional remediation technologies, but also add to a more sustainably funded decision on which crop should be grown on contaminated land.

Abstract: Development of a clear understanding of the relationship between the availability of dam-driven irrigation water and crop revenue is important in poverty reduction and food security process. As a result, large research efforts are devoted to understanding the relationship between the availability of irrigation water and crop revenue. However, earlier studies do have several limitations. For example, without considering its indirect effect, prior studies focused solely on the direct effect of availability of irrigation water on crop revue. In this study, using a structural equation model analysis, the direct and indirect effect of availability of dam-driven irrigation water on crop revenue is decomposed and quantified specifically for the Koga irrigation scheme, located in the Mecha district of Amhara region in Ethiopia. A primary data set was collected from a randomly selected sample of 450 households in the Koga irrigation scheme. More than half of the households (254) are supported by the Koga Dam irrigation water during the dry season, and the other 196 households depended only on rainfall. The results of the study showed that, in addition to its direct effect, the availability of irrigation water indirectly affected crop revenue through receptivity of the farmers to use modern farm inputs. Around 27 percent of the total effect of dam-driven irrigation water on crop revenue was mediated by farmers’ receptivity to use yield-enhancing modern farm inputs. The results of this study suggested that the availability of irrigation water is essential to improve both crop revenue and receptivity of the farmers to use modern farm inputs. This finding also drives a strategic framework that the receptivity of the farmers to use modern farm inputs is crucial for utilizing the positive effects of irrigation water availability on crop revenue.

Abstract: Several indicators and methods are already applied for sustainability assessment in agriculture. The links between sustainability indicators, agricultural management and policies are not well explained. The aim of this study is to combine biophysical and monetary sustainability assessment tools to support agriculture policy decision-making. Three methodological steps are considered: i) the environmental impacts of farms are assessed using terrestrial acidification, freshwater eutrophication, soil and freshwater ecotoxicity as well as natural land transformation; ii) the most relevant indicators of agriculture damages on ecosystems quality are aggregated into an index; iii) the farms' index scores are integrated with farm assets, land and labor, into the Sustainable Value approach (SVA), as indicator of natural resources used by farms. As a case study, the methodology was applied to arable farms with and without animal husbandry of the “Alta Murgia” National Park. The crop farms, in our sample, have a higher sustainable value using their economic and environmental resources. Mixed farms need to improve their resources use efficiency. Although crop farms have lower land-use efficiency compared to mixed farms, our results suggest supporting, by means of policy options, the specialized crop farms that, on average, perform better in terms of ecosystems quality preservation. Finally, we find that Life Cycle Assessment (LCA) to soundly measure the environmental impacts clearly enriches the SVA. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: Farms contribute heavily to overall sustainability. To date, various frameworks, approaches, methods and indicators have been developed to appraise how much corporations (firms, farms) contribute to sustainability. Among these, the Sustainable Value (SV) method helps to determine by which economic entity resources should be used in order to achieve the highest contributions to sustainability, by comparing company's efficiency of capital use against the efficiency of a benchmark. In this work we argue that the SV benchmark does not include certain crucial environmental concepts, such as the carrying capacity of an ecosystem or the multiple vital functions provided by ecosystem services. Thus, it is not a suitable reference for companies to evaluate their contribution to sustainability. As an alternative benchmark to standard SV applications, we propose a farm whose resource use productivity is correlated to the fulfilment of pre-determined environmental constraints: the Environmentally Sustainable Farm (ESF). To design this farm, we created an agro-environmental farm modelling framework that includes: (i) methods and approaches to assess indicators concerning specific environmental issues; (ii) an integrated ecological-economic model based on linear programming. This farm modelling framework is employed to determine both the environmental performance and the economic returns of two farming systems, conventional (CFS) and organic (OFS), which are compared using the Sustainable Value approach. Despite the fact that the OFS environmentally outperforms the CFS, none of them reaches the sustainable performances achieved by the ESF, both performing a negative Sustainable Value. The environmental constraints forced the ESF towards management choices that, although decreasing the economic performance, increase its environmental sustainability behaviour. Hence, the ESF is a viable benchmark that can be used to evaluate llllfarms' environmental sustainability. (C) 2015 Elsevier Ltd. All rights reserved.

Abstract: Assumptions on the perceptions of risks, made in agricultural economics literature, are recognized to be over-simplistic. For example most studies assume that risks are independent and static, while in reality most risks are interlinked and dynamic. We propose an alternative method to identify and present risk perception, closer to the actual comprehension of risk by farmers. Grounded theory is used to investigate the perceptions of risk by farmers while avoiding prior assumptions. Main findings are: (i) farmers have difficulty to rank or score probability and impact of risks in a (semi)quantitative manner; (ii) farmers attach different meanings to risk, when the focus shifts between, uncertain event, probability or value at stake and; (iii) farmers perceive risks as being interrelated. Based on these findings, we propose that farmers' risk perception can be best understood as a network of interrelated notions of uncertain events, their effects and uncertain outcomes. Furthermore, cognitive mapping is suggested to elucidate and present these networks. We test cognitive mapping, exploring dairy farmers' risk perception, and demonstrate the appropriateness of this methodology for capturing the complexity and context of perceived risk. Advantages are: (i) the qualitative approach, (ii) the focus on interrelations and context, (iii) the applicability at farm level, (iv) the farmer-driven rather than researcher-driven perspective, and (v) the elucidation of the polyvalent use of the risk concept. Cognitive maps can be used as a communication tool, a risk management tool, and a tool to stimulate bi-directional learning amongst farmers, policy makers, researchers and extension agents. (C) 2013 Elsevier Ltd. All rights reserved.