Abstract: Biobased chemistry has gained interest and has the potential to tackle some of the sustainability challenges the chemical industry must endure. Sustainability impacts need to be evaluated and monitored to highlight the advantages and pitfalls of different biobased routes over the entire product life cycle. This study aims for expert consensus concerning indicators needed and preferred for sustainability analysis of biobased chemicals in Europe. Experts are consulted by means of a Delphi method with stakeholders selected from three core groups: the private, public and academic sector. Best-Worst Scaling (BWS) is performed to gather data on the prioritization of the sustainability indicators per respondent. Afterwards, Multi-Criteria Decision Analysis (MCDA) is used to develop a consensus ranking among the experts. The results show that GHG emissions, market potential and acceptance of biobased materials are deemed the most crucial indicators for respectively environmental, economic and social sustainability. Expert consensus is positive in all three sustainability domains, with the strongest consensus measured for environmental sustainability showing a median Kendalls τ of 0.63 (τ ranging from -1 to 1) and the weakest consensus found within social sustainability showing a median Kendalls τ of 0.50. Further research can apply the ranked indicators on specific case studies to evaluate the practicability of the defined indicator set.

Abstract: Bioremediation is a remediation strategy, which has considerable strength but also certain limitations. Complex and uncertain relationships among biomass, contaminants, and nutrients lead to an uncertain level of removal efficiency. The uncertainty inherent to a bioremediation strategy should be addressed in the remediation selection process. In order to evaluate the bioremediation strategy economically, this study takes into account the reversibility of a decision. A decision tree structures the different remediation strategies, thus giving the possible courses of action open to the decision maker. The option value indicates the importance of having the possibility to reverse a previously made decision. Compared with conventional economic evaluation tools, more information to ground the selection made is revealed.

Abstract: Buildings are responsible for 40% of our worldwide energy consumption and 50% of this energy is converted for Heating Ventilation Air Conditioning (HVAC) systems in buildings. The increasing share of renewable energy production required to make the transition towards a carbon neutral energy system challenges the stability of the grid. Through demand response it becomes possible to activate these systems in support of grid balancing. However, this flexibility is currently not rewarded in the market. We simulate a domestic water heater participating in the balancing of the electricity net and calculated the revenue from this action. We simulate a water heater in connection with an Economic Model Predictive Controller (EMPC) which takes future usage, energy cost, and reward for delivering balanced power into account. We show that the choice of an EMPC controller is valid as it allows the setpoint to change if certain conditions are met, leading to a more optimal revenue stream from selling flexibility. We find that the economic benefits of participating in delivering balancing power is considerable and offset an increase in energy costs. The increase in energy consumption could be justified as the participation in net stabilisation allows the macro-system to integrate more renewable energy sources. More importantly, the simulations also show that the poorer the energy performance of the water heater, the more flexibility can be sold. From a policy point of view, a minimal energy performance should be determined before allowing participation in net stabilisation.

Abstract: Carbon capture and utilization (CCU) technologies capture CO2 waste emissions and utilize them to generate new products (such as fuels, chemicals, and materials) with various environmental, economic, and social opportunities. As most of these CCU technologies are in the R&D stage, their technical and economic viability are examined with less attention to the social aspect which is an important pillar for a holistic sustainability assessment. The lack of systematic social impact research is mainly due to the difficulty of identifying and quantifying social aspects through the entire life cycle of products. We will fill this gap for CCU technologies and identify the main social indicators. A multi-criteria decision making tool: TOPSIS (technique for order of preference by similarity to ideal solution) was applied to empirically determine which indicators are more relevant for assessing the social impact of a company operating CCU activities within a European context. First, seeing that social impact categories are linked to key stakeholder groups, we considered workers, consumers, and local communities as relevant stakeholders. Second, the main social impact categories and their potential performance indicators associated to each group of stakeholders were listed using the United Nations Environment Program/Society of Environmental Toxicology and Chemistry (UNEP/SETAC) guidelines. In the third step, an online questionnaire was distributed to identify the main social categories and indicators for CCU, to which 33 European CCU experts responded. Finally, a modified TOPSIS was applied to rank the indicators based on their relevance. We found that the indicators related to “end of life responsibility” and “transparency” within a CCU company achieved the highest rank affecting the consumers group, whereas “fair salary” and “equal opportunities/discriminations” were determined as the most relevant impact categories for the workers. For the local community group, “secure living conditions” and “local employment” received the highest priority from the experts’ point of view. Furthermore, “health and safety” considerations were identified as one of the most important criteria affecting all three groups of stakeholders. The ranking list of the main social indicators identified in our study provides the basis for the next steps in the social sustainability assessment of CCU technologies; that is, data collection and impact assessment. Our outcomes can also be used to inform the producers regarding the most and least relevant social aspects of CCU so that the potential social impacts caused by their production activities can be improved or prevented.

Abstract: Climate-Smart Agriculture (CSA) is seeking to overcome the food security problem and develop rural livelihoods while minimizing negative impacts on the environment. However, when such synergies exist, the situation of small-scale farmers is often overlooked, and they are unable to implement new practices and technologies. Therefore, the main aim of this study is to improve CSA by adding the neglected but very important element “small-scale farmer”, and introduce Vulnerable-Smart Agriculture (VSA) as a complete version of CSA. VSA indicates, based on the results of this study, that none of the decisions made by policymakers can be realistic and functional as long as the voice of the farmers influenced by their decisions is not heard. Therefore, to identify different levels for possible interventions and develop VSA monitoring indicators, a new conceptual framework needs to be developed. This study proposed such a framework consisting of five elements: prediction of critical incidents by farmers, measuring the consequences of incidents, identifying farmers' coping strategies, assessing farmers' livelihood capital when facing an incident, and adapting to climate incidents. The primary focus of this study is on farmers' learning and operational preparation to deal with tension and disasters at farm level. Understanding the implications of threats from climate change and the recognizing of coping mechanisms will contribute to an increase in understanding sustainable management.

Abstract: Cotton is one of the important crops that play an important role in creating a livelihood for rural people in many parts of Iran. Cotton production necessitates a large amount of resources (e.g., fossil energy and agrochemicals, all of which have the potential to damage the environment in various ways). The purpose of the current study was to evaluate the environmental effects of cotton production in the South Khorasan Province of Iran. For this purpose, life cycle assessment (LCA) and data envelopment analysis (DEA) techniques have been applied to investigate the environmental impacts of cotton production. LCA is a practical method to evaluate the environment on the product flow, in which all aspects of the product life cycle are examined by a comprehensive approach. Furthermore, combining the LCA method with other managerial strategies such as DEA could allow researchers to provide decision-makers with more practical and interpretable data. The findings of the efficiency test showed that the average technical efficiency, pure technical efficiency, and scale efficiency were 0.81, 0.92, and 0.87, respectively. Respiratory inorganics (i.e., respiratory effects resulting from winter smog caused by emissions of dust, sulfur, and nitrogen oxides to air) posed the greatest environmental burden in cotton production, followed by non-renewable energy, carcinogens, and global warming. In addition, the highest effects were on human health, and then, on resources and climate change. Energy, on-system pollution, and waste played a crucial role in the environmental impacts of cotton processing. This study suggests improving farmers' knowledge toward the optimum application of chemical fertilizers, or their substitution with green fertilizers, which reduces the environmental effect of growing cotton in the area.

Abstract: Decentralized energy production offers an increased share of renewable energy and autonomy compared to the conventional, grid-only solution. However, under the net-metering scheme, the energy losses in batteries translate into financial losses to an investor seeking to move away from grid-only electricity and set up a residential PV+Battery microgrid. Our paper examines a hypothetical support scheme for such a project, designed to balance the economic disadvantage through partially supporting the acquisition of batteries, and thus ensure that the microgrid solution is more attractive than no investment. For this we develop four case studies based on experiments carried out in Greece, Italy, Denmark and Finland. Using the minimization of the Net Present Cost for each project, we compare the PV+Battery solution to the grid-only scenario over 25 years, for a range of electricity prices. The results illustrate first how the success of this project depends on the price of electricity. Second, we find that under current conditions in the respective countries the need for battery support varies between zero in Denmark and 86% in Italy, which reflects how the disadvantages of net metering can only be counterbalanced by either very high electricity price or very high solar resource. Our paper contributes thus to the discussion about the favourable environment for batteries in residential microgrids.

Abstract: Demand response (DR) can aid with grid integration of renewables, ensuring security of supply, and reducing generation costs. However, not enough is known about how residential customers’ perceptions of DR shape their response to such programs. This paper offers a deeper understanding of – and reveals the heterogeneity in – this relationship by conducting a quantile regression analysis of a Belgian DR trial, combining data on response with information on household attitudes towards smart appliances. Results overall suggest that improving response requires subtle shifts in electricity consumption behaviour, which can be achieved through changes in user perceptions. Specifically, if customers are inclined to be flexible, a stronger perception of smart appliances as being beneficial can greatly improve response. With those who are less flexible, the cost of smart appliances is a bigger concern. Thus, when designing DR programs, policymakers should aim to promote modest behaviour changes – so as to minimise inconvenience – in customers, by improving awareness on the benefits of smart appliances. Uptake of such DR programs may be improved by explaining the financial benefits or offering incentives to less flexible population segments. Lastly, improving response among older population segments will require a deeper investigation into their concerns.

Abstract: Despite substantial policy efforts made by the French government to reduce dependence on pesticides, farming practices are only changing slowly. This paper analyses the socio-economic trade-offs that 110 farmers are currently facing in the transition to agro-ecological practices. A mixed-method approach – a quantitative discrete choice experiment (DCE) and qualitative interviews – was set up to understand these farmers' motivations and perspectives, and how policy can improve to accompany them on the road to low chemical input farming. Results of the DCE indicate that the majority of the farmers in our sample are keen to change practices but are at a loss as to how this can be done, as a number of preferences for this transition came out as inconclusive. Qualitative interviews with a representative sample of the farmers that took part in the DCE complemented this result by illustrating a deep uncertainty for the future and a disconnect felt between authorities and themselves as a group. We argue that this uncertainty contributed to a lack of clear-cut solutions established through the DCE. The indepth discussions with farmers illustrated the wish for concrete and local policy measures based on farmers' networks and peer support.

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: Drought is a persistent, sluggish natural disaster in developing countries that has generated a financial burden and an unstable climate. Farmers should adopt early warning systems (EWS) in their strategies for monitoring drought to reduce its serious consequences. However, farmers in developing countries are reluctant to use EWS as their management strategies. Hence, the aim of this study was to investigate the decision of farmers to use climate knowledge through the model of farming activity in Kermanshah Township, Iran. A surveyor questionnaire was used to gather data from 370 wheat farmers using random sampling methods inmulti-stage clusters. Results revealed that the decision to use climate information is affected by personal factors, attitude towards climate information, objectives of using climate information, and external/physical farming factors. The result of this study has implications for drought management practitioners. To be specific, the results can aid policymakers to design early alert programs to minimize the risk of drought and thus move from conventional to climate smart agriculture. (C) 2020 Elsevier B.V. All rights reserved.

Abstract: Due to climate change, the frequency and intensity of droughts are expected to increase. To improve resilience to droughts, proactive drought management is essential. Economic assessments are typically included to decide on the drought risk-reducing investments to make. The choice of both methods and scope of economic assessments influences the outcome, and thus the investment choice. This paper aims to identify how comprehensively economic assessments are applied in practice. Through a systematic literature review, 14 actual economic assessments are identified and their methods are evaluated based on seven criteria for economic assessments as derived from the United Nations Framework Convention on Climate Change (UNFCCC). The results show that in practice, economic assessments rarely address all criteria. Applying a limited number of criteria reduces the scope and narrows the approach, possibly leading to the underestimation of drought risk reduction approaches’ related benefits. Applying the seven criteria in practice will improve the results of economic assessments of drought risk reduction measures, allowing for optimal investment selection. Based on the different criteria, a Framework for Economic Assessments of Drought Risk-Reducing Applications (FEADRRA) is proposed. Applying the criteria of the framework can support decision-makers in drought risk management and in carrying out the most fitting drought interventions.

Abstract: Economic and environmental impact assessments are increasingly being adopted in the design and implementation of emerging systems. However, their emerging nature leads to several assessment challenges that need to be addressed to ensure the validity and usefulness of results in understanding their potential performance and supporting their development. There is the need to (i) account for spatial and temporal variability to allow a broader perspective at an early stage of development; (ii) handle uncertainties to systematically identify the critical factors and their interrelations that drive the results; (iii) integrate environmental and economic results to support sound decision-making based on two sustainability aspects. To address these assessment challenges, this study presents an alternative approach with the following corresponding features: (i) multiple scenario development to conduct an exploratory assessment of the systems under varying conditions and settings, (ii) global sensitivity analysis to identify the main critical factors and their interrelations, and (iii) trade-off and ecoefficiency analysis to integrate the economic and environmental results. The integrated approach is applied to a case study on plasma gasification for solid waste management. The results of the study highlight how the approach allows the identification of the dynamic relations between project settings and surrounding conditions. For example, the choice of gasifying agent largely depends on the background energy system, which dictates the impacts of the process energy requirement and the savings from the substituted energy of the syngas output. Based on these findings, the usefulness and validity of the proposed integrated approach are discussed in terms of how the key assessment challenges are addressed and how it can provide guidance for the development of emerging systems.

Abstract: Empirical evidence on household risk balancing behaviour is presented by estimating a fixed effects seemingly unrelated regression model using Swiss Farm Accountancy Data Network data. We find that in response to changes in expected business risks, Swiss farm households not only make strategic farm financial risk decisions (original risk balancing), but also make strategic off-farm decisions (household risk balancing) by altering their share of off-farm income and relative consumption. Small farms appear to make more use of household risk balancing strategies whereas large farms conversely make more use of the original risk balancing strategy.

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.