Social Life Cycle Assessment in Biobased Industries: Identifying Main Indicators and Impacts

peer reviewedAssessing social impacts of various products, services and human activities has achieved an increasing interest worldwide. The nature of sustainability of biobased industries from a social point of view is how and to what extent they are perceived by society, and how various societies take advantages from such activities. However, an important issue is that social factors are not usually easy to be quantitatively analyzed and although the social impacts might be very remarkable, especially at the local scale, they have been not possible to be investigated in the majority of impact evaluations in the past. Despite the existence of many different methodologies towards Social Life Cycle Assessment (SLCA) to address social impacts of various businesses and industries, most of them impartially address social performances of an industry. The aim of this paper is to highlight the main criteria that need to be taken into account in SLCA approaches for identifying the social indicators and impacts of biobased industries that is a timely topic worldwide toward climate change mitigation goals. Accordingly, considering the general approach of SLCA and particularly its inventory analysis phase for impact categories and indicator determinations, the paper provides an overview of the existing guidelines and frameworks for identifying social indicators and impact categories associated with bio-industries. In conclusion, main impact categories and indicators formulated in the existing frameworks applied to biobased industries are demonstrated as a basic set of applicable elements of social dimensions in evaluating bio-industries’ sustainability when conducting SLCAs. The state of the art for this study mainly includes leading journal articles, international reports and conference papers up to and including 2016 on SLCA in biobased industries. According to the reviewed frameworks in this study, quantitative, midpoint and site-specific data are the main elements taken into account when collecting the data for biobased product social impact assessment. This study also reveals that although SLCA is in its early steps of development and despite in numerous cases, conducting a comprehensive SLCA is not yet feasible, it has been considered to have substantially promising methodological attributes that can help policymakers and other stakeholders to quantify and assess sustainability of bio-industries from the social perspective. Recommendations for further research work concerning SLCA in bio-industries are also presented

Critical slowing down as early warning for the onset and termination of depression

About 17% of humanity goes through an episode of major depression at some point in their lifetime. Despite the enormous societal costs of this incapacitating disorder, it is largely unknown how the likelihood of falling into a depressive episode can be assessed. Here, we show for a large group of healthy individuals and patients that the probability of an upcoming shift between a depressed and a normal state is related to elevated temporal autocorrelation, variance, and correlation between emotions in fluctuations of autorecorded emotions. These are indicators of the general phenomenon of critical slowing down, which is expected to occur when a system approaches a tipping point. Our results support the hypothesis that mood may have alternative stable states separated by tipping points, and suggest an approach for assessing the likelihood of transitions into and out of depression

Daratumumab monotherapy for patients with intermediate-risk or high-risk smoldering multiple myeloma: a randomized, open-label, multicenter, phase 2 study (CENTAURUS)

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Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology:The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

OBJECTIVE: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual’s emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient’s ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0–16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation

Integrating social aspects into sustainability assessment of biobased industries: Towards a systemic approach

peer reviewedConsidering its potential impacts on development, biobased industries require to be assessed according to the positive and negative effects they can bring to the society. Typically, the implications of biobased industries are considered in terms of economic, environmental and technical indices while social factors are usually neglected in the majority of impact assessments. This is mainly due to the fact that social issues are not easy to be quantitatively analyzed, measured and monitored. Indeed, the following issues need to be addressed: (i) how the social dimension is understood from different stakeholders’ perspective; (ii) how the social pillar can be properly integrated into sustainability evaluation methodologies which are mainly focused on environmental performance and (techno)-economic assessments of biobased industries. This review paper aims to answer these questions firstly through identifying the main social impacts and indicators of the biobased industries at local level in order to find an answer for the second question by analyzing and comparing the current methodologies for assessing social impacts in bioindustries. These methods mainly include Social Impact Assessment (SIA), Socio-economic Impacts Assessment (SEIA) and Social Life Cycle Analysis (SLCA). The latter, although is in its early steps of development, has been considered to have substantially promising methodological attributes for bioindustries’ social sustainability assessment. Although ongoing research tackles the incorporation of the environmental dimension into extended techno-economic assessments, no integration of the social pillar into such assessments has been made. Given that, this review focuses on the social dimension for integrated sustainability assessments of biobased industries to assess the main social impacts resulting from each operation or from the bioenergy sector. The current review focuses on the importance of social sustainability indicators and evaluation techniques. By discussing the methodologies for evaluating social impacts, a systemic methodology for assessing and integrating the social dimension into the sustainability assessments of bioindustries is developed, considering the four main iterative steps of an SLCA framework and three useful SLCA-based approaches including Product Social Impact Assessment; Prosuite and the UNEP SETAC Guidelines for SLCA of Products. It is concluded that the term systemic analysis implies that the whole approach needs the capacity to understand different subsystems and relations between them. Accordingly, the systemic assessment of biobased technologies should simultaneously include technological, economic, social and environmental dimensions. The result of this study identifies social impacts in the bioeconomy and particularly highlight the importance of considering social issues in biobased industries’ design and innovation

Social activation: stepping stone or alternative to employment activation?

Today the local social offices in Belgium represent much more than purely providing benefits to those on income support or related benefits (or their equivalents) and support to the needy. So it is known that activation to paid work has taken a prominent place in the operation of the local social office. Less known is that the local social offices are also developing a large range of actions in the area of social activation. This paper examines to what extent social activation can be seen as a further differentiation of the services offered for those for whom employment activation is not considered feasible. The central question is which factors affect the extent in which the local social offices are offering this type of ‘social activation’, and how this is related to the employment activation of their clients. Our data are based on a web survey in 2011 with responsible officers of a sample of 234 local social offices in Belgium. Making use of structural equation modeling, we come to the conclusion that the variation in the extent of social activation can be explained from contextual, local policy and organizational factors. There are striking differences between the regions in the role that the local policy vision on activation plays for the degree of social activation in the commune.status: publishe

Combining Monte Carlo simulations and experimental design for incorporating risk and uncertainty in investment decisions for cleantech: a fast pyrolysis case study

The value of phytoextracting crops (plants cultivated for soil remediation) depends on the pro tability of the sequential investment in a conversion technology aimed at the economic valorization of the plants. However, the net present value (NPV) of an investment in such an innovative technology is risky due to technical and economic uncertainties. Therefore, decision makers want to dispose of information about the probability of a positive NPV, the largest possible loss, and the crucial economic and technical parameters in uencing the NPV. This paper maps the total uncertainty in the NPV of an investment in fast pyrolysis for the production of combined heat and power from willow cultivated for phytoextraction in the Belgian Campine. The probability of a positive NPV has been calculated by performing Monte Carlo simulations. Informa- tion about possible losses has been provided by means of experimental design. Both methods are then combined in order to identify the key economic and technical parameters in uencing the project’s pro tability. It appears that the case study has a chance of 87% of generating a positive NPV with an expected value of 3 million euro (MEUR), while worst-case scenarios predict possible losses of 7 MEUR. The amount of arable land, the biomass yield, the purchase price of the crop, the policy support, and the product yield of fast pyrolysis are identi ed as the most in uential parameters. It is concluded that both methods, i.e., Monte Carlo simulations and experimental design, provide decision makers with complementary information with regard to economic risk

Social sustainability assessments in the biobased economy: Towards a systemic approach

The majority of impact assessments for the biobased economy are primarily focused on the environmental and (techno-)economic aspects, while social aspects are rarely considered. This study proposes a modified systemic approach for a social sustainability impact assessment of the biobased economy, based on a review on the common methodologies for assessing social impacts. Accordingly, the proposed approach follows the four general iterative steps of social life cycle analysis (SLCA) as it considers all life cycle phases of the biobased economy. The systemic approach considers the potential social impacts on local communities, workers, and consumers as the main three groups of the stakeholders. The review showed that the most common social indicators for inventory analysis within the biobased economy include health and safety, food security, income, employment, land- and worker-related concerns, energy security, profitability, and gender issues. Multi-criteria decision analysis (MCDA) was also highlighted as the broadly utilized methodology for aggregating the results of impact assessments within the biobased economy. Taking a life cycle perspective, this study provides a holistic view of the full sustainability of research, design, and innovation in the biobased economy by suggesting the integration of the social aspects with techno-economic and an environmental life cycle assessment. Our proposed systemic approach makes possible to integrate the social impacts that are highly valued by the affected stakeholders into the existing sustainability models that focus only on environmental and techno-economic aspects. We discuss the steps of the proposed systemic approach in order to identify the challenges of applying them within the biobased economy. These challenges refer mainly to the definition of the functional unit and system boundaries, the selection and the analysis of social indicators (inventory analysis), the aggregation of the inventory to impact categories, and the uncertainties associated with the social sustainability evaluation. The result of this review and the proposed systemic approach serve as a foundation for industry and policy makers to gain a better insight into the importance of social sustainability impacts assessment within the biobased economy