In the wake of the 2011 Fukushima Daiichi Nuclear Power Station accident, to facilitate evidence-based risk communication we need to understand radiation risk perception and the effectiveness of risk-comparison information. We measured and characterized perceptions of dread risks and unknown risks regarding dietary radionuclides in residents of Fukushima, Tokyo, and Osaka to identify the primary factors among location, evacuation experience, gender, age, employment status, absence/presence of spouse, children and grandchildren, educational background, humanities/science courses, smoking habits, and various types of trustworthy information sources. We then evaluated the effects of these factors and risk-comparison information on multiple outcomes, including subjective and objective understanding, perceived magnitude of risk, perceived accuracy of information, backlash against information, and risk acceptance. We also assessed how risk-comparison information affected these multiple outcomes for people with high risk perception. Online questionnaires were completed by people (n = 9249) aged from 20 to 69 years in the three prefectures approximately 5 years after the accident. We gave each participant one of 15 combinations of numerical risk data and risk-comparison information, including information on standards, smoking-associated risk, and cancer risk, in accordance with Covello’s guidelines. Dread-risk perception among Fukushima residents with no experience of evacuation was much lower than that in Osaka residents, whereas evacuees had strikingly higher dread-risk perception, irrespective of whether their evacuation had been compulsory or voluntary. We identified location (distance from the nuclear power station), evacuation experience, and trust of central government as primary factors. Location (including evacuation experience) and trust of central government were significantly associated with the multiple outcomes above. Only information on “cancer risk from radiation and smoking risk” enhanced both subjective and objective understanding without diminishing trust in all participants and in the high dread-risk perception group; use of other risk-comparison information could lead the public to overestimate risk.
Purpose. Consequential LCA (CLCA) is becoming widely used in the scientific community as a modelling technique which describes the consequences of a decision. However, despite the increasing number of case studies published, a proper systematization of the approach has not yet been achieved. This paper investigates the methodological implications of CLCA and the extent to which the applications are in line with the theoretical dictates. Moreover, the predictive and explorative nature of CLCA is discussed, highlighting the role of scenario modelling in further structuring the methodology. Methods. An extensive literature review was performed, involving around 60 articles published over a period of approximately 18 years, and addressing both methodological issues and applications. The information was elaborated according to two main aspects: what for (questions and modes of LCA) and what (methodological implications of CLCA) , with focus on the nature of modelling and on the identification of the affected processes. Results and discussion. The analysis points out that since the modelling principles of attributional LCA (ALCA) and CLCA are the same, what distinguishes the two modes of LCA is the choice of the processes to be included in the system (i.e., in CLCA, those that are affected by the market dynamics). However, the identification of those processes is often done inconsistently, using different arguments, which leads to different results. We suggest the use of scenario modelling as a way to support CLCA in providing a scientifically-sound basis to model specific product-related futures with respect to technology development, market shift, and other variables. Conclusions. The CLCA is a sophisticated modelling technique that provides a way to assess the environmental consequences of an action/decision by including market mechanisms into the analysis. There is still room for improvements of the method and for further research, especially in relation to the following aspects: clarifying when and which market information is important and necessary; understanding the role of scenario modelling within CLCA; and developing a procedure to support the framing of questions to better link questions to models. Moreover, we suggest that the logic of mechanisms could be the reading guide for overcoming the dispute between ALCA and CLCA. Going further, this logic could also be extended, considering CLCA as an approach-rather than as a modelling principle with defined rules-to deepen LCA, providing the conceptual basis for including more mechanisms than just the market ones.
Urbanization and population growth have contributed to a tripling of building material consumption from 2000 to 2017. Building materials have a range of environmental impacts throughout their life cycle, from extraction, processing, and transport of raw materials to building construction, use, and eventual demolition and waste. Mitigation measures that target specific materials or value chain stages may therefore have incremental or even adverse net environmental effects. In this perspective, we develop a framework for applying life cycle thinking to identify key impacts and corresponding mitigation approaches, inform building design and material selection, and ensure effective treatment and recycling of construction and demolition wastes. Life cycle evaluation can also be used to assess and avoid environmental trade-offs among life cycle stages. Challenges for implementing these life cycle principles include collecting and integrating inventory data for products, managing multiple stakeholders within the construction industry, and monitoring end-of-life impacts; measures for overcoming such challenges are discussed.
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