A review of thermochemical upgrading of pyrolysis bio‐oil: Techno‐economic analysis,life cycle assessment,and technology readiness

Technologies for upgrading fast pyrolysis bio‐oil to drop‐in fuels and coproducts are under development and show promise for decarbonizing energy supply for transportation and chemicals markets. The successful commercialization of these fuels and the technologies deployed to produce them depend on production costs, scalability, and yield. To meet environmental regulations, pyrolysis‐based biofuels need to adhere to life cycle greenhouse gas intensity standards relative to their petroleum‐based counterparts. We review literature on fast pyrolysis bio‐oil upgrading and explore key metrics that influence their commercial viability through life cycle assessment (LCA) and techno‐economic analysis (TEA) methods together with technology readiness level (TRL) evaluation. We investigate the trade‐offs among economic, environmental, and technological metrics derived from these methods for individual technologies as a means of understanding their nearness to commercialization. Although the technologies reviewed have not attained commercial investment, some have been pilot tested. Predicting the projected performance at scale‐up through models can, with industrial experience, guide decision‐making to competitively meet energy policy goals. LCA and TEA methods that ensure consistent and reproducible models at a given TRL are needed to compare alternative technologies. This study highlights the importance of integrated analysis of multiple economic, environmental, and technological metrics for understanding performance prospects and barriers among early stage technologies.     

An Approach to Integrating Environmental Considerations Within Managerial Decision‐Making

Recent environmental trends, including (1) an expansion of existing command and control directives, (2) the introduction of market‐based policy instruments, and (3) the adoption of extended producer responsibility, have created a need for new tools to help managerial decision‐making. To address this need, we develop a nonlinear mathematical programming model from a profit‐maximizing firm's perspective, which can be tailored as a decision‐support tool for firms facing environmental goals and constraints. We typify our approach using the specific context of diesel engine manufacturing and remanufacturing. Our model constructs are based on detailed interviews with top managers from two leading competitors in the medium and heavy‐duty diesel engine industry. The approach allows the incorporation of traditional operations‐planning considerations—in particular, capacity, production, and inventory—together with environmental considerations that range from product design through production to product end of life. A current hurdle to implementing such a model is the availability of input data. We therefore highlight the need not only to involve all departments within businesses but also for industrial ecologists and business managers to work together to implement meaningful decision models that are based on accurate and timely data and can have positive economic and environmental impact.     

Double‐Counting in Life Cycle Calculations

Many popular frameworks apply life cycle calculations to examine environmental burdens occurring throughout the life cycle of products and services that are either purchased by final consumers or demanded as inputs by producers. Accounting for the full supply chain of producer items can lead to double‐counting effects when results of separate studies are added up and referenced or compared to totals. If, for instance, energy life cycle inventories were prepared for all consumer and producer items in an economy and added up, the resulting total amount of energy would be greater than national energy consumption. Although this double‐counting is inconsequential if analyses are appraised in isolation without reference to national totals, it leads to serious errors when large interconnected systems are analyzed or when results are placed into wider (e.g., regional, national, or global) contexts. The article lists a number of prominent policy and decision‐making frameworks that make use of life cycle techniques, where this double‐counting error is highly undesirable. It proposes a solution to the double‐counting problem in which supply chains in the product life cycle are split and burdens shared between the supplying and demanding sides of every transaction in the economy.     

Supply versus use designs of environmental extensions in input–output analysis: Conceptual and empirical implications for the case of energy

Input–output analysis is one of the central methodological pillars of industrial ecology. However, the literature that discusses different structures of environmental extensions (EEs), that is, the scope of physical flows and their attribution to sectors in the monetary input–output table (MIOT), remains fragmented. This article investigates the conceptual and empirical implications of applying two different but frequently used designs of EEs, using the case of energy accounting, where one represents energy supply while the other energy use in the economy. We derive both extensions from an official energy supply–use dataset and apply them to the same single‐region input–output (SRIO) model of Austria, thereby isolating the effect that stems from the decision for the extension design. We also crosscheck the SRIO results with energy footprints from the global multi‐regional input–output (GMRIO) dataset EXIOBASE. Our results show that the ranking of footprints of final demand categories (e.g., household and export) is sensitive to the extension design and that product‐level results can vary by several orders of magnitude. The GMRIO‐based comparison further reveals that for a few countries the supply‐extension result can be twice the size of the use‐extension footprint (e.g., Australia and Norway). We propose a graph approach to provide a generalized framework to disclosing the design of EEs. We discuss the conceptual differences between the two extension designs by applying analogies to hybrid life‐cycle assessment and conclude that our findings are relevant for monitoring of energy efficiency and emission reduction targets and corporate footprint accounting.     

Uncertainty of global warming potential for milk production on a New Zealand farm and implications for decision making

Background, aim and scope  

As a food exporting nation, New Zealand recognises that the Global Warming Potential (GWP) impact of agriculture has become important to food customers. Food production policy and industry analysts make GWP decisions based on greenhouse gas inventory and life cycle assessment (LCA) results. For decision making, the level of confidence associated with information is important. However, treatment of uncertainty has been problematic in LCA, especially in agricultural systems. In this paper, the GWP of 1 kg of milk was used as a case study to test the feasibility of quantifying uncertainties by Monte Carlo simulation in an LCA applied to an agriculture product. The study also contributes to the development of good practice and has implications for the incorporation of uncertainties into decision making.     

生命周期评价方法在城市生活垃圾管理中的应用研究述评

结合城市生活垃圾管理系统特征,系统归纳基于生命周期评价(Life cycle assessment,LCA)方法的城市生活垃圾管理模型的发展现状,并对LCA方法在城市生活垃圾管理中的实践以及在我国开展城市生活垃圾管理LCA研究的应用前景进行评述。分析表明,LCA是城市生活垃圾管理领域的重要工具之一,基于LCA方法的城市生活垃圾管理模型在全生命周期环境影响评价与识别、处置工艺选择与改进、可持续生活垃圾管理决策支持等方面具有十分重要的应用价值。中国在本地化生活垃圾管理系统LCA模型开发、清单数据库和评价指标体系构建以及与其他研究方法集成等方面面临挑战。     

Identification of Risks in the Life Cycle of Nanotechnology‐Based Products

In order to realize the projected market potential of nanotechnology, the environmental, health, and safety (EHS) uncertainties posed by a nano‐product (i.e., a nanotechnology‐enabled product) need to be characterized through the identification of risks and opportunities in early stages of product development. We present a methodology to identify risks from nano‐products using a scenario analysis approach that allows for expert elicitation on a set of preidentified use and disposal scenarios and what we have labeled “risk triggers” to obtain scores on their likelihood of occurrence and severity. Use and disposal scenarios describe product life‐cycle stages that could result in risk attributed to the nano‐product, whereas risk triggers are particular to nanoparticle properties. These are potential risks, as the risk assessment community is currently debating the specific risks attributed to nanotechnology. Through such a framework, our goal is to identify which products pose greater risks, where these risks occur in the product life cycle, and the impacts of these environmental risks on society. The comparison of risk triggers across nano‐products allows relative risk ranking on axes of exposure‐ and hazard‐related risk triggers. For the specific case of air fresheners, areas of acute risks resulted from bioavailability of nanoparticles in air release and water entrainment exposure scenarios; catalytic activity of nanoparticles in inhalation and air release exposure scenarios; the harmful effects due to the antibacterial property on useful bacteria particularly in susceptible populations; and, finally, risks from the lack of nanoparticle coating stability in air release scenarios.     

Prospective Environmental Analyses of Emerging Technology: A Critique,a Proposed Methodology,and a Case Study on Incremental Sheet Forming

Prospective environmental assessment of emerging technology is necessary in order to inform designers of beneficial changes early in a technology's development, and policy makers looking to fund projects and nudge manufacturers toward the most sustainable application of a technology. Existing analyses often have shortcomings such as failing to consider the environmental impacts in all stages of a product's life cycle; implicitly assuming that the emerging technology will be cost‐effective wherever it is technically viable; and assuming optimistic application scenarios that discontinue long‐established trends in human behavior. In this article, we propose a new approach, complementary to the prospective and anticipatory life cycle assessment literature, addressing the above concerns and attempting to make sense of the large uncertainties inherent in such analyses by using distributions to model all the inputs. The paper focuses on emerging manufacturing technologies, such as incremental sheet forming (ISF), but the issues examined are also applicable to new end‐use products, such as autonomous vehicles. This paper makes use of approaches (such as Bass modeling and product cannibalization considerations) familiar to those in the business community who anticipate market diffusion of a new technology and the effect on existing technology sales. The proposed methodology is demonstrated by estimating the potential environmental impacts in the U.S. car industry by 2030 of an emerging double‐sided ISF process. Energy and cost models of ISF and drawing are used to estimate potential mean savings of around 100 TJ_primary and 60 million U.S. dollars per year by 2030.     

Hierarchical Activity Model for Risk‐Based Decision Making

For the practical implementation of the assessment of environmental impact, actual procedures and data requirements should be clarified so that industrial decision makers understand them. Researchers should consider local risks related to processes and environmental impact throughout the life cycle of products simultaneously to supervise these adverse effects appropriately. Life cycle assessment (LCA) is a useful tool for quantifying the potential impact associated with a product life cycle. Risk assessment (RA) is a widely used tool for identifying chemical risks in a specific situation. In this study, we integrate LCA and RA for risk‐based decision making by devising a hierarchical activity model using the type‐zero method of integrated definition language (IDEF0). The IDEF0 activity modeling language has been applied to connect activities with information flows. Process generation, evaluation, and decision making are logically defined and visualized in the activity model with the required information. The activities, information flows, and their acquisitions are revealed, with a focus on which data should be collected by on‐site engineers. A case study is conducted on designing a metal cleaning process reducing chemical risks due to the use of a cleansing agent. LCA and RA are executed and applied effectively on the basis of integrated objective settings and interpretation. The proposed activity model can be used as a foundation to incorporate such assessments into actual business models.     

On the limitations of life cycle assessment and environmental systems analysis tools in general

The potential and limitations of life cycle assessment and environmental systems analysis tools in general are evaluated. More specifically this is done by exploring the limits of what can be shown by LCA and other tools. This is done from several perspectives. First, experiences from current LCAs and methodology discussions are used including a discussion on the type of impacts typically included, quality of inventory data, methodological choices in relation to time aspects, allocation, characterisation and weighting methods and uncertainties in describing the real world. Second, conclusions from the theory of science are practised. It is concluded that it can in general not be shown that one product is environmentally preferable to another one, even if this happens to be the case. This conclusion has important policy implications. If policy changes require that it must be shown that one product is more (or less) environmentally preferable before any action can be taken, then it is likely that no action is ever going to take place. If we want changes to be made, decisions must be taken on a less rigid basis. It is expected that in this decision making process, LCA can be a useful input. Since it is the only tool that can be used for product comparisons over the whole life cycle, it can not be replaced by any other tool and should be used. Increased harmonisation of LCA methodology may increase the acceptability of chosen methods and increase the usefulness of the tool.     

Integrating life cycle cost analysis and LCA

The private sector decision making situations which LCA addresses mustalso eventually take theeconomic consequences of alternative products or product designs into account. However, neither the internal nor external economic aspects of the decisions are within the scope of developed LCA methodology, nor are they properly addressed by existing LCA tools. This traditional separation of life cycle environmental assessment from economic analysis has limited the influence and relevance of LCA for decision-making, and left uncharacterized the important relationships and trade-offs between the economic and life cycle environmental performance of alternative product design decision scenarios. Still standard methods of LCA can and have been tightly, logically, and practically integrated with standard methods for cost accounting, life cycle cost analysis, and scenario-based economic risk modeling. The result is an ability to take both economic and environmental performance — and their tradeoff relationships — into account in product/process design decision making.     

Hybrid Framework for Managing Uncertainty in Life Cycle Inventories

Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input–output (I‐O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom‐up process model can be estimated via a top‐down approach such as the economic I‐O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long‐term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method.     

Environmental Assessment of Waste-Solvent Treatment Options

A comparison of various waste‐solvent treatment technologies, such as distillation (rectification) and incineration in hazardous‐waste‐solvent incinerators and cement kilns, is presented for 45 solvents with respect to the environmental life‐cycle impact. The environmental impact was calculated with the ecosolvent tool that was previously described in Part I of this work. A comprehensive sensitivity analysis was performed, and uncertainties were quantified by stochastic modeling in which various scenarios were considered. The results show that no single treatment technology is generally environmentally superior to any other but that, depending on the solvent mixture and the process conditions, each option may be optimal in certain cases. Nevertheless, various rules of thumb could be derived, and a results table is presented for the 45 solvents showing under which process conditions and amount of solvent recovery distillation is environmentally superior to incineration. On the basis of these results and the ecosolvent tool, an easily usable framework was developed that helps decision makers in chemical industries reduce environmental burdens throughout the solvent life cycle. With clear recommendations on the environmentally optimized waste‐solvent treatment technology, the use of this framework contributes to more environmentally sustainable solvent management and thus represents a practical application of industrial ecology.     

From Life Cycle Assessment to Life Cycle Management

Life cycle assessment (LCA) is a widely accepted methodology to support decision‐making processes in which one compares alternatives, and that helps prevent shifting of environmental burdens along the value chain or among impact categories. According to regulation in the European Union (EU), the movement of waste needs to be reduced and, if unavoidable, the environmental gain from a specific waste treatment option requiring transport must be larger than the losses arising from transport. The EU explicitly recommends the use of LCA or life cycle thinking for the formulation of new waste management plans. In the last two revisions of the Industrial Waste Management Programme of Catalonia (PROGRIC), the use of a life cycle thinking approach to waste policy was mandated. In this article we explain the process developed to arrive at practical life cycle management (LCM) from what started as an LCA project. LCM principles we have labeled the “3/3” principle or the “good enough is best” principle were found to be essential to obtain simplified models that are easy to understand for legislators and industries, useful in waste management regulation, and, ultimately, feasible. In this article, we present the four models of options for the management of waste solvent to be addressed under Catalan industrial waste management regulation. All involved actors concluded that the models are sufficiently robust, are easy to apply, and accomplish the aim of limiting the transport of waste outside Catalonia, according to the principles of proximity and sufficiency.     

Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent‐Based Modeling Approach

The aim of this study is to develop a framework for understanding the heterogeneity and uncertainties present in the usage phase of the product life cycle through utilizing the capabilities of an agent‐based modeling (ABM) technique. An ABM framework is presented to model consumers’ daily product usage decisions and to assess the corresponding electricity consumption patterns. The theory of planned behavior (TPB), with the addition of the habit construct, is used to model agents’ decision‐making criteria. A case study is presented on the power management behavior of personal computer users and the possible benefits of using smart metering and feedback systems. The results of the simulation demonstrate that the utilization of smart metering and feedback systems can promote the energy conservation behaviors and reduce the total PC electricity consumption of households by 20%.     

Monitoring in the Context of Structured Decision-Making and Adaptive Management

Abstract: In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play ≥3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill ≥1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring programs that are used for decision-making, not comprehensive studies that elucidate all manner of ecological relationships.     

Critical Components of Uncertainty Communication in Life Cycle Assessments of Emerging Technologies

Because of their recognition as a comprehensive tool of environmental assessments and their increasing use by governments and industries, life cycle assessments (LCAs) are positioned to be prominent sources of mass media information on new products and technologies. The LCA studies underlying media reports are often viewed by nonexperts after the initial reporting. However, uncertainty is rife in early assessments of emerging technologies, and LCA's ability to inform environmental opinions and decisions is limited without the accompanying communication on uncertainty. Though approaches to the technical aspects of uncertainty analysis in LCA are available in the literature, those on communicating that uncertainty, in ways that are cognitively accessible to the nonexperts, are still lacking despite their highlighted importance across various disciplines. With the focus on communication, this article uses the existing literature to derive five criteria for making uncertainty communication accessible to a nonexpert audience. Then, LCAs on engineered nanomaterial (ENM) and ENM‐enabled products, as a case study of emerging technologies where uncertainties abound, are reviewed for whether they meet these five criteria. The study concludes with recommendations for communicating uncertainty in LCAs in order to enhance their role as decision‐ and public opinion–informing assessments.     

Characterizing,Propagating, and Analyzing Uncertainty in Life‐Cycle Assessment: A Survey of Quantitative Approaches

Life‐cycle assessment (LCA) practitioners build models to quantify resource consumption, environmental releases, and potential environmental and human health impacts of product systems. Most often, practitioners define a model structure, assign a single value to each parameter, and build deterministic models to approximate environmental outcomes. This approach fails to capture the variability and uncertainty inherent in LCA. To make good decisions, decision makers need to understand the uncertainty in and divergence between LCA outcomes for different product systems. Several approaches for conducting LCA under uncertainty have been proposed and implemented. For example, Monte Carlo simulation and fuzzy set theory have been applied in a limited number of LCA studies. These approaches are well understood and are generally accepted in quantitative decision analysis. But they do not guarantee reliable outcomes. A survey of approaches used to incorporate quantitative uncertainty analysis into LCA is presented. The suitability of each approach for providing reliable outcomes and enabling better decisions is discussed. Approaches that may lead to overconfident or unreliable results are discussed and guidance for improving uncertainty analysis in LCA is provided.     

The Green Economy Mirage?

Taiwan is attempting to implement the concept of a green economy through a Low Carbon Growth Plan (LCGP). However, the existing decision support tools for this measure have three key limitations: ignorance regarding the open economy; a lack of life cycle thinking; and limited categories of environmental impact. This study integrates environmentally extended, multi‐region input‐output analysis and hybrid life cycle assessment to quantify the potential environmental impact of the industrial activities and energy structure in Taiwan in 2020. Two novel indicators, environmental debts and loans, are also applied to identify the geographical shifting effects and tie environmental responsibility to the discussion. The results of this study reveal that under the existing LCGP, relative decoupling will be attained, but no significant environmental cobenefits other than those affecting climate change can be gained. Moreover, the current emission pledges cannot be fulfilled. The presence of increased environmental debt ratios reveals the geographical shifting effect of the LCGP. The main driver of the expansion of the environmental footprint can be attributed to the export of electronic components and products, which are not included in the agenda of policy discussions. As a result, three crucial policies are suggested to modify the existing LCGP: the implementation of a higher energy efficiency improvement target; rethinking the constraints on the electronics industry; and the development of a mechanism to include environmental issues in free trade agreement negotiations. With these changes, the realization of the current emission pledge and a green economy could be possible.     

Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments

Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta‐analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change experiments. Additionally, policy and land management decisions related to global change scenarios should consider how ANPP and BNPP responses may differ, and that ecosystem responses to extreme events might not be predicted from relationships found under moderate environmental changes.