Missing inventory estimation tool using extended input-output analysis

Intention, Goal, Scope, Background  Input-Output Analysis (IOA) has recently been introduced to Life Cycle Assessment (LCA). In applying IOA to LCA studies, however, it is important to note that there are both advantages and disadvantages. Objectives  This paper aims to provide a better understanding of the advantages and disadvantages of adopting IOA in LCA, and introduces the methodology and principles of the Missing Inventory Estimation Tool (MIET) as one of the approaches to combine the strengths of process-specific LCA and IOA. Additionairy, we try to identify a number of possible errors in the use of IOA for LCA purposes, due to confusion between industry output and commodity, consumer’s price and producer’s price. Method  MIET utilises the 1996 US input-output table and various environmental statistics. It is based on an explicit distinction between commodity and industry output. Results and Discussion  MIET is a self-contained, publicly available database which can be applied directly in LCA studies to estimate missing processes. Conclusion  By adopting MILT results in existing, process-based, life-cycle inventory (LCI), LCA practitioners can fully utilise the process-specific information while expanding the system boundary. Recommendations and Outlook  MIET will be continuously updated to reflect both methodological developments and newly available data sources. For supporting information sec http:// wwwJeidenuniv.nl/cml/ssp/softwarc/miet.     

Individual adaptation of industry LCA practice: Results from two case studies in the Swedish forest products industry

Goal, Scope and Background The mere existence of life cycle assessment (LCA) methodology and general acceptance of the life cycle philosophy is not enough to make their use widespread in industry. To gain a better understanding of factors shaping LCA studies and life cycle related practice, field studies of the development of LCA practice in two companies were carried out. Methods In order to obtain a deeper understanding of LCA practice, the number of ‘variables’ was minimized and two similar companies were chosen for study: Stora Enso and SCA. Both companies are part of the Swedish forest products industry, are large multinational enterprises and have been working with LCA since the early 1990s. Both interviews and document studies were used to collect data regarding LCA work from its introduction until 2003. Results and Discussion We found fundamental differences in LCA practice between two similar companies in regard to LCA studies per se (the number of studies undertaken and methodological preferences) and also in regard to the organisation of and approach to LCA work. By testing various theoretical explanations of these divergent LCA practices, we identified the actions of individuals and their understanding of the situation as important factors shaping LCA practice. Conclusions Although sector-wide recommendations on LCA practice are common in the LCA community, this study indicates that companies use LCA differently despite similar structural conditions such as company size or sector affiliation. Recommendations and Perspectives Since the understanding and actions of individuals are important in shaping LCA practice, people working with LCA in industry probably have greater scope for action than they recognise and than sector recommendations may imply when it comes to organising and carrying out their work. Thus, those working with life cycle issues, even in different sectors, can learn much from each other about ways of organising and benefiting from LCA work.     

LCA and decision making: when and how to use consequential LCA; 62nd LCA forum,Swiss Federal Institute of Technology,Zürich, 9 September 2016

The 62nd life cycle assessment (LCA) forum was held on 9 September 2016 to discuss the state of research and application with regard to consequential life cycle assessment. This conference report presents the highlights of the LCA forum. The state of the art of consequential LCA was presented from different viewpoints. It was pointed out that consequential LCA is more than marginal mixes and avoided burdens and involves causal modelling. It was also said that social responsibility calls for consequential LCA. Currently, different models are used to support decision making. It was suggested to make use of the variety of models to check the conclusiveness of their results and thus the reliability of the LCAs. Current and future implementations of consequential LCI models in background databases and linking algorithms were presented. Several speakers presented consequential LCA case studies covering the sectors energy, transport, housing and mining. Some of the LCA models used in the case studies are complemented with general and partial computable equilibrium models and agent-based models and use environmentally extended input-output data or process-based LCA data. Some of the presentations focused on elements such as constrained production, marginal market mixes and technologies or recycling and system expansion. In three parallel workshops, the needs, contents and methodology, and implementation of consequential LCA approaches were discussed. The participants seemed to generally agree on the basic goal that LCA should be able to reflect the consequences of decisions. The inquiry among the participants showed that the demand for consequential LCA studies is hardly existent. The appropriate implementation of consequential modelling in LCA databases and on the appropriate model to be used in consequential LCA case studies was debated. It revealed a need for further and extensive discussions to be able to reach (minimum) consensus.     

Environmental impacts of European trade: interpreting results of process-based LCA and environmentally extended input–output analysis towards hotspot identification

Purpose

Trade is increasingly considered a significant contributor to environmental impacts. The assessment of the impacts of trade is usually performed via environmentally extended input–output analysis (EEIOA). However, process-based life cycle assessment (LCA) applied to traded goods allows increasing the granularity of the analysis and may be essential to unveil specific impacts due to traded products.

Methods

This study assesses the environmental impacts of the European trade, considering two modelling approaches: respectively EEIOA, using EXIOBASE 3 as supporting database, and process-based LCA. The interpretation of the results is pivotal to improve the robustness of the assessment and the identification of hotspots. The hotspot identification focuses on temporal trends and on the contribution of products and substances to the overall impacts. The inventories of elementary flows associated with EU trade, for the period 2000–2010, have been characterized considering 14 impact categories according to the Environmental Footprint (EF2017) Life Cycle Impact Assessment method.

Results and discussion

The two modelling approaches converge in highlighting that in the period 2000–2010: (i) EU was a net importer of environmental impacts; (ii) impacts of EU trade and EU trade balance (impacts of imports minus impacts of exports) were increasing over time, regarding most impact categories under study; and (iii) similar manufactured products were the main contributors to the impacts of exports from EU, regarding most impact categories. However, some results are discrepant: (i) larger impacts are obtained from IO analysis than from process-based LCA, regarding most impact categories, (ii) a different set of most contributing products is identified by the two approaches in the case of imports, and (iii) large differences in the contributions of substances are observed regarding resource use, toxicity, and ecotoxicity indicators.

Conclusions

The interpretation step is crucial to unveil the main hotspots, encompassing a comparison of the differences between the two methodologies, the assumptions, the data coverage and sources, the completeness of inventory as basis for impact assessment. The main driver for the observed divergences is identified to be the differences in the impact intensities of goods, both induced by inherent properties of the IO and life cycle inventory databases and by some of this study’s modelling choices. The combination of IO analysis and process-based LCA in a hybrid framework, as performed in other studies but generally not at the macro-scale of the full trade of a country or region, appears a potential important perspective to refine such an assessment in the future.

     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

Using Standard Statistics to Consider Uncertainty in Industry-Based Life Cycle Inventory Databases (7 pp)

Goal, Scope and Background Decision-makers demand information about the range of possible outcomes of their actions. Therefore, for developing Life Cycle Assessment (LCA) as a decision-making tool, Life Cycle Inventory (LCI) databases should provide uncertainty information. Approaches for incorporating uncertainty should be selected properly contingent upon the characteristics of the LCI database. For example, in industry-based LCI databases where large amounts of up-to-date process data are collected, statistical methods might be useful for quantifying the uncertainties. However, in practice, there is still a lack of knowledge as to what statistical methods are most effective for obtaining the required parameters. Another concern from the industry's perspective is the confidentiality of the process data. The aim of this paper is to propose a procedure for incorporating uncertainty information with statistical methods in industry-based LCI databases, which at the same time preserves the confidentiality of individual data. Methods The proposed procedure for taking uncertainty in industry-based databases into account has two components: continuous probability distributions fitted to scattering unit process data, and rank order correlation coefficients between inventory flows. The type of probability distribution is selected using statistical methods such as goodness-of-fit statistics or experience based approaches. Parameters of probability distributions are estimated using maximum likelihood estimation. Rank order correlation coefficients are calculated for inventory items in order to preserve data interdependencies. Such probability distributions and rank order correlation coefficients may be used in Monte Carlo simulations in order to quantify uncertainties in LCA results as probability distribution. Results and Discussion A case study is performed on the technology selection of polyethylene terephthalate (PET) chemical recycling systems. Three processes are evaluated based on CO2 reduction compared to the conventional incineration technology. To illustrate the application of the proposed procedure, assumptions were made about the uncertainty of LCI flows. The application of the probability distributions and the rank order correlation coefficient is shown, and a sensitivity analysis is performed. A potential use of the results of the hypothetical case study is discussed. Conclusion and Outlook The case study illustrates how the uncertainty information in LCI databases may be used in LCA. Since the actual scattering unit process data were not available for the case study, the uncertainty distribution of the LCA result is hypothetical. However, the merit of adopting the proposed procedure has been illustrated: more informed decision-making becomes possible, basing the decisions on the significance of the LCA results. With this illustration, the authors hope to encourage both database developers and data suppliers to incorporate uncertainty information in LCI databases.     

6th SETAC-Europe Meeting: LCA — Selected Papers

A study of industry’s use of LCA has been performed as a special analysis of the Business Environmental Barometer (B.E.B.). The B.E.B. is an international questionnaire survey on industry’s environmental management practices (LCA included), repeated every two years. The first round in 1993 included the Nordic countries. The 1997 round will include eight European countries. This analysis intends to describe industry’s LCA use as such (e.g. active industrial sectors, applications, changes over time) and differences between companies working with LCA and those not working with LCA. The survey indicates that industry is in the process of internalising LCA knowledge, although most companies are still in the learning phase. LCA companies have more developed environmental management systems than non-LCA companies. A company’s LCA use seems to be a competitor-driven activity, judging from LCA distribution among industrial sectors.     

Lifting the veil on the correction of double counting incidents in hybrid life cycle assessment

Life cycle assessment (LCA) and environmentally extended input–output analyses (EEIOA) are two techniques commonly used to assess environmental impacts of an activity/product. Their strengths and weaknesses are complementary, and they are thus regularly combined to obtain hybrid LCAs. A number of approaches in hybrid LCA exist, which leads to different results. One of the differences is the method used to ensure that mixed LCA and EEIOA data do not overlap, which is referred to as correction for double counting. This aspect of hybrid LCA is often ignored in reports of hybrid assessments and no comprehensive study has been carried out on it. This article strives to list, compare, and analyze the different existing methods for the correction of double counting. We first harmonize the definitions of the existing correction methods and express them in a common notation, before introducing a streamlined variant. We then compare their respective assumptions and limitations. We discuss the loss of specific information regarding the studied activity/product and the loss of coherent financial representation caused by some of the correction methods. This analysis clarifies which techniques are most applicable to different tasks, from hybridizing individual LCA processes to integrating complete databases. We finally conclude by giving recommendations for future hybrid analyses.     

Conformational lability of two molecular chaperones Hsc70 and gp96: effects of pH and temperature

Hsc70 and gp96 are two heat shock proteins with molecular chaperone and immune-related activities. The dynamic conformational properties of heat shock proteins appear to play a critical role in their biological activities. In this study, we investigated the effects of pH and temperature on the conformational states of Hsc70 and gp96. The quaternary, tertiary, and secondary structures of both proteins are evaluated by a variety of spectroscopic techniques, including far-UV circular dichroism, Trp fluorescence, ANS fluorescence, and derivative UV absorption spectroscopy. The results are summarized and compared employing an empirical phase diagram approach. Very similar behaviors are seen for both proteins despite their differences in sequence and tertiary structure. Both proteins show substantial conformational lability in responses to the pH and temperature changes of their environment. This study suggests a natural selection for related functional properties through common conformational dynamics rather than immediate structural homology.     

Dynamic Models of Fixed Capital Stocks and Their Application in Industrial Ecology

Industrial assets or fixed capital stocks are at the core of the transition to a low‐carbon economy. They represent substantial accumulations of capital, bulk materials, and critical metals. Their lifetime determines the potential for material recycling and how fast they can be replaced by new, more efficient facilities. Their efficiency determines the coupling between useful output and energy and material throughput. A sound understanding of the economic and physical properties of fixed capital stocks is essential to anticipating the long‐term environmental and economic consequences of the new energy future. We identify substantial overlap in the way stocks are modeled in national accounting, dynamic material flow analysis, dynamic input‐output (I/O) analysis, and life cycle assessment (LCA) and we merge these concepts into a common framework for modeling fixed capital stocks. We demonstrate the usefulness of the framework for simultaneous accounting of capital and material stocks and for consequential LCA. We apply the framework to design a demand‐driven dynamic I/O model with dynamic capital stocks, and we synthesize both the marginal and attributional matrix of technical coefficients (A‐matrix) from detailed process inventories of fixed assets of different age cohorts and technologies. The stock modeling framework allows researchers to identify and exploit synergies between different model families under the umbrella of socioeconomic metabolism.     

可持续消费的内涵及研究进展——产业生态学视角

生产和消费是产生诸多环境问题的根本原因,而可持续生产和消费则是实现可持续发展的根本途径。基于产业生态学视角,界定了可持续消费的定义及内涵,认为可持续消费首先须符合代内公平、代际公平和资源能源永续合理利用等可持续理念;其次辨识了可持续消费研究依次经历关注消费者行为直接环境影响、关注产品和服务生命周期环境影响到关注消费者责任3个阶段;最后结合我国城市化、工业化背景,提出我国可持续消费研究应该以城市居民为重点、加强生命周期数据库建设和内注重可持续生产等建议。     

中国居民消费隐含的碳排放量变化的驱动因素

应用基于投入产出技术的生命周期评价(EIO-LCA)核算了1997、2000、2002、2005和2007年5a的中国居民消费隐含的二氧化碳排放量,发现其呈现增加趋势。2007年达到18.53亿t,相当于1997年的1.61倍,年平均增长4.89%. 其次采用结构分解分析(SDA)分析了碳排放效率变化、经济内在结构变迁、消费结构转变、人均消费水平变化、城市化进程和人口总量变化等六项因素对碳排放总量变化的驱动作用。研究发现碳排放效率因素和人均消费水平变化是驱动碳排放变化的两大主要力量,并且作用相反。碳排放效率的持续提高,很大程度上缓解了居民消费的隐含碳排放急剧增加的趋势,是减缓碳排放量的主要因素;而人均消费水平的迅速提高成为推动碳排放增加的主要力量,是推动碳排放增加的主要因素。     

Understanding the LCA and ISO water footprint: A response to Hoekstra (2016) “A critique on the water-scarcity weighted water footprint in LCA”

Water footprinting has emerged as an important approach to assess water use related effects from consumption of goods and services. Assessment methods are proposed by two different communities, the Water Footprint Network (WFN) and the Life Cycle Assessment (LCA) community. The proposed methods are broadly similar and encompass both the computation of water use and its impacts, but differ in communication of a water footprint result. In this paper, we explain the role and goal of LCA and ISO-compatible water footprinting and resolve the six issues raised by Hoekstra (2016) in “A critique on the water-scarcity weighted water footprint in LCA”. By clarifying the concerns, we identify both the overlapping goals in the WFN and LCA water footprint assessments and discrepancies between them. The main differing perspective between the WFN and LCA-based approach seems to relate to the fact that LCA aims to account for environmental impacts, while the WFN aims to account for water productivity of global fresh water as a limited resource. We conclude that there is potential to use synergies in research for the two approaches and highlight the need for proper declaration of the methods applied.     

Framework for hybrid life cycle inventory databases: a case study on the Building for Environmental and Economic Sustainability (BEES) database

Purpose

In an effort to develop a whole building Life Cycle Assessment (LCA) tool, National Institute of Standards and Technology (NIST) is transforming new bottom-up Building for Environmental and Economic Sustainability (BEES) data into a hybrid database in which the strengths of both bottom-up and top-down approaches can be combined. The objective of this paper is to describe the framework and the process under which the hybrid BEES database is being built, with an emphasis on its accounting structure. This paper can support other efforts to build hybrid Life Cycle Inventory (LCI) databases.

Methods

The BEES hybridization utilizes the most detailed supply and use tables (SUTs)??known as item-level data??focusing particularly on the construction sectors. First, the partial SUTs at the item level are constructed and connected to standard SUTs that describe the rest of the economy, which is then followed by balancing and ??redefinition.?? Second, item-level environmental data are compiled and then also balanced and redefined, which completes the compilation of the bi-resolution SUTs with environmental data. Third, the bi-resolution SUTs are integrated with the BEES data that have been converted into matrix form. Because the completely rolled out BEES technology matrix involves a significant number of products, the integration prioritizes the product groups that are potentially the most significant contributors to the LCIA results for buildings.

Results

This step-by-step procedure will enable the creation of a hybridized BEES database, combining the strengths of both the bottom-up, process-based data and the top-down, input-output data with enhanced resolution. The benefit of hybridization at the database level??as opposed to at the individual LCA study level??is that whole-building LCA users can adopt the hybrid BEES approach, with its benefit of a more complete system definition, without the training or effort that would be required to construct a hybrid system from scratch. In addition, reformulation of new BEES data into a matrix structure better facilitates the parametric LCA application that is central to NIST??s vision to develop a tool for assessing the sustainability performance of energy technologies and systems in an integrated building design context.

Conclusions

There are currently a number of initiatives being organized to implement a hybrid approach at the LCI database level. In laying out the methodological framework for efficiently transforming an existing LCI database into a hybrid database, this paper can support future development of hybrid LCI databases.     

Life cycle inventory dataset review criteria—a new proposal

Purpose

A review of LCA process datasets is an important element of quality assurance for databases and for other systems to provide LCA datasets. Somewhat surprisingly, a broadly accepted and applicable set of criteria for a review of LCA process datasets was lacking so far. Different LCA databases and frameworks are proposing and using different criteria for reviewing datasets. To close this gap, a set of criteria for reviewing LCA dataset has been developed within the Life Cycle Initiative.

Methods

Previous contributions to LCA dataset review have been analysed for a start, from ISO and various LCA databases. To avoid somewhat arbitrary review criteria, four basic rules are proposed which are to be fulfilled by any dataset. Further, concepts for assessing representativeness and relevance are introduced into the criteria set from established practices in statistics and materiality. To better structure the criteria and to ease their application, they are grouped into clusters. A first version of the developed review criteria was presented in two workshops with database providers and users on different levels of experience, and draft versions of the criteria were shared within the initiative. The current version of the criteria reflects feedback received from various stakeholders and has been applied and tested in a review for newly developed datasets in Brazil, Malaysia and Thailand.

Results and discussion

Overall, 14 criteria are proposed, which are organised in clusters. The clusters are goal, model, value, relevance and procedure. For several criteria, a more science-based definition and evaluation is proposed in comparison to ‘traditional’ LCA. While most of the criteria depend on the goal and scope of dataset development, a core set of criteria are seen as essential and independent from specific LCA modelling. For all the criteria, value scales are developed, typically using an ordinal scale, following the pedigree approach.

Conclusions

Review criteria for LCI datasets are now defined based on a stringent approach. They aim to be globally acceptable, considering also database interoperability and database management aspects, as well as feedback received from various stakeholders, and thus close an important gap in LCA dataset quality assurance. The criteria take many elements of already existing criteria but are the first to fully reflect the implications of the ISO data quality definition, and add new concepts for representativeness and relevance with the idea to better reflect scientific practice outside of the LCA domain. A first application in a review showed to be feasible, with a level of effort similar to applying other review criteria. Aspects not addressed yet are the review procedure and the mutual recognition of dataset reviews, and their application for a very high number of datasets.

     

Economic aspects of commercial manufacture of biopharmaceuticals

Sustained approvals of new biopharmaceuticals supported by a sparkling pipeline are the drivers for the above-market growth of biopharmaceuticals. Due to usually high therapeutic dose of monoclonal antibodies, they are demanding for high capacity needs. This requires significant capital investment and stimulates innovation for process improvement to decrease cost of goods and to save capital investments. Such process improvements are either ongoing along the learning curve or result from significant process changes through regulatory authorities impact. Both approaches require extensive protein analytical guidance to maintain product quality, safety and equivalency. In addition to second generation processes, second generation products have the feature of optimizing the physiological principle of biopharmaceuticals to the therapeutic need and to decrease the therapeutic dose, which goes along with investment savings and lower cost of goods.     

Comparison of Tools for Quantifying the Environmental Performance of an Urban Territory

To support effective urban policies aimed at decreasing the environmental impacts of cities, it is important to develop robust tools for accounting those impacts. Environmentally extended input‐output analysis (EEIOA) is among the most used tools for this purpose, allowing the quantification of both direct and indirect impacts. Life cycle assessment (LCA) is also a holistic and comprehensive tool that accounts for direct and indirect impacts—but its application to cities is still very recent. This study aims at applying EEIOA and LCA to the municipality of Aveiro (Portugal) in order to compare the outcomes of the two tools in terms of total impacts (climate change and fossil fuel depletion) and hotspots (sectors/products contributing most to the impacts), to identify limitations and advantages of the tools when applied to Aveiro, and to illustrate how LCA can be applied to cities. The total impacts estimated with LCA and EEIOA were similar and the hotspots were also the same: transports, food, construction, and electricity. However, the relative contribution of some sectors was very different in the two tools due to methodological differences mainly in system boundaries, type of activities or products considered in each sector, and geographical coverage of impact data. This study concludes that the analyzed tools can provide complementary results to support decision making concerning urban planning and management.     

Simplified tools for global warming potential evaluation: when ‘good enough’ is best

Background, aim and scope  

In spite of a number of lingering issues, life cycle assessment (LCA) is widely recognised as one of the most powerful tools to investigate the environmental performance of a product or service. Carbon footprint (CF) analysis can also be considered a subset of LCA, limited to a single impact category (i.e. global warming potential (GWP)). However, the inherent complexity of a full LCA or CF analysis often stands in the way of their widespread application in the industry and policy-making sectors. For these latter ambits, this paper advocates the adoption of tailor-made streamlined approaches, with reduced inventory requirements and impact assessment scope. Two such examples are provided, respectively addressing the evaluation of GWP in the development of new product standards and the GWP savings attainable through the use of recycled materials.     

Methodology for systematic analysis and improvement of manufacturing unit process life-cycle inventory (UPLCI)—CO2PE! initiative (cooperative effort on process emissions in manufacturing). Part 1: Methodology description

Purpose  

This report proposes a life-cycle analysis (LCA)-oriented methodology for systematic inventory analysis of the use phase of manufacturing unit processes providing unit process datasets to be used in life-cycle inventory (LCI) databases and libraries. The methodology has been developed in the framework of the CO₂PE! collaborative research programme (CO2PE! 2011a) and comprises two approaches with different levels of detail, respectively referred to as the screening approach and the in-depth approach.