Consumption‐based Material Flow Accounting

In 2007, imports accounted for approximately 34% of the material input (domestic extraction and imports) into the Austrian economy and almost 60% of the GDP stemmed from exports. Upstream material inputs into the production of traded goods, however, are not yet included in the standard framework of material flow accounting (MFA). We have reviewed different approaches accounting for these upstream material inputs, or raw material equivalents (RME), positioning them in a wider debate about consumption‐based perspectives in environmental accounting. For the period 1995–2007, we calculated annual RME of Austria's trade and consumption applying a hybrid approach. For exports and competitive imports, we used an environmentally extended input‐output model of the Austrian economy, based on annual supply and use tables and MFA data. For noncompetitive imports, coefficients for upstream material inputs were extracted from life cycle inventories. The RME of Austria's imports and exports were approximately three times larger than the trade flows themselves. In 2007, Austria's raw material consumption was 30 million tonnes or 15% higher than its domestic material consumption. We discuss the material composition of these flows and their temporal dynamics. Our results demonstrate the need for a consumption‐based perspective in MFA to provide robust indicators for dematerialization and resource efficiency analysis of open economies.     

Using spatially explicit commodity flow and truck activity data to map urban material flows

To analyze and promote resource efficiency in urban areas, it is important to characterize urban metabolism and particularly, material flows. Material flow analysis (MFA) offers a means to capture the dynamism of cities and their activities. Urban‐scale MFAs have been conducted in many cities, usually employing variants of the Eurostat methodology. However, current methodologies generally reduce the study area into a “black box,” masking details of the complex processes within the city's metabolism. Therefore, besides the aggregated stocks and flows of materials, the movement of materials—often embedded in goods or commodities—should also be highlighted. Understanding the movement and dispersion of goods and commodities can allow for more detailed analysis of material flows. We highlight the potential benefits of using high‐resolution urban commodity flows in the context of understanding material resource use and opportunities for conservation. Through the use of geographic information systems and visualizations, we analyze two spatially explicit datasets: (1) commodity flow data in the United States, and (2) Global Positioning System‐based commercial vehicle (truck) driver activity data in Singapore. In the age of “big data,” we bring advancements in freight data collection to the field of urban metabolism, uncovering the secondary sourcing of materials that would otherwise have been masked in typical MFA studies. This brings us closer to a consumption‐based, finer‐resolution approach to MFA, which more effectively captures human activities and its impact on urban environments.     

Unified Materials Information System (UMIS): An Integrated Material Stocks and Flows Data Structure

Modern society depends on the use of many diverse materials. Effectively managing these materials is becoming increasingly important and complex, from the analysis of supply chains, to quantifying their environmental impacts, to understanding future resource availability. Material stocks and flows data enable such analyses, but currently exist mainly as discrete packages, with highly varied type, scope, and structure. These factors constitute a powerful barrier to holistic integration and thus universal analysis of existing and yet to be published material stocks and flows data. We present the Unified Materials Information System (UMIS) to overcome this barrier by enabling material stocks and flows data to be comprehensively integrated across space, time, materials, and data type independent of their disaggregation, without loss of information, and avoiding double counting. UMIS can therefore be applied to structure diverse material stocks and flows data and their metadata across material systems analysis methods such as material flow analysis (MFA), input‐output analysis, and life cycle assessment. UMIS uniquely labels and visualizes processes and flows in UMIS diagrams; therefore, material stocks and flows data visualized in UMIS diagrams can be individually referenced in databases and computational models. Applications of UMIS to restructure existing material stocks and flows data represented by block flow diagrams, system dynamics diagrams, Sankey diagrams, matrices, and derived using the economy‐wide MFA classification system are presented to exemplify use. UMIS advances the capabilities with which complex quantitative material systems analysis, archiving, and computation of material stocks and flows data can be performed.     

Evaluating the Use of Global Sensitivity Analysis in Dynamic MFA

Dynamic material flow analysis (MFA) provides information about material usage over time and consequent changes in material stocks and flows. In order to understand the effect of limited data quality and model assumptions on MFA results, the use of sensitivity analysis methods in dynamic MFA studies has been on the increase. So far, sensitivity analysis in dynamic MFA has been conducted by means of a one‐at‐a‐time method, which tests parameter perturbations individually and observes the outcomes on output. In contrast to that, variance‐based global sensitivity analysis decomposes the variance of the model output into fractions caused by the uncertainty or variability of input parameters. The present study investigates interaction and time‐delay effects of uncertain parameters on the output of an archetypal input‐driven dynamic material flow model using variance‐based global sensitivity analysis. The results show that determining the main (first‐order) effects of parameter variations is often sufficient in dynamic MFA because substantial effects attributed to the simultaneous variation of several parameters (higher‐order effects) do not appear for classical setups of dynamic material flow models. For models with time‐varying parameters, time‐delay effects of parameter variation on model outputs need to be considered, potentially boosting the computational cost of global sensitivity analysis. Finally, the implications of exploring the sensitivities of model outputs with respect to parameter variations in the archetypical model are used to derive model‐ and goal‐specific recommendations on choosing appropriate sensitivity analysis methods in dynamic MFA.     

Material Flows and Economic Growth in Developing China

The concept of sustainable development concerns not only the natural environment but also human societies and economies. The method of economy‐wide materials flow accounting and analysis (EW‐MFA) is internationally recognized as a valuable tool for studying the physical dimensions of economies. EW‐MFA has been carried out in many industrialized countries, but very little work has been done for developing China; this article can be regarded as one of the first attempts to study China's economy in terms of materials flows. In this article we have compiled materials flow accounts for China during the time series 1990 to 2002 and derived indicators associated with international comparison. Results show that the annual material consumption of China's economy continuously increased except for a slump around 1998, whereas the material efficiency exhibited a three‐phase trend reflecting different macropolicies of the Eighth, Ninth, and Tenth Five‐Year Plans implemented by the central government. Based on this experience with EW‐MFA for China, suggestions for methodology development and further research are given for improving EW‐MFA as a more effective tool for environmental management.     

Combining Material Flow Analysis,Life Cycle Assessment,and Multiattribute Utility Theory

Three assessment methods, material flow analysis (MFA), life cycle analysis (LCA), and multiattribute utility theory (MAUT) are systematically combined for supporting the choice of best end‐of‐life scenarios for polyethylene terephthalate (PET) waste in a municipality of a developing country. MFA analyzes the material and energy balance of a firm, a region, or a nation, identifying the most relevant processes; LCA evaluates multiple environmental impacts of a product or a service from cradle to grave; and MAUT allows for inclusion of other aspects along with the ecological ones in the assessment. We first systematically coupled MFA and LCA by defining “the service offered by the total PET used during one year in the region” as the functional unit. Inventory and impacts were calculated by multiplying MFA flows with LCA impacts per kilogram. We used MAUT to include social and economic aspects in the assessment. To integrate the subjective point of view of stakeholders in the MAUT, we normalized the environmental, social, and economic variables with respect to the magnitude of overall impacts or benefits in the country. The results show large benefits for recycling scenarios from all points of view and also provide information about waste treatment optimization. The combination of the three assessment methods offers a powerful integrative assessment of impacts and benefits. Further research should focus on data collection methods to easily determine relevant material flows. LCA impact factors specific to Colombia should be developed, as well as more reliable social indicators.     

A Novel Approach to Characterize Data Uncertainty in Material Flow Analysis and its Application to Plastics Flows in Austria

Material flow analysis (MFA) is widely used to investigate flows and stocks of resources or pollutants in a defined system. Data availability to quantify material flows on a national or global level is often limited owing to data scarcity or lacking data. MFA input data are therefore considered inherently uncertain. In this work, an approach to characterize the uncertainty of MFA input data is presented and applied to a case study on plastics flows in major Austrian consumption sectors in the year 2010. The developed approach consists of data quality assessment as a basis for estimating the uncertainty of input data. Four different implementations of the approach with respect to the translation of indicator scores to uncertainty ranges (linear‐ vs. exponential‐type functions) and underlying probability distributions (normal vs. log‐normal) are examined. The case study results indicate that the way of deriving uncertainty estimates for material flows has a stronger effect on the uncertainty ranges of the resulting plastics flows than the assumptions about the underlying probability distributions. Because these uncertainty estimates originate from data quality evaluation as well as uncertainty characterization, it is crucial to use a well‐defined approach, building on several steps to ensure the consistent translation of the data quality underlying material flow calculations into their associated uncertainties. Although subjectivity is inherent in uncertainty assessment in MFA, the proposed approach is consistent and provides a comprehensive documentation of the choices underlying the uncertainty analysis, which is essential to interpret the results and use MFA as a decision support tool.     

Assessing the “Short Mental Distance” in Eco‐Industrial Networks

Like many economic exchanges, industrial symbiosis (IS) is thought to be influenced by social relationships and shared norms among actors in a network. While many implicit references to social characteristics exist throughout the literature, there have been few explicit attempts to operationalize and measure the concepts. The “short mental distance,”“trust,”“openness,” and “communication” recorded among managers in Kalundborg, Denmark, set a precedent for examining and encouraging social interactions among key personnel in the dozens of eco‐industrial networks around the world. In this article we explore the relationships among various aspects of social embeddedness, social capital, and IS. We develop a conceptual framework and an approach using quantitative and qualitative methods to identify and measure these social characteristics, including social network structure, communication, and similarities in norms and conceptions of waste, and apply them in an industrial network in Nanjangud, South India. The findings suggest that there is a fairly high level of shared norms about dealing with waste—the “short mental distance”—in this network, but by‐product transactions are only weakly correlated with the structure and content of communication among managers. Replication of this approach can increase the understanding and comparability of the role of social characteristics in eco‐industrial activities around the world.     

Economic Integration in Tanzania (1970–2011): A Biophysical Assessment

This article assesses the impact of economic integration on Tanzania's sociometabolic profile for the years 1970–2011, which witnessed an opening and further integration of Tanzania's economy through increased trade and foreign investment, through a time‐series economy‐wide material flows analysis (EW‐MFA). The EW‐MFA results show that contrary to the trade patterns of many developing countries, increased economic integration has resulted in Tanzania becoming a net importer of resources across all material categories when measured by the physical trade balance indicator. Additionally, the article discusses the conceptual and empirical challenges of measuring ecologically unequal exchange with EW‐MFAs for developing countries whose export profiles are dominated by lightweight, high‐value precious stones and metals. It also assesses the degree to which the Tanzanian economy has undergone dematerialization over the past 40 years of economic integration.     

Global Patterns and Trends for Non‐Metallic Minerals used for Construction

Despite accounting for almost 50% of global material use, nonmetallic minerals—mostly used for construction of buildings and infrastructure—are the material flow analysis (MFA) category with the highest uncertainty. The main reason for this is incomplete reporting in official national statistics because of ease of availability and the low per‐unit cost of these materials. However, the environmental burden associated with nonmetallic minerals, which include energy use for extraction and transport, land‐use change, and disposal of large amounts of construction demolition waste, call for a thorough understanding of the magnitude of nonmetallic mineral flows. Previous estimates for nonmetallic minerals have used simplistic assumptions. This study aims to increase the precision of nonmetallic mineral accounts at national and global level using consumption of bitumen, bricks, cement, and railways in combination with technical coefficients from the engineering literature to infer the actual yearly consumption of nonmetallic minerals. We estimate the extraction of nonmetallic minerals and provide uncertainty estimates for the new accounts as well as information about consumption by different sectors. Analyzing the evolution of consumption for seven world regions, we find that, in North America and Europe, the consumption of nonmetallic minerals over the past 40 years has followed the growth patterns of population, whereas for all other regions consumption has been closely related to gross domestic product (GDP). A more accurate account of global and country‐by‐country extraction of nonmetallic minerals may provide insights into supply shortages and inform waste management strategies for construction and demolition waste.     

Using Web‐Based Technology to Bring Hands‐On Urban Material Flow Analysis to the Classroom

The main objective of this article is to introduce an open‐source, online software tool called OMAT as a teaching tool for performing economy wide‐material flow analysis (EW‐MFA) at urban or regional level in industrial ecology curricula. To that intent, we present a classroom and project activity that was developed for a masters‐level industrial ecology course offered by the Autonomous University of Barcelona. Insights are provided with regards to the outcome of the classroom exercise as well as lessons learned from both an academic and a software development point of view. The OMAT software provides users with a specialized tool to enter and process MFA data in a simple, intuitive way. The usefulness of OMAT as a teaching tool was tested by engaging students in a classroom activity that entailed using OMAT as a tool to perform an EW‐MFA applied to the Metropolitan Area of Barcelona for the years 2005‐2011. The aim of this exercise was to teach students specific skills required in performing an EW‐MFA, not through theory classes, but hands‐on through a learn‐as‐you‐go approach. The exercise not only equipped the students with knowledge about MFA, but also introduced them to solving problems as a team, meeting project deadlines, and communicating effectively with colleagues from different disciplines and backgrounds. Even though there is room for further improvements, this exercise showed that OMAT provided a useful addition to traditional methods that allowed students to get a more practical and thorough understanding of the MFA methodology.     

Unintentional Flow of Alloying Elements in Steel during Recycling of End‐of‐Life Vehicles

Alloying elements in steel add a wide range of valuable properties to steel materials that are indispensable for the global economy. However, they are likely to be effectively irretrievably blended into the steel when recycled because of (among other issues) the lack of information about the composition of the scrap. This results in the alloying elements dissipating in slag during steelmaking and/or becoming contaminants in secondary steel. We used the waste input‐output material flow analysis model to quantify the unintentional flows of alloying elements (i.e., chromium, nickel, and molybdenum) that occur in steel materials and that result from mixing during end‐of‐life (EOL) processes. The model can be used to predict in detail the flows of ferrous materials in various phases, including the recycling phase by extending steel, alloying element source, and iron and steel scrap sectors. Application of the model to Japanese data indicates the critical importance of the recycling of EOL vehicles (ELVs) in Japan because passenger cars are the final destination of the largest share of these alloying elements. However, the contents of alloying elements are rarely considered in current ELV recycling. Consequently, the present study demonstrates that considerable amounts of alloying elements, which correspond to 7% to 8% of the annual consumption in electric arc furnace (EAF) steelmaking, are unintentionally introduced into EAFs. This result suggests the importance of quality‐based scrap recycling for efficient management of alloying elements.     

Whole‐genome resequencing‐based QTL‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human‐made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy‐to‐use genetic markers enables early‐generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL‐seq approach for identification of key genomic regions and candidate genes. Whole‐genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta‐SNP index and identified a total of 10,759 genomewide high‐confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes—RING‐H2 finger protein and zeaxanthin epoxidase—were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL‐seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut.     

物质流分析研究述评

物质流分析方法近年来在循环经济和可持续发展研究领域发展迅速。阐述了物质流分析的定义及其与自然生态系统物质流的区别,着重回顾了该研究方法的发展历程,阐明了物质流分析的主要观点、理论基础、研究思路及研究框架,详细阐译和对比分析了物质流分析的六大类指标及分析方法,并在物质流分析框架的基础上,建立循环经济及可持续发展的评价指标体系,并对物质流分析指标体系和方法学的研究意义及其在环境经济学中的地位进行了客观的评价,进而指出了物质流分析方法的不足之处。对物质流分析在不同层次的应用研究也进行了充分的阐述和分析。对物质流分析今后相关领域的进一步研究予以了讨论和展望。     

Business‐to‐Business Information Technology User Practices at End of Life in the United Kingdom,Germany, and France

Business‐to‐business (B2B) electronics account for a significant volume of the electrical and electronic equipment (EEE) put on the market. Very little B2B waste electrical and electronic equipment (WEEE) is reported as collected in the European Union (EU) in compliance with the WEEE Directive, which uses the policy principle of extended producer responsibility (EPR) to ensure that WEEE is managed correctly. This presents a barrier to parties looking for access to the waste. Company practice dictates the channels into which B2B WEEE flows following primary use. This article presents a study that engaged with company actors directly to get a better understanding of business information technology (IT) EEE asset management. Data were collected to determine the barriers current practice could present to the collection of B2B IT EEE at end of life and the implications of these for the development of policies and strategies for EPR. A questionnaire was developed and data were gathered from organizations in three EU countries—the United Kingdom, Germany, and France—stratified by size. Some notable findings were that there are several routes by which end‐of‐life B2B WEEE can flow. The recycling and refurbishment of B2B IT units at end of use was shown to be commonplace, but it is likely that these units enter streams where they are not reported. The actors disposing of their units did not have information on the management or disposition of these streams. It is concluded that to achieve the goals of EPR for B2B IT WEEE, the networks and the operational practices of these streams need to be better understood when developing strategies and policies.     

A Probabilistic Dynamic Material Flow Analysis Model for Chinese Urban Housing Stock

The stock‐driven dynamic material flow analysis (MFA) model is one of the prevalent tools to investigate the evolution and related material metabolism of the building stock. There exists substantial uncertainty inherent to input parameters of the stock‐driven dynamic building stock MFA model, which has not been comprehensively evaluated yet. In this study, a probabilistic, stock‐driven dynamic MFA model is established and China's urban housing stock is selected as the empirical case. This probabilistic dynamic MFA model has the ability to depict the future evolution pathway of China's housing stock and capture uncertainties in its material stock, inflow, and outflow. By means of probabilistic methods, a detailed and transparent estimation of China's housing stock and its material metabolism behavior is presented. Under a scenario with a saturation level of the population, urbanization, and living space, the median value of the urban housing stock area, newly completed area, and demolished area would peak at around 49, 2.2, and 2.2 billion square meters, respectively. The corresponding material stock and flows are 79, 3.5, and 3.3 billion tonnes, respectively. Uncertainties regarding housing stock and its material stock and flows are non‐negligible. Relative uncertainties of the material stock and flows are above 50%. The uncertainty importance analysis demonstrates that the material intensity and the total population are major contributions to the uncertainty. Policy makers in the housing sector should consider the material efficiency as an essential policy to mitigate material flows of the urban building stock and to lower the risk of policy failures.     

Full Mode and Attribution Mode in Environmental Analysis

Several tools exist for the analysis of the environmental impacts of chains or networks of processes. These relatively simple tools include materials flow accounting (MFA), substance flow analysis (SFA), life-cycle assessment (LCA), energy analysis, and environmentally extended input-output analysis (IOA), all based on fixed input-output relations. They are characterized by the nature of their flow objects, such as products, materials, energy, substances, or money flows, and by their spatial and temporal characteristics. These characteristics are insufficient for their methodological characterization, and sometimes lead to inappropriate use. More clarity is desirable, both for clearer guidance of applications and for a more consistent methodology development. In addition to the nature of the flow object and to spatial and temporal characteristics, another key feature concerns the way in which processes are included in a system to be analyzed.
The inclusion of processes can be done in two fundamentally different ways: according to a full mode of analysis, with the inclusion of all flows and related processes to their full extent as present in a region in a specific period of time; and according to an attribution mode, taking processes into account insofar as these are required for a given social demand, function, or activity, in principle whenever and wherever these processes take place. This distinction, which cuts across families of tools that traditionally belong together, appears to have significant methodological and practical implications. Thus the distinction between the two modes of analysis, however crucial it may be, strengthens the idea of one coherent family of tools for environmental systems analysis.     

Mass Spectrometry‐Based Analysis of Time‐Resolved Proteome Quantification

The aspect of time is essential in biological processes and thus it is important to be able to monitor signaling molecules through time. Proteins are key players in cellular signaling and they respond to many stimuli and change their expression in many time‐dependent processes. Mass spectrometry (MS) is an important tool for studying proteins, including their posttranslational modifications and their interaction partners—both in qualitative and quantitative ways. In order to distinguish the different trends over time, proteins, modification sites, and interacting proteins must be compared between different time points, and therefore relative quantification is preferred. In this review, the progress and challenges for MS‐based analysis of time‐resolved proteome dynamics are discussed. Further, aspects on model systems, technologies, sampling frequencies, and presentation of the dynamic data are discussed.     

厦门市资源水与虚拟水耦合代谢效率评价

自然水循环与社会水循环的关联研究是制定系统性水代谢对策的前提。从水资源代谢过程与格局角度,用物质流分析法(MFA)剖析了亚热带季风气候雨影区缺水城市枯水年份资源水与虚拟水耦合代谢的路径、数量,提取代谢效率评价所需的过程与结构指标,以社会、经济、生态环境效益最优化为评价原则构建了城市水资源代谢效率评价指标体系,采用层次分析法赋权,评价了近10年来枯水年份厦门市资源水与虚拟水耦合代谢效率。结果表明,厦门水资源代谢效率呈加速提高趋势,主要由用水效率类和水代谢过程与结构类指标驱动。说明提高水资源代谢效率的根本对策在于用水行为和用水过程与结构的改善。采用情景分析法设计主导驱动指标不同组合下水资源代谢效率情景方案,提高了方案的可操作性,可基于这些指标制定水资源管理对策。基于MFA结果提取指标丰富了指标体系构建理论。