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.     

Information Content,Complexity, and Uncertainty in Material Flow Analysis

Material Flow Analysis (MFA) is a useful method for modeling, understanding, and optimizing sociometabolic systems. Among others, MFAs can be distinguished by two general system properties: First, they differ in their complexity, which depends on system structure and size. Second, they differ in their inherent uncertainty, which arises from limited data quality. In this article, uncertainty and complexity in MFA are approached from a systems perspective and expressed as formally linked phenomena. MFAs are, in a graph‐theoretical sense, understood as networks. The uncertainty and complexity of these networks are computed by use of information measures from the field of theoretical ecology. The size of a system is formalized as a function of its number of flows. It defines the potential information content of an MFA system and holds as a reference against which complexity and uncertainty are gauged. Integrating data quality measures, the uncertainty of an MFA before and after balancing is determined. The actual information content of an MFA is measured by relating its uncertainty to its potential information content. The complexity of a system is expressed based on the configuration of each individual flow in relation to its neighboring flows. The proposed metrics enable different material flow systems to be compared to one another and the role of individual flows within a system to be assessed. They provide information useful for the design of MFAs and for the communication of MFA results. For exemplification, the regional MFAs of aluminum and plastics in Austria are analyzed in this article.     

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.     

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.     

Dynamic Modeling of In‐Use Cement Stocks in the United States

A dynamic substance‐flow model is developed to characterize the stocks and flows of cement utilized during the 20th century in the United States, using the generic cement life cycle as a systems boundary. The motivation for estimating historical inventories of cement stocks and flows is to provide accurate estimates of contemporary cement in‐use stocks in U.S. infrastructure and future discards to relevant stakeholders in U.S. infrastructure, such as the federal and state highway administrators, departments of transportation, public and private utilities, and the construction and cement industries. Such information will assist in planning future rehabilitation projects and better life cycle management of infrastructure systems. In the present policy environment of climate negotiations, estimates of in‐use cement infrastructure can provide insights about to what extent built environment can act as a carbon sink over its lifetime. The rate of addition of new stock, its composition, and the repair of existing stock are key determinants of infrastructure sustainability. Based upon a probability of failure approach, a dynamic stock and flow model was developed utilizing three statistical lifetime distributions—Weibull, gamma, and lognormal—for each cement end‐use. The model‐derived estimate of the “in‐use” cement stocks in the United States is in the range of 4.2 to 4.4 billion metric tons (gigatonnes, Gt). This indicates that 82% to 87% of cement utilized during the last century is still in use. On a per capita basis, this is equivalent to 14.3 to 15.0 tonnes of in‐use cement stock per person. The in‐use cement stock per capita has doubled over the last 50 years, although the rate of growth has slowed.     

Tracking Construction Material over Space and Time: Prospective and Geo‐referenced Modeling of Building Stocks and Construction Material Flows

Construction material plays an increasingly important role in the environmental impacts of buildings. In order to investigate impacts of materials on a building level, we present a bottom‐up building stock model that uses three‐dimensional and geo‐referenced building data to determine volumetric information of material stocks in Swiss residential buildings. We used a probabilistic modeling approach to calculate future material flows for the individual buildings. We investigated six scenarios with different assumptions concerning per‐capita floor area, building stock turnover, and construction material. The Swiss building stock will undergo important structural changes by 2035. While this will lead to a reduced number in new constructions, material flows will increase. Total material inflow decreases by almost half while outflows double. In 2055, the total amount of material in‐ and outflows are almost equal, which represents an important opportunity to close construction material cycles. Total environmental impacts due to production and disposal of construction material remain relatively stable over time. The cumulated impact is slightly reduced for the wood‐based scenario. The scenario with more insulation material leads to slightly higher material‐related emissions. An increase in per‐capita floor area or material turnover will lead to a considerable increase in impacts. The new modeling approach overcomes the limitations of previous bottom‐up building models and allows for investigating building material flows and stocks in space and time. This supports the development of tailored strategies to reduce the material footprint and environmental impacts of buildings and settlements.     

A Material Flow Accounting Case Study of the Lisbon Metropolitan Area using the Urban Metabolism Analyst Model

This article describes a new methodological framework to account for urban material flows and stocks, using material flow accounting (MFA) as the underlying method. The proposed model, urban metabolism analyst (UMAn), bridges seven major gaps in previous urban metabolism studies: lack of a unified methodology; lack of material flows data at the urban level; limited categorizations of material types; limited results about material flows as they are related to economic activities; limited understanding of the origin and destination of flows; lack of understanding about the dynamics of added stock; and lack of knowledge about the magnitude of the flow of materials that are imported and then, to a great extent, exported. To explore and validate the UMAn model, a case study of the Lisbon Metropolitan Area was used. An annual time series of material flows from 2003 to 2009 is disaggregated by the model into 28 material types, 55 economic activity categories, and 18 municipalities. Additionally, an annual projection of the obsolescence of materials for 2010–2050 was performed. The results of the case study validate the proposed methodology, which broadens the contribution of existing urban MFA studies and presents pioneering information in the field of urban metabolism. In particular, the model associates material flows with economic activities and their spatial location within the urban area.     

Evaluation of Modeling Approaches to Determine End‐of‐Life Flows Associated with Buildings: A Viennese Case Study on Wood and Contaminants

Dynamic material flow analysis enables the forecasting of secondary raw material potential for waste volumes in future periods, by assessing past, present, and future stocks and flows of materials in the anthroposphere. Analyses of waste streams of buildings stocks are uncertain with respect to data and model structure. Wood construction in Viennese buildings serve as a case study to compare different modeling approaches for determining end‐of‐life (EoL) wood and corresponding contaminant flows (lead, chlorine, and polycyclic aromatic hydrocarbons). A delayed input and a leaching stock modeling approach are used to determine wood stocks and flows from 1950 until 2100. Cross‐checking with independent estimates and sensitivity analyses are used to evaluate the results’ plausibility. In the situation of the given data in the present case study, the delay approach is a better choice for historical observations of EoL wood and for analyses at a substance level. It has some major drawbacks for future predictions at the goods level, though, as the durability of a large number of historical buildings with considerably higher wood content is not reflected in the model. The wood content parameter differs strongly for the building periods and has therefore the highest influence on the results. Based on this knowledge, general recommendations can be derived for analyses on waste flows of buildings at a goods and substance level.     

Anthropogenic Carbon Stock Dynamics of Pulp and Paper Products in Germany

Carbon‐based materials (CBMs) for energetic and material purposes combine biogenic and anthropogenic carbon cycles. In the latter, numerous manufactured products with various in‐use lifespans accumulate as anthropogenic carbon stocks. Understanding the behavior of these stocks is an important requirement to estimate not only future waste amounts, source for secondary raw materials, but also the impacts and effects in carbon emissions and carbon management. Previous models have estimated material stock changes; however, a lack of research in carbon stocks is perceived. Moreover, studies follow in‐use lifespan estimation approaches, such as decay functions, which do not coincide with observed consumption and waste treatment patterns. In the first part of this article, we present a carbon stock‐flow model to analyze inter‐relationships between carbon flows and stocks from raw materials to waste treatment processes considering a consumer perspective, where the dynamics of anthropogenic carbon stocks are completely described. In the second part, we study the pulp and paper industry in Germany under a scenario approach to analyze the behavior, development, and impacts of paper stocks and flows between 2010 and 2040. The model provided coherent results, with industrial data estimating 33.9 million metric tons in 2010 in paper stocks, equivalent to 410 kilograms per person. Consumption per capita and in‐use lifespan of products were identified as the most significant variables in carbon stock building. Model simulations show a sustained growth in stocks for the next 30 years, with increase in waste and carbon emissions. But in combination with recycling and reuse mechanisms and consumption patterns, environmental impacts are reduced.     

Approaches for Quantifying the Metabolism of Physical Economies: Part I: Methodological Overview

This article is the first of a two-part series that describes and compares the essential features of nine existing "physical economy" approaches for quantifying the material demands of the human economy upon the natural environment. A range of material flow analysis (MFA) and related techniques is assessed and compared in terms of several major dimensions. These include the system boundary identification for material flow sources, extents, and the key socioinstitutional entities containing relevant driving forces, as well as the nature and detailing of system components and flow interconnections, and the comprehensiveness and types of flows and materials covered.
Shared conceptual themes of a new wave of physical economy approaches are described with a brief overview of the potential applications of this broad family of methodologies. The evolving and somewhat controversial nature of the characteristics and role that define MFA is examined. This review suggests the need to specify whether MFA is a general metabolic flow measurement procedure that can be applied from micro to macrolevels of economic activity, or a more specific methodology aimed primarily at economy-wide analyses that "map" the material relations between society and nature. Some alternative options for classifying MFA are introduced for discussion before a more detailed comparative summary of the key methodological features of each approach in the second part of this two-part article.
The review is presented (1) as a reference and resource for the increasing number of policy makers and practitioners involved in industrial ecology and the evaluation of the material basis of economies and the formulation of eco-efficiency strategies, and (2) to provoke discussion and ongoing dialogue to clarify the many existing areas of discordance in environmental accounting related to material flows, and help consolidate the methodological basis and application of MFA.     

Maintenance and Expansion: Modeling Material Stocks and Flows for Residential Buildings and Transportation Networks in the EU25

Material stocks are an important part of the social metabolism. Owing to long service lifetimes of stocks, they not only shape resource flows during construction, but also during use, maintenance, and at the end of their useful lifetime. This makes them an important topic for sustainable development. In this work, a model of stocks and flows for nonmetallic minerals in residential buildings, roads, and railways in the EU25, from 2004 to 2009 is presented. The changing material composition of the stock is modeled using a typology of 72 residential buildings, four road and two railway types, throughout the EU25. This allows for estimating the amounts of materials in in‐use stocks of residential buildings and transportation networks, as well as input and output flows. We compare the magnitude of material demands for expansion versus those for maintenance of existing stock. Then, recycling potentials are quantitatively explored by comparing the magnitude of estimated input, waste, and recycling flows from 2004 to 2009 and in a business‐as‐usual scenario for 2020. Thereby, we assess the potential impacts of the European Waste Framework Directive, which strives for a significant increase in recycling. We find that in the EU25, consisting of highly industrialized countries, a large share of material inputs are directed at maintaining existing stocks. Proper management of existing transportation networks and residential buildings is therefore crucial for the future size of flows of nonmetallic minerals.     

Material and Energy Flows and Environmental Impacts of the Internet in Switzerland

The Internet leads to material and energy consumption as well as various environmental impacts on both the regional and global scale. Yet, assessments of the Internet's energy consumption and resulting greenhouse gas emissions are still rare, and assessments of material flows and further environmental impacts are virtually non‐existent. This article investigates material flows, the direct energy consumption during the use phase, as well as environmental impacts linked to the service, “Internet in Switzerland.” In our model, the service, Internet in Switzerland, is divided into various Internet participant categories. All devices used to access or provide Internet services are merged in a limited number of equipment families and, as such, included in an inventory of the existing infrastructure (stock). Based on this inventory, a material flow analysis (MFA) is performed, which includes the current stock as well as flows resulting from growth and disposal. The direct energy consumption for the operation of the infrastructure is quantified. Environmental impacts are calculated with a life cycle assessment approach, using the ecoinvent database and the software, SimaPro, applying four different methods. The MFA results in a 2009 stock of 98,100 tonnes. Approximately 4,130 gigawatt hours per year, or 7% of the total Swiss electricity consumption, were used in 2009 to operate the Swiss infrastructure. The environmental impacts caused during the production and use phases vary significantly depending on the assessment method chosen. The disposal phase had mainly positive impacts as a result of material recovery.     

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。     

A Data Characterization Framework for Material Flow Analysis

The validity of material flow analyses (MFAs) depends on the available information base, that is, the quality and quantity of available data. MFA data are cross‐disciplinary, can have varying formats and qualities, and originate from heterogeneous sources, such as official statistics, scientific models, or expert estimations. Statistical methods for data evaluation are most often inadequate, because MFA data are typically isolated values rather than extensive data sets. In consideration of the properties of MFA data, a data characterization framework for MFA is presented. It consists of an MFA data terminology, a data characterization matrix, and a procedure for database analysis. The framework facilitates systematic data characterization by cell‐level tagging of data with data attributes. Data attributes represent data characteristics and metainformation regarding statistical properties, meaning, origination, and application of the data. The data characterization framework is illustrated in a case study of a national phosphorus budget. This work furthers understanding of the information basis of material flow systems, promotes the transparent documentation and precise communication of MFA input data, and can be the foundation for better data interpretation and comprehensive data quality evaluation.     

Material Flows in a Social Context: A Vietnamese Case Study Combining the Materials Flow Analysis and Action‐in‐Context Frameworks

Materials flow analysis (MFA) is one of the central achievements of industrial ecology. One direction in which one can move MFA beyond mere accounting is by putting the material flows in their social context. This “socially extended MFA” may be carried out at various levels of aggregation. In this article, specific material flows will be linked to concrete actors and mechanisms that cause these flows—using the action‐in‐context (AiC) framework, which contains, inter alia, both proximate and indirect actors and factors. The case study site is of Tat hamlet in Vietnam, set in a landscape of paddy fields on valley floors surrounded by steep, previously forested slopes. Out of the aggregate MFA of Tat, the study focuses on material flows associated with basic needs and sustainability. The most important actors causing these material flows are farming households, politicians, traders, and agribusiness firms—of which local politicians turned out to be pivotal. The study shows the value of combining MFA with actor‐based social analysis. MFA achieves the balanced quantification of the physical system, thus helping to pinpoint key processes. Actor‐based analysis adds the causal understanding of what drives these key processes, leading to improved scenarios of the future and the effective identification of target groups and instruments for policy making.     

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.     

Applying Ecological Input-Output Flow Analysis to Material Flows in Industrial Systems

This article, continuing with the themes of the companion article, expounds the capabilities of input-output techniques as applied to material flows in industrial systems. Material flows are the primary focus because of their role in directly linking natural and industrial systems and thereby being fundamental components of environmental issues in industrial economies. The specific topic in this article concerns several material flow metrics used to characterize system behavior that are derived from the ecological development of input-output techniques; most notable of these metrics are several measures of material cycling and a measure of the number of processes visited by material while in a system. These metrics are shown to be useful in analyzing the state of material flow systems. Further-more, the metrics are shown to be a central link in connecting input-output flow analysis to synthesis (i.e., the process of using measurements of system behavior to design changes to that system). By connecting the flow metrics to both environmental objectives and controllable aspects of flow models, changes to existing flow systems are synthesized to generate improved system behavior. To bring this pair of articles to a close, several limitations of input-output flow analysis are summarized with the goal of stimulating further interest and research.     

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.     

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.