Applying Fuzzy and Probabilistic Uncertainty Concepts to the Material Flow Analysis of Palladium in Austria

Material flow analysis (MFA) is a widely applied tool to investigate resource and recycling systems of metals and minerals. Owing to data limitations and restricted system understanding, MFA results are inherently uncertain. To demonstrate the systematic implementation of uncertainty analysis in MFA, two mathematical concepts for the quantification of uncertainties were applied to Austrian palladium (Pd) resource flows and evaluated: (1) uncertainty ranges expressed by fuzzy sets and (2) uncertainty ranges defined by normal distributions given as mean values and standard deviations. Whereas normal distributions represent the traditional approach for quantifying uncertainties in MFA, fuzzy sets may offer additional benefits in relation to uncertainty quantification in cases of scarce information. With respect to the Pd case study, the fuzzy representation of uncertain quantities is more consistent with the actual data availability in cases of incomplete databases, and fuzzy sets serve to highlight the effect of uncertainty on resource efficiency indicators derived from the MFA results. For both approaches, data reconciliation procedures offer the potential to reduce uncertainty and evaluate the plausibility of the model results. With respect to Pd resource management, improved formal collection of end‐of‐life (EOL) consumer products is identified as a key factor in increasing the recycling efficiency. In particular, the partial export of EOL vehicles represents a substantial loss of Pd from the Austrian resource system, whereas approximately 70% of the Pd in the EOL consumer products is recovered in waste management. In conclusion, systematic uncertainty analysis is an integral part of MFA required to provide robust decision support in resource management.     

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.     

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.     

Trade, Materials Flows, and Economic Development in the South: The Example of Chile

Materials flow analysis (MFA) is internationally recognized as a key tool to assess the biophysical metabolism of societies and to provide aggregated indicators for environmental pressures of human activities. Economy-wide MFAs have been compiled for a number of Organisation for Economic Cooperation and Development (OECD) countries, but so far very few studies exist for countries in the South. In this article, the first materials-flow-based indicators for Chile are presented. The article analyzes the restructuring of the Chilean economy toward an active integration in the world markets from the perspective of natural resource use in a time series from 1973 to 2000. Special emphasis is placed on the assessment of materials flows related to Chile's international trade relations. Results show that material inputs to the Chilean economy increased by a factor of 6, mainly as a result of the promotion of resource-intensive exports from the mining, fruit growing, forestry, and fishery sectors. At more than 40 tons, Chile's resource use per capita at present is one of the highest in the world. The article addresses the main shortcomings of the MFA approach, such as weightbased aggregation and the missing links between environmental pressures and impacts, and gives suggestions for methodological improvements and possible extensions of the MFA framework, with the intent of developing MFA into a more powerful tool for policy use.     

Metabolic flux analysis in plants: coping with complexity

Theory and experience in metabolic engineering both show that metabolism operates at the network level. In plants, this complexity is compounded by a high degree of compartmentation and the synthesis of a very wide array of secondary metabolic products. A further challenge to understanding and predicting plant metabolic function is posed by our ignorance about the structure of metabolic networks even in well-studied systems. Metabolic flux analysis (MFA) provides tools to measure and model the functioning of metabolism, and is making significant contributions to coping with their complexity.
This review gives an overview of different MFA approaches, the measurements required to implement them and the information they yield. The application of MFA methods to plant systems is then illustrated by several examples from the recent literature. Next, the challenges that plant metabolism poses for MFA are discussed together with ways that these can be addressed. Lastly, new developments in MFA are described that can be expected to improve the range and reliability of plant MFA in the coming years.     

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.     

Eukaryotic metabolism: measuring compartment fluxes

Metabolic compartmentation represents a major characteristic of eukaryotic cells. The analysis of compartmented metabolic networks is complicated by separation and parallelization of pathways, intracellular transport, and the need for regulatory systems to mediate communication between interdependent compartments. Metabolic flux analysis (MFA) has the potential to reveal compartmented metabolic events, although it is a challenging task requiring demanding experimental techniques and sophisticated modeling. At present no ready-made solution can be provided to cope with the complexity of compartmented metabolic networks, but new powerful tools are emerging. This review gives an overview of different strategies to approach this issue, focusing on different MFA methods and highlighting the additional information that should be included to improve the outcome of an experiment and associate estimation procedures.     

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.     

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.     

Balance between Noise and Information Flow Maximizes Set Complexity of Network Dynamics

Boolean networks have been used as a discrete model for several biological systems, including metabolic and genetic regulatory networks. Due to their simplicity they offer a firm foundation for generic studies of physical systems. In this work we show, using a measure of context-dependent information, set complexity, that prior to reaching an attractor, random Boolean networks pass through a transient state characterized by high complexity. We justify this finding with a use of another measure of complexity, namely, the statistical complexity. We show that the networks can be tuned to the regime of maximal complexity by adding a suitable amount of noise to the deterministic Boolean dynamics. In fact, we show that for networks with Poisson degree distributions, all networks ranging from subcritical to slightly supercritical can be tuned with noise to reach maximal set complexity in their dynamics. For networks with a fixed number of inputs this is true for near-to-critical networks. This increase in complexity is obtained at the expense of disruption in information flow. For a large ensemble of networks showing maximal complexity, there exists a balance between noise and contracting dynamics in the state space. In networks that are close to critical the intrinsic noise required for the tuning is smaller and thus also has the smallest effect in terms of the information processing in the system. Our results suggest that the maximization of complexity near to the state transition might be a more general phenomenon in physical systems, and that noise present in a system may in fact be useful in retaining the system in a state with high information content.     

从系统到景观:区域物质流分析的景观取向

物质流过程是考察系统属性的重要维度。区域物质流分析在研究框架、指标体系、数据集成、管理应用等方面的发展困境,都不同程度地反映了"黑箱假设"以及"系统隐喻"等产业生态学理论的应用局限性。基于整合复杂性科学、广义进化论的生态学组织层次理论,对区域物质流分析开展理论探讨,指出应在原有的"系统"思维之外引入"景观"概念,以拓展区域物质流分析的空间与认知维度。基于"从系统到景观"的理念,将景观生态学原理引入区域物质流分析,建构区域物质流分析的景观取向,并从空间结构与认知图式两个方面对这一取向的核心涵义做以解读。结合区域物质流分析的最新研究案例,从多尺度MFA的综合研究框架、物质流动过程的时空集成研究、物质流动过程的空间行为管理等几个方面,对区域物质流分析的景观取向做了进一步探讨。     

Metabolic flux analysis and visualization

One of the ultimate goals of systems biology research is to obtain a comprehensive understanding of the control mechanisms of complex cellular metabolisms. Metabolic Flux Analysis (MFA) is a important method for the quantitative estimation of intracellular metabolic flows through metabolic pathways and the elucidation of cellular physiology. The primary challenge in the use of MFA is that many biological networks are underdetermined systems; it is therefore difficult to narrow down the solution space from the stoichiometric constraints alone. In this tutorial, we present an overview of Flux Balance Analysis (FBA) and (13)C-Metabolic Flux Analysis ((13)C-MFA), both of which are frequently used to solve such underdetermined systems, and we demonstrate FBA and (13)C-MFA using the genome-scale model and the central carbon metabolism model, respectively. Furthermore, because such comprehensive study of intracellular fluxes is inherently complex, we subsequently introduce various pathway mapping and visualization tools to facilitate understanding of these data in the context of the pathways. Specific visualization of MFA results using the BioCyc Omics Viewer and Pathway Projector are shown as illustrative examples.     

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.     

基于MFA的生态工业园区物质代谢研究方法探析

物质流分析(Material Flow Analysis,MFA)是国家尺度物质代谢研究的重要手段。首先对国内外不同地域尺度下MFA的研究现状进行了概述总结;在此基础上,从工业区内的企业及其所形成的工业共生网络(Industrial Symbiosis Networks,ISNs)物质核算入手,针对如何在生态工业园区(Eco-Industrial Parks,EIPs)尺度开展物质代谢研究进行了详细论述,并通过引入部门间实物型投入产出表(Physical Input-Output Table,PIOT)对该尺度MFA的核算方法进行了改进,最终构建了EIPs-MFA模型及指标体系。以期为生态工业园区实践中的规划与管理提供方法指导。     

A General Nonlinear Least Squares Data Reconciliation and Estimation Method for Material Flow Analysis

The extraction, transformation, use, and disposal of materials can be represented by directed, weighted networks, known in the material flow analysis (MFA) community as Sankey or flow diagrams. However, the construction of such networks is dependent on data that are often scarce, conflicting, or do not directly map onto a Sankey diagram. By formalizing the forms of data entry, a nonlinear constrained optimization program for data estimation and reconciliation can be formulated for reconciling data sets for MFA problems where data are scarce, in conflict, do not directly map onto a Sankey diagram, and are of variable quality. This method is demonstrated by reanalyzing an existing MFA of global steel flows, and the resulting analytical solution measurably improves upon their manual solution.     

Society's Metabolism

"Societal metabolism" provides the appropriate conceptual basis for the rapidly growing development and analylical and policy interest in materials flow analysis (MFA). Following the review of the earlier intellectual background of societal metabolism in the first installment of this two-part article, this paper focuses on the current state of the art by examining more recent research referring t o societal metabolism in terms of material and substance flows. An operational classification of the literature according to frame of reference (socioeconomic system, ecosystem), system level (global, national, regional, functional, temporal), and types of flows under consideration (materials, energy, substances) highlights some of its characteristic features. There follows an integrated discussion of some of the major conceptual and methodological properties of MFA, with a particular focus on the field of bulk materials flows on a national level, comparing the major empirical results. Finally, the theoretical stringency research productivity, and political relevance of the MFA-related studies are assessed.     

Quantitative Evaluation of Data Quality in Regional Material Flow Analysis

A method for quantitative evaluation of data quality in regional material flow analysis (MFA) is presented. The principal idea is that data quality is a multidimensional problem that cannot be judged by individual characteristics such as the data source, given that data from official statistics may not be per se of good quality and expert estimations may not be per se of bad quality, respectively. It appears that MFA data are never totally accurate and may have certain defects that impair the quality of the data in more than one dimension. The concept of MFA information defects is introduced, and these information defects are mathematically formalized as functions of data characteristics. They are quantified on a scale from 0 (no information defect) to 1 (maximum information defect). The proposed method is illustrated in a case study on palladium flows in Austria. A quantitative evaluation of data quality provides opportunities for understanding and assessing MFA results, their a priori information basis, their reliability in decision making, and data uncertainties. It is a formal step toward better reproducibility and more transparency in MFA.