Monetary Input Output Research Articles

A review of methods to trace material flows into final products in dynamic material flow analysis: Comparative application of six methods to the United States and EXIOBASE3 regions, Part 2

Modeling pathways toward sustainable production and consumption requires improved spatio-temporal and material coverage of end-use product stocks. Momentarily, studies on inflow-driven, dynamic material flow analysis (dMFA) extrapolate scarce information on material end-use shares (i.e., ratios that split economy-wide material consumption to different end-use products) for single countries and years across longer time periods and global regions. Therefore, in part 1 of this work, we reviewed five methods to derive material end-use shares which use industry shipment data in physical units and monetary input–output tables (MIOTs). Herein, we comparatively apply these methods to the United States, drawing on detailed national data, as well as the multi-regional input–output model EXIOBASE3. To better match MIOT and dMFA system definitions, we propose the end-use transfer method, which re-routes specific intermediate outputs to final demand in MIOTs. In closing, we conclude on 12 points for improved end-use shares. We find mixed results regarding the fit between end-use shares derived from industry shipments and MIOTs: for detailed national data, we find good fit for some materials (e.g., aluminum), while others deviate strongly (e.g., steel). In many cases, the temporal trend of MIOT-derived end-use shares roughly agrees with industry shipments. For EXIOBASE3, we find good fit for some countries and materials, but substantial mismatches for others. Despite mixed results, combining MIOT-based end-use shares with industry shipments and auxiliary country-level data could enable improved temporal, geographical, and end-use resolution. However, the scarcity, documentation, and quality of input data are key limitations for more accurate and detailed end-use shares. This article met the requirements for a gold-gold data openness badge described at http://jie.click/badges.

A review of methods to trace material flows into final products in dynamic material flow analysis: From industry shipments in physical units to monetary input–output tables, Part 1

AbstractDynamic material flow analysis (dMFA) is widely used to model stock‐flow dynamics. To appropriately represent material lifetimes, recycling potentials, and service provision, dMFA requires data about the allocation of economy‐wide material consumption to different end‐use products or sectors, that is, the different product stocks, in which material consumption accumulates. Previous estimates of this allocation only cover few years, countries, and product groups. Recently, several new methods for estimating end‐use product allocation in dMFA were proposed, which so far lack systematic comparison. We review and systematize five methods for tracing material consumption into end‐use products in inflow‐driven dMFA and discuss their strengths and limitations. Widely used data on industry shipments in physical units have low spatio‐temporal coverage, which limits their applicability across countries and years. Monetary input–output tables (MIOTs) are widely available and their economy‐wide coverage makes them a valuable source to approximate material end‐uses. We find four distinct MIOT‐based methods: consumption‐based, waste input–output MFA (WIO‐MFA), Ghosh absorbing Markov chain, and partial Ghosh. We show that when applied to a given MIOT, the methods’ underlying input–output models yield the same results, with the exception of the partial Ghosh method, which involves simplifications. For practical applications, the MIOT system boundary must be aligned to those of dMFA, which involves the removal of service flows, sector (dis)aggregation, and re‐defining specific intermediate outputs as final demand. Theoretically, WIO‐MFA, applied to a modified MIOT, produces the most accurate results as it excludes massless and waste transactions. In part 2 of this work, we compare methods empirically and suggest improvements for aligning MIOT‐dMFA system boundaries.

A Visualization Method of the Economic Input–Output Table: Mapping Monetary Flows in the Form of Sankey Diagrams

The input–output table and input–output method have been widely used to understand complex economic structures and are often used in cross-disciplinary research between economics and other disciplines, such as analysis of embodied energy, carbon footprints, the water–food nexus, etc. However, when researchers present these results to audiences, especially policymakers, they often lack an effective visualization tool to present (1) the full picture of the input–output table; (2) the complicated upstream–downstream nexus, and (3) the input–output relationships between the economic sectors. Therefore, a better visualization method is developed to solve this problem. We propose mapping an input–output table into a Sankey diagram, a so-called monetary allocation Sankey diagram. We first designed the mapping structure of a monetary allocation Sankey diagram according to the general structure of an economic monetary input–output table to establish the correspondence nexus between the table and diagram. We used China as a case study to demonstrate the usage of the monetary allocation Sankey diagram. The purpose of the monetary allocation Sankey diagram is to help people understand the input–output table in a short time and quickly grasp the big picture of the economic system. To verify whether this goal is achieved, we presented and applied these Sankey diagrams on different occasions and obtained evaluations from scholars from different academic backgrounds. The evaluation shows that the monetary allocation Sankey diagram is not only a visualization result of the input–output table but also a miniature model of the economic system, which allows people to “truly observe” the complex input–output relationship and upstream–downstream nexus in the economic system. Researchers can quickly grasp the main features of the economic system by observing the miniature model, or they can use this miniature model as an auxiliary tool to introduce the economic system and its inherent complex relationships to the audience.

Analysis of driving factors on China's industrial solid waste generation: Insights from critical supply chains

Industrial solid waste (ISW) poses a huge potential threat to human health and the environment. To prevent pollution at its source, it is necessary to analyze the socioeconomic drivers and identify the key supply chains that cause changes in ISW generation. In this study, based on monetary input–output tables (MIOTs) in China from 2011 to 2015, structural decomposition analysis (SDA) was used to study the influence of socioeconomic drivers on common industrial solid waste (CISW) and hazardous waste (HW) generation. Structural path decomposition (SPD) was used to further trace the effects of drivers at the supply chain level and obtain more meaningful results for policy formulation. Economic expansion was found to play the most crucial role in the increase in total ISW generation while the reduction of generation intensity effectively slowed the growth trend. From the final demand perspective, fixed capital formation contributed the most to ISW generation growth, accounting for 65.05% of the total final demand effect. Construction was the primary trigger. For CISW, the supply chain with the greatest overall influence was “metal ore mining industry → fixed capital formation” (including intermediate consumption of metal smelting, general and special machinery, and construction), reflecting how fixed capital formation indirectly affected the metal ore mining industry. The supply chain with the greatest influence on HW generation was “paper industry → exports.” Based on the findings, corresponding policy adjustments are proposed.

Structural analysis of material flows in China based on physical and monetary input-output models

The physical input-output (PIO) model has different product flow scopes from the monetary input-output (MIO) model. Using the PIO and MIO models to analyze the structure of material flows can identify new hotspots for policy decisions over each other. However, PIO models are not well-studied in existing studies on the structure of China's material flows. This study uses both the PIO and MIO models to analyze consumption-based material flows of Chinese sectors and critical supply chain paths leading to China's material flows. Results show that the PIO and MIO models validate each other by simultaneously identifying critical sectors and important final demand categories. However, product prices and the treatment of services lead to different findings based on the MIO and PIO models. Compared with the PIO model, the MIO model underestimates the contribution of the construction sector to China's material flows, but overestimates that of the equipment and machinery and other services sectors. The PIO model reveals the higher importance of rural household consumption, while the MIO model identifies more critical supply chain paths associated with services. The PIO and MIO models can complement each other in the implementation and assessment of environmental measures (e.g., production efficiency improvement).

Exergy Life Cycle Assessment of electricity production from Waste-to-Energy technology: A Hybrid Input-Output approach

Exergy Life Cycle Assessment (ELCA) is proposed by literature to account for the exergy embodied in products of energy systems. In order to make results of ELCA comparable, supply chains that support the life cycle of the system should be analyzed through a unified model: this is one of the main concerns related to Life Cycle Assessment and Industrial Ecology disciplines.In this paper, Hybrid Input-Output analysis is proposed as the computational structure of ELCA: according to this method, national supply chains are modeled through the Monetary Input Output Tables (MIOTs) of national economies, a constantly updated and freely available data source. Then, the adopted national MIOT is expanded to include the detailed model of the considered energy system, hence defining a Hybrid Input-Output model. The (non-renewable) exergy embodied in electricity production and the Exergy Return on Investment (ExROI) are defined as the appropriate performance indicators based on ELCA. The introduced model is here adopted for the analysis of a Waste-to-Energy (WtE) power plant currently operating in the Italian context.It is found that the primary non-renewable exergy embodied in electricity produced by the analyzed WtE is non-negligible for both the construction (127.1toe) and the operation phases (11.6toe/y). Nonetheless, the plant is able to produce a net amount of electricity that pays back such primary non-renewable resources requirements about a hundred times. Finally, the joint application of Exergy Analysis and ELCA lead to improve the overall thermodynamic performances of the WtE system, increasing its exergy efficiency by 1%, and reducing the non-renewable exergy embodied in electricity production by 7938toe.

Balance issues in input–output analysis: A comment on physical inhomogeneity, aggregation bias, and coproduction

Recently, Merciai and Heijungs (2014) demonstrated that monetary input–output (IO) analysis can lead to system descriptions that do not conserve mass when the assumption of homogeneous prices is violated. They warn that this violation of basic balance laws can lead to biased estimates of environmental impacts, and they therefore recommend performing IO analysis in a physically accounted framework.We take a broader scope on this issue and present price inhomogeneity as a special case of product mix inhomogeneity. We demonstrate that even a fully physically accounted IO analysis or lifecycle assessment will violate balance laws if it suffers from inhomogeneous aggregation. The core issue is not whether a system is described using monetary or physical units, but rather whether product groups are too aggregated to allow for the concurrent respect of energy, mass, financial and elemental balances.We further analyze the link between the violation of physical balances and the introduction of biases. We find that imbalances are neither a necessary nor a sufficient condition for the presence of systematic errors in environmental pressure estimates.We suggest two ways to leverage the additional explanatory power of multi-unit inventory tables to reduce instances of imbalances and aggregation biases.

Multi-regional input–output model and ecological network analysis for regional embodied energy accounting in China

Chinese regions frequently exchange materials, but regional differences in economic development create unbalanced flows of these resources. In this study, we examined energy by assessing embodied energy consumption to describe the energy-flow structure in China's seven regions. Based on multi-regional monetary input–output tables and energy statistical yearbooks for Chinese provinces in 2002 and 2007, we accounted for both direct and indirect energy consumption, respectively, and the integral input and output of the provinces. Most integral inputs of energy flowed from north to south or from east to west, whereas integral output flows were mainly from northeast to southwest. This differed from the direct flows, which were predominantly from north to south and west to east. This demonstrates the importance of calculating both direct and indirect energy flows. Analysis of the distance and direction traveled by the energy consumption centers of gravity showed that the centers for embodied energy consumption and inputs moved southeast because of the movements of the centers of the Eastern region. However, the center for outputs moved northeast because the movement of the Central region. These analyses provide a basis for identifying how regional economic development policies influence the embodied energy consumption and its flows among regions.

The physical structure of urban economies — Comparative assessment

Urban metabolism provides a characterization of anthropogenic material flows in urban systems and should contribute to identify the economic activities that were involved on their supply and transformation. Typically, its quantification requires data that is not easily available in different geographies. This paper makes use of a methodology based on monetary input–output tables and international trade statistics that might be easily replicable to many metropolitan areas in the world, and which is intended to provide a first rough estimation of urban material flows.The paper discusses the results obtained for four metropolitan areas (Lisbon, Paris, Seoul–Incheon and Shanghai), assessing the material requirements of these economies. The urban areas are compared in terms of the quantity and the type of material input, destination of materials within the economy and their distribution among economic activities. The results showed that while Lisbon is the most diverse urban area in terms of the consumption of material types, it is also the urban area with the least diversified manufacturing sector.The application of this methodology to several urban areas and across multiple years enables the assessment of the technological and economic evolution of those regions.

Analysis of the energy metabolism of urban socioeconomic sectors and the associated carbon footprints: Model development and a case study for Beijing

Cities consume 80% of the world׳s energy; therefore, analyzing urban energy metabolism and the resulting carbon footprint provides basic data for formulating target carbon emission reductions. While energy metabolism includes both direct and indirect consumptions among sectors, few researchers have studied indirect consumption due to a lack of data. In this study, we used input–output analysis to calculate the energy flows among directly linked sectors. Building on this, we used ecological network analysis to develop a model of urban energy flows and also account for energy consumption embodied by the flows among indirectly linked sectors (represented numerically as paths with a length of 2 or more). To illustrate the model, monetary input–output tables for Beijing from 2000 to 2010 were analyzed to determine the embodied energy consumption and associated carbon footprints of these sectors. This analysis reveals the environmental pressure based on the source (energy consumption) and sink (carbon footprint) values. Indirect consumption was Beijing׳s primary form, and the carbon footprint therefore resulted mainly from indirect consumption (both accounting for ca. 60% of the total, though with considerable variation among sectors). To reduce emissions, the utilization efficiency of indirect consumption must improve.

Balance issues in monetary input–output tables

Input–output tables (IOTs) are widely used in several types of analyses. Although born in an economic context, IOTs are increasingly used for the environmental impact assessment of product systems, e.g. in environmental policy analysis, and for several others such as the accounting of greenhouse gases.However, the use in these contexts does not ensure the validity of the IOT as a consistent and robust multidisciplinary modeling tool in itself. It is in respect to certain basic requirements that IOTs should find their legitimacy. In this paper, we study their validity with respect to a well-established scientific law: the mass balance. Compliance with this basic balance is an important check for data consistency.Following such a track, we focus specifically on monetary input–output tables and we reach the conclusion that IOTs can fail in respecting the basic balance laws whenever prices differ per purchaser. Therefore caution is needed because the estimations in terms of environmental pressures can be biased. The drawback lays in the use of homogeneous prices, which determines a discrepancy in physical units between what is used and what is asked for, within and between activities.

Ecological network analysis of an urban metabolic system based on input–output tables: Model development and case study for Beijing

If cities are considered as “superorganisms”, then disorders of their metabolic processes cause something analogous to an “urban disease”. It is therefore helpful to identify the causes of such disorders by analyzing the inner mechanisms that control urban metabolic processes. Combining input–output analysis with ecological network analysis lets researchers study the functional relationships and hierarchy of the urban metabolic processes, thereby providing direct support for the analysis of urban disease. In this paper, using Beijing as an example, we develop a model of an urban metabolic system that accounts for the intensity of the embodied ecological elements using monetary input–output tables from 1997, 2000, 2002, 2005, and 2007, and use this data to compile the corresponding physical input–output tables. This approach described the various flows of ecological elements through urban metabolic processes and let us build an ecological network model with 32 components. Then, using two methods from ecological network analysis (flow analysis and utility analysis), we quantitatively analyzed the physical input–output relationships among urban components, determined the ecological hierarchy of the components of the metabolic system, and determined the distribution of advantage-dominated and disadvantage-dominated relationships, thereby providing scientific support to guide restructuring of the urban metabolic system in an effort to prevent or cure urban “diseases”.

Economic and environmental gains of China's fossil energy subsidies reform: A rebound effect case study with EIMO model

Abstract Energy consumption and efficiency emerged as the hottest topic in the context of China's sustainable development. Energy subsidies and “rebound effect” were closely related to this topic while few combinative studies on them with a focus on China. This paper employed a co-thinking approach, focusing on how the energy subsidies reform could mitigate the rebound effect in China, and how to achieve an “economic and environmental gains” that reduced pecuniary spending, improved the distorted energy market and reduced energy consumption simultaneously. Firstly, with price-gap approach we calculated the total energy subsidies scale of China in 2007, which amounted to582.0 billion CNY; then we detected and identified rebound effect of China energy consumption with the features. Furthermore, based on China 2007 monetary input–output table and energy flow analysis, we compiled a hybrid physical energy input and monetary output model (EIMO) to simulate the mitigation effect of subsidies reform. Results showed that removing energy subsidies would decrease ultimate demand of different economy sectors and reduce the accumulatively physical consumption of coal, oil, natural gas and electricity by 17.74, 13.47, 3.64 and 15.82 million tce, respectively. Finally we discussed relevant policy issues on China's energy subsidies reform in depth.

Estimation of regional physical imports and exports of EW-MFA in China using monetary input-output tables

Given the statistical gaps in material flow among provinces in China, a method was introduced to estimate regional physical imports and exports (RPIE), which includes international and interregional imports/exports. This method uses provincial monetary inputoutput tables (MIOT) and international trade statistics. A coefficient matrix representing correlations between monetary value and physical mass for years 2000–2009 was obtained based on a detailed commodity classification and 22 material production sectors in MIOT. With the coefficient matrix as reference, RPIE was measured. Pilot calculation of both regional physical trade balance and domestic material consumption, as well as a brief analysis of these methods, were conducted using 2002 data.

Sustainable urban materials management for air pollutants mitigation based on urban physical input–output model

Sustainable urban materials management is significant for environmental sustainability. This study identifies key economic sectors for sustainable urban materials management using urban physical input–output (PIOT) table and hierarchical cluster analysis method to mitigate urban air pollutants (comprising CO2, SO2 and NOx) and examines uncertainties. Suzhou city in China is taken as an example. Key economic sectors in Suzhou considering direct amount are production and supply of electric and heat power, smelting and pressing of ferrous metals, services, other manufacturing, textile, non-metallic mineral products and chemistry, while key economic sectors considering accumulative amount are agriculture, construction, production and supply of electric and heat power, services and smelting and pressing of ferrous metals. Uncertainties for sustainable urban materials management are consistent with the development stage of the economy. Thus, when constructing urban PIOT for a particular city based on monetary input–output table (MIOT) of another city or province, the development stage of the city or province whose MIOT is used should be similar to that of the particular city. If not, lower and upper limits for the development stage should be set to investigate uncertainties.

Physical and monetary input–output analysis: What makes the difference?

A recent paper in which embodied land appropriation of exports was calculated using a physical input–output model (Ecological Economics 44 (2003) 137–151) initiated a discussion in this journal concerning the conceptual differences between input–output models using a coefficient matrix based on physical input–output tables (PIOTs) in a single unit of mass and input–output models using a coefficient matrix based on monetary input–output tables (MIOTs) extended by a coefficient vector of physical factor inputs per unit of output. In this contribution we argue that the conceptual core of the discrepancies found when comparing outcomes obtained using physical vs. monetary input–output models lies in the assumptions regarding unit prices and not in the treatment of waste as has been claimed (Ecological Economics 48 (2004) 9–17). We first show that a basic static input–output model with the coefficient matrix derived from a monetary input–output table is equivalent to one where the coefficient matrix is derived from an input–output table in physical units provided that the assumption of unique sectoral prices is satisfied. We then illustrate that the input–output tables that were used in the original publication do not satisfy the assumption of homogenous sectoral prices, even after the inconsistent treatment of waste in the PIOT is corrected. We show that substantially different results from the physical and the monetary models in fact remain. Finally, we identify and discuss possible reasons for the observed differences in sectoral prices faced by different purchasing sectors and draw conclusions for the future development of applied physical input–output analysis.

Waste treatment in physical input–output analysis

When compared to monetary input–output tables (MIOTs), a distinctive feature of physical input–output tables (PIOTs) is that they include the generation of waste as part of a consistent accounting framework. As a consequence, however, physical input–output analysis thus requires that the treatment of waste is explicitly taken into account, because otherwise the results will be grossly underestimated. The treatment of waste has recently led to an interesting methodological debate. This paper reviews the discussion and introduces a new alternative. This alternative reconciles the existing methods and enables us to obtain additional information that cannot be derived from the other methods.

04/01582 The ecological footprint: a non-monetary metric of human consumption applied to North America: Senbel, M. et al. Global Environmental Change, 2003, 13, (2), 83–100

In the last few years some studies have been presented, which link land use accounting and input–output analysis (based on monetary input–output tables (MIOTs)) for the calculation of direct and indirect land appropriation of production and consumption activities. The compilation of the first comprehensive physical input–output tables (PIOTs) for some western European countries in the 1990s opened new possibilities for linking physical accounting and input–output analysis. Using a physical multiplier for this kind of calculation is more appropriate, as the most land intensive sectors are also the sectors with the highest amounts of material flows. Physical input–output analysis illustrates land appropriation in relation to material flows of each of the sectors, which is more appropriate from the point of view of environmental pressures than land appropriation in relation to monetary flows of a MIOT. Physical input–output analysis has so far not been applied for any land-related studies. Based on a physical input–output model of the EU-15, physical input–output analysis is applied in this paper, in order to calculate direct and indirect land requirements for the production of exports from EU-15 to the rest of the world.

Alternative Approaches of Physical Input–Output Analysis to Estimate Primary Material Inputs of Production and Consumption Activities

In the last few years, a number of studies have been presented that link material flow accounting and input–output analysis (based on monetary input–output tables) for the calculation of direct and indirect resource inputs for production and consumption activities. The compilation of the first physical input–output tables for some European countries in the 1990s opened new possibilities for linking physical accounting and input–output analysis. Physical input–output analysis has so far only been applied for selected materials, but it has not been used for comprehensive assessments of material requirements of economic activities. In this paper, possibilities and limits of this new input–output approach are clarified. We present and discuss a procedure similar to monetary input–output analysis and develop an alternative approach to account for primary inputs and waste otherwise not included in the analysis. Based on aggregated input–output tables for Germany, we present numerical examples intended to compare the alternative approaches of physical input–output analysis.

Material Flow Accounting for Metals in Japan

Planning transition from conventional mass production, mass consumption, and mass disposal society to JUNKANGATA-SHAKAI (recycling-oriented society), requires detailed and accurate information concerning material flows, especially from the viewpoint of dematerialization. However, as is well known, it is nearly impossible to observe every material flow directly. Hence, the importance of Material Flow Accounting model has increased. In this study, a Material Flow Accounting model using input-output technique is developed for Japanese metal flows. Since the model uses the Input-Output framework, it can be easily integrated with the MIOT (Monetary Input-Output Table) for further simulation. However, the scope of this study is limited to static framework, because the primal goal is accuracy. The data for year 2000 is organized with the developed framework, and gives the following results. Firstly, scraps play significant roles already. Second, non-ferrous metals can be grouped into two types. The first group's destination is mainly construction and machinery and these non-ferrous metals show the similar pattern of destination as iron. This indicates that the flows can be roughly predicted from the iron flows. The other group shows no uniform trend so that the flows are more difficult to predict than the first group.