A Supply‐Use Approach to Waste Input‐Output Analysis

In this article, we extend Namakura and Kondo's waste input‐output (WIO) framework by incorporating a supply‐use formalism, resulting in waste supply‐use tables (WSUTs). We present the theoretical underpinnings of the WSUT and, in particular, the transition from Nakamura and Kondo's WIO form to the new WSUT form. Further, we offer a mathematical proof of the equivalence of WIO and WSUT multipliers. We illustrate the workings of the WSUT calculus using economic and waste data for the Australian economy in 2008–2009.     

Disaggregating the Power Generation Sector for Input‐Output Life Cycle Assessment

The electric power industry plays a critical role in the economy and the environment, and it is important to examine the economic, environmental, and policy implications of current and future power generation scenarios. However, the tools that exist to perform the life cycle assessments are either too complex or too aggregated to be useful for these types of activities. In this work, we build upon the framework of existing input‐output (I‐O) models by adding data about the electric power industry and disaggregating this single sector into additional sectors, each representing a specific portion of electric power industry operations. For each of these disaggregated sectors, we create a process‐specific supply chain and a set of emission factors that allow calculation of the environmental effects of that sector's output. This new model allows a much better fit for scenarios requiring more specificity than is possible with the current I‐O model.     

A Hybrid‐Unit Energy Input‐Output Model to Evaluate Embodied Energy and Life Cycle Emissions for China's Economy

We develop a hybrid‐unit energy input‐output (I/O) model with a disaggregated electricity sector for China. The model replaces primary energy rows in monetary value, namely, coal, gas, crude oil, and renewable energy, with physical flow units in order to overcome errors associated with the proportionality assumption in environmental I/O analysis models. Model development and data use are explained and compared with other approaches in the field of environmental life cycle assessment. The model is applied to evaluate the primary energy embodied in economic output to meet Chinese final consumption for the year 2007. Direct and indirect carbon dioxide emissions intensities are determined. We find that different final demand categories pose distinctive requirements on the primary energy mix. Also, a considerable amount of energy is embodied in the supply chain of secondary industries. Embodied energy and emissions are crucial to consider for policy development in China based on consumption, rather than production. Consumption‐based policies will likely play a more important role in China when per capita income levels have reached those of western countries.     

Considering Variations in Waste Composition during Waste Input‐Output Modeling

Concentrations of pollutants vary in wastes from different sources. However, existing waste input‐output (WIO) models do not take these differing concentrations into account. This article proposes a new category of model, which we are calling a waste input‐output model at the substance level (WIOS model). The WIOS model considers variations in waste composition. These variations potentially affect the life cycle inventory of the waste treatment stage. The proposed model is expected to produce more accurate results than existing WIO models that do not consider variations in the composition of wastes. In addition, the proposed model provides a method to trace substances undergoing waste treatment. In this article, use of the WIOS model is illustrated by simulating the overall environmental loads of total organic carbon from wastewater treatment at a facility in Germany. The results show that variations in the composition of wastes entering treatment significantly affect the modeled estimates of total environmental loads caused by wastewater treatment. In addition, the results of the proposed model are different from results given by existing hybrid input‐output WIO models that do not consider variations in the composition of wastewater as it undergoes treatment.     

Input‐Output‐based Life Cycle Inventory

An input‐output‐based life cycle inventory (IO‐based LCI) is grounded on economic environmental input‐output analysis (IO analysis). It is a fast and low‐budget method for generating LCI data sets, and is used to close data gaps in life cycle assessment (LCA). Due to the fact that its methodological basis differs from that of process‐based inventory, its application in LCA is a matter of controversy. We developed a German IO‐based approach to derive IO‐based LCI data sets that is based on the German IO accounts and on the German environmental accounts, which provide data for the sector‐specific direct emissions of seven airborne compounds. The method to calculate German IO‐based LCI data sets for building products is explained in detail. The appropriateness of employing IO‐based LCI for German buildings is analyzed by using process‐based LCI data from the Swiss Ecoinvent database to validate the calculated IO‐based LCI data. The extent of the deviations between process‐based LCI and IO‐based LCI varies considerably for the airborne emissions we investigated. We carried out a systematic evaluation of the possible reasons for this deviation. This analysis shows that the sector‐specific effects (aggregation of sectors) and the quality of primary data for emissions from national inventory reporting (NIR) are the main reasons for the deviations. As a rule, IO‐based LCI data sets seem to underestimate specific emissions while overestimating sector‐specific aspects.     

Accounting for Emissions and Sinks from the Biogeochemical Cycle of Carbon in the U.S. Economic Input‐Output Model

Biogeochemical cycles are essential ecosystem services that continue to degrade as a result of human activities, but are not fully considered in efforts toward sustainable engineering. This article develops a model that integrates the carbon cycle with economic activities in the 2002 U.S. economy. Data about the carbon cycle, including emissions and sequestration flows, is obtained from the greenhouse gas inventory of the U.S. Environmental Protection Agency. Economic activities are captured by the economic input‐output model available from the Bureau of Economic Analysis. The resulting model is more comprehensive in its accounting for the carbon cycle than existing methods for carbon footprint (CF) calculations. Examples of unique flows in this model include the effect of land‐use and land‐cover change on carbon dioxide flow within the U.S. national boundary, carbon sequestration in urban trees, and emissions resulting from liming. This model is used to gain unique insight into the carbon profile of U.S. economic sectors by providing the life cycle emissions and sequestration in each sector. Such insight may be used to support policies, manage supply chains, and be used for more comprehensive CF calculations.     

Truncation Error Estimates in Process Life Cycle Assessment Using Input‐Output Analysis

Process life cycle assessment (PLCA) is widely used to quantify environmental flows associated with the manufacturing of products and other processes. As PLCA always depends on defining a system boundary, its application involves truncation errors. Different methods of estimating truncation errors are proposed in the literature; most of these are based on artificially constructed system complete counterfactuals. In this article, we review the literature on truncation errors and their estimates and systematically explore factors that influence truncation error estimates. We classify estimation approaches, together with underlying factors influencing estimation results according to where in the estimation procedure they occur. By contrasting different PLCA truncation/error modeling frameworks using the same underlying input‐output (I‐O) data set and varying cut‐off criteria, we show that modeling choices can significantly influence estimates for PLCA truncation errors. In addition, we find that differences in I‐O and process inventory databases, such as missing service sector activities, can significantly affect estimates of PLCA truncation errors. Our results expose the challenges related to explicit statements on the magnitude of PLCA truncation errors. They also indicate that increasing the strictness of cut‐off criteria in PLCA has only limited influence on the resulting truncation errors. We conclude that applying an additional I‐O life cycle assessment or a path exchange hybrid life cycle assessment to identify where significant contributions are located in upstream layers could significantly reduce PLCA truncation errors.     

Developing the Chinese Environmentally Extended Input‐Output (CEEIO) Database

Environmentally extended input‐output (EEIO) databases are increasingly used to examine environmental footprints of economic activities. Studies focusing on China have independently, repeatedly developed EEIO databases for China. These databases are usually not publicly available, leading to repeated efforts, inconsistent with one another using different approaches, of limited environmental accounts, and lacking transparency, preventing continuous updating. We developed a transparent, comprehensive, and consistent Chinese EEIO database covering a wide period of time (currently 1992, 1997, 2002, and 2007 for which benchmark input‐output tables [IOTs] are available), sector classifications (original sector classifications in benchmark IOTs, a 45‐sector classification commonly used in China's environmental and energy statistics, and a 91‐sector classification with maximized sector resolution ensuring temporal consistence), and environmental satellite accounts for 256 types of resources and 30 types of pollutants in this study. Moreover, the environmental satellite accounts cover households in addition to sectors, allowing developing closed models. We make this database publicly available with open access for broader dissemination ( www.ceeio.com ). We demonstrate the database by evaluating environmental pressures of Chinese products in 2007. Comparisons of our database with previous studies validate its rationality and reliability.     

A Carbon Footprint of High‐Speed Railways in China: A Case Study of the Beijing‐Shanghai Line

A carbon footprint (CF) assessment of Chinese high‐speed railways (HSRs) can help guide further development of the world's longest HSR network. In this research, a hybrid economic input‐output and life cycle assessment (EIO‐LCA) method was applied to estimate the CF of the Beijing‐Shanghai HSR line. Specific CFs were analyzed of different subsystems of the line, different stages of production, and three calculation scopes. Results showed that the annual CF of the Beijing‐Shanghai HSR is increasing, whereas the per‐passenger CF constantly declined between 2011 and 2014. Scope 1 emissions account for an average of 4% of the total annual CF, Scope 2 contribute 71%, and Scope 3 comprise 25%. Among the different stages, operation contributes the largest (71%), followed by construction (20%) and maintenance (9%). In the construction stage, the bridges have the largest CF, followed by trains, and then rails. A trade‐off exists between the increase in carbon emissions due to construction of bridges and the reduction in operation emissions affected by leveling changes in terrain. The Beijing‐Shanghai HSR line has a relatively higher per‐passenger CF than eight other HSR lines, which is largely due to China's coal‐based carbon‐intensive energy mix of electricity generation, high proportion of bridges, higher operating speed, and heavier train body. In the future, cleaner electricity supply options, more efficient raw material production, and improvement of trains are keys to reducing the CF of Chinese HSRs.     

Hybrid Input‐Output Life Cycle Assessment of First‐ and Second‐Generation Ethanol Production Technologies in Brazil

A hybrid approach combining life cycle assessment and input‐output analysis was used to demonstrate the economic and environmental benefits of current and future improvements in agricultural and industrial technologies for ethanol production in Brazilian biorefineries. In this article, three main scenarios were evaluated: first‐generation ethanol production with the average current technology; the improved current technology; and the integration of improved first‐ and second‐generation ethanol production. For the improved first‐generation scenario, a US$1 million increase in ethanol demand can give rise to US$2.5 million of total economic activity in the Brazilian economy when direct and indirect purchases of inputs are considered. This value is slightly higher than the economic activity (US$1.8 million) for an energy equivalent amount of gasoline. The integration of first‐ and second‐generation technologies significantly reduces the total greenhouse gas emissions of ethanol production: 14.6 versus 86.4 grams of carbon dioxide equivalent per megajoule (g CO₂‐eq/MJ) for gasoline. Moreover, emissions of ethanol can be negative (–10.5 g CO₂‐eq/MJ) when the system boundary is expanded to account for surplus bioelectricity by displacement of natural gas thermal electricity generation considering electricity produced in first‐generation optimized biorefineries.     

A Hybrid Approach for Assessing the Multi‐Scale Impacts of Urban Resource Use: Transportation in Phoenix,Arizona

Life cycle assessment (LCA) and urban metabolism (UM) are popular approaches for urban system environmental assessment. However, both approaches have challenges when used across spatial scales. LCA tends to decompose systemic information into micro‐level functional units that mask complexity and purpose, whereas UM typically equates aggregated material and energy flows with impacts and is not ideal for revealing the mechanisms or alternatives available to reduce systemic environmental risks. This study explores the value of integrating UM with LCA, using vehicle transportation in the Phoenix metropolitan area as an illustrative case study. Where other studies have focused on the use of LCA providing upstream supply‐chain impacts for UM, we assert that the broader value of the integrated approach is in (1) the ability to cross scales (from micro to macro) in environmental assessment and (2) establishing an analysis that captures function and complexity in urban systems. The results for Phoenix show the complexity in resource supply chains and critical infrastructure services, how impacts accrue well beyond geopolitical boundaries where activities occur, and potential system vulnerabilities.     

An Input‐Output Model of Extended Producer Responsibility

Under an extended producer responsibility (EPR) system, when a producer delivers a product to the market it must also pay a takeback fee, which is used to cover the costs of end‐of‐life disposal. EPR systems are currently used in Europe and beyond to manage a variety of products, including packaging and used tires. In this article we develop an input‐output (IO) model that is able to assess the impacts of an EPR system, and is based on the waste IO (WIO) model. The WIO model is itself a hybrid‐unit model extension of the Leontief model that is able to capture the substitution effect between recycled/recovered material/energy from waste treatment and their non‐waste cognates. The resulting EPRIO model, besides the conventional direct and indirect effects of the Leontief model and the substitution effects of the WIO model, is able to capture the opportunity costs of financing the EPR system, and additionally requires the specification of an alternative waste management policy, with its own opportunity costs. The impact of an EPR policy is thus the difference between the impacts of the reference EPR and the alternative waste treament policies. The resulting model is illustrated with a simple example of a used tire management EPR system.     

Insights on the Use of Hybrid Life Cycle Assessment for Environmental Footprinting

Establishing a comprehensive environmental footprint that indicates resource use and environmental release hotspots in both direct and indirect operations can help companies formulate impact reduction strategies as part of overall sustainability efforts. Life cycle assessment (LCA) is a useful approach for achieving these objectives. For most companies, financial data are more readily available than material and energy quantities, which suggests a hybrid LCA approach that emphasizes use of economic input‐output (EIO) LCA and process‐based energy and material flow models to frame and develop life cycle emission inventories resulting from company activities. We apply a hybrid LCA framework to an inland marine transportation company that transports bulk commodities within the United States. The analysis focuses on global warming potential, acidification, particulate matter emissions, eutrophication, ozone depletion, and water use. The results show that emissions of greenhouse gases, sulfur, and particulate matter are mainly from direct activities but that supply chain impacts are also significant, particularly in terms of water use. Hotspots were identified in the production, distribution, and use of fuel; the manufacturing, maintenance, and repair of boats and barges; food production; personnel air transport; and solid waste disposal. Results from the case study demonstrate that the aforementioned footprinting framework can provide a sufficiently reliable and comprehensive baseline for a company to formulate, measure, and monitor its efforts to reduce environmental impacts from internal and supply chain operations.     

Data Acquisition for Applying Physical Input‐Output Tables in Chinese Cities

The physical input‐output table (PIOT) is a useful tool for analyzing the environmental sustainability of cities. Taking Chinese statistical sources as an example in this study, we discuss data acquisition methods for applying the PIOT to cities. We propose several methods and present a case study of Suzhou City to illustrate the proposed methods. These methods can provide foundations for constructing the PIOT of cities in other countries.     

Method for endogenizing capital in the United States Environmentally‐Extended Input‐Output model

Each year businesses, governments, and homeowners in the United States invest around one fifth of gross domestic product into the creation of capital assets such as buildings, machinery, and software to enable production and consumption. Use of capital is typically included to some extent in environmental life cycle assessments of goods and services but is not incorporated into most environmentally extended input‐output (EEIO) models, including the US Environmental Protection Agency's USEEIO. Capital assets are typically created in years prior to their use, so a challenge lies in distributing the impacts of their creation over time. In this work, a highly detailed capital flow matrix approach is followed to distribute the use of fixed capital assets to consuming industries. Data from the US Bureau of Economic Analysis's Fixed Asset Accounts is merged with its Industry Accounts data by the creation of concordance tables. Public highways and streets are partially reallocated to industries operating vehicles. The resulting capital use matrix is later combined into a modified USEEIO. “Housing” is found to be the largest consumer of fixed assets, followed by general government, fossil fuel extraction, and financial industries involved in leasing. Construction, vehicles, and machinery are mostly used by industries in the form of fixed assets. The types of fixed assets used by industries are consistent with expectations: housing is dominated by structures, transport by equipment, and information industries by intellectual property products.     

Consequences of Future Data Center Deployment in Canada on Electricity Generation and Environmental Impacts: A 2015–2030 Prospective Study

The environmental impacts of data centers that provide information and communication technologies (ICTs) services are strongly related to electricity generation. With the increasing use of ICT, many data centers are expected to be built, causing more absolute impacts on the environment. Given that electricity distribution networks are very complex and dynamic systems, an environmental evaluation of future data centers is uncertain. This study proposes a new approach to investigate the consequences of future data center deployment in Canada and optimize this deployment based on the Energy 2020 technoeconomic model in combination with life cycle assessment methodology. The method determines specific electricity sources that will power the future Canadian data centers and computes related environmental impacts based on several indicators. In case‐study scenarios, the largest deployment of data centers leads to the smallest impact per megawatt of data centers for all of the environmental indicators. It is found that an increase in power demand by data centers would lead to a reduction in electricity exports to the United States, driving the United States to generate more electricity to meet its energy demand. Given that electricity generation in the United States is more polluting than in Canada, the deployment of data centers in Canada is indirectly linked to an increase in overall environmental impacts. However, though an optimal solution should be found to mitigate global greenhouse gas emissions, it is not clear whether the environmental burden related to U.S. electricity generation should be attributed to the Canadian data centers.     

Corporate and Product Carbon Footprint under Compound Hybrid Analysis: Application to a Spanish Timber Company

The European Union (EU) is advancing steadily toward the stabilization of atmospheric greenhouse gas concentrations. Various sectors are now obliged to make reductions, and new policies based on the carbon footprint are being encouraged. However, voluntary reporting of so‐called scope 3 emissions is hindering successful implementation of these policies. In this study, we present a tiered hybrid analysis to report emissions according to the ISO/TR 14069 standards and to obtain complete measures of scope 3 emissions. A process analysis for scope 1 and scope 2 emissions is complemented with a multiregional input‐output analysis for upstream scope 3 emissions. This novel approach is applied to the case study of a Spanish timber company. Its total carbon footprint in 2011 was 783,660 kilograms of carbon‐dioxide equivalent, of which 88% correspond to scope 3 emissions. These emissions are globally distributed; 71% are from European countries, followed by 8% from emerging economies (Brazil, Russia, India, Indonesia, Australia, and Turkey), 5% from China, and, finally, 16% from the rest of the world. We identify and discuss the advantages and disadvantages of this novel approach, the European implementation of which could be highly effective in reducing global carbon emissions.     

Coupling Input‐Output Tables with Macro‐Life Cycle Assessment to Assess Worldwide Impacts of Biofuels Transport Policies

Many countries see biofuels as a replacement to fossil fuels to mitigate climate change. Nevertheless, some concerns remain about the overall benefits of biofuels policies. More comprehensive tools seem required to evaluate indirect effects of biofuel policies. This article proposes a method to evaluate large‐scale biofuel policies that is based on life cycle assessment (LCA), environmental extensions of input‐output (I‐O) tables, and a general equilibrium model. The method enables the assessment of indirect environmental effects of biofuels policies, including land‐use changes (LUCs), in the context of economic and demographic growth. The method is illustrated with a case study involving two scenarios. The first one describes the evolution of the world economy from 2006 to 2020 under business as usual (BAU) conditions (including demographic and dietary preferences changes), and the second integrates biofuel policies in the United States and the European Union (EU). Results show that the biofuel scenario, originally designed to mitigate climate change, results in more greenhouse gas emissions when compared to the BAU scenario. This is mainly due to emissions associated with global LUCs. The case study shows that the method enables a broader consideration for environmental effects of biofuel policies than usual LCA: Global economic variations calculated by a general equilibrium economic model and LUC emissions can be evaluated. More work is needed, however, to include new biofuel production technologies and reduce the uncertainty of the method.     

Investigating Reasons for Differences in the Results of Environmental,Physical, and Hybrid Input‐Output Models

It is vital to find reasons for differences in the results of environmental input‐output (EIO), physical input‐output (PIO), and hybrid input‐output (HIO) models for industrial and environmental policy analysis. Using EIO, PIO, and HIO models, China's industrial metabolism is calculated. Four reasons were found to account for differences in the results of analysis using EIO, PIO, and HIO models: the manner in which they deal with residential consumption, service sectors, and waste recycling, and the assumption of unique sector prices. The HIO model, which treats residential consumption as sectors of the intermediate delivery matrix, is preferred to the EIO and PIO models for analyzing industrial and environmental policies. Moreover, waste recycling in five sectors—agriculture; the manufacture of paper, printing, and articles for culture, education, and sports activities; the manufacture of nonmetallic mineral products; smelting and pressing of metals; and construction—should be comprehensively considered when using the HIO model to study problems related to these five sectors. Improvements in the EIO, PIO, and HIO models and future work are also discussed.     

Combining Multiregional Input‐Output Analysis with a World Trade Model for Evaluating Scenarios for Sustainable Use of Global Resources,Part I: Conceptual Framework

Consumption in a particular country often entails resource extraction, production, and environmental degradation in remote locations. This fact has stimulated a growing body of empirical analysis using input‐output (I‐O) databases and techniques to reveal and quantify the underlying linkages. Two lines of research rooted in I‐O economics, multiregional input‐output (MRIO) analysis and I‐O modeling of the world economy, describe and analyze these relationships, the first for the past, increasingly in the form of footprints and the underlying pathways, and the latter under alternative scenarios about possible courses of action in the future. The article shows how organizing such scenario outcomes into an MRIO database can extend the reach of MRIO analysis to the future while simultaneously supplementing the capabilities of the world trade modeling framework. We describe the compilation of an MRIO database from the results of scenario analysis using the world trade model (WTM) in a companion article (Part II, Implementation); the subsequent application of MRIO techniques to this database permits the evaluation of prospects for the future. We also address several overlooked challenges, namely, the need to include factor endowments and distances between potential trade partners in an MRIO database, the representation of sectors providing transport of internationally traded goods, and the manipulation of mixed physical and money units when both quantities and prices are endogenous.