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.     

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.     

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.     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

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.     

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.     

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.     

Advancements in Input‐Output Models and Indicators for Consumption‐Based Accounting

The use of global, multiregional input‐output (MRIO) analysis for consumption‐based (footprint) accounting has expanded significantly over the last decade. Most of the global studies on environmental and social impacts associated with consumption or embodied in international trade would have been impossible without the rapid development of extended MRIO databases. We present an overview of the developments in the field of MRIO analysis, in particular as applied to consumption‐based environmental and social footprints. We first provide a discussion of research published on various global MRIO databases and the differences between them, before focusing on the virtual laboratory computing infrastructure for potentially making MRIO databases more accessible for collaborative research, and also for supporting greater sectoral and regional detail. We discuss work that includes a broader range of extensions, in particular the inclusion of social indicators in consumption‐based accounting. We conclude by discussing the need for the development of detailed nested MRIO tables for investigating linkages between regions of different countries, and the applications of the rapidly growing field of global MRIO analysis for assessing a country's performance toward the United Nations Sustainable Development Goals.     

Organization Environmental Footprint through Input‐Output Analysis: A Case Study in the Construction Sector

The implementation of global sustainability has gained worldwide attention in recent years. The Organization Environmental Footprint, which encompasses 14 impact categories, is a multicriteria measure of the environmental performance of goods and services provided by an organization from a life cycle perspective. In this article, the focus is on quantifying the Organization Environmental Footprint of a construction company in Spain. By applying an environmentally extended input‐output approach, its total footprint and impacts along the supply chain from two consecutive years were calculated. The results show that the environmental impacts from the second year of implementation were significantly higher than those from the first year. The impact category climate change was found to have experienced the greatest increase from one year to the other, with a 31% increase. This work provides an overview of 14 environmental impact categories of the company assessed, as well as recommendations for the implementation of this indicator in companies and public procurement. This approach could pave the way to shape organizations’ action plans and meet the European environmental challenges.     

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.     

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.     

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.     

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.     

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.     

Assessing the Greenhouse Gas Savings Potential of Extended Producer Responsibility for Mattresses and Boxsprings in the United States

Extended producer responsibility (EPR) legislation in the United States, which currently only exists on the state level, now includes three mattress EPR acts, which intend to shift the financial and operational burden of mattress end‐of‐life (EOL) management away from local and state government. It is important to keep in mind, however, that the original objective behind EPR is to reduce the environmental life cycle impacts of products. This article therefore quantifies the greenhouse gas (GHG) savings potential of mattress and boxspring recycling and reuse in the United States and also discusses labor implications and mattress design issues. We find that all three acts are unlikely to generate redesign incentives, but are expected to dramatically increase mattress collection and recycling. The collection and recycling of all 35 million EOL mattress and boxspring units estimated to reach the end of their lives in the United States every year would generate in the order of 10,000 jobs and GHG savings between 1 and 1.5 million metric tonnes.     

Towards a Circular Economy in Australian Agri‐food Industry: An Application of Input‐Output Oriented Approaches for Analyzing Resource Efficiency and Competitiveness Potential

The food industry in Australia (agriculture and manufacturing) plays a fundamental role in contributing to socioeconomic sectors nationally. However, alongside the benefits, the industry also produces environmental burdens associated with the production of food. Sectorally, agriculture is the largest consumer of water. Additionally, land degradation, greenhouse gas emissions, energy consumption, and waste generation are considered the main environmental impacts caused by the industry. The research project aims to evaluate the eco‐efficiency performance of various subsectors in the Australian agri‐food systems through the use of input‐output–oriented approaches of data envelopment analysis and material flow analysis. This helps in establishing environmental and economic indicators for the industry. The results have shown inefficiencies during the life cycle of food production in Australia. Following the principles of industrial ecology, the study recommends the implementation of sustainable processes to increase efficiency, diminish undesirable outputs, and decrease the use of nonrenewable inputs within the production cycle. Broadly, the research outcomes are useful to inform decision makers about the advantages of moving from a traditional linear system to a circular production system, where a sustainable and efficient circular economy could be created in the Australian food industry.     

Comparison of Tools for Quantifying the Environmental Performance of an Urban Territory

To support effective urban policies aimed at decreasing the environmental impacts of cities, it is important to develop robust tools for accounting those impacts. Environmentally extended input‐output analysis (EEIOA) is among the most used tools for this purpose, allowing the quantification of both direct and indirect impacts. Life cycle assessment (LCA) is also a holistic and comprehensive tool that accounts for direct and indirect impacts—but its application to cities is still very recent. This study aims at applying EEIOA and LCA to the municipality of Aveiro (Portugal) in order to compare the outcomes of the two tools in terms of total impacts (climate change and fossil fuel depletion) and hotspots (sectors/products contributing most to the impacts), to identify limitations and advantages of the tools when applied to Aveiro, and to illustrate how LCA can be applied to cities. The total impacts estimated with LCA and EEIOA were similar and the hotspots were also the same: transports, food, construction, and electricity. However, the relative contribution of some sectors was very different in the two tools due to methodological differences mainly in system boundaries, type of activities or products considered in each sector, and geographical coverage of impact data. This study concludes that the analyzed tools can provide complementary results to support decision making concerning urban planning and management.     

Identifying Lowest‐Emission Choices and Environmental Pareto Frontiers for Wastewater Treatment Wastewater Treatment Input‐Output Model based Linear Programming

This article proposes a linear programming model that is based on the wastewater treatment input‐output model (W²IO) to identify the lowest‐emission choice among alternative feasible options for wastewater treatment; this model can be considered as an application of the waste input‐output linear programming model (WIO‐LP) to wastewater issues. Using the data of the Tokyo metropolitan W²IO table, I apply this model to obtain the optimal wastewater treatment options under alternative scenarios. The Pareto frontiers of environmental loads are derived to show the trade‐off relationships among various types of environmental load and the effect of the introduction of high‐temperature incineration of dewatered sludge on the generation of environmental loads. The main conclusion of the study is that when all three types of environmental load (landfill level, global warming potential, and chemical oxygen demand) are considered, the introduction of high‐temperature incineration causes the widening of the Pareto frontier of environmental loads and also causes it to move closer to the origin.     

The Waste Footprint of French Households in 2020: A Comparison of Scenarios of Consumption Growth Using Input‐Output Analysis

This study aims at quantifying and analyzing the waste footprint of French household consumption in 2020 with respect to different scenarios of economic growth. Three models are jointly used: (1) a multiregional unilateral input‐output model extended to waste, to quantify waste generation from economic activities induced by household consumption; (2) a coefficient‐based model dedicated to quantifying postconsumer waste as a function of household consumption; and (3) the New Econometric Model of Evaluation by Sectorial Interdependency and Supply (NEMESIS), a macroeconometric model used to elaborate different scenarios of growth in household consumption in the period 2008–2020. Three scenarios consider changes primarily in terms of household consumption volume, while one scenario additionally considers changes in the composition of consumption according to the past‐30‐year trend. First, this study suggests that if the trend in changes of composition is maintained, it will lead, by 2020, to a “relative” decoupling between French household consumption and waste footprint with respect to dry recyclables, mixed wastes, and organic wastes and to an “absolute” decoupling with respect to mineral wastes. Second, this study provides a mapping of the changes in French household waste footprints from 2008 to 2020 as a function of scenarios, with indications of where these changes would actually occur in the economy (waste from economic activities or postconsumer waste) and geographically (in France or abroad). In particular, for most of the scenarios considered, changes in French household consumption from 2008 to 2020 primarily induce changes in organic and mineral waste generation abroad rather than in France.