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.     

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.     

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.     

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.     

Environmental Impacts of Products:Policy Relevant Information and Data Challenges

The research and analysis presented in this special issue shows that the same limited number of consumption categories are consistently revealed to be responsible for the largest share of environmental impact: mobility (automobile and air transport), food (meat, poultry, fish, and dairy followed by plant‐based food), and residential energy use in the house (heating, cooling, electrical appliances, and lighting). It appears that differences in impact per euro between the product groupings are relatively limited, so it is essential to reduce the life‐cycle impacts of products as such, rather than to shift expenditures to less impact‐intensive product groupings. Furthermore, the effectiveness of expenditure on material products to improve quality of life leaves much room for improvement. Environmentally extended input‐output (EEIO) tables probably form, in this field, the most appropriate information support tool for priority setting, prospective assessment of options, scenario analysis, and monitoring. A clear benefit would result from integrating the input–output (IO) tables in the report to Eurostat of the 25 individual countries that make up the European Union (EU), with other officially available information on emissions and resources use, into a 60‐sector EEIO table for the EU. This, obviously, would be the first step toward more detailed tables. Three strategies are suggested to realize the additional, desirable detail of 150 sectors or more, each achievable at an increasing time horizon and with increasing effort: (1) developing further the current CEDA EU25 table; (2) building a truly European detailed input–output table accepting the restrictions of existing data gathering procedures; and (3) as (2), but developing new, dedicated data gathering and classification procedures. In all cases, a key issue is harmonizing classification systems for industry sectors, consumer expenditure categories, and product classifications (as in import/export statistics) in such a way that data sets may adequately be linked to input–output tables.     

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.     

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.     

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.     

Structural Decomposition Analysis of Raw Material Consumption

The aim of this article is to quantify the drivers for the changes in raw material consumption (domestic material consumption expressed in the form of all materials extracted and used in the production phase) in terms of technology, which refers to the concept of sustainable production; the product structure of final demand, which refers to the concept of sustainable consumption; and the volume of final demand, which is related to economic growth. We also aim to determine to what extent the technological development and a shift in product structure of the final demand compensate for the growth in final consumption volume. Therefore, we apply structural decomposition analysis (SDA) to the change in raw material consumption (RMC) of the Czech Republic between 2000 and 2007. To present the study in a broader context, we also show other material flow indicators for the Czech Republic for 2000 and 2007. Our findings of SDA show that final demand structure has a very limited effect on the change in material flows. The rapid change in final demand volume was not compensated for crude oil, metal ores, construction materials, food crops, and timber. For the material category of non‐iron metal ores, even the change in technology contributes to an increase in material flows. The largest relative increases are reported for non‐iron metal ores (38%) and construction materials (30%). The main changes in material flows related to the Czech Republic are driven by exports and enabled by imports, the main source of these increased material flows. This emphasizes the increasing role of international trade.     

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.     

Lifting the veil on the correction of double counting incidents in hybrid life cycle assessment

Life cycle assessment (LCA) and environmentally extended input–output analyses (EEIOA) are two techniques commonly used to assess environmental impacts of an activity/product. Their strengths and weaknesses are complementary, and they are thus regularly combined to obtain hybrid LCAs. A number of approaches in hybrid LCA exist, which leads to different results. One of the differences is the method used to ensure that mixed LCA and EEIOA data do not overlap, which is referred to as correction for double counting. This aspect of hybrid LCA is often ignored in reports of hybrid assessments and no comprehensive study has been carried out on it. This article strives to list, compare, and analyze the different existing methods for the correction of double counting. We first harmonize the definitions of the existing correction methods and express them in a common notation, before introducing a streamlined variant. We then compare their respective assumptions and limitations. We discuss the loss of specific information regarding the studied activity/product and the loss of coherent financial representation caused by some of the correction methods. This analysis clarifies which techniques are most applicable to different tasks, from hybridizing individual LCA processes to integrating complete databases. We finally conclude by giving recommendations for future hybrid analyses.     

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.     

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.     

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.     

Use of Physical Supply and Use Tables for Calculation of Economy‐Wide Material Flow Indicators

The study described in this article presents the first‐ever physical supply and use tables (PSUTs) based on the recently published methodological standard for the System of Environmental‐Economic Accounting (SEEA). The tables were compiled for the Czech Republic for 2014. The compilation procedure followed was described in detail so that it can serve as a source of inspiration and a benchmark for other researchers and/or statisticians. The major shortcoming of the PSUTs is that not all needed data were readily available in physical units and required estimations based on proxies. Some parts of the tables are therefore burdened with a degree of uncertainty. In order to address the price inhomogeneity of sectoral prices for commodity outputs, imports, and exports, which tends to be typical for monetary supply and use tables (MSUTs), the PSUTs and MSUTs were further used for the calculation of raw material equivalents of import, exports, and raw material input (RMI) and raw material consumption (RMC) indicators. A comparison of results showed that the total indicators do not differ that much: the largest difference of 5% was recorded for raw material equivalents of exports, while RMC, for instance, remained nearly the same. However, we still argue for the use of PSUTs for the calculation of raw material equivalents, as changes in total volume of the indicators were accompanied with changes in their material structure. This can have significant consequences for the assessment of environmental impacts related to material consumption, as environmental impacts are very material specific.     

Loss and Benefit Caused by a Diesel Engine: From the Perspective of Human Health

This article presents a model that quantifies the health loss and benefit triggered by the life cycle of a diesel engine. The health loss and benefit are expressed in the form of disability‐adjusted life years (DALY), a metric used by the World Health Organization to conduct health impact assessments. In order to quantify the health loss, life cycle assessment methodology is applied. To estimate the health benefit, the relationship between DALY per capita and gross domestic product (GDP) per capita is modeled. The change in GDP per capita, resulting from the change in the level of employee compensation caused by the life cycle of the diesel engine, is used to estimate the change in the level of DALY per capita. An economic input‐output model is applied to estimate the amount of employee compensation required over the life cycle of the diesel engine. This study concludes that the health benefit achieved by the socioeconomic growth, triggered by the life cycle of the diesel engine, is higher than the health loss caused by the pollutions produced over the life cycle of the diesel engine. Furthermore, the results support findings in the literature that socioeconomic growth generates a higher health benefit in a lower‐income country than in a higher‐income country. This also might be one of the reasons for another statement found in the literature that developing countries put higher priorities on economic development.     

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.     

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.     

Global Supply Chains of Coltan

The spot price for tantalum, a metal used in high‐performance consumer electronics, spiked in 2000, triggering a boom in artisanal mining of surface deposits in the Democratic Republic of Congo (DRC). The profit from columbite‐tantalite ore, or coltan, is alleged to have funded militants during that country's civil war. One warlord famously claimed that in 2000, coltan delivered a million dollars per month. While coltan mining was neither a necessary nor sufficient cause for the civil war, there is nevertheless a clear association between mining and conflict. In order to trace global flows of coltan out of the DRC, we used a high‐resolution multiregion input‐output (MRIO) table and a hybrid life cycle assessment (LCA) approach to trace exports through international supply chains in order to estimate a “coltan footprint” for various products. In this case study, our aim is to highlight the power and utility of hybrid LCA analysis using high‐resolution global MRIO accounts. We estimate which supply chains, nations, and consumer goods carry the largest loads of embodied coltan. This hybrid LCA case study provides estimates on illicit flows of coltan, estimates a coltan footprint of consumption, and highlights the advantages and challenges of using hybrid monetary‐physical input‐output/LCA approaches to study and quantify a negative social impact as an input to production. If successful, the hybrid LCA approach could be a useful and expedient measurement tool for understanding flows of conflict minerals embodied in supply chains.     

Development of a Consumer Environmental Index and Results for Washington State Consumers

Consumer choices affect sustainability of societal systems, and state governments increasingly are interested in environmental impacts of consumption. This article describes a Consumer Environmental Index (CEI) to track the impacts of product purchase, use, and disposal and applies this initial CEI to Washington State in the United States. CEI has modules for product and service use, upstream resource extraction and manufacturing, and downstream disposal. CEI uses hybrid life cycle assessment (LCA) methods, combined with purchasing data from the Bureau of Labor Statistics (BLS) Consumer Expenditure Survey. For Washington State, when human health and ecosystem toxicity impact was assessed with the TRACI/CalTOX methods, weighted aggregate and per consumer impacts in all categories increased during the 6 years from 2000 to 2005. For impacts per real dollar spent, only the CEI's climate change component declined, falling nearly 7% between 2000 and 2005. Purchasing details in the BLS expenditure surveys enable the CEI to track environmental impact details on 700 individual categories of products and services. For example, sugar, motor oil, and wood heat appear to have serious environmental impacts, whereas recycling of paper, cardboard, and food and beverage container discards can be as effective at reducing greenhouse gas emissions as cutting vehicle fuel usage nearly in half. Such results may serve to increase understanding of environmentally effective actions to reduce climate, human health, and ecosystem impacts of consumption.