Environmental Impacts of Products: A Detailed Review of Studies

Environmental effects of economic activities are ultimately driven by consumption, via impacts of the production, use, and waste management phases of products and services ultimately consumed. Integrated product policy (IPP) addressing the life‐cycle impacts of products forms an innovative new generation of environmental policy. Yet this policy requires insight into the final consumption expenditures and related products that have the greatest life‐cycle environmental impacts. This review article brings together the conclusions of 11 studies that analyze the life‐cycle impacts of total societal consumption and the relative importance of different final consumption categories. This review addresses in general studies that were included in the project Environmental Impacts of Products (EIPRO) of the European Union (EU), which form the basis of this special issue. Unlike most studies done in the past 25 years on similar topics, the studies reviewed here covered a broad set of environmental impacts beyond just energy use or carbon dioxide (CO₂) emissions. The studies differed greatly in basic approach (extrapolating LCA data to impacts of consumption categories versus approaches based on environmentally extended input‐output (EEIO) tables), geographical region, disaggregation of final demand, data inventory used, and method of impact assessment. Nevertheless, across all studies a limited number of priorities emerged. The three main priorities, housing, transport, and food, are responsible for 70% of the environmental impacts in most categories, although covering only 55% of the final expenditure in the 25 countries that currently make up the EU. At a more detailed level, priorities are car and most probably air travel within transport, meat and dairy within food, and building structures, heating, and (electrical) energy‐using products within housing. Expenditures on clothing, communication, health care, and education are considerably less important. Given the very different approaches followed in each of the sources reviewed, this result hence must be regarded as extremely robust. Recommendations are given to harmonize and improve the methodological approaches of such analyses, for instance, with regard to modeling of imports, inclusion of capital goods, and making an explicit distinction between household and government expenditure.     

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.     

Supply versus use designs of environmental extensions in input–output analysis: Conceptual and empirical implications for the case of energy

Input–output analysis is one of the central methodological pillars of industrial ecology. However, the literature that discusses different structures of environmental extensions (EEs), that is, the scope of physical flows and their attribution to sectors in the monetary input–output table (MIOT), remains fragmented. This article investigates the conceptual and empirical implications of applying two different but frequently used designs of EEs, using the case of energy accounting, where one represents energy supply while the other energy use in the economy. We derive both extensions from an official energy supply–use dataset and apply them to the same single‐region input–output (SRIO) model of Austria, thereby isolating the effect that stems from the decision for the extension design. We also crosscheck the SRIO results with energy footprints from the global multi‐regional input–output (GMRIO) dataset EXIOBASE. Our results show that the ranking of footprints of final demand categories (e.g., household and export) is sensitive to the extension design and that product‐level results can vary by several orders of magnitude. The GMRIO‐based comparison further reveals that for a few countries the supply‐extension result can be twice the size of the use‐extension footprint (e.g., Australia and Norway). We propose a graph approach to provide a generalized framework to disclosing the design of EEs. We discuss the conceptual differences between the two extension designs by applying analogies to hybrid life‐cycle assessment and conclude that our findings are relevant for monitoring of energy efficiency and emission reduction targets and corporate footprint accounting.     

Setting Priorities within Product-Oriented Environmental Policy

To focus Danish product‐oriented environmental policy, a study applying extended input‐output analysis has been performed, identifying the most important product groups from an environmental perspective. The environmental impacts are analyzed from three different perspectives—the supply perspective, the consumption perspective, and the process perspective—differing primarily in their system delimitation. The top ten environmentally most important product groups (out of 138 industry products and 98 final consumption groups) are listed for each of the three perspectives, using both total environmental impact and environmental impact intensity as ranking principles. The study covers all substances that contribute significantly to the environmental impact categories of global warming, ozone depletion, acidification, nutrient enrichment, photochemical ozone formation, ecotoxicity, human toxicity, and nature occupation. The differences in results between the three perspectives are elaborated and their policy relevance discussed. The top ten product groups account for a surprisingly large share of the total environmental impact of Danish production and consumption (up to 45%, depending upon the perspective). This implies that product‐oriented environmental policy may achieve large improvements by focusing on a rather small number of product groups. Both imported products and products produced for export in general cause more environmental impact than products produced in Denmark for the Danish market. Especially noticeable are the export of meat and ship transport. This leads to the recommendation to include specific policy measures targeting both foreign producers and foreign markets. Because of its relatively large input of labor, public consumption is found to have a much smaller environmental impact intensity than private consumption. The results confirm results of other similar studies, but are more detailed and have lower uncertainty, due to a number of improvements in data and methodology. A short presentation of the methodology is provided as background information, although this is not the main focus of this article.     

Environmental Impacts of Consumption in the European Union:High-Resolution Input-Output Tables with Detailed Environmental Extensions

For developing product policy, insight into the environmental effects of products is required. But available life-cycle assessment studies (LCAs) are hardly comparable between different products and do not cover total consumption. Input-output analysis with environmental extensions (EEIOA) of full consumption is not available for the European Union. Available country studies have a low sector resolution and a limited number of environmental extensions. This study fills the gap between detailed LCA and low-resolution EEIOA, specifying the environmental effects of household consumption in the European Union, discerning nearly 500 sectors, while specifying a large number of environmental extensions. Added to the production sectors are a number of consumption activities with direct emissions, such as automobile driving, cooking and heating, and a number of postconsumer waste management sectors. The data for Europe have been constructed by using the sparse available and coarse economic and environmental data on European countries and adding technological detail mainly based on data from the United States.
A small number of products score high on environmental impact per Euro and also have a substantial share of overall consumer expenditure. Several meat and dairy products, household heating, and car driving thus have a large share of the total environmental impact. Due to their sales volume, however, products with a medium or low environmental score per Euro may also have a substantial impact. This is the case with bars and restaurants, clothing, residential construction, and even a service such as telecommunications. The limitations in real European data made heroic assumptions necessary to operationalize the model. One conclusion, therefore, is that provision of data in Europe urgently needs to be improved, at least to the level of sector detail currently available for the United States and Japan.     

When Do Allocations and Constructs Respect Material,Energy, Financial,and Production Balances in LCA and EEIO?

Conservation of mass and energy are essential to physical accounting, just as price and market balances are essential to economic accounting. These principles guide data collection and inventory compilation in industrial ecology. The resulting balanced surveys, however, can rarely be used directly for life cycle assessment (LCA) or environmentally extended input‐output (EEIO) analysis; some modeling is necessary to recast coproductions by multifunctional activities as monofunctional unit processes (a.k.a. Leontief production functions or technical “recipes”). This modeling is done with allocations in LCA and constructs in input‐output. In this article, we ask how these models respect or perturb the balances of the original inventory. Which allocations or constructs, applied to what type of data set, have the potential to simultaneously respect its multiple physical, financial, and market balances? Our analysis builds upon the recent harmonization of allocations and constructs and the ongoing development of multilayered supply and use inventory tables. We derive the necessary and sufficient conditions for balanced models, investigate the role of data aggregation, and clarify these models' relation to system expansion. We find that none of the modeling families in LCA and EEIO are balanced in general, but special data characteristics can allow for the respect of multiple balances. An analysis of these special cases allows for clear guidance for data compilation and methods integration.     

Hotspot Scenario Analysis

Increasingly, organizations are working to reduce the environmental footprint of their supply chains. The use of environmentally preferable purchasing criteria is one strategy organizations use to address this goal. However, evaluating the environmental performance of these criteria (e.g., recycled content, biodegradable, renewable, and so on) has remained elusive. Life cycle assessment (LCA) can measure the impact reduction potential of sourcing strategies. However, full process‐based LCAs are time‐consuming and costly across multiple criteria of thousands of products and inputs purchased in an organizational setting. A streamlined “hotspot” methodology is presented using a combination of environmentally extended economic input‐output (EEIO) approaches and extant literature to identify hotspots in which to constrain a parameterized process‐based LCA. A case study of breakfast cereal manufacturing is developed to (1) assess the efficiencies associated with the hotspotting approach and (2) demonstrate its applicability in generating comparable decision signals of environmentally preferable sourcing criteria for procurement and supply‐chain managers along the dimensions of global warming potential and water use.     

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.     

How Can the Eco‐efficiency of a Region be Measured and Monitored?

The concept of eco-efficiency is commonly referred to as a business link to sustainable development. In this article, ecoefficiency is examined at a regional level as an approach to promoting the competitiveness of economic activities in the Finnish Kymenlaakso region and mitigating their harmful impacts on the environment. The aim is to develop appropriate indicators for monitoring changes in the eco-efficiency of the region. A starting point is to produce indicators for the environmental and economic dimensions of regional development and use them for measuring regional eco-efficiency. The environmental impact indicators are based on a life-cycle assessment method, producing different types of environmental impact indicators: pressure indicators (e.g., emissions of CO₂), impact category indicators (e.g., CO₂ equivalents in the case of climate change), and a total impact indicator (aggregating different impact category indicator results into a single value). Environmental impact indicators based on direct material input, total material input, and total material requirement of the Kymenlaakso region are also assessed. The economic indicators used are the gross domestic product, the value added, and the output of the main economic sectors of Kymenlaakso. In the eco-efficiency assessment, the economic and environmental impact indicators are monitored in the same graph. In a few cases eco-efficiency ratios can also be calculated (the economic indicators are divided by the environmental indicators). Output (= value added + intermediate consumption) is used as an economic indicator related to the environmental impact indicators, which also cover the upstream processes of the region's activities. In the article, we also discuss the strengths and weaknesses of using the different environmental impact indicators.     

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.     

The Energy Structure of the Canadian Economy

We developed a model of a national economy in which the phenomena of supply, demand, economic growth, and international trade are represented in terms of energy flows. In examining the structure of the economy, we distinguish between the energy embodied in capital assets used in the production and distribution of energy and that embodied in capital assets and goods that consume energy. Sources used to quantify the energy flows include: end‐use energy data by economic sector; International Energy Agency–style national energy balances, and national input‐output tables. As an example, the Canadian economy for 2008 produced 16.97 exajoules (EJ) of energy, which after net export of 6.16 EJ and other adjustments left a total primary energy consumption of 10.61 EJ. The energy supply and distribution sectors used close to 32% (3.36 EJ) of total primary consumption. Analysis of primary energy consumption shows that 25.14% was embodied in household consumption, 22.85% was consumed directly by households, 7.88% was embodied in government services, and 34.07% was embodied in exports. Of significance to economic growth, 7.14% was embodied in capital in energy demanding sectors, 1.25% in energy consuming personal assets, and 1.52% in supply sector capital. The energy return on energy investment was relatively constant, averaging 5.14 between 1990 and 2008. Capital investments required to decouple the Canadian economy from its dependence on fossil fuels are discerned.     

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

Dynamic 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.     

Environmental impacts of European trade: interpreting results of process-based LCA and environmentally extended input–output analysis towards hotspot identification

Purpose

Trade is increasingly considered a significant contributor to environmental impacts. The assessment of the impacts of trade is usually performed via environmentally extended input–output analysis (EEIOA). However, process-based life cycle assessment (LCA) applied to traded goods allows increasing the granularity of the analysis and may be essential to unveil specific impacts due to traded products.

Methods

This study assesses the environmental impacts of the European trade, considering two modelling approaches: respectively EEIOA, using EXIOBASE 3 as supporting database, and process-based LCA. The interpretation of the results is pivotal to improve the robustness of the assessment and the identification of hotspots. The hotspot identification focuses on temporal trends and on the contribution of products and substances to the overall impacts. The inventories of elementary flows associated with EU trade, for the period 2000–2010, have been characterized considering 14 impact categories according to the Environmental Footprint (EF2017) Life Cycle Impact Assessment method.

Results and discussion

The two modelling approaches converge in highlighting that in the period 2000–2010: (i) EU was a net importer of environmental impacts; (ii) impacts of EU trade and EU trade balance (impacts of imports minus impacts of exports) were increasing over time, regarding most impact categories under study; and (iii) similar manufactured products were the main contributors to the impacts of exports from EU, regarding most impact categories. However, some results are discrepant: (i) larger impacts are obtained from IO analysis than from process-based LCA, regarding most impact categories, (ii) a different set of most contributing products is identified by the two approaches in the case of imports, and (iii) large differences in the contributions of substances are observed regarding resource use, toxicity, and ecotoxicity indicators.

Conclusions

The interpretation step is crucial to unveil the main hotspots, encompassing a comparison of the differences between the two methodologies, the assumptions, the data coverage and sources, the completeness of inventory as basis for impact assessment. The main driver for the observed divergences is identified to be the differences in the impact intensities of goods, both induced by inherent properties of the IO and life cycle inventory databases and by some of this study’s modelling choices. The combination of IO analysis and process-based LCA in a hybrid framework, as performed in other studies but generally not at the macro-scale of the full trade of a country or region, appears a potential important perspective to refine such an assessment in the future.

     

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.     

Key sectors in greenhouse gas emissions in Spain: An alternative input–output analysis

We develop an alternative input–output approach and apply it to the determination of key sectors in emissions. This methodology allows us to assess and classify the different productive sectors according to their greenhouse gas emissions and the role that they play in the productive structure, as well as the participation of their output in the total volume of production. In contrast with previous approaches, we do not focus on the responsibility of final demand, but on the responsibility of the total production of each sector. We apply our methodology to the 2014 input–output table for Spain provided by the World Input–Output Database (2016). The results show that the sectors that induce more emissions from other sectors are manufacture of food products, wholesale and retail trade, and construction. Those that are pulled to emit coincide with those that are relevant for their own final demand, being the most important electricity and gas provision, agriculture, and transportation. The classification obtained allows to orient the design of greenhouse gas emission mitigation policies for the different sectors.     

A value transfer GERT network model for carbon fiber industry chain based on input–output table

This paper builds an input–output table for carbon fiber industry chain in accordance with input–output theory. In order to get a clear picture of the dynamic input–output process between a variety of sectors involved in the carbon fiber industry chain and the increment of value hereinto, a Graphical Evaluation and Review Technique (GERT) network model is constructed on the basis of value flow, and an analytical algorithm for the GERT network model is proposed to get the value transfer probability, the amount of value increment, and the fluctuation variance, from which the equivalence value transfer process and results between sectors are obtained. Finally, in the case study part, this paper finds out the value transfer relationship within the carbon fiber industry chain in Jiangsu Province, China based on the empirical data gotten from field investigations, and then some constructive policy-making and investment suggestions are put forward in view of the results and analyses.     

A hybrid life cycle assessment of water treatment chemicals: an Australian experience

Purpose

Life cycle assessment (LCA) of chemicals is usually developed using a process-based approach. In this paper, we develop a tiered hybrid LCA of water treatment chemicals combining the specificity of process data with the holistic nature of input–output analysis (IOA). We compare these results with process and input–output models for the most commonly used chemicals in the Australian water industry to identify the direct and indirect environmental impacts associated with the manufacturing of these materials.

Methods

We have improved a previous Australian hybrid LCA model by updating the environmental indicators and expanding the number of included industry sectors of the economy. We also present an alternative way to estimate the expenditure vectors to the service sectors of the economy when financial data are not available. Process-based, input–output and hybrid results were calculated for caustic soda, sodium hypochlorite, ferric chloride, aluminium sulphate, fluorosilicic acid, calcium oxide and chlorine gas. The functional unit is the same for each chemical: the production of 1 tonne in the year 2008.

Results and discussion

We have provided results for seven impact categories: global warming potential; primary energy; water use; marine, freshwater and terrestrial ecotoxicity potentials and human toxicity potential. Results are compared with previous IOA and hybrid studies. A sensitivity analysis of the results to assumed wholesale prices is included. We also present insights regarding how hybrid modelling helps to overcome the limitations of using IO- or process-based modelling individually.

Conclusions and recommendations

The advantages of using hybrid modelling have been demonstrated for water treatment chemicals by expanding the boundaries of process-based modelling and also by reducing the sensitivity of IOA to fluctuations in prices of raw materials used for the production of these industrial commodities. The development of robust hybrid life cycle inventory databases is paramount if hybrid modelling is to become a standard practice in attributional LCA.     

An Australian Multi‐Regional Waste Supply‐Use Framework

The production of waste creates both direct and indirect environmental impacts. A range of strategies are available to reduce the generation of waste by industry and households, and to select waste treatment approaches that minimize environmental harm. However, evaluating these strategies requires reliable and detailed data on waste production and treatment. Unfortunately, published Australian waste data are typically highly aggregated, published by a variety of entities in different formats, and do not form a complete time‐series. We demonstrate a technique for constructing a multi‐regional waste supply‐use (MRWSU) framework for Australia using information from numerous waste data sources. This is the first MRWSU framework to be constructed (to the authors' knowledge) and the first sub‐national waste input‐output framework to be constructed for Australia. We construct the framework using the Industrial Ecology Virtual Laboratory (IELab), a cloud‐hosted computational platform for building Australian multi‐regional input‐output tables. The structure of the framework complies with the System of Environmental‐Economic Accounting (SEEA). We demonstrate the use of the MRWSU framework by calculating waste footprints that enumerate the full supply chain waste production for Australian consumers.