The Impact of Social Factors and Consumer Behavior on Carbon Dioxide Emissions in the United Kingdom

In this article we apply geodemographic consumer segmentation data in an input−output framework to understand the direct and indirect carbon dioxide (CO₂) emissions associated with consumer behavior of different lifestyles in the United Kingdom. In a subsequent regression analysis, we utilize the lifestyle segments contained in the dataset to control for aspects of behavioral differences related to lifestyles in an analysis of the impact of various socioeconomic variables on CO₂ emissions, such as individual aspirations and people's attitudes toward the environment, as well as the physical context in which people act.
This approach enables us to (1) test for the significance of lifestyles in determining CO₂ emissions, (2) quantify the importance of a variety of individual socioeconomic determinants, and (3) provide a visual representation of "where" the various factors exert the greatest impact, by exploiting the spatial information contained in the lifestyle data.
Our results indicate the importance of consumer behavior and lifestyles in understanding CO₂ emissions in the United Kingdom. Across lifestyle groups, CO₂ emissions can vary by a factor of between 2 and 3. Our regression results provide support for the idea that sociodemographic variables are important in explaining emissions. For instance, controlling for lifestyles and other determinants, we find that emissions are increasing with income and decreasing with education. Using the spatial information, we illustrate how the lifestyle mix of households in the United Kingdom affects the geographic distribution of environmental impacts.     

Toward a Carbon Dioxide Neutral Industrial Park

The industrial park of Herdersbrug (Brugge, Flanders, Belgium) comprises 92 small and medium‐sized enterprises, a waste‐to‐energy incinerator, and a power plant (not included in the study) on its site. To study the carbon dioxide (CO₂) neutrality of the park, we made a park‐wide inventory for 2007 of the CO₂ emissions due to energy consumption (electricity and fossil fuel) and waste incineration, as well as an inventory of the existing renewable electricity and heat generation. The definition of CO₂ neutrality in Flanders only considers CO₂ released as a consequence of consumption or generation of electricity, not the CO₂ emitted when fossil fuel is consumed for heat generation. To further decrease or avoid CO₂ emissions, we project and evaluate measures to increase renewable energy generation. The 21 kilotons (kt) of CO₂ emitted due to electricity consumption are more than compensated by the 25 kt of CO₂ avoided by generation of renewable electricity. Herdersbrug Industrial Park is thus CO₂ neutral, according to the definition of the Flemish government. Only a small fraction (6.6%) of the CO₂ emitted as a consequence of fossil fuel consumption (heat generation) and waste incineration is compensated by existing and projected measures for renewable heat generation. Of the total CO₂ emission (149 kt) due to energy consumption (electricity + heat generation) and waste incineration on the Herdersbrug Industrial Park in 2007, 70.5% is compensated by existing and projected renewable energy generated in the park. Forty‐seven percent of the yearly avoided CO₂ corresponds to renewable energy generated from waste incineration and biomass fermentation.     

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.     

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.     

Energy Cost of Living and Associated Pollution for Beijing Residents

China's remarkable economic growth in the last 3 decades has brought about big improvements in quality of life while simultaneously contributing to serious environmental problems. The aim of all economic activities is, ultimately, to provide the population with products and services. Analyzing environmental impacts of consumption can be valuable for illuminating underlying drivers for energy use and emissions in society. This study applies an environmentally extended input‐output analysis to estimate household environmental impact (HEI) of urban Beijing households at different levels of development. The analysis covers direct and indirect energy use and emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), and nitrogen oxide (NO_x). On the basis of observations of how HEI varies across income groups, prospects for near‐future changes in HEI are discussed. Results indicate that in 2007, an urban resident in Beijing used, on average, 52 gigajoules of total primary energy supply. The corresponding annual emissions were 4.2 tonnes CO₂, 27 kilograms SO₂, and 17 kilograms NO_x. Of this, only 18% to 34% was used or emitted by the households directly. While the overall expenditure elasticity of energy use is around 0.9, there is a higher elasticity of energy use associated with transport. The results suggest that significant growth in HEI can be expected in the near future, even with substantial energy efficiency improvements.     

Water Consumption Based on a Disaggregated Social Accounting Matrix of Huesca (Spain)

Making use of the social accounting matrix (SAM) of the Spanish province of Huesca in 2002, updated following Junius and Oosterhaven's GRAS method and work by Lenzen and colleagues, we have estimated the water footprint of the region. The water footprint is defined as the volume of water needed for the production of the goods and services consumed by the inhabitants plus the direct consumption in the households. We built an open Leontief model, which gives us the water embodied in the production of goods. The valuations concern the industrial, service, and domestic sectors’ water consumption, the embodied water imported from and exported to other countries, and the agrarian water use. This agrarian sector, clearly the sector that shows the greatest water consumption, is carefully examined, so it is disaggregated for the calculations into 31 irrigation land products, dry land, and 9 livestock classifications. As a consequence, the framework enables the observation of the relationships and flows of water taking place among all the sectors and activities in the economy. Finally, we also make use of the per capita water footprint estimations to get a clear picture of how the responsibility for water use is distributed once foreign trade is taken into account.     

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.     

Shifting Trade Patterns as a Means of Reducing Global Carbon Dioxide Emissions

This article extends and applies the world trade model with bilateral trade (WTMBT), a linear program with any number of goods, factors, and regional trade partners that determines regional production, bilateral trade patterns, and region-specific prices on the basis of comparative advantage by minimizing factor use. The model provides a consistent analysis of the global production system, representing geographical location at a regional level, region-specific technologies at a sector level, emissions from production, and resource constraints and costs. An illustrative analysis investigates how changes in the geographic distribution of production could contribute to reducing global carbon dioxide (CO₂) emissions and at what cost. The model provides a bridge between global objectives and their determinants and consequences in specific sectors in individual regions. Multi-objective analysis is used to construct a trade-off curve between global factor costs and CO₂ emissions. The relevance of both primal and dual solution variables is demonstrated. In particular, changes in goods prices and emissions are investigated. We conclude that the main impact of tightening carbon constraints is a substantial reduction in international trade accompanied by a shift away from regions most reliant on the combustion of coal. In addition to the analysis of the overall global trends, including the impact on prices, the implications of the global carbon constraint for one specific industry are investigated.     

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.     

Environmental Footprints and Scenario Analysis for Assessing the Impacts of the Agri‐Food Industry on a Regional Economy: A Case Study in Spain

The study of the environmental footprints of various sectors and industries is increasingly demanded by institutions and by society. In this context, the regional perspective is becoming particularly important, and even more so in countries such as Spain, where the autonomous communities have the primary responsibility for implementing measures to combat environmental degradation and promote sustainable development, in coordination with national strategies. Taking as a case study a Spanish region, Aragon, and significant economic sectors, including agriculture and the food industry, the aim of this work is twofold. First, we calculate the associated environmental footprints (of emissions and water) from the dual perspectives of production (local impacts) and consumption (final destination of the goods produced by the agri‐food industry). Second, through a scenarios analysis, based on a general equilibrium model designed and calibrated specifically for the region, we evaluate the environmental implications of changes in the agri‐food industry (changes in the export and import pattern, as well as in consumer behavior). This model provides a flexible approximation to the environmental impacts, controlling for a wider range of behavioral and economic interactions. Our results indicate that the agri‐food industry has a significant impact on the environment, especially on water resources, which must be responsibly managed in order to maintain the differential advantage that a regional economy can have, compared to other territories.     

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.     

The Corruption Footprints of Nations

In this study, we innovatively apply multiregional input‐output analysis to calculate corruption footprints of nations and show the details of commodities that use the most employment affected by corruption (EAC), as they flow between countries. Every country's corruption footprint includes its domestic corruption and the corruption imported by global supply chains to meet final demand. Our results show that, generally, the net corruption exporters are developing countries, with the exception of Italy where corruption is likely to be more affected by political and cultural factors than economic factors. China is the largest gross corruption exporter, and India follows close behind, with clothing as one of the industries in which the most people are affected by corruption. This is because: (1) China and India are major clothing exporters, thus many workers are employed in the clothing industry within the country as well as in countries providing intermediate commodities by supply chains, and (2) corruption is high in China and India. Our results can be useful to identify where regulations to combat corruption can have the greatest impact. More important, the method we use can be applied to link corruption to other economic and social aspects of trade, such as working conditions, thus making it possible to find avenues for tackling the problem that are not usually considered in anticorruption strategies.     

Sectoral Aggregation Error in the Accounting of Energy and Emissions Embodied in Trade and Consumption

Correctly accounting for the energy and emissions embodied in consumption and trade is essential to effective climate policy design. Robust methods are needed for both policy making and research—for example, the assignment of border carbon adjustments (BCAs) and greenhouse gas emission reduction responsibilities rely on the consistency and accuracy of such estimates. This analysis investigates the potential magnitude and consequences of the error present in estimates of energy and emissions embodied in trade and consumption. To quantify the error of embodied emissions accounting, we compare the results from the disaggregated Global Trade Analysis Project (GTAP 8) data set, which contains 57 sectors to results from different levels of aggregation of this data set (3, 7, 16, and 26 sectors), using 5,000 randomly generated sectoral aggregation schemes as well as aggregations generated using several commonly applied decisions rules. We find that some commonly applied decision rules for sectoral aggregation can produce a large error. We further show that an aggregation scheme that clusters sectors according to their energy, emissions, and trade intensities (net exports over output) can minimize error in embodied energy and emissions accounting at different levels of aggregation. This sectoral aggregation scheme can be readily used in any input‐output analysis and provide useful information for computable general equilibrium modeling exercises in which sector aggregation is necessary, although our findings suggest that, when possible, the most disaggregated data available should be used.     

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.     

Effect of Change of Forest Carbon Storage on Net Carbon Dioxide Balance of Wood Use for Energy in Japan

This study analyzed the net carbon dioxide (CO₂) emission reductions between 2005 and 2050 by using wood for energy under various scenarios of forest management and energy conversion technology in Japan, considering both CO₂ emission reductions from replacement of fossil fuels and changes in carbon storage in forests. According to our model, wood production for energy results in a significant reduction of carbon storage levels in forests (by 46% to 77% in 2050 from the 2005 level). Thus, the net CO₂ emission reduction when wood is used for energy becomes drastically smaller. Conventional tree production for energy increases net CO₂ emissions relative to preserving forests, but fast‐growing tree production may reduce net CO₂ emissions more than preserving forests does. When wood from fast‐growing trees is used to generate electricity with gas turbines, displacing natural gas, the net CO₂ emission reduction from the combination of fast‐growing trees and electricity generation with gas turbines is about 58% of the CO₂ emission reduction from electricity generation from gas turbines alone in 2050, and an energy conversion efficiency of around 20% or more is required to obtain net reductions over the entire period until 2050. When wood is used to produce bioethanol, displacing gasoline, net reductions are realized after 2030, provided that heat energy is recovered from residues from ethanol production. These results show the importance of considering the change in carbon storage when estimating the net CO₂ emission reduction effect of the wood use for energy.     

Lifting Industrial Ecology Modeling to a New Level of Quality and Transparency: A Call for More Transparent Publications and a Collaborative Open Source Software Framework

Industrial ecology (IE) is a maturing scientific discipline. The field is becoming more data and computation intensive, which requires IE researchers to develop scientific software to tackle novel research questions. We review the current state of software programming and use in our field and find challenges regarding transparency, reproducibility, reusability, and ease of collaboration. Our response to that problem is fourfold: First, we propose how existing general principles for the development of good scientific software could be implemented in IE and related fields. Second, we argue that collaborating on open source software could make IE research more productive and increase its quality, and we present guidelines for the development and distribution of such software. Third, we call for stricter requirements regarding general access to the source code used to produce research results and scientific claims published in the IE literature. Fourth, we describe a set of open source modules for standard IE modeling tasks that represent our first attempt at turning our recommendations into practice. We introduce a Python toolbox for IE that includes the life cycle assessment (LCA) framework Brightway2, the ecospold2matrix module that parses unallocated data in ecospold format, the pySUT and pymrio modules for building and analyzing multiregion input‐output models and supply and use tables, and the dynamic_stock_model class for dynamic stock modeling. Widespread use of open access software can, at the same time, increase quality, transparency, and reproducibility of IE research.     

Addressing the Carbon‐Crime Blind Spot: A Carbon Footprint Approach

Governments estimate the social and economic impacts of crime, but its environmental impact is largely unacknowledged. Our study addresses this by estimating the carbon footprint of crime in England and Wales and identifies the largest sources of emissions. By applying environmentally extended input‐output analysis–derived carbon emission factors to the monetized costs of crime, we estimate that crime committed in 2011 in England and Wales gave rise to over 4 million tonnes of carbon dioxide equivalents. Burglary resulted in the largest proportion of the total footprint (30%), because of the carbon associated with replacing stolen/damaged goods. Emissions arising from criminal justice system services also accounted for a large proportion (21% of all offenses; 49% of police recorded offenses). Focus on these offenses and the carbon efficiency of these services may help reduce the overall emissions that result from crime. However, cutting crime does not automatically result in a net reduction in carbon, given that we need to take account of potential rebound effects. As an example, we consider the impact of reducing domestic burglary by 5%. Calculating this is inherently uncertain given that it depends on assumptions concerning how money would be spent in the absence of crime. We find the most likely rebound effect (our medium estimate) is an increase in emissions of 2%. Despite this uncertainty concerning carbon savings, our study goes some way toward informing policy makers of the scale of the environmental consequences of crime and thus enables it to be taken into account in policy appraisals.     

Unraveling the Nexus: Exploring the Pathways to Combined Resource Use

In response to the unprecedented decline in global natural resource endowments, the so‐called nexus framework is gaining increasing influence on resource management practices. In this research, we approach the resource nexus through the concept of nexus pathways. Nexus pathways are configurations that resource flows follow along supply chains leading to the combined use of two or more resources. Three general types of pathways are identified: direct (on‐site use), dependent (one‐way supply chains), and interdependent (supply‐chain feedbacks). We quantify and compare each pathway by means of multiregional input‐output analysis and structural path analysis, and apply this approach to a comparative case study on the water‐energy nexus (WEN) in the United States and China. Interdependencies or feedbacks are generally thought to be relevant for the WEN, especially between water and energy sectors. Our economy‐wide analysis for both countries indicates, however, that feedbacks neither play an important role in the WEN nor substantially take place between water and energy sectors. The most important feedbacks contribute to less than 1% of total resource use, and these take place mostly between manufacturing sectors. Overall, the studied WEN is mostly driven by dependent pathways and, to a lesser degree, direct resource use. Comparative differences between the two countries are largely explained by differences in economic structure, technology, and resource endowments. Our findings call into question current research and policy focus and suggest greater attention to less complex, but more determining, pathways leading to absolute resource use.     

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.     

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.