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.     

Environmental Assessment of Wood‐Based Biofuel Production and Consumption Scenarios in Norway

In Norway, the boreal forest offers a considerable resource base, and emerging technologies may soon make it commercially viable to convert these resources into low‐carbon biofuels. Decision makers are required to make informed decisions about the environmental implications of wood biofuels today that will affect the medium‐ and long‐term development of a wood‐based biofuels industry in Norway. We first assess the national forest‐derived resource base for use in biofuel production. A set of biomass conversion technologies is then chosen and evaluated for scenarios addressing biofuel production and consumption by select industry sectors. We then apply an environmentally extended, mixed‐unit, two‐region input?output model to quantify the global warming mitigation and fossil fuel displacement potentials of two biofuel production and consumption scenarios in Norway up to 2050. We find that a growing resource base, when used to produce advanced biofuels, results in cumulative global warming mitigation potentials of between 58 and 83 megatonnes of carbon dioxide equivalents avoided (Mt‐CO₂‐eq.‐avoided) in Norway, depending on the biofuel scenario. In recent years, however, the domestic pulp and paper industry—due to increasing exposure to international competition, capacity reductions, and increasing production costs—has been in decline. In the face of a declining domestic pulp and paper industry, imported pulp and paper products are required to maintain the demand for these goods and thus the greenhouse gas (GHG) emissions of the exporting region embodied in Norway's pulp and paper imports reduce the systemwide benefit in terms of avoided greenhouse gas emissions by 27%.     

Subnational greenhouse gas and land‐based biodiversity footprints in the European Union

Insights into subnational environmental impacts and the underlying drivers are scarce, especially from a consumption‐based perspective. Here, we quantified greenhouse gas (GHG) emissions and land‐based biodiversity losses associated with final consumption in 162 regions in the European Union in 2010. For this purpose, we developed an environmentally extended multi‐regional input–output (MRIO) model with subnational European information on demand, production, and trade structures subdivided into 18 major economic sectors, while accounting for trade outside Europe. We employed subnational data on land use and national data on GHG emissions. Our results revealed within‐country differences in per capita GHG and land‐based biodiversity footprints up to factors of 3.0 and 3.5, respectively, indicating that national footprints may mask considerable subnational variability. The per capita GHG footprint increased with per capita income and income equality, whereas we did not find such responses for the per capita land‐based biodiversity footprint, reflecting that extra income is primarily spent on energy‐intensive activities. Yet, we found a shift from the domestic to the foreign part of the biodiversity footprints with rising population density and income. Because our analysis showed that most regions are already net importers of GHG emissions and biodiversity losses, we conclude that it is increasingly important to address the role of trade in national and regional policies on mitigating GHG emissions and averting further biodiversity losses, both within and outside the region itself. To further increase the policy relevance of subnational footprint analyses, we also recommend the compilation of more detailed subnational MRIO databases including harmonized environmental data.     

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.     

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.     

Bridging the climate mitigation gap with economy‐wide material productivity

Projections of UK greenhouse gas emissions estimate a shortfall in existing and planned climate policies meeting UK climate targets: the UK's mitigation gap. Material and product demand is driving industrial greenhouse gas emissions at a rate greater than carbon intensity improvements in the economy. Evidence shows that products can be produced with fewer carbon intensive inputs and demand for new products can be reduced. The economy‐wide contribution of material productivity and lifestyle changes to bridging the UK's mitigation gap is understudied. We integrate an input‐output framework with econometric analysis and case study evidence to analyse the potential of material productivity to help the UK bridge its anticipated emissions deficits, and the additional effort required to achieve transformative change aligned with 2 and 1.5°C temperature targets. We estimate that the emissions savings from material productivity measures are comparable to those from the Government's planned climate policy package. These additional measures could reduce the UK's anticipated emissions deficit up to 73%. The results demonstrate that material productivity deserves greater consideration in climate policy.     

Capital in the American carbon,energy, and material footprint

Stocks of fixed capital play a vital role in fulfilling basic human needs and facilitating industrial production. Their build‐up requires great quantities of energy and materials, and generates greenhouse gas emissions and other pollution. Capital stocks influence economic production and environmental pollution through their construction and over subsequent decades through their use. We perform an environmental footprint analysis of total consumption, capital investment, and capital consumption in the United States for 2007 and 2012. In 2012, capital consumption accounted for 13%, 19%, and 40% of total carbon, energy, and material footprints, respectively. Housing, federal defense, state and local government education and other services (including household consumption of roads), personal transport fuels, and hospitals are the consumption sectors with largest capital footprints. These sectors provide fundamental needs of shelter, transport, education, and health, underlying the importance of capital services. Endogenizing capital causes the biggest proportional increase to footprints of sectors with low environmental multipliers. This work builds upon existing input‐output models of production and consumption in the United States, and provides a capital‐inclusive database of carbon, energy, and material footprints and multipliers for 2007 and 2012. This article met the requirements for a gold – gold JIE data openness badge described at http://jie.click/badges .     

Time series analysis models for estimation of greenhouse gas emitted by different sectors in Turkey

Due to the increasing global warming in the world, analyzing greenhouse gas emissions is a crucial issue. This study has examined greenhouse gas emissions in Turkey according to energy sector, industrial processes sector, agriculture sector and waste sector. Then, time series analysis models are used to estimate greenhouse gas emissions based on sectors. Models' performances are tested using mean error, mean absolute error and root mean square error. The results show that forecasting models have a good potential to estimate the national greenhouse gas emissions for different sector within a reasonable error. The study results will help organize and estimate the national greenhouse gas emissions inventory.     

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.     

Comparison of greenhouse gas emission accounting for a constructed wetland wastewater treatment system

The method of systems accounting as a combination of process analysis and input–output analysis is applied to assess the greenhouse gas (GHG) emissions of Longdao River constructed wetland (LRCW), a typical constructed wetland in northern China. An improved GHG emission assessment for the constructed wetland wastewater treatment is made in this paper by using a local embodied GHG emissions intensity database for the Beijing economy 2002. Results show that the indirect GHG emission of the case constructed wetland accounts for 82.31% of the total GHG emissions. More than half of the indirect GHG emission is caused by the electricity. 64.48% of the total GHG emissions happened during the operation stage. There is a great gap between the GHG emissions of the LRCW in this study and in former study, which can be attributed to the diverse economy structures and technology levels of Beijing economy and Chinese economy.     

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

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

On the suitability of input–output analysis for calculating product-specific biodiversity footprints

Recently it has been estimated that one third of biodiversity threats are driven by consumer demand from outside the country in which the threat occurs. This occurs when the production of export goods exerts pressure on vulnerable populations. While population biologists have in cases been able to establish links between species threats and the causative industry(s), little has been done to trace this biodiversity footprint from the directly implicated industry out to final consumers, a step that would open a wider variety of policy responses. Here we investigate the suitability of multi-region input–output (MRIO) analysis for tracing out links between particular species threats, directly implicated industries, and the countries and consumer goods sectors ultimately driving these industries. Environmentally extended MRIO models are understood to provide reliable results at a macroeconomic level but uncertainty increases as the models are used to investigate individual sectors, companies, and products. In this study we examine several case studies (nickel mining in New Caledonia, coltan from the Democratic Republic of Congo, cut flowers from Kenya, and forestry in Papua New Guinea) in order to understand how and when MRIO techniques can be useful for studying biodiversity implicated supply chains. The study was conducted using the Eora global input–output database that documents >5 billion global supply chains. Calculating the biodiversity footprint at this level of detail, between specific threats, supply chains, and consumer goods, has not been done before. These case studies provide interesting insights in their own right and also serve to highlight the strengths and weaknesses of using input–output analysis techniques to calculate detailed biodiversity footprints. We conclude that MRIO analysis, while no panacea, can be useful for outlining supply chains and identifying which consumption sectors and trade and transformation steps can be subjected to closer analysis in order to enable remedial action.     

Features and influencing factors of carbon emissions indicators in the perspective of residential consumption: Evidence from Beijing,China

This research establishes a residential indirect carbon emissions model through input–output structure decomposition analysis (IO-SDA) and LMDI, analyses the influencing factors affecting urban and rural residential carbon emissions indicators in Beijing through input–output tables from 2000 to 2010, and calculates the direct carbon emissions from residential consumption. As the results suggest, the total carbon emissions from residential consumption in Beijing showed volatility. Growing rural and urban differences in direct emissions, and for indirect emissions, mean that urban greatly exceeds rural in this regard. Rising per capita GDP and population, as well as intermediate demand and sectoral emissions intensity change induce growth in indirect emissions in both urban and rural settings: of which, per capita GDP contributes the most. Declining energy intensity contributes the most to emission reductions, followed by residential consumption rates, the rural to urban consumption ratio and consumption structure effects are much smaller.     

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.     

How much do direct livestock emissions actually contribute to global warming?

Agriculture directly contributes about 10%–12% of current global anthropogenic greenhouse gas emissions, mostly from livestock. However, such percentage estimates are based on global warming potentials (GWPs), which do not measure the actual warming caused by emissions and ignore the fact that methane does not accumulate in the atmosphere in the same way as CO₂. Here, we employ a simple carbon cycle‐climate model, historical estimates and future projections of livestock emissions to infer the fraction of actual warming that is attributable to direct livestock non‐CO₂ emissions now and in future, and to CO₂ from pasture conversions, without relying on GWPs. We find that direct livestock non‐CO₂ emissions caused about 19% of the total modelled warming of 0.81°C from all anthropogenic sources in 2010. CO₂ from pasture conversions contributed at least another 0.03°C, bringing the warming directly attributable to livestock to 23% of the total warming in 2010. The significance of direct livestock emissions to future warming depends strongly on global actions to reduce emissions from other sectors. Direct non‐CO₂ livestock emissions would contribute only about 5% of the warming in 2100 if emissions from other sectors increase unabated, but could constitute as much as 18% (0.27°C) of the warming in 2100 if global CO₂ emissions from other sectors are reduced to near or below zero by 2100, consistent with the goal of limiting warming to well below 2°C. These estimates constitute a lower bound since indirect emissions linked to livestock feed production and supply chains were not included. Our estimates demonstrate that expanding the mitigation potential and realizing substantial reductions of direct livestock non‐CO₂ emissions through demand and supply side measures can make an important contribution to achieve the stringent mitigation goals set out in the Paris Agreement, including by increasing the carbon budget consistent with the 1.5°C goal.     

Model collaboration for the improved assessment of biomass supply,demand, and impacts

Existing assessments of biomass supply and demand and their impacts face various types of limitations and uncertainties, partly due to the type of tools and methods applied (e.g., partial representation of sectors, lack of geographical details, and aggregated representation of technologies involved). Improved collaboration between existing modeling approaches may provide new, more comprehensive insights, especially into issues that involve multiple economic sectors, different temporal and spatial scales, or various impact categories. Model collaboration consists of aligning and harmonizing input data and scenarios, model comparison and/or model linkage. Improved collaboration between existing modeling approaches can help assess (i) the causes of differences and similarities in model output, which is important for interpreting the results for policy‐making and (ii) the linkages, feedbacks, and trade‐offs between different systems and impacts (e.g., economic and natural), which is key to a more comprehensive understanding of the impacts of biomass supply and demand. But, full consistency or integration in assumptions, structure, solution algorithms, dynamics and feedbacks can be difficult to achieve. And, if it is done, it frequently implies a trade‐off in terms of resolution (spatial, temporal, and structural) and/or computation. Three key research areas are selected to illustrate how model collaboration can provide additional ways for tackling some of the shortcomings and uncertainties in the assessment of biomass supply and demand and their impacts. These research areas are livestock production, agricultural residues, and greenhouse gas emissions from land‐use change. Describing how model collaboration might look like in these examples, we show how improved model collaboration can strengthen our ability to project biomass supply, demand, and impacts. This in turn can aid in improving the information for policy‐makers and in taking better‐informed decisions.     

Labor Embodied in Trade

Global production chains carry environmental and socioeconomic impacts embodied in each traded good and service. Even though labor and energy productivities tend to be higher for domestic production in high‐income countries than those in emerging economies, this difference is significantly reduced for consumption, when including imported products to satisfy national demand. The analysis of socioeconomic and environmental aspects embodied in consumption can shed a light on the real level of productivity of an economy, as well as the effects of rising imports and offshoring. This research introduces a consumption‐based metric for productivity, in which we evaluate the loss of productivity of developed nations resulting from imports from less‐developed economies and offshoring of labor‐intensive production. We measure the labor, energy, and greenhouse gas emissions footprints in the European Union's trade with the rest of the world through a multiregional input‐output model. We confirm that the labor footprint of European imports is significantly higher than the one of exports, mainly from low‐skilled, labor‐intensive primary sectors. A high share of labor embodied in exports is commonly associated with low energy productivities in domestic industries. Hence, this reconfirms that the offshoring of production to cheaper and low‐skilled, labor‐abundant countries offsets, or even reverts, energy efficiency gains and climate‐change mitigation actions in developed countries.     

Life cycle greenhouse gas emissions of furniture and bioenergy production from oil palm trunks

The palm oil industry constantly attempts to increase the sustainability along the entire palm oil value chain. One important strategy is to utilize all co‐products. Oil palm trunks, which become available upon replanting of existing plantations, represent an important and increasing flow of underexploited biomass. In recent years, innovative technologies are emerging to use them for producing furniture or plywood or providing bioenergy. We assessed the life cycle greenhouse gas emissions of such products and the greenhouse gas emission savings due to replaced alternative products. Although challenging material properties result in a relatively high energy demand and related greenhouse gas emissions in the oil palm wood processing, substantial reductions in greenhouse gas emissions can arise from producing furniture or bioenergy from oil palm trunks, especially if the process energy demand is met by the energy recovery from oil palm wood‐processing residues.     

The greenhouse gas abatement potential of productivity improving measures applied to cattle systems in a developing region

Developing countries are experiencing an increase in total demand for livestock commodities, as populations and per capita demands increase. Increased production is therefore required to meet this demand and maintain food security. Production increases will lead to proportionate increases in greenhouse gas (GHG) emissions unless offset by reductions in the emissions intensity (Ei) (i.e. the amount of GHG emitted per kg of commodity produced) of livestock production. It is therefore important to identify measures that can increase production whilst reducing Ei cost-effectively. This paper seeks to do this for smallholder agro-pastoral cattle systems in Senegal; ranging from low input to semi-intensified, they are representative of a large proportion of the national cattle production. Specifically, it identifies a shortlist of mitigation measures with potential for application to the various herd systems and estimates their GHG emissions abatement potential (using the Global Livestock Environmental Assessment Model) and cost-effectiveness. Limitations and future requirements are identified and discussed. This paper demonstrates that the Ei of meat and milk from livestock systems in a developing region can be reduced through measures that would also benefit food security, many of which are likely to be cost-beneficial. The ability to make such quantification can assist future sustainable development efforts.     

Quantifying GHG emissions enabled by capital and labor: Economic and gender inequalities in France

Many studies have investigated the carbon footprint of households. They rely on consumption-based responsibility and focus on how many emissions are embodied in a product. Here we open a new field by discussing the emissions that individuals enable by providing labor and capital to companies, using the framework of income-based (downstream) responsibility. This perspective focuses on the emissions enabled by providing inputs to production processes, and is relevant for discussion of sustainable work and the carbon impact of investment and financial portfolios. We compute the downstream carbon intensity of primary inputs for 35 industries in France using the multi-regional input–output database EXIOBASE. We provide a detailed picture of enabled emissions, disaggregating those by industry and primary inputs. On average, capital inputs are more carbon intensive than labor inputs. Finally, we couple downstream carbon intensities with an extensive national survey on wages to obtain a distribution of the income-based emissions of employees. Income-based emissions are much more unequally distributed than wages due to the huge variability of carbon intensity across industries: a truck driver enables far more emissions than a social-care worker. Inequalities in emissions do not strongly interact with economic inequality. Yet they are gendered because women work disproportionately in low-carbon-intensive industries such as healthcare. As a result, women contribute less to GHG emissions than their wage share would seem to indicate.