The Energetic Metabolism of the European Union and the United States: Decadal Energy Input Time-Series with an Emphasis on Biomass

This article presents an assessment of energy inputs of the European Union (the 15 countries before the 2004 enlargement, abbreviated EU‐15) for the period 1970–2001 and the United States for 1980–2000. The data are based on an energy flow analysis (EFA) that evaluates socioeconomic energy flows in a way that is conceptually consistent with current materials flow analysis (MFA) methods. EFA allows assessment of the total amount of energy required by a national economy; it yields measures of the size of economic systems in biophysical units. In contrast to conventional energy balances, which only include technically used energy, EFA also accounts for socioeconomic inputs of biomass; that is, it also considers food, feed, wood and other materials of biological origin. The energy flow accounts presented in this article do not include embodied energy. Energy flow analyses are relevant for comparisons across modes of subsistence (e.g., agrarian and industrial society) and also to detect interrelations between energy utilization and land use. In the EU‐15, domestic energy consumption (DEC = apparent consumption = domestic extraction plus import minus export) grew from 60 exajoules per year (1 EJ = 10¹⁸ J) in 1970 to 79 EJ/yr in 2001, thus exceeding its territory's net primary production (NPP, a measure of the energy throughput of ecosystems). In the United States, DEC increased from 102 EJ/yr in 1980 to 125 EJ/yr in 2000 and was thus slightly smaller than its NPP. Taken together, the EU‐15 and the United States accounted for about 38% of global technical energy use, 31% of humanity's energetic metabolism, but only 10% of global terrestrial NPP and 11% of world population in the early 1990s. Per capita DEC of the United States is more than twice that of the EU‐15. Calculated according to EFA methods, energy input in the EU and the United States was between one‐fifth and one‐third above the corresponding value reported in conventional energy balances. The article discusses implications of these results for sustainability, as well as future research needs.     

The energy embodied in the first and second industrial revolutions

Understanding the nature of energy embodied in economies is essential to assessing their potential to grow or transform sustainably. As the first country to undergo industrialization, study of the United Kingdom during the Industrial Revolution is particularly important for understanding transformational processes. Historical accounts describe how exploitation of Britain's coal reserves supported the evolution of steel production, railways, and other industries; yet reconstructions of the UK's eighteenth/nineteenth century economy have found relatively small contributions from coal mining to economic growth. Here, economic input‐output models for 1841 and 1907 are used to calculate the coal embodied in capital investment, consumption, and exports. Most of the coal was embodied in consumption in 1841, with coal embodied in exports growing particularly fast by 1907. The coal embodied in capital was smaller, but the energy intensity of investment was about four times larger than the energy intensity of consumption. The coal embodied in building the capital stock, much of it used for production of materials such as iron, steel, and bricks, was important for economic growth and transformation. Using historical proxy data, it is estimated that ～1.1 billion imperial tons of coal (34,000 PJ) were used to build the UK's capital assets between 1760 and 1913. The conceptual model developed here helps to explain the role of energy in economic growth and is important to contemporary sustainable development. This article met the requirements for a gold – gold JIE data openness badge described at http://jie.click/badges .     

辽宁省能源消费与经济增长的灰色关联

我国能源消费与经济增长的矛盾日益突出.辽宁省是我国重工业基地和能源消耗大省,经济发展对能源依赖性强,能源供不应求的状态日益显著.为了深入了解辽宁省能源消费与经济增长的关系,提出科学的低碳发展建议,本文基于2000—2012年辽宁省能源消费与经济增长相关数据,应用灰色关联分析,分别对辽宁省能源消费产业和能源消费品种与经济增长的相关性进行实证分析.结果表明: 在各产业能源消费中,批发零售业和住宿餐饮业能源消费量很少,但与经济增长的关联程度最大,工业消费量最大,却与经济增长的关联度较弱;在能源消费品种中,石油和水电能源消费量与经济增长的灰色关联度显著,但煤炭能源消费量与经济增长的关联度不显著,表明煤炭的利用效率低.为实现低碳可持续发展,辽宁省应转变经济增长方式、调整产业结构、优化能源结构、提高能源利用效率,特别是应大力发展生产性服务业,推进清洁能源和可再生能源的开发.     

中国居民消费隐含的碳排放量变化的驱动因素

应用基于投入产出技术的生命周期评价(EIO-LCA)核算了1997、2000、2002、2005和2007年5a的中国居民消费隐含的二氧化碳排放量,发现其呈现增加趋势。2007年达到18.53亿t,相当于1997年的1.61倍,年平均增长4.89%. 其次采用结构分解分析(SDA)分析了碳排放效率变化、经济内在结构变迁、消费结构转变、人均消费水平变化、城市化进程和人口总量变化等六项因素对碳排放总量变化的驱动作用。研究发现碳排放效率因素和人均消费水平变化是驱动碳排放变化的两大主要力量,并且作用相反。碳排放效率的持续提高,很大程度上缓解了居民消费的隐含碳排放急剧增加的趋势,是减缓碳排放量的主要因素;而人均消费水平的迅速提高成为推动碳排放增加的主要力量,是推动碳排放增加的主要因素。     

An Urban Metabolism and Carbon Footprint Analysis of the Jing–Jin–Ji Regional Agglomeration

Urban energy metabolism includes processes for exploiting, transforming, and consuming energy, as well as processes for recycling by‐products and wastes. Embodied energy is the energy consumed during all of these activities, both directly and indirectly. Multiregional input‐output (MRIO) analysis can calculate the energy consumption embodied in flows among sectors for multiple cities or regions. Our goal was to address a problem apparent in previous research, which was insufficient attention to indirect energy flows. We combined MRIO analysis with ecological network analysis to calculate the embodied energy consumption and the energy‐related carbon footprints of five sectors in three regions that comprise the Jing‐Jin‐Ji agglomeration, using data from 2002 and 2007. Our analysis traced metabolic processes of sectors from the perspective of final consumption. Based on the embodied energy analysis, we quantified the indirect energy consumption implied in exchanges of sectors and its distribution and identified the relationships formed through the indirect consumption to analyze the roles of providers and receivers in the system. Results showed that the embodied energy consumption for the Jing‐Jin‐Ji region increased from 2002 to 2007 as a result of increased energy consumption in Tianjin and Hebei. Overall, consumption of Beijing decreased likely attributable to the fact that government policies relocated industries during this time in anticipation of the Olympic Games. The relationships among sectors changed: Beijing changed from a net exporter to an importer, whereas Hebei changed from a net importer of energy from Beijing to an exporter to Beijing, and Tianjin served as an importer in both years.     

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

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

A Metabolic Profile of Peru: An Application of Multi‐Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) to the Mining Sector's Exosomatic Energy Flows

The present Peru's metabolic profile study poses the specific question, What are the long‐term national energy system implications of the recent government‐supported growth of the mining sector? The question is addressed by analyzing interactions between human economic activity (in hours) and electricity input flows (in joules) in the mining sector of the Peruvian economy in 2000 and 2010, with a projection for 2020. The methodology is based on the multi‐scale integrated analysis of societal and ecosystem metabolism (MuSIASEM), which is an application of Georgescu‐Roegen's bioeconomics approach. Empirical results found for the national economy show: (1) the massive increase in size of the energy system, which is explained by exploitation of the Camisea natural gas (NG) reserves, and (2) the potential for establishing a carbon lock‐in in the electricity sector, owing to increasing construction of electricity plants based on NG as their primary energy source. Empirical results specific to the mining sector indicate: (1) the extremely high electricity metabolic rate of the mining sector (61.6 megajoules per hour in 2010), which was found to be 11 times the rate of electricity used per hour of human activity in the building and manufacturing sector in Peru, and (b) the potential increases in the proportion of electricity used in the mining sector (flow share), which could jeopardize the availability of high‐quality primary energy supplies for the rest of society. In light of these implications, it is argued that the Peruvian government's strong support for growth of the mining sector may have to be reconsidered.     

能源活动CO2排放不同核算方法比较和减排策略选择

能源活动CO₂排放是温室气体排放的最重要部分,这部分CO₂排放量的核算是温室气体清单编制和减排方案制定的关键和基础。采用直接法、电热终端法和隐含终端法核算了2009年中国能源消费的CO₂排放量,对不同核算法的CO₂排放部门分布、部门排放强度进行了比较,明确不同核算方法的差异和适用范围。采用电热终端法的核算结果定量分析了各产业部门和工业行业的经济增长和排放强度变化对中国能源活动CO₂排放增长的影响。结果表明,中国2009年隐含终端CO₂排放量为65.6亿t,略高于直接和电热终端CO₂排放量62.2亿t。3种核算方法的CO₂排放部门分布和排放强度有明显的差异:电、热力生产与供应业的直接排放占比为45.2%,而电热终端CO₂排放仅占4.5%;制造业的直接法、电热终端法和隐含终端法核算的CO₂排放占比分别为35.3% 、61.1%和65.5%,是终端能源消费CO₂排放最主要的部门;制造业、电热力生产与供应业和交通运输业的电热终端CO₂排放强度分别为2.166、1.72和1.622 t CO₂/万元GDP,是排放强度较高的部门。在产业部门中,制造业的色金属冶炼及压延加工业、非金属矿物制品业等5个行业以9.8%的经济增长贡献,排放了52.4%的CO₂,是产业结构调整、技术和工程减排的重点;服务业以7.2%的CO₂排放,贡献了38.4%的经济增长,应作为中国低碳经济优先发展的产业。     

Energy Efficiency and Structural Change in the Netherlands, 1980–1995

International agreement has been reached to reduce greenhouse gas emissions worldwide. One important way of decoupling CO₂ emissions from economic growth is by introducing technical measures to improve energy efficiency. In this article, we assess the influence of developments in energy efficiency and economic structure on the total primary energy consumption in the Netherlands over the period 1980– 1995. We find a distinct decoupling of the economic growth and energy consumption of 1.5% per year in the 15-year analysis period. We measure (technical) changes in energy efficiency by changes in the energy consumption per physical unit of production or activity. The aggregate rate of (technical) energy-efficiency improvement was 1.4% per year over the period 1980–1995. The use of physical production indicators makes it possible to measure energy-efficiency developments without detailed surveys at a very low level of aggregation. When we look at economic structural changes over this period, we find that (i) no substantial shift took place at the level of the economic sectors that we distinguish; (ii) the most energy intensive subsectors grew much faster than the total economy; and (iii) at the subsector level, on average, a sizable decoupling of physical production and value added occurred. We conclude that structural changes, that is, changes in the composition of the economy, did not lead to a net decrease in the energy intensity of the Netherlands over the period 1980–1995.     

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.     

Economy‐wide Material Flow Indicators on a Sectoral Level and Strategies for Decreasing Material Inputs of Sectors

The article presents a method for the calculation of selected economy‐wide material flow indicators (namely, direct material input [DMI] and raw material input [RMI]) for economic sectors. Whereas sectoral DMI was calculated using direct data from statistics, we applied a concept of total flows and a hybrid input‐output life cycle assessment method to calculate sectoral RMI. We calculated the indicators for the Czech Republic for 2000–2011. We argue that DMI of economic sectors can be used for policies aiming at decreasing the direct input of extracted raw materials, and imported raw materials and products, whereas sectoral RMI can be better used for justifying support for or weakening the role of individual sectors within the economy. High‐input material flows are associated in the Czech Republic with the extractive industries (agriculture and forestry, the mining of fossil fuels [FFs], other types of mining, and quarrying), with several manufacturing industries (manufacturing of beverages, basic metals, motor vehicles or electricity, and gas and steam supply) and with construction. Viable options for reducing inputs of agricultural biomass include changes in people's diet toward a lower amount of animal‐based food and a decrease in the wasting of food. For FFs, one should think of changing the structure of total primary energy supply toward cleaner gaseous and renewable energy sources, innovations in transportation systems, and improvements in overall energy efficiency. For metal ores, viable options include technological changes leading to smaller and lighter products, as well as consistent recycling and use of secondary metals.     

Avoiding investment in fossil fuel assets

Reducing greenhouse gas emissions requires a transformation of capital assets in the economy, especially those for energy supply. This paper explores the hypothesis that economically efficient decarbonization occurs when the demand for fossil fuels declines at the same rate as their capital assets depreciate. In theory this means that new investments in fossil fuel assets are avoided, but without incurring stranded assets. We examine the practicality of this hypothesis using a biophysical economic model of the US energy supply system, with an example focused on impacts of electric vehicles on the petroleum supply chain. We specifically address two questions: (1) What rate of market penetration for electric vehicles is necessary to avoid investments in the petroleum-related assets? (2) How do the costs of upstream capital assets change with the transformation to electric vehicles? High annual depreciation rates for oil refineries (δ = 9.47%) and assets for crude oil extraction (δ = 8.23%) have important impacts on results. To avoid new investment in oil refining assets through widespread electrification of light-duty vehicles, the vehicle stock would need to be transformed in just 4 or 5 years. Under most scenarios, some petroleum pipelines will likely become stranded assets due to their low rate of depreciation (δ = 2.48%). In some scenarios, additional investments in wind and solar power generation surpass oil and gas extraction for about 5 years during the transformation to electric vehicles. Once built, however, wind and solar capital assets last longer, as shown by their low rate of depreciation (δ = 3.26%).     

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.     

Material Flow and Spatial Data Analysis of the Petroleum Use to Carbon Dioxide (CO2) Emissions in Northeast China

This study investigated the petroleum consumption and petroleum‐related CO₂ emissions (PCOEs) in Northeast China at city level using material flow analysis (MFA) and spatial data analysis (SDA). The petroleum flows for the year 2014 were plotted, and then the spatial patterns, weighted mean centers (WMCs), and spatial autocorrelations of petroleum consumption and PCOEs were calculated, respectively. It was found that Northeast China is a petroleum exploitation‐processing‐export region in China; the total input of petroleum flows comprised two parts—exploitation (about 60%) and import (about 40%). About one third of the total product oil supply flowed into other provinces. In the consumption process, the product oil was dominated by two sectors: the industry sector (45.5%) and the transportation sector (31%). The rate of PCOEs was 36.69 million tonnes in the waste discharge process. Meanwhile, the WMCs of the petroleum consumption and the PCOEs were located in the south of Northeast China. The location of the petroleum pipelines was the factor shown to determine the spatial patterns of petroleum consumption and PCOEs and the hotspots were distributed along the petroleum pipeline, especially in the Circum‐Bohai Sea regions. Economic development in these regions shows a positive dependence on petroleum consumption and generates larger PCOEs. The findings obtained in this study could provide important decision‐making support to low‐carbon development in Northeast China.     

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.     

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.     

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.     

辽宁省能源消费和碳排放与经济增长的关系

在广泛收集资料的基础上,对辽宁省的能源利用效率、能源消费强度与经济增长的关系进行探索,其目的为辽宁省的节能与CO2减排及经济的快速发展提供科学依据。结果表明:辽宁整体单位GDP能耗高出全国水平52%—70%,第二产业单位GDP能耗是第三产业的5.67—8.41倍,第一产业的7.2—9.0倍;辽宁能源利用率只有全国平均水平的60%左右,第二产业能源利用效率只有第一产业的11.89%,第三产业的12.60%;GDP年增长速率大于能源消费量年增长速率,能源投入增加促进了国民生产总值的提高,但是经济增长并不是完全依赖能源消费的增长;能源消费量与经济增长的关系,呈现出"N型"曲线特征,随着GDP的增加,能源消费量出现反复上升和下降过程,辽宁省能源消费和经济增长关系没有达到长期的均衡性,尚处于非平衡的发展阶段。     

城市能源利用碳足迹分析——以厦门市为例

城市能源利用碳足迹分析综合考虑直接与间接碳排放,对于深度分析碳排放的本质过程、制定科学全面的碳减排计划具有重要意义。以厦门市为研究案例,应用碳足迹的混合分析方法,对厦门市2009年能源利用碳足迹进行了分析,除了包括传统研究中的城市能源终端利用产生的直接碳排放,还计算了跨界交通和城市主要消耗物质的内含能引起的间接碳排放。研究结果表明:(1)城市边界内的工业、交通、商业等部门的能源消耗产生的直接碳排放(即层次1和层次2)只占到总碳足迹的64%,而一直被忽略的跨界交通和城市主要消耗物质的内含能引起的间接碳排放(层次3)占到36%;(2)在直接碳排放中,工业部门的碳排放贡献率最大,占到直接碳排放的55%,其中化工行业带来的碳排放占到工业部门的25%;(3)在间接碳排放中,跨界交通引起的碳排放占间接碳排放的27%,其中长途道路运输贡献率最大,占跨界交通碳排放的38%;主要材料内含能碳排放占间接碳排的73%,其中燃料的内含能碳排放占总内含能的份额最大,达51%。;(4)从人均碳足迹角度比较,厦门市人均碳足迹和丹佛市的人均直接碳排(层次1+层次2)分别为5.74 t CO2e/人、18.9 t CO2e/人,包含3个层次的人均碳足迹分别为9.01 tCO2e/人、25.3 t CO2e/人,其中跨界交通引起的碳排放均占总碳足迹的10%左右,主要材料的内含能引起的碳排放分别占到总碳足迹的26%、15%;通过国内外典型城市不同层次碳足迹比较可见厦门还是相对低碳的,但有个显著的特点是主要消耗物质的内含碳排放比例较高,这在一定程度上说明了发展中国家城市消耗更多的基础材料,进一步证明了传统核算中忽略的第3层次碳排放核算与管理的重要性。     

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.