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Summary Recent years have seen increasing interest in life cycle greenhouse gas emissions accounting, also known as carbon footprinting, due to drivers such as transportation fuels policy and climate-related eco-labels, sometimes called carbon labels. However, it remains unclear whether applications of greenhouse gas accounting, such as carbon labels, are supportable given the level of precision that is possible with current methodology and data. The goal of this work is to further the understanding of quantitative uncertainty assessment in carbon footprinting through a case study of a rackmount electronic server. Production phase uncertainty was found to be moderate (±15%), though with a high likelihood of being significantly underestimated given the limitations in available data for assessing uncertainty associated with temporal variability and technological specificity. Individual components or subassemblies showed varying levels of uncertainty due to differences in parameter uncertainty (i.e., agreement between data sets) and variability between production or use regions. The use phase displayed a considerably higher uncertainty (±50%) than production due to uncertainty in the useful lifetime of the server, variability in electricity mixes in different market regions, and use profile uncertainty. Overall model uncertainty was found to be ±35% for the whole life cycle, a substantial amount given that the method is already being used to set policy and make comparative environmental product declarations. Future work should continue to combine the increasing volume of available data to ensure consistency and maximize the credibility of the methods of life cycle assessment (LCA) and carbon footprinting. However, for some energy-using products it may make more sense to increase focus on energy efficiency and use phase emissions reductions rather than attempting to quantify and reduce the uncertainty of the relatively small production phase.

The growth of international trade is increasing the separation between the location of consumption and the location of production and emissions. As a consequence of this growth, GHG emissions repor...

In this paper we develop a model which approximates the upstream supply chains for embodied transportation in products. The sector with the largest embodied freight transportation in consumption is petroleum products followed by government services, construction, and food products. Overall, pipeline contributes 7% to the total embodied freight movement per sector, air transport is generally under 1%, water is 5%, and rail and truck transportation are the most dominant modes (14% each) for domestic freight transportation for the average sector. International water is the largest mode (60%) even compared to domestic modes, and international air contributes less than 1%.

Despite the emergence of regional climate policies, growth in global CO 2 emissions has remained strong. From 1990 to 2008 CO 2 emissions in developed countries (defined as countries with emission-reduction commitments in the Kyoto Protocol, Annex B) have stabilized, but emissions in developing countries (non-Annex B) have doubled. Some studies suggest that the stabilization of emissions in developed countries was partially because of growing imports from developing countries. To quantify the growth in emission transfers via international trade, we developed a trade-linked global database for CO 2 emissions covering 113 countries and 57 economic sectors from 1990 to 2008. We find that the emissions from the production of traded goods and services have increased from 4.3 Gt CO 2 in 1990 (20% of global emissions) to 7.8 Gt CO 2 in 2008 (26%). Most developed countries have increased their consumption-based emissions faster than their territorial emissions, and non–energy-intensive manufacturing had a key role in the emission transfers. The net emission transfers via international trade from developing to developed countries increased from 0.4 Gt CO 2 in 1990 to 1.6 Gt CO 2 in 2008, which exceeds the Kyoto Protocol emission reductions. Our results indicate that international trade is a significant factor in explaining the change in emissions in many countries, from both a production and consumption perspective. We suggest that countries monitor emission transfers via international trade, in addition to territorial emissions, to ensure progress toward stabilization of global greenhouse gas emissions.

Automobile air emissions are a well-recognized problem and have been subject to considerable regulation. An increasing concern for greenhouse gas emissions draws additional considerations to the externalities of personal vehicle travel. This paper provides estimates of the costs for automobile air emissions for 86 U.S. metropolitan areas based on county-specific external air emission morbidity, mortality, and environmental costs. Total air emission costs in the urban areas are estimated to be $145 million/day, with Los Angeles, California, and New York City (each $23 million per day) having the highest totals. These external costs average $0.64 per day per person and $0.03 per vehicle mile traveled. Total air emission cost solely due to traffic congestion for the same 86 U.S. metropolitan areas was also estimated to be $24 million per day. These estimates are compared with others in the literature and are found to be generally consistent. These external automobile air emission costs are important for social benefit and cost assessment of transportation measures to reduce vehicle use. However, this study does not include any abatement costs associated with automobile emission controls or government investments to reduce emissions such as traffic signal setting.

Summary The impacts of information and communications technology (ICT) on the environment have been a rich area for research in recent years. A prime example is the continuing rise of digital music delivery, which has obvious potential for reducing the energy and environmental impacts of producing and delivering music to final consumers. This study assesses the energy and carbon dioxide (CO2) emissions associated with several alternative methods for delivering one album of music to a final customer, either through traditional retail or e-commerce sales of compact discs or through a digital download service. We analyze a set of six (three compact disc and three digital download) scenarios for the delivery of one music album from the recording stage to the consumer's home in either CD or digital form. We find that despite the increased energy and emissions associated with Internet data flows, purchasing music digitally reduces the energy and carbon dioxide (CO2) emissions associated with delivering music to customers by between 40% and 80% from the best-case physical CD delivery, depending on whether a customer then burns the files to CD. Despite the dominance of the digital music delivery method, however, there are scenarios by which digital music performs less well, and these scenarios are explored. We suggest future areas of research, including alternative digital media services, such as subscription and streaming systems, for which Internet energy usage may be larger than for direct downloads.

Carbon Border Tax Adjustments (BTAs) are a politically popular strategy for avoiding competitive disadvantage problems when a country implements a unilateral climate change policy. A BTA taxes carbon embodied in imported goods in order to protect domestic industry and motivate other countries to implement climate change policy. To estimate the effectiveness of a BTA, is it is necessary to know which products are covered, where they were originally produced and ultimately exported from, and how the covered amount compares to total production in foreign countries. Using a scrap-adjusted, mixed-unit input-output model in conjunction with a multiregional input-output model, this analysis evaluates the effectiveness of BTAs for the case study of U.S. steel imports. Most imported steel by mass is embedded in finished products (60%), and 30% of that steel is produced in a different country than the one from which the final good is exported. Given the magnitudes involved and complexities of global supply chains, a BTA that protects domestic industry will be a challenge to implement. We propose a logistically feasible BTA structure that minimizes the information burden while still accounting for these complexities. However, the amount of steel imported to the U.S. is negligible (5%) compared to foreign production in BTA-eligible countries and is unlikely to motivate affected countries to impose an emissions reduction policy.

The generation and distribution of electricity comprises nearly 40% of U.S. CO(2), emissions, as well as large shares of SO(2), NO(x), small particulates, and other toxins. Thus, correctly accounting for these electricity-related environmental releases is of great importance in life cycle assessment of products and processes. Unfortunately, there is no agreed-upon protocol for accounting for the environmental emissions associated with electricity, as well as significant uncertainty in the estimates. Here, we explore the limits of current knowledge about grid electricity in LCA and carbon footprinting for the U.S. electrical grid, and show that differences in standards, protocols, and reporting organizations can lead to important differences in estimates of CO(2) SO(2), and NO(x) emissions factors. We find a considerable divergence in published values for grid emissions factor in the U.S. We discuss the implications of this divergence and list recommendations for a standardized approach to accounting for air pollution emissions in life cycle assessment and policy analyses in a world with incomplete and uncertain information.

Summary Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input–output (I-O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom-up process model can be estimated via a top-down approach such as the economic I-O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long-term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method.

In developing a standardised approach for companies to inventory greenhouse gas (GHG) emissions along their value chains, key challenges identified by stakeholders and technical experts include: which emissions sources a company should include in their inventory and how to calculate them, what constitutes a full list of indirect supply chain activities, and how to determine which activities from such a list are significant by application of a cut-off threshold. Using GHG accounting based on input–output models from Australia and the United States, this work presents specific case study examples and general results for broad industry sectors in both economies to address the development of a complete upstream carbon footprint for screening purposes. This is followed by an analysis of the issues surrounding application of cut-off thresholds and the relationship with system capture rate and efforts in carbon footprint analysis. This knowledge can inform decision makers about where to expend effort in gaining ...

On March 10, 2009, the US Environmental Protection Agency (EPA) proposed a new rule, Mandatory Reporting of Greenhouse Gases. When final, the rule would compel most large sources of greenhouse gases (GHGs) to report their emissions to EPA as well as fossil fuel suppliers and vehicle engine manufacturers to report their fuel sales and engine emissions rates, respectively. We suggest a number of improvements to the rule that would enhance compatibility with expected future climate legislation and enable a broader range of policies and analysis: (1) lower the threshold for reporting to a level more consistent with expected future legislation, (2) require reporting of electricity use along with direct emissions, (3) require reporting of emissions per unit output for a small number of selected sectors, (4) include a system of identifying corporate ownership of reporting facilities, and (5) identify a path toward coverage for sectors that were left out of the proposal due to underdeveloped reporting protocols.

The steadily increasing focus on energy production and consumption has led to growing research attention to patterns of energy use within economies. Of particular interest has been comparing the driving forces of increasing efficiency and economic structural change. Input–output analysis (IOA) and decomposition analysis have become critical tools for performing such analyses. This study analyzes aggregate energy use in the United States in 1997 and 2002 to discover the causes of changing energy usage and flows. Results show that rising population and household consumption acted to drive up energy demand, but this driving force was offset by considerable structural change within the economy, particularly related to a quickly increasing trade deficit in manufacturing goods. Thus, while total energy intensity, the ratio of energy use to economic output, declined by approximately 12% between 1997 and 2002, changes in the structure of the economy explain this drop more than increased energy efficiency. The level of aggregation at which decomposition analyses are run was identified as a crucially sensitive parameter for the determination of structural change, and future studies should specifically address the amount of detail necessary to adequately measure changes in economic structure.

Significant recent attention, in both research and policy realms, has been given to the intersection of international trade and global climate change. Trade presents challenges to climate policy through carbon leakage and competitiveness concerns, but also potential solutions through the use of cooperative trade agreements, technology transfer, or carbon tariffs against recalcitrant nations. This study examines how trade may affect climate policy in the US and specifically examines the use of carbon tariffs as suggested by recent bills before the US Congress. We argue that even if such actions are legal at the World Trade Organization, they are probably not necessary to protect industrial competitiveness in the traditional sense, could cover only a small proportion of total embodied emissions in trade, and may in fact be counterproductive at a moment when global cooperation is desperately needed. While political agreement may necessitate at least the threat of carbon tariffs, cooperative agreements such as global sectoral agreements, technology sharing, etc. could be more productive in the short term.

China's energy consumption doubled within the first 25 years of economic reforms initiated at the end of the 1970s, and doubled again in the past 5 years. It has resulted of a threefold CO2 emissions increase since early of 1980s. China's heavy reliance on coal will make it the largest emitter of CO2 in the world. By combining structural decomposition and input–output analysis we seek to assess the driving forces of China's CO2 emissions from 1980 to 2030. In our reference scenario, production-related CO2 emissions will increase another three times by 2030. Household consumption, capital investment and growth in exports will largely drive the increase in CO2 emissions. Efficiency gains will be partially offset the projected increases in consumption, but our scenarios show that this will not be sufficient if China's consumption patterns converge to current US levels. Relying on efficiency improvements alone will not stabilize China's future emissions. Our scenarios show that even extremely optimistic assumptions of widespread installation of carbon dioxide capture and storage will only slow the increase in CO2 emissions.

Within 5 years, China's CO 2 emissions have nearly doubled, and China may already be the world's largest emitter of CO 2 . Evidence suggests that exports could be a main cause for the rise in Chinese CO 2 emissions; however, no systematic study has analyzed this issue, especially over time. We find that in 2005, around one-third of Chinese emissions (1700 Mt CO 2 ) were due to production of exports, and this proportion has risen from 12% (230 Mt) in 1987 and only 21% (760 Mt) as recently as 2002. It is likely that consumption in the developed world is driving this trend. A majority of these emissions have largely escaped the scrutiny of arguments over “carbon leakage” due to the current, narrow definition of leakage. Climate policies which would make the developed world responsible for China's export emissions have both benefits and costs, and must be carefully designed to achieve political consensus and equity. Whoever is responsible for these emissions, China's rapidly expanding infrastructure and inefficient coal-powered electricity system need urgent attention.

Because of increasing concern about global climate change and carbon emissions as a causal factor, many companies and organizations are pursuing "carbon footprint" projects to estimate their own contributions to global climate change. Protocol definitions from carbon registries help organizations analyze their footprints. The scope of these protocols varies but generally suggests estimating only direct emissions and emissions from purchased energy, with less focus on supply chain emissions. In contrast approaches based on comprehensive environmental life-cycle assessment methods are available to track total emissions across the entire supply chain, and experience suggests that following narrowly defined estimation protocols will generally lead to large underestimates of carbon emissions for providing products and services. Direct emissions from an industry are, on average, only 14% of the total supply chain carbon emissions (often called Tier 1 emissions), and direct emissions plus industry energy inputs are, on average, only 26% of the total supply chain emissions (often called Tier 1 and 2 emissions). Without a full knowledge of their footprints, firms will be unable to pursue the most cost-effective carbon mitigation strategies. We suggest that firms use the screening-level analysis described here to set the bounds of their footprinting strategy to ensure that they do not ignore large sources of environmental effects across their supply chains. Such information can help firms pursue carbon and environmental emission mitigation projects not only within their own plants but also across their supply chain.

Analysis of household consumption and its environmental impact remains one of the most important topics in sustainability research. Nevertheless, much past and recent work has focused on domestic national averages, neglecting both the growing importance of international trade on household carbon footprint and the variation between households of different income levels and demographics. Using consumer expenditure surveys and multi-country life cycle assessment techniques, this paper analyzes the global and distributional aspects of American household carbon footprint. We find that due to recently increased international trade, 30% of total US household CO 2 impact in 2004 occurred outside the US. Further, households vary considerably in their CO 2 responsibilities: at least a factor of ten difference exists between low and high-impact households, with total household income and expenditure being the best predictors of both domestic and international portions of the total CO 2 impact. The global location of emissions, which cannot be calculated using standard input–output analysis, and the variation of household impacts with income, have important ramifications for polices designed to lower consumer impacts on climate change, such as carbon taxes. The effectiveness and fairness of such policies hinges on a proper understanding of how income distributions, rebound effects, and international trade affect them.

Despite significant recent public concern and media attention to the environmental impacts of food, few studies in the United States have systematically compared the life-cycle greenhouse gas (GHG) emissions associated with food production against long-distance distribution, aka "food-miles." We find that although food is transported long distances in general (1640 km delivery and 6760 km life-cycle supply chain on average) the GHG emissions associated with food are dominated by the production phase, contributing 83% of the average U.S. household's 8.1 t CO2e/yr footprint for food consumption. Transportation as a whole represents only 11% of life-cycle GHG emissions, and final delivery from producer to retail contributes only 4%. Different food groups exhibit a large range in GHG-intensity; on average, red meat is around 150% more GHG-intensive than chicken or fish. Thus, we suggest that dietary shift can be a more effective means of lowering an average household's food-related climate footprint than "buying local." Shifting less than one day per week's worth of calories from red meat and dairy products to chicken, fish, eggs, or a vegetable-based diet achieves more GHG reduction than buying all locally sourced food.

Significant recent attention has been given to quantifying the environmental impacts of international trade. However, the United States, despite being the world's largest emitter of greenhouse gases and having large recent growth in international trade, has seen little analysis. This work uses a multi-country input-output model of the U.S. and its seven largest trading partners (Canada, China, Mexico, Japan, Germany, the UK, and Korea) to analyze the environmental effects of changes to U.S. trade structure and volume from 1997 to 2004. It is shown that increased import volume and shifting trade patterns during this time period led to a large increase in the U.S.' embodied emissions in trade (EET) for CO2, SO2, and NO(x). Methodological uncertainties, especially related to uncertainties of international currency conversion, lead to large differences in estimation of the total EET, but we estimate that the overall embodied CO2 in U.S. imports has grown from between 0.5 and 0.8 Gt of CO2 in 1997 to between 0.8 and 1.8 Gt of CO2 in 2004, representing between 9-14% and 13-30% of U.S. (2-4% to 3-7% of global) CO2 emissions in 1997 and 2004, respectively.

The recent increase in the production of natural gas from shale deposits has significantly changed energy outlooks in both the US and world. Shale gas may have important climate benefits if it displaces more carbon-intensive oil or coal, but recent attention has discussed the potential for upstream methane emissions to counteract this reduced combustion greenhouse gas emissions. We examine six recent studies to produce a Monte Carlo uncertainty analysis of the carbon footprint of both shale and conventional natural gas production. The results show that the most likely upstream carbon footprints of these types of natural gas production are largely similar, with overlapping 95% uncertainty ranges of 11.0-21.0 g CO(2)e/MJ(LHV) for shale gas and 12.4-19.5 g CO(2)e/MJ(LHV) for conventional gas. However, because this upstream footprint represents less than 25% of the total carbon footprint of gas, the efficiency of producing heat, electricity, transportation services, or other function is of equal or greater importance when identifying emission reduction opportunities. Better data are needed to reduce the uncertainty in natural gas's carbon footprint, but understanding system-level climate impacts of shale gas, through shifts in national and global energy markets, may be more important and requires more detailed energy and economic systems assessments.

China's annual CO(2) emissions grew by around 4 billion tonnes between 1992 and 2007. More than 70% of this increase occurred between 2002 and 2007. While growing export demand contributed more than 50% to the CO(2) emission growth between 2002 and 2005, capital investments have been responsible for 61% of emission growth in China between 2005 and 2007. We use structural decomposition analysis to identify the drivers for China's emission growth between 1992 and 2007, with special focus on the period 2002 to 2007 when growth was most rapid. In contrast to previous analysis, we find that efficiency improvements have largely offset additional CO(2) emissions from increased final consumption between 2002 and 2007. The strong increases in emissions growth between 2002 and 2007 are instead explained by structural change in China's economy, which has newly emerged as the third major emission driver. This structural change is mainly the result of capital investments, in particular, the growing prominence of construction services and their carbon intensive supply chain. By closing the model for capital investment, we can now show that the majority of emissions embodied in capital investment are utilized for domestic household and government consumption (35-49% and 19-36%, respectively) with smaller amounts for the production of exports (21-31%). Urbanization and the associated changes in lifestyle are shown to be more important than other socio-demographic drivers like the decreasing household size or growing population. We argue that mitigation efforts will depend on the future development of these key drivers, particularly capital investments which dictate future mitigation costs.

As populations and demands for land-intensive products, e.g., cattle and biofuels, increase the need to understand the relationship between land use and consumption grows. This paper develops a production-based inventory of land use (i.e., the land used to produce goods) in the U.S. With this inventory an input-output analysis is used to create a consumption-based inventory of land use. This allows for exploration of links between land used in production to the consumption of particular goods. For example, it is possible to estimate the amount of cropland embodied in processed foods or healthcare services. As would be expected, agricultural and forestry industries are the largest users of land in the production-based inventory. Similarly, we find that processed foods and forest products are the largest users of land in the consumption-based inventory. Somewhat less expectedly this work finds that the majority of manufacturing and service industries, not typically associated with land use, require substantial amounts of land to produce output due to the purchase of food and other agricultural and wood-based products in the supply chain. The quantitative land use results of this analysis could be integrated with qualitative metrics such as weighting schemes designed to reflect environmental impact or life cycle impact assessment methods.

There is growing need for effective and efficient environmental assessment tools for information technology (IT) products. This paper presents a streamlined life cycle analysis (LCA) methodology using a screening and triage approach. The methodology is applied to the case study of liquid crystal displays (LCDs). Global warming potential uncertainty is reduced by identifying and resolving uncertainty around key drivers of impact. The resolution of impact continues until a meaningful level of reduction of uncertainty is achieved, such as the ability to discriminate one class of LCD from another.

We expect this study to mark the beginning of a new field of study related to coordinating actual consumer data flows to create dynamic and interactive visualizations. This work will also contribute to research relating impacts from overall and individual product transportation.

This model estimates the ton-km required for each sector in the US economy which is important in understanding freight movement, modal resiliency, the relative dependence on transportation and transportation choices for various products and services. Relating this estimated freight movement to energy requirements and greenhouse gas emissions may lead to more effective policies in reducing the freight transportation emissions.

Several pressures have led to unprecedented corporate interest in “carbon footprinting” or life cycle assessment (LCA) of products. These pressures include historically high energy prices, climate change regulation, corporate sustainability efforts, and announcements from several major retailers that environmental data will be required from suppliers. There are significant challenges in standardizing such calculations and several proposed standards include those from the British Standards Institute, the International Standards Organization, and the World Resources Institute/World Business Council on Sustainable Development [1, 2]. This work discusses the particular challenges relevant to the information technologies (IT) industry's ongoing investigation into the environmental impact of their products. IT products are complex and experience high turnover both in their manufacturing and assembly process flows as well as the supply chains used to procure materials and components. Often the results of quantifying environmental impacts are dominated by significant uncertainty and variability in the calculation of footprints, particularly for complicated products with large supplier networks. The existence of uncertainty is undisputed, and yet efforts to quantify uncertainty and variability in carbon footprints and life cycle assessments remain nascent at best. This research helps elucidate the data and methodological challenges in assessing uncertainties in the carbon footprinting of laptop and desktop computers.

Companies are increasingly estimating and reporting their greenhouse gas emissions (GHGs) for voluntary and mandatory purposes. This paper includes a review of the quality of company GHG reporting for the global telecommunications sector. We find that company emissions vary significantly, from 3 metric tons CO 2 equivalent per million dollars operating revenue (MTCO 2 e/$M) to 215 MTCO 2 e/$M. We find that company reported emissions can also vary significantly annually (over 50% in some cases). Some of this variance is due to boundary issues, exclusion of in-scope emissions, unit conversion issues, and differences in electricity GHG intensity. We also find that focusing on Scope 1 and Scope 2 emissions may distort a company's GHG estimates by ignoring Scope 3 emissions, which are likely a significant part of its overall GHG footprint. We end by offering recommendations on improving reporting methods.

Many organizations look to carbon footprint protocols for guidance on measuring their greenhouse gas emissions, or carbon footprint. Existing protocols generally require estimation of direct emissions (Scope 1) and emissions from direct purchases of energy (Scope 2), but focus less on indirect emissions upstream and downstream of the supply chain (optional Scope 3). Because on average more than 75% of an industry sector's carbon footprint is attributed to Scope 3 sources, better knowledge of Scope 3 footprints can help organizations pursue emissions mitigation projects not just within their own plants but also across their supply chain. In this work, Scope 3 footprints of U.S. economic sectors are categorized using an Economic Input-Output Life Cycle Assessment (EIO-LCA) model to identify upstream emission sources that are likely to contribute significantly to different sectors' footprints. The portions of the upstream footprint captured by the sector's top-10 upstream suppliers are estimated at 3 different levels of specificity: general economy-wide, industry specific, and sector specific. The results show that enterprises can capture a large portion of their total upstream carbon footprint by collecting full emissions information from only a handful of direct suppliers, and Scope 3 footprint capture rates can be improved considerably by sector-specific categorization. Employee commuting and air transportation may be more important (7%-30%) for the services industries, but should not be a focus of detailed Scope 3 footprint estimates for the manufacturing industries (

Corporations and institutions, including the electronics manufacturing and computer services sectors have become concerned with their impacts on climate change and are participating in carbon footprint assessment and climate management discussions. Existing carbon footprint protocols classify carbon footprint into tiered “Scopes”: direct emissions as “Scope 1”, emissions from direct purchased energy as “Scope 2”, and all other indirect emissions as optional “Scope 3.” Because Scopes 1 and 2 footprints are generally less than 25% of the total direct and upstream footprint for a vast majority of businesses, Scope 3 emissions should not be ignored as knowledge of them can help inform more holistic approaches to address life cycle footprint across the supply chain. This research uses input-output life cycle assessment methods to conduct a “scoping analysis” that characterizes the carbon footprint profiles of 8 electronics manufacturing and computer services sectors. The results show that there are significant variations in the portions of total analyzed footprint captured by each footprint Scope among this sector group. Most of the footprints for the electronics manufacturing sectors do not come from their Scope 1 emissions, but from the embodied emissions in the supplies of parts, components, chemicals, and materials. Purchases of food, air transportation, and hotel accommodation from employees traveling to customer locations are found to be the largest sources of upstream Scope 3 footprint for computer system design services sector. The results presented in this work are intended to inform footprinting entities and companies of the potential Scope 3 subcategories to focus their footprint efforts.

High-brightness light-emitting diodes (LEDs) form the basis for solid-state lighting (SSL) systems. SSL systems have the potential to reduce electricity consumption of lighting systems as they are much more efficient than current lighting technologies. One concern is that the full life-cycle energy requirements of SSL systems, including the production of the materials and LED components, may negate any savings during the use phase. As a start to estimating the life-cycle energy requirements of SSL systems, we present an estimate for the manufacturing energy consumption of high-brightness light-emitting diodes. Results are based on full-scale, research-scale, and laboratory-scale equipment energy use data, and data from logic chip production processes. Energy consumption estimates for wafer production are 15 kWh to 60 kWh (approximately 1,000 LEDs).

The generation and distribution of electric power is enormously important in both economic and environmental terms. However, despite the obvious importance of electricity for life cycle assessment and policy analysis, accounting for the environmental emissions associated with electricity remains an uncertain task. In this analysis we examine the different methods available for electricity greenhouse gas emissions accounting, and show that different standards, protocols, and reporting organizations can lead to considerably different estimates of emissions associated with purchased electricity. We discuss the implications of this uncertainty and list recommendations for electricity emissions accounting in the world of incomplete and uncertain information.

[1] China's economy has been growing at an accelerated rate from 2002 to 2005 and with it China's carbon emissions. It is easier to understand the growth in China's carbon emissions by considering which consumption activities - households and government, capital investments, and international trade - drive Chinese production and hence emissions. This paper adopts structural decomposition analysis, a macro-economic approach using data from national statistical offices, to investigate the drivers of China's recent CO2 emissions surge. The speed of efficiency gains in production sectors cannot cope with the growth in emissions due to growth in final consumption and associated production processes. More specifically, Chinese export production is responsible for one-half of the emission increase. Capital formation contributes to one-third of the emission increase. A fast growing component is carbon emissions related to consumption of services by urban households and governmental institutions, which are responsible for most of the remaining emissions.

Due to increased international trade over the past decade, the global carbon footprint of the US has been expanding. Electronics are a major driver in this trend, as they are both heavily imported and energy intensive. We estimate that the embodied emissions in electronic goods imported to the US has increased from ~170 Mmt CO2 in 1997 to ~470 Mmt CO2 in 2004, primarily driven by increased consumption of computers and peripherals, audio/video equipment, wireless communications equipment, and various components. Two usually ignored portions of the supply chain, international transport and wholesaling/retailing, represent further emissions of 4-10 Mmt CO2 and ~33 Mmt CO2 respectively, showing the importance of including them in life cycle inventories of electronics.

Chemical speciation modeling is a vital tool for assessing the bioavailability of inorganic species, yet significant uncertainties in thermodynamic parameters and model form limit its potential for decision-making. In this paper we present a novel method for the quantification of thermodynamic parameter uncertainty and ionic strength correction model uncertainty using Bayesian Markov Chain Monte Carlo (MCMC) estimation methods. These methods allow for the inclusion of correlation modeling, which has not been present in previous work. The MCMC simulations are used to model a natural river water to determine the uncertainty in the calculated environmental speciation of ethylenediamenetetraacetate, a chelating agent that has attracted considerable environmental interest. The results indicate that incorporating correlation among related thermodynamic parameters into the uncertainty model is necessary to correctly quantify the overall system uncertainty. This result indicates the superiority of MCMC estimation methods overtraditional Monte Carlo methods when available data are used to estimate parameter uncertainty in systems with closely related model parameters.

In a recent Policy Forum, J. Liu reviewed “China's road to sustainability” (2 April, p. [50][1]). Liu focused on population growth and an increase in the number of households, but he failed to adequately address the most important socioeconomic driver behind environmental degradation in China

Despite their political popularity, carbon tariffs will be next to impossible to implement effectively, and as such will do little to solve the climate problem.