Biogenic Carbon and Temporary Storage Addressed with Dynamic Life Cycle Assessment

A growing tendency in policy making and carbon footprint estimation gives value to temporary carbon storage in biomass products or to delayed greenhouse gas (GHG) emissions. Some life cycle‐based methods, such as the British publicly available specification (PAS) 2050 or the recently published European Commission's International Reference Life Cycle Data System (ILCD) Handbook, address this issue. This article shows the importance of consistent consideration of biogenic carbon and timing of GHG emissions in life cycle assessment (LCA) and carbon footprint analysis. We use a fictitious case study assessing the life cycle of a wooden chair for four end‐of‐life scenarios to compare different approaches: traditional LCA with and without consideration of biogenic carbon, the PAS 2050 and ILCD Handbook methods, and a dynamic LCA approach. Reliable results require accounting for the timing of every GHG emission, including biogenic carbon flows, as soon as a benefit is given for temporarily storing carbon or delaying GHG emissions. The conclusions of a comparative LCA can change depending on the time horizon chosen for the analysis. The dynamic LCA approach allows for a consistent assessment of the impact, through time, of all GHG emissions (positive) and sequestration (negative). The dynamic LCA is also a valuable approach for decision makers who have to understand the sensitivity of the conclusions to the chosen time horizon.     

Corporate Carbon Performance Indicators

The dependency on carbon‐based materials and energy sources and the emission of greenhouse gases have been recognized as major problems of the 21st century. Companies are central to the effort to grapple with these issues due to the large material flows they process and their capabilities for technological innovation. It is important, on the one hand, to determine the individual stake companies have in these issues and, on the other, to measure companies' performance. Since the results of studies thus far have been ambiguous, we define four comprehensive and systematic corporate carbon performance indicators: (1) Carbon intensity is physically oriented and represents a company's carbon use in relation to a business metric. (2) Carbon dependency illustrates the change in physical carbon performance within a given time period. (3) Carbon exposure reveals the financial implications of using and emitting carbon. (4) Carbon risk estimates the change in financial implications of carbon usage within a given time period. On the basis of these general definitions, we specify the indicators for a standardized application that can support two important stakeholders in their decision making: policy makers, who can include such information when evaluating current climate policies and formulating future ones, and investors and financial institutions, which can compare companies with respect to their carbon performance and corresponding financial effects.     

The Carbon Footprint of Games Distribution

This research investigates the carbon footprint of the lifecycle of console games, using the example of PlayStation®3 distribution in the UK. We estimate total carbon equivalent emissions for an average 8.8‐gigabyte (GB) game based on data for 2010. The bulk of emissions are accounted for by game play, followed by production and distribution. Two delivery scenarios are compared: The first examines Blu‐ray discs (BDs) delivered by retail stores, and the second, games files downloaded over broadband Internet. Contrary to findings in previous research on music distribution, distribution of games by physical BDs results in lower greenhouse gas emissions than by Internet download. The estimated carbon emissions from downloading only fall definitively below that of BDs for games smaller than 1.3 GB. Sensitivity analysis indicates that as average game file sizes increase, and the energy intensity of the Internet falls, the file size at which BDs would result in lower emissions than downloads could shift either up‐ or downward over the next few years. Overall, the results appear to be broadly applicable to title games within the European Union (EU), and for larger‐than‐average sized games in the United States. Further research would be needed to confirm whether similar findings would apply in future years with changes in game size and Internet efficiency. The study findings serve to illustrate why it is not always true that digital distribution of media will have lower carbon emissions than distribution by physical means when file sizes are large.     

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

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

Impact of Power Generation Mix on Life Cycle Assessment and Carbon Footprint Greenhouse Gas Results

The mix of electricity consumed in any stage in the life cycle of a product, process, or industrial sector has a significant effect on the associated inventory of emissions and environmental impacts because of large differences in the power generation method used. Fossil‐fuel‐fired or nuclear‐centralized steam generators; large‐scale and small‐scale hydroelectric power; and renewable options, such as geothermal, wind, and solar power, each have a unique set of issues that can change the results of a life cycle assessment. This article shows greenhouse gas emissions estimates for electricity purchase for different scenarios using U.S. average electricity mix, state mixes, state mixes including imports, and a sector‐specific mix to show how different these results can be. We find that greenhouse gases for certain sectors and scenarios can change by more than 100%. Knowing this, practitioners should exercise caution or at least account for the uncertainty associated with mix choice.     

Life Cycle Assessment of Frozen Tilapia Fillets From Indonesian Lake‐Based and Pond‐Based Intensive Aquaculture Systems

We used life cycle assessment to evaluate a subset of the cradle‐to‐destination‐port environmental impacts associated with the production, processing, and transportation of frozen, packaged Indonesian tilapia (Oreochromis niloticus) fillets to ports in Chicago and Rotterdam. Specifically, we evaluated the cumulative energy use; biotic resource use; and global warming, acidifying, and eutrophying emissions at each life cycle stage and in aggregate. We identify the importance of least environmental cost feed sourcing for reducing supply chain environmental impacts. We also highlight the need for more effective nutrient cycling in intensive aquaculture. The environmental trade‐offs inherent in substituting technological inputs for ecosystem services in intensive pond‐based versus lake‐based production systems are discussed. We further call for more nuanced considerations of comparative environmental advantage in the production and interregional trade of food commodities than has been characteristic of historic food miles discussions. Significant opportunities exist for improving environmental performance in tilapia aquaculture. This product compares favorably, however, with several other fishery, aquaculture, and animal husbandry products, according to the suite of impact categories considered in this study.     

Defining (Urban) Producer and Consumer Sinks

This contribution was prompted by the article “Gross Direct and Embodied Carbon Sinks for Urban Inventories” by Mohareb and Kennedy published in this issue. The authors define two types of urban carbon sinks—direct and embodied—and discuss their relation to producer and consumer emissions (and sinks) accounting. This commentary continues that discussion by clarifying boundary considerations and definitions between producer and consumer sinks, and between direct and indirect sinks. Extending the notion of production‐ versus consumption‐based emissions accounting, a corollary for producer and consumer sinks can be drawn. Producer sinks would include direct sequestration through industrial and private activities occurring within a defined territory. Consumer sinks would refer to direct and indirect sequestration activities associated with the consumption of goods and services within the same territory, wherever that sequestration may occur. As with emissions accounting, in carbon sinks accounting I propose that the exact categorization depends on the perspective taken. Clear boundaries and well‐defined terminology—historically present in emissions accounting—are critical to this novel approach to sinks accounting.     

Data for the Carbon Footprinting of Rendering Operations

This article presents a tool and data for calculation of the carbon footprint of rendering operations in North America, quantifying Scope 1 (direct) and Scope 2 (indirect) greenhouse gas emissions. Scope 3 (life cycle) emissions are not included. According to the sample data, in one year an average‐size rendering plant in North America processes 100,000 tonnes (t) of meat by‐products, fallen animals, and restaurant grease and produces 40,000 t of marketable fats and proteins. A plant of this size emits directly about 20,000 t of carbon dioxide (CO₂), mostly by burning fuels to operate cookers that destroy pathogens, drive off moisture, and separate the fat and protein. Another 4,000 t of CO₂ is emitted by utility companies to provide electricity for the rendering process. These direct and indirect emissions are equivalent to about 30% of the CO₂ that would be released if all of the carbon in the rendered raw material were decomposed into CO₂.     

The Corruption Footprints of Nations

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

The Concept of City Carbon Maps: A Case Study of Melbourne,Australia

Cities are thought to be associated with most of humanity's consumption of natural resources and impacts on the environment. Cities not only constitute major centers of economic activity, knowledge, innovation, and governance—they are also said to be linked to approximately 70% to 80% of global carbon dioxide emissions. This makes cities primary agents of change in a resource‐ and carbon‐constraint world. In order to set meaningful targets, design successful policies, and implement effective mitigation strategies, it is important that greenhouse gas (GHG) emissions accounting for cities is accurate, comparable, comprehensive, and complete. Despite recent developments in the standardization of city GHG accounting, there is still a lack of consistent guidelines regarding out‐of‐boundary emissions, thus hampering efforts to identify mitigation priorities and responsibilities. We introduce a new conceptual framework—based on environmental input‐output analysis—that allows for a consistent and complete reconciliation of direct and indirect GHG emissions from a city. The “city carbon map” shows local, regional, national, and global origins and destinations of flows of embodied emissions. We test the carbon map concept by applying it to the greater metropolitan area of Melbourne, Australia. We discuss the results and limitations of the approach in the light of possible mitigation strategies and policies by different urban stakeholders.     

Gross Direct and Embodied Carbon Sinks for Urban Inventories

Cities and urban regions are undertaking efforts to quantify greenhouse (GHG) emissions from their jurisdictional boundaries. Although inventorying methodologies are beginning to standardize for GHG sources, carbon sequestration is generally not quantified. This article describes the methodology and quantification of gross urban carbon sinks. Sinks are categorized into direct and embodied sinks. Direct sinks generally incorporate natural process, such as humification in soils and photosynthetic biomass growth (in urban trees, perennial crops, and regional forests). Embodied sinks include activities associated with consumptive behavior that result in the import and/or storage of carbon, such as landfilling of waste, concrete construction, and utilization of durable wood products. Using methodologies based on the Intergovernmental Panel on Climate Change 2006 guidelines (for direct sinks) and peer‐reviewed literature (for embodied sinks), carbon sequestration for 2005 is calculated for the Greater Toronto Area. Direct sinks are found to be 317 kilotons of carbon (kt C), and are dominated by regional forest biomass. Embodied sinks are calculated to be 234 kt C based on one year's consumption, though a complete life cycle accounting of emissions would likely transform this sum from a carbon sink to a source. There is considerable uncertainty associated with the methodologies used, which could be addressed with city‐specific stock‐change measurements. Further options for enhancing carbon sink capacity within urban environments are explored, such as urban biomass growth and carbon capture and storage.     

Increasing Precision in Greenhouse Gas Accounting Using Real‐Time Emission Factors

For many companies, the greenhouse gas (GHG) emissions associated with their purchased and consumed electricity form one of the largest contributions to the GHG emissions that result from their activities. Currently, hourly variations in electricity grid emissions are not considered by standard GHG accounting protocols, which apply a national grid emission factor (EF), potentially resulting in erred estimates for the GHG emissions. In this study, a method is developed that calculates GHG emissions based on real‐time data, and it is shown that the use of hourly electricity grid EFs can significantly improve the accuracy of the GHG emissions that are attributed to the purchased and consumed electricity of a company. A model analysis for the electricity delivered to the Spanish grid in 2012 reveals that, for companies operating during the day, GHG emissions calculated by the real‐time method are estimated to be up to 5% higher (and in some special cases up to 9% higher) than the emissions calculated by the conventional method in which a national grid EF is applied, whereas for companies operating during nightly hours, GHG emissions are estimated to be as low as 3% below the GHG emissions determined by the conventional method. A significant error can therefore occur in the organizational carbon footprint (CF) of a company and, consequently, also in the product CF. It is recommended that hourly EFs be developed for other countries and power grids.     

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

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

Uncertainty and Variability in Product Carbon Footprinting

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.     

Modeling Corn Ethanol and Climate

New fuel regulations based on life cycle greenhouse gas (GHG) emissions have focused renewed attention on life cycle models of biofuels. The BESS model estimates 25% lower life cycle GHG emissions for corn ethanol than does the well-known GREET model, which raises questions about which model is more accurate. I develop a life cycle metamodel to compare the GREET and BESS models in detail and to explain why the results from these models diverge. I find two main reasons for the divergence: (1) BESS models a more efficient biorefinery than is modeled in the cases to which its results have been compared, and (2) in several instances BESS fails to properly count upstream emissions. Adjustments to BESS to account for these differences raise the estimated global warming intensity (not including land use change) of the corn ethanol pathway considered in that model from 45 to 61 g CO₂e MJ⁻¹. Adjusting GREET to use BESS's biorefinery performance and coproduct credit assumptions reduces the GREET estimate from 64 to 61 g CO₂e MJ⁻¹. Although this analysis explains the gap between the two models, both models would be improved with better data on corn production practices and by better treatment of agricultural inputs.     

Using the Lashof Accounting Methodology to Assess Carbon Mitigation Projects With Life Cycle Assessment

As governments elaborate strategies to counter climate change, there is a need to compare the different options available on an environmental basis. This study proposes a life cycle assessment framework integrating the Lashof accounting methodology, which enables the assessment and comparison of different carbon mitigation projects (e.g., biofuel use, a sequestering plant, an afforestation project). The Lashof accounting methodology is chosen amid other methods of greenhouse gas (GHG) emission characterization for its relative simplicity and capability to characterize all types of carbon mitigation projects. Using the unit of megagram‐year (Mg‐year), which accounts for the mass of GHGs in the atmosphere multiplied by the time it stays there, the methodology calculates the cumulative radiative forcing caused by GHG emission within a predetermined time frame. Basically, the developed framework uses the Mg‐year as a functional unit and isolates impacts related to the climate mitigation function with system expansion. The proposed framework is demonstrated with a case study of tree ethanol pathways (maize, sugarcane, and willow). The study shows that carbon mitigation assessment through life cycle assessment is possible and that it could be a useful tool for decision makers, as it can compare different projects regardless of their original context. The case study reveals that system expansion, as well as each carbon mitigation project's efficiency at reducing carbon emissions, are critical factors that have a significant impact on the results. Also, the framework proves to be useful for treating land‐use change emissions, as they are considered through the functional unit.     

Greenhouse Gas Emissions Quantification and Reduction Efforts in a Rural Municipality

The present article aims to determine the current carbon footprint (CF) of Zernez, a Swiss mountain village, and to identify reduction potentials of greenhouse gas (GHG) emissions. For this purpose, material and energy flows were assessed mainly based on detailed household surveys, interviews, and energy bills, but also by means of other information sources, for example, national statistics, traffic censuses, and literature values. To set up the GHG balance, special attention was paid to the consistent definition of system boundaries by adopting two fundamentally different perspectives: purely geographical accounting (PGA) and the consumption‐based footprint (CBF) method. Each of these two perspectives total approximately 10 tonnes of carbon dioxide equivalents per capita per year. The PGA revealed that 70% of the direct emissions in Zernez are caused by agricultural activities, whereas no consumption area dominated the consumption‐induced CF. For the identification of targeted measures, both perspectives were considered in a complementary manner. The building stock and its underlying energy supply system showed a GHG reduction potential of 80%. The building sector was thus detected as a reasonable first step for the municipality to adopt GHG mitigation strategies. In the case of Zernez, building‐stock‐related measures are predicted to decrease the current CF by 13% (CBF) and 17% (PGA), respectively.     

Carbon and Water Footprints and Energy Use of Greenhouse Tomato Production in Northern Italy

This study reports on the carbon, water, and energy footprints of tomatoes grown in a greenhouse in Northern Italy and two possible future variations of heating and carbon dioxide (CO₂) fertilization on the current setup. The heat supply in place, consisting of natural gas (NG) and canola oil combustion, is compared to cogeneration and incineration of municipal solid waste for heating and CO₂ from industrial exhaust for fertilization. As a benchmark, the current system is also compared to a conventional system, in which heat is delivered solely based on NG. Each kilogram (kg) of fresh tomatoes (“Cuore di Bue” variety) produced in the current greenhouse emits 2.28 kg CO₂ equivalents (eq) and uses 95.5 megajoules (MJ) eq energy and 122 liters (L) of water. Relative to the system in place, the carbon footprint (CF) is 57.5% and 18% higher with conventional NG heating and cogeneration and is 40% lower with waste valorization. Further, 33%, 55%, and 63% less energy and 9%, 96%, and 14% less water are used in the conventional, cogeneration, and waste valorization scenarios, respectively. This confirms that there are multiple strategies to reduce the impact of the tomato production under consideration.     

Corporate Carbon and Financial Performance: A Meta‐analysis

We use meta‐analytical techniques to address the question“When does it pay to be green?” Existing meta‐studies in this research field cover a range of ecological issues and synthesize a variety of environmental performance measurements. This precludes a detailed examination of how differences in measurement approaches account for variations in empirical results. In order to conduct such an examination, we focus on only one ecological issue, climate change, and one particular operational performance dimension: corporate carbon performance as expressed by a firm's level of carbon dioxide (CO₂) emission equivalents. Our sample comprises 68 estimations from 32 empirical studies, covering a total of 101,775 observations. In addition to our examination of the causal relationship, we analyze whether differences in operationalizations of carbon performance and financial performance predetermine empirical outcomes. The meta‐analytic findings indicate that carbon emissions vary inversely with financial performance, indicating that good carbon performance is generally positively related to superior financial performance. The results show that relative emissions are more likely to produce statistically significant results than absolute emissions. Furthermore, market‐based measures of financial performance are more positively related to carbon performance than accounting‐based measures. We conclude that measurement characteristics, which were not analyzed in detail by previous meta‐studies, may present a great source of cross‐study variability.