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.     

Response to Wiedmann

This commentary is prompted by Thomas Wiedmann's “Defining (Urban) Producer and Consumer Sinks” published in this issue. In his article, Wiedmann presents a new framework for categorizing carbon sinks by borrowing practices from carbon emissions accounting and, essentially, proposing a “carbon sink footprint” model for urban inventories. While this is a valuable new concept, we argue that it is difficult to apply accurately given current knowledge and practices in urban life cycle assessment. Instead, a direct versus embodied classification based on where the sequestration service exists, not where the sink is located, is more useful from the perspective of municipal control and influence over creating and managing carbon sinks. This is ultimately important for the development of urban climate change mitigation measures.     

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

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

Estimating Corporate Carbon Footprints with Externally Available Data

Corporate carbon footprints (CCFs) are a core tool in greenhouse gas emissions reporting. Established approaches for CCF calculation are based on an internal perspective that requires detailed corporate information. However, many firms do not publish information about their emissions. We seek to close this data gap by estimating scope 1 and 2 CCFs from an external perspective. The study uses a regression analysis approach, using actual firm‐internally computed CCFs to assess their degree of predictability from the outside. Data were collected from 93 European companies belonging to the chemicals, construction and engineering, and industrial machinery sectors. As predictors, we use five measures that are computed with publicly available corporate data: firm size; level of vertical integration; capital intensity; centrality of production; and carbon intensity of the national energy mix. The analysis shows that significant explanatory power for the CCF can be observed for size, capital intensity, and centrality of production. The best estimation results are achieved when data from different sectors are integrated into a comprehensive all‐sector model, while accounting for sector‐specific emission intensities by means of dummy variables. With an adjusted R² value of 0.817, the proposed procedure estimates CCFs in an accurate, yet also efficient, manner. Moreover, the study enhances trust in the current CCF calculation practices by showing that their results are plausible from a third‐party perspective.     

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.     

Energy and Carbon Management Systems

This article examines an important class of information system that serves as the foundation for corporate energy and greenhouse gas (GHG) accounting: energy and carbon management systems (ECMS). Investors, regulators, customers, and employees increasingly demand that organizations provide information about their organizational energy use and GHG emissions. However, there is little transparency about how organizations use ECMS to meet such demands. To shed light on ECMS implementation and application, we collected extensive qualitative interview data from two service‐sector organizations: one that uses a spreadsheet‐based ECMS and another that implemented an ECMS provided by a third‐party vendor. Our analysis of collected data revealed numerous challenges in the areas of business processes, managerial capabilities, data capture and integration, and data quality. Though our study is built on only two organizations and requires confirmation in large‐sample surveys, we provide several recommendations for organizations regarding ECMS. We also provide suggestions for future studies to build on our tentative results.     

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.     

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.     

Surfactants Based on Renewable Raw Materials

Under the European Commission's European Climate Change Programme, a group of experts studied the possibilities of using more renewable raw materials as chemical feedstock and assessed the related potential for greenhouse gas (GHG) emission reduction. Surfactants were among the products studied. Surfactants are currently produced from both petro-chemical feedstocks and renewable resources (oleochemical surfactants). Assuming, in a first step, that total surfactant production in the European Union remains constant until 2010, it was estimated that the amount of oleochemical surfactants could be increased from about 880 kilotons (kt) in 1998 to approximately 1, 100 kt in 2010 (an increase of 24%). This substitution reduces the life-cycle CO₂ emissions from surfactants by 8%; the theoretical maximum potential for total substitution is 37%. Because the surfactant market is expected to grow, the avoided emissions will probably exceed 8% of the current life-cycle CO₂ emissions from surfactants. If compared to the CO₂ emissions from the total industrial sector and, even more so, if compared to the total economy, the relative savings are much lower (0.02% to 0.09%). This leads to the conclusion that the increased production and use of biobased surfactants should be part of an overall GHG emission reduction strategy consisting of a whole range of measures addressing both energy demand and supply. This article also discusses policies and measures designed to increase the use of biobased surfactants.     

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.     

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.     

Large‐scale patterns in summer diffusive CH4 fluxes across boreal lakes,and contribution to diffusive C emissions

Lakes are a major component of boreal landscapes, and whereas lake CO₂ emissions are recognized as a major component of regional C budgets, there is still much uncertainty associated to lake CH₄ fluxes. Here, we present a large‐scale study of the magnitude and regulation of boreal lake summer diffusive CH₄ fluxes, and their contribution to total lake carbon (C) emissions, based on in situ measurements of concentration and fluxes of CH₄ and CO₂ in 224 lakes across a wide range of lake type and environmental gradients in Québec. The diffusive CH₄ flux was highly variable (mean 11.6 ± 26.4 SD mg m^?2 d^?1), and it was positively correlated with temperature and lake nutrient status, and negatively correlated with lake area and colored dissolved organic matter (CDOM). The relationship between CH₄ and CO₂ concentrations fluxes was weak, suggesting major differences in their respective sources and/or regulation. For example, increasing water temperature leads to higher CH₄ flux but does not significantly affect CO₂ flux, whereas increasing CDOM concentration leads to higher CO₂ flux but lower CH₄ flux. CH₄ contributed to 8 ± 23% to the total lake C emissions (CH₄ + CO₂), but 18 ± 25% to the total flux in terms of atmospheric warming potential, expressed as CO₂‐equivalents. The incorporation of ebullition and plant‐mediated CH₄ fluxes would further increase the importance of lake CH₄. The average Q₁₀ of CH₄ flux was 3.7, once other covarying factors were accounted for, but this apparent Q₁₀ varied with lake morphometry and was higher for shallow lakes. We conclude that global climate change and the resulting shifts in temperature will strongly influence lake CH₄ fluxes across the boreal biome, but these climate effects may be altered by regional patterns in lake morphometry, nutrient status, and browning.     

Patterns in CH4 and CO2 concentrations across boreal rivers: Major drivers and implications for fluvial greenhouse emissions under climate change scenarios

It is now widely accepted that boreal rivers and streams are regionally significant sources of carbon dioxide (CO₂), yet their role as methane (CH₄) emitters, as well as the sensitivity of these greenhouse gas (GHG) emissions to climate change, are still largely undefined. In this study, we explore the large‐scale patterns of fluvial CO₂ and CH₄ partial pressure (pCO₂, pCH₄) and gas exchange (k) relative to a set of key, climate‐sensitive river variables across 46 streams and rivers in two distinct boreal landscapes of Northern Québec. We use the resulting models to determine the direction and magnitude of C‐gas emissions from these boreal fluvial networks under scenarios of climate change. River pCO₂ and pCH₄ were positively correlated, although the latter was two orders of magnitude more variable. We provide evidence that in‐stream metabolism strongly influences the dynamics of surface water pCO₂ and pCH₄, but whereas pCO₂ is not influenced by temperature in the surveyed streams and rivers, pCH₄ appears to be strongly temperature‐dependent. The major predictors of ambient gas concentrations and exchange were water temperature, velocity, and DOC, and the resulting models indicate that total GHG emissions (C‐CO₂ equivalent) from the entire network may increase between by 13 to 68% under plausible scenarios of climate change over the next 50 years. These predicted increases in fluvial GHG emissions are mostly driven by a steep increase in the contribution of CH₄ (from 36 to over 50% of total CO₂‐equivalents). The current role of boreal fluvial networks as major landscape sources of C is thus likely to expand, mainly driven by large increases in fluvial CH₄ emissions.     

Absolute Sustainability‐Based Life Cycle Assessment (ASLCA): A Benchmarking Approach to Operate Agri‐food Systems within the 2°C Global Carbon Budget

Given the increasing environmental impacts associated with global agri‐food systems, operating and developing these systems within the so‐called absolute environmental boundaries has become crucial, and hence the absolute environmental sustainability concept is particularly relevant. This study introduces an approach called absolute sustainability‐based life cycle assessment (ASLCA) that informs the climate impacts of an agri‐food system (on any economic level) in absolute terms. First, a global carbon budget was calculated that is sufficient to limit global warming to below 2°C. Next, a share of the carbon budget available to the global agri‐food sector was estimated, and then it was shared between agri‐food systems on multiple economic levels using four alternative methods. Third, the climate impacts of those systems were calculated using life cycle assessment methodology and were benchmarked against those carbon budget shares. This approach was used to assess a number of New Zealand agri‐food systems (agri‐food sector, horticulture industries and products) to investigate how these systems operated relative to their carbon budget shares. The results showed that, in 2013, the New Zealand agri‐food systems were within their carbon budget shares for one of the four methods, and illustrated the scale of change required for agri‐food systems to perform within their carbon budget shares. This method can potentially be extended to consider other environmental impacts with global boundaries; however, further development of the ASLCA is necessary to account for other environmental impacts whose boundaries are only meaningful when defined at a regional or local level.     

Fast Carbon Footprinting for Large Product Portfolios

Publicly Available Specification 2050‐2011 (PAS 2050), the Green House Gas Product Protocol (GHGPP) standard and forthcoming guideline 14067 from the International Organization for Standardization (ISO) have helped to propel carbon footprinting from a subdiscipline of life cycle assessment (LCA) to the mainstream. However, application of carbon footprinting to large portfolios of many distinct products and services is immensely resource intensive. Even if achieved, it often fails to inform company‐wide carbon reduction strategies because footprint data are disjointed or don't cover the whole portfolio. We introduce a novel approach to generate standard‐compliant product carbon footprints (CFs) for companies with large portfolios at a fraction of previously required time and expertise. The approach was developed and validated on an LCA dataset covering 1,137 individual products from a global packaged consumer goods company. Three novel techniques work in concert in a single approach that enables practitioners to calculate thousands of footprints virtually simultaneously: (i) a uniform data structure enables footprinting all products and services by looping the same algorithm; (ii) concurrent uncertainty analysis guides practitioners to gradually improve the accuracy of only those data that materially impact the results; and (iii) a predictive model generates estimated emission factors (EFs) for materials, thereby eliminating the manual mapping of a product or service's inventory to EF databases. These autogenerated EFs enable non‐LCA experts to calculate approximate CFs and alleviate resource constraints for companies embarking on large‐scale product carbon footprinting. We discuss implementation roadmaps for companies, including further road‐testing required to evaluate the effectiveness of the approach for other product portfolios, limitations, and future improvements of the fast footprinting methodology.     

Uncertainty and Sensitivity in the Carbon Footprint of Shopping Bags

Carbon footprints for several shopping bag alternatives (polyethylene, paper, cotton, biodegradable modified starch, and recycled polyethylene) were compared with life cycle assessment. Stochastic uncertainty analysis was used to study the sensitivity of the comparison to scenario and parameter uncertainty. On the basis of the results, we could give only a few robust conclusions without choosing a waste treatment scenario or limiting the parameter space. Given the scenario of current waste infrastructure in Finland, recycled polyethylene bags seem to be the most preferable (?7 to 24 g CO₂ eq./bag) and biodegradable bags the least preferable (38 to 60 g CO₂ eq./bag) option. In each analyzed waste treatment scenario, a few parameters dominated the uncertainty of results. Most of these parameters were downstream of the shopping bag manufacturing (consumer behavior, landfill conditions, method of waste combustion, etc.). The choice of waste treatment scenario had a greater effect on the ranking of bags than parameter uncertainty within scenarios. This result highlights the importance of including several scenarios in comparative life cycle assessments.     

A Carbon Footprint of Textile Recycling: A Case Study in Sweden

Global population growth and rising living standards are increasing apparel consumption. Consequently, consumption of resources and generation of textile waste are increasing. According to the Swedish Environmental Protection Agency, textile consumption increased by 40% between the years 2000 and 2009 in Sweden. Given that there is currently no textile recycling plant in Sweden, the aim of this article is to explore the potential environmental benefits of various textile recycling techniques and thereby direct textile waste management strategies toward more sustainable options. Three different recycling techniques for a model waste consisting of 50% cotton and 50% polyester were identified and a life cycle assessment (LCA) was made to assess the environmental performance of them. The recycling processes are: material reuse of textile waste of adequate quality; separation of cellulose from polyester using N‐methylmorpholine‐N‐oxide as a solvent; and chemical recycling of polyester. These are compared to incineration, representing conventional textile waste treatment in Sweden. The results show that incineration has the highest global warming potential and primary energy usage. The material reuse process exhibits the best performance of the studied systems, with savings of 8 tonnes of carbon dioxide equivalents (CO₂‐eq) and 164 gigajoules (GJ) of primary energy per tonne of textile waste. Sensitivity analyses showed that results are particularly sensitive to the considered yields of the processes and to the choice of replaced products. An integration of these recycling technologies for optimal usage of their different features for treatment of 1 tonne of textile waste shows that 10 tonnes CO₂‐eq and 169 GJ of primary energy could be saved.     

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.