The contribution of PAS 2050 to the evolution of international greenhouse gas emission standards

Background, aim, and scope  The assessment of greenhouse gas (GHG) emissions arising from products (goods and services) is emerging as a high profile application of life cycle assessment (LCA), with an increasing desire from retailers and other supply chain organizations to better understand, and in some cases communicate, the carbon footprint of products. Publicly Available Specification 2050:2008, Specification for the assessment of the life cycle greenhouse gas emissions of goods and services, addresses the single-impact category of global warming to provide a standardized and simplified implementation of process LCA methods for assessing GHG emissions from products. This paper briefly reviews the development process followed for PAS 2050, before examining the treatment of GHG-specific contribution of PAS 2050 to product carbon footprinting. Materials and methods  PAS 2050 was jointly sponsored by the Carbon Trust and the UK Department for Environment, Food and Rural Affairs and was published by the British Standards Institution on 29 October 2008. An independent steering group oversaw the development of the specification, including the establishment of an expert workgroup program, comprehensive international consultation, and expert input on the requirements of the specification. Results  The development process for PAS 2050 resulted in a specification that includes specific requirements that limit the interpretation of the underlying LCA approach to product carbon footprinting. These requirements, including goal setting and life cycle inventory assessment, aspects of system boundary identification and temporal aspects of GHG emissions, clarify the approach to be taken by organizations implementing product carbon footprinting, and simplify the application of LCA procedures in relation to product carbon footprinting. Discussion  Assessment of the emissions arising from the life cycle of products has a clear international component, and delivering consistent results across the supply chain requires the application of consistent methods. There is an emerging recognition that further standardization of methods for product carbon footprinting is needed, and the specific requirements resulting from the PAS 2050 development process make a valuable contribution across a range of GHG assessment issues. Conclusions  The widespread interest in PAS 2050 from individuals and organizations, together with the development of similar guidance by other organizations, confirmed that there is a need for clarification, certainty, and requirements in the field of product carbon footprint analysis. The use of PAS 2050 to refine, clarify, and simplify existing LCA methods and standards has resulted in specific approaches to key GHG assessment issues being developed; it is important that future standards development work considers the impact of these approaches and their further refinement. Recommendations and perspectives  It is the consumption of goods and services by individuals around the world that drives global GHG emission, and PAS 2050 is a first attempt to provide integrated, consistent approaches that directly address the role of consumption at the product level in contributing to GHG emissions. Climate science and GHG assessment techniques are both evolving areas and it will be necessary to review the approach taken by PAS 2050 in the future: a formal review process for PAS 2050 will commence towards the end of 2009 and practitioners are encouraged to participate in this review process.

An appraisal of carbon footprint of milk from commercial grass-based dairy farms in Ireland according to a certified life cycle assessment methodology

Purpose

Life cycle assessment (LCA) studies of carbon footprint (CF) of milk from grass-based farms are usually limited to small numbers of farms (<30) and rarely certified to international standards, e.g. British Standards Institute publicly available specification 2050 (PAS 2050). The goals of this study were to quantify CF of milk from a large sample of grass-based farms using an accredited PAS 2050 method and to assess the relationships between farm characteristics and CF of milk.

Materials and methods

Data was collected annually using on-farm surveys, milk processor records and national livestock databases for 171 grass-based Irish dairy farms with information successfully obtained electronically from 124 farms and fed into a cradle to farm-gate LCA model. Greenhouse gas (GHG) emissions were estimated with the LCA model in CO₂ equivalents (CO₂-eq) and allocated economically between dairy farm products, except exported crops. Carbon footprint of milk was estimated by expressing GHG emissions attributed to milk per kilogram of fat and protein-corrected milk (FPCM). The Carbon Trust tested the LCA model for non-conformities with PAS 2050. PAS 2050 certification was achieved when non-conformities were fixed or where the effect of all unresolved non-conformities on CF of milk was?<?±5 %.

Results and discussion

The combined effect of LCA model non-conformities with PAS 2050 on CF of milk was <1 %. Consequently, PAS 2050 accreditation was granted. The mean certified CF of milk from grass-based farms was 1.11 kg of CO₂-eq/kg of FPCM, but varied from 0.87 to 1.72 kg of CO₂-eq/kg of FPCM. Although some farm attributes had stronger relationships with CF of milk than the others, no attribute accounted for the majority of variation between farms. However, CF of milk could be reasonably predicted using N efficiency, the length of the grazing season, milk yield/cow and annual replacement rate (R ²?=?0.75). Management changes can be applied simultaneously to improve each of these traits. Thus, grass-based farmers can potentially significantly reduce CF of milk.

Conclusions

The certification of an LCA model to PAS 2050 standards for grass-based dairy farms provides a verifiable approach to quantify CF of milk at a farm or national level. The application of the certified model highlighted a wide range between the CF of milk of commercial farms. However, differences between farms’ CF of milk were explained by variation in various aspects of farm performance. This implies that improving farm efficiency can mitigate CF of milk.     

Evaluating the carbon footprint of the cork sector with a dynamic approach including biogenic carbon flows

Purpose

The aim of the present study is to assess the influence of two different attributional life cycle assessment (LCA) approaches, namely static LCA (sLCA) and dynamic LCA (dLCA), through their application to the calculation of the carbon footprint (CF) of the entire cork sector in Portugal. The effect of including biogenic carbon sequestration and emissions is considered as well.

Methods

sLCA is often described as a static tool since all the emissions are accounted for as if occurring at the same time which may not be the case in reality for greenhouse gases. In contrast, dLCA aims to evaluate the impact of life cycle greenhouse gas emissions on radiative forcing considering the specific moment when these emissions occur.

Results and discussion

The results show that the total CF of the cork sector differs depending on the approach and time horizon chosen. However, the greater it is the time horizon chosen, the smaller the difference between the CF results of the two approaches. Additionally, the inclusion of biogenic carbon sequestration and emissions also influences significantly the CF result. The cork sector is considered a net carbon source when biogenic carbon is excluded from the calculations and a net carbon sink when biogenic carbon is included in the calculations since more carbon is sequestered than emitted along the sector.

Conclusions

dLCA allows an overview of greenhouse gas emissions along the time. This is an advantage as it allows to identify and plan different management approaches for the cork sector. Even though dLCA is a more realistic approach, it is a more time-consuming and complex approach for long life cycles. The choice of time horizon was found to be another important aspect for CF assessment.

     

Approaches for inclusion of forest carbon cycle in life cycle assessment – a review

Forests are a significant pool of terrestrial carbon. A key feature related to forest biomass harvesting and use is the typical time difference between carbon release into and sequestration from the atmosphere. Traditionally, the use of sustainably grown biomass has been considered as carbon neutral in life cycle assessment (LCA) studies. However, various approaches to account for greenhouse gas (GHG) emissions and sinks of forest biomass acquisition and use have also been developed and applied, resulting in different conclusions on climate impacts of forest products. The aim of this study is to summarize, clarify, and assess the suitability of these approaches for LCA. A literature review is carried out, and the results are analyzed through an assessment framework. The different approaches are reviewed through their approach to the definition of reference land‐use situation, consideration of time frame and timing of carbon emissions and sequestration, substitution credits, and indicators applied to measure climate impacts. On the basis of the review, it is concluded that, to account for GHG emissions and the related climate impacts objectively, biomass carbon stored in the products and the timing of sinks and emissions should be taken into account in LCA. The reference situation for forest land use has to be defined appropriately, describing the development in the absence of the studied system. We suggest the use of some climate impact indicator that takes the timing of the emissions and sinks into consideration and enables the use of different time frames. If substitution credits are considered, they need to be transparently presented in the results. Instead of carbon stock values taken from the literature, the use of dynamic forest models is recommended.     

Temporal Aspects in Evaluating the Greenhouse Gas Mitigation Benefits of Using Residues from Forest Products Manufacturing Facilities for Energy Production

Methods for carbon footprinting typically combine all emissions into a single result, representing the emissions of greenhouse gases (GHGs) over the life cycle. The timing of GHG impacts, however, has become a matter of significant interest. In this study, two approaches are used to characterize the timing of GHG emission impacts associated with the production of energy from various biomass residues produced by the forest products industry. The first approach accounts for the timing of emissions and characterizes the impact using Intergovernmental Panel on Climate Change (IPCC) 100‐year global warming potentials (GWPs). The second is a dynamic carbon footprint approach that considers the timing of the GHG emissions, their fate in the atmosphere, and the associated radiative forcing as a function of time. The two approaches generally yield estimates of cumulative impacts over 100 years that differ by less than 5%. The timing of impacts, however, can be significantly affected by the approach used to characterize radiative forcing. For instance, the time required to see net benefits from a system using woody mill residues (e.g., bark and sawdust) is estimated to be 1.2 years when using a fully dynamic approach, compared to 7.5 years when using 100‐year GWPs, with the differences being primarily attributable to methane (CH₄). The results obtained for a number of different biomass residue types from forest products manufacturing highlight the importance of using a fully dynamic approach when studying the timing of emissions impacts in cases where emissions are distributed over time or where CH₄ is a significant contributor to the emissions.     

Life cycle analysis of biochemical cellulosic ethanol under multiple scenarios

Cellulosic ethanol is widely believed to offer substantial environmental advantages over petroleum fuels and grain‐based ethanol, particularly in reducing greenhouse gas emissions from transportation. The environmental impacts of biofuels are largely caused by precombustion activities, feedstock production and conversion facility operations. Life cycle analysis (LCA) is required to understand these impacts. This article describes a field‐to‐blending terminal LCA of cellulosic ethanol produced by biochemical conversion (hydrolysis and fermentation) using corn stover or switchgrass as feedstock. This LCA develops unique models for most elements of the biofuel production process and assigns environmental impact to different phases of production. More than 30 scenarios are evaluated, reflecting a range of feedstock, technology and scale options for near‐term and future facilities. Cellulosic ethanol, as modeled here, has the potential to significantly reduce greenhouse gas (GHG) emissions compared to petroleum‐based liquid transportation fuels, though substantial uncertainty exists. Most of the conservative scenarios estimate GHG emissions of approximately 45–60 g carbon dioxide equivalent per MJ of delivered fuel (g CO₂e MJ^?1) without credit for coproducts, and 20–30 g CO₂e MJ^?1 when coproducts are considered. Under most scenarios, feedstock production, grinding and transport dominate the total GHG footprint. The most optimistic scenarios include sequestration of carbon in soil and have GHG emissions below zero g CO₂e MJ^?1, while the most pessimistic have life‐cycle GHG emissions higher than petroleum gasoline. Soil carbon changes are the greatest source of uncertainty, dominating all other sources of GHG emissions at the upper bound of their uncertainty. Many LCAs of biofuels are narrowly constrained to GHG emissions and energy; however, these narrow assessments may miss important environmental impacts. To ensure a more holistic assessment of environmental performance, a complete life cycle inventory, with over 1100 tracked material and energy flows for each scenario is provided in the online supplementary material for this article.     

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.     

Including albedo in time‐dependent LCA of bioenergy

Albedo change during feedstock production can substantially alter the life cycle climate impact of bioenergy. Life cycle assessment (LCA) studies have compared the effects of albedo and greenhouse gases (GHGs) based on global warming potential (GWP). However, using GWP leads to unequal weighting of climate forcers that act on different timescales. In this study, albedo was included in the time‐dependent LCA, which accounts for the timing of emissions and their impacts. We employed field‐measured albedo and life cycle emissions data along with time‐dependent models of radiative transfer, biogenic carbon fluxes and nitrous oxide emissions from soil. Climate impacts were expressed as global mean surface temperature change over time (?T) and as GWP. The bioenergy system analysed was heat and power production from short‐rotation willow grown on former fallow land in Sweden. We found a net cooling effect in terms of ?T per hectare (?3.8 × 10^–11 K in year 100) and GWP₁₀₀ per MJ fuel (?12.2 g CO₂e), as a result of soil carbon sequestration via high inputs of carbon from willow roots and litter. Albedo was higher under willow than fallow, contributing to the cooling effect and accounting for 34% of GWP₁₀₀, 36% of ?T in year 50 and 6% of ?T in year 100. Albedo dominated the short‐term temperature response (10–20 years) but became, in relative terms, less important over time, owing to accumulation of soil carbon under sustained production and the longer perturbation lifetime of GHGs. The timing of impacts was explicit with ?T, which improves the relevance of LCA results to climate targets. Our method can be used to quantify the first‐order radiative effect of albedo change on the global climate and relate it to the climate impact of GHG emissions in LCA of bioenergy, alternative energy sources or land uses.     

The Greenhouse Gas Footprint of China's Food System: An Analysis of Recent Trends and Future Scenarios

Food chain systems (FCSs), which begin in agricultural production and end in consumption and waste disposal, play a significant role in China's rising greenhouse gas (GHG) emissions. This article uses scenario analysis to show China's potential trajectories to a low‐carbon FCS. Between 1996 and 2010, the GHG footprint of China's FCSs increased from 1,308 to 1,618 megatonnes of carbon dioxide equivalent (Mt CO₂‐eq), although the emissions intensity of all food categories, except for aquatic food, recorded steep declines. We project three scenarios to 2050 based on historical trends and plausible shifts in policies and environmental conditions: reference scenario; technology improvement scenario; and low GHG emissions scenario. The reference scenario is based on existing trends and exhibits a large growth in GHG emissions, increasing from 1,585 Mt CO₂‐eq in 2010 to 2,505 Mt CO₂‐eq in 2050. In the technology improvement scenario, emissions growth is driven by rising food demand, but that growth will be counterbalanced by gains in agricultural technology, causing GHG emissions to fall to 1,413 Mt CO₂‐eq by 2050. Combining technology improvement with the shift to healthier dietary patterns, GHG emissions in the low GHG emissions scenario will decline to 946 Mt CO₂‐eq in 2050, a drop of 41.5% compared with the level in 2010. We argue that these are realistic projections and are indeed indicative of China's overall strategy for low‐carbon development. Improving agricultural technology and shifting to a more balanced diet could significantly reduce the GHG footprint of China's FCSs. Furthermore, the transition to a low‐carbon FCS has potential cobenefits for land sustainability and public health.     

Sensitivity of the carbon footprint of New Zealand milk to greenhouse gas metrics

Milk production is responsible for emitting a range of greenhouse gases (GHGs), mainly carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄). In Life Cycle Assessments (LCA), the Global Warming Potential with a time horizon of 100 years (GWP100) is used almost universally to aggregate emissions of individual gases into so-called CO₂-equivalent emissions that are used to calculate the overall carbon footprint of milk production. However, there is growing awareness that, depending on the purpose of the LCA, metrics other than GWP100 could be justified and some would give a very different weighting for the short-lived gas CH₄ relative to the long-lived gases CO₂ and N₂O when calculating the carbon footprint. Pastoral dairy production systems at different levels of intensification differ in the balance of short- and long-lived GHGs associated with on- and off-farm emissions. Differences in the carbon footprint of different production systems could therefore be highly sensitive to the choice of GHG metric. Here we explore the extent to which alternative GHG metric choices would alter the carbon footprint of New Zealand milk production at different levels of intensification at national, regional and individual farm scales and compared to the carbon footprint of milk of selected European countries. We find that the ranking of different production systems and individual farms in terms of their carbon footprint is relatively robust against the choice of GHG metric, despite significant differences in their utilisation of pastures versus supplementary off-farm feed, fertiliser use and energy consumption at various stages of farm operations. However, there are instances where alternative GHG metric choices would fundamentally change the conclusions of LCA of different production systems, including whether a move towards higher or lower input systems would increase or decrease the average carbon footprint of milk production in New Zealand. Greater transparency about the implications of alternative GHG metrics for LCA, and the often inadvertent and implicit value judgements embedded in these metrics, would help ensure that policy decisions and consumer choices based on LCA indeed deliver the climate outcomes intended by end-users.     

Climate mitigation by dairy intensification depends on intensive use of spared grassland

Milk and beef production cause 9% of global greenhouse gas (GHG) emissions. Previous life cycle assessment (LCA) studies have shown that dairy intensification reduces the carbon footprint of milk by increasing animal productivity and feed conversion efficiency. None of these studies simultaneously evaluated indirect GHG effects incurred via teleconnections with expansion of feed crop production and replacement suckler‐beef production. We applied consequential LCA to incorporate these effects into GHG mitigation calculations for intensification scenarios among grazing‐based dairy farms in an industrialized country (UK), in which milk production shifts from average to intensive farm typologies, involving higher milk yields per cow and more maize and concentrate feed in cattle diets. Attributional LCA indicated a reduction of up to 0.10 kg CO₂e kg^?1 milk following intensification, reflecting improved feed conversion efficiency. However, consequential LCA indicated that land use change associated with increased demand for maize and concentrate feed, plus additional suckler‐beef production to replace reduced dairy‐beef output, significantly increased GHG emissions following intensification. International displacement of replacement suckler‐beef production to the “global beef frontier” in Brazil resulted in small GHG savings for the UK GHG inventory, but contributed to a net increase in international GHG emissions equivalent to 0.63 kg CO₂e kg^?1 milk. Use of spared dairy grassland for intensive beef production can lead to net GHG mitigation by replacing extensive beef production, enabling afforestation on larger areas of lower quality grassland, or by avoiding expansion of international (Brazilian) beef production. We recommend that LCA boundaries are expanded when evaluating livestock intensification pathways, to avoid potentially misleading conclusions being drawn from “snapshot” carbon footprints. We conclude that dairy intensification in industrialized countries can lead to significant international carbon leakage, and only achieves GHG mitigation when spared dairy grassland is used to intensify beef production, freeing up larger areas for afforestation.     

Life cycle assessment comparison of wooden and plastic pallets in the grocery industry

Wooden and plastic pallets are used extensively in global trade to transport finished goods and products. This article compares the life cycle performance of treated wooden and plastic pallets through a detailed cradle‐to‐grave life cycle assessment (LCA), and conducts an analysis of the various phytosanitary treatments. The LCA investigates and evaluates the environmental impacts due to the resources consumed and emissions of the product throughout its life cycle. The environmental impacts of the pallets are compared on a one‐trip basis and a 100,000‐trips basis. Impact categories are chosen with respect to environmental concerns. The results show that on a one‐trip basis, wooden pallets with conventional and radio frequency (RF) heat treatment incur an overall carbon footprint of 71.8% and 80.3% lower, respectively, than plastic pallets during their life cycle; and in comparison with wooden pallets treated with methyl bromide fumigation, they incur 20% and 30% less overall carbon footprint. Theoretical calculations of the resource consumption and emissions of RF treatment of pallets suggest that dielectric technology may provide a lower‐carbon alternative to both current ISPM 15‐approved treatments and to plastic pallets. Methyl bromide fumigation (15.95 kg CO₂ equivalent [eq.]) has a larger carbon footprint than conventional heat treatment (12.69 kg CO₂ eq.) of pallets. For the 100,000‐trips basis, the differences are even more significant. The results recommend that wooden pallets are more environmentally friendly than plastic pallets, and conventional and RF heat treatment for wooden pallets is more sustainable than methyl bromide fumigation treatment.     

Dry Matter Losses and Methane Emissions During Wood Chip Storage: the Impact on Full Life Cycle Greenhouse Gas Savings of Short Rotation Coppice Willow for Heat

A life cycle assessment (LCA) approach was used to examine the greenhouse gas (GHG) emissions and energy balance of short rotation coppice (SRC) willow for heat production. The modelled supply chain includes cutting multiplication, site establishment, maintenance, harvesting, storage, transport and combustion. The relative impacts of dry matter losses and methane emissions from chip storage were examined from a LCA perspective, comparing the GHG emissions from the SRC supply chain with those of natural gas for heat generation. The results show that SRC generally provides very high GHG emission savings of over 90 %. The LCA model estimates that a 1, 10 and 20 % loss of dry matter during storage causes a 1, 6 and 11 % increase in GHG emissions per MWh. The GHG emission results are extremely sensitive to emissions of methane from the wood chip stack: If 1 % of the carbon within the stack undergoes anaerobic decomposition to methane, then the GHG emissions per MWh are tripled. There are some uncertainties in the LCA results, regarding the true formation of methane in wood chip stacks, non-CO₂ emissions from combustion, N₂O emissions from leaf fall and the extent of carbon sequestered under the crop, and these all contribute a large proportion of the life cycle GHG emissions from cultivation of the crop.     

Spatial and technological variability in the carbon footprint of durum wheat production in Iran

Purpose

The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran.

Methods

The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N₂O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat.

Results and discussion

The average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO₂-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO₂-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of ?2/3. This indicates that the carbon footprint of durum wheat production (in kg CO₂-eq kg^?1) typically decreases by 67% with a 100% increase in yield (in kg ha^?1 year^?1).

Conclusions

Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.

     

Implications of emissions timing on the cost‐effectiveness of greenhouse gas mitigation strategies: application to forest bioenergy systems

Conventional cost‐effectiveness calculations ignore the implications of greenhouse gas (GHG) emissions timing and thus may not properly inform decision‐makers in the efficient allocation of resources to mitigate climate change. To begin to address this disconnect with climate change science, we modify the conventional cost‐effectiveness approach to account for emissions timing. GHG emissions flows occurring over time are translated into an ‘Equivalent Present Emission’ based on radiative forcing, enabling a comparison of system costs and emissions on a consistent present time basis. We apply this ‘Present Cost‐Effectiveness’ method to case studies of biomass‐based electricity generation (biomass co‐firing with coal, biomass cogeneration) to evaluate implications of forest carbon trade‐offs on the cost‐effectiveness of emission reductions. Bioenergy production from forest biomass can reduce forest carbon stocks, an immediate emissions source that contributes to atmospheric greenhouse gases. Forest carbon impacts thereby lessen emission reductions in the near‐term relative to the assumption of biomass ‘carbon neutrality’, resulting in higher costs of emission reductions when emissions timing is considered. In contrast, conventional cost‐effectiveness approaches implicitly evaluate strategies over an infinite analytical time horizon, underestimating nearer term emissions reduction costs and failing to identify pathways that can most efficiently contribute to climate change mitigation objectives over shorter time spans (e.g. up to 100 years). While providing only a simple representation of the climate change implications of emissions timing, the Present Cost‐Effectiveness method provides a straightforward approach to assessing the cost‐effectiveness of emission reductions associated with any climate change mitigation strategy where future GHG reductions require significant initial capital investment or increase near‐term emissions. Timing is a critical factor in determining the attractiveness of any investment; accounting for emissions timing can better inform decisions related to the merit of alternative resource uses to meet near‐, mid‐, and long‐term climate change mitigation objectives.     

LIFE BEEF CARBON: a common framework for quantifying grass and corn based beef farms’ carbon footprints

Europe’s roadmap to a low-carbon economy aims to cut greenhouse gas (GHG) emissions 80% below 1990 levels by 2050. Beef production is an important source of GHG emissions and is expected to increase as the world population grows. LIFE BEEF CARBON is a voluntary European initiative that aims to reduce GHG emissions per unit of beef (carbon footprint) by 15% over a 10-year period on 2172 farms in four large beef-producing countries. Changes in farms beef carbon footprint are normally estimated via simulation modelling, but the methods current models apply differ. Thus, our initial goal was to develop a common modelling framework to estimate beef farms carbon footprint. The framework was developed for a diverse set of Western Europe farms located in Ireland, Spain, Italy and France. Whole farm and life cycle assessment (LCA) models were selected to quantify emissions for the different production contexts and harmonized. Carbon Audit was chosen for Ireland, Bovid-CO₂ for Spain and CAP’2ER for France and Italy. All models were tested using 20 case study farms, that is, 5 per country and quantified GHG emissions associated with on-farm live weight gain. The comparison showed the ranking of beef systems gross carbon footprint was consistent across the three models. Suckler to weaning or store systems generally had the highest carbon footprint followed by suckler to beef systems and fattening beef systems. When applied to the same farm, Carbon Audit’s footprint estimates were slightly lower than CAP’2ER, but marginally higher than Bovid-CO₂. These differences occurred because the models were adapted to a specific region’s production circumstances, which meant their emission factors for key sources; that is, methane from enteric fermentation and GHG emissions from concentrates were less accurate when used outside their target region. Thus, for the common modelling framework, region-specific LCA models were chosen to estimate beef carbon footprints instead of a single generic model. Additionally, the Carbon Audit and Bovid-CO₂ models were updated to include carbon removal by soil and other environmental metrics included in CAP’2ER, for example, acidification. This allows all models to assess the effect carbon mitigation strategies have on other potential pollutants. Several options were identified to reduce beef farms carbon footprint, for example, improving genetic merit. These options were assessed for beef systems, and a mitigation plan was created by each nation. The cumulative mitigation effect of the LIFE BEEF CARBON plan was estimated to exceed the projects reduction target (−15%).     

Time-adjusted global warming potentials for LCA and carbon footprints

Purpose

The common practice of summing greenhouse gas (GHG) emissions and applying global warming potentials (GWPs) to calculate CO₂ equivalents misrepresents the global warming effects of emissions that occur over a product or system??s life cycle at a particular time in the future. The two primary purposes of this work are to develop an approach to correct for this distortion that can (1) be feasibly implemented by life cycle assessment and carbon footprint practitioners and (2) results in units of CO₂ equivalent. Units of CO₂ equilavent allow for easy integration in current reporting and policy frameworks.

Methods

CO₂ equivalency is typically calculated using GWPs from the Intergovernmental Panel on Climate Change. GWPs are calculated by dividing a GHG??s global warming effect, as measured by cumulative radiative forcing, over a prescribed time horizon by the global warming effect of CO₂ over that same time horizon. Current methods distort the actual effect of GHG emissions at a particular time in the future by summing emissions released at different times and applying GWPs; modeling them as if they occur at the beginning of the analytical time horizon. The method proposed here develops time-adjusted warming potentials (TAWPs), which use the reference gas CO₂, and a reference time of zero. Thus, application of TAWPs results in units of CO₂ equivalent today.

Results and discussion

A GWP for a given GHG only requires that a practitioner select an analytical time horizon. The TAWP, however, contains an additional independent variable; the year in which an emission occurs. Thus, for each GHG and each analytical time horizon, TAWPs require a simple software tool (TAWPv1.0) or an equation to estimate their value. Application of 100-year TAWPs to a commercial building??s life cycle emissions showed a 30?% reduction in CO₂ equivalent compared to typical practice using 100-year GWPs. As the analytical time horizon is extended the effect of emissions timing is less pronounced. For example, at a 500-year analytical time horizon the difference is only 5?%.

Conclusions and recommendations

TAWPs are one of many alternatives to traditional accounting methods, and are envisioned to be used as one of multiple characterizations in carbon accounting or life cycle impact assessment methods to assist in interpretation of a study??s outcome.     

Linear Approaches to Characterization of Delayed Emissions of Methane

It is becoming more common to include the effects of delayed greenhouse gas emissions as an additional aspect in carbon footprinting. Although full dynamic assessment is the only accurate option to calculate those effects, the linear approach as outlined in, for example, the International Reference Life Cycle Data System (ILCD) Handbook, which is a popular reference. This approach overestimates the benefits of delayed emissions in all cases, but, for methane, the deviation is orders of magnitude. An alternative linear approach is proposed that does not start at t = 0. When using a time horizon of 100 years, an initial no‐accounting period of 75 years is found to be appropriate for delayed emissions of methane, in most cases. The difference between the two approaches, when applying the concept of temporary carbon storage or delayed emissions to landfill, is considerable.     

Carbon sequestration in LCA,a proposal for a new approach based on the global carbon cycle; cases on wood and on bamboo

Purpose

There are many recent proposals in life cycle assessment (LCA) to calculate temporary storage of carbon in bio-based products. However, there is still no consensus on how to deal with the issue. The main questions are: how do these proposals relate to each other, to what extent are they in line with the classical LCA method (as defined in ISO 14044) and the global mass balances as proposed by the IPCC, and is there really a need to introduce a discounting system for delayed CO₂ emissions?

Methods

This paper starts with an analysis of the widely applied specification of PAS 2050 and the ILCD Handbook, both specifying the credit for carbon sequestration as ‘optional’ in LCA. From this analysis, it is concluded that these optional calculations give rather different results compared to the baseline LCA method. Since these optional calculations are not fully in line with the global carbon mass balances, a new calculation method is proposed. To validate the new method, two cases (one on wood and one bamboo products) are given. These cases show the practical application and the consequences of the new approach. Finally, the main issue is evaluated and discussed: is it a realistic approach to allocate less damage to the same emission, when it is released later in time?

Results and discussion

This paper proposes a new approach based on the global carbon cycle and land-use change, translated to the level of individual products in LCA. It is argued that only a global growth of forest area and a global growth of application of wood in the building industry contribute to extra carbon sequestration, which might be allocated as a credit to the total market of wood products in LCA. This approach is different from approaches where temporary storage of carbon in trees is directly allocated to a product itself.

Conclusions

In the proposed approach, there seems to be no need for a discounting system of delayed CO₂ emissions. The advantage of wood and wood-based products can be described in terms of land-use change on a global scale in combination with a credit for heat recovery at the end-of-life (if applicable).     

Atmospheric impact of bioenergy based on perennial crop (reed canary grass,Phalaris arundinaceae,L.) cultivation on a drained boreal organic soil

Marginal organic soils, abundant in the boreal region, are being increasingly used for bioenergy crop cultivation. Using long‐term field experimental data on greenhouse gas (GHG) balance from a perennial bioenergy crop [reed canary grass (RCG), Phalaris arundinaceae L.] cultivated on a drained organic soil as an example, we show here for the first time that, with a proper cultivation and land‐use practice, environmentally sound bioenergy production is possible on these problematic soil types. We performed a life cycle assessment (LCA) for RCG on this organic soil. We found that, on an average, this system produces 40% less CO₂‐equivalents per MWh of energy in comparison with a conventional energy source such as coal. Climatic conditions regulating the RCG carbon exchange processes have a high impact on the benefits from this bioenergy production system. Under appropriate hydrological conditions, this system can even be carbon‐negative. An LCA sensitivity analysis revealed that net ecosystem CO₂ exchange and crop yield are the major LCA components, while non‐CO₂ GHG emissions and costs associated with crop production are the minor ones. Net bioenergy GHG emissions resulting from restricted net CO₂ uptake and low crop yields, due to climatic and moisture stress during dry years, were comparable with coal emissions. However, net bioenergy emissions during wet years with high net uptake and crop yield were only a third of the coal emissions. As long‐term experimental data on GHG balance of bioenergy production are scarce, scientific data stemming from field experiments are needed in shaping renewable energy source policies.