Managing the carbon footprint of products: the contribution of the method composed of financial statements (MC3)

Purpose  

Carbon footprints (CF) provide companies, customers, and other agents with information related to greenhouse gas (GHG) emissions from the life cycle of products, identifying key points in the supply chain, potential risks, and opportunities of improvement. This paper briefly examines how the method composed of financial statements (MC3) (MC3, as coined from the name of the method in Spanish, i.e., método compuesto de las cuentas contables.) approaches to specific requirements related to the assessment of product GHG emissions, pointing out the contribution of this method to assessing and communicating the carbon footprint of products.     

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.

     

Estimating the greenhouse gas footprint of Knorr

Purpose  

Greenhouse gas (GHG) emissions have been identified as one of Unilever’s priority environmental impact themes: this assessment was therefore conducted to help the Knorr brand measure and understand the GHG emissions related to its product portfolio, identify opportunities to manage GHG emissions in the Unilever-owned operations (manufacture) and influence managed reductions elsewhere in the Knorr product lifecycles, and assess the impact of the brand’s innovation and portfolio strategies on its GHG footprint.     

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products—a case study on laundry washing in Europe

Purpose

Variability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.

Methods

Data from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.

Results and discussion

Both inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5?×?10² g CO_2?eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.

Conclusions

The combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

     

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.

Carbon footprint and embodied energy assessment of a civil works program in a residential estate of Western Australia

Purpose

With building construction and demolition waste accounting for 50 % of land fill space, the diversion of reusable materials is essential for Perth”s environment. The reuse and recovery of embodied energy-intensive construction materials during civil engineering works programs can offer significant energy savings and assist in the mitigation of the carbon footprint.

Methods

A streamlined life cycle assessment, with limited focus, was carried out to determine the carbon footprint and embodied energy associated with a 100-m section of road base. A life cycle inventory of inputs (energy and materials) for all processes that occurred during the development of a 100-m road section was developed. Information regarding the energy and materials used for road construction work was obtained from the Perth-based firm, Cossill and Webley, Consulting Engineers. These inputs were inserted into Simapro LCA software to calculate the associated greenhouse gas emissions and embodied energy required for the construction and maintenance of a 100-m road section using. Two approaches were employed; a traditional approach that predominantly employed virgin materials, and a recycling approach.

Results and discussion

The GHG emissions and embodied energy associated with the construction of a 100-m road section using virgin materials are 180 tonnes of CO₂-e and 10.7 terajoules (TJ), respectively. The substitution of crushed rock with recycled brick road base does not appear to reduce the carbon footprint in the pre-construction stage (i.e. from mining to material construction, plus transportation of materials to the construction site). However, this replacement could potentially offer environmental benefits by reducing quarrying activities, which would not only conserve native bushland but also reduce the loss of biodiversity along with reducing the space and cost requirements associated with landfill. In terms of carbon footprint, it appears that GHG emissions are reduced significantly when using recycled asphalt, as opposed to other materials. About 22 to 30 % of greenhouse gas (GHG) emissions can be avoided by replacing 50 to 100 % of virgin asphalt with Reclaimed Asphalt Pavement (RAP) during the maintenance period.

Conclusions

The use of recycled building and road construction materials such as asphalt, concrete, and limestone can potentially reduce the embodied energy and greenhouse gas emissions associated with road construction. The recycling approach that uses 100 % reused crushed rock base and recycled concrete rubble, and 15 % RAP during the maintenance period could reduce the total carbon footprint by approximately 6 %. This large carbon saving in pavement construction is made possible by increasing the percentage of RAP in the wearing course.     

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.     

Carbon footprint of a Cavendish banana supply chain

Purpose

Bananas are one of the highest selling fruits worldwide, and for several countries, bananas are an important export commodity. However, very little is known about banana’s contribution to global warming. The aims of this work were to study the greenhouse gas emissions of bananas from cradle to retail and cradle to grave and to assess the potential of reducing greenhouse gas (GHG) emissions along the value chain.

Methods

Carbon footprint methodology based on ISO-DIS 14067 was used to assess GHG emissions from 1 kg of bananas produced at two plantations in Costa Rica including transport by cargo ship to Norway. Several methodological issues are not clearly addressed in ISO 14067 or the LCA standards 14040 and ISO 14044 underpinning 14067. Examples are allocation, allocation in recycling, representativity and system borders. Methodological choices in this study have been made based on other standards, such as the GHG Protocol Products Standard.

Results and discussion

The results indicate that bananas had a carbon footprint (CF) on the same level as other tropical fruits and that the contribution from the primary production stage was low. However, the methodology used in this study and the other comparative studies was not necessarily identical; hence, no definitive conclusions can be drawn. Overseas transport and primary production were the main contributors to the total GHG emissions. Including the consumer stage resulted in a 34 % rise in CF, mainly due to high wastage. The main potential reductions of GHG emissions were identified at the primary production, within the overseas transport stage and at the consumer.

Conclusions

The carbon footprint of bananas from cradle to retail was 1.37 kg CO₂ per kilogram banana. GHG emissions from transport and primary production could be significantly reduced, which could theoretically give a reduction of as much as 44 % of the total cradle-to-retail CF. The methodology was important for the end result. The choice of system boundaries gives very different results depending on which life cycle stages and which unit processes are included. Allocation issues were also important, both in recycling and in other processes such as transport and storage. The main uncertainties of the CF result are connected to N₂O emissions from agriculture, methane emissions from landfills, use of secondary data and variability in the primary production data. Thus, there is a need for an internationally agreed calculation method for bananas and other food products if CFs are to be used for comparative purposes.     

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.     

How does co-product handling affect the carbon footprint of milk? Case study of milk production in New Zealand and Sweden

Purpose  

This paper investigates different methodologies of handling co-products in life cycle assessment (LCA) or carbon footprint (CF) studies. Co-product handling can have a significant effect on final LCA/CF results, and although there are guidelines on the preferred order for different methods for handling co-products, no agreed understanding on applicable methods is available. In the present study, the greenhouse gases (GHG) associated with the production of 1 kg of energy-corrected milk (ECM) at farm gate is investigated considering co-product handling.     

A methodology for separating uncertainty and variability in the life cycle greenhouse gas emissions of coal-fueled power generation in the USA

Purpose

Results of life cycle assessments (LCAs) of power generation technologies are increasingly reported in terms of typical values and possible ranges. Extents of these ranges result from both variability and uncertainty. Uncertainty may be reduced via additional research. However, variability is a characteristic of supply chains as they exist; as such, it cannot be reduced without modifying existing systems. The goal of this study is to separately quantify uncertainty and variability in LCA.

Methods

In this paper, we present a novel method for differentiating uncertainty from variability in life cycle assessments of coal-fueled power generation, with a specific focus on greenhouse gas emissions. Individual coal supply chains were analyzed for 364 US coal power plants. Uncertainty in CO₂ and CH₄ emissions throughout these supply chains was quantified via Monte Carlo simulation. The method may be used to identify key factors that drive the range of life cycle emissions as well as the limits of precision of an LCA.

Results and discussion

Using this method, we statistically characterized the carbon footprint of coal power in the USA in 2009. Our method reveals that the average carbon footprint of coal power (100 year time horizon) ranges from 0.97 to 1.69 kg CO₂eq/kWh of generated electricity (95 % confidence interval), primarily due to variability in plant efficiency. Uncertainty in the carbon footprints of individual plants spans a factor of 1.04 for the least uncertain plant footprint to a factor of 1.2 for the most uncertain plant footprint (95 % uncertainty intervals). The uncertainty in the total carbon footprint of all US coal power plants spans a factor of 1.05.

Conclusions

We have developed and successfully implemented a framework for separating uncertainty and variability in the carbon footprint of coal-fired power plants. Reduction of uncertainty will not substantially reduce the range of predicted emissions. The range can only be reduced via substantial changes to the US coal power infrastructure. The finding that variability is larger than uncertainty can obviously not be generalized to other product systems and impact categories. Our framework can, however, be used to assess the relative influence of uncertainty and variability for a whole range of product systems and environmental impacts.     

Carbon footprint of pomegranate (<Emphasis Type="Italic">Punica granatum</Emphasis>) cultivation in a hyper-arid region in coastal Peru

Purpose

The cultivation of pomegranate worldwide has increased sharply in the past few years, mainly due to the growing perception that this fruit has numerous medical benefits. Despite the proliferation of studies delving into the properties of pomegranate from a medical and dietary perspective, its analysis from an environmental perspective has yet to be carried out in depth. Hence, the present study aims at understanding the life cycle environmental impacts in terms of greenhouse gas (GHG) emissions derived from the cultivation, processing and distribution abroad of fresh pomegranate grown at an innovative farm in a hyper-arid area in the region of Ica (Peru).

Methods

The international standards for life cycle methodologies were considered in order to obtain the overall carbon footprint (CFP) of fresh pomegranate cultivation, processing and distribution. Data acquisition was performed at the cultivation site and supported by the ecoinvent^® database, whereas GHG emissions were modelled using the IPCC 2007 method. In addition, biogenic carbon sequestration was included in the assessment, using two distinct models, a first one to model the aerial carbon sequestered by the pomegranate trees and a second, using the IPCC Soil Carbon Tool for soil storage.

Results and discussion

Annual results show that on-site GHG emissions can be mitigated to a great extent in the first years of production thanks to biogenic carbon sequestration. However, through time, this tendency is reverted, and in years of maximum pomegranate productivity, GHG emissions are estimated to outweigh those linked to sequestration, despite the relevant minimization of emissions when using innovative irrigation schemes as compared to the conventional flood irrigation in the region.

Conclusions

Despite the threat in terms of water depletion and security, the expansion of Peru’s agricultural frontier in hyper-arid areas appears to be a feasible strategy for carbon fixation, although current agricultural practices, such as the use of machinery or electricity, need to be optimized to make positive the carbon balance.

     

Carbon footprint and air emissions inventories for US honey production: case studies

Purpose

The primary purpose of this study is to estimate the life cycle greenhouse gas (GHG) emissions (carbon footprint) and criteria pollutant emissions during honey production and processing for US conditions based on several case studies of different scale beekeeping and processing operations. Commercial beekeeping operations yield two coproducts, honey and pollination services. These two products present an interesting coproduct allocation problem since beekeeping operations cannot be clearly subdivided, pollination services do not have a substitutable product or service, and pollination services cannot be characterized by physical properties for value-based allocation. Thus, a secondary purpose is to identify an appropriate allocation method and to discuss how the choice of allocation strategies influences the outcomes.

Methods

The commercial honey production supply chain comprises the following two primary steps: raw honey production by beekeepers and honey processing and packaging by processors. A case study approach was used based on detailed operation data provided by several beekeepers and processors from key honey-producing regions in the USA. Process-based life cycle assessment was conducted following the ISO guidelines, and economic allocation was used as a baseline method for coproduct allocation.

Results and discussion

Life cycle modeling of one complete commercial supply chain (raw honey production, transport to a processer, and processing) shows that total life cycle GHG emissions range from 0.67 to 0.92 kg CO₂ equivalent/kg of processed honey; however, outcomes show significant variability. Results show commercial honey production emits more GHGs and criteria pollutants than processing. Truck transport of bees is the dominant contributor of both GHG emissions and criteria pollutants within the life cycle of raw honey production. However, honey processing, which depends on natural gas and electricity, contributes a significant fraction of SO _x . These results are based on economic allocation among beekeeping coproducts. In addition to economic allocation, subdivision was applied to beekeeping activities. Because hive management (feed and medication) could not be further subdivided, a bounded range was generated for raw honey production, where the lower and upper bounds represent two extremes where all the environmental burdens associated with hive management were allocated to pollination or honey production.

Conclusions

Economic allocation tends to fall near or below the lower bound for the subdivision method. Interestingly, some beekeepers reported that their hive management practices were driven more by demand for pollination services than honey, which seems to be reflected in the coordination of lower-bound subdivision and economic allocation results.     

Reference and functional unit can change bioenergy pathway choices

Purpose

This study aims to compare the life cycle greenhouse gas (GHG) emissions of two cellulosic bioenergy pathways (i.e., bioethanol and bioelectricity) using different references and functional units. It also aims to address uncertainties associated with a comparative life cycle analysis (LCA) for the two bioenergy pathways.

Methods

We develop a stochastic, comparative life cycle GHG analysis model for a switchgrass-based bioenergy system. Life cycle GHG offsets of the biofuel and bioelectricity pathways for cellulosic bioenergy are compared. The reference system for bioethanol is the equivalent amount of gasoline to provide the same transportation utility (e.g., vehicle driving for certain distance) as bioethanol does. We use multiple reference systems for bioelectricity, including the average US grid, regional grid in the USA according to the North American Electric Reliability Corporation (NERC), and average coal-fired power generation, on the basis of providing the same transportation utility. The functional unit is one unit of energy content (MJ). GHG offsets of bioethanol and bioelectricity relative to reference systems are compared in both grams carbon dioxide equivalents per hectare of land per year (g CO₂-eq/ha-yr) and grams carbon dioxide equivalents per vehicle kilometer traveled (g CO₂-eq/km). For the latter, we include vehicle cycle to make the comparison meaningful. To address uncertainty and variability, we derive life cycle GHG emissions based on probability distributions of individual parameters representing various unit processes in the life cycle of bioenergy pathways.

Results and discussion

Our results show the choice of reference system and functional unit significantly changes the competition between switchgrass-based bioethanol and bioelectricity. In particular, our results show that the bioethanol pathway produces more life cycle GHG emissions than the bioelectricity pathway on a per unit energy content or a per unit area of crop land basis. However, the bioethanol pathway can offer more GHG offsets than the bioelectricity pathway on a per vehicle kilometer traveled basis when using bioethanol and bioelectricity for vehicle operation. Given the current energy mix of regional grids, bioethanol can potentially offset more GHG emissions than bioelectricity in all grid regions of the USA.

Conclusions

The reference and functional unit can change bioenergy pathway choices. The comparative LCA of bioenergy systems is most useful for decision support only when it is spatially explicit to address regional specifics and differences. The difference of GHG offsets from bioethanol and bioelectricity will change as the grid evolves. When the grids get cleaner over time, the favorability of bioethanol for GHG offsets increases.     

Improving the integrated hybrid LCA in the upstream scope 3 emissions inventory analysis

Purpose

The protocols of carbon footprints generally define three scopes for different greenhouse gas (GHG) emissions levels. The most important carbon footprint emissions source comes from upstream indirect emissions of scope 3 for products that do not consume energy during their use phase. Upstream scope 3 GHG inventory can usually be analyzed through input–output or hybrid LCA analysis. The economic input–output life cycle analysis (EIO-LCA) and the hybrid LCA model have been widely used for this purpose. However, a cutoff error exists in the hybrid model, and the lack of a truncation criterion between process and IO inventory may lead to a high level of uncertainty in the hybrid model. This study attempts to improve the problem of cutoff uncertainty in hybrid LCA and proposes a method to minimize the cutoff uncertainty.

Methods

The way to improve the cutoff uncertainty could follow two steps. First, through the IO inventory analysis of EIO-LCA, we can define the emissions by various tiers of product components. The IO inventory indicator can provide a definitive criterion for the process inventory of the hybrid model. Second, we connect the process- and IO-LCI according to the IO inventory result. The advantage of the process inventory is that it provides detailed manufacturing information on the target while the IO encompasses a complete system boundary. For improvements, the process inventory can catch the most important process of the GHG emissions, and the IO inventory could compensate for the remainder of the incomplete system inventory.

Results and discussion

In this case study, the printed circuit board production process is used to evaluate the efficiency of the improved method. The threshold M was set to 70 in this case study, and the IO inventory provides the remaining 30 %. For the integrated hybrid model, the tier 3 process inventory takes only 64 % while the incorporation of the proposed method can include 92 % of the total emissions, which shows the cutoff uncertainty can be reduced through the improvement.

Conclusions

This study provides a clear guideline for process and IO cutoff criteria, which can help the truncation uncertainty. When higher precision is required, process LCI will need to play an important role, and thus, a higher M value should be set. In this situation, the emissions from IO-LCI would be smaller than the emissions from the process LCI. The appropriate solution would attain a comfortable balance between data accuracy and time and labor consumption.     

Life cycle assessment of energy and GHG emissions during ethanol production from grass straws using various pretreatment processes

Purpose  

The aim of this study was to perform a well-to-pump life cycle assessment (LCA) to investigate the overall net energy balance and environmental impact of bioethanol production using Tall Fescue grass straw as feedstock. The energy requirements and greenhouse gas (GHG) emissions were compared to those of gasoline to explore the potential of bioethanol as sustainable fuel.     

Including CO2 implications of land occupation in LCAs—method and example for livestock products

Purpose

Until recently, life cycle assessments (LCAs) have only addressed the direct greenhouse gas emissions along a process chain, but ignored the CO₂ emissions of land-use. However, for agricultural products, these emissions can be substantial. Here, we present a new methodology for including the implications of land occupation for CO₂ emissions to realistically reflect the consequences of consumers?? decisions.

Method

In principle, one can distinguish five different approaches of addressing the CO₂ consequences of land occupation: (1) assuming constant land cover, (2) land-use change related to additional production of the product under consideration, (3) historic land-use change, assuming historical relations between existing area and area expansion (4) land-use change related to less production of the product under consideration (??missed potential carbon sink?? of land occupation), and (5) an approach of integrating land conversion emissions and delayed uptake due to land occupation. Approach (4) is presented in this paper, using LCA data on land occupation, and carbon dynamics from the IMAGE model. Typically, if less production occurs, agricultural land will be abandoned, leading to a carbon sink when vegetation is regrowing. This carbon sink, which does not occur if the product would still be consumed, is thus attributed to the product as ??missed potential carbon sink??, to reflect the CO₂ implications of land occupations.

Results

We analyze the missed potential carbon sink by relating land occupation data from LCA studies to the potential carbon sink as calculated by an Integrated Global Assessment Model and its process-based, spatially explicit carbon cycle model. Thereby, we account for regional differences, heterogeneity in land-use, and different time horizons. Example calculations for several livestock products show that the CO₂ consequences of land occupation can be in the same order of magnitude as the other process related greenhouse gas emissions of the LCA, and depend largely on the production system. The highest CO₂ implications of land occupation are calculated for beef and lamb, with beef production in Brazil having a missed potential carbon sink more than twice as high as the other GHG emissions.

Conclusions

Given the significant contribution of land occupation to the total GHG balance of agricultural products, they need to be included in life cycle assessments in a realistic way. The new methodology presented here reflects the consequences of producing or not producing a certain commodity, and thereby it is suited to inform consumers fully about the consequences of their choices.     

Life cycle assessment of a field-grown red maple tree to estimate its carbon footprint components

Purpose  

This study analyzes the interrelated components in the production of a 5-cm caliper, field-grown, spade-dug Acer rubrum ‘October Glory’ tree in terms of their contributions to the carbon footprint, global warming potential (GWP), of this balled and burlapped product during production and its complete life cycle.     

A comparison of the GHG emissions caused by manufacturing tissue paper from virgin pulp or recycled waste paper

Purpose

The aim of this work is to compare greenhouse gas (GHG) emissions from producing tissue paper from virgin pulp (VP) or recycled waste paper (RWP). In doing so, the study aims to inform decision makers at both company and national levels which are the main causes of emissions and to suggest the actions required to reduce pollution.

Methods

An attributional life cycle assessment (LCA) was performed in order to estimate and compare the GHG emissions of the two processes. LCA allows us to assess how the choice of raw material for VP and RWP processes influences total GHG emissions of tissue paper production, what are the main drivers behind these emissions and how do the direct materials; energy requirements and transportation contribute to the generation of emissions. The cradle-to-gate approach is carried out.

Results and discussion

The results show that demands for both thermal energy and electricity are higher for the RWP than for the VP if only the manufacturing stages are considered. However, a different picture emerges when the analysis looks at the entire life cycle of the production. GHG from the VP are about 30 % higher than the RWP, over the life cycle emitting 568 kg CO₂ eq more per kilogram of tissue paper. GHG emissions from the wood pulping alone were 559 g CO₂ eq per kilogram of tissue paper, three times higher than waste paper collection and transportation.

Conclusions

In terms of GHG emissions from cradle to gate, the recycled process less intensive than the virgin one for two reasons. First, as shown in the results the total GHG emissions from RWP are lower than those from VP due to relatively lower energy and material requirements. Second is the non-recyclability nature of tissue paper. Because the tissue paper is the last use of fibre, using RWP as an input would be preferable over using VP. The environmental profile of the tissue products both from RWP and VP can be improved if the following conditions are considered by the company. First, the company should consider implementing a cogeneration unit to simultaneously generate both useful heat and electricity. Second, it may consider changing the VP mix, in order to avoid the emissions associated with long distance transpiration effort. Third, there is the option of using sludge as fuel, which would reduce the total fossil fuel requirement.     

Life cycle carbon footprint of the packaging and transport of New Zealand kiwifruit

Purpose

The aim of this study is to assess the life cycle carbon footprint of the New Zealand kiwifruit packaging and transport supply chain to retailers in two major markets (Japan and Germany). Results of this study have been used to identify areas of the New Zealand kiwifruit packaging and transport supply chain that contribute significantly to the carbon footprint and to identify options for reduction.

Methods

This study is based on the ISO standards for life cycle assessment (namely, ISO 14040:2006 and ISO 14044:2006). The PAS 2050 also provided further methodological guidance. Primary packaging data were sourced from Zespri’s suppliers. End-of-life data were sourced from the market and waste statistics of the relevant countries. Gabi 4.4 was used for upstream material information and modelling.

Results and discussion

The carbon footprint of the packaging and transport of kiwifruit ranged from 0.33 to 0.67 kg CO₂e per kilogram of fruit delivered to a store depending on pack type and market. Shipping accounted for the majority of these emissions (58–82 %), and Zespri is actively working with shipping companies to reduce this. There are also opportunities to reduce the carbon footprint through reducing the amount of fruit repacked in the market, using trains for long-distance transport and increasing packaging recycling rates.

Conclusions

There is a range of options for reducing the carbon footprint of the New Zealand kiwifruit packaging and transport supply chain. These will tend to be incremental (i.e. a number of small gains) and would involve working closely with partners in the supply chain. Options include increased efficiency in shipping, use of trains for land transport, reductions in the addition of structural packaging in the market, managing the product mix to minimize those supply chains with a higher carbon footprint, identifying alternative material for components of the packaging, replacing the use of polystyrene clamshells with alternative materials or plastic bags and maximizing recycling rates along all stages of the supply chain.