Environmental Profile of Brazilian Green Coffee (6 pp)

Goal, Scope and Background

Brazil is the world's biggest producer of coffee beans with approx. a 30% market share. Depending on climate conditions, approx. 30 million bags of coffee beans are exported annually from Brazil, while domestic consumption is around 10 million bags, which makes Brazil the world's third largest coffee-consuming country. Therefore, the goal of this paper is to present the LCA of green coffee produced in Brazil for the reference crops 2001/02 and 2002/03 in order to generate detailed production inventory data as well as to identify the potential environmental impacts of its tillage in order to realize how to reduce those impacts and increase the environmental sustainability of this product. Only the inputs and outputs relative to the coffee tillage were considered. The production of fertilizers, correctives and pesticides were not included in the boundary, but only their amounts. The functional unit selected for this study was 1,000 kg of green coffee destined for exportation.

Methods

The LCI was performed according to the ISO 14040 standard series. All information considered in this study (use of water, fossil based energy, fertilizers and chemicals) were taken up in in-depth data collection and evaluation by questionnaires applied on a farm level and/or received by mail. Four Brazilian coffee producer regions were evaluated: Cerrado Mineiro, South of Minas Gerais State, the Marília and Alta Mogiana regions in São Paulo State. These regions have the following geographic coordinates: 44 to 50° W longitude and 18 to 24° S latitude. The data refer to a production of 420,000 coffee bean bags and a productive area of approx. 14,300 ha. The varieties of coffee beans considered in this study were Mundo Novo, Catuaí (yellow and red), Icatu (yellow and red), Catucaí (yellow and red) and Obatã. Farm specific data along with agricultural production data have been combined to elaborate a coffee cultivation inventory, which will be applied in an emissions estimation.

Results and Conclusion

The production of 1,000 kg of green coffee in Brazil requires approx. 11,400 kg of water, 94 kg of diesel, 270 kg of fertilizers as NPK, 900 kg of total fertilizers, 620 kg of correctives, 10 kg of pesticides and 0.05 hectare of annual land use. Outputs related to these functional units are approx. 3,000 kg of waste water from coffee washing, 8,500 kg of waste water from the wet method and 750 kg of organic residue that is reincorporated to the tillage as fertilizer. The publication of an LCI of agricultural products is a fundamental step for understanding the potential environmental impacts of each tillage and then establishes the basis for product sustainability. In this way, this work is the first Brazilian initiative for applying LCA to coffee cultivation.

Recommendation and Perspective

Different agricultural practices demonstrate different environmental profiles. The amount of agricultural pesticide is directly related to agricultural practices as tillage rotation, density of plants, etc. This study supplied important results for a better correlation of the agricultural practices and potential environmental impacts of coffee. Future updates of this study will show the evolution of the natural resource management such as land use, new agricultural practices, lower fertilizers and chemicals use.     

Data quality

A methodology is presented that enables incorporating expert judgment regarding the variability of input data for environmental life cycle assessment (LCA) modeling. The quality of input data in the life-cycle inventory (LCI) phase is evaluated by LCA practitioners using data quality indicators developed for this application. These indicators are incorporated into the traditional LCA inventory models that produce non-varying point estimate results (i.e., deterministic models) to develop LCA inventory models that produce results in the form of random variables that can be characterized by probability distributions (i.e., stochastic models). The outputs of these probabilistic LCA models are analyzed using classical statistical methods for better decision and policy making information. This methodology is applied to real-world beverage delivery system LCA inventory models. The inventory study results for five beverage delivery system alternatives are compared using statistical methods that account for the variance in the model output values for each alternative. Sensitivity analyses are also performed that indicate model output value variance increases as input data uncertainty increases (i.e., input data quality degrades). Concluding remarks point out the strengths of this approach as an alternative to providing the traditional qualitative assessment of LCA inventory study input data with no efficient means of examining the combined effects on the model results. Data quality assessments can now be captured quantitatively within the LCA inventory model structure. The approach produces inventory study results that are variables reflecting the uncertainty associated with the input data. These results can be analyzed using statistical methods that make efficient quantitative comparisons of inventory study alternatives possible. Recommendations for future research are also provided that include the screening of LCA inventory model inputs for significance and the application of selection and ranking techniques to the model outputs.     

Missing inventory estimation tool using extended input-output analysis

Intention, Goal, Scope, Background  Input-Output Analysis (IOA) has recently been introduced to Life Cycle Assessment (LCA). In applying IOA to LCA studies, however, it is important to note that there are both advantages and disadvantages. Objectives  This paper aims to provide a better understanding of the advantages and disadvantages of adopting IOA in LCA, and introduces the methodology and principles of the Missing Inventory Estimation Tool (MIET) as one of the approaches to combine the strengths of process-specific LCA and IOA. Additionairy, we try to identify a number of possible errors in the use of IOA for LCA purposes, due to confusion between industry output and commodity, consumer’s price and producer’s price. Method  MIET utilises the 1996 US input-output table and various environmental statistics. It is based on an explicit distinction between commodity and industry output. Results and Discussion  MIET is a self-contained, publicly available database which can be applied directly in LCA studies to estimate missing processes. Conclusion  By adopting MILT results in existing, process-based, life-cycle inventory (LCI), LCA practitioners can fully utilise the process-specific information while expanding the system boundary. Recommendations and Outlook  MIET will be continuously updated to reflect both methodological developments and newly available data sources. For supporting information sec http:// wwwJeidenuniv.nl/cml/ssp/softwarc/miet.     

Methodology for systematic analysis and improvement of manufacturing unit process life-cycle inventory (UPLCI)—CO2PE! initiative (cooperative effort on process emissions in manufacturing). Part 1: Methodology description

Purpose  

This report proposes a life-cycle analysis (LCA)-oriented methodology for systematic inventory analysis of the use phase of manufacturing unit processes providing unit process datasets to be used in life-cycle inventory (LCI) databases and libraries. The methodology has been developed in the framework of the CO₂PE! collaborative research programme (CO2PE! 2011a) and comprises two approaches with different levels of detail, respectively referred to as the screening approach and the in-depth approach.     

Quantifying life cycle inventories of agricultural field operations by considering different operational parameters

Purpose

The ability to estimate fuel and lubricant consumption as well as depreciated weight of agricultural machinery used for field operations is very useful for energy and environmental analyses. In this study, life cycle inventory data of agricultural field operations were established by considering different parameters of such operations.

Methods

Agricultural operations considered in this study include tillage, cultivation, planting, harvesting and post-harvest operations. For these operations, the fuel and lubricant consumption as well as depreciated weight of tractors, combine harvesters and agricultural implements was estimated by considering different operational parameters such as tractor power, field condition, depth of operation, soil condition, tractor type, operational capacity of machine, width of operation and speed. Technical standards were used to estimate different types of power required for most agricultural operations (drawbar power, rotary power and motion power). The standards were then used to evaluate the variability of the fuel and lubricant consumption as well as depreciated weight of the implements by varying the aforementioned parameters.

Results and discussion

The results were compared to those that can be calculated with other approaches for life cycle inventory analysis of agricultural operations. Such comparison indicates that by using different parameters, representing the diverse local conditions of different field operations, a great variability of the results is obtained. For instance, diesel fuel consumption of tillage operations ranges from 12.6 to 76.0 L ha^?1, with an average of 34.15 L ha^?1 and standard deviation of 11.7 L ha^?1. Such representativeness of the different conditions of each field operation cannot be modelled with other tools or via the use of standard LCI datasheets.

Conclusions

The final result of this study is a novel approach for the life cycle inventory analysis of agricultural operations, in terms of fuel and lubricant consumption and of depreciated weight of the machines, which are estimated by simply selecting the operational parameters which best represent the effect of local conditions.

     

Life cycle assessment (LCA) applied to the process industry: a review

Purpose

Life cycle assessment (LCA) methodology is a well-established analytical method to quantify environmental impacts, which has been mainly applied to products. However, recent literature would suggest that it has also the potential as an analysis and design tool for processes, and stresses that one of the biggest challenges of this decade in the field of process systems engineering (PSE) is the development of tools for environmental considerations.

Method

This article attempts to give an overview of the integration of LCA methodology in the context of industrial ecology, and focuses on the use of this methodology for environmental considerations concerning process design and optimization.

Results

The review identifies that LCA is often used as a multi-objective optimization of processes: practitioners use LCA to obtain the inventory and inject the results into the optimization model. It also shows that most of the LCA studies undertaken on process analysis consider the unit processes as black boxes and build the inventory analysis on fixed operating conditions.

Conclusions

The article highlights the interest to better assimilate PSE tools with LCA methodology, in order to produce a more detailed analysis. This will allow optimizing the influence of process operating conditions on environmental impacts and including detailed environmental results into process industry.     

Integration of life cycle assessment in the environmental information system

Background, aim, and scope  As the sustainability improvement becomes an essential business task of industry, a number of companies are adopting IT-based environmental information systems (EIS). Life cycle assessment (LCA), a tool to improve environmental friendliness of a product, can also be systemized as a part of the EIS. This paper presents a case of an environmental information system which is integrated with online LCA tool to produce sets of hybrid life cycle inventory and examine its usefulness in the field application of the environmental management. Main features  Samsung SDI Ltd., the producer of display panels, has launched an EIS called Sustainability Management Initiative System (SMIS). The system comprised modules of functions such as environmental management system (EMS), green procurement (GP), customer relation (e-VOC), eco-design, and LCA. The LCA module adopted the hybrid LCA methodology in the sense that it combines process LCA for the site processes and input–output (IO) LCA for upstream processes to produce cradle-to-gate LCA results. LCA results from the module are compared with results of other LCA studies made by the application of different methodologies. The advantages and application of the LCA system are also discussed in light of the electronics industry. Results and discussion  LCA can play a vital role in sustainability management by finding environmental burden of products in their life cycle. It is especially true in the case of the electronics industry, since the electronic products have some critical public concerns in the use and end-of-life phase. SMIS shows a method for hybrid LCA through online data communication with EMS and GP module. The integration of IT-based hybrid LCA in environmental information system was set to begin in January 2006. The advantage of the comparing and regular monitoring of the LCA value is that it improves the system completeness and increases the reliability of LCA. By comparing the hybrid LCA and process LCA in the cradle-to-gate stage, the gap between both methods of the 42-in. standard definition plasma display panel (PDP) ranges from 1% (acidification impact category) to −282% (abiotic resource depletion impact category), with an average gap of 68.63%. The gaps of the impact categories of acidification (AP), eutrophication (EP), and global warming (GWP) are relatively low (less than 10%). In the result of the comparative analysis, the strength of correlation of three impact categories (AP, EP, GWP) shows that it is reliable to use the hybrid LCA when assessing the environmental impacts of the PDP module. Hybrid LCA has its own risk on data accuracy. However, the risk is affordable when it comes to the comparative LCA among different models of similar product line of a company. In the results of 2 years of monitoring of 42-in. Standard definition PDP, the hybrid LCA score has been decreased by 30%. The system also efficiently shortens man-days for LCA study per product. This fact can facilitate the eco-design of the products and can give quick response to the customer's inquiry on the product's eco-profile. Even though there is the necessity for improvement of process data currently available, the hybrid LCA provides insight into the assessments of the eco-efficiency of the manufacturing process and the environmental impacts of a product. Conclusions and recommendations  As the environmental concerns of the industries increase, the need for environmental data management also increases. LCA shall be a core part of the environmental information system by which the environmental performances of products can be controlled. Hybrid type of LCA is effective in controlling the usual eco-profile of the products in a company. For an industry, in particular electronics, which imports a broad band of raw material and parts, hybrid LCA is more practicable than the classic LCA. Continuous efforts are needed to align input data and keep conformity, which reduces data uncertainty of the system.     

Popularize or publish? Growth in Australia

While the community of life cycle assessment (LCA) practitioners in Australia has developed relatively recently and is naturally smaller than in Europe or the United States, it is a vibrant community. The idea for this article was to examine the contribution made to LCA development by Australians, the rate of growth of this work, and its industry sectoral focus by quantitative analysis of publication data from four key LCA journals. Although these data suggest that the country’s publication rate has not changed much in the last 8 years and fallen relative to the international rate, applied LCA is playing an increasing role in the work of Australian industry and government. Current efforts of the Australian LCA Society are focused on the renewal and expansion of available inventory resources, standardization of life cycle inventory methodology, and improvement of impact assessment processes.     

Uncertainty of global warming potential for milk production on a New Zealand farm and implications for decision making

Background, aim and scope  

As a food exporting nation, New Zealand recognises that the Global Warming Potential (GWP) impact of agriculture has become important to food customers. Food production policy and industry analysts make GWP decisions based on greenhouse gas inventory and life cycle assessment (LCA) results. For decision making, the level of confidence associated with information is important. However, treatment of uncertainty has been problematic in LCA, especially in agricultural systems. In this paper, the GWP of 1 kg of milk was used as a case study to test the feasibility of quantifying uncertainties by Monte Carlo simulation in an LCA applied to an agriculture product. The study also contributes to the development of good practice and has implications for the incorporation of uncertainties into decision making.     

A spatially explicit life cycle inventory of the global textile chain

Background, aim, and scope  Life cycle analyses (LCA) approaches require adaptation to reflect the increasing delocalization of production to emerging countries. This work addresses this challenge by establishing a country-level, spatially explicit life cycle inventory (LCI). This study comprises three separate dimensions. The first dimension is spatial: processes and emissions are allocated to the country in which they take place and modeled to take into account local factors. Emerging economies China and India are the location of production, the consumption occurs in Germany, an Organisation for Economic Cooperation and Development country. The second dimension is the product level: we consider two distinct textile garments, a cotton T-shirt and a polyester jacket, in order to highlight potential differences in the production and use phases. The third dimension is the inventory composition: we track CO₂, SO₂, NO _x , and particulates, four major atmospheric pollutants, as well as energy use. This third dimension enriches the analysis of the spatial differentiation (first dimension) and distinct products (second dimension). Materials and methods  We describe the textile production and use processes and define a functional unit for a garment. We then model important processes using a hierarchy of preferential data sources. We place special emphasis on the modeling of the principal local energy processes: electricity and transport in emerging countries. Results  The spatially explicit inventory is disaggregated by country of location of the emissions and analyzed according to the dimensions of the study: location, product, and pollutant. The inventory shows striking differences between the two products considered as well as between the different pollutants considered. For the T-shirt, over 70% of the energy use and CO₂ emissions occur in the consuming country, whereas for the jacket, more than 70% occur in the producing country. This reversal of proportions is due to differences in the use phase of the garments. For SO₂, in contrast, over two thirds of the emissions occur in the country of production for both T-shirt and jacket. The difference in emission patterns between CO₂ and SO₂ is due to local electricity processes, justifying our emphasis on local energy infrastructure. Discussion  The complexity of considering differences in location, product, and pollutant is rewarded by a much richer understanding of a global production–consumption chain. The inclusion of two different products in the LCI highlights the importance of the definition of a product's functional unit in the analysis and implications of results. Several use-phase scenarios demonstrate the importance of consumer behavior over equipment efficiency. The spatial emission patterns of the different pollutants allow us to understand the role of various energy infrastructure elements. The emission patterns furthermore inform the debate on the Environmental Kuznets Curve, which applies only to pollutants which can be easily filtered and does not take into account the effects of production displacement. We also discuss the appropriateness and limitations of applying the LCA methodology in a global context, especially in developing countries. Conclusions  Our spatial LCI method yields important insights in the quantity and pattern of emissions due to different product life cycle stages, dependent on the local technology, emphasizing the importance of consumer behavior. From a life cycle perspective, consumer education promoting air-drying and cool washing is more important than efficient appliances. Recommendations and perspectives  Spatial LCI with country-specific data is a promising method, necessary for the challenges of globalized production–consumption chains. We recommend inventory reporting of final energy forms, such as electricity, and modular LCA databases, which would allow the easy modification of underlying energy infrastructure. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Attributional and consequential LCA of milk production

Background, aim and scope  Different ways of performing a life cycle assessment (LCA) are used to assess the environmental burden of milk production. A strong connection exists between the choice between attributional LCA (ALCA) and consequential LCA (CLCA) and the choice of how to handle co-products. Insight is needed in the effect of choice on results of environmental analyses of agricultural products, such as milk. The main goal of this study was to demonstrate and compare ALCA and CLCA of an average conventional milk production system in The Netherlands. Materials and methods  ALCA describes the pollution and resource flows within a chosen system attributed to the delivery of a specified amount of the functional unit. CLCA estimates how pollution and resource flows within a system change in response to a change in output of the functional unit. For an average Dutch conventional milk production system, an ALCA (mass and economic allocation) and a CLCA (system expansion) were performed. Impact categories included in the analyses were: land use, energy use, climate change, acidification and eutrophication. The comparison was based on four criteria: hotspot identification, comprehensibility, quality and availability of data. Results  Total environmental burdens were lower when using CLCA compared with ALCA. Major hotspots for the different impact categories when using CLCA and ALCA were similar, but other hotspots differed in contributions, order and type. As experienced by the authors, ALCA and use of co-product allocation are difficult to comprehend for a consequential practitioner, while CLCA and system expansion are difficult to comprehend for an attributional practitioner. Literature shows concentrates used within ALCA will be more understandable for a feeding expert than the feed used within CLCA. Outcomes of CLCA are more sensitive to uncertainties compared with ALCA, due to the inclusion of market prospects. The amount of data required within CLCA is similar compared with ALCA. Discussion  The main cause of these differences between ALCA and CLCA is the fact that different systems are modelled. The goal of the study or the research question to be answered defines the system under study. In general, the goal of CLCA is to assess environmental consequences of a change in demand, whereas the goal of ALCA is to assess the environmental burden of a product, assuming a status-quo situation. Nowadays, however, most LCA practitioners chose one methodology independent of their research question. Conclusions  This study showed it is possible to perform both ALCA (mass and economic allocation) and CLCA (system expansion) of milk. Choices of methodology, however, resulted in differences in: total quantitative outcomes, hotspots, degree of understanding and quality. Recommendations and perspectives  We recommend LCA practitioners to better distinguish between ALCA and CLCA in applied studies to reach a higher degree of transparency. Furthermore, we recommend LCA practitioners of different research areas to perform similar case studies to address differences between ALCA and CLCA of the specific products as the outcomes might differ from our study.     

Modelling Representative Life Cycle Inventories for Swiss Arable Crops (9 pp)

Goal, Scope and Background Life cycle inventories (LCIs) of agricultural products, infrastructure, inputs and processes are required to optimise food supply chains. In the past, the use of LCA was hindered by the limited availability of databases with LCIs for such agricultural inputs, processes and products in combination with LCIs of other major economic sectors. The ecoinvent database covers this need for the Swiss, and to an extent, the European context. A suitable approach had to be outlined for defining representative datasets for products from arable crops, since there was no comprehensive survey of agricultural production.Methods No single data source was available for defining representative datasets for arable crops. It was therefore decided to define model crops on the basis of a variety of sources in collaboration with experts on the crops in question. The datasets were validated by experts and by comparison with literature. Field emissions were calculated using a set of models taking into account situation-specific parameters. Data defined by this procedure are more generally usable, but their definition is also more laborious. Results and Discussion Selected results (inventories and impact assessment) are presented for infrastructure (buildings, machinery), work processes, fertilisers, pesticides, seed and arable crop products. Infrastructure has a higher share of environmental impacts than in typical industrial processes, often due to low utilisation rates. Energy use is dominated by mechanisation, the use of mineral fertilisers (particularly nitrogen) and grain drying. Eutrophication is caused mainly by nitrogen compounds. In general, field emissions are of decisive importance for many environmental impacts. Conclusion and Outlook The ecoinvent database provides representative agricultural data for the Swiss, and to an extent, the European context. It also provides the meta-information necessary for deciding whether a dataset is suitable for the purpose of a particular LCA study. To further improve the representativeness of the datasets, an environmental farm monitoring network is required.     

Tillage and herbicide reduction mitigate the gap between conventional and organic farming effects on foraging activity of insectivorous bats

The increased use of pesticides and tillage intensification is known to negatively affect biodiversity. Changes in these agricultural practices such as herbicide and tillage reduction have variable effects among taxa, especially at the top of the trophic network including insectivorous bats. Very few studies compared the effects of agricultural practices on such taxa, and overall, only as a comparison of conventional versus organic farming without accurately accounting for underlying practices, especially in conventional where many alternatives exist. Divergent results founded in these previous studies could be driven by this lack of clarification about some unconsidered practices inside both conventional and organic systems. We simultaneously compared, over whole nights, bat activity on contiguous wheat fields of one organic and three conventional farming systems located in an intensive agricultural landscape. The studied organic fields (OT) used tillage (i.e., inversion of soil) without chemical inputs. In studied conventional fields, differences consisted of the following: tillage using few herbicides (T), conservation tillage (i.e., no inversion of soil) using few herbicides (CT), and conservation tillage using more herbicide (CTH), to control weeds. Using 64 recording sites (OT = 12; T = 21; CT = 13; CTH = 18), we sampled several sites per system placed inside the fields each night. We showed that bat activity was always higher in OT than in T systems for two (Pipistrellus kuhlii and Pipistrellus pipistrellus) of three species and for one (Pipistrellus spp.) of two genera, as well as greater species richness. The same results were found for the CT versus T system comparison. CTH system showed higher activity than T for only one genus (Pipistrellus spp.). We did not detect any differences between OT and CT systems, and CT showed higher activity than CTH system for only one species (Pipistrellus kuhlii). Activity in OT of Pipistrellus spp. was overall 3.6 and 9.3 times higher than CTH and T systems, respectively, and 6.9 times higher in CT than T systems. Our results highlight an important benefit of organic farming and contrasted effects in conventional farming. That there were no differences detected between the organic and one conventional system is a major result. This demonstrates that even if organic farming is presently difficult to implement and requires a change of economic context for farmers, considerable and easy improvements in conventional farming are attainable, while maintaining yields and approaching the ecological benefits of organic methods.     

Efficient information visualization in LCA: approach and examples

Aim, Scope and Background  The data-intensive nature of life cycle assessment (LCA), even for non-complex products, quickly leads to the utilization of various methods of representing the data in forms other than written characters. Up until now, traditional representations of life cycle inventory (LCI) data and environmental impact analysis (EIA) results have usually been based on 2D and 3D variants of simple tables, bar charts, pie charts and x/y graphs. However, these representation methods do not sufficiently address aspects such as representation of life cycle inventory information at a glance, filtering out data while summarizing the filtered data (so as to reduce the information load), and representation of data errors and uncertainty. Main Features  This new information representation approach with its glyph-based visualization method addresses the specific problems outlined above, encountered when analyzing LCA and EIA related information. In particular, support for multi-dimensional information representation, reduction of information load, and explicit data feature propagation are provided on an interactive, computer-aided basis. Results  Three-dimensional, interactive geometric objects, so called OM-glyphs, were used in the visualization method introduced, to represent LCA-related information in a multi-dimensional information space. This representation is defined by control parameters, which in turn represent spatial, geometric and retinal properties of glyphs and glyph formations. All relevant analysis scenarios allowed and valid can be visualized. These consist of combinations of items for the material and energy inventories, environmental items, life cycle phases and products, or their parts and components. Individual visualization scenarios, once computed and rendered on a computer screen, can then interactively be modified in terms of visual viewpoint, size, spatial location and detail of data represented, as needed. This helps to increase speed, efficiency and quality of the assessment performance, while at the same time considerably reducing mental load due to the more structured manner in which information is represented to the human expert. Conclusions  The previous paper in this series discussed the motivation for a new approach to efficient information visualization in LCA and introduced the essential basic principles. This second paper offers more insight into and discussion on technical details and the framework developed. To provide a means for better understanding the visualization method presented, examples have been given. The main purpose of the examples, as already indicated, is to demonstrate and make transparent the mapping of LCA related data and their contexts to glyph parameters. Those glyph parameters, in turn, are used to generate a novel form of sophisticated information representation which is transparent, clear and compact, features which cannot be achieved with any traditional representation scheme. Outlook  Final technical details of this approach and its framework will be presented and discussed in the next paper. Theoretical and practical issues related to the application of this visualization method to the computed life cycle inventory data of an actual industrial product will also be discussed in this next paper.     

Physicochemical modelling of the classical steelmaking route for life cycle inventory analysis

Goal, scope and background  

Integrating environmental issues into the traditional product design process, for powerful eco-efficiency, is now one of the major priorities for steelmakers. Life cycle assessment (LCA) is currently undertaken as the most holistic approach for assessing environmental impact and selecting new technologies to reduce emissions for steel industry. However, in order to identify new ways for environmental friendly production of steel, it is essential to carry out the process Life cycle inventory (LCI) which is the core part of LCA. According to LCA practitioners, the quality and the availability of data are the main important limiting factors when applying this methodology for new steelmaking processes without large industrial application. In this paper, we propose a new approach of LCIA of steelmaking, based on the simulation of traditional processes which guarantees the quality of data, the mass and the energy balances. This approach is validated for an existing integrated plant and will be used to assess the inventory for breakthrough steelmaking technologies.     

End-of-life of a polypropylene bumper skin

The aim of this article is to show how, at PSA peugeot-citroën, Life Cycle Assessment (LCA) is used as a tool to evaluate the environmental burdens associated with a product, a process or an activity by identifying and quantifying energy, material used and wastes released to the environment. In this paper, the LCA methodology is applied to a practical case study: the comparison of various end-of-life scenarios (recycling versus incineration with or without energy recovery with landfill as a reference) for a polypropylene (PP) bumper skin. All the LCA steps (goal, inventory, impacts assessment, interpretation) are developed in this study. It is shown that in the particular case of PP, incineration with energy recovery is on an environmental point of view between 30 and 60% recycling. However, due to some uncertainties on data quality, the absolute values of the inputs/outputs for the inventory step may not be sufficient to allow strong decision making and the use of the factorial experiments (Taguchi) is then proposed to select the dominant parameters of the study. Strong environmental conclusions can then be drawn from the study.     

System delimitation in agricultural consequential LCA

Background, aim, and scope

When dealing with system delimitation in environmental life cycle assessment (LCA), two methodologies are typically referred to: consequential LCA and attributional LCA. The consequential approach uses marginal data and avoids co-product allocation by system expansion. The attributional approach uses average or supplier-specific data and treats co-product allocation by applying allocation factors. Agricultural LCAs typically regard local production as affected and they only include the interventions related to the harvested area. However, as changes in demand and production may affect foreign production, yields and the displacement of other crops in regions where the agricultural area is constrained, there is a need for incorporating the actual affected processes in agricultural consequential LCA. This paper presents a framework for defining system boundaries in consequential agricultural LCA. The framework is applied to an illustrative case study; LCA of increased demand for wheat in Denmark. The aim of the LCA screening is to facilitate the application of the proposed methodology. A secondary aim of the LCA screening is to illustrate that there are different ways to meet increased demand for agricultural products and that the environmental impact from these different ways vary significantly.

Materials and methods

The proposed framework mainly builds on the work of Ekvall T, Weidema BP (Int J Life Cycle Assess 9(3):pp. 161–171, 2004), agricultural statistics (FAOSTAT, FAOSTAT Agriculture Data, Food and Agriculture Organisation of the United Nations (2006), http://apps.fao.org/ (accessed June)), and agricultural outlook (FAPRI, US and world agricultural outlook, Food and Agriculture Research Institute, Iowa, 2006a). The framework and accompanying guidelines concern the suppliers affected, the achievement of increased production (area or yield), and the substitutions between crops. The framework, which is presented as a decision tree, proposes four possible systems that may be affected as a result of the increased demand of a certain crop in a certain area.

Results

The core of the proposed methodology is a decision tree, which guides the identification of affected processes in consequential agricultural LCA. The application of the methodology is illustrated with a case study presenting an LCA screening of wheat in Denmark. Different scenarios of how increased demand for wheat can be met show significant differences in emission levels as well as land use.

Discussion

The great differences in potential environmental impacts of the analysed results underpin the importance of system delimitation. The consequential approach is appointed as providing a more complete and accurate but also less precise result, while the attributional approach provides a more precise result but with inherent blind spots, i.e. a less accurate result.

Conclusions

The main features of the proposed framework and case study are: (1) an identification of significant sensitivity on results of system delimitation, and (2) a formalised way of identifying blind spots in attributional agricultural LCAs.

Recommendations and perspectives

It is recommended to include considerations on the basis of the framework presented in agricultural LCAs if relevant. This may be done either by full quantification or as qualitative identification of the most likely ways the agricultural product system will respond on changed demand. Hereby, it will be possible to make reservations to the conclusions drawn on the basis of an attributional LCA.     

Life cycle assessment for emerging materials: case study of a garden bed constructed from lumber produced with three different copper treatments

Purpose

The objective of this research was to evaluate the appropriateness of using life cycle assessment (LCA) for new applications that incorporate emerging materials and involve site-specific scenarios. Cradle-to-grave impacts of copper-treated lumber used in a raised garden bed are assessed to identify key methodological challenges and recommendations applying LCA for such purposes as well as to improve sustainability within this application.

Methods

The functional unit is a raised garden bed measuring 6.67 board feet (bf) in volume over a period of 20 years. The garden beds are made from softwood lumber such as southern yellow pine. The two treatment options considered were alkaline copper quaternary and micronized copper quaternary. Ecoinvent 2.2 provided certain life cycle inventory (LCI) data needed for the production of each garden bed, while additional primary and secondary sources were accessed to supplement the LCI.

Results and discussion

Primary data were not available for all relevant inventory requirements, as was anticipated, but enough secondary data were gathered to conduct a screening-level LCA on these raised garden bed applications. A notable finding was that elimination of organic solvent could result in a more sustainable lumber treatment product. Conclusions are limited by data availability and key methodological challenges facing LCA and emerging materials.

Conclusions

Although important data and methodological challenges facing LCA and emerging materials exist, this LCA captured material and process changes that were important drivers of environmental impacts. LCA methods need to be amended to reflect the properties of emerging materials that determine their fate, transport, and impacts to the environment and health. It is not necessary that all recommendations come to light before LCA is applied in the context of emerging materials. Applications of such materials involve many inputs beyond emerging materials that are already properly assessed by LCA. Therefore, LCA should be used in its current state to enhance the decision-making context for the sustainable development of these applications.