Accounting for overfishing in life cycle assessment: new impact categories for biotic resource use

Purpose

Overfishing is a relevant issue to include in all life cycle assessments (LCAs) involving wild caught fish, as overfishing of fish stocks clearly targets the LCA safeguard objects of natural resources and natural ecosystems. Yet no robust method for assessing overfishing has been available. We propose lost potential yield (LPY) as a midpoint impact category to quantify overfishing, comparing the outcome of current with target fisheries management. This category primarily reflects the impact on biotic resource availability, but also serves as a proxy for ecosystem impacts within each stock.

Methods

LPY represents average lost catches owing to ongoing overfishing, assessed by simplified biomass projections covering different fishing mortality scenarios. It is based on the maximum sustainable yield concept and complemented by two alternative methods, overfishing though fishing mortality (OF) and overfishedness of biomass (OB), that are less data-demanding.

Results and discussion

Characterization factors are provided for 31 European commercial fish stocks in 2010, representing 74 % of European and 7 % of global landings. However, large spatial and temporal variations were observed, requiring novel approaches for the LCA practitioner. The methodology is considered compliant with the International Reference Life Cycle Data System (ILCD) standard in most relevant aspects, although harmonization through normalization and endpoint characterization is only briefly discussed.

Conclusions

Seafood LCAs including any of the three approaches can be a powerful communicative tool for the food industry, seafood certification programmes, and for fisheries management.     

Life cycle assessment in green chemistry: overview of key parameters and methodological concerns

Purpose

Several articles within the area of green chemistry often promote new techniques or products as ‘green’ or ‘more environmentally benign’ than their conventional counterpart although these articles often do not quantitatively assess the environmental performance. In order to do this, life cycle assessment (LCA) is a valuable methodology. However, on the planning stage, a full-scale LCA is considered to be too time consuming and complicated. Two reasons for this have been recognised, the method is too comprehensive and it is hard to find inventory data. In this review, key parameters are presented with the purpose to reduce the time-consuming steps in LCA.

Methods

In this review, several LCAs of so-called ‘green chemicals’ are analysed and key parameters and methodological concerns are identified. Further, some conclusions on the environmental performance of chemicals were drawn.

Results and discussion

For fossil-based platform chemicals several LCAs exists but for chemicals produced with industrial biotechnology or from renewable resources the number of LCAs is limited, with the exception of biofuels, for which a large number of studies are made. In the review, a significant difference in the environmental performance of bulk and fine chemicals was identified. The environmental performance of bulk chemicals are closely connected to the production of the raw material and thereby different land use aspects. Here, a lot can be learnt from biofuel LCAs. In many of the reviewed articles focusing on bulk chemicals a comparison regarding fossil and renewable raw material was done. In most of the comparisons the renewable alternative turned out to be more environmentally preferable, especially for the impact on GWP and energy use. However, some environmental concerns were identified as important to include to assess overall environmental concern, for example eutrophication and the use of land.

Conclusions

To assess the environmental performance of green chemicals, quantitative methods are needed. For this purpose, both simple metrics and more comprehensive methods have been developed, one recognised method being LCA. However, this method is often too time consuming to be valuable in the process planning stage. This is partly due to a lack of available inventory data, but also because the method itself is too comprehensive. Here, key parameters for the environmental performance and methodological concerns were described to facilitate a faster and simpler use of LCA of green chemicals in the future.     

Use of LCA as a development tool within early research: challenges and issues across different sectors

Purpose

The aim of this paper is to highlight the challenges that face the use of life cycle assessment (LCA) for the development of emerging technologies. LCA has great potential for driving the development of products and processes with improved environmental credentials when used at the early research stage, not only to compare novel processing with existing commercial alternatives but to help identify environmental hotspots. Its use in this way does however provide methodological and practical difficulties, often exacerbated by the speed of analysis required to enable development decisions to be made. Awareness and understanding of the difficulties in such cases is vital for all involved with the development cycle.

Methods

This paper employs three case studies across the diverse sectors of nanotechnology, lignocellulosic ethanol (biofuel), and novel food processes demonstrating both the synergy of issues across different sectors and highlighting the challenges when applying LCA for early research. Whilst several researchers have previously highlighted some of the issues with use of LCA techniques at an early stage, most have focused on a specific product, process development, or sector. The use of the three case studies here is specifically designed to highlight conclusively that such issues are prevalent to use of LCA in early research irrespective of the technology being assessed.

Results and discussion

The four focus areas for the paper are system boundaries, scaling issues, data availability, and uncertainty. Whilst some of the issues identified will be familiar to all LCA practitioners as problems shared with standard LCAs, their importance and difficulty is compounded by factors distinct to novel processes as emerging technology is often associated with unknown future applications, unknown industrial scales, and wider data gaps that contribute to the level of LCA uncertainty. These issues, in addition with others that are distinct to novel applications, such as the challenges of comparing laboratory scale data with well-established commercial processing, are exacerbated by the requirement for rapid analysis to enable development decisions to be made.

Conclusions

Based on the challenges and issues highlighted via illustration through the three case studies, it is clear that whilst transparency of information is paramount for standard LCAs, the sensitivities, complexities, and uncertainties surrounding LCAs for early research are critical. Full reporting and understanding of these must be established prior to utilising such data as part of the development cycle.     

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.     

LCA of petroleum-based lubricants: state of art and inclusion of additives

Purpose

While the application of Life Cycle Assessment (LCA) to lubricants can be considered fully operational for general purposes outside the lubricants industry, where Life Cycle Inventories (LCIs) of mineral and synthetic base oils can be used interchangeably and where additives can be excluded, this is not the case for research and development purposes within the industry. Previous LCAs of base oils are not sufficiently detailed and comprehensive for R&D purposes, and there are no LCAs of lube additives and fully formulated lubricants. The aim of this paper is to integrate and expand previous LCAs of base oils and to investigate on the contribution of lube additives to the environmental impacts of a fully formulated lubricant.

Materials and methods

This study considers three base oils (mineral, poly-alpha-olefins (PAO) and hydrocracked) and a set of lubricating additives typically used in fully formulated engine oil. The LCA model is based on both industry and literature data.

Results and discussion

Trends in the lubricants industry towards more sophisticated base oils correspond to remarkably higher environmental impacts per kilogram of product but lead to reduced impacts per kilometre. The contribution of additives to the life cycle impacts of commercial lube oil was found to be remarkably high for some impact categories (nearly 35?% for global warming).

Conclusions

As base oil is concerned, this study made the point on data availability and provided a contribution in order to integrate and expand previous LCAs of mineral base oil and PAO. On the side of additives, the main conclusion is that in modern lubricants, the contribution of additives in terms of environmental impact can be remarkably high and, therefore, they should not be excluded.     

Global characterisation factors to assess land use impacts on biotic production

Purpose

The inclusion of land-use activities in life cycle assessment (LCA) has been subject to much debate in the LCA community. Despite the recent methodological developments in this area, the impacts of land occupation and transformation on its long-term ability to produce biomass (referred to here as biotic production potential [BPP]) — an important endpoint for the Area of Protection (AoP) Natural Resources — have been largely excluded from LCAs partly due to the lack of life cycle impact assessment methods.

Materials and methods

Several possible methods/indicators for BPP associated with biomass, carbon balance, soil erosion, salinisation, energy, soil biota and soil organic matter (SOM) were evaluated. The latter indicator was considered the most appropriate for LCA, and characterisation factors for eight land use types at the climate region level were developed.

Results and discussion

Most of the indicators assessed address land-use impacts satisfactorily for land uses that include biotic production of some kind (agriculture or silviculture). However, some fail to address potentially important land use impacts from other life cycle stages, such as those arising from transport. It is shown that the change in soil organic carbon (SOC) can be used as an indicator for impacts on BPP, because SOC relates to a range of soil properties responsible for soil resilience and fertility.

Conclusions

The characterisation factors developed suggest that the proposed approach to characterize land use impacts on BBP, despite its limitations, is both possible and robust. The availability of land-use-specific and biogeographically differentiated data on SOC makes BPP impact assessments operational. The characterisation factors provided allow for the assessment of land-use impacts on BPP, regardless of where they occur thus enabling more complete LCAs of products and services. Existing databases on every country’s terrestrial carbon stocks and land use enable the operability of this method. Furthermore, BPP impacts will be better assessed by this approach as increasingly spatially specific data are available for all geographical regions of the world at a large scale. The characterisation factors developed are applied to the case studies (Part D of this special issue), which show the practical issues related to their implementation.     

Stochastic multi-attribute analysis (SMAA) as an interpretation method for comparative life-cycle assessment (LCA)

Purpose

Comparative life-cycle assessments (LCAs) today lack robust methods of interpretation that help decision makers understand and identify tradeoffs in the selection process. Truncating the analysis at characterization is misleading and existing practices for normalization and weighting may unwittingly oversimplify important aspects of a comparison. This paper introduces a novel approach based on a multi-criteria decision analytic method known as stochastic multi-attribute analysis for life-cycle impact assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces.

Methods

To contrast different valuation methods, this study performs a comparative LCA of liquid and powder laundry detergents using three approaches to normalization and weighting: (1) characterization with internal normalization and equal weighting, (2) typical valuation consisting of external normalization and weights, and (3) SMAA-LCIA using outranking normalization and stochastic weighting. Characterized results are often represented by LCA software with respect to their relative impacts normalized to 100 %. Typical valuation approaches rely on normalization references, single value weights, and utilizes discrete numbers throughout the calculation process to generate single scores. Alternatively, SMAA-LCIA is capable of exploring high uncertainty in the input parameters, normalizes internally by pair-wise comparisons (outranking) and allows for the stochastic exploration of weights. SMAA-LCIA yields probabilistic, rather than discrete comparisons that reflect uncertainty in the relative performance of alternatives.

Results and discussion

All methods favored liquid over powder detergent. However, each method results in different conclusions regarding the environmental tradeoffs. Graphical outputs at characterization of comparative assessments portray results in a way that is insensitive to magnitude and thus can be easily misinterpreted. Typical valuation generates results that are oversimplified and unintentionally biased towards a few impact categories due to the use of normalization references. Alternatively, SMAA-LCIA avoids the bias introduced by external normalization references, includes uncertainty in the performance of alternatives and weights, and focuses the analysis on identifying the mutual differences most important to the eventual rank ordering.

Conclusions

SMAA-LCIA is particularly appropriate for comparative LCAs because it evaluates mutual differences and weights stochastically. This allows for tradeoff identification and the ability to sample multiple perspectives simultaneously. SMAA-LCIA is a robust tool that can improve understanding of comparative LCA by decision or policy makers.     

Life cycle assessment evaluation of green product labeling systems for residential construction

Purpose

Life cycle assessment (LCA) is a tool that can be utilized to holistically evaluate novel trends in the construction industry and the associated environmental impacts. Green labels are awarded by several organizations based on single or multiple attributes. The use of multi-criteria labels is a good start to the labeling process as opposed to single criteria labels that ignore a majority of impacts from products. Life cycle thinking, in theory, has the potential to improve the environmental impacts of labeling systems. However, LCA databases currently are lacking in detailed information about products or sometimes provide conflicting information.

Method

This study compares generic and green-labeled carpets, paints, and linoleum flooring using the Building for Environmental and Economic Sustainability (BEES) LCA database. The results from these comparisons are not intuitive and are contradictory in several impact categories with respect to the greenness of the product. Other data sources such as environmental product declarations and ecoinvent are also compared with the BEES data to compare the results and display the disparity in the databases.

Results

This study shows that partial LCAs focused on the production and transportation phase help in identifying improvements in the product itself and improving the manufacturing process but the results are uncertain and dependent upon the source or database. Inconsistencies in the data and missing categories add to the ambiguity in LCA results.

Conclusions

While life cycle thinking in concept can improve the green labeling systems available, LCA data is lacking. Therefore, LCA data and tools need to improve to support and enable market trends.     

A review of life cycle assessments on wind energy systems

Purpose

Several life cycle assessments (LCAs) of wind energy published in recent years are reviewed to identify methodological differences and underlying assumptions.

Methods

A full comparative analysis of 12 studies were undertaken (ten peer-reviewed papers, one conference paper, and one industry report) regarding six fundamental factors (methods used, energy use accounting, quantification of energy production, energy performance and primary energy, natural resources, and recycling). Each factor is discussed in detail to highlight strengths and shortcomings of various approaches.

Results

Several potential issues are found concerning the way LCA methods are used for assessing energy performance and environmental impact of wind energy, as well as dealing with natural resource use and depletion. The potential to evaluate natural resource use and depletion impacts from wind energy appears to be poorly exploited or elaborated on in the reviewed studies. Estimations of energy performance and environmental impacts are critically analyzed and found to differ significantly.

Conclusions and recommendations

A continued discussion and development of LCA methodology for wind energy and other energy resources are encouraged. Efforts should be made to standardize methods and calculations. Inconsistent use of terminology and concepts among the analyzed studies are found and should be remedied. Different methods are generally used and the results are presented in diverse ways, making it difficult to compare studies with each other, but also with other renewable energy sources.     

Simplifying a life cycle assessment of a mobile phone

Purpose

The possibilities for full life cycle assessment (LCA) of new Information and Communication Technology (ICT) products are often limited, so simplification approaches are needed. The aim of this paper is to investigate possible simplifications in LCA of a mobile phone and to use the results to discuss the possibilities of LCA simplifications for ICT products in a broader sense. Another aim is to identify processes and data that are sensitive to different methodological choices and assumptions related to the environmental impacts of a mobile phone.

Methods

Different approaches to a reference LCA of a mobile phone was tested: (1) excluding environmental impact categories, (2) excluding life cycle stages/processes, (3) using secondary process data from generic databases, (4) using input-output data and (5) using a simple linear relationship between mass and embodied emissions.

Results and discussion

It was not possible to identify one or a few impact categories representative of all others. If several impact categories would be excluded, information would be lost. A precautionary approach of not excluding impact categories is therefore recommended since impacts from the different life cycle stages vary between impact categories. Regarding use of secondary data for an ICT product similar to that studied here, we recommend prioritising collection of primary (specific) data on energy use during production and use, key component data (primarily integrated circuits) and process-specific data regarding raw material acquisition of specific metals (e.g. gold) and air transport. If secondary data are used for important processes, the scaling is crucial. The use of input-output data can be a considerable simplification and is probably best used to avoid data gaps when more specific data are lacking.

Conclusions

Further studies are needed to provide for simplified LCAs for ICT products. In particular, the end-of-life treatment stage need to be further addressed, as it could not be investigated here for all simplifications due to data gaps.     

Inclusion of discard assessment indicators in fisheries life cycle assessment studies. Expanding the use of fishery-specific impact categories

Purpose

The main purpose of this article is to propose specific discard indexes for their development in fisheries life cycle assessment (LCA). The objective of these is to characterize and standardize discards in worldwide fisheries.

Methods

The global discard index (GDI) is intended to be an easily understood index whose use is extendible to any fishery in the world. It is presented as a dynamic index that aims to characterize and standardize discard rates between fisheries by direct comparison with the global discard rates reported periodically by FAO. Furthermore, a simplified approach excluding characterization is presented for scenarios in which the data quality linked to discards is poor. Two additional indicators, survival rate of discards and slipping, are proposed to improve the reporting and quantification of biomass waste by fishing vessels.

Results

GDI implementation, together with two other fishery-specific impact categories, showed remarkable differences in the environmental impacts of several fishing fleets when compared with the obtained results for conventional impact categories. Results for the conventional categories were strongly influenced by the energy use in the fishery, while results obtained for fishery-specific categories presented variable trends due to the dependence on a wider range of factors. GDI inclusion favored direct comparison with worldwide average discard rates on a time scale basis, from a wet weight or a net primary productivity perspective, depending on the selected approach.

Conclusions

Proposed indicators achieved the important objective of integrating discard data as a fishery-specific impact in fishery LCAs, increasing the benefits of implementing LCA in fisheries assessment. Specific advantages of these indicators include assessing changes in capture and landing composition, evaluating the selectivity of the fishing gears, and monitoring the behavior of fisheries in a normalized context respect to other fisheries. GDI was identified as an adequate methodological improvement for regular use in fisheries LCA. Future developments GDI include its harmonization for inclusion in damage assessment.     

Comment on the editorial note by Baitz et XXI aliis

Background

The editor of this journal has been waiting for such a contribution of the life cycle assessment (LCA) practitioners and users for years, since the last debate of this kind dates back to beginning of the new century. It is remembered as the “Two planets debate” and coincided with the emergence of life cycle management, i.e. the use of life-cycle based methods in industry.

The “Two planets”

This is a metaphor coined at the Society of Environmental Toxicology and Chemistry (SETAC) Europe case studies symposium 2000 and designates the fact that many academic LCA developers and the LCA practitioners seem to live in different spheres. The editorial note by Baitz et al. shows that this seems to be true still today. It is argued that the practitioners do not frequently enough participate in the working groups organized by SETAC, the UNEP/SETAC life cycle initiative and other international organizations and therefore cannot bring in the practical experience they have acquired in performing “real-life” LCA studies. The new LCIA methods, for instance, are often not accepted by the LCA practitioners and commissioners, since essential aspects were not recognised during method development.

Tentative proposal for a solution

The solution of the problems pointed out in Baitz et al. cannot be to hinder the inhabitants of the academic planet in inventing ingenious new methods for reasons of academic freedom. It is proposed that new methods developed should be tested by practitioners in real-life LCA studies. Data asymmetries in comparative (i.e. most) LCA studies using more demanding methods may shift problems from LCIA to the LCI databases. With regard to the financing of such studies, it should be remembered that practitioners do their living by performing LCAs and other studies and have to calculate a full overhead in addition to the pure working costs.     

International Molybdenum Association (IMOA) life cycle assessment program and perspectives on the LCA harmonization effort

Purpose

In 2001, the International Molybdenum Association (IMOA) initiated their life cycle assessment (LCA) program performing cradle-to-gate life cycle inventories (LCIs) of three molybdenum metallurgical products, followed by LCIs of eight molybdenum chemicals and an update to the metallurgical LCIs. From 2012 to 2014, IMOA participated in a multi-metal industry initiative to harmonize the methodological approach to metal-related LCAs. This paper describes some of IMOA’s conclusions formed from its program and, coupled with its involvement in the multi-metal initiative, provides some lessons learned.

Methods

For this paper, IMOA evaluated the benefits of its LCI program, including its ability to communicate effectively with member companies and stakeholders on the development, use, and application of life cycle data. Likewise, IMOA developed the competence to recognize and provide input on potentially inappropriate use of LCA. IMOA performed a literature review to highlight some of the scientific research using the molybdenum LCI data. IMOA also reviewed the metal industry’s guidance document to provide its perspective on it, including similarities, differences, and substantiation of elements of the four topic areas.

Results and discussion

The metal industry’s guidance document identified four topic areas as essential for alignment with respect to metal-related LCAs: (1) system boundaries, (2) coproduct modelling, (3) life cycle impact assessment (LCIA), and (4) metals recycling modelling. IMOA is largely in agreement with the approaches described in the document. The paper provides examples of how these have been applied to LCAs on Mo-bearing products as well as examples of how some LCA work can benefit from the guidance document.

Conclusions

Having taken part in the harmonization effort, IMOA is poised to educate its member companies and stakeholders about some of the challenging issues encountered in LCA and will continue to lead through active industry participation. IMOA supplies its LCI data via a formal request process which enables open dialogue with stakeholders and LCA practitioners while providing IMOA with insights into how its products fit into the broader lifecycle context and facilitating stakeholders’ awareness of LCA and metals.

     

Enabling optimization in LCA: from “ad hoc” to “structural” LCA approach—based on a biodiesel well-to-wheel case study

Purpose

Applied life cycle assessment (LCA) studies often lead to a comparison of rather few alternatives; we call this the “ad hoc LCA approach.” This can seem surprising since applied LCAs normally cover countless options for variations and derived potentials for improvements in a product life cycle. In this paper, we will suggest an alternative approach to the ad hoc approach, which more systematically addresses the many possible variations to identify the most promising. We call it the “structural LCA approach.” The goals of this paper are (1) to provide basic guidelines for the structural approach, including an easy expansion of the LCA space; (2) to show that the structural LCA approach can be used for different types of optimization in LCA; and (3) to improve the transparency of the LCA work.

Methods

The structural approach is based on the methodology “design of experiments” (Montgomery 2005). Through a biodiesel well-to-wheel study, we demonstrate a generic approach of applying explanatory variables and corresponding impact categories within the LCA methodology. Explanatory variables are product system variables that can influence the environmental impacts from the system. Furthermore, using the structural approach enables two different possibilities for optimization: (1) single-objective optimization (SO) based on response surface methodology (Montgomery 2005) and (2) multiobjective optimization (MO) by the hypervolume estimation taboo search (HETS) method. HETS enables MO for more than two or three objectives.

Results and discussion

Using SO, the explanatory variable “use of residual straw from fields” is, by far, the explanatory variable that can contribute with the highest decrease of climate change potential. For the respiratory inorganics impact category, the most influencing explanatory variable is found to be the use of different alcohol types (bioethanol or petrochemical methanol) in biodiesel production. Using MO, we found the Pareto front based on 5 different life cycle pathways which are nondominated solutions out of 66 different analyzed solutions. Given that there is a fixed amount of resources available for the LCA practitioner, it becomes a prioritizing problem whether to apply the structural LCA approach or not. If the decision maker only has power to change a single explanatory variable, it might not be beneficial to apply the structural LCA approach. However, if the decision maker (such as decision makers at the societal level) has power to change more explanatory variables, then the structural LCA approach seems beneficial for quantifying and comparing the potentials for environmental improvement between the different explanatory variables in an LCA system and identifying the overall most promising product system configurations among the chosen PWs.

Conclusions

The implementation of the structural LCA approach and the derived use of SO and MO have been successfully achieved and demonstrated in the present paper. In addition, it is demonstrated that the structural LCA approach can lead to more transparent LCAs since the potentially most important explanatory variables which are used to model the LCAs are explicitly presented through the structural LCA approach. The suggested structural approach is a new approach to LCA and it seems to be a promising approach for searching or screening product systems for environmental optimization potentials. In the presented case, the design has been a rather simple full factorial design. More complicated problems or designs, such as fractional designs, nested designs, split plot designs, and/or unbalanced data, in the context of LCA could be investigated further using the structural approach.     

Sampling error in US field crop unit process data for life cycle assessment

Purpose

The research presented here was motivated by an interest in understanding the magnitude of sampling error in crop production unit process data developed for life cycle assessments (LCAs) of food, biofuel, and bioproduct production. More broadly, uncertainty data are placed within the context of conclusive interpretations of comparative bioproduct LCA results.

Methods

Data from the US Department of Agriculture's Agricultural Resource Management Survey were parameterized for 466 crop–state–year combinations, using 146 variables representing the previous crop, tillage and seed operations, irrigation, and applications of synthetic fertilizer, lime, nitrogen inhibitor, organic fertilizer, and pesticides. Data are described by Student's t distributions representing sampling error through the relative standard error (RSE) and are organized by the magnitude of the RSE by data point. Also, instances in which the bounds of the 95 % confidence intervals are less than zero or exceed actual limits are identified.

Results and discussion

Although the vast majority of the data have a RSE less than 100 %, values range from 0 to 1,600 %. The least precision was found in data collected between 2001 and 2002, in the production of corn and soybeans and in synthetic and pesticide applications and irrigation data. The highest precision was seen in the production of durum wheat, rice, oats, and peanuts and in data representing previous crops and till and seed technology use. Additionally, upwards of 20 % of the unit process, data had 95 % confidence intervals that are less than or exceed actual limits, such as an estimation of a negative area or a portion exceeding a total area, as a consequence of using a jackknife on subsets of data for which the weights are not calibrated explicitly and a low presence of certain practices.

Conclusions

High RSE values arise from the RSE representing a biased distribution, a jackknife estimate being nearly zero, or error propagation using low-precision data. As error propagates to the final unit process data, care is required when interpreting an inventory, e.g., Monte Carlo simulation should only be sampled within the appropriate bounds. At high levels of sampling error such as those described here, comparisons of LCA bioproduct results must be made with caution and must be tested to ensure mean values are different to a desired level of significance.     

Comparative attributional life cycle assessment of European cellulase enzyme production for use in second-generation lignocellulosic bioethanol production

Purpose

The production of cellulase enzymes (CE) has been identified as one major contributor towards the life cycle environmental and economic impacts of second-generation lignocellulosic bioethanol (LCB) production. Despite this knowledge, the literature lacks consistent and transparent life cycle assessments (LCA) which compare CE production based on the three more commonly proposed carbon sources: cornstarch glucose, sugar cane molasses and pre-treated softwood. Furthermore, numerous LCAs of LCB omit CE production from their system boundaries, with several authors citing the lack of available production data.

Methods

In this article, we perform a comparative attributional LCA for the on-site production of 1 kg CE in full broth via submerged aerobic fermentation (SmF) based on the three alternative carbon sources, cases A, B and C, respectively. We determine life cycle inventory (LCI) material consumption using stoichiometric equations and volume flow, supplemented with information from the literature. All LCIs are provided in a consistent and transparent manner, filling the existing data gaps towards performing representative LCAs of LCB production with on-site CE production. Life cycle impact assessment (LCIA) results are determined with SimaPro 8 software using CML 1A baseline and non-baseline methods along with cumulative energy demand and are compared to results of similar studies. Sensitivity analysis is performed both for all major assumptions and for market changes with the application of advanced attributional LCA (AALCA).

Results and discussion

We find that CE production from pre-treated softwood (case C) provides the lowest environmental impacts, followed by sugar cane molasses (case B) and then cornstarch glucose (case A), with global warming potentials of 7.9, 9.1 and 10.6 kg CO₂ eq./kg enzyme, respectively. These findings compare well with those of similar studies, though great variation exists in the literature. Through sensitivity analysis, we determine that results are sensitive to assumptions made concerning carbon source origin, applied allocation, market changes, process efficiency and electricity supply.

Conclusions

Furthermore, we find that the contribution of CE production towards the overall life cycle impacts of LCB is significant and that the omission of this sub-process in LCAs of LCB production can compromise their representativeness.

     

Fusion of conflicting information for improving representativeness of data used in LCAs

Purpose

Employing representative data is necessary for producing a credible LCA informing decision making process. When the data is available from multiple sources, and in incompatible formats such as point estimates, intervals, approximations, and may even be conflicting in nature, it is important to synthesize it with minimal loss of information to enhance the credibility of LCA. This article introduces a framework for information fusion that can serve this purpose within the current operational procedure of LCA.

Methods

The character of information gathered from multiple sources is inherently different than that exhibited by the information generated by a single random source. The framework of possibility theory can be used to merge such heterogeneous information as demonstrated by its application in the diverse fields such as engineering, finance, and social sciences. This article introduces this methodology for LCAs by first introducing the theory behind data modeling and data fusion with possibility theory. Then, this framework is applied to the disparate data from literature on the manufacturing energy requirements for semiconductor device fabrication, and also to a hypothetical example of linguistic inputs from experts in order to demonstrate the operationalization of the theory. A flowchart is provided to recap the framework and for easy navigation through the steps of merging procedure.

Results and discussion

The framework for fusion of information applied the numerical and linguistic heterogeneous data in the LCA context illustrates that this methodology can be implemented relatively easily to increase the data quality and credibility of LCA. This can be done without making any changes in the usual preferred way of conducting an LCA. Information fusion may be performed either after the sensitivity analysis identifies the most impactful categories that need further investigation, or it can be performed upfront to the select input categories of interest.

Conclusions

The article introduces a well-established framework of information fusion to the field of LCA where disparate data may need to be fused to perform the assessment under certain conditions. This framework can be easily implemented, and will enhance data quality and LCA credibility. We also hope that data entry software such as ecoEditor make provision for the data entry mechanism necessary to enter fused data.     

Life cycle assessment of the supply and use of bioenergy: impact of regional factors on biogas production

Purpose

This article evaluates the parameters that influence the results of a life cycle assessment (LCA) of biogas production from maize and the conversion of biogas into electricity. The environmental impacts of biogas vary according to regional farming procedures and, therefore, the soil, climate conditions, crop yield, and cultivation management. This study focuses on these regional parameters and the existing infrastructure, including the number of installed biogas plants and their share of used heat.

Materials and methods

To assess the regional impact, the LCAs of maize cultivation, on the one hand, and the production and use of biogas, on the other, were performed for three different areas. These areas were the administrative districts of Celle, Hildesheim, and Goettingen; all located in the south of Lower Saxony, Germany. The areas differed in geographic location conditions, crop yield, and the number of installed biogas plants. The necessary data for modeling the cultivation of maize were derived from the specific regional and local parameters of each area. The most important parameters were the soil characteristics and the climate conditions for cultivating maize. The share of used heat from combined heat and power unit (CHP) was another relevant factor for biogas production and use.

Results

Our results demonstrate significant differences among the investigated areas. The smallest environmental impact of all the considered categories occurs in Goettingen and the largest in Celle. The net greenhouse gas emissions vary from 0.179?kg CO₂ eq./kWh_el in Celle to 0.058?kg CO₂ eq./kWh_el in Goettingen. This result is due to the maize cultivation system and the different credits for using heat from the CHP. Variances in energy crop cultivation result from different nitrogen and irrigation demands. In addition, despite higher applications of nitrogen fertilizer and irrigation, the maize yield is lower in Celle. The impact category of total fossil energy shows similar results to that of the greenhouse gas (GHG) emissions. The results range from ?0.274 to 0.175 kWh/kWh_el. The results of acidification and eutrophication vary from 1.62 in Goettingen to 1.94?g SO₂ eq./kWh_el in Celle and respectively 0.330 to 0.397?g PO ₄ ^3? eq./kWh_el. These differences are primarily caused by maize cultivation, especially irrigation.

Conclusions and perspectives

Cultivating maize and using waste heat from the CHP were identified as the most influential parameters for the GHG emissions and total fossil energy demand. Regarding acidification and eutrophication, the most relevant factors are the application of digester output and the emissions from the CHP. Our results show the need to consider regional parameters in the LCA of bioenergies, particularly biogas production and use, especially if the LCA studies are used for generalized evaluations such as statements on the climate protection potential of biogas.