<Emphasis Type="Bold">Zinc nutrition in wheat-based cropping systems</Emphasis>

Background

Zinc (Zn) deficiency is one of the most important micronutrient disorders affecting human health. Wheat is the staple food for 35% of the world’s population and is inherently low in Zn, which increases the incidence of Zn deficiency in humans. Major wheat-based cropping systems viz. rice–wheat, cotton–wheat and maize–wheat are prone to Zn deficiency due to the high Zn demand of these crops.

Methods

This review highlights the role of Zn in plant biology and its effect on wheat-based cropping systems. Agronomic, breeding and molecular approaches to improve Zn nutrition and biofortification of wheat grain are discussed.

Results

Zinc is most often applied to crops through soil and foliar methods. The application of Zn through seed treatments has improved grain yield and grain Zn status in wheat. In cropping systems where legumes are cultivated in rotation with wheat, microorganisms can improve the available Zn pool in soil for the wheat crop. Breeding and molecular approaches have been used to develop wheat genotypes with high grain Zn density.

Conclusions

Options for improving grain yield and grain Zn concentration in wheat include screening wheat genotypes for higher root Zn uptake and grain translocation efficiency, the inclusion of these Zn-efficient genotypes in breeding programs, and Zn fertilization through soil, foliar and seed treatments.

     

Partial modelling of the perennial crop cycle misleads LCA results in two contrasted case studies

Purpose

As highlighted in recent reviews, there is a need to harmonise the way life cycle assessment (LCA) of perennial crops is conducted. In most published LCA on perennial crops, the modelling of the agricultural production is based on data sets for just one productive year. This may be misleading since performance and impacts of the system may greatly vary year by year. The purposes of this study are to analyse how partial modelling of the perennial cycle through non-holistic data collection may affect LCA results and to make recommendations.

Methods

Three modelling choices for the perennial crop cycle were tested in parallel in two contrasted LCA case studies: oil palm fruits from Indonesia, and small citrus from Morocco. Modelling choices tested were as follows: (i) a chronological modelling over the complete crop cycle of orchards, (ii) a 3-year average from the productive phase, and (iii) various single years from the productive phase. In both case studies, the system boundary was a cradle-to-farm gate with a functional unit of 1 kg fresh fruits. LCA midpoint impacts were calculated with ReCiPe 2008 in Simapro©V.7. We first analysed how inputs, yields and potential impacts varied over time. We then analysed process contributions in the baseline model, i.e. the chronological modelling, and finally compared LCA results for the various perennial modelling choices.

Results and discussion

Agricultural practices, yields and impacts varied over the years especially during the first 3–9 years depending on the case study. In both case studies, the modelling choices to account or not for the whole perennial cycle drastically influenced LCA results. The differences could be explained by the inclusion or not of the yearly variability and the accounting or not of the immature phase, which contributed to 7–40 or 6.5–29 % of all impact categories for oil palm fruit and citrus, respectively.

Conclusions

The chosen approach to model the perennial cycle influenced the final LCA results for two contrasted case studies and deserved specific attention. Although data availability may remain the limiting factor in most cases, assumptions can be made to interpolate or extrapolate some data sets or to consolidate data sets from chronosequences (i.e. modular modelling). In all cases, we suggest that the approach chosen to model the perennial cycle and the representativeness of associated collected data should be made transparent and discussed. Further research work is needed to improve the understanding and modelling of perennial crop functioning and LCA assessment.

     

Regionalization of agri-food life cycle assessment: a review of studies in Portugal and recommendations for the future

Purpose

One of the main trends in life cycle assessment (LCA) today is towards increased regionalization in inventories and impact assessment methods. LCA studies require the collection of activity data but also of increasingly region-specific background data to accurately depict supply chain processes and enable the application of an increasing number of geographically explicit impact assessment models. This is particularly important for agri-food products. In this review, we assess progress in Portugal towards this goal and provide recommendations for future developments.

Methods

We perform a comprehensive review of available LCA studies conducted for Portuguese agri-food products, in order to evaluate the current state of Portuguese agri-food LCA. Among other issues, we assess availability of data, methods used, level of regionalization, impact assessment model relevance and coherence for inter-product comparability. We also provide conclusions and recommendations based on recent developments in the field.

Results and discussion

We found 22 LCA studies, covering 22 different products. The analysis of these studies reveals limitations in inter-study comparability. The main challenges have to do with a lack of country-specific foreground data sources applied consistently in the studies found, with discrepancies in impact assessment categories, and with the use of simple functional units that may misrepresent the product analyzed.

Conclusions

We conclude that Portuguese agri-food LCA studies do not have a systematic and country-scale approach in order to guarantee regional accuracy and comparability. We propose a research strategy to engage the Portuguese agri-food LCA community in devising a consistent framework before practical application studies are conducted.

     

The need for co-product allocation in the life cycle assessment of agricultural systems—is “biophysical” allocation progress?

Purpose

Several new “biophysical” co-product allocation methodologies have been developed for LCA studies of agricultural systems based on proposed physical or causal relationships between inputs and outputs (i.e. co-products). These methodologies are thus meant to be preferable to established allocation methodologies such as economic allocation under the ISO 14044 standard. The aim here was to examine whether these methodologies really represent underlying physical relationships between the material and energy flows and the co-products in such systems, and hence are of value.

Methods

Two key components of agricultural LCAs which involve co-product allocation were used to provide examples of the methodological challenges which arise from adopting biophysical allocation in agricultural LCA: (1) the crop production chain and (2) the multiple co-products produced by animals. The actual “causal” relationships in these two systems were illustrated, the energy flows within them detailed, and the existing biophysical allocation methods, as found in literature, were critically evaluated in the context of such relationships.

Results and discussion

The premise of many biophysical allocation methodologies has been to define relationships which describe how the energy input to agricultural systems is partitioned between co-products. However, we described why none of the functional outputs from animal or crop production can be considered independently from the rest on the basis of the inputs to the system. Using the example of manure in livestock systems, we also showed why biophysical allocation methodologies are still sensitive to whether a system output has economic value or not. This sensitivity is a longstanding criticism of economic allocation which is not resolved by adopting a biophysical approach.

Conclusions

The biophysical allocation methodologies for various aspects of agricultural systems proposed to date have not adequately explained how the physical parameters chosen in each case represent causal physical mechanisms in these systems. Allocation methodologies which are based on shared (but not causal) physical properties between co-products are not preferable to allocation based on non-physical properties within the ISO hierarchy on allocation methodologies and should not be presented as such.

     

Crop metabolomics: from diagnostics to assisted breeding

Background

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.

Aim of Review

We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.

Key Scientific Concepts of Review

Translational metabolomics applied to crop breeding programs.

     

Data strategy for environmental assessment of agricultural regions via LCA: case study of a French catchment

Purpose

Various approaches have been carried out to extrapolate environmental assessments of farms to the regional level, some of them oversimplified and thus leading to high uncertainty. Key challenges include selection of a representative sample, construction of a farm/land use typology, the extrapolation strategy and dealing with data limitations. This work proposes a method for addressing these issues by means of statistically supported approaches.

Methods

We applied a novel approach combining a sampling strategy, estimation of farm-level environmental impacts via life cycle assessment (LCA), a farm typology based on principal component analysis, a statistical method for extending the farm sample given data constraints and finally linear extrapolation based on regional production and land use, taking into account the regional import–export balance. The approach was applied to a French case study, the Lieue de Grève catchment in the dairy-intensive Brittany region. A decision flowchart was developed to generalise the approach for similar applications dealing with farm and LCA data constraints. Additionally, innovative farm practices were modelled and their impacts propagated to the regional level.

Results and discussion

The typology developed identified “dairy”, “beef”, “dairy + beef” and “swine” farms as the dominant farm types in the region. While swine farms had the highest mean impacts per hectare, dairy and dairy + beef farms had impacts two to five times as high as those of beef and swine farms, when extrapolated to the entire catchment. Multiple linear regressions based on an extended farm and LCA dataset were used to predict environmental impacts of dairy farms lacking LCA results, thus increasing their sample size before extrapolation. The inclusion of farm and LCA data from a neighbouring region did not contribute to the accuracy of predicted impacts, as determined by comparing them to those of the farm closest to the dairy cluster’s centre, but rather produced significantly larger coefficients of variation. Results of tests of including two extra-regional farm and LCA datasets helped determine decision rules for the decision flowchart. Modelling of innovative agricultural practices yielded regional impacts consistent with previous estimates.

Conclusions

This approach provides a generalisable approach for farm typologies, data handling and regional extrapolation of farm-level LCAs, applicable to estimate environmental impacts of any agricultural area if requirements of a representative farm sample are met. We demonstrate the utility of the method for estimating effects of innovative agricultural practices on a region’s impacts by modelling practices on virtual farms and extrapolating their results.

     

Geographic variability of agriculture requires sector-specific uncertainty characterization

Purpose

Regionalization in life cycle assessment (LCA) has focused on spatially differentiated environmental variables for regional impact assessment models. Relatively less attention has been paid to spatial disparities in intermediate flows for life cycle inventory (LCI).

Methods

First, we compiled state-specific LCIs for four major crops in the USA and evaluated their geographic variability in the characterized results due to the differences in intermediate inputs. Second, we evaluated the consequence of choosing average or region-specific LCIs in understanding the life cycle environmental implications of land use change from cotton to corn or soybean. Finally, we analyzed the implications of our findings in characterizing the uncertainties associated with geographic variability under the conventional pedigree approach.

Results and discussion

Our results show that spatial disparities in LCI alone lead to two to fourfold differences in characterized results for most impact categories. The differences, however, increase to over an order of magnitude for freshwater ecotoxicity and human health non-cancer. Among the crops analyzed, winter wheat shows higher variability partly due to a larger difference in yield. As a result, the use of national average data derived from top corn and soybean producing states significantly underestimates the characterized impacts of corn and soybean in the states where land conversion from cotton to corn or soybean actually took place. The results also show that the conventional pedigree approach to uncertainty characterization in LCA substantially underestimates uncertainties arising from geographic variability of agriculture. Compared to the highest geometric standard deviation (GSD) value of 1.11 under the pedigree approach, the GSDs that we derived are as high as 7.1, with the median around 1.9.

Conclusions

The results highlight the importance of building regional life cycle inventory for understanding the environmental impacts of crops at the regional level. The high geographic variability of crops also indicates the need for sector-specific approaches to uncertainty characterization. Our results also suggest that the uncertainty values in the existing LCI databases might have been signficantly underestimated especially for those products with high geographic variability, demanding a cautious interpretation of the results derived from them. 

     

Interpretation of comparative LCAs: external normalization and a method of mutual differences

Purpose

Identification of environmentally preferable alternatives in a comparative life cycle assessment (LCA) can be challenging in the presence of multiple incommensurate indicators. To make the problem more manageable, some LCA practitioners apply external normalization to find those indicators that contribute the most to their respective environmental impact categories. However, in some cases, these results can be entirely driven by the normalization reference, rather than the comparative performance of the alternatives. This study evaluates the influence of normalization methods on interpretation of comparative LCA to facilitate the use of LCA in decision-driven applications and inform LCA practitioners of latent systematic biases. An alternative method based on significance of mutual differences is proposed instead.

Methods

This paper performs a systematic evaluation of external normalization and describes an alternative called the overlap area approach for the purpose of identifying relevant issues in a comparative LCA. The overlap area approach utilizes the probability distributions of characterized results to assess significant differences. This study evaluates the effects in three LCIA methods, through application of four comparative studies. For each application, we call attention to the category indicators highlighted by each interpretation approach.

Results and discussion

External normalization in the three LCIA methods suffers from a systematic bias that emphasizes the same impact categories regardless of the application. Consequently, comparative LCA studies that employ external normalization to guide a selection may result in recommendations dominated entirely by the normalization reference and insensitive to data uncertainty. Conversely, evaluation of mutual differences via the overlap area calls attention to the impact categories with the most significant differences between alternatives. The overlap area approach does not show a systematic bias across LCA applications because it does not depend on external references and it is sensitive to changes in uncertainty. Thus, decisions based on the overlap area approach will draw attention to tradeoffs between alternatives, highlight the role of stakeholder weights, and generate assessments that are responsive to uncertainty.

Conclusions

The solution to the issues of external normalization in comparative LCAs proposed in this study call for an entirely different algorithm capable of evaluating mutual differences and integrating uncertainty in the results.

     

From correlation to causation: analysis of metabolomics data using systems biology approaches

Introduction

Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.

Objectives

This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.

Methods

We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.

Results

We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.

Conclusions

Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.

     

The EcoSpold 2 format—why a new format?

Purpose

This paper introduces the new EcoSpold data format for life cycle inventory (LCI).

Methods

A short historical retrospect on data formats in the life cycle assessment (LCA) field is given. The guiding principles for the revision and implementation are explained. Some technical basics of the data format are described, and changes to the previous data format are explained.

Results

The EcoSpold 2 data format caters for new requirements that have arisen in the LCA field in recent years.

Conclusions

The new data format is the basis for the Ecoinvent v3 database, but since it is an open data format, it is expected to be adopted by other LCI databases. Several new concepts used in the new EcoSpold 2 data format open the way for new possibilities for the LCA practitioners and to expand the application of the datasets in other fields beyond LCA (e.g., Material Flow Analysis, Energy Balancing).

     

Bridge processes: a solution for LCI datasets independent of background databases

Introduction

New platforms are emerging that enable more data providers to publish life cycle inventory data.

Background

Providing datasets that are not complete LCA models results in fragments that are difficult for practitioners to integrate and use for LCA modeling. Additionally, when proxies are used to provide a technosphere input to a process that was not originally intended by the process authors, in most LCA software, this requires modifying the original process.

Results

The use of a bridge process, which is a process created to link two existing processes, is proposed as a solution.

Discussion

Benefits to bridge processes include increasing model transparency, facilitating dataset sharing and integration without compromising original dataset integrity and independence, providing a structure with which to make the data quality associated with process linkages explicit, and increasing model flexibility in the case that multiple bridges are provided. A drawback is that they add additional processes to existing LCA models which will increase their size.

Conclusions

Bridge processes can be an enabler in allowing users to integrate new datasets without modifying them to link to background databases or other processes they have available. They may not be the ideal long-term solution but provide a solution that works within the existing LCA data model.

     

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

Purpose

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

Methods

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

Results and discussion

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

Conclusions

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

     

The application of life cycle assessment to public policy development

Purpose

Despite the potential value it offers, integration of life cycle assessment (LCA) into the development of environmental public policy has been limited. This paper researches potential barriers that may be limiting the use of LCA in public policy development, and considers process opportunities to increase this application.

Methods

Research presented in this paper is primarily derived from reviews of existing literature and case studies, as well as interviews with key public policy officials with LCA experience. Direct experience of the author in LCA projects with public policy elements has also contributed to approaches and conclusions.

Results and discussion

LCAs have historically been applied within a rational framework, with experts conducting the analysis and presenting results to decision-makers for application to public policy development. This segmented approach has resulted in limited incorporation of LCA results or even a broader approach of life cycle thinking within the public policy development process. Barriers that limit the application of LCA within the public policy development process range from lack of technical knowledge and LCA understanding on the part of policy makers, to a lack of trust in LCA process and results. Many of the identified barriers suggest that the failure of LCAs to contribute positively to public policy development is due to the process within which the LCA is being incorporated, rather than technical problems in the LCA itself. Overcoming the barriers to effective use of LCAs in public policy development will require a more normative approach to the LCA process that incorporates a broad group of stakeholders at all stages of the assessment. Specifically, a set of recommendations have been developed to produce a more inclusive and effective process.

Conclusions

In an effort to effectively incorporate LCA within the overall public policy decision-making process, the decision-making process should incorporate a multi-disciplinary approach that includes a range of stakeholders and public policy decision-makers in a collaborative process. One of the most important aspects of incorporating LCA into public policy decisions is to encourage life cycle thinking among policy makers. Considering the life cycle implications will result in more informed and thoughtful decisions, even if a full LCA is not undertaken.

     

Inclusion of uncertainty in the LCA comparison of different cherry tomato production scenarios

Purpose

Knowledge regarding environmental impacts of agricultural systems is required. Consideration of uncertainty in life cycle assessment (LCA) provides additional scientific information for decision making. The aims of this study were to compare the environmental impacts of different growing cherry tomato cultivation scenarios under Mediterranean conditions and to assess the uncertainty associated to the different agricultural production scenarios.

Materials and methods

The burdens associated to cherry tomato production were calculated and evaluated by the LCA methodology. The functional unit (FU) chosen for this study was the mass unit of 1 t of commercial loose cherry tomatoes. This study included the quantitative uncertainty analysis through Monte Carlo simulation. Three scenarios were considered: greenhouse (GH), screenhouse (SH), and open field (OF). The flows and processes of the product scenario were structured in several sections: structure, auxiliary equipment, fertilizers, crop management, pesticides, and waste management. Six midpoint impact categories were selected for their relevance: climate change, terrestrial acidification, marine eutrophication, metal depletion, and fossil depletion using the impact evaluation method Recipe Midpoint and ecotoxicity using USEtox.

Results and discussion

The structure, auxiliary equipment, and fertilizers produced the largest environmental impacts in cherry tomato production. The greatest impact in these stages was found in the manufacture and drawing of the steel structures, manufacture of perlite, the amount of HDPE plastics used, and the electricity consumed by the irrigation system and the manufacture and application of fertilizers. GH was the cropping scenario with the largest environmental impact in most categories (varying from 18 and 37% higher than SH and OF, respectively, in metal depletion, to 96% higher than SH and OF, in eutrophication). OF showed the highest uncertainty in ecotoxicity, with a bandwidth of 60 CTUe and a probability of 100 and 99.4% to be higher than GH and SH, respectively.

Conclusions

The LCA was used to improve the identification and evaluation of the environmental burdens for cherry tomato production in the Mediterranean area. This study demonstrates the significance of conducting uncertainty analyses for comparative LCAs used in comparative relative product environmental impacts.

     

Choice of land reference situation in life cycle impact assessment

Purpose

Land use life cycle impact assessment is calculated as a distance to target value—the target being a desirable situation defined as a reference situation in Milà i Canals et al.’s (Int J Life Cycle Assess 12(1):2–4, 2007) widely accepted framework. There are several reference situations. This work aims to demonstrate the effect of the choice of reference situation on land impact indicators.

Methods

Various reference situations are reported from the perspective of the object of assessment in land in life cycle assessment (LCA) studies and the modeling choices used in life cycle land impact indicators. They are analyzed and classified according to additional LCA modeling requirements: the type of LCA approach (attributional or consequential), cultural perspectives (egalitarian, hierarchist or individualist), and temporal preference. Sets of characterization factors (CF) by impact pathway, land cover, and region are calculated for different reference situations. These sets of CFs by reference situation are all compared with a baseline set. A case study on different crop types is used to calculate impact scores from different sets of CFs and compare them.

Results and discussion

Comparing the rankings of the CFs from two different sets present inversions from 5% to 35% worldwide. Impact scores of the case study present inversions of 10% worldwide. These inversions demonstrate that the choice of a reference situation may reverse the LCA conclusions for the land use impact category. Moreover, these reference situations must be consistent with the different modeling requirements of an LCA study (approach, cultural perspective, and time preference), as defined in the goal and scope.

Conclusions

A decision tree is proposed to guide the selection of a consistent and suitable choice of reference situation when setting other LCA modeling requirements.

     

Principles for life cycle inventories of land use on a global scale

Purpose

To assess the diverse environmental impacts of land use, a standardization of quantifying land use elementary flows is needed in life cycle assessment (LCA). The purpose of this paper is to propose how to standardize the land use classification and how to regionalize land use elementary flows.

Materials and methods

In life cycle inventories, land occupation and transformation are elementary flows providing relevant information on the type and location of land use for land use impact assessment. To find a suitable land use classification system for LCA, existing global land cover classification systems and global approaches to define biogeographical regions are reviewed.

Results and discussion

A new multi-level classification of land use is presented. It consists of four levels of detail ranging from very general global land cover classes to more refined categories and very specific categories indicating land use intensities. Regionalization is built on five levels, first distinguishing between terrestrial, freshwater, and marine biomes and further specifying climatic regions, specific biomes, ecoregions and finally indicating the exact geo-referenced information of land use. Current land use inventories and impact assessment methods do not always match and hinder a comprehensive assessment of land use impact. A standardized definition of land use types and geographic location helps to overcome this gap and provides the opportunity to test the optimal resolution of land cover types and regionalization for each impact pathway.

Conclusions and recommendation

The presented approach provides the necessary flexibility to providers of inventories and developers of impact assessment methods. To simplify inventories and impact assessment methods of land use, we need to find archetypical situations across impact pathways, land use types and regions, and aggregate inventory entries and methods accordingly.

     

Comparing land use impacts using ecosystem quality,biogenic carbon emissions,and restoration costs in a case study of hydropower plants in Norway

Purpose

Habitat destruction is today the most severe threat to global biodiversity. Despite decades of efforts, there is still no proper methodology on how to assess all aspects of impacts on biodiversity from land use and land use changes (LULUC) in life cycle analysis (LCA). A majority of LCA studies on land extensive activities still do not include LULUC. In this study, we test different approaches for assessing the impact of land use and land use change related to hydropower for use in LCA and introduce restoration cost as a new approach.

Methods

We assessed four hydropower plant projects in planning phase (two upgrading plants with reservoir and two new run-of-river plants) in Southern Norway with comparable geography, biodiversity, and annual energy production capacity. LULUC was calculated for each habitat type, based on mapping of present and future land use, and was further allocated to energy production for each power plant. Three different approaches to assess land use impact were included: ecosystem scarcity/vulnerability, biogenic greenhouse gas (bGHG) emissions, and the cost of restoring affected habitats. Restoration cost represents a novel approach to LCA for measuring impact of LULUC.

Results and discussion

Overall, the three approaches give similar rankings of impacts: larger impact for small and new power plants and less for larger and expanding existing plants. Reservoirs caused a larger total area affected. Permanent infrastructure has a more similar absolute impact for run-of-river and reservoir-based hydropower, and consequently give relatively larger impact for smaller run-of-river hydropower. All approaches reveal impacts on wetland ecosystems as most important relative to other ecosystems. The methods used for all three approaches would benefit from higher resolution data on land use, habitats, and soil types. Total restoration cost is not accurate, due to uncertainty of offset ratios, but relative restoration costs may still be used to rank restoration alternatives and compare them to the costs of biodiversity offsets.

Conclusions

The different approaches assess different aspects of land use impacts, but they all show large variation of impact between the studied hydropower plants, which shows the importance of including LULUC in LCA for hydropower projects. Improved data of total restoration cost (and cost accounting) are needed to implement this approach in future LCA.

     

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.