Moving towards an Egyptian national life cycle inventory database

Purpose

Life cycle inventory (LCI) data are region-specific because energy fuel mixtures and methods of production often differ from region to region. LCI database examples include US LCI, Ecoinvent v.2, and NIST, each of which is country-specific. Thus, the main aim of this study is to show that Egypt is in need of an Egyptian National LCI (ENLCI) database and to focus on the means of developing a database specific to Egypt.

Methods

Arab countries have thus far engaged in virtually no life cycle assessment (LCA) studies, and a significant neglect of this matter is in evidence for the continent of Africa and, in particular, Egypt. Thus, this study suggests an organizational and managerial framework for the development of a national LCI database and sheds light on the required LCI database categories and data quality for practical solutions reflecting who is equipped to do what in order to keep pace with the world.

Results

The results from this review are useful to standardize the study of the life cycle assessment concept in Egypt; to form a foundation for development of an Egyptian database for facilitating a cleaner environment; to encourage stakeholders, such as the environmental agencies, Egyptian Housing and Building Research Center, and the Ministry of Industry; to propose an organizational framework in which they play a central role; and to provide investment to initiate development.

Conclusions

The analysis indicates that the development of a LCI database specific to Egypt is difficult because Egypt has various technical and organizational challenges, but a roadmap of actions to be taken to move ahead is provided. The success of this roadmap depends on the capacity for developing the necessary technical and financial support and on strong partnerships with industry, government, LCA professionals, and academia.     

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.     

Application of robust optimization in matrix-based LCI for decision making under uncertainty

Purpose

When product systems are optimized to minimize environmental impacts, uncertainty in the process data may impact optimal decisions. The purpose of this article is to propose a mathematical method for life cycle assessment (LCA) optimization that protects decisions against uncertainty at the life cycle inventory (LCI) stage.

Methods

A robust optimization approach is proposed for decision making under uncertainty in the LCI stage. The proposed approach incorporates data uncertainty into an optimization problem in which the matrix-based LCI model appears as a constraint. The level of protection against data uncertainty in the technology and intervention matrices can be controlled to reflect varying degrees of conservatism.

Results and discussion

A simple numerical example on an electricity generation product system is used to illustrate the main features of this methodology. A comparison is made between a robust optimization approach, and decision making using a Monte Carlo analysis. Challenges to implement the robust optimization approach on common uncertainty distributions found in LCA and on large product systems are discussed. Supporting source code is available for download at https://github.com/renwang/Robust_Optimization_LCI_Uncertainty.

Conclusions

A robust optimization approach for matrix-based LCI is proposed. The approach incorporates data uncertainties into an optimization framework for LCI and provides a mechanism to control the level of protection against uncertainty. The tool computes optimal decisions that protects against worst-case realizations of data uncertainty. The robust optimal solution is conservative and is able to avoid the negative consequences of uncertainty in decision making.     

Quantifying system uncertainty of life cycle assessment based on Monte Carlo simulation

Background, aim, and scope

Many studies evaluate the results of applying different life cycle impact assessment (LCIA) methods to the same life cycle inventory (LCI) data and demonstrate that the assessment results would be different with different LICA methods used. Although the importance of uncertainty is recognized, most studies focus on individual stages of LCA, such as LCI and normalization and weighting stages of LCIA. However, an important question has not been answered in previous studies: Which part of the LCA processes will lead to the primary uncertainty? The understanding of the uncertainty contributions of each of the LCA components will facilitate the improvement of the credibility of LCA.

Methodology

A methodology is proposed to systematically analyze the uncertainties involved in the entire procedure of LCA. The Monte Carlo simulation is used to analyze the uncertainties associated with LCI, LCIA, and the normalization and weighting processes. Five LCIA methods are considered in this study, i.e., Eco-indicator 99, EDIP, EPS, IMPACT 2002+, and LIME. The uncertainty of the environmental performance for individual impact categories (e.g., global warming, ecotoxicity, acidification, eutrophication, photochemical smog, human health) is also calculated and compared. The LCA of municipal solid waste management strategies in Taiwan is used as a case study to illustrate the proposed methodology.

Results

The primary uncertainty source in the case study is the LCI stage under a given LCIA method. In comparison with various LCIA methods, EDIP has the highest uncertainty and Eco-indicator 99 the lowest uncertainty. Setting aside the uncertainty caused by LCI, the weighting step has higher uncertainty than the normalization step when Eco-indicator 99 is used. Comparing the uncertainty of various impact categories, the lowest is global warming, followed by eutrophication. Ecotoxicity, human health, and photochemical smog have higher uncertainty.

Discussion

In this case study of municipal waste management, it is confirmed that different LCIA methods would generate different assessment results. In other words, selection of LCIA methods is an important source of uncertainty. In this study, the impacts of human health, ecotoxicity, and photochemical smog can vary a lot when the uncertainties of LCI and LCIA procedures are considered. For the purpose of reducing the errors of impact estimation because of geographic differences, it is important to determine whether and which modifications of assessment of impact categories based on local conditions are necessary.

Conclusions

This study develops a methodology of systematically evaluating the uncertainties involved in the entire LCA procedure to identify the contributions of different assessment stages to the overall uncertainty. Which modifications of the assessment of impact categories are needed can be determined based on the comparison of uncertainty of impact categories.

Recommendations and perspectives

Such an assessment of the system uncertainty of LCA will facilitate the improvement of LCA. If the main source of uncertainty is the LCI stage, the researchers should focus on the data quality of the LCI data. If the primary source of uncertainty is the LCIA stage, direct application of LCIA to non-LCIA software developing nations should be avoided.     

A framework for modelling the transport and deposition of eroded particles towards water systems in a life cycle inventory

Purpose

Topsoil erosion due to land use has been characterised as one of the most damaging problems from the perspective of soil-resource depletion, changes in soil fertility and net soil productivity and damage to aquatic ecosystems. On-site environmental damage to topsoil by water erosion has begun to be considered in Life Cycle Assessment (LCA) within the context of ecosystem services. However, a framework for modelling soil erosion by water, addressing off-site deposition in surface water systems, to support life cycle inventory (LCI) modelling is still lacking. The objectives of this paper are to conduct an overview of existing methods addressing topsoil erosion issues in LCA and to develop a framework to support LCI modelling of topsoil erosion, transport and deposition in surface water systems, to establish a procedure for assessing the environmental damage from topsoil erosion on water ecosystems.

Methods

The main features of existing methods addressing topsoil erosion issues in LCA are analysed, particularly with respect to LCI and Life Cycle Impact Assessment methodologies. An overview of nine topsoil erosion models is performed to estimate topsoil erosion by water, soil particle transport through the landscape and its in-stream deposition. The type of erosion evaluated by each of the models, as well as their applicable spatial scale, level of input data requirements and operational complexity issues are considered. The WATEM-SEDEM model is proposed as the most adequate to perform LCI erosion analysis.

Results and discussion

The definition of land use type, the area of assessment, spatial location and system boundaries are the main elements discussed. Depending on the defined system boundaries and the inherent routing network of the detached soil particles to the water systems, the solving of the multifunctionality of the system assumes particular relevance. Simplifications related to the spatial variability of the input data parameters are recommended. Finally, a sensitivity analysis is recommended to evaluate the effects of the transport capacity coefficient in the LCI results.

Conclusions

The published LCA methods focus only on the changes of soil properties due to topsoil erosion by water. This study provides a simplified framework to perform an LCI of topsoil erosion by considering off-site deposition of eroded particles in surface water systems. The widespread use of the proposed framework would require the development of LCI erosion databases. The issues of topsoil erosion impact on aquatic biodiversity, including the development of characterisation factors, are now the subject of on-going research.     

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.     

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).

     

Life cycle inventory processes of the Mittal Steel Poland (MSP) S.A. in Krakow, Poland—blast furnace pig iron production—a case study

Purpose

The goal of this paper is to describe the life cycle inventory (LCI) approach of pig iron produced by Mittal??s Steel Poland Blast Furnace (MSPBF) in Krakow, Poland. The present LCI is representative for the reference year 2005 by application of PN-EN ISO 14040: 2009 (PN-EN ISO 2009). The system boundaries were labeled as gate-to-gate (covering a full chain process of pig iron production). The background input and output data from the blast furnace (BF) process have been inventoried as follows: sinter, several types of pellets, ore (from Brazil or Venezuela), limestone, coke, and from 2005 coal powder, pig iron, blast furnace gas, blast furnace slug, consumption of energy and fuels, including: pulverized coal, natural gas, blast furnace gas and coke oven gas, and emission of air pollutants.

Main feature

LCI energy generation was developed mainly on the basis of following sources: site specific measured or calculated data, study carried out by Mittal Steel Poland (MSP) Environmental Impact Report, study carried out by the Faculty of Mining Surveying and Environmental Engineering of the AGH University of Science and Technology in Krakow, literature information, and expert consultations. The functional unit is represented by 1,504,088?Mg of pig iron, produced BF process. Time coverage is 2005. Operating parameters as well as air emissions associated with the BF process were presented. The production data (pig iron) was given. The emissions of SO₂, NO₂, CO, CO₂, aliphatic hydrocarbons, dust, heavy metals (Cr, Cd, Cu, Pb, Ni, and Mn), and waste are the most important outcomes of the pig iron process.

Results

With regard to 1,504,088?Mg of pig iron produced by MSP, the consumption of coke, pulverized coal, sinters, pellets, and natural gas were 808,509, 16,921, 1,669,023, and 914,080?Mg, respectively. Other material consumption, industrial water, was 1,401,419 m³/year.

Conclusions

The LCI study is the first tentative study to express pig iron production in Poland in terms of LCA/LCI for the pig iron in steel industry. The results may help steel industry government make decisions in policy making. Presentation of the study in this paper is suitable for the other industries.

Recommendations and outlook

The LCI offers environmental information consisting on the list of environmental loads. The impact assessment phase aims the results from the inventory analysis more understandable and life cycle impact assessment will be direction for future research. Another issue to discuss is integration of LCA and risk assessment for industrial processed.     

PestLCI 2.0: a second generation model for estimating emissions of pesticides from arable land in LCA

Purpose

The spatial dependency of pesticide emissions to air, surface water and groundwater is illustrated and quantified using PestLCI 2.0, an updated and expanded version of PestLCI 1.0.

Methods

PestLCI is a model capable of estimating pesticide emissions to air, surface water and groundwater for use in life cycle inventory (LCI) modelling of field applications. After calculating the primary distribution of pesticides between crop and soil, specific modules calculate the pesticide??s fate, thus determining the pesticide emission pattern for the application. PestLCI 2.0 was developed to overcome the limitations of the first model version, replacement of fate calculation equations and introducing new modules for macropore flow and effects of tillage. The accompanying pesticide database was expanded, the meteorological and soil databases were extended to include a range of European climatic zones and soil profiles. Environmental emissions calculated by PestLCI 2.0 were compared to results from the risk assessment models SWASH (surface water emissions), FOCUSPEARL (groundwater via matrix leaching) and MACRO (groundwater including macropore flow, only one scenario available) to partially validate the updated model. A case study was carried out to demonstrate the spatial variation of pesticide emission patterns due to dependency on meteorological and soil conditions.

Results

Compared to PestLCI 1.0, PestLCI 2.0 calculated lower emissions to surface water and higher emissions to groundwater. Both changes were expected due to new pesticide fate calculation approaches and the inclusion of macropore flow. Differences between the SWASH and FOCUSPEARL and PestLCI 2.0 emission estimates were generally lower than 2 orders of magnitude, with PestLCI generally calculating lower emissions. This is attributed to the LCA approach to quantify average cases, contrasting with the worst-case risk assessment approach inherent to risk assessment. Compared to MACRO, the PestLCI 2.0 estimates for emissions to groundwater were higher, suggesting that PestLCI 2.0 estimates of fractions leached to groundwater may be slightly conservative as a consequence of the chosen macropore modelling approach. The case study showed that the distribution of pesticide emissions between environmental compartments strongly depends on local climate and soil characteristics.

Conclusions

PestLCI 2.0 is partly validated in this paper. Judging from the validation data and case study, PestLCI 2.0 is a pesticide emission model in acceptable accordance with both state-of-the-art pesticide risk assessment models. The case study underlines that the common pesticide emission estimation practice in LCI may lead to misestimating the toxicity impacts of pesticide use in LCA.     

Assessing freshwater use impacts in LCA: Part I—inventory modelling and characterisation factors for the main impact pathways

Background, aim and scope

Freshwater is a basic resource for humans; however, its link to human health is seldom related to lack of physical access to sufficient freshwater, but rather to poor distribution and access to safe water supplies. On the other hand, freshwater availability for aquatic ecosystems is often reduced due to competition with human uses, potentially leading to impacts on ecosystem quality. This paper summarises how this specific resource use can be dealt with in life cycle analysis (LCA).

Main features

The main quantifiable impact pathways linking freshwater use to the available supply are identified, leading to definition of the flows requiring quantification in the life cycle inventory (LCI).

Results

The LCI needs to distinguish between and quantify evaporative and non-evaporative uses of ‘blue’ and ‘green’ water, along with land use changes leading to changes in the availability of freshwater. Suitable indicators are suggested for the two main impact pathways [namely freshwater ecosystem impact (FEI) and freshwater depletion (FD)], and operational characterisation factors are provided for a range of countries and situations. For FEI, indicators relating current freshwater use to the available freshwater resources (with and without specific consideration of water ecosystem requirements) are suggested. For FD, the parameters required for evaluation of the commonly used abiotic depletion potentials are explored.

Discussion

An important value judgement when dealing with water use impacts is the omission or consideration of non-evaporative uses of water as impacting ecosystems. We suggest considering only evaporative uses as a default procedure, although more precautionary approaches (e.g. an ‘Egalitarian’ approach) may also include non-evaporative uses. Variation in seasonal river flows is not captured in the approach suggested for FEI, even though abstractions during droughts may have dramatic consequences for ecosystems; this has been considered beyond the scope of LCA.

Conclusions

The approach suggested here improves the representation of impacts associated with freshwater use in LCA. The information required by the approach is generally available to LCA practitioners

Recommendations and perspectives

The widespread use of the approach suggested here will require some development (and consensus) by LCI database developers. Linking the suggested midpoint indicators for FEI to a damage approach will require further analysis of the relationship between FEI indicators and ecosystem health.     

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

Purpose

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

Methods

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

Results and discussion

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

Conclusions

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

Notions on the Design and Use of an Ideal Regional or Global LCA Database

Goal, Scope and Background

More and more national and regional life cycle assessment (LCA) databases are being established satisfying the increasing demand on LCA in policy making (e.g. Integrated Product Policy, IPP) and in industry. In order to create harmonised datasets in such unified databases, a common understanding and common rules are required. This paper describes major requirements on the way towards an ideal national background LCA database in terms of co-operation, but also in terms of life cycle inventory analysis (LCI) and impact assessment (LCIA) methodology.

Methods

A classification of disputed methodological issues is made according to their consensus potential. In LCI, three main areas of dissent are identified where consensus seems hardly possible, namely system modelling (consequential versus attributional), allocation (including recycling) and reporting (transparency and progressiveness). In LCIA the time aspect is added to the well-known value judgements of the weighting step.

Results and Discussions

It is concluded that LCA methodology should rather allow for plurality than to urge harmonisation in any case. A series of questions is proposed to identify the most appropriate content of the LCA background database or the most appropriate LCI dataset. The questions help to identify the best suited approach in modelling the product system in general and multioutput and recycling processes in particular. They additionally help to clarify the position with regard to time preferences in LCIA. Intentionally, the answers to these questions are not attributed to particular goal and scope definitions, although some recommendations and clarifying explanations are provided.

Recommendations and Perspective

It is concluded that there is not one single ideal background database content. Value judgements are also present in LCI modelling and require pluralistic solutions; solutions possibly based on the same primary data. It is recommended to focus the methodological discussion on aspects where consensus is within reach, sensible and of added value for all parties.

     

Temporal differentiation of background systems in LCA: relevance of adding temporal information in LCI databases

Purpose

Because the potential impacts of emissions and extractions can be sensitive to timing, the temporal aggregation of life cycle inventory (LCI) data has often been cited as a limitation in life cycle assessment (LCA). Until now, examples of temporal emission and extraction distributions were restricted to the foreground processes of product systems. The objective of this paper is to evaluate the relevance of considering the temporal distribution of the background system inventory.

Methods

The paper focuses on the global warming impact category for which so-called dynamic characterization factors (CFs) were developed and uses the ecoinvent v2.2 database as both an example database to which temporal information can be added and a source of product systems to test the relevance of adding temporal information to the background system. Temporal information was added to the elementary and intermediate exchanges of 22 % of the unit processes in the database. Using the enhanced structure path analysis (ESPA) method to generate temporally differentiated LCIs in conjunction with time-dependent global warming characterization factors, potential impacts were calculated for all 4,034 product systems in the ecoinvent database.

Results and discussion

Each time, the results were calculated for (1) systems in which temporal information was only added to the first two tiers, representing studies in which only the foreground system is temporally differentiated, and (2) systems in which temporal information was also added to the background system. For 8.6 % of the database product systems, adding temporal differentiation to background unit processes affected the global warming impact scores by more than 10 %. For most of the affected product systems, considering temporal information in the background unit processes decreased the global warming impact scores. The sectors that show most sensitivity to the temporal differentiation of background unit processes are associated with wood and biofuel sectors.

Conclusions

Even though the addition of temporal information to unit processes in LCI databases would not benefit every LCA study, the enhancement can be relevant. It allows for a more accurate global warming impact assessment, especially for LCAs in which products of biomass are present in substantial amounts. Relevance for other impact categories could be discussed in further work.     

The ecoinvent database version 3 (part I): overview and methodology

Purpose

Good background data are an important requirement in LCA. Practitioners generally make use of LCI databases for such data, and the ecoinvent database is the largest transparent unit-process LCI database worldwide. Since its first release in 2003, it has been continuously updated, and version 3 was published in 2013. The release of version 3 introduced several significant methodological and technological improvements, besides a large number of new and updated datasets. The aim was to expand the content of the database, set the foundation for a truly global database, support regionalized LCIA, offer multiple system models, allow for easier integration of data from different regions, and reduce maintenance efforts. This article describes the methodological developments.

Methods

Modeling choices and raw data were separated in version 3, which enables the application of different sets of modeling choices, or system models, to the same raw data with little effort. This includes one system model for Consequential LCA. Flow properties were added to all exchanges in the database, giving more information on the inventory and allowing a fast calculation of mass and other balances. With version 3.1, the database is generally water-balanced, and water use and consumption can be determined. Consumption mixes called market datasets were consistently added to the database, and global background data was added, often as an extrapolation from regional data.

Results and discussion

In combination with hundreds of new unit processes from regions outside Europe, these changes lead to an improved modeling of global supply chains, and a more realistic distribution of impacts in regionalized LCIA. The new mixes also facilitate further regionalization due to the availability of background data for all regions.

Conclusions

With version 3, the ecoinvent database substantially expands the goals and scopes of LCA studies it can support. The new system models allow new, different studies to be performed. Global supply chains and market datasets significantly increase the relevance of the database outside of Europe, and regionalized LCA is supported by the data. Datasets are more transparent, include more information, and support, e.g., water balances. The developments also support easier collaboration with other database initiatives, as demonstrated by a first successful collaboration with a data project in Québec. Version 3 has set the foundation for expanding ecoinvent from a mostly regional into a truly global database and offers many new insights beyond the thousands of new and updated datasets it also introduced.

     

The Quebec Life Cycle Inventory Database Project

Purpose

Life cycle assessment (LCA) in Quebec (Canada) is increasingly important. Yet, studies often still need to rely on foreign life cycle inventory (LCI) data. The Quebec government invested in the creation of a Quebec LCI database. The approach is to work as an ecoinvent “National Database Initiative” (NDI), whereby the Quebec database initiative uses and contributes to the ecoinvent database. The paper clarifies the relationship between ecoinvent and the Quebec NDI and provides details on prioritization and data collection.

Methods

The first steps were to select a partner database provider and to work out the modalities of the partnership. The main criterion for partner selection was database transparency, i.e., availability of unit process data (gate-to-gate), necessary for database adaptation. This and other criteria, such as free access to external reviewers, conservation of dataset copyright, seamless embedding of datasets, and overall database sophistication, pointed to ecoinvent. Once started, the NDI project proceeded as follows: (1) data collection was prioritized based on several criteria; (2) some datasets were “recontextualized,” i.e., existing datasets were duplicated and relocated in Quebec and linked to datasets representing regional suppliers, where relevant; (3) new datasets were created; and (4) Canadian environmentally extended supply-use tables were created for the ecoinvent IO repository.

Results and discussion

Prioritization identified 500 candidate datasets for recontextualization, based on the relative importance of relative contribution of direct electricity consumption to cradle-to-gate impacts, and 12 key sectors from which about 450 data adaptation or collection projects were singled out. Data collection and private sector solicitation are underway. Private sector participation is highly variable. A number of communication tools have been elaborated and a solicitation team formed to palliate this obstacle. The new ecoinvent database protocol (Weidema et al. 2011) increases the amount of information that is required to create a dataset, which can lengthen or, in extreme cases, impede dataset creation. However, this new information is required for the new database functionalities (e.g., providing multiple system models based on the same unit process data and regionalized LCA).

Conclusions

Being an NDI is advantageous for the Quebec LCI database project on multiple levels. By conserving dataset copyright, the NDI remains free to spawn or support other LCI databases. Embedding datasets in ecoinvent enables the generation of LCI results from “day 1.” The costs of IT infrastructure and data review are null. For these reasons, and because every NDI improves the global representativity of ecoinvent, we recommend other regional or national database projects work as NDIs.

     

A new hybrid method for reducing the gap between WTW and LCA in the carbon footprint assessment of electric vehicles

Purpose

The well-to-wheel (WTW) methodology is widely used for policy support in road transport. It can be seen as a simplified life cycle assessment (LCA) that focuses on the energy consumption and CO₂ emissions only for the fuel being consumed, ignoring other stages of a vehicle’s life cycle. WTW results are therefore different from LCA results. In order to close this gap, the authors propose a hybrid WTW+LCA methodology useful to assess the greenhouse gas (GHG) profiles of road vehicles.

Methods

The proposed method (hybrid WTW+LCA) keeps the main hypotheses of the WTW methodology, but integrates them with LCA data restricted to the global warming potential (GWP) occurring during the manufacturing of the battery pack. WTW data are used for the GHG intensity of the EU electric mix, after a consistency check with the main life cycle impact (LCI) sources available in literature.

Results and discussion

A numerical example is provided, comparing GHG emissions due to the use of a battery electric vehicle (BEV) with emissions from an internal combustion engine vehicle. This comparison is done both according to the WTW approach (namely the JEC WTW version 4) and the proposed hybrid WTW+LCA method. The GHG savings due to the use of BEVs calculated with the WTW-4 range between 44 and 56 %, while according to the hybrid method the savings are lower (31–46 %). This difference is due to the GWP which arises as a result of the manufacturing of the battery pack for the electric vehicles.

Conclusions

The WTW methodology used in policy support to quantify energy content and GHG emissions of fuels and powertrains can produce results closer to the LCA methodology by adopting a hybrid WTW+LCA approach. While evaluating GHG savings due to the use of BEVs, it is important that this method considers the GWP due to the manufacturing of the battery pack.

     

10-year experience with the Thai national LCI database: case study of “refinery products”

Purpose

Due to various environmental pressures such as climate change and scarcity of natural resources, as well as nontariff barriers from trade partners, Thailand has established the Thai national life cycle inventory (LCI) database in 2006. In the 1st phase (2006–2007), three working groups were developed for natural gas, refinery, and petrochemical products. Another seven working groups were established in the 2nd phase (2007–2010) for ferrous and non-ferrous metals, utilities and transportation, construction materials, agricultural materials and products, basic chemicals, recycling and waste management, and others. In the 3rd phase (2010 to present), expansion of the number of data sets from the previous phases has been carried out. The purpose of this paper is to present the experiences on national database development in emerging countries with the example of Thailand on both strategic and technical levels using refinery products as the case study.

Methods

Data sets were developed according to ISO 14044:2006. The LCI data were managed and archived at the central facility known as the “central LCI database”. The Life Cycle Assessment lab (LCA lab) at MTEC, NSTDA, has been responsible for the central LCI database management. From 2008 to 2010, the “Thai national LCI database and its applications” project was granted a 3-year funding of over 50 million THB, and was operated under supervision of a steering committee set up by the Ministry of Industry (MoI). For this case study, to illustrate the development process, primary data of the refinery products were collected by Petroleum Institute of Thailand in the year 2005 from seven refineries covering more than 70 % of the production in the country. Attributional modelling has been used, with energy content as an allocation criterion.

Results and discussion

During the initial phase of the “Thai National LCI Database Development Project”, two key barriers have been faced. One was the lack of awareness from stakeholders as LCI and LCA were quite new tools for most people in Thailand. This problem was tackled by collaborating with the right strategic partners to drive the LCI national project and educating stakeholders with the training supports from Japan. The other hindrance was the lack of expertise of local experts on LCA. It took several years to continually build the capacity through seminars and workshops in Thailand and Japan, including “on the job training” on some pilot projects. As of May 2016, there were more than 700 data sets in the Thai national LCI database, considering only the data that MTEC acted as the project commissioner. However, only 515 data were certified as the national database. The other 211 data were qualified merely as the data from pilot projects. More details of the database list and how to access the data can be viewed in Thai language at the URL: http://www.thailcidatabase.net. Because the Thai national LCI data were mostly primary data from a core set of products for the Thai economy with a very high representativeness (>60 %) of the actual Thai productions, the data have been treated carefully. Only C-to-G data and G-to-G data from literature were allowed to disclose to Thai delegates with some signing agreements. However, G-to-G data from the actual Thai productions were sometimes provided, only with the signing confidentiality contracts. For refinery products, seven average data sets were established as national LCI data sets, i.e. liquefied petroleum gas, sulfur, gasoline, kerosene/jet oil, naphtha, fuel oil and diesel, with the year 2005 as the reference year. The data representativeness was very high covering more than 70 % of the production in Thailand. Due to the positive feedback and engagement from industries, several LCI projects have been started after this initial phase. The national LCI data sets have been used in various national applications and policies such as sustainable biofuels, government green public procurement, green GDP, Thai carbon footprint, etc. However, some relevant limitations of the Thai LCI database were listed as follows. Similar to most surveyed national LCI database worldwide, the climate change impact category has been chosen as the main focus for these data sets. Nevertheless, there is a more growing demand to use the data for other applications. As a result, more data sets that cover other impact categories will be required in the near future. Regarding the nomenclature and format, the Thai data sets were technically unique and not fully compatible with any other database.

Conclusions

The Thai national LCI database could be considered as the pioneer case for other countries in the South East Asia region. Thailand has further progressed in its LCI database development. Since 2009, the Thai national LCI database has been used as one of the key infrastructures of Thailand to support public policies and applications related to green growth. Many Thai stakeholders are well aware on LCI, LCA, and EcoDesign. Expertise of local experts has been increasingly improved. However, there are still more challenges to be faced to harvest the value of the Thai database in its full potential for better decision making in industry and policy, and for better positioning of Thai products on the global markets. From our experience, the following issues could be identified as “lessons learned”. At the onset of the project, it was crucial to get in expert advices from LCA-experienced countries to establish local expertise. Also, industry experts from abroad could help in clarifying the concept and addressing confidentiality concerns, as well as building awareness on LCA to Thai industries. Searching for some supporting programmes for capacity building, such as the GPP from Japan in our case, could provide great benefits to any emerging economies for national LCI initiatives. However, sustaining the trained human resources was also vital. Continual funding supports for LCI development and its applications were necessary to keep the momentum of active people in the field. Multiplying effect of the LCI knowledge to related organizations in the three main groups, i.e. government, academia, and industries, could help sustain the knowhow. Also, effective knowledge management through media such as books, guidelines, training courses, etc. would relief the turnover problem of trained staffs. Although it took a lot of time to develop local expertise, it was an essential step to have sufficient number of local experts to sustain the national database project. Moreover, a strong network of experts and researchers locally and internationally also strengthened the technical capacity to deal with any challenges during the project implementation. Furthermore, collaboration with the right strategic partners to drive the project was also very important in order to elevate it to the national level. It should be noted for any emerging economies aiming to initiate national LCI, the work plan for LCI database development (including the database management system) and its applications should be well balanced. Also, a well-designed database management system would enhance the database usage in the long run, especially when dealing with various impact categories like those in PEF.

     

LCA benchmarking study on textiles made of cotton,polyester, nylon,acryl, or elastane

Purpose

The purpose of this paper is to provide an improved (up-to-date) insight into the environmental burden of textiles made of the base materials cotton, polyester (PET), nylon, acryl, and elastane. The research question is: Which base material and which life cycle stage (cradle-to-gate as well as cradle-to-grave) have the biggest impact on the environment?

Methods

Life cycle inventory (LCI) data are collected from the literature, life cycle assessment (LCA) databases, and emission registration database of the Dutch government, as well as communications with both manufacturing companies of production equipment and textile companies. The output of the calculations is presented in four single indicators: Eco-costs 2012 (a prevention-based indicator), CO₂ equivalent (carbon footprint), cumulative energy demand (CED), and ReCiPe (a damage-based indicator).

Results and discussion

From an analysis of the data, it becomes clear that the environmental burden is not only a function of the base materials (cotton, PET, nylon, acryl, and elastane) but also of the thickness of the yarn (for this research, the range of 50–500 dtex is examined). The authors propose that the environmental burden of spinning, weaving, and knitting is a function of 1/yarn size. The cradle-to-grave analysis from raw material extraction to discarded textile demonstrates that textiles made out of acryl and PET have the least impact on the environment, followed by elastane, nylon, and cotton. The use phase has less relative impact than it is suggested in the classical literature.

Conclusions

The impact of spinning and weaving is relatively high (for yarn thicknesses of less than 100 dtex), and from the environmental point of view, knitting is better than weaving. LCA on textiles can only be accurate when the yarn thickness is specified. In case the functional unit also indicates the fabric per square meter, the density must be known. LCA results of textile products over the whole value chain are case dependent, especially when dyeing and finishing processes and the use phase and end-of-life are included in the analysis. Further LCI data studies on textiles and garments are urgently needed to lower the uncertainties in contemporary LCA of textile materials and products.