Life cycle inventories of electricity generation and power supply in version 3 of the ecoinvent database—part I: electricity generation

Purpose

Life cycle inventories (LCI) of electricity generation and supply are among the main determining factors regarding life cycle assessment (LCA) results. Therefore, consistency and representativeness of these data are crucial. The electricity sector has been updated and substantially extended for ecoinvent version 3 (v3). This article provides an overview of the electricity production datasets and insights into key aspects of these v3 inventories, highlights changes and describes new features.

Methods

Methods involved extraction of data and analysis from several publically accessible databases and statistics, as well as from the LCA literature. Depending on the power generation technology, either plant-specific or region-specific average data have been used for creating the new power generation inventories representing specific geographies. Whenever possible, the parent–child relationship was used between global and local activities. All datasets include a specific technology level in order to support marginal mixes used in the consequential version of ecoinvent. The use of parameters, variables and mathematical relations enhances transparency. The article focuses on documentation of LCI data on the unlinked unit process level and presents direct emission data of the electricity-generating activities.

Results and discussion

Datasets for electricity production in 71 geographic regions (geographies) covering 50 countries are available in ecoinvent v3. The number of geographies exceeds the number of countries due to partitioning of power generation in the USA and Canada into several regions. All important technologies representing fossil, renewable and nuclear power are modelled for all geographies. The new inventory data show significant geography-specific variations: thermal power plant efficiencies, direct air pollutant emissions as well as annual yields of photovoltaic and wind power plants will have significant impacts on cumulative inventories. In general, the power plants operating in the 18 newly implemented countries (compared to ecoinvent v2) are on a lower technology level with lower efficiencies and higher emissions. The importance of local datasets is once more highlighted.

Conclusions

Inventories for average technology-specific electricity production in all globally important economies are now available with geography-specific technology datasets. This improved coverage of power generation representing 83 % of global electricity production in 2008 will increase the quality of and reduce uncertainties in LCA studies worldwide and contribute to a more accurate estimation of environmental burdens from global production chains. Future work on LCI of electricity production should focus on updates of the fuel chain and infrastructure datasets, on including new technologies as well as on refining of the local data.

     

Life cycle inventories of electricity generation and power supply in version 3 of the ecoinvent database—part II: electricity markets

Purpose

Representative, consistent and up-to-date life cycle inventories (LCI) of electricity supply are key elements of ecoinvent as an LCI background database since these are often among the determining factors with regard to life cycle assessment (LCA) results. ecoinvent version 3 (ev3) offers new LCI data of power supply (electricity markets) in 71 geographies. This article gives an overview of these electricity markets and discusses new ecoinvent features in the context of power supply.

Methods

The annual geography- and technology-specific electricity production for the year 2008 specifies the technology shares on the high-, medium- and low-voltage level electricity markets. Data are based on IEA statistics. Different voltage levels are linked by transformation activities. Region-specific electricity losses due to power transmission and voltage transformation are considered in the market and transformation activities. The majority of the 71 power markets are defined by national boundaries. The attributional ecoinvent system model in ev3 with linking to average current suppliers results in electricity markets supplied by all geography-specific power generation technologies and electricity imports, while the consequential system model generates markets only linked to unconstrained suppliers.

Results and discussion

The availability of LCI data for 71 electricity markets in ev3 covering 50 countries reduces the “Rest-of-the-World” electricity supply not covered by country- or region-specific inventories to 17 % for the year 2008. Specific power supply activities for all countries contributing more than 1 % to global electricity production are available. The electricity markets show large variations concerning contributions from specific technologies and energy carriers. Imports can substantially change the national/regional power mix, especially in small markets. Large differences can also be observed between the electricity markets in the attributional and the consequential database calculation. Region-specific total power losses between production on the high voltage level and consumer on the low voltage level are on the order of 2.5–23 %.

Conclusions

Electricity supply mixes (electricity markets) in the ecoinvent database have been updated and substantially extended for v3. Inventories for electricity supply in all globally important economies are available with geography-specific technology and market datasets which will contribute to increasing quality and reducing uncertainties in LCA studies worldwide and to allow more accurate estimation of environmental burdens from global production chains. Future work should focus on improving the details of country-specific data, implementation of more countries into the database, splitting of large countries into smaller regions and on developing a more sophisticated approach specifying country-specific electricity mixes in consequential system models.

     

The integration of long-term marginal electricity supply mixes in the ecoinvent consequential database version 3.4 and examination of modeling choices

Purpose

The long-term marginal electricity supply mixes of 40 countries were generated and integrated into version 3.4 of the ecoinvent consequential database. The total electricity production originating from these countries accounts for 77% of the current global electricity generation. The goal of this article is to provide an overview of the methodology used to calculate the marginal mixes and to evaluate the influence of key parameters and methodological choices on the results.

Methods

The marginal mixes are based on public energy projections from national and international authorities and reflect the accumulated effect of changes in demand for electricity on the installation and operation of new-generation capacities. These newly generated marginal mixes are first examined in terms of their compositions and environmental impacts. They are then compared to several sets of alternative electricity supply mixes calculated using different methodological choices or data sources.

Results and discussion

Renewable energy sources (RES) as well as natural gas power plants show the highest growth rates and usually dominate the marginal mixes. Nevertheless, important variations may exist between the marginal mixes of the different countries in terms of their technological compositions and environmental impacts. The examination of the modeling choices reveals substantial variations between the marginal mixes integrated into the ecoinvent consequential database version 3.4 and marginal mixes generated using alternative modeling options. These different modeling possibilities include changes in the methodology, temporal parameters, and the underlying energy scenarios. Furthermore, in most of the impact categories, average (i.e., attributional) mixes cause higher impact scores than marginal mixes due to higher shares of RES in marginal mixes.

Conclusions

Accurate and consistent data for electricity supply is integrated into a consequential database providing a strong basis for the development of consequential Life Cycle Assessments. The methodology adopted in this version of the database eliminates several shortcomings from the previous approach which led to unrealistic marginal mixes in several countries. The use of energy scenarios allows the evolution of the electricity system to be considered within the definition of the marginal mixes. The modeling choices behind the electricity marginal mix should be adjusted to the goal and scope of individual studies and their influence on the results evaluated.

     

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.

     

Life cycle assessment of the selective catalytic reduction process for power plants

The overall reduction of the environmental impact by the use of selective catalytic reduction (SCR) of nitrogen oxide emissions in power plants was determined by strict application of ISO 14040 and ISO/DIS 14041. Special emphasis was placed on the implementation of the total product life cycle (PLC) of ammonium molybdate as a key input material. The environmental impact was generated by application of the life cycle assessment (LCA) concept of “ecoscarcity” and integrated in the life cycle inventory analysis (LCI) of SCR systems. The LCI was used to generate the life cycle impact assessment (LC1A) by use of different quantitative valuation methods. Under consideration of the overall LCIA results and the environmental protection costs of the SCR variants, the Ecological Effectiveness of the SCR alternatives was determined. The results enable plausible conclusions with regard to the ecological advantages of the use of deNOx catalysts in the SCR used in hard-coal fired power plants.     

Life cycle assessment of an offshore grid interconnecting wind farms and customers across the North Sea

Purpose

This study aims to contribute to an improved understanding of the environmental implications of offshore power grid and wind power development pathways. To achieve this aim, we present two assessments. First, we investigate the impacts of a North Sea power grid enabling enhanced trade and integration of offshore wind power. Second, we assess the benefit of the North Sea grid and wind power through a comparison of scenarios for power generation in affected countries.

Methods

The grid scenario explored in the first assessment is the most ambitious scenario of the Windspeed project and is the result of cost minimization analysis using a transmission-expansion-planning model. We develop a hybrid life cycle inventory for array cables; high voltage, direct current (HVDC) links; and substations. The functional unit is 1 kWh of electricity transmitted. The second assessment compares two different energy scenarios of Windspeed for the North Sea and surrounding countries. Here, we utilize a life cycle inventory for offshore grid components together with an inventory for a catalog of power generation technologies from Ecoinvent and couple these inventories with grid configurations and electricity mixes determined by the optimization procedure in Windspeed.

Results and discussion

Developing, operating, and dismantling the grid cause emissions of 2.5 g CO₂-Eq per kWh electricity transmission or 36 Mt CO₂-Eq in total. HVDC cables are the major cause of environmental damage, causing, for example, half of total climate change effects. The next most important contributors are substations and array cabling used in offshore wind parks. Toxicity and eutrophication effects stem largely from leakages from disposed copper and iron mine tailings and overburden. Results from the comparison of two scenarios demonstrate a substantial environmental benefit from the North Sea grid extension and the associated wind power development compared with an alternative generation of electricity from fossil fuels. Offshore grid and wind power, however, entail an increased use of metals and, hence, a higher metal depletion indicator.

Conclusions

We present the first life cycle assessment of a large offshore power grid, using the results of an energy planning model as input. HVDC links are the major cause of environmental damage. There are differences across impact categories with respect to which components or types of activities that are responsible for damage. The North Sea grid and wind power are environmentally beneficial by an array of criteria if displacing fossil fuels, but cause substantial metal use.     

The ecoinvent database version 3 (part II): analyzing LCA results and comparison to version 2

Purpose

Version 3 of ecoinvent includes more data, new modeling principles, and, for the first time, several system models: the “Allocation, cut-off by classification” (Cut-off) system model, which replicates the modeling principles of version 2, and two newly introduced models called “Allocation at the point of substitution” (APOS) and “Consequential” (Wernet et al. 2016). The aim of this paper is to analyze and explain the differences in life cycle impact assessment (LCIA) results of the v3.1 Cut-off system model in comparison to v2.2 as well as the APOS and Consequential system models.

Methods

In order to do this, functionally equivalent datasets were matched across database versions and LCIA results compared to each other. In addition, the contribution of specific sectors was analyzed. The importance of new and updated data as well as new modeling principles is illustrated through examples.

Results and discussion

Differences were observed in between all database versions using the impact assessment methods Global Warming Potential (GWP100a), ReCiPe Endpoint (H/A), and Ecological Scarcity 2006 (ES’06). The highest differences were found for the comparison of the v3.1 Cut-off and v2.2. At average, LCIA results increased by 6, 8, and 17 % and showed a median dataset deviation of 13, 13, and 21 % for GWP, ReCiPe, and ES’06, respectively. These changes are due to the simultaneous update and addition of new data as well as through the introduction of global coverage and spatially consistent linking of activities throughout the database. As a consequence, supply chains are now globally better represented than in version 2 and lead, e.g., in the electricity sector, to more realistic life cycle inventory (LCI) background data. LCIA results of the Cut-off and APOS models are similar and differ mainly for recycling materials and wastes. In contrast, LCIA results of the Consequential version differ notably from the attributional system models, which is to be expected due to fundamentally different modeling principles. The use of marginal instead of average suppliers in markets, i.e., consumption mixes, is the main driver for result differences.

Conclusions

LCIA results continue to change as LCI databases evolve, which is confirmed by a historical comparison of v1.3 and v2.2. Version 3 features more up-to-date background data as well as global supply chains and should, therefore, be used instead of previous versions. Continuous efforts will be required to decrease the contribution of Rest-of-the-World (RoW) productions and thereby improve the global coverage of supply chains.

     

Establishing Life Cycle Inventories of Chemicals Based on Differing Data Availability (9 pp)

Goal, Scope and Background In contrast to inventory data of energy and transport processes, public inventory data of chemicals are rather scarce. Chemicals are important to consider in LCA, because they are used in the production of many, if not all, products. Moreover, they may cause considerable environmental impacts. For these reasons, it was one goal of the new ecoinvent database to provide LCI data on chemicals. In this paper, the methods and procedures used for establishing LCIs of chemicals in ecoinvent are presented.Methods Three different approaches are suggested for situations of differing data availability. First, in the case of good data availability, the general quality guidelines of ecoinvent can be followed. Second, a procedure is proposed for the translation of aggregated inventory data (cumulative LCI results) from industry into the ecoinvent format. This approach was used, if adequate unit process data was not available. Third, a procedure is put forward for estimating inventory data using stoichiometric equations from technical literature as a main information source. This latter method was used if no other information was available. The application of each of the three procedures is illustrated with the help of a case study.Results and Conclusion When sufficient information is available to follow the general guidelines of ecoinvent, the resulting dataset is characterized by a high degree of detail, and it is thus of high quality. For chemicals, however, the application of the standard procedure is possible in only a few cases. When using industrial data, the main drawback is the fact that those data are often available only as aggregated data, thus being out of tune with the quality guidelines of ecoinvent and its main aim, the harmonization of LCI data. As a third approach, the use of the stoichiometric reaction equation is used for the compilation of LCI datasets of chemicals. This approach represents an alternative to neglecting chemicals completely, but it contains a high risk to not consider important aspects of the life cycle of the respective substance.Outlook Further work in the area of chemicals should focus on an improvement of datasets, so far established by either of the two estimation procedures (APME method; estimation based on technical literature) described. Besides the improvement of already established inventories, the compilation of further harmonized inventories of specific types of chemicals (e.g. solvents) or of chemicals for new industrial sectors (e.g. electronics industry) are in discussion.     

Life cycle assessment of the Peruvian industrial anchoveta fleet: boundary setting in life cycle inventory analyses of complex and plural means of production

Purpose

This work has two major objectives: (1) to perform an attributional life cycle assessment (LCA) of a complex mean of production, the main Peruvian fishery targeting anchoveta (anchovy) and (2) to assess common assumptions regarding the exclusion of items from the life cycle inventory (LCI).

Methods

Data were compiled for 136 vessels of the 661 units in the fleet. The functional unit was 1 t of fresh fish delivered by a steel vessel. Our approach consisted of four steps: (1) a stratified sampling scheme based on a typology of the fleet, (2) a large and very detailed inventory on small representative samples with very limited exclusion based on conventional LCI approaches, (3) an impact assessment on this detailed LCI, followed by a boundary-refining process consisting of retention of items that contributed to the first 95 % of total impacts and (4) increasing the initial sample with a limited number of items, according to the results of (3). The life cycle impact assessment (LCIA) method mostly used was ReCiPe v1.07 associated to the ecoinvent database.

Results and discussion

Some items that are usually ignored in an LCI’s means of production have a significant impact. The use phase is the most important in terms of impacts (66 %), and within that phase, fuel consumption is the leading inventory item contributing to impacts (99 %). Provision of metals (with special attention to electric wiring which is often overlooked) during construction and maintenance, and of nylon for fishing nets, follows. The anchoveta fishery is shown to display the lowest fuel use intensity worldwide.

Conclusions

Boundary setting is crucial to avoid underestimation of environmental impacts of complex means of production. The construction, maintenance and EOL stages of the life cycle of fishing vessels have here a substantial environmental impact. Recommendations can be made to decrease the environmental impact of the fleet.     

The Glasgow consensus on the delineation between pesticide emission inventory and impact assessment for LCA

Purpose

Pesticides are applied to agricultural fields to optimise crop yield and their global use is substantial. Their consideration in life cycle assessment (LCA) is affected by important inconsistencies between the emission inventory and impact assessment phases of LCA. A clear definition of the delineation between the product system model (life cycle inventory—LCI, technosphere) and the natural environment (life cycle impact assessment—LCIA, ecosphere) is missing and could be established via consensus building.

Methods

A workshop held in 2013 in Glasgow, UK, had the goal of establishing consensus and creating clear guidelines in the following topics: (1) boundary between emission inventory and impact characterisation model, (2) spatial dimensions and the time periods assumed for the application of substances to open agricultural fields or in greenhouses and (3) emissions to the natural environment and their potential impacts. More than 30 specialists in agrifood LCI, LCIA, risk assessment and ecotoxicology, representing industry, government and academia from 15 countries and four continents, met to discuss and reach consensus. The resulting guidelines target LCA practitioners, data (base) and characterisation method developers, and decision makers.

Results and discussion

The focus was on defining a clear interface between LCI and LCIA, capable of supporting any goal and scope requirements while avoiding double counting or exclusion of important emission flows/impacts. Consensus was reached accordingly on distinct sets of recommendations for LCI and LCIA, respectively, recommending, for example, that buffer zones should be considered as part of the crop production system and the change in yield be considered. While the spatial dimensions of the field were not fixed, the temporal boundary between dynamic LCI fate modelling and steady-state LCIA fate modelling needs to be defined.

Conclusions and recommendations

For pesticide application, the inventory should report pesticide identification, crop, mass applied per active ingredient, application method or formulation type, presence of buffer zones, location/country, application time before harvest and crop growth stage during application, adherence with Good Agricultural Practice, and whether the field is considered part of the technosphere or the ecosphere. Additionally, emission fractions to environmental media on-field and off-field should be reported. For LCIA, the directly concerned impact categories and a list of relevant fate and exposure processes were identified. Next steps were identified: (1) establishing default emission fractions to environmental media for integration into LCI databases and (2) interaction among impact model developers to extend current methods with new elements/processes mentioned in the recommendations.

     

Life Cycle Inventories for the Nuclear and Natural Gas Energy Systems,and Examples of Uncertainty Analysis (14 pp)

Goal, Scope and Background The energy systems included in the ecoinvent database v1.1 describe the situation around year 2000 of Swiss and Western European power plants and boilers with the associated energy chains. The addressed nuclear systems concern Light Water Reactors (LWR) with mix of open and closed fuel cycles. The system model ‘Natural Gas’ describes production, distribution, and combustion of natural gas. Methods Comprehensive life cycle inventories of the energy systems were established and cumulative results calculated within the ecoinvent framework. Swiss conditions for the nuclear cycle were extrapolated to major nuclear countries. Long-term radon emissions from uranium mill tailings have been estimated with a simplified model. Average natural gas power plants were analysed for different countries considering specific import/export of the gas, with seven production regions separately assessed. Uncertainties have been estimated quantitatively. Results and Discussion Different radioactive emission species and wastes are produced from different steps of the nuclear cycle. Emissions of greenhouse gases from the nuclear cycle are mostly from the upstream chain, and the total is small and decreasing with increasing share of centrifuge enrichment. The results for natural gas show the importance of transport and low pressure distribution network for the methane emissions, whereas energy is mostly invested for production and long-distance pipeline transportation. Because of significant differences in power plant efficiencies and gas supply, country specific averages differ greatly. Conclusion The inventory describes average worldwide supply of nuclear fuel and average nuclear reactors in Western Europe. Although the model for nuclear waste management was extrapolated from Swiss conditions, the ranges obtained for cumulative results can represent the average in Europe. Emissions per kWh electricity are distributed very differently over the natural gas chain for different species. Modern combined cycle plants show better performance for several burdens like cumulative greenhouse gas emissions compared to average plants. Recommendation and Perspective Comparison of country-specific LWRs or LWR types on the basis of these results is not recommended. Specific issues on different strategies for the nuclear fuel cycle or location-specific characteristics would require extension of analysis. Results of the gas chain should not be directly applied to areas other than those modelled because emission factors and energy requirements may differ significantly. A future update of inventory data should reconsider production and transport from Russia, as it is a major producer and exporter to Europe. The calculated ranges of uncertainty factors in ecoinvent provide useful information but they are more indications of uncertainties rather than strict 95% intervals, and should therefore be applied carefully.     

Life Cycle Inventory Information of the United States Electricity System (11/17 pp)

Goal and Scope This study estimates the life cycle inventory (LCI) of the electricity system in the United States, including the 10 NERC (North American Electric Reliability Council) regions, Alaska, Hawaii, off-grid non-utility plants and the US average figures. The greenhouse gas emissions associated with the United States electricity system are also estimated. Methods The fuel mix of the electricity system based on year 2000 data is used. The environmental burdens associated with raw material extraction, petroleum oil production and transportation for petroleum oil and natural gas to power plants are adopted from the DEAMTM LCA database. Coal transportation from a mining site to a power plant is specified with the data from the Energy Information Administration (EIA), which includes the mode of transportation as well as the distance traveled. The gate-to-gate environmental burdens associated with generating electricity from a fossil-fired power plant are obtained from the DEAMTM LCA database and the eGRID model developed by the United States Environmental Protection Agency. For nuclear power plants and hydroelectric power plants, the data from the DEAMTM LCA database are used.Results and Discussion Selected environmental profiles of the US electricity system are presented in the paper version, while the on-line version presents the whole LCI data. The overall US electricity system in the year 2000 released about 2,654 Tg CO2 eq. of greenhouse gas emissions based on 100-year global warming potentials with 193 g CO2 eq. MJe–1 as an weighted average emission rate per one MJ electricity generated. Most greenhouse gases are released during combusting fossil fuels, accounting for 78–95% of the total. The greenhouse gas emissions released from coal-fired power plants account for 81% of the total greenhouse gas emissions associated with electricity generation, and natural gas-fired power plants contribute about 16% of the total. The most significant regions for the total greenhouse gas emissions are the SERC (Southeastern Electric Reliability Council) and ECAR (East Central Area Reliability Coordination Agreement) regions, which account for 22% and 21% of the total, respectively. A sensitivity analysis on the generation and consumption based calculations indicates that the environmental profiles of electricity based on consumption are more uncertain than those based on generation unless exchange data from the same year are available because the exchange rates (region to region import and export of electricity) vary significantly from year to year.Conclusions and Outlook Those who are interested in the LCI data of the US electricity system can refer to the on-line version. When the inventory data presented in the on-line version are used in a life cycle assessment study, the distribution and transmission losses should be taken into account, which is about 9.5% of the net generation [1]. The comprehensive technical information presented in this study can be used in estimating the environmental burdens when new information on the regional fuel mix or the upstream processes is available. The exchange rates presented in this study also offer useful information in consequential LCI studies.     

Variability in greenhouse gas footprints of the global wind farm fleet

While technological characteristics largely determine the greenhouse gas (GHG) emissions during the construction of a wind farm and meteorological circumstances the actual electricity production, a thorough analysis to quantify the GHG footprint variability (in g CO₂eq/kWh electricity produced) between wind farms is still lacking at the global scale. Here, we quantified the GHG footprint of 26,821 wind farms located across the globe, combining turbine-specific technological parameters, life-cycle inventory data, and location- and temporal-specific meteorological information. These wind farms represent 79% of the 651 global wind (GW) capacity installed in 2019. Our results indicate a median GHG footprint for global wind electricity of 10 g CO₂eq/kWh, ranging from 4 to 56 g CO₂eq/kWh (2.5th and 97.5th percentiles). Differences in the GHG footprint of wind farms are mainly explained by spatial variability in wind speed, followed by whether the wind farm is located onshore or offshore, the turbine diameter, and the number of turbines in a wind farm. We also provided a metamodel based on these four predictors for users to be able to easily obtain a first indication of GHG footprints of new wind farms considered. Our results can be used to compare the GHG footprint of wind farms to one another and to other sources of electricity in a location-specific manner.     

Linking land use inventories to biodiversity impact assessment methods

The International Journal of Life Cycle Assessment - There is generally a mismatch in the land use classification of life cycle inventory (LCI) databases and life cycle impact assessment (LCIA)...     

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.

     

Impact of Power Generation Mix on Life Cycle Assessment and Carbon Footprint Greenhouse Gas Results

The mix of electricity consumed in any stage in the life cycle of a product, process, or industrial sector has a significant effect on the associated inventory of emissions and environmental impacts because of large differences in the power generation method used. Fossil‐fuel‐fired or nuclear‐centralized steam generators; large‐scale and small‐scale hydroelectric power; and renewable options, such as geothermal, wind, and solar power, each have a unique set of issues that can change the results of a life cycle assessment. This article shows greenhouse gas emissions estimates for electricity purchase for different scenarios using U.S. average electricity mix, state mixes, state mixes including imports, and a sector‐specific mix to show how different these results can be. We find that greenhouse gases for certain sectors and scenarios can change by more than 100%. Knowing this, practitioners should exercise caution or at least account for the uncertainty associated with mix choice.     

Life cycle inventory for electricity generation in China

Background, Goal and Scope The objective of this study was to produce detailed a life cycle inventory (LCI) for the provision of 1 kWh of electricity to consumers in China in 2002 in order to identify areas of improvement in the industry. The system boundaries were processes in power stations, and the construction and operation of infrastructure were not included. The scope of this study was the consumption of fossil fuels and the emissions of air pollutants, water pollutants and solid wastes, which are listed as follows: (1) consumption of fossil fuels, including general fuels, such as raw coal, crude oil and natural gas, and the uranium used for nuclear power; (2) emissions of air pollutants from thermal power, hydropower and nuclear power plants; (3) emissions of water pollutants, including general water waste from fuel electric plants and radioactive waste fluid from nuclear power plants; (4) emissions of solid wastes, including fly ash and slag from thermal power plants and radioactive solid wastes from nuclear power plants. Methods Data were collected regarding the amount of fuel, properties of fuel and the technical parameters of the power plants. The emissions of CO₂, SO₂, NO_x, CH₄, CO, non-methane volatile organic compound (NMVOC), dust and heavy metals (As, Cd, Cr, Hg, Ni, Pb, V, Zn) from thermal power plants as well as fuel production and distribution were estimated. The emissions of CO₂ and CH₄ from hydropower plants and radioactive emissions from nuclear power plants were also investigated. Finally, the life cycle inventory for China’s electricity industry was calculated and analyzed. Results Related to 1 kWh of usable electricity in China in 2002, the consumption of coal, oil, gas and enriched uranium were 4.57E-01, 8.88E-03, 7.95E-03 and 9.03E-08 kg; the emissions of CO₂, SO₂, NO_x, CO, CH₄, NMVOC, dust, As, Cd, Cr, Hg, Ni, Pb, V, and Zn were 8.77E-01, 8.04E-03, 5.23E-03, 1.25E-03, 2.65E-03, 3.95E-04, 1.63E-02, 1.62E-06, 1.03E-08, 1.37E-07, 7.11E-08, 2.03E-07, 1.42E-06, 2.33E-06, and 1.94E-06 kg; the emissions of waste water, COD, coal fly ash, and slag were 1.31, 6.02E-05, 8.34E-02, and 1.87E-02 kg; and the emissions of inactive gas, halogen and gasoloid, tritium, non-tritium, and radioactive solid waste were 3.74E+01 Bq, 1.61E-01 Bq, 4.22E+01 Bq, 4.06E-02 Bq, and 2.68E-10 m³ respectively. Conclusions The comparison result between the LCI data of China’s electricity industry and that of Japan showed that most emission intensities of China’s electricity industry were higher than that of Japan except for NMVOC. Compared with emission intensities of the electricity industry in Japan, the emission intensities of CO₂ and Ni in China were about double; the emission intensities of NO_x, Cd, CO, Cr, Hg and SO₂ in China were more than 10 times that of Japan; and the emission intensities of CH₄, V, Pb, Zn, As and dust were more than 20 times. The reasons for such disparities were also analyzed. Recommendations and Perspectives To get better LCI for the electricity industry in China, it is important to estimate the life cycle emissions during fuel production and transportation for China. Another future improvement could be the development of LCIs for construction and operation of infrastructure such as factory buildings and dams. It would also be important to add the information about land use for hydropower.     

Waste Treatment and Assessment of Long-Term Emissions (8pp)

Goal, Scope and Background The disposal phase of a product’s life cycle in LCA is often neglected or based on coarse indicators like ‘kilogram waste’. The goal of report No. 13 of the ecoinvent project (Doka 2003) is to create detailed Life Cycle Inventories of waste disposal processes. The purpose of this paper is to give an overview of the models behind the waste disposal inventories in ecoinvent, to present exemplary results and to discuss the assessment of long-term emissions. This paper does not present a particular LCA study. Inventories are compiled for many different materials and various disposal technologies. Considered disposal technologies are municipal incineration and different landfill types, including sanitary landfills, hazardous waste incineration, waste deposits in deep salt mines, surface spreading of sludges, municipal wastewater treatment, and building dismantling. The inventoried technologies are largely based on Swiss plants. Inventories can be used for assessment of the disposal of common, generic waste materials like paper, plastics, packaging etc. Inventories are also used within the ecoinvent database itself to inventory the disposal of specific wastes generated during the production phase. Inventories relate as far as possible to the specific chemical composition of the waste material (waste-specific burdens). Certain expenditures are not related to the waste composition and are inventoried with average values (process-specific burdens). Methods The disposal models are based on previous work, partly used in earlier versions of ecoinvent/ETH LCI data. Important improvements were the extension of the number of considered chemical elements to 41 throughout all disposal models and new landfill models based on field data. New inventories are compiled for waste deposits in deep salt mines and building material disposal. Along with the ecoinvent data and the reports, also Excel-based software tools were created, which allow ecoinvent members to calculate waste disposal inventories from arbitrary waste compositions. The modelling of long-term emissions from landfills is a crucial part in any waste disposal process. In ecoinvent long-term emissions are defined as emissions occurring 100 years after present. They are reported in separate emission categories. The landfill inventories include long-term emissions with a time horizon of 60’000 years after present. Results and Discussion As in earlier studies, the landfills prove to be generally relevant disposal processes, as also incineration and wastewater treatment processes produce landfilled wastes. Heavy metals tend to concentrate in landfills and are washed out to a varying degree over time. Long-term emissions usually represent an important burden from landfills. Comparisons between burdens from production of materials and the burdens from their disposal show that disposal has a certain relevance. Conclusion The disposal phase should by default be included in LCA studies. The use of a material not only necessitates its production, but also requires its disposal. The created inventories and user tools facilitate heeding the disposal phase with a similar level of detail as production processes. The risk of LCA-based decisions shifting burdens from the production or use phase to the disposal phase because of data gaps can therefore be diminished. Recommendation and Perspective Future improvements should include the modelling of metal ore refining waste (tailings) which is currently neglected in ecoinvent, but is likely to be relevant for metals production. The disposal technologies considered here are those of developed Western countries. Disposal in other parts of the World can differ distinctly, for logistic, climatic and economic reasons. The cross-examination of landfill models to LCIA soil fate models could be advantageous. Currently only chemical elements, like copper, zinc, nitrogen etc. are heeded by the disposal models. A possible extension could be the modelling of the behaviour of chemical compounds, like dioxins or other hydrocarbons.