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.

     

Life cycle greenhouse gas emissions of electricity generation in the province of Ontario, Canada

Purpose

This paper assesses facility-specific life cycle greenhouse gas (GHG) emission intensities for electricity-generating facilities in the province of Ontario in 2008. It offers policy makers, researchers and other stakeholders of the Ontario electricity system with data regarding some of the environmental burdens from multiple generation technology currently deployed in the province.

Methods

Methods involved extraction of data and analysis from several publically accessible datasets, as well as from the LCA literature. GHG emissions data for operation of power plants came from the Government of Canada GHG registry and the Ontario Power Generation (OPG) Sustainable Development reports. Facility-specific generation data came from the Independent Electricity System Operator in Ontario and the OPG.

Results

Full life cycle GHG intensity (tonnes of CO₂ equivalent per gigawatt hour) estimates are provided for 4 coal facilities, 27 natural gas facilities, 1 oil/natural gas facility, 3 nuclear facilities, 7 run-of-river hydro facilities and 37 reservoir hydro facilities, and 7 wind facilities. Average (output weighted) life cycle GHG intensities are calculated for each fuel type in Ontario, and the life cycle GHG intensity for the Ontario grid as a whole (in 2008) is estimated to be 201 t CO₂e/GWh.

Conclusions

The results reflect only the global warming impact of electricity generation, and they are meant to inform a broader discussion which includes other environmental, social, cultural, institutional and economic factors. This full range of factors should be included in decisions regarding energy policy for the Province of Ontario, and in future work on the Ontario electricity system.     

Life Cycle Assessment for Emerging Technologies: Case Studies for Photovoltaic and Wind Power (11 pp)

Goal, Scope and Background This paper describes the modelling of two emerging electricity systems based on renewable energy: photovoltaic (PV) and wind power. The paper shows the approach used in the ecoinvent database for multi-output processes.Methods Twelve different, grid-connected photovoltaic systems were studied for the situation in Switzerland. They are manufactured as panels or laminates, from mono- or polycrystalline silicon, installed on facades, slanted or flat roofs, and have a 3kWp capacity. The process data include quartz reduction, silicon purification, wafer, panel and laminate production, supporting structure and dismantling. The assumed operational lifetime is 30 years. Country-specific electricity mixes have been considered in the LCI in order to reflect the present situation for individual production stages. The assessment of wind power includes four different wind turbines with power rates between 30 kW and 800 kW operating in Switzerland and two wind turbines assumed representative for European conditions – 800 kW onshore and 2 MW offshore. The inventory takes into account the construction of the plants including the connection to the electric grid and the actual wind conditions at each site in Switzerland. Average European capacity factors have been assumed for the European plants. Eventually necessary backup electricity systems are not included in the analysis.Results and Discussion The life cycle inventory analysis for photovoltaic power shows that each production stage may be important for specific elementary flows. A life cycle impact assessment (LCIA) shows that there are important environmental impacts not directly related to the energy use (e.g. process emissions of NOx from wafer etching). The assumption for the used supply energy mixes is important for the overall LCIA results of different production stages. The allocation of the inventory for silicon purification to different products is discussed here to illustrate how allocation has been implemented in ecoinvent. Material consumption for the main parts of the wind turbines gives the dominant contributions to the cumulative results for electricity production. The complex installation of offshore turbines, with high requirements of concrete for the foundation and the assumption of a shorter lifetime compared to onshore foundations, compensate the advantage of increased offshore wind speeds.Conclusion The life cycle inventories for photovoltaic power plants are representative for newly constructed plants and for the average photovoltaic mix in Switzerland in the year 2000. A scenario for a future technology helps to assess the relative influence of technology improvements for some processes in the near future (2005-2010). The differences for environmental burdens of wind power basically depend upon the capacity factor of the plants, the lifetime of the infrastructure, and the rated power. The higher these factors, the more reduced the environmental burdens are. Thus, both systems are quite dependent on meteorological conditions and the materials used for the infrastructure.Recommendation and Perspective Many production processes for photovoltaic power are still under development. Future updates of the LCI should verify the energy uses and emissions with available data from industrial processes in operation. For the modelling of a specific power plant or power plant mixes outside of Switzerland, one has to consider the annual yield (kWh/kWp) and if possible also the size of the plant. Considering the steady growth of the size of wind turbines in Europe, the development of new designs, and the exploitation of offshore location with deeper waters than analysed in this study, the inventory for wind power plants may need to be updated in the future.     

Comparative LCAs for Curbside Recycling Versus Either Landfilling or Incineration with Energy Recovery (12 pp)

Background This article describes two projects conducted recently by Sound Resource Management (SRMG) – one for the San Luis Obispo County Integrated Waste Management Authority (SLO IWMA) and the other for the Washington State Department of Ecology (WA Ecology). For both projects we used life cycle assessment (LCA) techniques to evaluate the environmental burdens associated with collection and management of municipal solid waste. Both projects compared environmental burdens from curbside collection for recycling, processing, and market shipment of recyclable materials picked up from households and/or businesses against environmental burdens from curbside collection and disposal of mixed solid waste. Method logy. The SLO IWMA project compared curbside recycling for households and businesses against curbside collection of mixed refuse for deposition in a landfill where landfill gas is collected and used for energy generation. The WA Ecology project compared residential curbside recycling in three regions of Washington State against the collection and deposition of those same materials in landfills where landfill gas is collected and flared. In the fourth Washington region (the urban east encompassing Spokane) the WA Ecology project compared curbside recycling against collection and deposition in a wasteto- energy (WTE) combustion facility used to generate electricity for sale on the regional energy grid. During the time period covered by the SLO study, households and businesses used either one or two containers, depending on the collection company, to separate and set out materials for recycling in San Luis Obispo County. During the time of the WA study households used either two or three containers for the residential curbside recycling programs surveyed for that study. Typically participants in collection programs requiring separation of materials into more than one container used one of the containers to separate at least glass bottles and jars from other recyclable materials. For the WA Ecology project SRMG used life cycle inventory (LCI) techniques to estimate atmospheric emissions of ten pollutants, waterborne emissions of seventeen pollutants, and emissions of industrial solid waste, as well as total energy consumption, associated with curbside recycling and disposal methods for managing municipal solid waste. Emissions estimates came from the Decision Support Tool (DST) developed for assessing the cost and environmental burdens of integrated solid waste management strategies by North Carolina State University (NCSU) in conjunction with Research Triangle Institute (RTI) and the US Environmental Protection Agency (US EPA)1. RTI used the DST to estimate environmental emissions during the life cycle of products. RTI provided those estimates to SRMG for analysis in the WA Ecology project2. For the SLO IWMA project SRMG also used LCI techniques and data from the Municipal Solid Waste Life- Cycle Database (Database), prepared by RTI with the support of US EPA during DST model development, to estimate environmental emissions from solid waste management practices3. Once we developed the LCI data for each project, SRMG then prepared a life cycle environmental impacts assessment of the environmental burdens associated with these emissions using the Environmental Problems approach discussed in the methodology section of this article. Finally, for the WA study we also developed estimates of the economic costs of certain environmental impacts in order to assess whether recycling was cost effective from a societal point of view. Conclusions Recycling of newspaper, cardboard, mixed paper, glass bottles and jars, aluminum cans, tin-plated steel cans, plastic bottles, and other conventionally recoverable materials found in household and business municipal solid wastes consumes less energy and imposes lower environmental burdens than disposal of solid waste materials via landfilling or incineration, even after accounting for energy that may be recovered from waste materials at either type disposal facility. This result holds for a variety of environmental impacts, including global warming, acidification, eutrophication, disability adjusted life year (DALY) losses from emission of criteria air pollutants, human toxicity and ecological toxicity. The basic reason for this conclusion is that energy conservation and pollution prevention engendered by using recycled rather than virgin materials as feedstocks for manufacturing new products tends to be an order of magnitude greater than the additional energy and environmental burdens imposed by curbside collection trucks, recycled material processing facilities, and transportation of processed recyclables to end-use markets. Furthermore, the energy grid offsets and associated reductions in environmental burdens yielded by generation of energy from landfill gas or from waste combustion are substantially smaller then the upstream energy and pollution offsets attained by manufacturing products with processed recyclables, even after accounting for energy usage and pollutant emissions during collection, processing and transportation to end-use markets for recycled materials. The analysis that leads to this conclusion included a direct comparison of the collection for recycling versus collection for disposal of the same quantity and composition of materials handled through existing curbside recycling programs in Washington State. This comparison provides a better approximation to marginal energy usage and environmental burdens of recycling versus disposal for recyclable materials in solid waste than does a comparison of the energy and environmental impacts of recycling versus management methods for handling typical mixed refuse, where that refuse includes organics and non-recyclables in addition to whatever recyclable materials may remain in the garbage. Finally, the analysis also suggests that, under reasonable assumptions regarding the economic cost of impacts from pollutant emissions, the societal benefits of recycling outweigh its costs.     

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.     

Differential Convergence of Life-Cycle Inventories toward Upstream Production Layers

We present an input-output analysis of the life-cycle labor, land, and greenhouse gas (GHG) requirements of alternative options for three case studies: investing money in a new vehicle versus in repairs of an existing vehicle (labor), passenger transport modes for a trip between Sydney and Melbourne (land use), and renewable electricity generation (GHG emissions). These case studies were chosen to demonstrate the possibility of rank crossovers in life-cycle inventory (LCI) results as system boundaries are expanded and upstream production inputs are taken into account. They demonstrate that differential convergence can cause crossovers in the ranking of inventories for alternative functional units occurring at second-and higher-order upstream production layers. These production layers are often excluded in conventional process-type life-cycle assessment (LCA) by the delineation of a finite system boundary, leading to a systematic truncation error within the LCI. The exclusion of higher-order upstream inputs can be responsible for ranking crossovers going unnoticed. In this case, an incomplete conventional process-type LCA of two alternative options can result in preferences and recommendations to decision makers that are different from preferences and recommendations concluded from a complete hybrid input-output-based assessment. Therefore, the need to avoid misleading effects on the ranking of alternative functional units due to differential convergence supports the practice of hybrid input-output-based LCA techniques.     

A methodology for separating uncertainty and variability in the life cycle greenhouse gas emissions of coal-fueled power generation in the USA

Purpose

Results of life cycle assessments (LCAs) of power generation technologies are increasingly reported in terms of typical values and possible ranges. Extents of these ranges result from both variability and uncertainty. Uncertainty may be reduced via additional research. However, variability is a characteristic of supply chains as they exist; as such, it cannot be reduced without modifying existing systems. The goal of this study is to separately quantify uncertainty and variability in LCA.

Methods

In this paper, we present a novel method for differentiating uncertainty from variability in life cycle assessments of coal-fueled power generation, with a specific focus on greenhouse gas emissions. Individual coal supply chains were analyzed for 364 US coal power plants. Uncertainty in CO₂ and CH₄ emissions throughout these supply chains was quantified via Monte Carlo simulation. The method may be used to identify key factors that drive the range of life cycle emissions as well as the limits of precision of an LCA.

Results and discussion

Using this method, we statistically characterized the carbon footprint of coal power in the USA in 2009. Our method reveals that the average carbon footprint of coal power (100 year time horizon) ranges from 0.97 to 1.69 kg CO₂eq/kWh of generated electricity (95 % confidence interval), primarily due to variability in plant efficiency. Uncertainty in the carbon footprints of individual plants spans a factor of 1.04 for the least uncertain plant footprint to a factor of 1.2 for the most uncertain plant footprint (95 % uncertainty intervals). The uncertainty in the total carbon footprint of all US coal power plants spans a factor of 1.05.

Conclusions

We have developed and successfully implemented a framework for separating uncertainty and variability in the carbon footprint of coal-fired power plants. Reduction of uncertainty will not substantially reduce the range of predicted emissions. The range can only be reduced via substantial changes to the US coal power infrastructure. The finding that variability is larger than uncertainty can obviously not be generalized to other product systems and impact categories. Our framework can, however, be used to assess the relative influence of uncertainty and variability for a whole range of product systems and environmental impacts.     

Policy Implications of Allocation Methods in the Life Cycle Analysis of Integrated Corn and Corn Stover Ethanol Production

A biorefinery may produce multiple fuels from more than one feedstock. The ability of these fuels to qualify as one of the four types of biofuels under the US Renewable Fuel Standard and to achieve a low carbon intensity score under California’s Low Carbon Fuel Standard can be strongly influenced by the approach taken to their life cycle analysis (LCA). For example, in facilities that may co-produce corn grain and corn stover ethanol, the ethanol production processes can share the combined heat and power (CHP) that is produced from the lignin and liquid residues from stover ethanol production. We examine different LCA approaches to corn grain and stover ethanol production considering different approaches to CHP treatment. In the baseline scenario, CHP meets the energy demands of stover ethanol production first, with additional heat and electricity generated sent to grain ethanol production. The resulting greenhouse gas (GHG) emissions for grain and stover ethanol are 57 and 25 g-CO₂eq/MJ, respectively, corresponding to a 40 and 74 % reduction compared to the GHG emissions of gasoline. We illustrate that emissions depend on allocation of burdens of CHP production and corn farming, along with the facility capacities. Co-product handling techniques can strongly influence LCA results and should therefore be transparently documented.     

Environmental impacts of future bioenergy pathways: the case of electricity from wheat straw bales and pellets

This study presents the life cycle assessment of electricity generation from straw bales and pellets. Straw is the most abundant biomass residue in Europe and its use for energy purposes is promoted on the premise of high greenhouse gas savings. This assumption has delayed the study of sustainability of straw‐fired systems on a broader sense and the literature on the topic is almost absent. This study uses data from specific literature and emissions inventories to model a number of straw pathways. The plant modeled is a medium‐scale straw‐fired power plant of 50 MWth capacity. The results show that electricity from straw‐fired power plants can indeed realize high greenhouse gas savings compared both with existing coal plants and with the European electricity mix. The savings are in the range 70–94%. The influence of the geographical origin of straw is analyzed by using datasets for the cultivation of wheat in five different European countries. The highest emissions are recorded for the case of straw from Spain due to the small yields, whereas cultivation processes in United Kingdom and the Netherlands show high environmental impacts due to the high level of fertilization. Other environmental impacts are evaluated, such as acidification potential, eutrophication, particulate matter emissions, and photochemical ozone formation. The bioenergy system scores worse than the current European electricity mix for all the categories. However, it is important to notice that in Spain and United Kingdom the straw system shows lower impacts compared with the local average coal electricity. Finally, the study investigates the ‘break‐even’ distance at which the higher emissions from the pellets production are paid off by the saved emissions in their transport compared with the bales. The results show that no reasonable break‐even distance exists for road transport, whereas advantages for pellets are evident in any configuration for transoceanic transport.     

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.     

Consequences of Future Data Center Deployment in Canada on Electricity Generation and Environmental Impacts: A 2015–2030 Prospective Study

The environmental impacts of data centers that provide information and communication technologies (ICTs) services are strongly related to electricity generation. With the increasing use of ICT, many data centers are expected to be built, causing more absolute impacts on the environment. Given that electricity distribution networks are very complex and dynamic systems, an environmental evaluation of future data centers is uncertain. This study proposes a new approach to investigate the consequences of future data center deployment in Canada and optimize this deployment based on the Energy 2020 technoeconomic model in combination with life cycle assessment methodology. The method determines specific electricity sources that will power the future Canadian data centers and computes related environmental impacts based on several indicators. In case‐study scenarios, the largest deployment of data centers leads to the smallest impact per megawatt of data centers for all of the environmental indicators. It is found that an increase in power demand by data centers would lead to a reduction in electricity exports to the United States, driving the United States to generate more electricity to meet its energy demand. Given that electricity generation in the United States is more polluting than in Canada, the deployment of data centers in Canada is indirectly linked to an increase in overall environmental impacts. However, though an optimal solution should be found to mitigate global greenhouse gas emissions, it is not clear whether the environmental burden related to U.S. electricity generation should be attributed to the Canadian data centers.     

Provision of LCI data in the European aluminium industry Methods and examples

Background, aim, and scope

The development of robust and up-to-date generic life cycle inventory data for materials is absolutely crucial for the LCA community since many LCA studies rely on these generic data about materials. LCA databases and software usually include within their package such generic LCI datasets. However, in many cases, the quality of these data is poor while the methodology and the models used for their development are rarely accessible or transparent. This paper presents the development of robust European LCI datasets for the production of primary and recycled aluminium ingots and for the transformation of aluminium ingot into semi-finished products, i.e. sheet, foil and extrusion.

Materials and methods

The environmental data have been collected through an extensive environmental survey, organised among the European aluminium industry, focusing on the year 2005 and covering EU27 countries as well as EFTA countries (Norway, Iceland and Switzerland). From this survey, European averages, i.e. foreground data, have been calculated for the direct inputs and outputs of the various aluminium processes. Using the GaBi software, the foreground data have been combined within LCI models integrating background LCI data on energy supply systems, ancillary processes and materials. For the primary aluminium production (smelters), a specific model for the electricity production has been developed. The methodology for the data consolidation and for the development of the various models is explained as well as the main differences between the new modelling approach and LCI models used in the past. An independent expert has critically reviewed the entire LCI project including data collection, models development, calculation of LCI data and associated environmental indicators.

Results

As confirmed by the critical review, the new LCI datasets for aluminium ingot production and transformation into semi-finished products have been developed though a robust methodology in full accordance with ISO 14040 and 14044. Most significant environmental data and LCI results are reported in this paper with an emphasis on energy use and the major emissions to air. The full environmental report, including the critical review report and the calculation of environmental indicators for a pre-set of impact categories, is available on the website of the European Aluminium Association (EAA 2008). Whenever possible, the updated European averages and the new LCI data are compared with previous results developed from two past European surveys covering respectively the years 2002 and 1998. For the aluminium processes related to primary production, European averages are also benchmarked against global averages calculated from two worldwide surveys covering the years 2000 and 2005.

Discussion

While some data evolutions are directly attributed to the variation of foreground data, e.g. raw materials consumption or energy use within the aluminium processes, modifications related to the system boundaries, the background data and the modelling hypotheses can also influence significantly the LCI results. For primary aluminium production, the evolution of the foreground data is dominated by the strong decrease of PFC (perfluorocarbon) emissions (about 70% since 1998). In addition, the electricity structure calculated from the refined electricity model shows significant differences compared to previous models. In the 2005 electricity model, the hydropower share reaches 58% while coal contributes to 15% only of the electricity production. In 1998, the respective share of coal-based and hydro-electricity were respectively calculated to 25% and 52%. As a result, the electricity background LCI data are then significantly affected and influence also positively the environmental profile of primary aluminium in Europe. For the semi-production processes, the reduction of process scrap production, especially for extrusion and foil, demonstrates the increase of process efficiency from 1998. In parallel, a significant reduction of energy use is observed between 1998 and 2005. However, this positive trend is not fully reflected within LCI data due to the significant contribution of the background electricity data. The choice of the electricity model plays also a critical role for these transformation processes since electricity production contributes to about 2/3 of the consumption of the non-renewable energy and to about the same level of the air emissions. In such a case, the move from the UCPTE electricity model used in the past towards the EU25 electricity model used for the development of the updated LCI data has a detrimental effect on the environmental profile of the three LCI datasets respectively related to sheet, foil and extrusion. In addition to energy and process scrap reduction, the reduction of the VOC (volatile organic compounds) emission is also a major trend in foil production. Finally, for old aluminium scrap recycling, the new LCI data show a dramatic improvement regarding energy efficiency, reinforcing the environmental soundness of promoting and supporting aluminium recycling within the aluminium product life cycles.

Conclusions

This paper shows the development of generic LCI data about aluminium production and transformation processes which are based on robust data, methodologies and models in full accordance with ISO 14040 and 14044 standards, as confirmed by the critical review. The publishing of these LCI datasets definitely shows the commitment of the European aluminium industry to contribute in a transparent, fair and scientifically sound manner to product sustainability in a life cycle thinking perspective.

Recommendations and perspectives

Software houses and LCA practitioners are invited to update their generic European data on aluminium with the herewith datasets. Even if the quality and the completeness of these LCI data reach a high standard, some areas for data improvements have been identified, as described within the review report. Land use, water use and solid waste treatment appear as three priority areas for data refining and improvement. The land use dimension, particularly meaningful for bauxite mining, is not covered in the current LCI data while it is now integrated within many LCA studies. Up to now, the reporting of meaningful and robust data on water origins and use have not been possible due to the huge discrepancies between the surveyed sites combined with the difficulty to report coherent input and output water mass flows. The development of water data, only focussing on water-stressed areas, will most probably make more sense in the future. Finally, collecting more qualitative information about solid waste processing and treatment will help to include such operations within the system boundaries and to model their associated air, water and soil emissions.

     

Life cycle assessment of natural gas power plants in Thailand

Background, aim, and scope  The main primary energy for electricity in Thailand is natural gas, accounting for 73% of the grid mix. Electricity generation from natural gas combustion is associated with substantial air emissions. The two technologies currently used in Thailand, thermal and combined cycle power plant, have been evaluated for the potential environmental impacts in a “cradle-to-grid” study according to the life cycle assessment (LCA) method. This study evaluates the environmental impacts of each process of the natural gas power production over the entire life cycle and compares two different power plant technologies currently used in Thailand, namely, combined cycle and thermal. Materials and methods  LCA is used as a tool for the assessment of resource consumption and associated impacts generated from utilization of natural gas in power production. The details follow the methodology outlined in ISO 14040. The scope of this research includes natural gas extraction, natural gas separation, natural gas transmission, and natural gas power production. Most of the inventory data have been collected from Thailand, except for the upstream of fuel oil and fuel transmission, which have been computed from Greenhouse gases, Regulated Emissions, and Energy use in Transportation version 1.7 and Global Emission Model for Integrated Systems version 4.3. The impact categories considered are global warming, acidification, photochemical ozone formation, and nutrient enrichment potential (NEP). Results  The comparison reveals that the combined cycle power plant, which has a higher efficiency, performs better than the thermal power plant for global warming potential (GWP), acidification potential (ACP), and photochemical ozone formation potential (POCP), but not for NEP where the thermal power plant is preferable. Discussion  For the thermal power plant, the most significant environmental impacts are from power production followed by upstream of fuel oil, natural gas extraction, separation, and transportation. For the combined cycle power plant, the most significant environmental impacts are from power production followed by natural gas extraction, separation, and transportation. The significant difference between the two types of power production is mainly from the combustion process and feedstock in power plant. Conclusions  The thermal power plant uses a mix of natural gas (56% by energy content) and fuel oil (44% by energy content); whereas, the combined cycle power plant operates primarily on natural gas. The largest contribution to GWP, ACP, and NEP is from power production for both thermal as well as combined cycle power plants. The POCP for the thermal power plant is also from power production; whereas, for combined cycle power plant, it is mainly from transmission of natural gas. Recommendations and perspectives  In this research, we have examined the environmental impact of electricity generation technology between thermal and combined cycle natural gas power plants. This is the overview of the whole life cycle of natural gas power plant, which will help in decision making. The results of this study will be useful for future power plants as natural gas is the major feedstock being promoted in Thailand for power production. Also, these results will be used in further research for comparison with other feedstocks and power production technologies.     

Estimating Emissions from Electricity Generation Using Electricity Dispatch Models: The Importance of System Operating Constraints

This article develops a modeling approach for estimating emissions (e.g., carbon dioxide) from nuclear, coal, natural gas, and hydropower generators in reaction to short‐term changes to electricity demand. The modeling approach accounts for a set of operating constraints (OCs), including scheduled maintenance, forced outage, spinning reserves, fuel switching, seasonal output capacities, and seasonal hydro resource availability. It is found that these OCs are important to achieve reasonable estimates of electricity production by fuel type as well as associated emissions. This conclusion follows from an analysis of electric power generation by networks of power plants in Texas and New York in 2004 and 2005. The inputs to the model with operating constraints (OC model) developed in this article include hourly electricity demand, fuel costs, a list of power plants in the network, their basic generation characteristics, and the set of OCs developed in this article. Given these inputs, the OC model estimates the hourly amount of electricity generation by each power plant in the network, which leads to estimates of marginal resource consumption and emissions. Our central result is that historical annual and monthly generation by fuel type and efficiency are well estimated by the OC model and that the exclusion of OCs leads to poor estimates. This work can be combined with emerging work on wind and solar generation to provide a complete picture of contemporary grid dispatch and associated emissions.     

Adapting Stand‐Alone Renewable Energy Technologies for the Circular Economy through Eco‐Design and Recycling

Renewable energy (RE) technologies are looked upon favorably to provide for future energy demands and reduce greenhouse gas (GHG) emissions. However, the installation of these technologies requires large quantities of finite material resources. We apply life cycle assessment to 100 years of electricity generation from three stand‐alone RE technologies—solar photovoltaics, run‐of‐river hydro, and wind—to evaluate environmental burden profiles against baseline electricity generation from fossil fuels. We then devised scenarios to incorporate circular economy (CE) improvements targeting hotspots in systems’ life cycle, specifically (1) improved recycling rates for raw materials and (ii) the application of eco‐design. Hydro presented the lowest environmental burdens per kilowatt‐hour of electricity generation compared with other RE technologies, owing to its higher efficiency and longer life spans for main components. Distinct results were observed in the environmental performance of each system based on the consideration of improved recycling rates and eco‐design. CE measures produced similar modest savings in already low GHG emissions burdens for each technology, while eco‐design specifically had the potential to provide significant savings in abiotic resource depletion. Further research to explore the full potential of CE measures for RE technologies will curtail the resource intensity of RE technologies required to mitigate climate change.     

Effects of Using Heterogeneous Prices on the Allocation of Impacts from Electricity Use: A Mixed‐Unit Input‐Output Approach

Economic input‐output life cycle assessment (IO‐LCA) models allow for quick estimation of economy‐wide greenhouse gas (GHG) emissions associated with goods and services. IO‐LCA models are usually built using economic accounts and differ from most process‐based models in their use of economic transactions, rather than physical flows, as the drivers of supply‐chain GHG emissions. GHG emissions estimates associated with input supply chains are influenced by the price paid by consumers when the relative prices between individual consumers are different. We investigate the significance of the allocation of GHG emissions based on monetary versus physical units by carrying out a case study of the U.S. electricity sector. We create parallel monetary and mixed‐unit IO‐LCA models using the 2007 Benchmark Accounts of the U.S. economy and sector specific prices for different end users of electricity. This approach is well suited for electricity generation because electricity consumption contributes a significant share of emissions for most processes, and the range of prices paid by electricity consumers allows us to explore the effects of price on allocation of emissions. We find that, in general, monetary input‐output models assign fewer emissions per kilowatt to electricity used by industrial sectors than to electricity used by households and service sectors, attributable to the relatively higher prices paid by households and service sectors. This fact introduces a challenging question of what is the best basis for allocating the emissions from electricity generation given the different uses of electricity by consumers and the wide variability of electricity pricing.     

Input‐Output‐based Life Cycle Inventory

An input‐output‐based life cycle inventory (IO‐based LCI) is grounded on economic environmental input‐output analysis (IO analysis). It is a fast and low‐budget method for generating LCI data sets, and is used to close data gaps in life cycle assessment (LCA). Due to the fact that its methodological basis differs from that of process‐based inventory, its application in LCA is a matter of controversy. We developed a German IO‐based approach to derive IO‐based LCI data sets that is based on the German IO accounts and on the German environmental accounts, which provide data for the sector‐specific direct emissions of seven airborne compounds. The method to calculate German IO‐based LCI data sets for building products is explained in detail. The appropriateness of employing IO‐based LCI for German buildings is analyzed by using process‐based LCI data from the Swiss Ecoinvent database to validate the calculated IO‐based LCI data. The extent of the deviations between process‐based LCI and IO‐based LCI varies considerably for the airborne emissions we investigated. We carried out a systematic evaluation of the possible reasons for this deviation. This analysis shows that the sector‐specific effects (aggregation of sectors) and the quality of primary data for emissions from national inventory reporting (NIR) are the main reasons for the deviations. As a rule, IO‐based LCI data sets seem to underestimate specific emissions while overestimating sector‐specific aspects.     

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.     

Life Cycle Assessment of End‐of‐Life Management Options for Construction and Demolition Debris

A life cycle assessment (LCA) of various end‐of‐life management options for construction and demolition (C&D) debris was conducted using the U.S. Environmental Protection Agency's Municipal Solid Waste Decision Support Tool. A comparative LCA evaluated seven different management scenarios using the annual production of C&D debris in New Hampshire as the functional unit. Each scenario encompassed C&D debris transport, processing, separation, and recycling, as well as varying end‐of‐life management options for the C&D debris (e.g., combustion to generate electricity versus landfilling for the wood debris stream and recycling versus landfilling for the nonwood debris stream) and different bases for the electricity generation offsets (e.g., the northeastern U.S. power grid versus coal‐fired power generation). A sensitivity analysis was also conducted by varying the energy content of the C&D wood debris and by examining the impact of basing the energy offsets on electricity generated from various fossil fuels. The results include impacts for greenhouse gas (GHG) emissions, criteria air pollutants, ancillary solid waste production, and organic and inorganic constituents in water emissions. Scenarios with nonwood C&D debris recycling coupled with combustion of C&D wood debris to generate electricity had lower impacts than other scenarios. The nonwood C&D debris recycling scenarios where C&D wood debris was landfilled resulted in less overall impact than the scenarios where all C&D debris was landfilled. The lowest impact scenario included nonwood C&D debris recycling with local combustion of the C&D wood debris to generate electricity, providing a net gain in energy production of more than 7 trillion British thermal units (BTU) per year and a 130,000 tons per year reduction in GHG emissions. The sensitivity analysis revealed that for energy consumption, the model is sensitive to the energy content of the C&D wood debris but insensitive to the basis for the energy offset, and the opposite is true for GHG emissions.