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 inventory processes of the ArcelorMittal Poland (AMP) S.A. in Kraków,Poland—basic oxygen furnace steel production

Purpose  

The goal of this paper is to describe the life cycle inventory (LCI) approach to steel produced by ArcelorMittal’s Basic Oxygen Furnace (AMBOF) in Kraków, 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 steel production). The background input and output data from the basic oxygen furnace (BOF) steelmaking process has been inventoried as follows: pig iron, scrap, slag forming materials (CaO), ferroalloys, Al, carbon and graphite carburizer (material for carburization of steel), isolating powder, consumption of energy and fuels including natural gas, blast furnace gas and coke oven gas, electric energy, steam, air, oxygen, industrial water and heat, emission of air pollutants, waste, internal transport and land use.     

Life cycle inventory for electric energy system in Brazil

Goal, Scope and Background  

The goal of this paper is to present the modeling of life cycle inventory (LCI) for electric energy production and delivery in Brazil for the reference year 2000 by application of ISO 14040. Site specific data along with sector production data have been combined to construct an energy production model, which has been applied to emissions estimation. Background-data of all the inputs and outputs from the system have been inventoried as follows: gross electric energy generation, installed nameplate capacity, flooded area, losses, emissions to air / water, process waste, used fuel, efficiency and land use.     

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 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.

     

Using monte carlo simulation in life cycle assessment for electric and internal combustion vehicles

1 Background

The U.S. Government has encouraged shifting from internal combustion engine vehicles (ICEVs) to alternatively fueled vehicles such as electric vehicles (EVs) for three primary reasons: reducing oil dependence, reducing greenhouse gas emissions, and reducing Clean Air Act criteria pollutant emissions. In comparing these vehicles, there is uncertainty and variability in emission factors and performance variables, which cause wide variation in reported outputs.

2 Objectives

A model was developed to demonstrate the use of Monte Carlo simulation to predict life cycle emissions and energy consumption differences between the ICEV versus the EV on a per kilometer (km) traveled basis. Three EV technologies are considered: lead-acid, nickel-cadmium, and nickel metal hydride batteries.

3 Methods

Variables were identified to build life cycle inventories between the EVs and ICEV. Distributions were selected for each of the variables and input to Monte Carlo Simulation soft-ware called Crystal Ball 2000®.

4 Results and Discussion

All three EV options reduce U.S. oil dependence by shifting to domestic coal. The life cycle energy consumption per kilometer (km) driven for the EVs is comparable to the ICEV; however, there is wide variation in predicted energy values. The model predicts that all three EV technologies will likely increase oxides of sulfur and nitrogen as well as particulate matter emissions on a per km driven basis. The model shows a high probability that volatile organic compounds and carbon monoxide emissions are reduced with the use of EVs. Lead emissions are also predicted to increase for lead-acid battery EVs. The EV will not reduce greenhouse gas emissions substantially and may even increase them based on the current U.S. reliance on coal for electricity generation. The EV may benefit public health by relocating air pollutants from urban centers, where traffic is concentrated, to rural areas where electricity generation and mining generally occur. The use of Monte Carlo simulation in life cycle analysis is demonstrated to be an effective tool to provide further insight on the likelihood of emission outputs and energy consumption.     

Traffic noise in LCA

Background, aim, and scope  

An inclusion of traffic noise effects could change considerably the overall results of many life cycle assessment (LCA) studies. However, at present, noise effects are usually not considered in LCA studies, mainly because the existing methods for their inclusion do not fulfill the requirement profile. Two methods proposed so far seem suitable for inclusion in generic life cycle inventory (LCI) databases, and a third allows for inter-modal comparison. The aim of this investigation is an in-depth analysis of the existing methods and the proposition of a framework for modeling road transport noise emissions in LCI in accordance to the requirement profile postulated in part 1.     

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

Purpose

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

Methods

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

Results

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

Conclusions

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

A decision support tool for modifications in crop cultivation method based on life cycle assessment: a case study on greenhouse gas emission reduction in Taiwanese sugarcane cultivation

Background, aim, and scope  

Nowadays, various crops are cultivated to supply emerging needs in sustainable fuels and materials. In addition to the development of crop processing technologies, cultivation processes in a cropping system could be modified to meet the emerging needs, along with the conventional needs in food supply. This study provides a decision tool for modifications in cultivation of crops based on life cycle assessment. Sugarcane cultivation in Taiwan is chosen as a case study to present such a decision tool, because it is an important potential indigenous resource for energy (for example, bio-ethanol) and materials (for example, bio-plastics). First, this study presents the amount of greenhouse gas (GHG) emissions associated with the production of 1 ton of sugarcane in Taiwan, which makes it possible to understand how it is consistent to develop this bio-resource in terms of both objectives: i.e., resource security and reduction of global warming impact. Next, sensitivity of the parameters in cropping systems, such as amount of irrigation, fertilization and tillage are assessed from a viewpoint of GHG emissions, using the LCI model constructed in the first step. Finally, equivalent impact level (EIL) lines are presented for some important parameters in the cropping system to support considerations in modification of agricultural methods. Because the objective is to discuss parameters in cultivation processes, the scope of study is limited to cradle-to-gate of raw sugarcane transported to the cane processing plant.     

Life cycle assessment of energy and GHG emissions during ethanol production from grass straws using various pretreatment processes

Purpose  

The aim of this study was to perform a well-to-pump life cycle assessment (LCA) to investigate the overall net energy balance and environmental impact of bioethanol production using Tall Fescue grass straw as feedstock. The energy requirements and greenhouse gas (GHG) emissions were compared to those of gasoline to explore the potential of bioethanol as sustainable fuel.     

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

Purpose

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

Methods

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

Results and discussion

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

Conclusions

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

Development of a new tank-to-wheels methodology for energy use and green house gas emissions analysis based on vehicle fleet modeling

Background, aim and scope  

Tank-to-Wheels (TtW) makes the largest contribution to the total Well-to-Wheels (WtW) energy consumption and greenhouse gas (GHG) emissions from fossil-derived transportation fuels. The most commonly adopted TtW methodologies to obtain vehicle energy consumption, energy efficiency, and GHG emissions used to date all have significant limitations. A new TtW methodology, which combines micro-scale virtual vehicle simulation with macro-scale fleet modeling, is proposed in this paper. The models capabilities are demonstrated using a case study based on data from the passenger car sector in Great Britain.     

Comparative life cycle assessment of current and future electricity generation systems in the Czech Republic and Poland

Purpose

The purpose of the study was to perform a comparative life cycle assessment of current and future electricity generation systems in the Czech Republic and Poland. The paper also outlines the main sources of environmental impact for the different impact categories for the electricity generation technologies analyzed. The analyses covered the years 2000–2050, and were conducted within the framework of the international programme Interreg V-A Czech Republic-Poland, Microprojects Fund 2014–2020 in the Euroregion Silesia.

Methods

Environmental assessment was done using the life cycle assessment (LCA) and ReCiPe Midpoint and Endpoint methods, which allowed the presentation of different categories of environmental impact and damage. The LCA was based on ISO 14040 and ISO 14044, using SimaPro 8.2.3 software with the Ecoinvent 3.2 database. The analyses cover both the current electricity production structures in the Czech Republic and Poland, and the projected energy production.

Results and discussion

The LCA analyses performed for the energy systems under consideration in the Czech Republic and Poland enabled a comparative analysis of current and forecast energy systems in these countries, as well as identification of the main sources of environmental impact. Comparative analysis of the LCA results showed that current and future electricity generation systems in Poland caused higher environmental impact there, than in the Czech Republic.

Conclusions

The assessment of the life cycle of electricity sources showed that the main determinant of the negative impact on the environment of energy systems in both Poland and the Czech Republic was the consumption of solid fuels, and in particular, the consumption of lignite. It is important to highlight that this is the first attempt of a comparative LCA of electricity production in the Czech Republic and Poland. This is also the first approach that contains analyses of the life cycle assessment of both present and future energy systems. The economic assessment and eco-efficiency of current and future electricity generation systems in European Union countries will be addressed in future research.

     

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.     

Pilot-scale conversion of lime-treated wheat straw into bioethanol: quality assessment of bioethanol and valorization of side streams by anaerobic digestion and combustion

Introduction  

The limited availability of fossil fuel sources, worldwide rising energy demands and anticipated climate changes attributed to an increase of greenhouse gasses are important driving forces for finding alternative energy sources. One approach to meeting the increasing energy demands and reduction of greenhouse gas emissions is by large-scale substitution of petrochemically derived transport fuels by the use of carbon dioxide-neutral biofuels, such as ethanol derived from lignocellulosic material.     

Inventory analysis of the timber industry in Ghana

Background, aim, and scope  

The timber sector, i.e., forestry and timber industry, plays an important role in the socioeconomic development of Ghana through timber products export. Timber production in this sector is associated with increasing environmental burdens in terms of use of materials and energy, production of emissions and waste, and land use changes. The purpose of this study was to compile a comprehensive life cycle inventory (LCI) to identify the most dominant environmental pressures for five major production lines in the timber industry, and to evaluate the influence of the choice of the functional unit on the results (1 m³, 1 kg, and 1 euro). LCA’s of wood typically base their functional unit on volume, but mass or money may be more appropriate for the rather different products considered in this study.     

Environmental assessment of German electricity generation from coal-fired power plants with amine-based carbon capture

Background, aim, and scope  

One of the most important sources of global carbon dioxide emissions is the combustion of fossil fuels for power generation. Power plants contribute more than 40% of the worldwide anthropogenic CO₂ emissions. Therefore, the increased requirements for climate protection are a great challenge for the power producers. In this context a significant increase in power plant efficiency will contribute to reduce specific CO₂ emissions. Additionally, CO₂ capture and storage (CCS) is receiving considerable attention as a greenhouse gas (GHG) mitigation option. CCS allows continued use of fossil fuels with no or little CO₂ emissions given to the atmosphere. This could approve a moderate transition to a low-carbon energy generation over the next decades. Currently, R&D activities in the field of CCS are mainly concentrated on the development of capture techniques, the geological assessment of CO₂ storage reservoirs, and on economic aspects. Although first studies on material and energy flows caused by CCS are available, a broader environmental analysis is necessary to show the overall environmental impacts of CCS. The objectives in this paper are coal-based power plants with and without CO₂ capture via mono-ethanolamine (MEA) and the comparison of their environmental effects based on life cycle assessment methodology (LCA).     

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

Purpose

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

Methods

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

Results and discussion

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

Conclusions

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

     

Life cycle energy consumption and CO2 emission of an office building in China

Purpose  

Building is one of the main factors of energy use and greenhouse gas emissions. Reducing energy consumption and carbon dioxide (CO₂) emission from building is urgent for environmental protection and sustainable development. The objective of this study is to develop a life cycle assessment (LCA) model for an office building in China to assess its energy consumption and CO₂ emission, determine the whole life cycle phases, and the significant environmental aspects that contribute most to the impact.