A life cycle method for assessment of a colliery’s eco-indicator

Global Scope and Background  The study was aimed at presenting the methodology of the process eco-indicator, in relation to hard coal mines, and thereby making evaluation of the impact of the mine’s coal extraction process on the environment. The life cycle of a mine is made up of three phases: opening and developing the mine’s deposit, extraction of the mine’s deposit, closing the mine. Methods  The assessment of environmental influence of mining operation of a colliery was executed on a basis of the life cycle analysis, in accordance with the standard series PN-EN 14040. The environmental loads caused by individual unit processes were calculated by means of the aforementioned methodology with division into the basic influence categories: human health, ecosystem quality and natural resources. The obtained values of eco-indicators for the individual unit processes made it possible to compare the unit-process-caused environmental loads. Mean values of the eco-indicators of the individual unit processes were calculated by means of the inventory analysis covering 38 collieries. Next, these indicators were used to compare environmental load values by each similar process in a colliery. A total eco-indicator was calculated for colliery by summing up the eco-indicators of the individual unit processes. The eco-indicators, structured as above, were calculated for the phase of opening out a deposit and for the phase of extraction. Results and Discussion  The model mine in the phase of extraction of a deposit causes a total environmental load which expressed in points of the eco-indicator 99 amounts to 23.9 [MEw]. In the ‘human health’ category losses amount to 8.4 per cent, in the ‘quality of ecosystem’ 0.6 per cent and in the ‘resourses’ category 91 per cent. The greatest losses in all categories are caused by the process of getting body of coal and the next greatest ones are:

Impact Characterization in the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts

The tool for the reduction and assessment of chemical and other environmental impacts (TRACI) is a set of life-cycle impact assessment (LCIA) characterization methods that has been developed by a series of U.S. Environmental Protection Agency research projects. TRACI facilitates the characterization of stressors that may have potential effects, including ozone depletion, global warming, acidification, eutrophication, tropospheric ozone (smog) formation, eco-toxicity, human particulate effects, human carcinogenic effects, human non-carcinogenic effects, fossil fuel depletion, and land-use effects. This article describes the methodologies developed to address acidification, eutrophication, and smog. Each of these methods offers the ability to take account of differences in expected strength of impact as a function of pollution release location within North America. Specifically, the methods employ regionalized fate and transport modeling. The resulting factors differ regionally by up to more than an order of magnitude.     

On the possibilities to apply the result from an LCA disclosed to public

Aim, Scope and background  Given the communication limitation of a damage-oriented approach, the question addressed in this paper is how normalisation can be developed instead. Normalisation of product service systems without value choices is, in accordance to ISO 14042, suitable for external communication. Reason normalisation approaches use a geographically-defined baseline year of emissions, optionally combined with politically established target emissions (Guinée 2002, Stranddorf et al. 2001). In contradiction to these approaches, this paper aims to draw up the general structure of an alternative normalisation procedure. The normalisation procedure suggested here is based on environmental quality objectives (EQO), in order to streamline the result to include as few output parameters as possible, without compromising the scientific robustness of the method. Main Features  This article describes a normalisation procedure based on environmental quality objectives. Comparison between this approach and a damage-oriented approach is conducted. The relevant working area concerning dose and effect is evaluated. Then a discussion is conducted focusing on the trade-off necessary to achieve an integrated category indicator, covering the following issues; model reliability, user applicability and the unambiguously of the result. Result  A damage-oriented approach will have to take into account all the defined consequences from all impact categories that affect the safeguards in parallel. In other words, each impact category indicator and its potential effects on all safeguards must be evaluated and accounted for. In the case where a single category indicator cannot be found without utilising value choices, a number of category indicators will then have to constitute an intermediate category indicator result, where weighting must be applied in order to streamline the result. In contrast to the above approach, the suggested normalisation procedure utilises the precautionary principle with respect to the essential EQO in order to achieve a category indicator result, called a critical load category indicator result. In practice, this means that the number of figures in an LCIA-profile based on critical load will always be the same as the number of impact categories. Conclusions  The suggested EQO normalisation procedure forms a set of critical loads per impact category, where each is defined by a critical load function where linearity is defined between a zero load and the critical load. This procedure will affect the temporal resolution and the field of application of the LCIA method. The positive aspect is that the suggested normalisation procedure renders the method applicable for long-lived products like, for example, buildings or other infrastructures. This aspect is gained by reducing the damage-oriented resolution. Consequently, for long-lived products where the main environmental loads will appear in the future, it is hard to assess by a damage-oriented LCIA method (if all boundary conditions are not assumed to be fixed). The EQO normalisation method will, in this respect, improve the overall reliability of the outcome of an LCA when long-lived products are assessed. For short-lived products, adequate boundary conditions can be achieved, and for this reason a damage-oriented approach will have the possibility to address current consequences. Nevertheless, a damage-oriented approach working area is not applicable beneath thresholds unlike the EQO normalisation procedure. The most effective decision support of short-lived products is therefore achieved when both approaches are applied. Outlook  A complementary paper will be produced where the described normalisation procedure is exemplified in a case study, with special interest on assessment of chemical substances.     

LUCAS - A New LCIA Method Used for a Canadian-Specific Context

Goal, Scope and Background Canadian LCA practitioners currently use European or American methodologies when conducting comprehensive impact assessments, despite the fact that these methods may not be appropriate for Canadian conditions. Due to the lack of suitable models that are currently available, work has been undertaken to develop an LCIA method by adapting existing LCIA models to the Canadian context. This new method allows the characterization of 10 impact categories. Methods This project is strongly based on preliminary outcomes from SETAC recommendations for the best available practices in LCIA. Models from 3 recent LCIA site-dependent methods, EDIP2003, IMPACT2002+ and TRACI, were used in this midpoint Canadian-specific method. Characterization models were chosen based on their level of comprehensiveness, scientific sophistication and the possibility of integrating site-specific values in the models. Results and Discussion All regional and local impact categories in the method are site-differentiated. For aquatic eutrophication, (eco)toxicity and land-use impact categories, regionally-differentiated models taking into account fate and effect were already available: the parameters of these models were modified for the Canadian context. For acidification, aquatic and terrestrial eutrophication, existing models were spatially differentiated for fate: regionalization of the effect factor was also included, based on the level of sensitivity of each ecozone assessed with vulnerability factors. The default spatial resolution selected for this method was Canadian ecozones, which define spaces in an ecologically meaningful way where organisms and their physical environment evolve as a system. For each ecozone, 2334 site-dependent characterization factors have been calculated. Conclusion This LCIA methodology proposes an attractive and useful set of site-dependent characterization factors for the 15 Canadian terrestrial ecozones. Recommendation and Outlook Efforts are being carried out to extend the specificity of some factors used in eutrophication modelization. Finally, the transparency of the methodology will allow to re-calculate site-dependent characterization factors for different regions and for additional substances.     

No Matter – How?: Dealing with Matter‐less Stressors in LCA of Wind Energy Systems

The portfolio of impacts that are quantified in life cycle assessment (LCA) has grown to include rather different stressors than those that were the focus of early LCAs. Some of the newest life cycle impact assessment (LCIA) models are still in an early phase of development and have not yet been included in any LCA study. This is the case for sound emissions and noise impacts, which have been only recently modeled. Sound emissions are matter‐less, time dependent, and bound to the physical properties of waves. The way sound emissions and the relative noise impacts are modeled in LCA can show how new or existing matter‐less impacts can be addressed. In this study, we analyze, through the example of sound emissions, the specific features of a matter‐less impact that does not stem from the use of a kilogram of matter, nor is related to the emission of a kilogram of matter. We take as a case study the production of energy by means of wind turbines, contradicting the commonly held assumption that windmills have no emissions during use. We show how to account for sound emissions in the life cycle inventory phase of the life cycle of a wind turbine and then calculate the relative impacts using a noise LCIA model.     

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

Background, aim, and scope

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

Methodology

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

Results

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

Discussion

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

Conclusions

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

Recommendations and perspectives

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

Comparison between three different LCIA methods for aquatic ecotoxicity and a product environmental risk assessment

Background and Objective  In the OMNIITOX project 11 partners have the common objective to improve environmental management tools for the assessment of (eco)toxicological impacts. The detergent case study aims at: i) comparing three Procter &c Gamble laundry detergent forms (Regular Powder-RP, Compact Powder-CP and Compact Liquid-CL) regarding their potential impacts on aquatic ecotoxicity, ii) providing insights into the differences between various Life Cycle Impact Assessment (LCIA) methods with respect to data needs and results and iii) comparing the results from Life Cycle Assessment (LCA) with results from an Environmental Risk Assessment (ERA). Material and Methods  The LCIA has been conducted with EDIP97 (chronic aquatic ecotoxicity) [1], USES-LCA (freshwater and marine water aquatic ecotoxicity, sometimes referred to as CML2001) [2, 3] and IMPACT 2002 (covering freshwater aquatic ecotoxicity) [4]. The comparative product ERA is based on the EU Ecolabel approach for detergents [5] and EUSES [6], which is based on the Technical Guidance Document (TGD) of the EU on Environmental Risk Assessment (ERA) of chemicals [7]. Apart from the Eco-label approach, all calculations are based on the same set of physico-chemical and toxicological effect data to enable a better comparison of the methodological differences. For the same reason, the system boundaries were kept the same in all cases, focusing on emissions into water at the disposal stage. Results and Discussion  Significant differences between the LCIA methods with respect to data needs and results were identified. Most LCIA methods for freshwater ecotoxicity and the ERA see the compact and regular powders as similar, followed by compact liquid. IMPACT 2002 (for freshwater) suggests the liquid is equally as good as the compact powder, while the regular powder comes out worse by a factor of 2. USES-LCA for marine water shows a very different picture seeing the compact liquid as the clear winner over the powders, with the regular powder the least favourable option. Even the LCIA methods which result in die same product ranking, e.g. EDIP97 chronic aquatic ecotoxicity and USES-LCA freshwater ecotoxicity, significantly differ in terms of most contributing substances. Whereas, according to IMPACT 2002 and USES-LCA marine water, results are entirely dominated by inorganic substances, the other LCIA methods and the ERA assign a key role to surfactants. Deviating results are mainly due to differences in the fate and exposure modelling and, to a lesser extent, to differences in the toxicological effect calculations. Only IMPACT 2002 calculates the effects based on a mean value approach, whereas all other LCIA methods and the ERA tend to prefer a PNEC-based approach. In a comparative context like LCA the OMNIITOX project has taken the decision for a combined mean and PNEC-based approach, as it better represents the ‘average’ toxicity while still taking into account more sensitive species. However, the main reason for deviating results remains in the calculation of the residence time of emissions in the water compartments. Conclusion and Outlook  The situation that different LCIA methods result in different answers to the question concerning which detergent type is to be preferred regarding the impact category aquatic ecotoxicity is not satisfactory, unless explicit reasons for the differences are identifiable. This can hamper practical decision support, as LCA practitioners usually will not be in a position to choose the ’right’ LCIA method for their specific case. This puts a challenge to the entire OMNIITOX project to develop a method, which finds common ground regarding fate, exposure and effect modelling to overcome the current situa-tion of diverging results and to reflect most realistic conditions.     

A technique for reporting Life Cycle Impact Assessment (LCIA) results

Life Cycle Impact Assessment (LCIA) results are typically reported as individual scores, or as a breakdown of the most direct inputs; either as absolute values or relative scores. It is proposed to report not only the direct or primary LCIA scores, but also the impacts from secondary and tertiary processes. A graphical technique to report LCIA results is described where a combination of pie and donut charts, with the inner most layer representing direct impacts and subsequent outer layers representing preceding indirect impacts, is presented. An MS-EXCEL spread sheet is presented where the methods and outcomes are shown. This can then be used to display LCIA results. It is possible to present both primary and indirect impacts in a single figure. Significant indirect impacts contributing to the total score of an LCA are clearly visible.