Relations phylogénétiques chez les marchantiales (Hepaticae). Incongruence apparente entre données morphologiques et moléculaires

A cladistic analysis of the order Marchantiales based on morphological characters (43 characters) did not agree with the classification in current use. Molecular sequences of nuclear-encoded 26S rRNA genes of seven species of the order and two out-groups (1254–1299 bp) were analysed to solve this contradiction. Results between morphologial and sequence data are conflicting. The combination of the two data sets shows that a weighting of the morphological data corresponding to equal contributions of the two sets resolves contradiction. We demonstrate that the structure of two data sets can be compatible even if the resultant trees are incongruent. Addition of a few compatible data (for instance, via character weighting) can result in congruent trees. The taxonomic incongruence we observed could illustrate a case of too limited molecular sampling.     

Weighting of environmental trade-offs in CCS—an LCA case study of electricity from a fossil gas power plant with post-combustion CO2 capture, transport and storage

Purpose

Carbon capture and storage (CCS) is increasingly acknowledged as a potent global warming abatement option. It is demonstrated that whilst the global warming potential (GWP) decreases, the other environmental impact category potentials often increase in a life cycle perspective. Despite this, only a few studies clearly address this trade-off or use weighting to compare the positive and negative effects of CCS. The present life cycle assessment (LCA) study focuses, therefore, on presenting several environmental indicators and on weighting the inventory results in order to ascertain which of the analysed systems is to be preferred.

Method

The case studied is a projected gas power plant at Tjeldbergodden (Norway), where it is proposed to include post-combustion CCS. Four main scenarios have been analysed, one without and three with CCS. The principal variation between the CCS scenarios is that the steam required for amine regeneration is produced in three different ways: in a separate gas fuelled steam boiler; in a separate biomass fuelled steam boiler; and delivered from the low-pressure steam turbine in the power plant. Design information and technical specifications have been available. The study has used LCA methodology based on the ISO standard 14044, SimaPro 7.3.2.4 software and the Ecoinvent 2.0 database. The functional unit is 1?TWh electricity delivered to the grid. The following environmental impact categories have been included: GWP, acidification potential, eutrophication potential, photochemical ozone creation potential (POCP) and cumulative energy demand (CED). Three weighting methods have been used to ascertain the robustness of the weighting results: ReCiPe, EPS 2000 and IMPACT 2002+.

Results and discussion

The characterisation results show that the CCS scenarios have reduced impacts only in the case of GWP. The weighting demonstrates that in the ReCiPe model, climate change is strongly in focus, whilst in EPS 2000, human health and depletion of reserves are dominant. Climate change is also an important factor in IMPACT 2002+, together with effects on human health (respiratory inorganics). The process integration scenario has, however, the best result for all three weighting models. This contrasts with the results from the impact analysis where four of the five analysed impact categories rated the CCS-3 scenario as worse than the reference scenario. One possible option for improving the biofuel boiler scenario is to capture the CO₂ from the combustion of biomass in the external steam boiler. This would not, in all probability, affect the acidification, eutrophication, POCP and CED to any significant degree, but the GWP, and hence the ReCiPe and the IMPACT 2002+, weighting results could be expected to improve.

Conclusions

The weighting exercise has identified toxicity as a concern with regard to the biofuel boiler scenarios (CCS-2) and human health issues as having importance for the CCS-3 scenario. It would seem that process integration is a better CCS option than that of CCS providing steam from a separate steam boiler (without CCS), even where this boiler is biomass-fuelled. Any future analysis should focus both on the process integration scenario and the biofuel boiler scenario with CCS of biological CO₂.     

Development of a Composite Index with Quantitative Indicators for Drought Disaster Risk Analysis at the Micro Level

It is the aim of this study to provide non-state as well as state actors with an effective tool to assess the drought risk of households. The developed methodology introduces a technique for comparative measuring in the context of drought disaster risk management. This approach is designed to contribute to the effectiveness and accuracy of drought risk analyses at the micro level. In a process of qualitative and quantitative empirical research in East India, 10 single indicators for drought risk at the household level have been developed and validated. Based on this, methods of combining these single indicators within a composite index are introduced. Within the study area in Orissa, this instrument can be used for drought risk analysis in order to prioritize preventive measures. Outside the study area, the developed methodology can be adopted to gain suitable risk indicators and composite index weighting criteria. This study tackles the desire of disaster risk management projects for comparative risk analysis at the micro level and demonstrates how certain characteristics of households’ can be quantified. Thus the developed instrument facilitates prioritizing preventive actions for the most vulnerable households.     

Evaluating Environmental Performance of Pulp and Paper Manufacturing Using the Analytic Hierarchy Process and Life-Cycle Assessment

This article addresses the need for a structured and compre-hensive methodology for assessing the environmental perfor-mance of manufacturing processes. The analytic hierarchy pro-cess (AHP) is used as the basic framework for analyzing environmental impacts and improvement options following a streamlined life-cycle assessment (LCA) approach that is fo-cused on the manufacturing operation. The multicriteria de-cision analysis approach of the AHP is consistent with the LCA concept because the environmental factors can be hierarchi-cally structured into impacts and improvement options. Its po-tential as a valuation tool for impact and improvement assess-ment addresses both qualitative and quantitative issues in environmental decision making.
Through application to a pulp and paper manufacturing case study, the viability of the AHP for evaluating environmen-tal impacts and prioritizing process improvement options rela-tive to these impacts is demonstrated. AHP was used to pro-vide a quantitative tool for the design of a set of weighting factors for impact and improvement analyses.     

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.     

Valuation methods within LCA - Where are the values?

It is generally recognised that the valuation in LCA requires political, ideological and/or ethical values (hence the term). These values, however, are seldom discussed, and this paper may he seen as an early attempt. One result is that not only the valuation weighting factors, but also the choice of valuation methodology and the choice of using a valuation weighting method at all, are influenced by fundamental ethical and ideological valuations. Since there is no societal consensus on these fundamental values, and never will be one in an open democratic society, there is no reason to expect consensus either on valuation weighting factors, or on the valuation method or even on the choice of using a valuation weighting method at all. Another result of the discussion on values is that the ethical and ideological valuations are often made implicitly in the choice of method, data, etc., thus making it difficult to discuss the values and the implications of different standpoints. Although this paper focus on the valuation methods within LCA, it is expected that much of the discussion and the conclusions are of relevance for other environmental management tools, e.g. Environmental Impact Assessment.     

On the limitations of life cycle assessment and environmental systems analysis tools in general

The potential and limitations of life cycle assessment and environmental systems analysis tools in general are evaluated. More specifically this is done by exploring the limits of what can be shown by LCA and other tools. This is done from several perspectives. First, experiences from current LCAs and methodology discussions are used including a discussion on the type of impacts typically included, quality of inventory data, methodological choices in relation to time aspects, allocation, characterisation and weighting methods and uncertainties in describing the real world. Second, conclusions from the theory of science are practised. It is concluded that it can in general not be shown that one product is environmentally preferable to another one, even if this happens to be the case. This conclusion has important policy implications. If policy changes require that it must be shown that one product is more (or less) environmentally preferable before any action can be taken, then it is likely that no action is ever going to take place. If we want changes to be made, decisions must be taken on a less rigid basis. It is expected that in this decision making process, LCA can be a useful input. Since it is the only tool that can be used for product comparisons over the whole life cycle, it can not be replaced by any other tool and should be used. Increased harmonisation of LCA methodology may increase the acceptability of chosen methods and increase the usefulness of the tool.     

Current status of weighting methodologies in Japan

In Japan, requirements for the development of valuation methodology are very stringent. Several methodologies have been proposed to meet these demands in recent years. These methods, however, are quite different in many points such as selected impact categories, the numbers of substances considered, and basic concepts for the environment. The results of LCA are fully dependent on the goals of LCA practitioners and commissioners. If they misunderstand the concept of method and use it, the result may not fit for the purpose. Consequently, it is important to characterize the methods selected by the practitioner in accordance with their LCA goals. In this paper, weighting methodologies proposed in Japan have been introduced with a comparison between the results of case studies for common industrial products. Furthermore, we considered the present situations and future directions of valuation methodologies in Japan. This consideration is carried out based on the results of investigations performed by the Impact Assessment Committee of the National LCA Project of Japan     

Weighting against homoplasy improves phylogenetic analysis of morphological data sets

The problem of character weighting in cladistic analysis is revisited. The finding that, in large molecular data sets, removal of third positions (with more homoplasy) decreases the number of well supported groups has been interpreted by some authors as indicating that weighting methods are unjustified. Two arguments against that interpretation are advanced. Characters that collectively determine few well‐supported groups may be highly reliable when taken individually (as shown by specific examples), so that inferring greater reliability for sets of characters that lead to an increase in jackknife frequencies may not always be warranted. But even if changes in jackknife frequencies can be used to infer reliability, we demonstrate that jackknife frequencies in large molecular data sets are actually improved when downweighting characters according to their homoplasy but using properly rescaled functions (instead of the very strong standard functions, or the extreme of inclusion/exclusion); this further weakens the argument that downweighting homoplastic characters is undesirable. Last, we show that downweighting characters according to their homoplasy (using standard homoplasy‐weighting methods) on 70 morphological data sets (with 50–170 taxa), produces clear increases in jackknife frequencies. The results obtained under homoplasy weighting also appear more stable than results under equal weights: adding either taxa or characters, when weighting against homoplasy, produced results more similar to original analyses (i.e., with larger numbers of groups that continue being supported after addition of taxa or characters), with similar or lower error rates (i.e., proportion of groups recovered that subsequently turn out to be incorrect). Therefore, the same argument that had been advanced against homoplasy weighting in the case of large molecular data sets is an argument in favor of such weighting in the case of morphological data sets. © The Willi Hennig Society 2008.     

Weighting across safeguard subjects for LCIA through the application of conjoint analysis

Background  

Many types of weighting methods, which have integrated the various environmental impacts that are used for life-cycle impact assessment (LCIA), were proposed with the aim of developing the methodology as a useful information resource for decision making, such as in the selection of products. Economic valuation indexes, in particular, have attracted attention, as their assessment results are easy to understand and can be applied in conjunction with other assessment tools, including life-cycle costing (LCC) and environmental accounting. Conjoint analysis has been widely used in market research, and has recently been applied to research in environmental economics. The method enables us to provide two types of assessment results; an economic valuation and a dimensionless index. This method is therefore expected to contribute greatly to increasing the level of research into weighting methodology, in which an international consensus has yet to be established. Conjoint analysis, however, has not previously been applied to LCIA.     

Eco-efficiency indicator framework implemented in the metallurgical industry: part 1—a comprehensive view and benchmark

Purpose

The purpose of this work was to develop an indicator framework for the environmental sustainability benchmarking of products produced by the metallurgical industry. Sustainability differentiation has become an important issue for companies throughout the value chain. Differentiation is sometimes not attainable, due to the use of average data, lack of comparative data, certain issues being overshadowed by others, and a very narrow palette of indicators dominating the current sustainability assessments. There is a need for detailed and credible analyses, which show the current status and point out where improvements can be made. The indicator framework is developed to give a comprehensive picture of eco-efficiency, to provide methods that enable relevant comparisons as well as the tools for communicating the results. In this way, the methodology presented in this study aims to make differentiation easier and thus aid companies in driving the development toward more sustainable solutions.

Methods

The framework is based on the existing indicator framework Gaia Biorefiner, which is primarily intended for bio-based products. In this work, the framework was further developed for application in the metallurgical industry. The indicator framework is built by first looking at the issues, which are critical to the environment and global challenges seen today and which the activities of the metallurgical industry may have an impact on. Based on these issues, suitable indicators are chosen if they exist and built if they do not. The idea is that all indicators in a group form a whole, showing areas of innovation while refraining from aggregating and weighting, which often compromise a comprehensive and objective view. Both qualitative and quantitative indicators are included. The indicators are constructed following the criteria set by the EU and OECD for building indicators. Each indicator further has a benchmark. The rules for building the benchmark are connected to the indicators. Suitable data sources and criteria for the benchmark and the indicators are gathered from literature, publicly available databases, and commercial LCA software. The use of simulation tools for attaining more reliable data is also studied.

Results and discussion

The result is a visual framework consisting of ten indicator groups with one to five indicators each, totaling up to 31 indicators. These are visualized in a sustainability indicator “flower.” The flower can be further opened up to study each indicator and the reasons behind the results. The sustainability benchmark follows a methodology that is based on utilization of baseline data and sustainability criteria or limits. A simulation approach was included in the methodology to address the problem with data scarcity and data reliability. The status of the environment, current production technologies, location-specific issues, and process-specific issues all affect the result, and the aim of finding relevant comparisons that will support sustainability differentiation is answered by a scalable scoping system.

Conclusions

A new framework and its concise visualization has been built for assessing the eco-efficiency of products from the metallurgical industry, in a way that aims to answer the needs of the industry. Since there is a baseline, against which each indicator can be benchmarked, a sustainability indicator “flower” can be derived, one of the key innovations of this methodology. This approach goes beyond the usual quantification, as it is also scalable and linked to technology and its fundamental parameters. In part 2, a case study “A case study from the copper industry” tests and illustrates the methodology.

     

Computational procedure for a weighted diallel analysis

Summary A diallel analysis is described for the case in which the values of the characteristic used in an inheritance study have unequal variances. Such a characteristic can be a mean, a slope of a regression line, or the estimates of some parameter of a linear or nonlinear model. Computational formulae are presented which incorporate the necessary weighting along with the statistics of the Hayman-Jinks method for diallel analysis. The method described can also be used to perform a weighted diallel analysis based on means when there are unequal numbers of replications per cross. A simple example demonstrates the computations necessary to complete a weighted diallel analysis.Journal paper no. 87-117-J of the Kansas Agricultural Experiment Station. This study was conducted by the senior author in partial fulfillment for the PhD degree in genetics     

Weighting in LCA Based on Ecotaxes - Development of a Mid-point Method and Experiences from Case Studies

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DOI: http://dx.doi.org/10.1065/lca2006.04.015

Goal, Scope and Background

The weighting phase in Life Cycle Assessment (LCA) is and has always been a controversial issue, partly because this element requires the incorporation of social, political and ethical values. Despite the controversies, weighting is widely used in practise. In this paper we will present an approach for monetisation of environmental impacts which is based on the consistent use of ecotaxes and fees in Sweden as a basis for the economic values. The idea behind this approach is that taxes and fees are expressions of the values society places on resource uses and emissions. An underlying assumption for this is that the decisions taken by policy-makers are reflecting societal values thus reflecting a positive view of representative democracy.

Methods

In the method a number of different ecotaxes are used. In many cases they can directly be used as valuation weighting factors, an example is the CO2-tax that can be used as a valuation of CO2-emissions. In some cases, a calculation has to be made in order to derive a weighting factor. An example of this is the tax on nitrogen fertilisers which can be recalculated to an emission of nitrogen which can be used as a weighting factor for nitrogen emissions. The valuation weighting factors can be connected to characterisation methods in the normal LCA practise. We have often used the Ecotax method in parallel to other weighting methods such as the Ecoindicator and EPS methods and the results are compared.

Results and Discussion

A new set of weighting factors has been developed which has been used in case studies. It is interesting to note that the Ecotax method is able to identify different environmental problems as the most important ones in different case studies. In some cases, the Ecotax method has identified some interventions as the most important ones which lack weighting factors in other weighting methods. The midpoint-endpoint debate in the LCA literature has often centred on different types of uncertainties. Sometimes it is claimed that an advantage with having an endpoint approach is that the weighting would be easier and less uncertain. Here we are however suggesting a mid-point weighting method that we claim are no less uncertain than other often used weighting methods based on a damage assessment. This paper can therefore be seen as a discussion paper also in the midpoint-endpoint debate.

Conclusion and Recommendation

The Ecotax method is ready to use. It should be further updated and developed as taxes are changed and new characterisation methods are developed. The method is not only relevant for LCA but also for other environmental systems analysis. The Ecotax method has also been used as a valuation method for Cost-Benefit Analysis (CBA), Life Cycle Costing (LCC) and within the context of a Strategic Environmental Assessment (SEA).

     

Sensitivity analysis for causal inference using inverse probability weighting

Evaluation of impact of potential uncontrolled confounding is an important component for causal inference based on observational studies. In this article, we introduce a general framework of sensitivity analysis that is based on inverse probability weighting. We propose a general methodology that allows both non‐parametric and parametric analyses, which are driven by two parameters that govern the magnitude of the variation of the multiplicative errors of the propensity score and their correlations with the potential outcomes. We also introduce a specific parametric model that offers a mechanistic view on how the uncontrolled confounding may bias the inference through these parameters. Our method can be readily applied to both binary and continuous outcomes and depends on the covariates only through the propensity score that can be estimated by any parametric or non‐parametric method. We illustrate our method with two medical data sets.     

Longitudinal Studies of Binary Response Data Following Case–Control and Stratified Case–Control Sampling: Design and Analysis

Summary We discuss design and analysis of longitudinal studies after case–control sampling, wherein interest is in the relationship between a longitudinal binary response that is related to the sampling (case–control) variable, and a set of covariates. We propose a semiparametric modeling framework based on a marginal longitudinal binary response model and an ancillary model for subjects' case–control status. In this approach, the analyst must posit the population prevalence of being a case, which is then used to compute an offset term in the ancillary model. Parameter estimates from this model are used to compute offsets for the longitudinal response model. Examining the impact of population prevalence and ancillary model misspecification, we show that time‐invariant covariate parameter estimates, other than the intercept, are reasonably robust, but intercept and time‐varying covariate parameter estimates can be sensitive to such misspecification. We study design and analysis issues impacting study efficiency, namely: choice of sampling variable and the strength of its relationship to the response, sample stratification, choice of working covariance weighting, and degree of flexibility of the ancillary model. The research is motivated by a longitudinal study following case–control sampling of the time course of attention deficit hyperactivity disorder (ADHD) symptoms.     

Prediction of thermostability from amino acid attributes by combination of clustering with attribute weighting: a new vista in engineering enzymes

The engineering of thermostable enzymes is receiving increased attention. The paper, detergent, and biofuel industries, in particular, seek to use environmentally friendly enzymes instead of toxic chlorine chemicals. Enzymes typically function at temperatures below 60°C and denature if exposed to higher temperatures. In contrast, a small portion of enzymes can withstand higher temperatures as a result of various structural adaptations. Understanding the protein attributes that are involved in this adaptation is the first step toward engineering thermostable enzymes. We employed various supervised and unsupervised machine learning algorithms as well as attribute weighting approaches to find amino acid composition attributes that contribute to enzyme thermostability. Specifically, we compared two groups of enzymes: mesostable and thermostable enzymes. Furthermore, a combination of attribute weighting with supervised and unsupervised clustering algorithms was used for prediction and modelling of protein thermostability from amino acid composition properties. Mining a large number of protein sequences (2090) through a variety of machine learning algorithms, which were based on the analysis of more than 800 amino acid attributes, increased the accuracy of this study. Moreover, these models were successful in predicting thermostability from the primary structure of proteins. The results showed that expectation maximization clustering in combination with uncertainly and correlation attribute weighting algorithms can effectively (100%) classify thermostable and mesostable proteins. Seventy per cent of the weighting methods selected Gln content and frequency of hydrophilic residues as the most important protein attributes. On the dipeptide level, the frequency of Asn-Glu was the key factor in distinguishing mesostable from thermostable enzymes. This study demonstrates the feasibility of predicting thermostability irrespective of sequence similarity and will serve as a basis for engineering thermostable enzymes in the laboratory.     

Participatory Development and Analysis of a Fuzzy Cognitive Map of the Establishment of a Bio-Based Economy in the Humber Region

Fuzzy Cognitive Mapping (FCM) is a widely used participatory modelling methodology in which stakeholders collaboratively develop a ‘cognitive map’ (a weighted, directed graph), representing the perceived causal structure of their system. This can be directly transformed by a workshop facilitator into simple mathematical models to be interrogated by participants by the end of the session. Such simple models provide thinking tools which can be used for discussion and exploration of complex issues, as well as sense checking the implications of suggested causal links. They increase stakeholder motivation and understanding of whole systems approaches, but cannot be separated from an intersubjective participatory context. Standard FCM methodologies make simplifying assumptions, which may strongly influence results, presenting particular challenges and opportunities. We report on a participatory process, involving local companies and organisations, focussing on the development of a bio-based economy in the Humber region. The initial cognitive map generated consisted of factors considered key for the development of the regional bio-based economy and their directional, weighted, causal interconnections. A verification and scenario generation procedure, to check the structure of the map and suggest modifications, was carried out with a second session. Participants agreed on updates to the original map and described two alternate potential causal structures. In a novel analysis all map structures were tested using two standard methodologies usually used independently: linear and sigmoidal FCMs, demonstrating some significantly different results alongside some broad similarities. We suggest a development of FCM methodology involving a sensitivity analysis with different mappings and discuss the use of this technique in the context of our case study. Using the results and analysis of our process, we discuss the limitations and benefits of the FCM methodology in this case and in general. We conclude by proposing an extended FCM methodology, including multiple functional mappings within one participant-constructed graph.     

Development of weighting factors for G20 countries—explore the difference in environmental awareness between developed and emerging countries

Purpose

Weighting is one of the steps involved in LCIA. This enables us to integrate various environmental impacts and facilitates the interpretation of environmental information. Many different weighting methodologies have already been proposed, and the results of many case studies with a single index have been published. LIME2 (Itsubo et al. Int J Life Cycle Assess 17(4):488-498, 2012) developed weighting factors for four different areas of protection that reflect environmental awareness among the Japanese public. This method has already been widely used in Japan, but difficulties exist universally using the Japanese weighting factors around the world. It is presumed that the weighting varies depending on economic, cultural, and social conditions, and there are still few cases in which weighting factors have been specifically invented or studied in consideration of variance in these elements. This study attempted to develop weighting factors applicable to the Group of Twenty (G20) countries with a view toward developing those that could be used in different countries. In the study, a survey was conducted with a uniform questionnaire in G20 countries to compare the weighting factors calculated for different countries, along with an investigation on development and utilization of global weighting factors.

Methods

A conjoint analysis was conducted to give a weighting between the four areas of protection defined by LIME: human health, social assets, biodiversity, and primary production. The analysis is suitable for measuring the value of each of the multiple attributes of the environment. This study conducted a questionnaire in all the G20 member states. The survey puts priority on making the questions understood by the respondents and minimizing bias, adopting interviews, visiting surveys, and surveys in venues in the 11 emerging countries. In the developed countries, Internet surveys were conducted after confirming that their results are statistically significant from the pretest results in these states. In both surveys, random sampling was performed to take 200–250 samples (households) in each of the emerging countries and 500–600 samples in each of the developed countries. The surveys collected a total of 6400 responses. Statistical values based on this model can be considered to reflect the variability between each individual’s environmental thoughts. The calculated results can then be used to compare the variety of environmental thoughts in developed and emerging countries.

Results and discussion

The study was able to obtain two different kinds of results: dimensionless weighting factors and economic indicators using the amount of willingness to pay. This paper solely presents the former. The weighting factors in the entire G20 community, in the group of developed countries (G8) and in the group of emerging countries (G20 states excluding the G8) and those in the individual G20 countries, were estimated. The calculated values were significant statistically at the 1 % level (all p values for the safeguard subject coefficients were less than 0.0001), with the exception of monetary attributes for several emerging countries. Converted into dimensionless values, so that the total sum for the four subjects equals 1, the weighting factor was the highest for human health in the entire G20 circles, at 0.34, followed by biodiversity at 0.29, and primary production at 0.23. The weighting for social assets was relatively poor, at 0.13. In the G8 developed states, the figures of biodiversity and primary production were relatively higher than those of the same two subjects in the full G20. Biodiversity had the highest value, at 0.34, and was followed by human health at 0.30. On the other hand, in emerging countries, the weighting of health impacts was particularly significant, at 0.44, whereas the three other subjects had almost equivalent weightings—biodiversity at 0.19, social assets at 0.18, and primary product at 0.18. The weighting factors by country and the variance of preference intensities by country showed minor differences among developed countries while they reflected considerable differences among emerging countries.

Conclusions

Accurate weighting factors representing the environmental attitudes of the world and national public are needed in order to conduct general purpose LCA. This study is the world’s first to conduct surveys with the use of the same questionnaire not only in developed countries but also in emerging countries, and to compare the findings. A total of 6400 responses were obtained via interviews and Internet surveys. The survey thus gained a statistically significant result on all the environmental attributes including the weighting factors for the G20 circles, G8 states, emerging countries exclusive of the G8 states, and individual countries in which surveys took place. The results have revealed a relatively minor difference in weighting factors and variation coefficients between the areas of protection in the developed countries whereas a considerable difference was observed between those subjects in emerging countries.