Assessing the sustainability of biofuels: A logic-based model

Assessing the sustainability of biofuels: A logic-based model

Energy 36 (2011) 2089e2096 Contents lists available at ScienceDirect Energy journal homepage: Assessing the sustaina...

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Energy 36 (2011) 2089e2096

Contents lists available at ScienceDirect

Energy journal homepage:

Assessing the sustainability of biofuels: A logic-based model Edgard Gnansounou* Swiss Federal Institute of Technology Lausanne (EPFL), ENAC INTER GR-GN station 18, 1015 Lausanne, Switzerland

a r t i c l e i n f o

a b s t r a c t

Article history: Received 10 September 2009 Received in revised form 9 April 2010 Accepted 15 April 2010 Available online 3 June 2010

Over the last decade, the production and consumption of biofuels increased rapidly worldwide, in an attempt to reduce GHG (greenhouse gas) emissions, diversify transportation fuels, promote renewable energy, and create or maintain employment, especially in rural areas and developing countries. Although policy instruments being currently implemented in industrialized regions focus on sustainable biofuels, the definition and assessment of sustainability remains a highly debated issue. Several countries have adopted compulsory targets or financial incentives for promoting biofuels, and only a few countries have accounted for sustainability certification schemes for those biofuels within their policy framework. In this paper, a logic-based model for assessing the sustainability of biofuels is presented. The model uses a hierarchical structure to link multiple factors from the more specific variables to the most general one, sustainability performance. The strengths and limitations of the model are discussed and the anticipated improvements are provided. Ó 2010 Elsevier Ltd. All rights reserved.

Keywords: Biofuels Certification Label Sustainability impact assessment Logic-based model

1. Introduction A few years ago, biofuels were perceived as one of the most viable alternatives to fossil fuels for transportation. The transportation sector worldwide is particularly vulnerable to oil disruption, with a dependence on fossil oil over 95%. Biofuels have multiple advantages which make them attractive for inclusion within a diversification strategy. They supposedly have the potential to be CO2-neutral, they can be flexibly blended with fossil fuels at various percentages, and they are renewable and cause less of a local environmental burden compared to fossil fuels. However, this positive image has changed dramatically in the last few years. Perceptions started to change with the rise of tortillas prices in Mexico in 2007. Overall, the global food price crisis of 2007e2008 was associated with an increase in biofuels production in industrialized countries, especially in the United States (US). After analyzing several factors related to higher food prices since 2002, Mitchell [23] concluded that the diversion of large proportions of grains from food to biofuels production in the US and Europe was the most important driver of increased food prices. Another criticism of biofuels is the fact that their GEP (global ecological performance) was often worse than that of fossil fuels. One measure of this indicator uses the Swiss Ecological

* Tel./fax: þ41 216932863. E-mail address: [email protected] 0360-5442/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/

Scarcity method (UBP) [13], which accounts for the following impact categories: deposited waste; emissions into the air, top soil, surface water, and ground water; depletion of nonrenewable energy resources; and the use of other natural resources such as land. Zah et al. [34] analysed the LCA (life cycle assessment) of various biofuels pathways in the context of imports to Switzerland, and found poor performance for most first generation biofuels. The development of second generation biofuels is still in the pilot or demonstration stage. These biofuels are perceived more positively, as their production only competes with food and feed production in a limited fashion, especially if agricultural or forest waste products are used. However, relying on waste products for large-scale production is very challenging due to expensive logistics. Furthermore, dedicated crops would induce long-term land use change, which causes potential indirect competition with food production. For these reasons, the contribution of biofuels to transportation in the long term should remain limited to a reasonable percentage. Depending on the scenario, the market share of biofuels within the global transportation sector would be in the range of 15e23% by 2050, according to the OECD’s Energy technology perspectives [10]. This limited percentage of biofuels should be based only on sustainable pathways. This paper investigates the concept of sustainability as it applies to biofuels policies. Policy and market instruments such as certification and labelling are reviewed. Finally, a model for assessing the sustainability of biofuels is proposed and illustrated.


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2. The concept of sustainability and its application to biofuels 2.1. The concept and measurements of sustainability The concept of sustainability is derived from “sustainable development,” defined in 1987 by the Brundtland Commission as “development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs” [5]. There have been several attempts to measure sustainability at different levels, i.e., within international and national policy, production systems, or products. Most earlier work included sets of indicators to benchmark different countries or policies; a review of existing indicators at the country level is provided in a United Nations’ technical report (2008). As an example, the European Commission endorsed a set of 133 indicators that are distributed among several themes, including: socioeconomic development, demographic changes, public health, climate change and energy, sustainable transport, natural resources, global partnership, and good governance. The concept of a SIA (sustainability impact assessment) has been established in regard to policy monitoring. Arbter [2], using as a basis several works such as UK DETR [31], Verheem [33], and George [17], defined the SIA as “a systematic and iterative process for the ex-ante assessment of the likely economic, social and environmental impacts of policies, plans, programmes and strategic projects which is undertaken during the preparation of the above and where the stakeholders concerned participate pro-actively. The main aim is to improve the performance of the strategies by enhancing positive effects, mitigating negative ones and avoiding the transfer of negative impacts to future generations”. Theoretically, the SIA has extended the concept of the SEA (strategic environmental assessment) to include the additional dimensions of sustainable development. Practically, these impact assessments are very similar, as the SEA has previously been extended to include social and economic dimensions in many countries. A third type of assessment is RIA (regulatory impact assessment). While the SIA investigates the impacts of various policy options on the economy, society, and the environment, the scope of the RIA covers the possible impact of a projected regulation. Several previous reports have proposed measurements at a production system or product level. Belcher et al. [4] simulated the sustainability of an agri-ecosystem using a SD (System Dynamics) model; other recent papers on sustainable agriculture include Aerni [1], Meul et al. [22], and Partidário et al. [24]. Schmidt [27] used an LCA to propose a PSI (Product Sustainability Index) which was used to monitor the sustainability of the Ford Company at the vehicle level. The index included eight indicators, and the performance of different vehicle models was represented in a radar diagram showing sustainability strengths and weaknesses. Other papers, e.g., Evans et al. [12], Patlitzianas et al. [25], and Karger and Hennings [21], also have been devoted to sustainable energy. 2.2. Application to biofuels The production of biofuels worldwide has increased rapidly during the last decade. In 2008, the world production of bioethanol was estimated to be about 69 billion litres, 90% of which was from the US (35 billion litres, primarily from corn) and Brazil (27 billion litres, primarily from sugarcane). The worldwide production of biodiesel was approximately 14.8 billion litres in 2008; the top producers were Germany (21%) and the US (18%). Biofuels are promoted in most industrialized countries for improving energy security and reducing (GHG) emissions. In 2009, the European Union (EU) set a compulsory target of 10% market share by 2020 for renewable transportation fuels. In the US, the

new administration also defined a biofuels policy that strongly supports domestic corn growers. As the US is the dominant exporter of corn, there is a concern that this policy will lead to high cereal prices in the medium-to-long term, and may foster more agricultural development in other countries. A similar effect is foreseen as a consequence of the biofuels policy in the EU, where limited available land and high production costs favours the importation of biofuels. Brazil is seeking to exports its biofuels to the US and to other countries in the medium-to-long term. With the anticipated increasing demand for biofuels in industrialized countries, several developing countries plan to use this opportunity to develop activity in rural areas, increase national income, and reduce poverty. However, the rapid increase of biofuels production worldwide has only been possible because of subsidies, excise exemptions, and other incentives from public authorities. Thus, one of the issues regarding the sustainability assessment of biofuels is whether the anticipated sustainability advantages merit these existing and projected public expenditures. The advantages themselves are controversial, with uncertainties over the life cycle emissions of GHG, possible deforestation for feedstock production, degradation of soil and air quality, increased water consumption, possible loss of biodiversity, possible competition with food production, and other potential social imbalances. Due to the multi-dimensional impact of biofuels, the sustainability impact assessment of policies is as relevant as the sustainability assessment of production pathways and regulatory impact assessment. Garcia and Vianna [16] investigated the Brazilian Biodiesel Policy from social and environmental points of view. The following themes were considered within the social dimension: the social inclusion of family farmers, regional development, and food security. Environmental themes included the carbon and energy balances of biodiesel, the promotion of sustainable agricultural practises, and feedstocks diversity. Silalertruksa and Gheewala [28] assessed the environmental sustainability of four existing ethanol plants in Thailand based on their net energy ratio portfolio and an LCA. They found significant variability among the plants even if the same feedstock was used. Delzeit and Holm-Müller [8] proposed criteria for certifying bioethanol in Brazil. From an initial list of 127 criteria, they based a successive filtering process on theory, relevance for users, and verifiability. The result of that process was a set of questions to be answered by the certifiers in the field. In the present paper, we focus on the sustainability impact assessment of biofuels for the purpose of certification or labelling. Several certification initiatives exist in agriculture, e.g., certification promoted by the Sustainable Agriculture Network [29] and Forest Stewardship [15]. The specificity of biofuels is due to its hybrid nature. Biofuels’ pathways include several successive segments over the fuels’ life cycle: (1) feedstock production, (2) conversion of the feedstock to biofuels, (3) wholesale trade, (4) retail, and (5) use of biofuels in engines. The multiple actors involved include the feedstock suppliers, biofuels producers, biofuels consumers who may partly buy biofuels produced abroad, and public authorities who regulate the sector and design and implement policy instruments for promoting sustainable biofuels. The length and complexity of the biofuel supply chains make the sustainability issue very challenging. 3. Initiatives for certification or labelling of biofuels 3.1. Initiatives for certification Public incentives promoting biofuels must focus on a number of sustainability conditions. Gnansounou et al. [18] reviewed several initiatives that defined criteria for biofuels sustainability, and Van

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Dam et al. [32] provided an overview of sustainable biomass certification. In 2007, the Netherlands established criteria for sustainable biomass based on the work of Cramer et al. [6]. Similar to this Dutch initiative, a certification scheme in the United Kingdom (UK) provided criteria for “carbon and sustainability certification” using the framework of “RTFO (Renewable Transport Fuel Obligation)”. Within this latter framework, Bauen et al. [3] proposed a carbon reporting scheme, Dehue [7] investigated sustainability reporting, and Tipper et al. [30] drafted environmental standards for the UK. The official version of the regulation was published in 2008 by the Renewable Fuels Agency [26]. On 23 April 2009, the EU [11] adopted the directives related to the ClimateeEnergy package, in which the sustainability criteria were used to determine the eligibility of biofuels for 10% compulsory market share by 2020. However, it was not the intention to design a unique European certification scheme. In Germany, an “(International Sustainability & Carbon Certification) e ISCC” was initiated with the objective of developing a certification system for biomass and bioenergy [20]. Despite the objective of providing clear signals to consumers and encouraging them to purchase only sustainable biofuels, paradoxically, the result may have been paralysis of the market due to a lack of consistency between those numerous initiatives. With public resistance to the development of biomass-derived fuels on a wide scale, even sustainable biofuels suffer from a general adverse perception. In that context, each country is developing its own sustainability principles and criteria, as well as its own certification scheme. Although the principles are often similar, the requirements change from one country to the next. 3.2. Biofuels labelling initiative The separate sustainability and certification initiatives on the biofuels market may contribute to an increase in transaction costs if no consistency measures are taken. As an example, to reach the minimum target of GHG emissions reduction, the following requirements have been imposed in different regulations: UK (40% in 2008, 45% in 2009, 50% in 2010); Germany (30% in 2009, 40% in 2011); the Netherlands (30% in 2009); the EU (35% in 2013, 50% in 2017, and 60% from 2018 for new plants in service from 2017); and Switzerland (40% in 2008). To cope with this range of requirements, an initiative for labeling European biofuels (ethaStar for bioethanol and fameStar for biodiesel) was launched by the BPE (Bioenergy and Energy Planning Research unit) of the Swiss Federal Institute of Technology (EPFL), in collaboration with Swiss private companies. The objective of “etha/fame STAR” is to increase the visibility of high-level sustainable biofuels and to promote stakeholder awareness of the high sustainability quality of the labeled biofuels. The definition of sustainability within this labeling initiative is based on four dimensions: technical, environmental, social, and economic. The technical dimension within the labeling framework relates to compliance with the European standards regarding the quality of fuels, i.e., EN15376 for bioethanol and EN14214 for biodiesel. These standards will be updated as the regulations progress further, such as the possible development of an international standard (ISO) for liquid biofuels. The environmental dimension comprises the following items: GHG emissions, global ecological performance, conservation of energy resources (use of renewable energy), rational life-cycle water use, effect on soil quality, conservation of biodiversity, use of agricultural chemicals, and the practice of slash and burn. Finally, the socio-economic dimensions include issues such as: competition with food and feed, contribution to local well being, and the quality of working conditions.


The label will comply with all existing biofuels sustainability standards in the EU and Switzerland, with approval sought by the EU, UK, the Netherlands, and Swiss authorities. The investigation of the compliance of a given product with the requirements of this label requires the use of various assessments and decisions based on globalSP (sustainability performance). However, assessing this SP indicator is not straightforward. In this paper, a logic-based model is proposed with the goal of helping assessors implement their evaluation in a transparent and effective way. 4. The logic based model 4.1. Methodology The problem investigated here can be formulated as follows: given a biofuel produced according to a given pathway and used in a given way, what is its sustainability performance according to the etha/fame Star label? This performance is called its SLSP (Star-LabelSustainability-Performance). Sustainability indicators are often assessed and represented in a radar diagram, allowing the visualisation of the product’s sustainability profile. Sometimes, theWMV (Weighted Mean Value) is calculated to estimate a quantitative aggregate index. The LBM (Logic-Based Model) that is proposed in this paper differs from an arithmetic aggregation, such as the WMV, by the following aspects: (1) compensation between the various dimensions is significantly limited; (2) qualitative dimensions of the sustainability concept are considered; (3) indicators are organized into three hierarchical classes depending on their specificity levels; (4) specific indicators are used to define the meaning of general indicators; and (5) the most general variable (SLSP) is defined through a logic path. 4.2. Definition The SLSP is qualitative in the sense that each of its values can represent many different specific situations. For this reason, it is worth tracing the logic pathway that relates a value of the SLSP to a given biofuel. This is done by defining the determinants of the SLSP. Then for each determinant, a set of general indicators is defined and used as explanation variables. A determinant is a variable such as “Environmental Performance”, “Social Performance”, or “Economic Performance”. This kind of variable has a certain level of generality, making it necessary to use indicators to narrow down its definition. The values of a determinant are only qualitative. General indicators are used to define the determinants, and they can take both quantitative and qualitative values. For example, the general indicators related to the determinant “Environmental Performance” can be: “integration within the local environment”, “effect on the local environment”, or “effect on the global environment”. As most of these indicators remain general, specific indicators are required to define them more precisely. Besides having qualitative values, a specific indicator must be related to quantitative values. For example, the specific indicators “net GHG emissions reduction” and “net non-renewable energy use” can be related to the general indicator “Effect on the global environment”. The quantitative values, which are related to the specific indicators (i.e., support data), are then discretized into qualitative values. The term “variable” refers to determinants, general indicators, and specific indicators. The qualitative value of a variable is expressed in linguistic terms that characterise a level of performance, for example: low, medium, or high. Each linguistic value is related to a numeric value, such as 1 (low); 2 (medium); or 3 (high). These numbers are used to evaluate


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Table 1 Determinants and general indicators within the pilot knowledge base. Determinant

General indicators 1



D1 Economic performance D2 Social performance D3

D1.1 Integration to local economy D2.1 Social control

D1.2 Competitiveness D2.2 Working conditions D3.1 Integration to local environment


Environmental performance

e D3.2 Effects on local environment

D3.3 Effects on global environment

the distance between combinations of qualitative values derived from various variables. In the proposed model, the distance to the worst combination is used as a similarity measurement to match combinations of the qualitative values of the explaining variables with qualitative values of the explained variable. This matching function can be tuned manually should semantic inconsistency be detected. The final match represents a consistent rule base. 4.3. Development of the LBM The development of the LBM requires the identification and selection of the determinants, general indicators, and specific indicators, and the construction of the matching function. The technical dimension demands strict compliance with the standards; thus, the related criterion is a veto. The knowledge base considers exclusively economic, social, and environmental dimensions. Within these dimensions, requirements such as the GHG reduction target or the global ecological performance also induce veto criteria. 4.4. Elaboration of a pilot version Three determinants and seven general indicators have been proposed in the pilot version of the knowledge base (Table 1), and twenty specific indicators were defined (Table 2). The result is 243 rules describing the relations between the specific indicators and the general indicators, the general indicators and the determinants, and the determinants and the SLSP. 4.4.1. Economic performance (D1) A concept underlying Economic Performance is that biofuels should increase the well being of the local population. The

geographic proximity of the value chain between the feedstock producers and the biofuels consumers is considered to be a favourable condition for fulfilling this objective. Another idea is that a biofuel should tend to competitiveness. To implement this, a strong reliance on public incentives was penalised. Two general indicators are used to describe D1. The integration of the value chain with the local economy (D1.1) accounts for the possible direct, indirect, and induced economic effects at local level. It is described using the geographic proximity between feedstock producers and biofuels producers (D1.1.1), the persistency of the feedstock economic viability (D1.1.2), and the persistency of the economic viability of biofuels production (D1.1.3). The two latter specific indicators address the economic reliability of the pathway’s segments over the long term. The second general indicator (D1.2) addresses competitiveness issues and is described by three specific indicators. D1.2.1 considers the competitiveness of the feedstock production segment, including the following aspects: possible direct competition between various uses of the feedstock, possible direct competition among different cultures for agricultural land use, and possible indirect competition for various land uses. High feedstock prices increase the production cost of biofuels. Depending on the characteristics of the pathways, the prices of fossil oil, and the level of public incentives, a higher price for feedstock may make biofuels uncompetitive. D1.2.2 refers specifically to the incentive schemes. In several cases, the incentives are provisional and might decrease over time to encourage gains in productivity. Otherwise, the high production cost of biofuels might be hidden for years by public incentives, thereby becoming a hurdle when the incentives diminish. Finally, competitiveness at retail market. (D1.2.3) is made to be dependent on other competitors’ products and on fossil oil prices. As the latter are very volatile, incentives such as a fixed tax exemption may become insufficient when fossil oil market prices are low. 4.4.2. Social performance (D2) Social performance comprises the following aspects: priority to food and feed e the production of biofuels should not reduce food security; respect for land rights, in particular the land rights of small farmers; local control of seeds e local farmers should not become dependent on big companies for seed procurement; and conformity at least with ILO’s regulations related to working conditions e the work process should be sufficiently comfortable and the health and safety of workers should be frequently monitored. Several tools exist for determining Corporate Social

Table 2 Specific indicators within the pilot knowledge base. Specific indicators

D1 economic performance D1.1 Integration to local economy D1.2 Competiveness D2 social performance D2.1 Social control D2.2 Working conditions D3 environmental performance D3.1 Integration to local environment D3.2 Effects on the local environment D3.3 Effects on global environment




D1.1.1 Geographic closeness between feedstock producers and biofuels producers D1.2.1 Competitiveness of the feedstock production

D1.1.2 Persistency of the feedstock economic viability D1.2.2 Competiveness of the biofuels production

D1.1.3 Persistency of the economic viability of the biofuels production D1.2.3 Competitiveness of the biofuels on fuels retail market

D2.1.1 Priority to food and feed D2.2.1 Conformity at least with the ILO regulations

D2.1.2 Respect of the land rights D2.2.2 Comfort of the work process

D2.1.3 Local control of seeds D2.2.3 Monitoring of the health and safety of the workers

D3.1.1 Integration to the landscape D3.2.1 Acidification D3.3.1 Reduction of the GHG emissions

D3.1.2 Local land use and biodiversity D3.2.2 Eutrophication D3.3.2 Net non-renewable energy use

D3.1.3 Rational use of water D3.2.3 Air quality e

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Responsibility, such as the Social Accountability Standard 8000 (SA 8000) and the ISO 26000 under discussion. The Global Reporting Initiative [19] provides guidelines for corporate reporting. Within the pilot LBM knowledge base, two general indicators describe social performance. Social control (D2.1) addresses the ability of the local communities to retain control on food security (D2.1.1), land rights (D2.1.2), and seeds (D2.1.3). Working conditions (D2.2) are described by three specific indicators: compliance with ILO regulations or more stringent local regulations if any (D2.2.1), comfort of the working conditions (D2.2.2), and finally, support of the health and safety of the workers (D2.2.3). 4.4.3. Environmental performance (D3) Eight indicators are considered for environmental performance. For instance, the production of both feedstock and biofuels should be suitably integrated within the landscape; and local land use should not be significantly affected, i.e., natural ecosystems and protected areas must be preserved. The other indicators are acidification, eutrophication, air quality, reduction of GHG emissions, rational use of water, and net non-renewable energy use. These latter indicators are estimated using an LCA based on support data submitted by the applicants, as well as on the ecoinvent Life cycle inventory database presented in Frischknecht et al. [14]. The ecological scarcity life cycle impact (UBP) within the LCA is used to evaluate compliance with Swiss regulations defining minimum requirements for a positive ecological balance. In the pilot version of the LBM, D3 is described using three general indicators. Integration with the local environment (D3.1) covers issues such as preservation of the landscape (D3.1.1), biodiversity and local land use concerns (D3.1.2), and the rational use of natural resources, particularly water resources (D3.1.3). The second general indicator (D3.2) addresses effects on the local environment, namely waste deposits, and the pollution of air, top soil, and surface and ground water. Impact classes can then be defined, such as acidification (D3.2.1), eutrophication (D3.2.2), and air quality (D3.2.3). Finally, the third general indicator (D3.3) is related to effects on the global environment, such as global warming (D3.3.1) and the use of nonrenewable energy (D3.3.2). 4.4.4. Rule-base Rules are used to define each value of a given variable by appropriate combinations of lower-level explanation variables. As an example, consider the determinant D3 (presented in Table 3), whose values are defined through 27 rules that are based on combinations of the values of the three general indicators, each of which has three possible values. The following procedure is used to define the qualitative value of each combination of the general indicators’ values: first, the distance to the worst combination (D3.1 ¼ 1; D3.2 ¼ 1; D3.3 ¼ 1) is estimated using a qualitative similarity matching function; a short distance to the worst combination is interpreted as a low performance of D3. Next, manual tuning of the rule base is allowed provided that the consistency of the rule base is preserved. Table 3 illustrates manual changes to the rule base that impose a veto on low values of D3.1 and D3.3: if D3.1 ¼ 1 or D3.3 ¼ 1, then D3 ¼ 1 independently of the values of D3.2. These rules are defined to reflect the requirement of the etha/fame STAR label. For example, a minimum target required by the etha/fame STAR label is a 50% reduction of GHG emissions from the biofuel compared with emissions from the corresponding fossil fuel (gasoline or diesel). Thus, D3.3 ¼ 1 for any biofuel that does not comply with this requirement. In the same way, each general indicator can be defined using combinations of values for its specific indicators. Finally, the values of the SLSP are deduced from combinations of values from the determinants (D1, D2, D3).


Table 3 Rules using the qualitative values of the general indicators to define the qualitative values of a determinant, in the case of D3. No of the rule




D3 environmental performance

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3

1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3

1 1 1 2 2 2 3 3 3 1 1 1 2 2 2 3 3 3 1 1 1 2 2 2 3 3 3

1 1 1 1 2 2 1 2 2 1 1 1 2 2 3 1 3 3 1 1 1 1 3 3 1 3 3

1: low performance; 2: medium performance; 3: high performance.

4.5. Use of the LBM The actual use of the LBM within the etha/fame STAR labelling is more complex than the pilot version presented here. Three actors are involved in the process. Producer, trader, supplier, or end-user applicants submit a request to the label committee. The request includes a file with all support data listed in a template. The data are verified by an independent controller. The evaluation by the label committee comprises several steps (Fig. 1) that account for compliance with the regulations of the countries and the regions covered by the label, i.e., EU (especially UK, the Netherlands), and/ or Switzerland. A pre-evaluation step investigates compliance with GHG emissions targets and the global ecological performance (UBP) target as required by Swiss regulations. A simplified version of the LCA, available online, is used for this step. If the product complies with the GHG emissions target of the etha/fame STAR label and the Swiss UBP target, then the procedure continues; otherwise, recommendations are made so the applicant can take actions to improve performance and reapply. At the beginning of the second step, control & evaluation, the submitted product must be compliant with the etha/fame STAR GHG and Swiss UBP targets. Then, the support data are verified onsite as far as the technical, social, economic, and environmental criteria. The controller reports to the label committee for a detailed evaluation based on the verification of the support data. Compliance with the technical criteria is evaluated first, and if the results are positive, then a detailed LCA is performed for the environmental assessment; other tools are used to assess the economic and social criteria. The results are used to evaluate the specific indicators, and proceeding with the rule base of the LBM, then evaluate the SLSP of the product. Once the label is granted, within a period of two years the controller performs a random verification of the support data and undertakes new evaluations of the compliance, using various models and tools including the LBM.


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Fig. 1. The etha/fame label; procedure of label accreditation. Source: ENERS [9].

In the case of non-compliance during the monitoring process, the applicant is invited to immediately perform the recommended improvements. If the results after these actions are not satisfactory, the label is removed and the applicant is obliged to follow the full accreditation procedure to reinstate it. 4.6. Illustration

is to be distributed over an average distance of 250 km (100 km by lorry and 150 km by train). The cultivation of wheat would occur using typical agricultural practices, reputed to be good. The average yield is 6.425 t/ha of grains (fresh matter at 15% wt. moisture), and 3.915 t/ha of straw (fresh matter at 15% wt. moisture). The grains would be sent to the ethanol plant over a distance of 50 km (10 km by tractor and 40 km by lorry).

4.6.1. Case study A A bioethanol plant in a European country was ex-ante analysed based on production using wheat, in a facility with a capacity of 40,000 t/yr (i.e., 134,000 t/yr of wheat). The agricultural area was of the order of 20,900 ha and was located in a region near the future site of the ethanol plant. The plant would also produce about 48,600 t/yr of DDGS to be sold on the local market. The ethanol fuel

4.6.2. Pre-evaluation step A simplified LCA was performed using the support data submitted by the applicant. It showed that the product does not comply with the GHG emission reduction target required by the etha/fame STAR label. Recommendations were made to the applicant, who then devised a new pathway for the second step of the procedure. The main change was made to the feedstock, now

E. Gnansounou / Energy 36 (2011) 2089e2096 Table 4 Assessment of the specific indicators. Specific indicators

D1 economic performance D1.1 Integration to local economy D1.2 Competiveness D2 social performance D2.1 Social control D2.2 Working conditions D3 environmental performance D3.1 Integration to local environment D3.2 Effects on the local environment D3.3 Effects on global environment




D1.1.1 ¼ 3 D1.2.1 ¼ 3

D1.1.2 ¼ 2 D1.2.2 ¼ 2

D1.1.3 ¼ 2 D1.2.3 ¼ 2

D2.1.1 ¼ 2 D2.2.1 ¼ 3

D2.1.2 ¼ 3 D2.2.2 ¼ 3

D2.1.3 ¼ 3 D2.2.3 ¼ 3

D3.1.1 ¼ 3 D3.2.1 ¼ 2 D3.3.1 ¼ 3

D3.1.2 ¼ 3 D3.2.2 ¼ 2 D3.3.2 ¼ 3

D3.1.3 ¼ 3 D3.2.3 ¼ 3

Performance: 1 ¼ low, 2 ¼ medium, 3 ¼ high.


international trade agreements such as those of the World Trade Organization (WTO). The LBM presented in this paper illustrates how this tool can be used for selecting sustainable biofuels. The LBM is being extended for use in an effective expert system. Knowledge-based systems are particularly suitable for sustainability assessment, and the model described in this paper can be applied to any problem where an object is characterised by qualitative or quantitative indicators. The main strengths of the LBM are its transparency, simplicity, and possibly low compensatory property (e.g., use of veto rules). Its main weakness is its hierarchical form which assumes independency between the indicators. However, after it is extended to a full expert system, additional consistency rules in the knowledge base will be used to eliminate non-compatible combinations. It will also be possible to consider other relevant values’ combinations of indicators that belong to disjointed branches within the LBM.

composed of damaged grains of cereals (wheat, triticale, and barley). Acknowledgement 4.6.3. Case study B The pre-evaluation of the new ethanol pathway gave positive results for both GHG emissions and the global ecological performance. Next, an in-depth control & evaluation was performed. The onsite control of the support data was positive, and the specific indicators were then assessed (Table 4). 4.6.4. Evaluation of the economic performance The project was considered profitable to the local economy; however, the long-term economic viability of the feedstock was rated medium, as future availability of the resource is uncertain. The estimated production cost of 0.50e0.60 V/litre embedded a high uncertainty due to the short-term nature of the feedstock procurement contract and the high share of that segment in the production cost. These limitations are to be further monitored. 4.6.5. Evaluation of the social performance The working conditions were rated high due to the quality of life in the country and the high mechanisation of agriculture. The competition with food and feed was considered by the evaluators to be low, since the feedstock is rated as a residue (waste product). 4.6.6. Assessment of the environmental performance The integration within the local environment was evaluated through anEIA (Environmental Impact Assessment), which concluded a high performance. The effects on the local environment and the effects on the global environment were then evaluated using a detailed LCA. Both were rated high; the reduction of GHG emissions exceeded the threshold of 50% required by the etha/ fame STAR. The application of the rule base resulted in the highest values of general indicators and determinants. Finally, the value of the SLSP was maximized. 5. Conclusion The world’s energy sources will be influenced by various challenges, such as depletion of fossil energy resources and the response to global warming. The demand for energy in emerging economies and developing countries is accelerating rapidly. In addition to efforts to increase energy efficiency and enhance the rational use of energy, it is necessary to consider substitute fuels to replace fossil sources. Sustainable biofuels are part of the solution. By using various instruments and combining public incentives with market instruments such as labels, it is possible to discriminate among non-sustainable biofuels while complying with

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