Review of existing frameworks and tools for developing eco-efficiency indicators

Transcription

1 Meso-level eco-efficiency indicators to assess technologies and their uptake in water use sectors Collaborative project, Grant Agreement No: Deliverable 1.4 Review of existing frameworks and tools for developing eco-efficiency indicators 11 August 2012

2 DOCUMENT INFORMATION Project Project acronym Project full title EcoWater Grant agreement no Funding scheme Meso-level eco-efficiency indicators to assess technologies and their uptake in water use sectors Collaborative Project Project start date 01/11/2011 Project duration Call topic Project web-site Document Deliverable number D1.4 Deliverable title 36 months Due date of deliverable 30 April 2012 Actual submission date 11 August 2012 Editor(s) Author(s) Reviewer(s) Work Package no. Work Package title Work Package Leader Dissemination level ENV : Development of eco-efficiency meso-level indicators for technology assessment Review of existing frameworks and tools for developing eco-efficiency indicators Elina Manoli Vassilis Kourentzis Dionysis Assimacopoulos WP1 Frameworks and tools for meso-level eco-efficiency analysis and technology assessment National Technical University of Athens (NTUA) PU Version 8.0 Draft/Final Final No of pages (including cover) 97 Keywords Eco-efficiency, methodologies, software tools, review, recommendations D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 2 of 97

3 Abstract Deliverable 1.4 is a review of existing frameworks and tools developed and used for eco-efficiency analysis and assessment. The review aims at providing insight for the development of the EcoWater environmental and economic assessment tools, the Systemic Environmental Analysis Tool - SEAT, and the Economic Value chain Analysis Tool EVAT, respectively. It is structured in two Parts. Part A (Chapters 2 and 3) focuses on analysis frameworks that can be considered most relevant to the EcoWater objectives. These include: (i) the OECD Sustainable Manufacturing Toolkit, (ii) the LCA guidelines and mostly LCIA, (iii) the Sustainability Quantification Methods developed by the BASF chemical company, and particularly the BASF eco-efficiency analysis methodology, (iv) the Material Flow Analysis (MFA), and (v) the System Dynamics Modeling methods. The review of these methods/frameworks provides the basis for selecting and evaluating existing software tools, which can support their implementation. Most importantly, it provides insight about the methods that the EcoWater software tools can implement. Part B of the review (Chapter 4) focuses on the description of software tools, which implement the methods identified as most relevant in Part A. Part B focuses on underpinning the methods, characteristics and functionalities which can be integrated in the EcoWater tools, by assessing popular software packages on the basis of six main criteria: (i) integration and reusability of components; (ii) flexibility and adaptability to various case studies, (iii) ease of use, (iv) characteristics and presentation of output results, (v) cost of using the tool, and (vi) relevance to EcoWater. Based on the review undertaken in Part A, the methodology frameworks identified as most suitable for environmental analysis in EcoWater are MFA and LCA. Consequently, Part B focuses on reviewing the GaBi, STAN, TEAM, SimaPro and Umberto tools which can support the implementation of the methodologies considered most appropriate. For value-based economic analysis, Part B focuses on reviewing the WaterStrategyMan Decision Support System, which integrates hydroeconomic modelling concepts, and the SWITCH City Water Economics Model, which analyses interrelations among actors in water value chains. The review of Part B leads to the selection of functions and features that could be embedded in the EcoWater tools, and particularly the SEAT and the EVAT. These will be further integrated in the web-based EcoWater ToolBox. The ToolBox will act as the interface between SEAT and EVAT, combining environmental and economic analyses results to assess eco-efficiency and allow the cross-evaluation of alternative technological configurations and scenarios for their implementation. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 3 of 97

4 Contents 1 Introduction The EcoWater framework The EcoWater tools Purpose and objectives of the review of existing frameworks and tools Structure of the review Review of analysis methods and frameworks Overview The Material Flow Analysis (MFA) method Introduction Methodology overview Relevance to EcoWater The OECD Sustainable Manufacturing Toolkit Introduction Methodology overview Relevance to EcoWater Life Cycle Assessment (LCA) guidelines The Life Cycle Impact Assessment (LCIA) framework Relevance of LCA and LCIA to EcoWater The BASF Sustainability Quantification Methods The BASF Eco-Efficiency Analysis method The BASF SEEBALANCE method The BASF AgBalance method for measuring sustainability in agriculture Relevance of the BASF Sustainability Quantification Methods to EcoWater System Dynamics Modeling Overview Relevance of System Dynamics Modelling to EcoWater Discussion on reviewed methodology frameworks Review of existing analysis tools Introduction Tools relevant to Systemic Environmental Analysis Modeling GaBi STAN Software for SubSTance Flow Analysis TEAM TM 4.0 Tools for Environmental Analysis and Management SimaPro 7 (System for Integrated environmental Assessment of PROducts) Umberto Tools relevant to Economic Value Chain Analysis D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 4 of 97

5 4.3.1 WaterStrategyMan Decision Support System (WSM DSS) The SWITCH City Water Economics Model (CWE) Discussion and recommendations for the development of the EcoWater analysis tools The Systemic Environmental Analysis Tool SEAT The Economic Value chain Analysis Tool EVAT The functionality of the Toolbox Common Analysis Modules References Annex: List of existing environmental and economic analysis tools D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 5 of 97

6 List of Figures Figure 1: A schematic summary of the EcoWater analysis framework... 9 Figure 2: The concept of actors in EcoWater Figure 3: The EcoWater assessment framework Figure 4: The review process Figure 5: The EcoWater analytical framework, building on a synthesis of existing methodologies Figure 6: The MFA scheme (adapted from Hirschnitz-Garbers, 2012) Figure 7: An example of a Material Flow Network for paper production (Möller, 2010) Figure 8: The three stages of the manufacturing process (OECD, 2011) Figure 9: The OECD "Sustainable Manufacturing" Toolkit methodology (adapted from OECD, 2011) Figure 10: The "cradle to grave" approach of LCA (adapted from Woods and Jones, 1996) Figure 11: A simplified view of the midpoint impact categories: (a) Greenhouse effect, (b) Acidification potential and (c) Eutrophication potential (PE International, 2011). 25 Figure 12: The four phases of LCA and LCIA (adapted from Pennington et. al., 2004) Figure 13: Classification of impact categories for characterization modeling at midpoint and endpoint (Areas of Protection) levels (Source: JRC, European Platform on LCA) Figure 14: Schematic definition of EcoWater s system boundaries and value chains Figure 15: Potential methods for deriving weighting factors Figure 16: Example of the graphical presentation of combined impacts for all environmental impact categories (Source: BASF) Figure 17: Example of the Eco-Efficiency Portfolio (Source: BASF) Figure 18: The Eco-Efficiency Internet-Manager (Source: BASF) Figure 19: Example of a SEEBALANCE graph ( 34 Figure 20: The WorldWater causal diagram (Simonovic, 2003) Figure 21: Example of a system modelled in the STELLA ( 37 Figure 22: An example of a plan with processes and flows modelled in GaBi 4 (PE International, 2011) Figure 23: A snapshot of the STAN modeling environment (TU Wien website) Figure 24: Use of Layers and Periods in STAN (TU Wien website) Figure 25: A snapshot of the system editor (adapted from the Ecobilan Website) Figure 26: A simplified example of the specification value chain representation in TEAM (Siegenthaler et al., 2005) Figure 27: The SimaPro LCA Explorer (PRé Website) Figure 28: Diagram of the 4 subsystems for wastewater treatment (Callego et al., 2008) Figure 29: An example of value chain representation, showing the navigation and flow windows of SimaPro (PRé Website) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 6 of 97

7 Figure 30: Presentation of inventory results in (a) tabular form and(b) in graph form, (c) per process and impact category (PRé Website) Figure 31: Presentation of analysis results in the form of a single aggregate index (PRé Website) Figure 32: Default layout of Umberto s user s interface (IFU Hamburg, 2012) Figure 33: A simple example of system modeling in Umberto (IFU Hamburg, 2011) 64 Figure 34: Simple transition specification in Umberto, by using production coefficients (Wohlgemuth et al., 2006) Figure 35: Example of Umberto s system evaluation results, based on CO 2 emissions (IFU Hamburg Website) Figure 36: Visualization of Umberto s results in Sankey diagrams (IFU Hamburg Website) Figure 37: The CWE Case and Scenario analysis steps (NTUA, 2011) Figure 38: Economic instruments along the water cycle and the scope of the CWE (NTUA, 2011) Figure 39: Procedural view of the SEAT functionalities Figure 40: Components of the value of water (adapted from Rogers et al., 1996) Figure 41: Suggested Toolbox architecture Figure 42: The Common Analysis Modules and their interrelations with the SEAT and the EVAT Figure 43: Example of comparison of results through a spider chart (adapted from Michelsen, 2006) Figure 44: Graphical presentation of aggregate environmental impact and value added per stage (adapted from Michelsen, 2006) Figure 45: Example of comparison of the results through an overall eco-efficiency index (adapted from Michelsen, 2006) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 7 of 97

8 List of Tables Table 1: Catalogue of the OECD "Sustainable Manufacturing" Indicators (adapted from: OECD, 2011) Table 2: The AgBalance indicators (adapted from BASF) Table 3: Criteria for the assessment of existing tools Table 4: Indicators for the analysis of on-site urban water management options (NTUA, 2011) Table 5: List of existing tools D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 8 of 97

9 1 Introduction 1.1 The EcoWater framework EcoWater seeks to address the existing gap in eco-efficiency metrics, focusing on the development of meso-level eco-efficiency indicators for assessing the systemwide performance and impacts of innovative technologies. The Project objectives are achieved through the development of an analytical framework which will be tested and refined through 8 Case Studies focused on water service systems. The keywords that characterize the overall Project approach are: eco-efficiency, assessment, technologies, meso-level, value chains and interrelations among actors. The above terms denote the dimensions of the analytical approach that will be developed by the Project. Technologies will be assessed in a holistic way by utilizing a comprehensive set of eco-efficiency indicators. A technology inventory will be compiled, describing the main features (footprints, costs) of technology innovations to be tested through a number of Case Studies. Eco-efficiency Indicators will contrast resource usage and systemic environmental impact vs. activity levels and economic value added across the analyzed value chains, thus combining systemic environmental analysis and economic analysis at the meso-level. Furthermore, the analysis of value chains and of the interactions among actors would be also necessary for evaluating incentives and barriers for technology implementation, and for assessing uptake scenarios and their key drivers. All the above will be tested in the 8 EcoWater Case Studies, which concern different systems of water use, within the context of the generic system presented in Figure 1. Economic Assessment Total value of products and services related to water use Financial cost assessment Economic value added from water use (generated products and services) Financial cost assessment Water resource Abstraction Storage Treatment Distribution Water Use Collection Treatment Disposal Assessment of environmental impacts Assessment of environmental impacts Environmental Assessment 1. Aggregation to derive baseline indicators 2. Normalization and weighting to derive a composite index for comparison purposes Figure 1: A schematic summary of the EcoWater analysis framework D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 9 of 97

10 The motivation for analyzing water service systems is based on: The importance of water as input to most production processes, The significant environmental impact and costs entailed in making water suitable for different water-use purposes, The need for a holistic (system-wide) approach in assessing the performance of different water-related innovative technologies, and The fact that the uptake of water-related innovations remains regulatorydriven. It should be noted that eco-efficiency metrics are widely applied both at the microand at the macro-levels of analysis. However, at these levels, the eco-efficiency indicators cannot be used to analyze systemic changes. On the other hand, mesolevel assessments, which focus on the interconnection between the micro and the macro level, and address the dynamic behavior of product and service systems, can be used to analyze interdependencies and heterogeneity among different industries and actors; thus, meso-level eco-efficiency metrics can offer valuable information to support policies towards sustainable production and consumption. In the EcoWater concept, water is seen both as a product and as a resource entering the production chain of other products/services. By studying the corresponding value chains relating to both water production/supply and to products or services using water as input, as well as the interactions among the (economic) actors involved in these processes, EcoWater will seek to understand how technological changes in water service systems interrelate and influence the economic and environmental profile of water use in different sectors (Figure 2). Actor 1 (e.g. River Basin Agency) Actor 2 (e.g. Municipality) Actor 3 (e.g. Industry x) Water resource Abstraction Storage Treatment Distribution Water Use Treatment Disposal Figure 2: The concept of actors in EcoWater The assessment methodology (Figure 3) follows three steps: First, an assessment is performed with regard to the current (baseline) eco-efficiency levels. Then, alternative technologies, as well as regulatory, market and policy aspects, are assessed. Finally, the comparison of results from these assessments will provide information on the relative eco-efficiency improvement of the analysed systems, thus arriving at the best alternative configuration(s). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 10 of 97

11 Eco-efficiency assessment Present situation Technology & Innovation Scenarios Regulatory, market & policy aspects Future situation Eco-efficiency assessment Figure 3: The EcoWater assessment framework 1.2 The EcoWater tools In order to support the assessment framework of Figure 3, EcoWater will integrate existing and new tools and assessment methods in a coherent modelling environment. The modelling environment will support system-wide environmental and economic benchmarks of innovative technologies, considering impacts across the relevant value chains and interactions among the actors involved. To achieve this goal, a pair of new tools will be developed, which will perform environmental and economic analyses, and support the assessment of the environmental and the economic components of eco-efficiency. These tools are the Systemic Environmental Analysis Tool (SEAT) and the Economic Value chain Analysis Tool (EVAT). SEAT is described as a modelling environment for the quantification of ecoefficiency indicators, building on existing methods, models and tools. The tool will focus on the environmental component of eco-efficiency, with the following main functionalities: Development of a model representation of the analysed physical system; Description of the stages of the value chains and of their production processes; Analysis of the flow of resources per stage and process; and Assessment of environmental loads (emissions and generated waste). EVAT is described as a flexible tool to perform economic assessments across the analysed value chains. EVAT will focus on the economic component of the ecoefficiency indicators and on the analysis of potential distributional effects among the actors involved in the studied systems, with the following main functionalities: Representation of the water management system in terms of costs, benefits and interactions between actors, Provision of an overall estimation for the Value Added, Calculation of the financial costs and economic benefits incurred to individual actors, and D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 11 of 97

12 Analysis of scenario impacts, including the analysis of the value added, aggregated over the value chain, and of the impact of policy instruments. Both tools, together with additional computational and data analysis resources, will be integrated in the web-based EcoWater Toolbox. Based on their output, the ToolBox will estimate eco-efficiency indicators for a baseline scenario, and for different technology configurations. Furthermore, the Toolbox will support post- EcoWater extensions, potentially relating to new problem-oriented indicators and result presentation methods, for applying the methodology to other systems and products. 1.3 Purpose and objectives of the review of existing frameworks and tools The purpose of this review is to analyse existing frameworks and tools that can be applied for eco-efficiency assessment, thus providing a methodological framework for the development of the EcoWater environmental and economic assessment tools (SEAT and EVAT, respectively) and of the EcoWater ToolBox. The review will conclude with a set of recommendations for the development of the SEAT and the EVAT, and identify functionalities that can be embedded in their approach and interface. As such, the review has the objectives to: 1. Analyse existing frameworks and methodologies relevant to EcoWater, 2. Analyse well-established tools for environmental and economic assessment. Existing tools are selected according to their relevance and applicability to the EcoWater context and objectives, focusing on their methodology and usefulness for supporting meso-level analysis, eco-efficiency assessment and technology benchmarking. The review process is presented in Figure 4. Figure 4: The review process D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 12 of 97

13 1.4 Structure of the review The review is organized into two parts. Part A, Analysis of established methods and frameworks, includes Chapters 2 and 3, where: Chapter 2 concerns the review of the following frameworks and methodologies: (a) Material Flow Analysis (b) the OECD Sustainable Manufacturing Toolkit, (c) the LCA and LCIA framework, (d) the BASF analysis methods, and (e) System Dynamics Modelling, and Chapter 3 discusses findings and concludes on the methods most suitable for eco-efficiency analysis. Part B of the review focuses on existing tools that can support the frameworks and methodologies discussed in Part A. The review concerns the criteria mentioned above, and aims at highlighting the strengths and usefulness of the software tools, in order to derive recommendations for the development of the EcoWater tools. Part B is organized in the following way: Section 4.2 reviews software tools for systemic environmental impact analyses, and focuses on GaBi (v. 4), STAN, TEAM (version 4), SimaPro (version 7) and Umberto (version 5.5). Section 4.3 reviews software tools for the economic assessment of value chains, focusing on the WSM DSS and the SWITCH City Water Economics Model. Finally, Part B concludes with a discussion on recommendations for the development of the EcoWater tools and Toolbox. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 13 of 97

14 PART A

15 2 Review of analysis methods and frameworks 2.1 Overview A review of existing literature reveals that there are four (4) well-established analysis frameworks and guidelines, which can be considered most relevant to EcoWater. These include Material Flow Analysis (MFA), the OECD Sustainable Manufacturing Toolkit, the LCA guidelines and the Sustainability Quantification Methods developed by the BASF chemical company. Additionally, Systems Dynamics Modeling methods will also be described, since they could possibly be of use in situations where it is required to describe feedback mechanisms and socio-technical dynamics/interactions. This Chapter provides a brief description of the above methods, in order to highlight their specific features that can form the basis for the EcoWater analytical framework. The EcoWater analytical framework will be developed as a synthesis of elements from these existing frameworks with additional elements that are more specific to the EcoWater context, as illustrated in Figure 5. Figure 5: The EcoWater analytical framework, building on a synthesis of existing methodologies D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 15 of 97

16 2.2 The Material Flow Analysis (MFA) method Introduction Material Flow Analysis is a systems analysis methodology, described as the systematic assessment of the flows and stocks of materials within a system defined in space and time (Reisinger et al., 2009). MFA is used to measure the flow of materials in an economic region, a factory, a production process, or an industry (Hirschnitz-Garbers, 2012, p.11). The concept of MFA is based on the calculation of (mass) balances along a production process, including the extraction of resources and the corresponding emissions (Figure 6). This analysis can provide information on the resources used and their amount, which can lead to cost accounting and economic value estimations. Overall, MFA provides information at various levels of aggregation; hence, it allows for the development of targets, interventions and policy recommendations (Hirschnitz-Garbers, 2012). Figure 6: The MFA scheme (adapted from Hirschnitz-Garbers, 2012) In summary, the objectives of MFA (Reisinger et al., 2009) are to: Describe (i.e. model) systems of material flows and stocks, Provide the means to reduce the complexity of this description, while maintaining the basis for decision-making, Obtain a complete picture of the transition/conversion/extraction/metabolism of certain elements or substances within the scope of the system, Calculate and assess flows and stocks quantitatively, checking mass balances, sensitivities and uncertainties, Present system results (flows, stocks and their economic and environmental impacts) in a reproducible, understandable and transparent way. Results obtained through MFA can form the basis for the better management of resources, wastes and the environment, as they can be used to monitor possible environmental loads and design environmentally-beneficial goods, processes and systems Methodology overview MFA provides a systematic approach for modeling and evaluating all material and energy flows and stocks within a production system. The analysis can (and usually should) also cover the stocks and flows that are not addressed by financial accounting, such as waste flows, depletions, or stocks of obsolete products. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 16 of 97

17 Material Flow Analysis is based on the principle of balances. Mass balance, a concept very familiar in Chemical Engineering is a direct consequence of the basic physical principle of mass conservation. However, it is the extension the concept of balance to the more general idea of process balance that turns MFA into a powerful and versatile quantification method. The requirement for a balance to hold for each process enables to obtain a comprehensive view of the materials used, produced, and discarded within it. The selection of the balances to be analysed for any given system depends on the specific processes that are considered, and often on the goals of the analysis. For example, the analysis can refer to a chemical element (e.g. water), energy, total mass of materials or something even more abstract. Using MFA, production systems are modelled as Material Flow Networks, based on the concept of Petri nets (Reising, 1985). They consist of the following basic elements: Network nodes, which can be either transitions (usually symbolized by squares) or places (usually symbolized by circles), Arrows (or directed arcs), which connect the network nodes and describe which places are pre- and/or post- conditions for which transitions. Transitions represent the locations in the Material Flow Network where material and energy transformation processes take place. MFA studies can be refined through disaggregation or simplified through aggregation. Places represent storages where stocks are held and where conversions take place. Each transition is connected, through arrows/arcs, to places from where it is supplied with materials and energy (these are its inputs), and to places to which it provides materials (these are its outputs - Figure 7). Consequently, arrows (or arcs) can represent material and energy flows. Figure 7: An example of a Material Flow Network for paper production (Möller, 2010) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 17 of 97

18 In this way, an MFA model allows to graphically allocate measurements, statistical data or estimations in the form of stocks and flows that are related to certain processes in a given system at a certain time. It should be noted that the term material in MFA serves as an umbrella term for substances (meaning physical entities) and goods (meaning economic entities, i.e. entities having an economic value) (Brunner & Rechberger, Chapter 2.1.3). The difference between a Material Flow Network and a Petri net is that the system representation in the Material Flow Network is not used for running discreet simulation models. Instead, MFA networks can be interpreted as an accounting system, in the sense that they consider material and energy flows instead of financial flows. This accounting system is period oriented, and provides information on which material and energy flows occur in the period under review (e.g. a fiscal period) and how the opening inventory has changed after this period in terms of stocks (Möller, 2010). As such, MFA differs from other methodologies described in this Chapter (e.g. LCA), which are product (unit)-oriented. However, both methods offer different views of the same system, and the transition between them is rather easy. Complexities may arise in cases where there is stock accumulation/management and environmental impacts occurring outside the MFA analysis timeframe. Nonetheless, MFA can be (and frequently is) used as a basis for other analyses (e.g. LCA/LCIA, Cost Accounting, means-ends analysis). It is important to define the extent of the system by defining the system boundaries, as these significantly influence the total balances of flows. For converting the periodoriented view of MFA to the product-oriented view of LCA, the system boundaries of MFA must be extended to include the so-called pre-chains and post-chains, which concern the extraction of raw materials, the production of resources, their distribution, use and the disposal of waste. This extensibility is an important advantage of MFA over conventional cost-accounting methodologies, which use fixed system boundaries. This feature, together with the extensive use of process balances which is explained later on, is one of the features that make MFA particularly suitable for eco-efficiency analyses. The scale and scope of the system also need to be specified. The spatial scale is the geographical entity that is covered by the system. A system, representing a certain industrial sector, can concern a corporation, a country, a region or even the world as a whole. The temporal scale is the point in time or the time interval for which the system will be analysed. A system can represent a snapshot of flows and stocks at a certain point in time or at an interval, or it can include time series which describe the temporal evolution of the system variables. The material (scope) of the system is the actual physical entity which is quantified. The material can be a chemical element or a substance such as CO2. More general or composite concepts of materials can also be quantified (e.g. product, good, energy), provided that some kind of balance can be established. Flows and stocks in systems analyzed through MFA are quantified either by measurements or from statistical data. In any case, process balances have to be cross-checked to ensure the correctness of the quantification and to reveal possible data inconsistencies or even misconceptions resulting from the omission of a flow or D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 18 of 97

19 a process. This procedure, used in reverse order, can provide an efficient way to calculate unknown flows, (and, conditionally, stocks) from a few flows that have been measured or estimated. Consequently, the overall calculation algorithm aims at closing data gaps in the MFA network. If some flows, stocks and the production rules (i.e. the formal specifications of technical conversions between resources and product materials) are known, then unknown flows and stocks can be calculated by balancing each node (i.e. a transition, process or place) of the network. The calculation starts from nodes that have some known flows and/or stocks; it then moves outwards, to cover the whole network. Material and energy conversion can be done through simple conversion factors. However, the concept is open for extension towards the detailed engineering and modelling of production units. In this way, the whole MFA model behaves as a database which can be evaluated directly by retrieving absolute material and energy flows according to the time period (Möller, 2010). Thus, the result of this calculation is a system inventory transitions/conversions, flows and stocks Relevance to EcoWater It can easily be supported that MFA is of high relevance to EcoWater, since it can very well conform and support eco-efficiency analyses concepts. The fact that MFA provides a way to model the systems analyzed, so that they can be easily visualized and carefully checked process-by-process in order to identify the use of environmental resources and the production of emission and wastes, makes it a suitable methodology for eco-efficiency analysis. By establishing a comprehensive system inventory (database) of all flows, it is relatively easy to use it in order to estimate potential environmental impacts. Costs and values added along the production chains can also be estimated in a similar way. Moreover, through the submodelling of individual production processes into transition functions that model the conversion of input into output flows, MFA can offer a convenient mechanism for modelling alternative technology configurations and thus for (cross-)evaluating technology options. It also offers an efficient way to breakdown impacts, costs and values at the level of individual actors. Based on the above, the Material Flow Analysis framework will form the basis of the EcoWater analytical framework and tools. The other components of the EcoWater analytical framework will build upon the basis that MFA will provide, in order to perform a cost accounting and value added analysis on the MFA network and further estimate, assess and visualize eco-efficiency indicators for each technology option or scenario evaluated. 2.3 The OECD Sustainable Manufacturing Toolkit Introduction The OECD Toolkit is based on the concept of sustainable manufacturing, which is defined as the creation of manufactured products that use processes that minimize negative environmental impacts, conserve energy and natural resources, are safe for employees, communities, and consumers and are economically sound. The Toolkit D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 19 of 97

20 is aimed at the assessment of manufacturing facilities in terms of environmental performance, by providing internationally applicable, common and comparable indicators. It focuses on the environmental component of sustainability, providing a baseline for the improvement of the overall efficiency of various production processes. The Toolkit analysis framework is mostly applied to products and production processes at the plant or manufacturing facility level; however, its usefulness can be extended to any type and size of organization of production. By using the provided concepts and methods, small and medium-sized manufacturing organizations can identify improvements for their current environmental performance, and facilitate their sustainable development and green growth. The aim is to support the creation of environmentally responsible enterprises, motivating them towards the adoption of green manufacturing processes (e.g. low carbon technologies and strategies, water saving devices, installation of roof solar panels). The Toolkit includes 18 environmental quantitative indicators, which are formulated to potentially address all types of manufacturing, throughout the lifecycle of the products produced. As presented in Figure 8, indicators can be classified into three categories, each corresponding to their role and the stage in the production chain they apply to (OECD, 2011): Inputs concern the materials or intermediate products used in the manufacturing of a product; Operations correspond to the processes required to turn inputs into products, as well as to the activities necessary to operate the production processes (e.g. facility operation, transport of inputs and products); Products refer to the manufactured goods, including their use and their handling at the end of their lifetime. Figure 8: The three stages of the manufacturing process (OECD, 2011) Table 1 lists indicators according to the above categories. Indicators O1, O2 and O4 can be extended to measure the impacts associated both with the supply chain and the manufacturing facility (Lehni, 2000, p.8). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 20 of 97

21 Table 1: Catalogue of the OECD "Sustainable Manufacturing" Indicators (adapted from: OECD, 2011) Inputs Operations Products I1: Non-renewable materials intensity I2: Restricted substances intensity I3: Recycled/reused content O1: Water intensity P1: Recycled/reused content O2: Energy intensity P2: Recyclability O3: Renewable proportion of energy O4: Greenhouse gas intensity O5: Residuals intensity O6: Air releases intensity O7: Water releases intensity O8: Proportion of natural land P3: Renewable materials content P4: non-renewable materials intensity P5: Restricted substances content P6: Energy consumption intensity P7: Greenhouse gas emissions intensity Methodology overview The methodology supported by the OECD Sustainable Manufacturing Toolkit follows a 3-stage process ( Prepare, Measure and Improve ), and consists of a total of seven (7) steps (Figure 9). This sequential, step-to-step, approach is based on the definitions of the indicators listed in Table 1, in order to prepare and develop the measurements required for their estimation. Figure 9: The OECD "Sustainable Manufacturing" Toolkit methodology (adapted from OECD, 2011) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 21 of 97

22 The development of all seven steps is not necessarily a one-way route; instead, a cyclic process can be applied, so that some steps are revisited on a regular basis (e.g. yearly). In more detail, the seven steps are: Stage A Prepare 1. Mapping of impacts and setting of priorities: The step refers to the mapping of the impacts related to the organization s activities and is used to identify the activities affecting environmental performance the most, and to define objectives, review environmental performance and make decisions for prioritising actions. 2. Selection of useful performance indicators. The step concerns the identification of the most important indicators to monitor improvement, as well as the data required for their estimation. A subset of the 18 quantitative indicators, proposed by the OECD Toolkit, can be used, according to current organizational needs, goals and data availability, while additional indicators can be taken into consideration. Stage B Measure 3. Measurement of the inputs used in production: The step involves the identification and estimation of the influence of raw materials, components and intermediate products on environmental performance. 4. Assessment of the operations of the manufacturing facility: The step focuses on the impacts and the efficiency of operations within the facility (energy use intensity, greenhouse gas emissions, other emissions to air and water, etc.). Stage C Improve 5. Evaluation of the end-products: The step focuses on identifying and evaluating the factors that determine the sustainability performance of the final product, such as energy consumption in use, recyclability, use of hazardous substances, etc. 6. Understanding of the measured results: In this step, results from the estimated indicators and generated information are interpreted in order to understand performance trends, as well as the alternative options that are available. 7. Taking action to improve performance: The step involves the selection of the best alternative options to improve environmental performance, the setting of clear targets and the development of tangible action plans for their achievement Relevance to EcoWater The OECD Sustainable Manufacturing Toolkit focuses on environmental aspects in order to support the continuous improvement of the environmental performance of manufacturing activities. Despite the fact that this analysis framework, including the indicators proposed, can be useful for any size and type of organization and manufacturing activities, its main focus is on micro-level analysis. In order to use this framework in EcoWater, it would be necessary to extend the Toolkit to account for D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 22 of 97

23 meso-level system improvements, and towards the assessment of value added across extended value chains. Such an extension would primarily require the identification of a number of additional indicators, which could be applied throughout the value chain to provide guidance on actions to be taken for improving performance, and support the analysis of the dynamic environmental-economic interactions that constitute the meso-level focus. Nevertheless, the OECD Toolkit framework provides a solid basis to guide the development process of the EcoWater Case Studies. EcoWater Deliverable 1.8 (Roadmap for Case Study development) provides a stepwise methodology to be followed in each EcoWater Case Study, so that actions and measures can be proposed to improve the performance of each studied system. 2.4 Life Cycle Assessment (LCA) guidelines Life Cycle Assessment (LCA) is both a concept and a methodology used for the holistic evaluation of the environmental efficiency of products, activities and services. The methodology requires the quantification of all inputs (resources used) and outputs (waste, emissions) throughout the life cycle of a product or service, from the extraction of resources to the use of the product, and to waste disposal (EEA, 2012). Inputs and outputs are then aggregated to assess their contribution to various impact categories (JRC, 2010). LCA can be used as a decision-support tool, as it can facilitate the identification of environmental burdens and evaluate the environmental consequences of a product or service from cradle to grave (WBCSD). LCA is a powerful product management instrument, which expands the narrow focus from the impacts that result from the use of a product, to the full set of emissions, pollution, resource use, and generated waste, required to produce, use and dispose of the product (Hirschnitz-Garbers et al. 2012, p. 8). For this reason, the proper application of the LCA is data intensive and requires the compilation of complete system inventories (Hirschnitz-Garbers et al., 2012). According to ISO (1997), LCA comprises four (4) stages, which are briefly described below. Stage 1: Goal and Scope definition The definition of the goal and scope of an LCA application provides a description of the product system in terms of system boundaries and functional units. System boundaries should consider the full sequence of operations in a physical system, as these are required to provide the corresponding product or service (WBCSD). As per Figure 10, stages refer to (i) acquisition (extraction of resources) and processing of raw materials, (ii) manufacturing, (iii) use and (iv) recycling and end-of-life disposal, and should account for all distinct processes within each stage. The functional unit concept allows for the analysis and comparison of alternative goods or services. For example, alternative packaging types can be compared on the basis of 1 m³ of packed and delivered product. The amount of packaging material required, termed as the reference flow, can vary according to the selected packaging option (e.g. paper, plastic, metal, etc.). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 23 of 97

24 Industrial wastes Raw materials extraction Raw materials processing Resources Manufacturing Products Consumption - Use side Waste Waste management - Waste side Reuse Remanufacture Recycle Figure 10: The "cradle to grave" approach of LCA (adapted from Woods and Jones, 1996) Stage 2: Life Cycle Inventory (LCI) LCI is used for the estimation of the consumption of resources and of the waste and emissions attributable to a product s life cycle. Resource consumption and generation of waste/emissions are likely to occur: At multiple sites and regions, As different fractions of the total emissions at any site, At different life-cycle phases (e.g. use of a product vs. its disposal at the end of its life cycle), and Over different time periods within a life cycle phase. The results obtained at this stage include a list of the quantities of all resources used in a product s or service s life cycle (input-output balances). Subsequently, the corresponding product s or service s footprint is analysed with regard to its input and output flows from and to the environment respectively (Menoufi, 2011). Stage 3: Life Cycle Impact Assessment (LCIA) At this stage, an inventory is made for the categories of environmental impacts. The inventory provides the basis for the analysis of the impacts of wastes, emissions and resource extraction. Results of this analysis are derived over the life cycle of a product or service, and consider different potential impacts. The latter include midpoint impact categories (such as the greenhouse effect, acidification potential, eutrophication potential see Figure 11), and aggregate endpoint impact categories (impact on human health, natural environment, natural resources). The derived indicators describe the severity of the contribution of each impact category to the environment (Menoufi, 2011). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 24 of 97

25 (a) (b) (c) Figure 11: A simplified view of the midpoint impact categories: (a) Greenhouse effect, (b) Acidification potential and (c) Eutrophication potential (PE International, 2011) Stage 4: Life Cycle Interpretation At the last stage, LCA requires the examination of results from all previous stages. Although interpretations based only on the LCI can sometimes lead to a conclusion (e.g. if one alternative has a consistently higher consumption for each material/resource than any other alternative), Life Cycle Interpretation should provide further information for the comparison across impact categories. This information is particularly important in the case that there are trade-offs among product alternatives or prioritization of the areas of concern within a single life cycle study. Therefore, Life Cycle Interpretation should identify, quantify, check and finally evaluate the LCI and the LCIA results (UNEP, 2011). An example of the additional input that can be provided at this stage, concerns the case of CO 2 emissions, which may result to a higher climate change indicator in Alternative A than in Alternative B. However, Alternative B can involve the use of more pesticides than Alternative A, and thus contribute more to toxicological impacts. The selection of the best alternative depends on the prioritization of the impacts that a stakeholder is interested in. According to Pennington et al. (2004), these issues (although they may not always be necessary to be assessed) concern not only natural sciences but also social sciences and economics. In this way, a set of conclusions and recommendations can be generated in order to provide guidance for the decision-making process. Further verification of the results and their interpretation can be achieved through three (3) checks (Menoufi, 2011): A completeness check, to ensure that the identified environmental issues adequately represent the information of all stages, and that the overall objective of the study has been addressed. A set of sensitivity checks, to ensure that results and conclusions are not affected by uncertainties in data or in evaluation methods. Hence, all assumptions made need to be tested, in order to increase the confidence in the results. What if scenarios and simulations (e.g. Monte Carlo simulations) are two methods frequently used for sensitivity checks. A set of consistency checks, to ensure the consistency of methods, procedures and data used, based on their coherence with the goals of the study. Data sources and accuracy, geographical representation, system boundaries and assumptions can all be subject to consistency checks. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 25 of 97

26 The four stages of the LCA framework are illustrated in Figure 12, which also depicts the analysis of the (most relevant to EcoWater) LCIA stage into specific steps. LCIA is discussed in the section that follows. Figure 12: The four phases of LCA and LCIA (adapted from Pennington et. al., 2004) The Life Cycle Impact Assessment (LCIA) framework Life Cycle Impact Assessment, which is used at the third stage of the LCA to evaluate the potential impacts of input resources and of emissions/wastes is considered of particular relevance to EcoWater. LCIA links the life cycle ( from cradle to grave ) of the analyzed product or process with its potential environmental impacts. Primary impact categories used in LCIA address ecological and human health effects, and resource depletion. Results of the analysis cross-evaluate the environmental impacts of alternative options, indicating the product or process which contributes the most to each midpoint or endpoint category. LCIA is developed through four (4) steps (Figure 12), which are outlined below. Step 1: Selection of impact categories and classification (mandatory) The step involves the definition and classification of environmental impacts. The results on the elementary flows from LCI are assigned to environmental impact categories, according to their contribution to different environmental issues. The impact categories correspond to impacts caused by resource consumption and the emissions/wastes generated throughout a product s or service s life cycle (Menoufi, 2011). Impact categories are grouped into midpoint and endpoint (Areas of Protection AoP) categories, as illustrated in Figure 13. The three most commonly used AoPs concern human health, natural environment and natural resources. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 26 of 97

27 Figure 13: Classification of impact categories for characterization modeling at midpoint and endpoint (Areas of Protection) levels (Source: JRC, European Platform on LCA) Step 2: Characterisation (mandatory) At this step, the relative contribution of the input/output (elementary) flows to the environmental impacts is estimated. The contribution of each flow/substance is assigned to impact categories, leading to the estimation of indicators that describe the corresponding impacts on the environment. This quantitative modelling is performed by multiplying the results of the classification step by the characterisation factor of each flow/substance within each impact category, according to the following equation (Menoufi, 2011): n i i (2.1) i 1 Category Indicator Characterization Factor Emission Inventory The estimation of the characterisation factors is based on quantitative models and scientific analyses of the relevant environmental processes. Factors can vary according to national or regional differences in production processes (Menoufi, 2011). As a result, all elementary flows within the same category are converted to a common unit of assigned elementary flows (UNEP 2011, p. 8). Step 3: Normalisation (optional) Although, according to ISO 14040, normalisation is an optional step, it allows for the comparison across different midpoint impact categories and/or AoPs (JRC, 2010). Additionally, it provides the contribution of each impact category with regard to a reference, by converting different units into a common and dimensionless format D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 27 of 97

28 (UNEP 2011, p. 8). Specifically, the sum of each category indicator can be divided by a reference value, as in the following equation (Menoufi, 2011): N k S R k (2.2) k where: k: an impact category N: the normalized indicator S: the initial (non-normalized) indicator R: a reference value The common reference value R may vary in different applications of the LCIA, and depends on the scope of each study. Hence, it can represent (Menoufi, 2011): A geographical area over a certain time period, Total emissions or resource use for a given area on a per capita basis, The ration of an alternative to another (i.e. the baseline configuration) or The highest value among all options. Step 4: Weighting (optional) Weighting and (optionally) aggregation are important in the case of trade-off situations, where different alternatives, each being best in some impact categories, need to be compared (UNEP, 2011). The normalized indicators for each impact category, estimated in step 3, are multiplied by weighting factors, as in the following equation (Menoufi, 2011): k k (2.3) EI V N where: EI: the overall environmental impact indicator k: an impact category V: a weighting factor N: the normalized indicator for a category Weighting factors permit the ranking of different environmental impact categories or Areas of Protection according to their relative importance in each study. Weighting factors are typically based on subjective valuations and can vary, depending on the geographical area of the analysis, as well as on socio-economic criteria. They are often used in order to allow stakeholders to express their relative preference according to policies and targets. Different weighting methods have been developed, such as (Menoufi, 2011): Proxy approach, where a set of quantitative measures are considered to be indicative of the total environmental impact, Monetarization, based on an assessment of the willingness-to-pay for environmental protection, D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 28 of 97

29 Distance-to-target, where the weighting factors are related to a target decided by national or local authorities, and Panel approach, which is based on cataloguing the views of stakeholders, scientific experts, governments and international bodies. A clear distinction should be made between weighting (whose purpose is to assign relative values to the different impact categories, according to their perceived importance) and normalization (which provides the basis for the comparison of different types of environmental impact categories) Relevance of LCA and LCIA to EcoWater The framework for eco-efficiency analysis in EcoWater (see Section 1.1) will follow in general the 4-stage methodology proposed by the LCA guidelines, including the described LCIA methodology. In the Case Studies, the systems will be analyzed following the from cradle to grave approach for water. As already mentioned, the value chains in EcoWater include all production stages required for rendering water suitable for specific purpose. All corresponding processes within each stage will be taken into consideration, focusing particularly on the water using/wastewater generating processes when water is used as input for a production process or for providing services in an urban environment. Additional inputs required in each specific stage (such as energy and materials) will be accounted for; however, the upstream/downstream impacts over their own value chains will not be explicitly taken into account (Figure 14). Energy Materials Agricultural produce (e.g. olives) Industrial product (e.g. milk) Figure 14: Schematic definition of EcoWater s system boundaries and value chains The functional unit, which will be used in order to compare alternative technologies and systems, is the volume (m³) of water used. The results on input/output flows, accounting for all phases / stages of the life cycle of water for each specific use will be estimated, both for a baseline configuration and for all the alternative technologies to be assessed. These flows will be the basis for the estimation of the environmental component of the eco-efficiency indicators, focusing primarily on midpoint impact D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 29 of 97

30 categories (which can be further grouped into resource use intensities and emissions to water, air and soil). The relative contribution of each flow to the corresponding midpoint category will be identified by multiplying its value by a characterization factor. This will express all flows by a common reference quantity (e.g. kg of CO 2 equivalent in the climate change category). Environmental impact indicators will be normalized based on the volume of water used or on the quantity of the Final Product produced. Indicators will be divided by a common reference value to allow comparisons. Subsequently, scaling will be applied by dividing the indicator value for a specific configuration by its average over all configurations which are being cross-evaluated. This simple normalization method, expressed by equation 2.4, allows for the comparison of alternative configurations per environmental impact category: k p relative k p n i 1 k i absolute n absolute (2.4) In order to assess the overall eco-efficiency performance, the normalized environmental impact indicators will be combined into a single aggregate ecoeffficiency index through weights, reflecting their relative importance for each environmental aspect considered (e.g. Global warming potential vs. Eutrophication potential). The following three alternative methods, for assigning weights to indicators, will be independently used, as illustrated in Figure 15: 1. Through the participation of local actors and decision-makers (corresponding to the panel LCIA approach), 2. Through the deviations from a standard or target (corresponding to the distanceto-target LCIA approach) 3. Through conversion to monetized values (corresponding to monetization). = =1 Figure 15: Potential methods for deriving weighting factors Following that, a single aggregate eco-efficiency index can be derived, based both on normalization and weighting methodologies, as described above. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 30 of 97

31 The estimated indices can be tested through sensitivity analyses to identify how the selected weighting scheme influences the performance of each alternative. This can ensure that the relevant assumptions do not conclusively affect the results. Furthermore, different weighting schemes can be also used to present results from the point-of-view of different actors. 2.5 The BASF Sustainability Quantification Methods The BASF company, within the context of enhancing its environmental responsibility and emphasizing its commitment to a sustainable future, has developed three (3) different analysis methods for quantifying and assessing total costs and ecological impacts of products and processes over their lifecycle. These methods evaluate the eco-efficiency of products and processes following a Life Cycle Assessment (LCA) approach, from the extraction of raw materials to product manufacturing, use and disposal. Their application is aimed at supporting the minimization of the use of raw materials and energy in production processes, as well as of any generated wastes and emissions The BASF Eco-Efficiency Analysis method This method focuses on the assessment of products or processes over their entire life cycle, including the impacts of raw materials used, the use of the products and alternative recycling and disposal options. The derived results quantify the environmental impacts and the economic output of different alternatives; as such, they provide information on the most ecological and economical products. The interpretation of the eco-efficiency indicators allows for the identification of additional improvements in terms of environmental impacts and economic performance. The relevant analyses are based on different components and tools, described below. The environmental component The analysis of the environmental component of eco-efficiency is based on the LCA methodology and environmental categories, further incorporating the toxicity potential and the use of land and water associated with a product s life cycle. The total ( from cradle to grave ) environmental impact is derived from the combination (i.e. normalization and weighting) of the estimated individual environmental impacts. These impacts are classified into six (6) categories: 1. Raw materials consumption 2. Energy consumption 3. Land use 4. Air and water emissions, as well as solid waste 5. Potential toxicity 6. Potential risks Results are presented as a spider chart, which gives an overview of the ecological fingerprint of the analysed system. An example is illustrated in Figure 16. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 31 of 97

32 Figure 16: Example of the graphical presentation of combined impacts for all environmental impact categories (Source: BASF) The economic component The analysis of the economic component focuses, by turn, on each stage of the system, accounting for all the costs associated with the manufacturing processes and the use of a product. The analysis is based on the Total Cost of Ownership (TCO) method, which includes both the costs of purchase and of the subsequent use of the products (e.g. energy costs, maintenance, environmental protection cost). Eco-Efficiency assessment Results from the environmental and the economic components of analysis are presented in a customized x/y type of diagram (referred to as the Eco-Efficiency Portfolio - Figure 17). In this diagram, the x-axis represents the economic component, while the y-axis represents the environmental component. The placement of an alternative configuration on this graph (x-y point of the intersection of the two components) corresponds to the eco-efficiency index of the analysed product or process. Figure 17: Example of the Eco-Efficiency Portfolio (Source: BASF) The Eco-Efficiency Internet-Manager The Eco-Efficiency Internet-Manager is a web-based tool that can support ecoefficiency assessments in case of regularly varying inputs (BASF). Through this tool D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 32 of 97

33 (Figure 18) new parameters can be entered into the Eco-Efficiency Portfolio, allowing for the specification and analysis of alternative scenarios. Figure 18: The Eco-Efficiency Internet-Manager (Source: BASF) The BASF SEEBALANCE method SEEBALANCE is a sustainability quantification method, which assesses the environmental impacts and costs of products and processes, and their societal impacts. Thus, this assessment method measures the performance of a system by taking into consideration all sustainability dimensions. SEEBALANCE methodology The SEEBALANCE method groups societal impacts into five (5) stakeholder categories: employees, international community, future generations, consumers, local and national communities. Stakeholder groups are considered by defining and using indicators specific to each group, such as the number of jobs and the number of working accidents occurring during production, which are estimated throughout the product life cycle. The values of social indicators are summarized in a societal fingerprint chart (Figure 19), very similar to the ecological fingerprint of Figure 16. Results of the SEEBALANCE quantification method are visualized in a triangle type of graph (a 3D cube), which represents the three dimensions of sustainability. Through this approach, the most sustainable alternative configurations can be identified. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 33 of 97

34 Figure 19: Example of a SEEBALANCE graph ( The BASF AgBalance method for measuring sustainability in agriculture AgBalance is a method used for measuring the sustainability of agricultural practices. The method incorporates a set of indicators and weighting schemes for the evaluation of sustainable practices in the entire food value chain. In particular, 69 indicators linked to the three sustainability dimensions are proposed (Table 2). These indicators, estimated through an assessment of almost 200 primary evaluation factors, form the basis for the comparison of different farming systems, agricultural enterprises, processes and products, and can be used to identify weaknesses, drivers and potential solutions. Table 2: The AgBalance indicators (adapted from BASF) Environmental indicators Aspect Indicators Soil Soil carbon balance, nutrients balance, compaction, erosion Biodiversity Water use Land use Energy consumption Emissions Resource consumption Eco-Toxicity potential State indicators, agri-environmental schemes, protected areas, Eco-Toxicity, farming intensity, N-surplus, crop rotation, potential for intermixing Assessed total water use Actual agricultural area, assessed total area Non-renewable energy, renewable energy Air emissions, GHGs, acidification potential, ozone depletion potential, photochemical ozone creation pot, water emissions, solid waste Abiotic resource depletion Assessed Eco-Toxicity potential D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 34 of 97

35 Aspect Variable costs Fixed costs Macro economy Aspect Farmer/ Entrepreneur Consumer Local & national community International community Future generations Indicators Economic indicators Soil preparation, seed, crop protection, fertilization, machinery Depreciations, maintenance, insurances, labour, investment, other fixed costs Subsidies, Gross Value of Production (GVP), farm profits, wider economic effects Social indicators Indicators Wages, professional training, association membership, wages/salaries (pre chain and downstream chain), toxicity potential, risk potential, strikes and lockouts Residues in feed & food, unauthorized/unlabelled GMO, toxicity potential, functional product characteristics, other risks Access to land, employment, gender equality, integration, qualified employees, part time workers, family support Imports from developing countries, fair trade, child labour, foreign direct investment Trainees, social security, R&D Expenditures, capital investments Relevance of the BASF Sustainability Quantification Methods to EcoWater The analysis methodology followed in EcoWater can employ several elements of the BAS eco-efficiency analysis method (see Section 2.5.1). Specifically, the environmental influence of different alternative technologies will be evaluated throughout the value chains, as well as the corresponding economic output (in terms of Value Added). Results will be illustrated both separately (e.g. in an ecological fingerprint type of graph) and in the form of an eco-efficiency portfolio. Through scenario generation and evaluation, alternative technologies will be assessed, in order to conclude on the most eco-efficient, as well as on the policy measures required to enforce its application and uptake. 2.6 System Dynamics Modeling Overview System Dynamics Modeling (SDM) focuses on (complex) feedback systems (systems containing feedback loops), and provides a methodology for their analysis (Sušnik and Vamvakeridou-Lyroudia, 2010). A system can be defined as a set of components interrelated with each other and with the environment. These relations represent the exchange of matter, energy and information. Input to the system corresponds to relations influencing the system components, while output from the D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 35 of 97

36 system corresponds to relations influencing the environment (Atanasova et al., 2006). By providing links between different feedback mechanisms and simulating system evolution over time, SDM can be used to identify underlying causal relationships. SDM system simulation is particularly useful in cases where formal analytical models do not exist. In these cases, SDM can effectively support decision-making by experts and stakeholders, as it can provide suitable indicators; in this context, business policy and strategy problems have been successfully addressed in complex environmental and water systems (Sušnik and Vamvakeridou-Lyroudia, 2010). For example, Simonovic (2003) developed the CanadaWater model to assist in the sustainable management of the Canadian water resources, based on system dynamics and the WorldWater model (Figure 20), which was adapted to meet regional conditions. Modelling complex systems by SDM can be broken down into two main steps: The first step involves the construction of a conceptual qualitative model and then of a simple quantitative model with limited detail and feedback loops. System components can include stocks (interlinked compartments), flows (direct links) and converters (influences) (Ford, 1999). This initial working model can then be modified to address the desired system complexity. If needed, complex systems can also be divided into various sub-models representing different components (Sušnik and Vamvakeridou- Lyroudia, 2010). Figure 20: The WorldWater causal diagram (Simonovic, 2003) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 36 of 97

37 Various software tools have been developed to provide the model interface, visualize system components and offer the capability of solving complex differential equations. Examples include the VENSIM ( STELLA ( and SIMULINK, which is an add-on to MATLAB ( For example, by using the STELLA tool, users can simulate the behaviour of a system over time, for different what-if type of alternatives, and identify key leverage points and optimal conditions. Figure 21 presents a simple example of a system modeled in the STELLA software. Figure 21: Example of a system modelled in the STELLA ( Relevance of System Dynamics Modelling to EcoWater SDM has recently emerged as a modelling technique to address interactions among actors in complex supply chains. As such, the method has been recommended for the assessment of meso-level dynamics, in order to facilitate the capture of the interdependencies among actors in extended chains and assess the systemic impact of eco-innovations (Reid and Miedzinski, 2008, p. 12). An interesting example of this type of SDM application is provided by Halog and Manik (2011), who describe an Integrated Systems Modelling Framework for Life Cycle Sustainability Assessment, using the forest biofuels supply chain as an application example. In the framework developed by Halog and Manik, SDM is used to capture impacts (social, environmental and economic) that can occur only after some time interval; the application of SDM is used to enhance the understanding of the interrelations among the different components of a supply chain and thus provides insights on systems synergy, as well as on the system behaviour at an individual/actor level, and in an integrated level. SDM can be considered applicable to the EcoWater concept in the case that complex feedback loops and other dynamic mechanisms are required to simulate the behaviour of specific systems. Possible situations, in which the need for SDM methods can arise, include: (i) Where complex interrelations (e.g. both positive and negative feedback loops with dynamic behaviour) are found to exist between actors (or stakeholders) of the system. In that case, SDM could be used to model D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 37 of 97

38 (ii) (iii) technology uptake difficulties and measures, in order to provide support to decision-makers. Where complex recycling technologies (e.g. secondary production of energy, water-recycling) need to be assessed. Where there are complex interrelations between different waste products, different environmental impact categories, and time-delayed actions. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 38 of 97

39 3 Discussion on reviewed methodology frameworks Chapter 2 provided a brief description of the frameworks for eco-efficiency analysis, which are considered most relevant to EcoWater. The information compiled provides: (i) methodological guidelines for the analysis procedures that can be supported by the EcoWater tools, and (ii) criteria for the selection for review of the most relevant existing tools, on the basis of the framework and analysis methods that they should support. The EcoWater tools should allow users to map the system and its boundaries for each Case Study, in order to support the modelling of all stages required for rendering water suitable for specific use purposes. Depending on the collection of data on input and output flows, the tools should provide all necessary information for the evaluation of eco-efficiency performance, both for a baseline and for alternative configurations. The assessment of eco-efficiency will be based on the combined use of environmental impact indicators (e.g. representing sets of environmental parameters) and of the economic output expressed in terms of Value Added from water use. The evaluation results for each configuration should be comparable, so as to allow the construction of comparison diagrams, similar to the ecological fingerprint and the eco-efficiency portfolio diagrams. The functional unit for all results is the quantity of water used. Environmental impact indicators can be normalized and weighted to derive a single eco-efficiency index. The comparison of results of the analysis for each alternative technology will enable the proposal of technologies which would support technology implementation and uptake. As a result, the tools to be developed would allow users to: i. Map the system for each Case Study, specifying its boundaries, ii. Build a convincingly accurate representation (model) of the system, iii. Use existing data to calculate and double-check all flows (products, resources and emissions/wastes) and build a system inventory for analysis, iv. Select the most relevant, to each Case Study, indicators, v. Assess all the relevant environmental impact categories, vi. Estimate the Total Value Added, focusing both on the entire value chain and on the distribution of costs and benefits for the actors involved, vii. Estimate a single aggregate eco-efficiency index, and viii. Compare the baseline and alternative configurations (e.g. using comparison graphs, such as the ecological fingerprint and the eco-efficiency portfolio ). Consequently, all tools subsequently selected for review should provide all or part of the above functionality, by supporting Material Flow Analysis (MFA) as a methodology to establish an inventory for environmental and economic assessment (e.g. LCA / LCIA, LCC, etc.). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 39 of 97

40 PART B

41 4 Review of existing analysis tools 4.1 Introduction Several eco-efficiency analysis tools, embedding the methods and guidelines described in Chapter 2, have been identified. This Chapter briefly describes those that are considered most relevant to the concepts of EcoWater, and those that are most well established. The description aims at highlighting the functionalities, strengths and weaknesses of each tool, in order to conclude to design elements that can be taken into consideration in the development of the EcoWater tools. Tools discussed in this Chapter are divided into two categories: 1. Tools most relevant to the Systemic Environmental Analysis. These, typically, support methodologies such as Substance/Material Flow Analysis (MFA) to produce an inventory of components and flows for the analyzed system. The system inventory is, in turn, used to support analysis methodologies identified in Part A, such as Life Cycle Impact Assessment (LCIA), Life Cycle Sustainability Assessment, etc. 2. Tools most relevant to the economic analysis of value chains, which can be used to perform cost-benefit analysis, such as Life Cycle Costing (LCC), economic valuation of environmental goods and services (particularly water), etc. The review of tools will be based upon specific criteria in order to highlight their strengths and weaknesses, and for assessing their usefulness and relevance to the EcoWater context. This will lead to a set of recommendations for the development of the EcoWater tools and for re-using existing tools in link with the EcoWater Web Toolbox. Additional functionalities, which could be developed and build into the EcoWater tools, will also be considered. Review criteria are listed in Table 3. Table 3: Criteria for the assessment of existing tools No Primary criteria Defined as (secondary criteria) Integration Potential for integration with other tools/databases 1 of methods Reuse of components Value chain representation Flexibility - 2 Scenario generation adaptability Assessment of diverse technologies 3 Ease of use 4 Model output Input data requirements/flexibility User-friendly interface External links to knowledge bases (e.g. technology inventory) Documentation Supported languages Ease to analyze and understand results Clarity of presentation (e.g. mathematical, graphical) Computational accuracy & efficiency D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 41 of 97

42 No Primary criteria Defined as (secondary criteria) 5 Costs 6 Relevance to EcoWater Comparison of results across alternatives Costs of use (data provision & structuring) Training costs Maintenance costs Support for environmental analyses Support for both cost-based and value-based analyses (economic component of eco-efficiency) Integration of different resource-use and environmental impact indicators Description of the main stages and processes of a system Analysis of interrelations among actors Analysis of the economic impacts of technology scenarios Adaptability to Case Study specificities It should be noted that this Chapter does not provide a thorough description of each examined tool; instead, it focuses on specific features, which could be most useful for the design of the EcoWater tools and eventually of the EcoWater Toolbox. 4.2 Tools relevant to Systemic Environmental Analysis Modeling The European Platform on LCA of the Joint Research Centre 1 provides a list and a short description of existing tools, which are relevant to systemic environmental analysis modelling. The main (but not necessarily the only) EcoWater tool for this type of analysis will be SEAT. Five (5) of these tools are reviewed here: GaBi 4, STAN (Software for SubSTance Flow Analysis), TEAM TM 4 (Tools for Environmental Analysis and Management), SimaPro 7 and Umberto 5.5. Although there are other tools in the list, which offer similar functionalities, the above tools have been considered to be well-established and closer to the EcoWater concept. As such, their review will provide sufficient input for the development of the SEAT within the EcoWater analytical framework GaBi 4 Short description Gabi 4 is a software tool that can be used to create comprehensive life cycle environmental balances. These are then used to support both LCA and eco-balance methods, additionally incorporating technical and socio-economic aspects (IKP, 2003). It is a modular system, based on plans (models), processes, flows and their corresponding functions, which all employ a modular basis. A plan represents a model of a specific system, with its own boundaries, consisting of processes that correspond to the actual processes of the examined system (PE International, 2011). 1 D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 42 of 97

43 Generic process types (e.g. industrial, transport, cleaning, transformation, power plants) contain specific industrial processes (Menke et al., 1996). Input and output flows, associated with these process types, represent all materials and energy balances flowing to and from each process of a plan. Flows are characterized by mass, energy and costs with their respective values (PE International, 2011, p. 30). Additionally, each flow can belong to a flow group, providing users with the ability to develop a hierarchical system. For example, CO 2 would belong to the emissions to air flow group (Menke et al., 1996). Thus, a user can built multiple sub-systems within each plan, which can be re-used in alternative scenarios. These features are illustrated in Figure 22. Figure 22: An example of a plan with processes and flows modelled in GaBi 4 (PE International, 2011) GaBi 4 can support the following analysis methodologies: (i) Life Cycle Analysis (LCA); (ii) Life Cycle Inventory (LCI); (iii) Life Cycle Impact Assessment (LCIA); (iv) Life Cycle Work Environment (LCWE); (v) Product stewardship; (vi) Supply Chain Management (SCM); (vii) Life Cycle Sustainability Assessment (LCS); (viii) Life Cycle Costing (LCC); (ix) Design for Environment (DfE, DfR); and (x) Substance/Material Flow Analysis (SFA/MFA). Integration GaBi 4 can be considered a software tool that can be easily integrated with other tools. It can be used in analysis methodologies based on process chains, as it incorporates fundamental features similar to all analysis methods used for this purpose. These include material and energy analysis, specification of system boundaries, reference quantities and environmental LCIA (IKP, 2003). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 43 of 97

44 Flexibility adaptability GaBi 4 is considered a flexible tool, applicable to a wide range of industries. It offers a large variety of functions, although this can also become a drawback when comparing complex systems. Users can interactively define the functional unit, boundaries and flow allocation of the system to be examined, according to casespecific requirements. The functional unit of the system is defined with regard to a reference flow, and provides the basis for calculations. System boundaries allow for the specification of the stages and processes to be included in the analysis, which, in turn, describe the extent to which the value chain is taken into consideration. According to PE International (2011), GaBi 4 provides a large array of boundary choices, which include: From Cradle to Grave, including all processes from raw material extraction to end-of-life treatment, particularly focusing on the material and energy production chains, From Cradle to Gate, focusing on all processes from raw material extraction throughout the production phase, especially used for the determination of the environmental impact of the production of a product, From Gate to Grave, including the use and end-of-life processes, i.e. the post-production processes, used for determining the environmental impacts of a product after the production process, and From Gate to Gate, focusing only on the production phase processes and used to determine the environmental impacts of a single production step or process. The editing of the attributes of a process allows for the specification and evaluation of alternative technologies. In addition to technology comparisons, the tool can be used to generate full scenarios. Through the Scenario Analyst function, users can specify parameters to create a scenario and compare the impact of alternative configurations. Input flows to and output flows from each process can be allocated in four different ways (PE International, 2011): (a) proportionally to their quantity, (b) according to their heating value (often used for fuel production processes), (c) according to their market value, or (d) according to other rules (e.g. energy, substance content). Ease of use The tool has a user-friendly interface running on MS Windows (NT, 2000, XP, 98, 95) and supports four different languages (English, Dutch, German and Japanese). This fact, in conjunction with a well-structured documentation, enhances its ease of use for new users. Documentation is based on a procedure following ISO for LCA, offering further advice for each step of the modelling procedure. Multi-functional pop-up dialogue boxes are used for the specification of properties and parameters, allowing users to input and edit data, text descriptions and comments. These are specified for each process, depending on the data collection requirements. Additionally, global parameters can be specified, applicable throughout a plan, to increase the flexibility of the modelling. Data quality should be determined D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 44 of 97

45 from the very beginning, as it significantly affects the accuracy of the results. Therefore, there are issues that should be taken into consideration in the data collection step, and they particularly concern (PE International, 2011): Data acquisition: The data measured, calculated or estimated should be clearly specified, Time reference: The derived results should correspond to the data collection timeframe, Geographical reference: All data should concern a specific geographical area, Best available technology: In the case that data have been retrieved from literature, these should be carefully collected to represent the state-of-the-art technologies, Precision: The collected data should provide an accurate representation of the physical system, Completeness: In case of missing data, all assumptions should be as precise as possible and clearly stated, and Representativeness, consistency and reproducibility. Data input is primarily done through spreadsheets, while interfaces for and web-based data input are additional alternatives (Siegenthaler et al., 2005). Users can upload MS Excel spreadsheets, which can be automatically adapted to the GaBi requirements (Boureima, 2007). According to the GaBi Software website, the tool can support various pre-built databases. Over 4,500 Life Cycle Inventory datasets are available, spanning a wide range of industries (including agriculture, textile, automotive and energy industries, services). PE International also offers the choice of creating a user-specific dataset according to data-on-demand and the specificities of each plan. The databases of GaBi Professional also incorporate the ecoinvent database, providing access to unit processes and from cradle to gate inventories, which cover various industrial areas. The US Life Cycle Inventory (LCI) Database is also available online, incorporating data collected on commonly used materials, processes and products. The specific database provides a cradle-to-grave accounting of the energy and material flows into and out of the environment. Additional databases like Australian databases, APME, EAA, IISI and DUWAL 250 are also available, while users can enter their own databases (Siegenthaler et al., 2005). Model output Results derived from GaBi 4 can be characterized as accurate and efficient. The GaBi Analyst incorporates sensitivity analysis, Monte Carlo and scenario analyses, as well as parameter variation. The latter enables users to develop a gradual variation of key variables to check performance of the model under changing conditions. Sensitivity analysis focuses on the identification of those parameters which influence the results the most, while the significance of the results can be assessed through Monte Carlo analysis. The results, including all information and data used, such as materials properties and eco-profiles for each plan and scenario, can be stored, so that different configurations and scenarios can be compared. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 45 of 97

46 Therefore alternative technologies and scenarios can be assessed in comparison, so as to conclude to the most efficient ones (IKP, 2003). Results derived from solving input/output balances can be easily understood and analyzed. They can be presented in tabular form and as Sankey diagrams. The latter offer an overview of mass, energy and cost flows in proportion to their quantities. Customized diagrams can also be created and results can be exported to all Microsoft applications, for further processing and exporting (Boureima, 2007). Costs A free demo of the tool is available at its website. The price for purchasing GaBi 4 varies according to its version (Siegenthaler et al., 2005). Training costs are not very significant, as 2 training days can be sufficient to get familiar with GaBi 4 (Siegenthaler et al., 2005). Relevance to EcoWater Based on the above information, GaBi 4 is a tool incorporating most of the features, pertinent to the environmental analysis that forms part of the EcoWater analysis framework. GaBi 4 focuses on the four stages of the LCA framework, integrating various resource-use and environmental impact indicators. It can represent all stages of the life-cycle of a product or service, while illustrating the processes within each stage of the corresponding system. In parallel with environmental analysis methodologies, GaBi 4 supports cost-based analysis, focusing on various factors connected to processes or products. However, no clear information is provided regarding the interrelation among economic actors involved in the distinct stages. Finally, it should be noted that GaBi 4 has been extensively applied in a wide range of sectors, and can thus be considered a versatile tool, applicable to diverse sectors. Recommendations for the development of the EcoWater tools Based on elements of the above description, it can be suggested that the EcoWater tools, which focus on the assessment of the environmental impact of different technological configurations, and particularly the SEAT, can embed specific useful features (similar to those found in GaBi 4), which could enable users to: Add, edit or delete all elements of the system s model by using a graphical interface, e.g. draw model processes to represent distinct stages (or processes) within a system, as well as model flows to represent flows of resources. Save and restore any model created, Focus on the analysis of input/output balances on a process level, Specify the boundaries of each Case Study system, including all four choices mentioned (cradle to grave, cradle to gate, gate to grave and gate to gate), Change any parameters in a specific model, so as to create a new model based on alternative configurations, Specify rules for the calculation of input/output flows, either on a process basis or for the whole model (global parameters), D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 46 of 97

47 Add descriptions and comments for each process (or any other model element), Export the system modelled, so it could be the basis for other analyses (e.g. economic analysis), Present results in the form of graphs demonstrating the eco-efficiency of the analyzed system; Perform sensitivity analysis, in order to ensure that the results are not biased; Import process data conforming to the EcoSpold format; Specify all elements, materials and reference units interactively. In addition, a scenario generation module could be included in the EcoWater Toolbox, to be used both for the environmental and economic assessments. Such functionality would facilitate the cross-evaluation of alternative configurations, possibly concluding on benchmarking STAN Software for SubSTance Flow Analysis Short description STAN is a software tool specializing in Substance and Material Flow Analysis (SFA/MFA) applications for waste management. It can be used in order to analyze the potential for resource efficiency, under the aim of process improvement and with consideration of data uncertainties (Eco-manufacturing Website). The software follows the Austrian standard ÖNorm S The system model is designed interactively in a graphic editor, based on predefined components, such as system boundaries, processes, flows and text fields (TU Wien website). Figure 23 presents a simple example of the STAN modelling environment, illustrating the above elements. Figure 23: A snapshot of the STAN modeling environment (TU Wien website) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 47 of 97

48 Inputs concern known data for the system, such as mass flows, volume flows, stocks and transfer coefficients. Subsequently, STAN calculates the unknown quantities by using alternative methods, such as mass conservation, data reconciliation or error propagation. Multiple periods and different layers, i.e. goods, substances and energy, can be specified, as shown in Figure 24 (TU Wien website). Figure 24: Use of Layers and Periods in STAN (TU Wien website) Integration STAN mainly uses MS EXCEL as an interface and tool for the importing and exporting of data and results, and for the further analysis of results. The software is also compatible with the PIUS framework and other well known dataset formats (Eco-manufacturing website). Flexibility adaptability STAN is a flexible tool for its purpose, as users can design all model elements interactively in a graphical environment. Depending on the requirements of each system analysed, different elements can be included in the model. Although STAN focuses on waste management, users can design complex systems for diverse value chains. As a result, data on different technologies can be retrieved, and alternative scenarios can be created by changing input and output variables. Ease of use The general user interface of STAN is similar to that of several MS Office applications. Thus, the software can be characterized as user-friendly, requiring only limited learning time. This impression is strengthened by the fact that users can draw all model elements by simply selecting them and clicking; a drag-and-drop process is also supported (Eco-manufacturing website). A help window is available, explaining the basic rules on which STAN is based. Supported languages include German and English. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 48 of 97

49 On the left side of the model designer environment, there is a model-explorer tab, providing an overview of all elements used in the model, and allowing users to quickly access any element. On the right side, an overview of the flow properties is provided, including information about the layer, period, emanating and target process for the selected flow. Additionally, both input and the calculated values are illustrated. There are also tabs for literature references and remarks, to support model documentation. MS Excel is used as an interface for importing data. The underlying databases have Microsoft Access and XML database formats (JRC, European Platform on LCA). Model output The calculation of the unknown quantities of the model is based on four (4) basic types of equations. These are (Cencic and Rechberger, 2008, p. 441): (1) Balance equation: inputs outputs change in stock (4.1) (2) Transfer coefficient equation: output Transfer coefficient inputs x to output x (4.2) (3) Stock equation: stock stock change in stock periodi 1 periodi periodi (4.3) (4) Concentration equation: mass mass concentration substance good substance (4.4) An error propagation method can be used for the calculation of uncertainties, and statistical tests point out any random errors (Cencic and Rechberger, 2008). Results are presented in the form of Sankey diagrams. Calculated data can be exported in MS Excel spreadsheets, and model graphs can be exported and printed. Costs STAN is a cost-free software (freeware). Interested users can download it from the official website, upon registration. Relevance to EcoWater The analysis of the flow of materials/resources is included in the objectives of EcoWater, both for developing system inventories and as a means to enhance resource efficiency in specific industries/sectors. The estimation of environmental impacts for the systems to be analyzed will be based on the results on the flow of resources, and thus, on the concepts of Material Flow Analysis (MFA). However, STAN does not estimate eco-efficiency indicators; it focuses on providing data on resource flows, which can be the basis for all other analyses and D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 49 of 97

50 estimations. Consequently, the overall concept of STAN is considered applicable as the basis for the environmental analysis. Since STAN allows users to model different stages and processes in a value chain, regardless of the complexity of the system, all EcoWater Case Studies could be modelled by using this tool. Although literature review on STAN provided no information regarding its support to cost-based and value-based analyses, the results on material flows can be the basis for the cost and value analysis as well. Finally, no evidence could be found that STAN can support the analysis of the economic interrelations among actors, which is one of the primary objectives of EcoWater. Recommendations for the development of the EcoWater tools Features of STAN which can be implemented in the EcoWater tools, and particularly the SEAT are the: Importing of data and the exporting of results from/to MS Excel; Exporting of the designed system model in printable and storable form; Integration of help windows to provide guidance and instructions; Visualization, in an overview form, of all the elements used in the modelled system; Potential to add auxiliary information for each element of the system modeled (e.g. literature source, description, remarks); Storage and retrieval of calculated results both for the model as a whole and for individual elements; Design of a model of the system through a click-and-draw process, and the selection of a specific element from a toolkit and drawing it into the model editor pane; Use of Sankey diagrams to present results. Since systems analyzed can have different resources, it will be useful to be able to select a specific resource in order to present its flows in a Sankey diagram. Referring specifically to the SEAT, it is suggested that it could focus on the calculation of resource flows on the basis of flow balancing equations similar to the ones used by STAN. Specifically, the balance and transfer coefficient equations (equations 4.1 and 4.2) can be used for the calculation of the input/output balances per process. Transfer coefficient parameters for each resource can be added by the user. It is also suggested that the tool could also implement a time-series function for stocks, which would use a stock equation (similar to equation 4.3). This can be used to analyze specific industrial sectors, such as the cogeneration of thermal energy and electricity and storage of thermal energy TEAM TM 4.0 Tools for Environmental Analysis and Management Short description TEAM is a system analysis tool for modelling industrial systems of any complexity and size. System models can represent any operation associated with the life cycle of products, processes and activities, by focusing on value chain analysis. In order to simplify the design and management of complex models, a graphical interface allows D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 50 of 97

51 users to access all system components at the same time. This method is based on dividing the working space into four panes, as illustrated in Figure Flow window 2. Module window 3. Tree window 4. Graphical model window Figure 25: A snapshot of the system editor (adapted from the Ecobilan Website) The upper left part of the user interface is assigned to a Flow window (TEAM Online Demonstration, Ecobilan Website). Flows represent input and output elements of industrial operations. Users can select a suitable flow type and specify its name and unit of the resource, as well as its physical properties and other information. Flows can include raw materials, products (final, intermediate and by-products), air emissions, indicators for energy consumption, wastes, water effluents and financial flows. At the upper-right side, a Module window allows to specify operations or steps/stages (e.g. industrial processes, transportation, commercial activities) and to allocate inputs, outputs and energy indicators to each. These modules are connected through their inputs and outputs. Each module is assigned a name, lists of inputs and outputs, as well as local variables, allocation formulas and other descriptive information. Users can add flows to each module through a drag-and-drop operation, and then enter a value for the flow. There are two module types: Source and Local modules. The former is generic, usable in any sub-system, whereas the latter is unique to a specific system. Although Local modules can also be copied to any other system, modifications are treated differently: changes in Source modules are automatically inherited and applied in all instances, while changes in a Local module apply only to the currently edited instance of the module (Ecobilan Website). Nevertheless, all modules can be stored and reused in other systems and projects. At the bottom-left, a Tree window provides a model overview, where sub-systems and elements are presented in a hierarchical order (outline). Finally, at the bottomright, modules can be added to the model in a Graphical window through a dragand-drop process. Results derived from a model comprise an inventory of aggregated input and output flows that can be presented in tabular and graphical D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 51 of 97

52 form (Ecobilan Website). Numerical inventory values, information sources, uncertainty, variability and measurement techniques can all be stored. TEAM is particularly useful when it is important to consider a wide range of decision criteria and to explicitly identify unquantifiable and uncertainty aspects associated with potential adaptations (UNFCCC). As such, it should be used in conjunction with other decision support tools (e.g. cost-benefit analysis). According to the European Platform on LCA of the JRC, the tool can support the following system s analysis methodologies: (i) Compliance checks, (ii) Design for Environment (DfE, DfR); (iii) Life Cycle Assessment (LCA); (iv) Life Cycle Inventory (LCI); (v) Life Cycle Impact Assessment (LCIA); (vi) Life Cycle Costing (LCC); (vii) Life Cycle Management (LCM); (viii) Product stewardship, supply chain management; (ix) Substance / Material Flow Analysis (SFA / MFA); and (x) Sensitivity and Uncertainty Analysis. Application examples This section presents three TEAM application examples to demonstrate its versatility in supporting the analysis of a wide variety of systems (industrial, infrastructure projects, etc.). The largest system modelled in TEAM includes almost 2,200 linked operations. Industrial cooked dish product (tuna with tomato) This model was aimed at the identification of the environmental performance over the value chain (Zufia and Arana 2008). The life cycle of the system (i.e. the food chain) was divided into four phases: (i) Fishing and supply of tunids, (ii) Product elaboration, (iii) Distribution and sale, and (iv) Use and elimination. Data used were partly provided by the company and in part by the software database. The environmental impact values were calculated for each stage of the value chain through the impact assessment module. Coal-fired power production TEAM was used for the Life Cycle Analysis of coal power production, in order to track the material and energy flows among the process blocks. These processes were divided into three main sub-systems: coal mining, transportation, and electricity generation (Spath et al., 1999). Drinking and wastewater treatment systems of the Bologna metropolitan area This is a TEAM application example related to the concept of EcoWater, as it was aimed at the comparison between the existing (BAU) and proposed innovative water and wastewater treatment systems. The TEAM TM 3.0 was used to identify the environmentally critical processes for different environmental impact categories. The results of the analysis highlighted that the treatment of drinking water is a highenergy consuming stage. This was primarily attributed to the electricity required at the pumping stations, demonstrating the need for reducing energy consumption and for optimizing the design and operation of the pumping installations (Tarantini and Ferri, 2001). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 52 of 97

53 Integration TEAM can be used in combination with various decision-support tools, ranging from cost-benefit analyses tools to workgroups with key decision-makers and stakeholders. This can enable the assessment of various soft issues, such as equity, flexibility and policy coordination (UNFCCC). Additionally, modules (both Source and Local ones), created within the context of a specific model or case study, can be stored and reused. Flexibility adaptability TEAM focuses on the value chain of a product or service. Users can specify distinct stages within a value chain (e.g. production, use and end-of-life) and analyse each stage into sub-stages or processes (Figure 26). Several sets of values for the specified key parameters can be chosen, allowing for the generation of alternative scenarios. The parameterized simulations focus on the influence of different alternatives on the inputs and outputs of an inventory. The simulation of these what if scenarios does not necessarily lead to the identification of the optimal strategy, unless one strategy outperforms others in all specified criteria. Instead, the assessment of alternative scenarios highlights the relative strengths and weaknesses of alternative strategies, so as to provide decision-support. By adding or editing modules (processes) or the parameters of modules, users are able to assess diverse technological configurations (Ecobilan, 2004). Figure 26: A simplified example of the specification value chain representation in TEAM (Siegenthaler et al., 2005) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 53 of 97

54 Ease of use All the functionalities of TEAM are fully documented. Documentation includes user manuals, tutorial, data register, sample data, case study examples and on-line help. This allows to easily understand and familiarize with the use and requirements of the tool (JRC, European Platform on LCA). The interface of the tool allows users to easily access all system components at the same time. A series of menus prompt users to specify unit operations and links, further simplifying the creation and management of the system model. Title and description text fields open when creating new systems, so as to allow users to easily describe a system (Menke et al., 1996). With regard to the specification of the evaluation criteria, TEAM provides a pre-defined list, which can be further expanded if required (Herrod-Julius and Scheraga, 2000). Additionally, the object-oriented management of the tool helps to easily access the database, variables, inventories, etc. Supported data formats include ASCII, MS Excel, XML and Ecospold (JRC, European Platform on LCA). Input and output allocation rules can be defined at the lowest process/unit level (a module ), while all flows can be defined by values, variables or equations, as well as mathematical functions (Menke et al., 1996). Allocation of burdens between coproducts and for recycle streams can be defined on a flow-by-flow basis, while reused and recycled materials can be credited back to the inventory (Menke et al., 1996). The Eco-indicator #99 is used as a weighting method; however, users can also input their own weighting function (Siegenthaler et al., 2005). Finally, TEAM uses DEAM (Data for Environmental Analysis and Management) as its main inventory database. This is continuously developed to provide updated versions of datasets (JRC, European Platform on LCA). This database includes over 300 modules, sufficient for the modelling of almost any system (Ecobilan Website). Ecoinvent is an additional database, which becomes available with the tool. Furthermore, TEAM can support any XML-formatted inventory database, which can be used in conjunction with DEAM. The data management features of TEAM allow users to import and export module data in a standardized format. Model output In addition to scenario analysis, TEAM can also be used to perform sensitivity and uncertainty analyses. Sensitivity analyses are used for checking the influence of different alternatives on the inventory, whereas uncertainty analyses are aimed at evaluating data uncertainty. Uncertainty analyses can be developed through the following methods (Ecobilan, 2004): By testing the minimum and maximum values of variables (Min-Max Analysis), or By testing the statistical distribution of variables (Monte Carlo Analysis). The consistency of results derived by the tool is tested in order to avoid incorrect flow connections, double counts, etc. Thus, it can be concluded that TEAM supports computational accuracy and efficiency. Model results are presented both in tabular as well as graphical format. An inventory of results is presented in tabular form, based on predefined format menus and D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 54 of 97

55 percentages, which are especially useful for comparison purposes (Ecobilan Website). The creation of graphs and charts allows users to interpret and analyze the relative strengths and weaknesses of potential strategies. Regarding the comparison of alternative configurations, TEAM is somewhat limited as it supports the creation of bar graphs between only two scenarios. Result exporting can be used for extended comparisons (Menke et al., 1996). Costs Referring to the 2009 price policy, the first license purchased is priced at 3,000 for all types of users, except universities, as well as industrial and governmental organizations (2,000 ). The LCA Software TEAM 4.0, the DEAM Starter Kit and technical support on the installation of the software are included in the aforementioned prices, while an additional license costs 1,000. There is also a TEAM demo, which is a cost-free version, downloadable from the official website. Further services (such as online support, automatic upgrades and updates) involve additional charges (Ecobilan Website). Relevance to EcoWater TEAM is a tool which supports the representation of the main stages and processes of a system, as it focuses on a life cycle assessment methodology. Each user can specify an infinite number of modules, according to the requirements of the analysed system. Therefore, value chains in water use sectors can be modelled with TEAM. Results can concern both economic and environmental parameters, which are both required for eco-efficiency assessments. With regard to environmental outputs, TEAM integrates LCA databases, and hence midpoint impact categories can be assessed. As a result, the tool does not only calculate resource flows, but also their contribution to environmental impacts, through the environmental impacts database included with the tool. On the other hand, the economic assessment and comparison of alternative configurations is based on the specification of cost- or value-based resources. In contrast, the interrelations among individual actors cannot be analysed. Finally, it is worth mentioning that TEAM can be used to support workshops and consultations with key stakeholders. Recommendations for the development of the EcoWater tools Features of TEAM which can be considered useful for the development of the EcoWater tools, and particularly the SEAT, include the: Visualization of results in the tabular form, both per module as well as for the whole system; Exporting of results in different formats; Possibility to add an unlimited number of resources, including raw materials, products (final, intermediate and co-products), air emissions, wastes and effluents; Use of an unlimited number of modules (or processes), as well as of flow connections among them; D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 55 of 97

56 Assessment of diverse technological configurations by adding, editing and deleting any module, flow or parameter, Visualization of data and further information on specific technologies according to the specifications of a technology inventory, Ability to perform sensitivity analysis on each model focusing on a specific parameter set, Modeling of what if scenarios by changing specific parameters, Definition of flows per process / stage / module, according to absolute values, relative values or functions SimaPro 7 (System for Integrated environmental Assessment of PROducts) Short description SimaPro is a tool for modelling products and systems from a life cycle perspective, allowing users to build complex models in a systematic and transparent way (JRC, European Platform on LCA). Models are evaluated to identify important environmental impacts of a product (PRé Website). The SimaPro LCA Explorer (Figure 27) gives access to all the data of the tool, organised into to six (6) categories: the wizard, data sets corresponding to the four LCA steps (goal and scope, inventory, impact assessment and interpretation) and general data. Within these categories, users can select specific libraries and databases that they want to use within a specific model, view processes/product stages, system descriptions, waste types and parameters included in the corresponding databases, and inspect the definition of a process. The assessment of a value chain is based on a list of environmental impact assessment methodologies, and users can interactively select the most suitable (PRé Website). Figure 27: The SimaPro LCA Explorer (PRé Website) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 56 of 97

57 There are six available versions of SimaPro 7 (Analyst, Classroom, Compact, Developer, Faculty, PhD) that, in total, support the following system analysis methodologies (JRC, European Platform on LCA): (i) Life Cycle Assessment (LCA); (ii) Life Cycle Inventory (LCI); (iii) Life Cycle Impact assessment (LCIA); (iv) Life Cycle Costing (LCC); (v) Life Cycle Management (LCM); (vi) Life Cycle Sustainability Assessment (LCS); (vii) Life Cycle Engineering (LCE); (viii) Life Cycle Work Environment (LCWE); (ix) Design for Environment (DfE, DfR); (x) Product stewardship; (xi) Supply Chain Management (SCM); and (xii) Substance / Material Flow Analysis (SFA/MFA). Application examples SimaPro has been used in a significant number of LCA studies by consultants, research institutes and universities. A few examples are briefly described below. Application of SimaPro to a study on bioethanol fuel The specific study focused on bioethanol fuel derived from cellulose by enzymatic hydrolysis, in order to compare among different ethanol-petrol blends and traditional petrol, in terms of different environmental impact categories. Various scenarios were defined and evaluated, in order to test the tool and identify the influence of different parameters on the LCA results. All results were grouped into different impact categories (e.g. energy demand, solid wastes), in order to be easily comparable (OECD, 2001). Evaluation of 13 wastewater treatment plants for small communities The study cross-evaluated thirteen (13) wastewater treatment plants (WWTPs) of small communities in Galacia, Spain. Each WWTP was divided into four subsystems (Figure 28), as follows (Callego et al., 2008): Pre-treatment and primary treatment (subsystem 1); Secondary treatment (subsystem 2); Sludge line (subsystem 3); and Transport and sludge use (subsystem 4). Figure 28: Diagram of the 4 subsystems for wastewater treatment (Callego et al., 2008) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 57 of 97

58 The environmental assessment of all subsystems included the use of energy and chemicals. The various databases, available within the tool, that were used for the description of different processes of the systems were: Electricity production: The IDEMAT (2001) database, updated with the 2004 production profile for Spain, was used. Treatment of solid waste: Residues generated in all WWTPs were transported to an incineration plant with energy recovery. Since the IDEMAT (2001) database had no data for waste incineration, these were retrieved from Ecoinvent (1996), modified by adding the recovered energy. Chemicals: Polyelectrolyte and hypochlorite were used as the main chemicals for sludge conditioning and cleaning purposes respectively. The former was referenced to acrylonitrile I (IDEMAT 2001) and the latter to sodium hypochlorite (Ecoinvent 1996). Transport of solid wastes, chemicals and sludge: Data from the IDEMAT (2001) database were used due to their similarity with the load capacity of trucks. Fertilizers avoided: The use of sludge as fertilizer reduces the need for synthetic fertilizers, reducing the environmental impacts if the content of heavy metals in sludge is acceptable. The substitutability was assumed to be 70% for P and 50% for N, while entries from the IDEMAT (2001) database were used (N-based and P-based fertilizers). Comparison of the environmental impacts of membrane technologies for wastewater reclamation, including the indirect toxicity contribution from energy and infrastructure The aim of this study was to identify the technology which produces the lowest environmental load, focusing on the life cycle assessment of wastewater treatment and water reuse. The estimations were based on SimaPro 5.1, and three different evaluation methods were applied (CML baseline 2000, Eco-Points 97 and Eco- Indicator 99). The results highlighted that environmental loads were not significantly increased due to tertiary treatment; instead, tertiary treatment provided new uses for reclaimed water. As a result, the study justified the intensive use of water reuse techniques in areas facing water scarcity (Ortiz et al., 2007). Comparison of desalination technologies The entire life cycle of the analysed technologies was examined, encompassing: extraction and processing of raw materials, manufacturing, transportation and distribution, operation, and waste disposal. The assessments were based on SimaPro 5, and different evaluation methods were applied (CML 2 baseline 2000, Eco-Points 97 and Eco-Indicator 99). The data used in the inventory analysis for desalination were obtained for existing plants in operation, while additional data were retrieved from the ERWT Project and further databases implemented in the SimaPro software (BUWAL 250, ETH-ESU 96 and IDEMAT 2001). Scenarios were defined to estimate the potential for the reduction of induced environmental loads for state-ofthe-art of technologies, and to identify those that are the most likely to be adopted in the future (Raluy et al., 2005). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 58 of 97

59 Integration The database included in SimaPro contains both European and international validated data. Data is organized in a set of libraries that can be used in any project. All data used can be copied between different libraries and projects. Users can define any number of projects. SimaPro is available in a multi-user version that allows multiple users to work using the same database and on the same projects. The main database of the tool contains all add-on databases and a library with 11 impact assessment methods (JRC, European Platform on LCA). Flexibility adaptability SimaPro focuses on the analysis and assessment of value chains. Figure 29 provides a simple example of a value chain, as represented by SimaPro. By selecting and defining various parameters, including non-linear relations for the specified elements, SimaPro allows users to analyze complex systems and assess diverse technologies. The specification of a range of values for a specific parameter facilitates the analysis of different scenarios (e.g. waste treatment and recycling scenarios). Uncertainty values can be added to parameters, by defining different uncertainty ranges or statistical distributions in scenario analysis for every impact category and emission (PRé Website). Ease of use SimaPro has extensive documentation, including a manual, tutorial, sample data, case studies and online help (Siegenthaler et al., 2005). Inventory data are well documented with text fields, while impact assessment methods and libraries are described in the SimaPro database manuals. Users can add comments to the goal and scope and the interpretation sections of the results, for future reference. A demo version is available at the PRé Website, while a large number of languages is supported (Danish, Dutch, English, French, German, Greek, Italian, Japanese and Spanish). Additionally, SimaPro includes an LCA wizard, which is especially useful for beginner users as it facilitates the definition of a lifecycle by entering the most important data through a series of questions (JRC, European Platform on LCA). The interface of the tool can be characterized as user-friendly, as users can easily access all options of the tool and elements of a specific model. On the upper right side of the interface, users can overview the value chain examined and navigate to a specific process through the navigation window. Additionally, the inflow and outflow values of the system are presented in the flow window (lower right), while the selection of a specific process allows users to view details of its flows (Figure 29). Users can build hybrid data models that combine input/output processes with traditional ones (JRC, European Platform on LCA). Linear, non-linear and conditional expressions can also be defined, while all data can be imported in cvs (created via Excel), Spold99, ECOSpold and SimaPro database formats (Siegenthaler et al., 2005). The database of SimaPro can include add-on databases, as a well as a library with impact assessment methods. The datasets are harmonized in terms of structure and nomenclature, in line with the impact assessment methods (JRC, European Platform on LCA). These ad-on databases include the ecoinvent v.2, US LCI, ELCD, US Input D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 59 of 97

60 Output, EU and Danish Input Output, Dutch Input Output, LCA Food and Industry data v.2, and the IVAM database. More than 2,500 substances are included in the inventory, while users can import their own database (Siegenthaler et al. 2005). These databases can be accessed and edited at any time, whereas, through the use of parameters, values and assumptions can be changed (PRé Website). Users can also define any unit and its conversion to the standard units used in the corresponding databases. Figure 29: An example of value chain representation, showing the navigation and flow windows of SimaPro (PRé Website) Regarding impact assessment methods used, SimaPro is known for its flexibility in handling different methods, including the ReCiPe, Eco-indicator 99, USEtox, IPCC 2007, EPD, Impact 2002+, CML-IA, Traci 2, BEES, Ecological Footprint EDIP 2003, Ecological scarcity 2006, EPS 2000 and Greenhouse Gas Protocol (PRé Website). Model output SimaPro supports weak point, sensitivity and uncertainty analyses, as well as normalization and weighting. Weak point analysis focuses on the identification of the hot spots in the life cycle, based on the full process tree of the model (PRé Website). Temporary changes in data, especially if these are created and saved via wizards, allow users to perform sensitivity analyses through what if scenarios (Siegenthaler et al., 2005). The uncertainty in the inventory results can be evaluated by the use of Monte Carlo analysis 2, which enable users to identify the reliability, completeness and representativeness of results throughout the model. For the 2 Uncertainty analysis is only available in SimaPro Analyst, Developer and PhD versions (PRé Website). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 60 of 97

61 comparison of the uncertainties between two LCA models, SimaPro incorporates advanced process coupled techniques; for similar processes within the two models, the same variations can be used. In general, SimaPro provides sufficient flexibility in comparing results from alternative configurations (PRé Website). Results derived from the analysis are reported in an informative way, in order to evaluate the need for reducing the environmental impacts of products/services. Users can click on a result screen and drill down to the underlying data in order to identify the most important emissions and processes. This functionality is further enhanced through filtering and grouping options, i.e. groups can be defined containing specific processes, in order to assess the contribution of various types of processes and life cycle stages to the overall results (PRé Website). Results can be presented both in a tabular and graphical form, as illustrated in Figure 30 (Siegenthaler et al., 2005). Figure 30: Presentation of inventory results in (a) tabular form and(b) in graph form, (c) per process and impact category (PRé Website) Various types of graphs can be created according to the analysis requirements, e.g. by focusing on the most important processes for a stakeholder or on the contribution of a process to impact categories. In addition a graph can be created, within the context of certain methods (e.g. the eco-indicator), by aggregating and comparing, for different systems and scenarios, the weighted results into a single score, corresponding to the overall environmental load (Figure 31). Results can also be presented as Sankey diagrams (PRé Website). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 61 of 97

62 Figure 31: Presentation of analysis results in the form of a single aggregate index (PRé Website) Finally, results can be exported to various MS Office tools, to Spold99 and the SimaPro database (Boureima et al., 2007). In some versions of the tool, users can link and store a numeric field directly to external data sources, such as MS Excel and SQL datasets. Costs The cost of using SimaPro depends on various parameters. Costs of both the professional and the educational versions vary depending to the specific version, the number of users and the duration of the license. Indefinite time licenses include a free one-year service contract, while temporary licences include service for the corresponding licence period (PRé Website). Relevance to EcoWater SimaPro focuses on Life Cycle Analysis, incorporating all the stages described in the LCA framework. Thus, it can be used to identify the weak stages and processes in a value chain (from extraction to waste disposal), based on a comprehensive set of indicators. Users can evaluate and compare alternative configurations for the improvement of environmental performance. Although SimaPro has been used in water- and wastewater-related studies, it mostly depends on predefined processes. Thus, it cannot be very easily used to build models with custom processes and uncommon attributes. Therefore, the adaptability of the tool in the specificities of the EcoWater Case Studies cannot be definitely decided at this point. Recommendations for the development of the EcoWater tools Based on the above description, the EcoWater tools can embed the following SimaPro 7 features, in order to enable users to: D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 62 of 97

63 Familiarize themselves with the graphical environment and the basic functions of the tools; Build complex systems from a life cycle perspective, Easily access all options and elements of the tool through the Graphical User Interface, Add comments to any element of a model, for easy future reference, Specify the inflows and outflows of a process by setting (at least linear) parameters, which will provide flexibility in changing values and assumptions, Interactively specify the unit of each resource, Model alternative configurations and assess scenarios by changing model element parameters, Derive a single aggregate index, through normalization and weighting, Define groups of processes (e.g. a stage) and view the results by group, View the attributes of a process input and output flows by just clicking on, View results of the input and output flows in a table, for each node and in total and filter results by selecting their frame of reference (e.g. view results per resource, process, etc.), Manage the result sets from alternative system configurations / scenarios by easily storing, reloading, exporting them to an MS Excel spreadsheet and comparing them. View results in various graph forms, e.g. through Sankey diagrams Umberto 5.5 Short description Umberto is a flexible tool for modeling complex (production) process structures, as well as for visualizing and evaluating material and energy flows or carbon footprints (JRC, European Platform on LCA). It allows users to assess products and processes according to economic, environmental and social criteria, and to optimize costs, resource use and environmental performance (IFU Hamburg Website). Model design is based on the drawing a simple network using a limited number of types of elements. The degree of detail depends on data availability and the goals of the study. It can be used to address company-specific or industry-specific needs, regardless of the size of the model (JRC, European Platform on LCA). The user interface of Umberto 3 comprises of four (4) model editing tools (panes): the Net Editor, the Project Explorer, the Property Editor and the Specification Editor (Figure 32). The Net Editor allows users to easily model hierarchical systems, by constructing process maps through the drawing of a network view of the modeled system, using predefined elements as building blocks (IFU Hamburg Website). 3 The description is based on Umberto for Carbon Footprint v1.2. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 63 of 97

64 Figure 32: Default layout of Umberto s user s interface (IFU Hamburg, 2012) It includes a drawing area and a list of available system element types, which can be drawn on it. These element types are: Processes, which are the most important element in the model. They represent activities where input flows are converted into output flows (IFU Hamburg, 2012). Therefore, processes indicate the location of material and energy transformation (Wohlgemuth et al., 2006). Places, separating processes and serving as inventories (Wohlgemuth et al., 2006). Three types of places are included (IFU Hamburg, 2012): o Input places, representing an input to a process or system, o Output places, representing an output from a process or system and o Connection places, representing connections between processes. Arrows, which connect processes with places, representing flows. Several different flows can run along the same arrow (e.g. energy and materials) (Wohlgemuth et al., 2006). Figure 33: A simple example of system modeling in Umberto (IFU Hamburg, 2011) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 64 of 97

65 The Property Editor is used to change the default attributes (including shape and color) of model elements and add names and short descriptions. The Project Explorer shows a hierarchical overview of the model, allowing quick access to all elements. The main functionality of the Specification Editor is the linking and transition of input to output flows per process. There are two ways of specifying transitions: (a) by using simple production coefficients, which define linear relations between the inputs and outputs of a process (Figure 34); knowing the value for a flow enables the calculation of values for all other flows, (b) by more complex methods which use conditional expressions for transition, in order to model non-linear relations between the input and output flows of a process (Wohlgemuth et al., 2006). Figure 34: Simple transition specification in Umberto, by using production coefficients (Wohlgemuth et al., 2006) Additionally, Umberto can take into consideration stocks and stock changes (occurring at the place elements); thus, dynamic and time-dependent processes can be modelled through the use of time series (IFU Hamburg Website). Flow calculation is done sequentially and locally, by closing data gaps in the Material Flow Network, according to process balance sheet analysis. If some flows and stocks, as well as all the production coefficients in each process are known, then all unknown flows and stocks of the system can be determined in a stepwise procedure (Möller, 2010). Umberto for Carbon Footprint is available in just one version, whereas Umberto 5 in four different versions, which include (IFU Hamburg Website): Umberto for LCA, focusing on impact assessment and evaluation for the improvement of the environmental performance of products or processes. Umberto for Efficiency, focusing on process optimization aimed at cost savings, and enhancement of resource productivity and energy efficiency. Umberto for Eco-Efficiency, integrating environmental management with cost analysis and process optimization. This version focuses on planning and assessing sustainable supply chains and production systems. It is intended to be an all-in-one solution, but no additional information was available at the time that this review was compiled. Umberto for Education. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 65 of 97

66 According to the JRC Website, analysis methodologies that can be supported by Umberto are: (i) Life Cycle Assessment (LCA); (ii) Life Cycle Inventory (LCI); (iii) Life Cycle Impact Assessment (LCIA); (iv) Life Cycle Management (LCM); (v) Life Cycle Costing (LCC); (vi) Life Cycle Sustainability Assessment (LCS); (vii) Life Cycle Engineering (LCE); (viii) Supply Chain Management (SCM); (ix) Product stewardship; and (x) Substance / Material Flow Analysis (SFA/MFA). Application examples Umberto has been widely used in industries with material-intensive and costintensive production, such as the automotive, chemical, printing, food, semiconductor and waste industries (JRC, European Platform on LCA; Siegenthaler et al., 2005). It has also been used by consulting companies and research facilities in diverse projects (JRC Website). Two application examples are briefly described below. The Mohn media GmbH printing plant The objective of this study was to build a corporate environmental balance to be used on a regular basis. Using Umberto, a material flow model was set-up, including all equipment having environmental impact, analysed to the level of individual machines. The model included approximately 450 processes, organized in hierarchical order. The data of the annual corporate environmental balance were presented to all interested stakeholders, in order to support a yearly comparison of environmental inventories. Results were used to efficiently respond to customer inquiries regarding environmental issues. The DSD waste management system The objective of this study was the analysis of all energy and material flows in the German waste industry, which could be allocated to DSD (Duales System Deutschland GmbH). The core activity of DSD concerns the handling of disposal and recycling obligations for packaging producers, fillers and distributors; additionally DSD maintains a national system for collecting, sorting and treating packaging waste, and consequently re-feeding secondary materials into the material cycle. The activities of the company encompass more than 450 contract regions, 2,000 treatment plants and 4,000 processes. They concern 97 generic treatment plant types, 150 different materials and 46 substitute materials. This complex system was modelled through the use of Umberto, in order to develop a solution for material flow management, scenario evaluation and sustainability assessment. Integration Umberto can be used to address diverse objectives and operational contexts. It can connect to standard business software like SAP, which enables managing business operations and customer relations, while avoiding redundant data entry (JRC, European Platform on LCA). Additionally, users of Umberto can store processes and subsets of a model, and reuse them in other projects (IFU Hamburg Website). Flexibility adaptability Umberto can model complex processes in detail to support decision-making. The whole value chain (from extraction to end-of-life treatment) can be modelled by using D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 66 of 97

67 distinct process nodes, so as to enable users to visualize the entire system or zoom into specific production processes (JRC, European Platform on LCA). The assessment of diverse technologies can be achieved by changing the production coefficients and recalculating mass and energy balances, either for the entire system or for any arbitrary subsystem (IFU Website). This way, causal relationships between the alternative technological configurations can be identified, further revealing the consequences of technological changes. Results are derived and presented in an effective way for scenario evaluation and comparison, enabling users to propose policies based on optimization measures, and provide support to critical decisions for the implementation of the most environmentally sensible scenario (JRC, European Platform on LCA; IFU Hamburg Website). Ease of use The documentation of the software includes a comprehensive manual and a tutorial, online support, availability of diverse case studies and a user forum (IFU Hamburg Website; Siegenthaler et al., 2005). Regular training courses, both for beginner and advanced users, are offered by IFU Hamburg. The user interface includes a graphical editor for building model networks from resizable elements, while the whole model can be viewed in a hierarchical tree view. Additional options include a grid, a ruler, as well as zoom and align choices, and users can define technical, economic and ecological properties of materials used in the model. There are predefined units for mass (kg) and energy (kj), while custom units can also be defined interactively. The definition of input/output coefficients for each process provides flexibility in the data required for modelling a system. Supported data formats include MS Excel spreadsheets, as well as the Ecospold (JRC Website). Umberto has integrated the ecoinvent LCI database, which supports more than 4,000 generic LCA data records, as well as the Sabento library, which includes modules for enzymatic processes, cell cultures and microbiological systems of production (JRC Website). All processes defined in these databases can be stored in the process library that is included in Umberto (IFU Hamburg Website). This library includes a wide range of generic upstream and downstream processes, ranging from raw material extraction to waste treatment and disposal (JRC Website). Users can enter their own inventory databases and build their own process library depending on the requirements of their project (Siegenthaler et al., 2005). Model output Umberto measures system performance according to the LCA framework. Additional impact assessment methodologies are incorporated in the tool, such as (i) Ecoindicator 99, (ii) CML 2001, (iii) Swiss Ecopoints, (iv) German EPA method, and (v) Cumulated Energy Demand. In addition, Umberto supports the creation of custom performance measurement indicators (JRC, European Platform on LCA), by enabling the aggregation of inventory results and the calculation of composite indicator values (Figure 35). The accuracy of the derived results is supported through sensitivity and uncertainty D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 67 of 97

68 analyses, which are implemented by using the Data Quality Indicator System and Monte Carlo simulations (Siegenthaler et al., 2005). Figure 35: Example of Umberto s system evaluation results, based on CO 2 emissions (IFU Hamburg Website) The derived balances (input/output flows) can be grouped, viewed and analyzed either for the whole system or for specific sections. This is performed by grouping results based on selected elements/subnets (groups of processes) or materials. Period-oriented assessments (reports per months, year, etc.) are also provided, so as to be used for the evaluation of corporate performance (JRC, European Platform on LCA). Input/output balances can be viewed both in tabular and in graphical form. Results can be further viewed as Sankey diagrams, so as to clearly visualize the contribution of each process to the corresponding environmental impacts (Figure 36). The style and width of the Sankey diagram arrows are modifiable (IFU Hamburg, 2012). D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 68 of 97

69 Figure 36: Visualization of Umberto s results in Sankey diagrams (IFU Hamburg Website) All the results can be exported to MS Excel spreadsheets; Umberto further supports EcoSpold export for independent exchange of LCA datasets (IFU Hamburg Website). Export files can contain the results for the balances, material lists, cost analysis, key performance indicators (KPI), graphs and Sankey diagrams, which all can be exported in standard formats. Results for alternative configurations can be compared, both in a table and in various types of diagrams (IFU Hamburg Website). Costs The license for Umberto for Carbon Footprint costs 1,200 per year, while a free 30-days trial with limited functionalities can also be downloaded (IFU Hamburg Website). The website does not provide cost information for purchasing Umberto 5, specifying that the cost of each version may be given through an request. Nonetheless, according to Siegenthaler et al. (2005), the cost of Umberto (in 2005) was approximately 7,500. Finally, it must be mentioned that there are various versions of Umberto 5 license (academic, business, consultation, educational, trial), with differing costs (JRC, European Platform on LCA). Relevance to EcoWater Umberto can describe both stages and specific processes in a system, and support both environmental and economic assessments. Environmental assessment is based on the estimation and presentation of various environmental impact indicators, while economic assessment focuses on Life Cycle Costing to calculate material and process costs, and identify key cost drivers (IFU Hamburg Website). This, especially after the release of the Eco-efficiency version of Umberto, allows users to assess the eco-efficiency of diverse systems, so as to gain insight into process and operation optimization (JRC, European Platform on LCA). However, the tool does not address the incentives that must be provided to individual (economic) actors, as it does not seem to support analysis of the interrelations them. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 69 of 97

70 Recommendations for the development of the EcoWater tools Through the above description, the following features of Umberto 5.5 are considered of potential usefulness for the development of the EcoWater tools, and particularly the SEAT: Construction of process maps by drawing interactively all model elements in a visual editor, with zoom in/out facilities. Elements can be selected from a short list of basic types, such as processes, places and arrows connecting them; Overview the model in a hierarchical tree-view to easily access all elements; Specification of linear production coefficients in each process, to link the input/output flows, providing flexibility regarding data collection requirements; Modeling of time-dependent processes through the use of time series and stocks; Storing of model data and results, in order to re-use and compared it with alternative technological configurations; Import and export of data and results; Grouping and visualizing the results per material or element group in tables & graphs, including Sankey diagrams. The network map of any system modelled could be build by following a simple set of rules, concerning the element types used: Processes represent activities converting input to output flows, Input nodes represent the emanating sources of all material flows, Output nodes represent the target sources of all material flows, Connection places are used for the connection of two processes; hence representing both an intermediate input and output node, Arrows are used for the connection of a process with a place, The basic calculation procedure to be run on this type of network would be an algorithm closing all gaps in data representing flows of materials. Knowing (at least) one flow and the production coefficients ensures the calculation of all system flows. The direction of the calculations can be independent of the flow of materials. 4.3 Tools relevant to Economic Value Chain Analysis Regarding the development tools for Economic Value Chain Analysis (particularly EVAT), the framework of the WaterStrategyMan Decision Support System and the SWITCH City Water Economics Model will be described, as they embed necessary economic and cost allocation principles. These principles will be further updated in EcoWater to account for additional parameters and factors (e.g. economic, regulatory, institutional) governing the allocation of technology costs among the actors involved. This will allow the EcoWater analysis to highlight the interrelations among heterogeneous actors, so as to address the concept of the meso-level and propose the most suitable policy measures. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 70 of 97

71 4.3.1 WaterStrategyMan Decision Support System (WSM DSS) The WaterStrategyMan Decision Support System (WSM DSS), is a simulation model for water resource systems that embeds hydro-economic modelling concepts, in order to provide cost-benefit assessments of water allocation schemes, water management options and integrated scenarios, combining changes in water availability, demands and infrastructure. Hydro-economic models represent spatially distributed water resource systems, infrastructure, management options and economic values in an integrated manner (Harou et al., 2009). Such models, which can be based on optimization or simulation, typically embed the concept of the economic value of water to its users, in order to drive or support water allocation decisions and evaluation of water management options based on financial costs and economic value (benefit) generated from water use. Water resource systems are typically represented through water balance components (e.g. river flows, surface water bodies, etc.), water supply infrastructure and operations (e.g. canals, reservoirs, desalination plants, water and waste-water treatment plants, etc.). These hydrologic and engineering features are included in a node-link network, where economic demands have locations (nodes) and costs (or benefits), which are incurred either on links or nodes. The network accommodates both physical and economic spatially distributed systems, and integrates all hydroeconomic model elements. Based on the above concept, the WaterStrategyMan DSS combines a hydrological model, a water demand and pollution load estimation model, and a simulation model for water allocation that minimizes water shortage under limited water availability (Manoli et al., 2001). It further includes models for economic water value and gross benefit assessments, and cost estimations. Costs can be allocated to corresponding use(r)s, on the basis of generalized graph algorithms. All the above components are integrated in a holistic environment, which allows the representation of water systems as networks of nodes, representing water supply sources, infrastructures and demands, and links, which stand for their physical or conceptual interconnections. Cost assessments in the WSM DSS expand beyond financial costs for the operation of the current water system and capacity expansions, to include also external environmental and resource costs. On the basis of the water allocation performed by the core model, the DSS estimates financial, environmental and resource costs linked to water management interventions and allocation, and distributes these to water use(r)s. The estimation of financial costs is straightforward and uses Life Cycle Costing. Estimations depend on data entered for the amortization of capital investments, specific energy consumption and cost, and other infrastructure operation and maintenance costs, as well as demand management options. A distinction is made between measures that are implemented by management authorities or water service providers (e.g. infrastructure) and costs of demand management options that are directly borne by individual users. For the assessment of economic benefits from water use, the model distinguishes between the following cases: When water is an input to a production process, such as in crop irrigation, hydropower generation and commercial or industrial uses, it is an D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 71 of 97

72 intermediate good and its demand is referred to as a derived demand. In this case, estimating the economic value of water is equivalent to isolating the marginal contribution of water to the total output value (residual value approach). When water is a final good (i.e. in residential and recreational uses), it provides direct utility to consumers, who are willing to pay a specific amount of money for it. In this case, the economic value is associated with the willingness-to-pay or (in the case that no relevant data are available), with the marginal price charged to water users. The allocation of estimated financial, environmental and resource costs is performed on the basis of quantities abstracted or pollution discharged which determine: (a) the share of capital, and operation and maintenance costs that should be allocated to each use(r) and (b) the share of environmental and resource costs incurred from overexploitation, pollution discharges or inefficient allocation. Results can be further used to define water charges and mechanisms to recover different cost elements in order to support improved recovery of costs, and their fair allocation across different user groups, and incentive pricing. Recommendations for the development of the EcoWater tools Although the WSM DSS is a tool to support water management and planning, specific elements of the approach can be considered pertinent to the value-based assessments that will be performed by EVAT. These include: The assessment of financial costs through Life Cycle Costing, accounting for operational, maintenance, capital, administrative and other costs, The allocation of financial costs to individual water users, proportionally to the water distributed to each one of them (on an annual basis). The underlying principle for this allocation is that users should pay for the part of the infrastructure that they use, The assessment of economic values associated with water use in different sectors; Cost-benefit assessments of alternative interventions (technological options), and their impact in terms of increasing the total value added from water use The SWITCH City Water Economics Model (CWE) Overview The main concept of the City Water Economics (CWE) concerns the assessment of institutional arrangements and alternative cost allocation schemes for urban water services, emphasizing on incentives provided by pricing schemes and cost allocation principles. The specific model is based on the following functions (SWITCH Project, 2011): Conceptualization of the institutional framework for water service provision, concerning all entities of a system, as well as their (financial) interrelations. Allocation of water service costs among the different water service providers and end-users categories, according to the user-pays principle. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 72 of 97

73 Analysis of alternative water pricing scenarios and mechanisms, primarily aimed at the recovery of water service costs. Water services include all activities between natural water resources and end-users, covering the supply side (abstraction, conveyance, storage, treatment and distribution) and the wastewater and stormwater side (collection, treatment and disposal). The corresponding costs concern all financial costs incurred for building, operating, maintaining and rehabilitating the infrastructure required to provide water services. The cost recovery mechanism focuses on the way through which costs are covered (e.g. charges, prices, fees and taxes paid by the users for the services received). Therefore, the application of economic instruments is linked to the way that water services are managed, focusing on: (i) actors, utilities and providers involved, (ii) the overall water governance framework, and (iii) wider policy goals. Concepts and functionalities The main concept behind City Water Economics pertains to the assessment of the implications of different forms of institutional organization and of alternative cost allocation schemes towards sustainable cost recovery. These are examined from two perspectives: (a) the perspective of those dealing with water service provision at various levels (metropolitan area, metropolitan area subset, river basin) and (b) from the social perspective, with emphasis placed on social equity, affordability and incentives offered by alternative pricing schemes and cost allocation mechanisms. Sustainable cost recovery, as defined in Rouse (2007), means that costs are recovered so that the entity undertaking water services can achieve and maintain a specified standard of service, both for present and future generations. This level of cost recovery can be achieved wholly through water charges, as in some developed countries, or through a combination of water charges and targeted, reliable, longterm government subsidies. From the financial perspective, the total costs to be recovered include operational and maintenance, capital and administrative costs (EC-CIS WATECO, 2002). The CWE model is framed around the following two concepts (NTUA, 2011): The Case, comprising a conceptualization of the framework for water service provision in a given area, as well as a scenario on alternative pricing schemes for different water services. It is based on baseline data, also including projections on water demand, supply, and future infrastructure investments, in order to analyze alternative schemes for the recovery of the corresponding financial costs (SWITCH Project, 2011). The Scenario, involving the definition of parameters for cost allocation among water service providers and the design of cost recovery schemes. Different scenarios can be evaluated and cross-compared, in order to conclude on the most suitable alternative, according to specified evaluation criteria. The distinct steps included in the specific modeling approach are presented in Figure 37. Among them, the first two concern the Case concept, while the rest concern the Scenario concept. These steps are: Case configuration, which concerns the input of baseline data for a case. These can include water flows and infrastructure elements (over a specific D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 73 of 97

74 timeframe), water service areas and reference data on disposable income and consumption distribution among different population segments in the service areas. Definition of the framework for water service provision through the mapping of actors involved in the provision of water services in an urban area (operation and maintenance of water collection, storage, treatment, distribution, wastewater collection and treatment and stormwater systems). Water service providers can include state, regional or local authorities, water utilities, etc. Cost allocation among water service providers, which concerns the attainment of cost recovery objectives through the estimation of the corresponding bulk prices, according to the user-pays principle (the payment received for water services equals to the corresponding cost of these services). This includes the definition of mechanisms for the recovery of financial costs for water services that the agents provide to each other, along the chain of water service provision. An additional (optional step) includes Life Cycle Costing for all infrastructure elements, provided that the appropriate data have been entered when configuring a case. Definition of pricing schemes, which can include both fixed and variable charges. Tariff schemes are defined at the level of water service providers who assume the management of cluster infrastructure and are responsible for metering and invoicing. They are designed separately for each water service provided by the provider, considering that a key objective is related transparency (i.e. ensuring that recovered costs correspond only to the specific water service and that the assessment of tariff elements is transparent in relation to the specific cost components). Analysis of the economic viability, from a users perspective, of potential on-site interventions for Urban Water Management, in order to provide insight on the incentives offered by the defined pricing schemes and on the subsidies that are potentially required to enable their uptake. Calculation of output indicators and sensitivity analysis, which concern: o The affordability of water charges, o Revenue patterns for water service providers, o The potential impact of the price elasticity of water demand to the range of objectives set, o The rate of return and payback period for decentralized closed-loop systems and water saving appliances. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 74 of 97

75 Figure 37: The CWE Case and Scenario analysis steps (NTUA, 2011) A key aspect of the specific modelling approach concerns incentives towards decentralized solutions (options). The utilization of alternative water sources within the urban environment (e.g. treated wastewater) often requires financial motivation to render such options economically viable. In addition to regulatory measures (e.g. water saving standards), economic instruments 4, such as eco-incentives, direct subsidies or significant reductions in the expenditure for water services through tariff reforms, can foster wide implementation and uptake. Figure 38 illustrates the economic instruments along the water cycle, as well as the scope of the CWE. 4 Economic instruments refer to mechanisms that create the economic incentives for individuals to freely opt for modifying or reducing their activities, thus indirectly producing an environmental improvement. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 75 of 97

76 Groundwater Surface water Self Supply Tradable abstraction permits Abstraction taxes/charges City Water Economics Public Water System Water prices Taxes on water supply Self-supplied uses Subsidies for water saving measures Subsidies for pollution control Potable water use Sewerage charges Taxes on sewerage charges Effluent treatment Effluent charges Sewage Treatment Tradable discharge permits Adapted from Kraemer et al., 2003 Surface water bodies/sea Figure 38: Economic instruments along the water cycle and the scope of the CWE (NTUA, 2011) The model allows the configuration of case parameters, as well as the importing of external data. The types of input files that are accepted are MS Excel, ASCII (txt) and xml files that have been generated through the Combined Water Information System (CWIS) platform. External input data concern: Clustering (i.e. specific regions) of an area, with variations in water demand requirements, household and unit block number, and population connected to the network. Infrastructure used, including (i) infrastructure costs (investment, operation and maintenance), (ii) interconnections between infrastructure elements, and (iii) the corresponding flows. On-site interventions (e.g. raintanks, on-site wastewater treatment units). The derived results can be displayed both in a tabular and graph form and can be copied or exported in order to be further processed. Output indicators calculated by the model are presented in Table 4. Table 4: Indicators for the analysis of on-site urban water management options (NTUA, 2011) Indicator category Total savings per household Indicator Reduction in mains water usage Description The total reduction in the use of mains water as a result of the intervention, throughout its lifetime (m³/household) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 76 of 97

77 Indicator category Indicator Description Total savings in expenditure for water services Reduction in outflows to the sewerage network Reduction in outflows to stormwater network Savings from the mains water bill Savings from the wastewater bill Savings from the stormwater bill Total savings The total reduction in the discharge to the sewerage network as a result of the intervention, throughout its lifetime (m³/household) The total reduction in the discharge to the stormwater network as a result of the intervention, throughout its lifetime (m³/household) Lifecycle savings from the expenditure for water supply services for an average household (Currency units/household) Lifecycle savings from the expenditure for sewerage services for an average household (Currency units/household) Lifecycle savings from the expenditure for drainage services for an average household (Currency units/household) The total reduction in the expenditure for water services (Currency units/household) Lifecycle Cost Cost The lifecycle cost associated with an UWM option, including: (a) investment, (b) operation and maintenance costs in present value terms Required subsidy or payback period Total subsidy Subsidy as share of investment cost Payback period The amount of subsidy required to make the UWM option financially viable The share of investment costs that need to be subsidized for the UWM option to be financially viable The option payback period (applicable only when the total reduction in the expenditure for water services is higher than lifecycle costs) Recommendations for the development of the EVAT According to the aforementioned description, elements of the SWITCH CWE approach which can be considered useful to the EVAT concern: The importing of baseline data for a specific case, including infrastructure elements and water flows, The mapping of actors involved in the provision of water services, The mapping of the financial interactions of all the involved actors along the value chain, The accounting, through Life Cycle Costing, of investment expenditure, fixed and variable costs; D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 77 of 97

78 The assessment of the net economic output (revenues and costs) at the level of individual actors; The assessment of the potential impact of economic instruments, such as eco-incentives, subsidies, grants and pricing/tariff schemes. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 78 of 97

79 5 Discussion and recommendations for the development of the EcoWater analysis tools Based on the information gathered from the review of existing methodological frameworks (Chapter 2) and, particularly, from the review of existing analysis tools (chapter 4), this Chapter discusses how the relevant recommendations can be used to define the overall structure of the EcoWater analysis tools. Furthermore, this Chapter discusses the functionalities that need to be embedded in these tools, and particularly in the SEAT and EVAT, which will form the backbone of the EcoWater Toolbox. The SEAT and the EVAT in pair are thought of as potentially stand-alone tools, which will be used for setting up the model representation of the systems being analyzed in the EcoWater Case Studies. Various features noted throughout the review of existing tools can be suggested as potential features to be embedded in the SEAT, the EVAT and the proposed list of Common Analysis Modules that can be integrated in the (web-based) EcoWater Toolbox. The environmental and financial analysis of production systems is a well-established practice, based on well-established methodologies and is being assisted by various well-established software tools. It should be understandable that the EcoWater tools will be based on these generic methodologies and include many features and functionalities already embedded in existing tools. However, the EcoWater tools need to be further developed, so as to address some additional requirements, unique to the EcoWater framework. The most important of these includes the provision of sufficient support for the assessment of the eco-efficiency of water-related value chains and for addressing meso-level interactions among heterogeneous actors involved in these. 5.1 The Systemic Environmental Analysis Tool SEAT The SEAT will be the main system model building tool of EcoWater. It will support the assessment of the environmental impact of alternative technological configurations of a water production and water use system, by building a model representation of the corresponding physical system, its components, processes and interactions. The SEAT will support Material Flow Analysis (MFA) towards a complete system inventory that will be used by other tools, as well as SEAT itself. With respect to the assistance provided for using the tool, it will be accompanied by a user s manual, as well as example models from the EcoWater Case Studies, so as to allow quick familiarization. Although not absolutely necessary, it would be useful if, through the web-based Toolbox, some multi-user capabilities could be implemented, allowing different users to use the tool for viewing (or even editing) the same system model and access its inventory for analysis and presentation purposes. The following basic analysis methodologies and functions are proposed to be directly supported by SEAT: Material / Substance Flow Analysis (MFA / SFA), D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 79 of 97

80 Life Cycle Inventory (LCI), and Estimation of environmental loads (resources, emissions, wastes) by type, aggregated to any level needed. Four (4) main functionality groups are suggested for implementation. They correspond to distinct steps in the system modelling procedure using the tool (Figure 39). Figure 39: Procedural view of the SEAT functionalities In more detail, functionalities include: A. Model design, based on the representation of the value chains and service systems from a life cycle perspective. This would include the specification of distinct life cycle stages and the processes taking place within them. Model design should follow a visual approach, by providing a graphical editor to interactively draw the elements comprising a system s model. The boundaries of a system being modelled can be expanded or contracted, depending on the requirements for the specific project (case study). This would provide sufficient flexibility to facilitate the application of the tool to diverse production systems and industries. Accordingly, the tool should provide all necessary building blocks (system elements) to allow the building of a network model of any system conceivable, namely: Stages, allowing the representation of distinct parts of a product life-cycle or value chain. Stages will generally serve as containers for grouping other model elements and for presenting the results of the analysis. Through the EVAT, actors will later be associated with stages, D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 80 of 97

81 Processes, which will be most important element of a model, as they represent activities in which material transformations take place, converting input flows into output flows, Input nodes, representing the sources from which (resource) flows emanate towards processes, Output nodes, representing the targets towards which flows from processes (products, resources, emissions/wastes) are directed, Junctions, used to connect processes and serving both as input and output intermediate nodes and possibly as stocking places, and Links, representing the physical or virtual paths or means, through which resources flow from/to a process (several resources may flow along a single link). Links can also be used to define causal relationships. As the design of the network model will be based on a visual approach, it would be desirable to show a grid on the editor s surface, in order to facilitate the correct placement of model elements. Zoom and align options can be included to help manage large models, while model size (number of elements) would be practically unrestricted. Finally, it is suggested that users would be able to overview the entire network model in a hierarchical tree-view, so as to easily check and access all elements used and their parameters. The result of the model design step will create the frame (database) for the system inventory, to be filled in steps B and C, described below. B. Process mapping, concerning the specification of the resource flows to and from each process of the model of the system, and the definition of relations between input and output flows. A Resource Manager Function (RMF) will be used for adding, editing and removing resources interactively. This function would enable also assigning a name, a category and a unit of measurement to each resource. There will be no restriction as to the types and variety of resources, which can include water, wastewater, intermediate materials, energy, final products, etc. However, within the concept of EcoWater, monetary flows will not be treated as resources ; financial flows would be added to the model in an entirely separate operation (using EVAT), as an element of the water management component of the system s analysis. The relations between input and output flows will be specified interactively in a Process Specification Editor (PSE). The editor would manage input and output resources and flows at a process-by-process basis. Relation factors would also be specified in PSE, determining the relations among input/output resources and flows at each process, as well as among flows of the same side of a process (input/input and output/output). These coefficients will be linear (although this is not a necessary restriction) and they could also be imported in MS Excel format, a functionality that would be useful in cases where iterations need to be performed by varying the values of the coefficients. The specification of local, process-level parameters, used to define more complex relations, will also be possible. The use of Global parameters, remaining constant throughout the D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 81 of 97

82 model, can also be implemented. This would provide flexibility to use data defined either as relative or as absolute values. C. Flows calculation, concerning the automatic calculation of all flows of resources by using the input / output coefficients and specifying at least one reference flow manually. The algorithm will calculate input/output balances, according to the balance and transfer coefficient equations discussed in Section The calculation algorithm would not necessarily follow the direction of the flow of resources; instead, starting from any known flow, all unknown quantities will be calculated iteratively, so as to close all gaps in the flow data values. Consistency and balance checks should also be performed to pinpoint possible errors in model design or the specification of the reference flow. Following that, flows should be stored in the model s system inventory. D. Flows presentation, concerning the aggregation and presentation of the results from the calculation of unknown flows. The derived results can be presented in a tabular form of calculated flows per link and per process. Users could also view the results directly, either in aggregate form (e.g. for the whole model or per stage) or interactively for each individual model element. Results could also be grouped or filtered by element and by resource type. Suitable filtering of the results would allow the extraction and presentation, in a meaningful way, of all environmental loads resulting from the system. It is further suggested that the flows of the resources, particularly environmental loads, could also be viewed as Sankey type of diagrams, in order to allow users to visualize and interpret the contribution of each process to the environmental performance of the system. Sankey diagrams could be created either for a specific resource or for all resources, depending on the requirements of each study. The above functionalities would allow users to easily assess diverse technological configurations and investigate various what-if scenarios. This can be done either by adding or deleting specific elements of the model (e.g. a process, a resource) or by editing the transition coefficients between the input and output flows of resources. Therefore, each model, including both data and results, can be stored and reused, in order to create new models and alternative scenarios. The storage of a model reduces the work effort required in the EVAT as well, as the corresponding EVAT functionalities will be based on the same system inventory. Finally, it is suggested that either SEAT databases are be compatible with specific data formats or that data conversion options are provided, so as to allow users to link with or import data from other relevant databases. In the EcoWater tools concept, the technology inventory, (which will be included in the EcoWater Toolbox, will be used as an external database. 5.2 The Economic Value chain Analysis Tool EVAT The EVAT will be used to build a representation of the water management component for the analyzed systems and estimate the economic component of ecoefficiency. The economic assessment will follow a value-based (vs. a cost-based) approach, focusing on the economic value of water to its users (Figure 40) and on the financial costs required to make water suitable for specific use purposes and for D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 82 of 97

83 safely discharging generated wastewater to the environment. The estimation of production and waste disposal costs will be based on Life Cycle Costing, using results of SEAT on resource flows. Intrinsic Value Adjustment for societal objectives Net benefits from indirect use Economic Value Net benefits from return flows Value to users of water Figure 40: Components of the value of water (adapted from Rogers et al., 1996) Six main groups of functionalities are suggested for the EVAT: A. Importing and visualizing the system inventory, produced by the SEAT, which will provide the background model for the analysis in the EVAT. This would include the representation of the water service system in terms of processes, stages, water flows and further resources used, as well as environmental loads (emissions and waste products). A visual interactive user interface similar to that of SEAT will also be provided by the EVAT, to support the functionalities described below. B. Actors mapping, involving the identification of actors involved in the value chain and assigning one or more stages (or group of processes and/or stock places) of the water service system to individual actors. EVAT should provide sufficient support for visualizing and documenting actors, e.g. by providing options to draw actor areas in the visual environment and differentiate between them, and by providing the functionality to enter information about actors in a structured way (i.e. through input and display forms), etc. C. Specification of cost components, allowing the complete identification and specification of: Parameters for costs incurred at each stage of the system, per unit of resource (e.g. /kwh of energy used; /ton of chemicals used) for each resource used. The business rules for allocating costs among all actors involved, including the assignment of each individual cost component to each actor and the definition of rules for their recovery (i.e. the prices paid for water services provided or received). D. Financial costs and value added calculation, involving the estimation of the Total Value Added throughout the water service system and of the Net Economic D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 83 of 97

84 Output per actor involved. This estimation will be based on the estimation of the economic value from water use, the total financial costs (investment, operation, maintenance, administrative and other costs) derived from the unit costs, and the results of the SEAT in terms of resource flows. Both fixed and variable costs will be accounted for. E. Analysis of economic interactions among actors, through the aggregation of the financial costs on a per stage and per actor basis. This operation provides also the capability to assess the effects of potential economic instruments (e.g. different water rates, subsidies for technology implementation) and the impact of changes in cost parameters (e.g. resulting from changes in technology market prices, energy costs, etc.). F. Presentation and Reporting. All economic costs and values specified for a system model, would be visualized in the graphical environment of EVAT, to provide a detailed view of costs and values allocations to the system s elements, useful for checking and for building of alternatives. Additional reporting functionality should be provided for presenting the outcome of EVAT s estimations for the entire value chain, as well as by Actor, in tabular and / or graph form. Derived results can also be exported in MS-EXCEL spreadsheet format, for further processing, reporting and graphing. 5.3 The functionality of the Toolbox Common Analysis Modules The SEAT and the EVAT will be used to estimate the environmental (impacts) and economic (value added) components of eco-efficiency, respectively. In order to provide maximum flexibility, the EcoWater web-based Toolbox will be the common interface among the two tools and it will further include external databases, including the EcoWater technology inventory, as well as additional tools for estimating ecoefficiency indicators. A three-layer architecture is proposed to be the basis for the ToolBox design, as illustrated in Figure 41. The upper layer would focus on defining and editing Case Studies, scenarios and indicators, as well as on evaluating and managing the derived results. The middle layer would include the two main tools (SEAT and EVAT), while the bottom layer would provide data storage and data management for all analyses, including the Case Study system inventories, scenarios, indicators and technologies. Overall, the Toolbox will embed modules for: (a) the estimation of the eco-efficiency indicators (including aggregation, normalization and weighting functions), (b) the presentation of results and (c) the creation, storage and management of alternative technology options and scenarios. In the case that other types of analyses prove necessary additional analysis modules, supporting it can be added to the ToolBox. The ToolBox will also support post-ecowater use in five (5) ways: (a) by providing a platform allowing many different users to use the tools and work concurrently of different or even the same case studies, (b) by allowing future expansions (methodological, computational and/or data resources) to be added, (c) by providing a mechanism to developers of new technologies to demonstrate the effect of their technologies on eco-efficiency, (d) by allowing policy-makers to assess impacts of D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 84 of 97

85 new regulations and (e) by transferring the knowledge and methodologies integrated into the EcoWater tools for application to other sectors. Web-Based Graphical User Interface Define and Edit View and Evaluate Case Study Manager & Editor Scenario Manager & Editor Indicator Manager & Editor Case Study Evaluator Scenario Evaluator EcoWater Tools Systemic Environmental Analysis Tool (SEAT) Economic Value chain Analysis Tool (EVAT) Data Storage Case Studies & Scenarios Indicators Inventory Technologies Inventory Figure 41: Suggested Toolbox architecture Therefore, it is suggested that additional Toolbox modules could support the LCIA and eco-efficiency frameworks, utilizing results retrieved from the SEAT and EVAT analyses. These Common Analysis Modules would also support: (i) the Management of alternative configurations, (ii) the definition and Management of Eco-Efficiency indicators and (iii) Evaluation and Comparison of alternatives (Figure 42). Figure 42: The Common Analysis Modules and their interrelations with the SEAT and the EVAT D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 85 of 97

86 In more detail: The Management of alternative configurations module will be used for defining alternative configurations in terms of technologies, as well as other parameters (e.g. market prices, technology prices, etc.). The model representation defined through SEAT will be used as the baseline and will be modified for each alternative (change of configuration for the introduction of a technology and modification of the relevant parameters). Furthermore, the module will also include functionalities for the storage and retrieval of results from the application of the two tools. The Indicators management module will be used to define rules for the estimation of the eco-efficiency indicators. This can be linked to a database of indicators, according to Case Study requirements. The Evaluation and comparison of alternatives module will be used to evaluate results, and cross-compare alternative configurations, based on the respective values of the eco-efficiency indicators. The comparison of the results can be based both on tabular and graph forms. Graphs could include predefined formats, such as the eco-efficiency portfolio (see Section 2.5), spider charts (e.g. Figure 43), cumulative (stage-by-stage) graphs of environmental impact comparing all alternatives (Figure 44), graphs comparing the total eco-efficiency performance of alternative scenarios (Figure 45) etc. Energy consumption Heavy metals Materials consumption Photochemicals Ozone depletion Waste Water consumption Acidification GHG Baseline Configuration 1 Configuration 2 Configuration 3 Figure 43: Example of comparison of results through a spider chart (adapted from Michelsen, 2006) D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 86 of 97

87 Figure 44: Graphical presentation of aggregate environmental impact and value added per stage (adapted from Michelsen, 2006) 1.7 Value performance 1 BAU A B Configuration A Environmental impact Configuration B Eco-efficiency A > Eco-efficiency B Figure 45: Example of comparison of the results through an overall eco-efficiency index (adapted from Michelsen, 2006) The evaluation of results will be aimed at supporting the development of policy recommendations, towards the implementation and uptake of the most suitable technological configurations. The analysis of costs and benefits at the level of individual actors will be of considerable help in that direction. D1.4: Review of existing frameworks and tools for developing eco-efficiency indicators Page 87 of 97