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GRANT AGREEMENT NO. : PROJECT ACRONYM: PROJECT TITLE: FUNDING SCHEME: THEMATIC PRIORITY: PROJECT START DATE: DURATION:

608775 INDICATE Indicator-based Interactive Decision Support Information Exchange Platform for Smart Cities STREP EeB.ICT.2013.6.4 1st October 2013 36 Months

and

DELIVERABLE 3.4 INDICATE Sustainable Urban Indicators Review History Date Submitted By Reviewed By Version 22.02.2016 Stephen M. Purcell, Stephen Walsh, Aidan Melia (IES), Thomas Grey Draft Conor Dowling (FAC) (TCD), John Loane (DkIT) 30.04.2016 Stephen M. Purcell, Stephen Walsh, Aidan Melia (IES) Draft Conor Dowling (FAC) 29.06.2016 Stephen M. Purcell, Stephen Walsh, Aidan Melia (IES) Final Conor Dowling (FAC)

Dissemination Level PU Public PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services)

X


Executive summary Deliverable 3.4 (D3.4) contains the Sustainable Urban Indicators (SUIs) derived for integration into the INDICATE cloud based decision support tool. There are 32 SUIs in total, which are individually broken down in Section 4.0 and Appendix A. In recognition of Task 3.3 requirements and the functionality of the INDICATE decision support tool, the SUIs were designed to be flexible in order to address the vast extent of urban energy processes without becoming unwieldy and ineffective. Equally, the SUIs were designed to utilise a broad range of data sources in order to provide an effective grounding for their functionality in the INDICATE platform. The objectives articulated in Task 3.3 were brought forward as the key “domains” under which the SUIs would be categorised. During the SUI development process, it became apparent due to the reviewed literature that the domains of the INDICATE SUI suite intersect with the conceptual definition of “sustainable development” as defined by the Bruntland Commission1 and articulated with reference to the INDICATE project in figure 1, below. The linkages between the objectives and corresponding sustainable development pillars are outlined below: Deliverable 3.4 Objs

Decision Support Tool

Sustainable Development

Reduced Costs

Economic

Reduced Emissions

Environmental

Energy Efficiency

Social

Figure 1: INDICATE Sustainable Urban Indicators and Sustainability

In order to draft the INDICATE SUI suite, this deliverable has relied on the following:       

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Outputs of Work Packages 1 and 2; Methodological requirements as identified in D3.1; Data availability as identified in D3.2; A sector specific literature review, including similar research projects, existing indices as well as energy sector standards; An investigation of data characteristics associated with the demonstration site scenarios for the INDICATE project; Consultation with industry stakeholders; and Evaluation by the INDICATE External Advisory Panel.

WCED, 1987

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The SUIs have also been developed to meet the needs of the project stakeholders including the INDICATE consortium, subject matter experts and representatives of the end user community. These indicators provide a broad spectrum through which energy and its level of use can be determined in existing urban environments. Following initial delivery of D3.4 in April 2016, further refinements and modest additions were made to the list of SUIs, as described in section 4.5 of this report. .

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Contents Executive summary ...................................................................................................................................................... ii 1.0 Introduction – Context, Overview and Framework ................................................................................................1 1.1 Overview ............................................................................................................................................................3 1.2 Deliverable Methodology ...................................................................................................................................3 1.3 Deliverable Framework ......................................................................................................................................4 2.0 The Role of this Deliverable in the Overall Project................................................................................................5 3.0 Methodological Approach ......................................................................................................................................7 3.1 Indicator Overview .............................................................................................................................................7 3.2 Indicator Compilation Process............................................................................................................................8 3.2.1 Literature Review ........................................................................................................................................8 3.2.2 Pre Drafting Considerations ......................................................................................................................15 3.2.3 SUI Selection .............................................................................................................................................15 3.2.4 SUI Goal ....................................................................................................................................................16 3.2.5 SUI Scope ..................................................................................................................................................16 3.2.6 SUI “Domains”/Framework ......................................................................................................................17 3.2.7 SUI Identification ......................................................................................................................................18 3.2.8 SUI Selection Criteria ................................................................................................................................27 3.2.9 SUI Performance .......................................................................................................................................27 3.2.10 SUI Finalisation .......................................................................................................................................28 3.2.11 SUI Weighting .........................................................................................................................................28 3.2.12 Summary ..................................................................................................................................................28 3.3 Sustainable Energy Indicator Consultation and Validation Process .................................................................29 3.3.1 Overview ...................................................................................................................................................29 3.3.2 Pre Consultation Review ...........................................................................................................................30 3.3.3 Consultation and Validation Introduction..................................................................................................30 3.3.4 Phase One Consultation .............................................................................................................................30 3.3.5 Phase Two Consultation ............................................................................................................................31 3.3.6 Phase Three Consultation ..........................................................................................................................32 3.3.7 Phase Four Consultation ............................................................................................................................33 3.3.8 Summary ....................................................................................................................................................33 4.0 Refined Sustainable Urban Indicators ..................................................................................................................35 4.1 Carbon Emissions Reduction Indicator Rationale ............................................................................................35

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4.2 Energy Efficiency Indicators Rationale ............................................................................................................37 4.3 Cost Reduction Indicator Rationale ..................................................................................................................41 4.4 Sustainable Urban Indicators Weightings ........................................................................................................43 4.4.1 INDICATE ICCI Calculation ....................................................................................................................44 5.0 Indicator Operationalisation .................................................................................................................................46 6.0 Summary and Conclusions ...................................................................................................................................49 6.1 Limitations ........................................................................................................................................................49 6.2 Possible Solutions .............................................................................................................................................49 References ..................................................................................................................................................................51 Appendix A: Final List of Indicators ..........................................................................................................................53 Appendix B: ‘Zurich List of Indicators’ .....................................................................................................................58 Appendix D: 186 ‘Long’ SUI List ..............................................................................................................................60

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1.0 Introduction – Context, Overview and Framework The “Indicator-based Interactive Decision Support and Information Exchange Platform for Smart Cities” (INDICATE) project is funded by the Seventh EU Framework Programme involving participants from across Europe including Ireland, Italy, Switzerland and the UK. INDICATE will support decision makers and other stakeholders towards transforming their cities in becoming ‘smart’. This will be achieved through the development of an interactive cloudbased tool, which will provide dynamic assessment of the interactions between buildings, the electricity grid, renewable technologies and Information Communication Technologies (ICT). This project aims to address aspects of a ‘smart city’ concept through the INDICATE decision support tool, which will plan, integrate and optimise subsystems of the overall city system including: (i) (ii) (iii) (iv)

Buildings; Energy Efficient Technologies; Renewable Technologies; and The Electricity Grid.

The INDICATE tool will be developed to be compatible with other sub-systems which can be subsequently integrated to the initial development model. The project considers urban energy usage in the wider context with an appreciation of the interrelationships that exist between the various sectors in society and the multiple components of the urban and built environment. To achieve its stated goals and required outcomes, the INDICATE tool will require a robust yet flexible suite of indicators in order to guide the determination of end users and decision makers involved with the management of urban environments and their relationships with energy consumption in the urban environment.

Figure 2 Deliverable 3.4 Deliverable & Task Interrelationships

As stated in D3.1 and reiterated in D3.2, the success of global sustainability as a concept is reliant on the creation of energy efficient cities. This deliverable posits a set of Sustainable Urban Indicators (SUIs) which attempts to quantify how interventions in the built environment on the part of developers, decision makers and citizens may move urban environments toward the goal of achieving carbon and cost reductions while contributing to the

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enhancement of energy efficiency. By deploying a tool with urban design and planning at its core, combined with the utility of accessing interventions in the built environment, decision makers and citizens can actively assess the implications of their own energy consumption patterns and adopt measures, which are conducive to creating sustainable urban environment. The Earth’s urban population currently stands at 3.5 billion people and it is estimated to grow to 5 billion within the next 20 years2; as a result, the majority of the global population will reside in cities. ‘Smart Technologies’3 are seen as a major technological step forward with respect to improving the efficiency and effectiveness of urban systems. As a result, these technologies can contribute to the sustainability of both the city and its occupants (social, environmental and economic)4. The smart city can be defined as the integration of technology into a strategic approach to sustainability, citizen well-being, and economic development. The word ‘smart’ means that modern and new approaches must be adopted for urban design, low energy & carbon public transit, pedestrianized areas, integrated zones for residential, industrial and commercial use, optimal building density, renewable energy, urban water infrastructure, transport infrastructure, etc5. Against the back drop of climate change, the urbanization the globe’s population and corresponding need for energy to power societal processes, the management and measurement of energy related interventions in the urban environment will become critical in order to enhance the overall energy efficiency of our society as well as reduce costs and emissions. In order to chart the interaction between society, energy and its consumption and generation, Sustainable Urban Indicators are required in order to quantify use and measure enhancements. There are many existing approaches to quantify the use of energy in the urban environment depending on various industry perspectives and origin of the designers. A common approach of the indices, projects and standards considered in the formation of the SUIs in this deliverable relate to the assessment of performance such as the cost of production per unit or level of service delivery per unit of investment. These metrics can also be used to show how and where amendments may be made to bring about improvements in organisational or system performance. They are most commonly used in the production of KPIs, which measure and define performance and/or efficiency. Within the more traditional context where metrics are frequently employed, the process for designing and refining the required metrics would follow through a number of stages, including: 1. Deciding what to measure/what the metric is for, why it is needed or what can be achieved by assessing it; 2. Deciding what is the best/most appropriate information or variable on which to base the metric, where it is to be sourced and how it should be processed; 3. Establishing a target/baseline against which the metric should be assessed. By following the steps in this approach, the chosen metrics will be clearly aimed at measuring a specific aspect or set of parameters, and can be tailored to identify ways of addressing perceived or identified shortcomings. This deliverable has focused on extracting and then validating a selection of key indicators, which are focused on

2

United Nations, 2012 Worden, K., et al., 2003 4 Smart Cities 5 Tang, 2011 3

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reflecting the concept outlined above, practically and feasibly in a decision support tool dealing with energy focused interventions in the built environment.

1.1 Overview D3.4 follows on from the outputs of Task 3.1, 3.2 and 3.4 (D3.1, D3.2 and D3.3) respectively as it seeks to develop a refined suite of SUIs and thereby achieve the overall aim of Work Package 3 (WP3). In addition, it has been influenced by outputs from Work Package 1 (D1.4) and Work Package 2 (D2.1). The SUIs, outlined in detail in Section 4.0, successfully facilitate the integration of the energy characteristics of buildings, in terms of consumption and generation, with other components of a city’s infrastructure and governance. This set of SUIs, will be used to aid decision support within the urban environment, through integration with the INDICATE Virtual City Model (VCM). In order for the decision platform to be transferable across a number of urban contexts, the selection of these SUIs will be normalised in order to recognise differences in climate, culture, lifestyles, governance and building typology in the settings in which they will be employed. This normalised set of SUIs will in turn intersect with the INDICATE Common City Index (ICCI), the methodological composition of which is comprehensively outlined in D3.3. The SUIs will be operationalised effectively through the development of a customised graphical user interface (GUI) in Work Package 5, with the application of the SUIs and the ICCI in scenario testing in Work Package 6. Effectively, these developments, when combined, will allow end users to identify potential energy efficiency measures, which can be implemented within urban areas, yielding clear environmental/sustainable and financial benefits within an urban context. The data underpinning these decisions can be added by users or approximated through the use of benchmark values contained in the INDICATE decision support platform. Conceptually, the diagram below outlines the evolution and influence of this deliverable in the context of the wider project.

1.2 Deliverable Methodology This deliverable has been informed by a number of research methodologies similar to those utilised in D3.1 and D3.2 as outlined in Section 1.3 of both deliverables. A brief outline of these methodologies is outlined below. The literature review undertaken for this report, followed established methods by Arksey and O’Malley (2005). In order to identify primary studies, reviews and guidance documents suitable for answering the central research question and to be as comprehensive as possible, the strategy adopted involved searching for research evidence via diverse sources:    

Electronic databases and search engines; Searching of key journals; Existing networks, relevant organisations and conferences; and Reference lists.

The review included a number of computer-based searches of Google, Google Scholar, Trinity College Dublin (TCD) online library catalogue as well as online journal databases such as Science Direct and Scopus. This was supplemented by manual searching of reference lists in the publications identified and restricted to publications in the English language. The methodology for the development of the INDICATE SUI consists of three stages. The first consisted of compiling an expansive list of sustainable urban indicators, which relate to considerations relating to energy in the urban 30/04/2016

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environment. The second phase consisted of a focused consultation exercise involving members of the INDICATE consortium, representatives of the case study sites and members of the end user community, in this case members of the urban environment professions, energy agencies and national energy research organisations. The third stage consists of the operationalisation of the INDICATE SUI suite. While this process has commenced in order Work Packages, the commencement of that process overlaps with the remit of this deliverable. The collation of existing indices, projects and energy management standards applied by key stakeholders active in the urban environment was of vital importance to the delivery of this research. Given the prevalence of such standards and the comprehensive and sector, specific examination that each affords to the facets of the intersection between the built environments it was concluded that the formation of completely new indicators would be counterproductive. Instead, an analysis of existing energy indicators was undertaken after all energyfocused indicators from existing indices had been compiled into a single, comprehensive list. By using the expertise of the INDICATE Consortium, the Expert Advisory Panel and the views of the end user community, an iterative consultation approach was employed in order to select the indicators from the expanded list referred to above. By utilising end user expertise and priorities, and while being cognisant of the need to imbue the key SUI list with the requisite flexibility to be applicable in multiple contexts, a shortlist of preferred indicators was developed. As the shortlisting process progressed, considerations relating to data availability, guided by D3.2 as well as in consultation with the case study partners were examined. The technical feasibility of operationalising the individual, shortlisted indicators was also considered and the outputs of this exercise facilitated the advancement of certain indicators and the omission of others. The result of this process led to the development of 32 SUIs, with 5 of these then selected for prototype operationalisation of the INDICATE decision support tool.

1.3 Deliverable Framework This deliverable consists of six sections in total, which present the methodology and key findings arising from the compilation of the INDICATE SUI suite.  

  

Section 1: Introduces the deliverable and provides an overview of the impetus and context underpinning the development of the INDICATE SUI suite; Section 2: Provides a background to this deliverable and looks at the role of the Sustainable Urban Indicators in the overall project context for the development of the INDICATE tool including the immediate next steps as a prelude to the development of the Virtual City Model (VCM) in WP4 as well as the evaluation which the indicator logic will undergo in WP6. Section 2 concludes with an introduction to the methodology employed in the development of the Sustainable Urban Indicators; Section 3: Describes the methodology employed in determining and selecting the Sustainable Urban Indicators best suited to assess the existing energy efficiencies in energy generation, transmission and consumption across an urban environment; Section 4: Presents the key findings relating to the Sustainable Urban Indicators. Each indicator is broken down into its constituent elements and the availability of data will be considered; and Section 5: Will provide a summary of the next steps for the application of the INDICATE SUI suite. Section 6: Will summarise and conclude this report.

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2.0 The Role of this Deliverable in the Overall Project The goal of Work Package 3 is to select a suite of suitable Sustainable Urban Indicators (SUI), which will quantify the energy characteristics of buildings as well as reflect the impact of energy related interventions in the fabric of modelled structures in the urban environment. The SUIs will be used to aid decision support within the urban environment, through integration with the INDICATE decision support platform. In order to be applicable across the EU, the selection of indicators contained in this deliverable was influenced by differences in climate, culture, life styles, governance and building typology by virtue of the data sources which will underpin the operation of the SUIs in the INDICATE decision support tool. This normalised set of indicators will inform the INDICATE Common City Index (ICCI). The methodology for the compilation of the ICCI has been developed and is contained in D3.3. The overall aim of WP3 is the development and selection of these SUIs that integrate the energy characteristics of buildings, in terms of consumption and generation, with other components of a city’s infrastructure and governance. The SUIs will be incorporated into the INDICATE decision support tool and will be operationalised through the development of an intuitive graphical user interface (GUI) in Work Package 5. The CCI and the SUIs will be evaluated through scenario testing in Work Package 6. Effectively, these developments, when combined, will allow end users to identify potential energy efficiency measures, which can be implemented within urban areas, yielding clear sustainable and financial benefits within an urban context. The SUIs are a key facet of the project as they will be central to the help and support decision making processes with the tool. D3.4 was submitted initially in April 2016 and through the process of researching and refining the indicators list to create a final list that was suitable for the decision support tool two indicators have since been excluded. While 32 indicators are listed throughout the deliverable, 30 of these will be utilised in the decision support tool. Although the full list of SUIs are present throughout the deliverable the two excluded SUIs have since been excluded from the remaining INDICATE research, as it was not deemed practical to work them into the prototype. The excluded SUIs have been highlighted where appropriate and their exclusion is set out in section 4.5 of this report. Work Package 3 began by undertaking a comprehensive evaluation of urban energy efficiency and evaluating current methodologies for monitoring and quantifying energy consumption. The outputs of that work formed D3.1 which specified the requirements needed in order to develop a robust methodological basis for the INDICATE SUI suite and its operation in the INDICATE tool. Building on this evaluation, an extensive catalogue of data, relating to energy efficiency and the factors, which may influence it, was compiled. This work is contained in D3.2. A review of the most suitable data sources for energy efficiency and potential sustainability solutions was also carried out. Drawing on the content of this work package to date, this deliverable has generated an expanded and refined list of SUIs, which can measure:  Reduce the costs to urban areas of energy provision;  Reduce CO2 production; and  Enhance urban energy efficiency. The methods of formulation and modes of use of indicators addressing sustainability and energy efficiency are constantly evolving. European projects, such as the EU Sustainable Development Strategy and the EU FP6 project STATUS utilised specially designed indicator sets monitor energy efficiency, as well as other issues relating to the sustainability of urban areas in Europe. Projects such as the Siemens Green City Index and the Global City Indicator Facility, which utilise indicators from various different urban contexts throughout Europe and beyond were used to 30/04/2016

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provide valuable insights into how to develop the SUIs in a manner that meets the transferability and flexibility needs of the project. In this way, these and other projects have been used to assist in the development of the INDICATE Sustainable Urban Indicators. Given the number of existing indices and industry standards and the attendant indicators contained therein, energy indicators determined to be of importance to the end user were extracted from these sources and validated through consultation with key stakeholders. Although these SUIs have been drawn upon a range of existing indicators, they will be refined and developed to meet the specific needs of the INDICATE project and the VCM.

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3.0 Methodological Approach 3.1 Indicator Overview Figure 3, below outlines the stages of the INDICATE Sustainable Urban Indicator (SUI) development process. The methodology employed for the SUI development is a synthesis of academic, and industry based research, combined with a comprehensive consultation process. The final output of this approach is a short list of 32 key SUIs. While conceivably, any of the indicators listed in Appendix A of this report could be developed given the availability of data and the technical capacity to operationalise them, the shortlisted indicators in this deliverable were found to be of the most interest to the end user community. By prioritising the interests of this community, the utility and flexibility of the INDICATE SUI suite and the attractiveness of the INDICATE decision support tool as an aid to the end user community could be enhanced.

Figure 3 INDICATE Sustainable Energy Indicator (SUI) Methodology Overview3.2 Compilation Phase

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3.2 Indicator Compilation Process As per figure 4 below, this phase consisted of the headline actions above which resulted in the development of 184 Sustainable Urban Indicators (SUIs). This section describes the process under which the SUIs were developed and outlines the key focuses, which shaped the indicator drafting process.

Figure 4 Phase One Overview

3.2.1 Literature Review Prior to the commencement of the indicator drafting process, a literature review was carried out with the aim of establishing a clear understanding of best practice in indicator development, structuring and management. In addition, once the SUIs had been determined the literature was again reviewed to ensure alignment with academic literature on the topic of sustainability and best practice approaches. The literature review undertaken for this Deliverable, followed established methods by Arksey and O’Malley6. The identified literature aimed to clarify indicators and metrics for the assessment of interventions to reduce costs and carbon emissions as well as enhancing urban energy efficiency. The strategy adopted involved searching for research evidence via diverse sources: • • • • •

Electronic databases and search engines Searching of key journals Existing networks, relevant organisations and conferences Reference lists from the above Consultation with industry leaders

The review included a number of computer-based searches of University College Dublin (UCD) online library catalogue, Trinity College Dublin (TCD) online library catalogue, as well as online journal databases such as Energy Policy, Science Direct and Scopus. This was supplemented by manual searching of reference lists in the publications identified and restricted to publications in the English language. The sourced literature, which will be outlined in the following subsections proved to be highly useful as it, contributed a significant number of diverse indicators across a range of domains and interest areas.

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Arksey, and O'Malley, 2005

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3.2.1.1 Indicator Selection “The Handbook on Constructing Composite Indicators: Methodology and User Guide”7 was reviewed in terms of guiding the definition of the structure of the SUIs. Regard was had to the 10-step process outlined in that publication with regard to the formation of composite indicators. The methodology advanced for the selection of the SUIs outlined in this deliverable largely adhered to the steps outlines below. Deviations occurred out of necessity arising from the fact that the operationalisation of a final set of indicators would be within the purview of future technical work packages and would be contingent on the feasibility of data integration and graphic representation. In addition to the content of the handbook, existing indices were reviewed and the following structure was devised for the SUIs. The structure was deemed appropriate as it transparently outlines the constituent elements and rationale for each SUI. The structure is set out below:     

Indicator - refers to the name of the indicator; Scale - refers to the spatial applicability of the indicator; Definition - describes the remit and focus of the indicator; Unit of Measurement - refers to the measureable attribute of the indicator; and Pattern of Use - refers to temporal and seasonal considerations, which apply to the indicator.

The Bellagio Principles summarised below express the need for ‘indicators’ and ‘standardised measurements’: When considering indicators for sustainable development, the issue can appear complicated by the lack of any firm foundation on which to base their development. Stoeckl8 suggests that we cannot measure sustainability; therefore, indicators can only provide an indication of change and will only ever be partial. It is important to note that there will always be a gap between what we are interested in and what is measured, and what we want to measure and what we can measure. This is the essence of the paradox whereby we often value what we can measure, rather than measuring what we value. The Bellagio Principles are outlined here9; 1. ‘Sustainable development’ should be clearly defined in its specific context; 2. Sustainability should be viewed in a holistic sense, including economic, social and ecological components; 3. Notions of equity should be included in any perspective of sustainable development; 4. Time horizon should span both human and ecosystem timescales, and the spatial scale should include local and long-distance impacts on people and ecosystems; 5. Progress towards sustainable development should be based on the measurement of a limited number of indicators based on standardised measurement. 6. Methods and data employed for assessment of progress should be open and accessible to all; 7. Progress should be effectively communicated to all; 8. Broad participation is required; 9. Allowance should be made for repeated measurement in order to determine trends and incorporate results of experience; 10. Institutional capacity in order to monitor progress towards sustainable development needs to be assured.8

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OECD, JRC European Commission, 2005 Stoeckl, N., Walker, D., Mayocchi, C. and Roberts, B., 2004 9 Hardi, P. and Zdan, T. 1997 8

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“Indicators quantify change, identify processes and provide a framework for setting targets and monitoring performance”10. It is important to note that indicators are not intended to accomplish a required change, but rather they act as catalysts for change, providing an ‘early warning system’, highlighting areas of concern and thereby enabling decision-makers to initiate the necessary remedial measures. Indicators of sustainable development should provide a continual assessment of the overall sustainability of a system, the indicators themselves will require constant review, and updating over time, as changes occur; implementing indicators is a dynamic process. In providing a means for monitoring progress towards sustainability, indicators are also an important communication tool: “Communication is the main function of indicators: they should enable or promote information exchange regarding the issue they address.”11 There are often complex issues and intricate processes underlying indicator work and while it is important to maintain a sufficient level of detail and transparency in the process, so that data can be tracked and decisions justified, there remains a need to achieve a certain level of simplicity in the end result. Indicators must be meaningful, useable by all, and not limited to the ‘experts’. Thus, a balance between quantity and depth of analytical indicators is needed. Public consultation and stakeholder participation throughout the indicator development process can play a significant role. An indicator should measure what those concerned are interested in and must provide meaningful information, enabling action to be taken. Having completed a comprehensive assessment of literature relating to the formation of indicators it was concluded that the INDICATE SUI suite be a synthesis of composite indicators which lend themselves to intra-national comparison and indicators which in tandem with expert evaluation. This will support decision making in respect of energy based on the accurate reflection of changes in the manner in which a specific, building, district or city manages its relationship with energy. The latter indicators examine metrics arising from the modelling of interventions to the structure or group of structures. 3.2.1.2 Conceptual Framework A conceptual framework allows for the coherent and consistent selection of indicators. This is particularly important given that any indicator selection process is value laden, for example stakeholder opinion may differ over the weight given to different criteria for a good indicator; assuming a trade-off between cost and complexity; the objectives chosen; the baseline and benchmark data etc. Thus, having an explicit framework allows a more transparent, responsive and robust process for indicator selection. Waldron and Williams describe five broad categories of frameworks12: 1. Domain-based: Addressing a variety of performance issues to include social, economic and environmental but not necessarily linking with specific management goals; 2. Goal-based: To identify indicators that respond directly to sustainability goals but do not address interrelationships; 3. Sectoral: These respond to the function of a specific management group, and thus are useful in assessing management response to specific issues; 4. Issue-based: Often provide a short-term response to address the ‘issue of the day’; longer term sustainability implications may be overlooked; and

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Crabtree, B. and Bayfield, N., 1998 Smeets, E. and Weterings, R., 1999 12 Waldron, D. and Williams, P.W., 2002 11

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5. Causal frameworks: These assess the existing conditions, stresses and responses but within-domain interactions are overlooked Kelly and Baker13 put forward the following criteria: Indicators should be adapted to suit local needs, consist of both objective and subjective data and make links between different issues. In addition, indicators should be based on: Validity (acceptable, believable; related to a higher order theme, related to theory): Reliability (can be used over time, and across space but only within the region): Data Availability and Accessibility; (qualitative and quantitative): Methodology (timely, uses existing data, considers scale; considers capacity to collect and use data) and relevance (to objectives; beneficial to investors/taxpayers; links to other indicators). There are many examples of ‘checklists’ for indicators available in the literature (see table 1) and these can provide a useful tool for reviewing indicators as they are developed, highlighting any tensions which may mean the indicator ultimately needs to be abandoned. Table 1: A ‘Good’ indicator Checklist 14

A ‘Good’ indicator 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.

Characteristic Measurable Sensitive Economically Viable Acceptable and accessible Useable and easily interpreted Reliable and robust Verifiable and replicable Participative process Specific Timely Transparency Relevant Scientifically well founded

Note Necessary data must be available For spatial and temporal change Cost effective Plain language Meets the needs of stakeholders Clearly relate to outcomes Show trends over time In methodology and selection Applicable in different cities -

A sound theoretical framework is the starting point in constructing composite indicators. The framework should clearly define the phenomenon to be measured and its sub-components; as part of the INDICATE decision support system the indicators must accounts for all major systems and activities relevant to developing energy-efficient cities. The indicators will aid in the creation of a ‘Smart Economy’, integrated smart urban planning tools including architectural master planning, detailed energy optimisation, and environmental analysis. Composite indicators in newly emerging policy areas, e.g. competitiveness, sustainable development, e-business readiness, etc., might be very subjective, since the economic research in these fields is still being developed. Transparency is thus essential in constructing credible indicators. This entails: 13 14

Kelly, G. and Baker, B.L., 2002 Whate V., et al., 2006

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1. Defining the concept: The definition should give the reader a clear sense of what is being measured by the composite indicator. It should refer to the theoretical framework, linking various sub-groups and the underlying indicators. For example, the Growth Competitiveness Index (GCI) developed by the World Economic Forum is founded on the idea “that the process of economic growth can be analysed within three important broad categories: the macroeconomic environment, the quality of public institutions, and technology.” The GCI has, therefore, a clear link between ‘the framework’ and the structure of the composite indicator. Some complex concepts, however, are difficult to define and measure precisely or may be subject to controversy among stakeholders. Ultimately, the users of composite indicators should assess their quality and relevance; 2. Determining sub-groups: Multi-dimensional concepts can be divided into several sub-groups. These sub-groups need not be (statistically) independent of each other, and existing linkages should be described theoretically or empirically to the greatest extent possible. The Technology Achievement Index, for example, is conceptually divided into four groups of technological capacity: creation of technology, diffusion of recent innovations, diffusion of old innovations and human skills. Such a nested structure improves the user’s understanding of the driving forces behind the composite indicator. It may also make it easier to determine the relative weights across different factors. This step, as well as the next, should involve experts and stakeholders as much as possible, in order to take into account multiple viewpoints and to increase the robustness of the conceptual framework and set of indicators; and 3. Identifying the selection criteria for the underlying indicators: The selection criteria should work as a guide to whether an indicator should be included or not in the overall composite index. It should be as precise as possible and should describe the phenomenon being measured, i.e. input, output or process. Too often composite indicators include both input and output measures. For example, an Innovation Index could combine R&D expenditures (inputs) and the number of new products and services (outputs) in order to measure the scope of innovative activity in a given country. However, only the latter set of output indicators should be included (or expressed in terms of output per unit of input) if the index is intended to measure innovation performance. The strengths and weaknesses of composite indicators largely derive from the quality of the underlying variables. Ideally, variables should be selected based on their relevance, analytical soundness, timeliness, accessibility, etc. While the choice of indicators must be guided by the theoretical framework for the composite, the data selection process can be quite subjective as there may be no single definitive set of indicators. A lack of relevant data may also limit the development of sound composite indicators. Given a scarcity of internationally comparable quantitative hard data, composite indicators may include qualitative soft data from surveys or policy reviews.15 Proxy measures can be used when the desired data are unavailable or when cross-city comparability is limited. As in the case of soft data, caution must be taken in the utilisation of proxy indicators. To the extent that data permit, the accuracy of proxy measures should be checked through correlation and sensitivity analysis. In designing a framework, close attention should be paid to whether the indicator in question is dependent on size-related factors. To have an objective comparison across small and large cities, scaling of variables by an appropriate size measure, e.g. population or populated land area is required. 15

Nardo, M., et al. 2005

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The quality and accuracy of composite indicators should evolve in parallel with improvements in data collection and indicator development. The current trend towards constructing composite indicators of city performance in a range of policy areas may provide further impetus to improving data collection, identifying new data sources and enhancing the comparability of statistics. Poor data will produce poor results, from a pragmatic point of view; however, compromises need to be done when constructing a composite: What is essential is the transparency of any compromises. 3.2.1.3 Sustainability Sustainable development was defined by the World Commission on Environment and Development (WCED) as; "development that meets the needs of the present without compromising the ability of future generations to meet their own needs"16, this has been widely cited by many authors who adopted varying stances on ‘sustainability’. Haughton and Hunter17 argue that the concepts of building for the future, resource equity and environmental impact must underpin the process of sustainable development, such that the principles of inter-generational equity and trans-frontier responsibility are at the forefront of sustainable development policy. These concepts continue to be widely debated and most recently, world leaders discussed how to address sustainability issues at the 2015 United Nations Climate Change Conference in Paris18. The concept of sustainable development is based on the observation that a cities’ economy, environment and wellbeing can no longer be separated. The definition of sustainable development is often quoted from the World Commission on Environment and Development: ‘development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs’.19 The fundamental principle behind this definition is to accept that all human individuals have equal rights, whether living today or in the future. This gives an overview of the concept rather than giving any rigid rule that can be applied right away. Therefore, sustainability can and will be interpreted differently by different people, evoking the critique that the term sustainability could mean almost anything.20 However, the room left for interpretation proves to be valuable as the multi-dimensional character of sustainability is fundamental to the design of these indicators. The integration of considerations relating to the built environment, energy use and sustainability is of key importance to the INDICATE project. Kua, H.W. and Lee, S.E., 2002 as well as Mitcham, 1995 outline that considerations relating to the quantification of sustainability in the built environment are mixed. They cite Kohler, 1999, who characterises sustainable building as outlined in figure 5, below.

16

Brundtland, G.H. and Mansour, K., (WCED). 1987 Haughton, G. and Hunter, C., 1994 18 United Nations 19 WCED, U., 1987 20 Mitcham, C., 1995 17

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Figure 5 Kohler, 1999 Dimensions of Sustainable Building

The conceptualising of sustainable building as outlined above couple with the objective areas outlined in Task 3.3, the interrelationships drawn between the pillars of that concept and the objective areas of the INDICATE SUI suite are outlined in figure 6 below.

Deliverable 3.4 SUI Domains

INDICATE SUI Suite

Sustainable Development

Reduced Costs

Economic

Reduced Emissions

Environmental

Energy Efficiency

Social

Figure 6 INDICATE SUI Suite Task 3.3 Objectives Interrelated with Sustainable Development

The linkages between the above SUI “domains� and the concept of sustainable development as outlined above are practical and based on a consideration of decision makers, built environment professionals and citizen who reside, work and recreate within the built environment. The reduction of costs has appreciable economic effects on the dynamics of generation and consumption in the built environment. Positive energy interventions, which reduce carbon emissions, have quantifiably positive effects on the environment. Measures that enhance energy efficiency can have positive social consequences such as the alleviation of fuel poverty.

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3.2.2 Pre Drafting Considerations In line with the rationale advanced in Keirstead21, before the drafting process commenced, the goal and scope of the indicators was explored in order to provide a foundation upon which the indicators could be based. The goal of the indicators with reference to their role within the INDICATE tool was established, in line with the expectations of T3.3 and D3.4 as per the INDICATE Description of Work. The goal of the indicators is to reflect changes arising from interventions in the simulated built environment in a manner, which is accessible to the citizen, decision maker as well as professional practitioner. It was envisioned that a number of the Sustainable Urban Indicators would be applicable across the spectrum of spatial scales outlined above, depending on the availability of accurate data and technical feasibility. Due to the expected interrelationship between those domains, the framework for the INDICATE suite would be advanced as a comprehensive, responsive and sufficiently nuanced feature of the INDICATE platform in respect of its abilities to reflect the impact of modelled energy interventions on modelled structures. In tandem with the above and drawing on work undertaken and completed in T 2.2/ D 2.2 by Trinity College, consideration was given the need to incorporate an acknowledgement of temporal as well as seasonal influences on the use of energy. As a result, a seasonal and temporal attribute was built in to the indicator drafting process in order to accurately indicate the energy dynamics of the chosen intervention at a specified spatial scale where the data permits. Figure 7 below references the process that informed the development of the INDICATE suite of indicators.

Figure 7 Indicator Selection Process22

3.2.3 SUI Selection The purpose of this section is to outline the manner in which the SUI selection process was undertaken. The rationale for dividing the indicator development process as depicted in figure 3 arose from the need to establish a comprehensive assessment of the existing academic work and professional practice in the field of sustainable energy research, to comprehensively collate existing energy focused indicators and to assess that body of indicators against the needs of the end user community. By combining this with existing indices relating to energy and

21

Keirstead, J (2007)

22

Keirstead, J. 2007

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sustainable communities with the aforementioned, the indicators could then be assessed with reference to their relevance to the identified domains of the INDICATE tool. Morse23 questioned the quest for quantitative indicators, highlighting how qualitative measurements may provide better understandings of sustainability, given its socially constructed nature and the need for perceptions to change in order to achieve more sustainable behaviour. Considering the potential for indicators to mislead, or be manipulated and ‘cherry-picked’ to show what is desired, Meadows24 warns that, as an integral part of the decisionmaking process, indicators can be a ‘dangerous tool’. The desire of stakeholders and decision-makers, for simplicity, comparability and interpretability of indicators may inadvertently result in over-aggregation, over-simplification of complex relationships. Consequently, this may mislead or result in false representation.25 Achieving a compromise by including qualitative and quantitative based indicators can, in theory, offer a solution, but in practice may be far more difficult to achieve. It is important to keep sight of the overall aim of developing indicators; what are they aiming to show and what is it that they are supposed to achieve? During the development of the SUIs, it was determined during consultation that the incorporation of qualitative indicators would present a technical challenge as well as one of transferability in terms of normalising such indicators across a variety of socio-environmental, cultural and economic contexts. 3.2.4 SUI Goal The goal of the SUIs devised in this deliverable is to facilitate the creation of a solid evidence base upon which decisions relating to interventions in the urban environment can be assessed and validated against the principles of sustainable development. Additionally, the SUIs were developed to illustrate existing conditions and to identify where best to target interventions across the urban environment. The indicators would need to be able to accurately represent the impact of modelled interventions in respect of the following components of the urban environment as characterised in D2.1. These components are outlined below: 

Energy sources: Sites where energy is generated (supply-side)

Energy sinks: Sites where energy is consumed (demand-side)

Energy networks: The infrastructure that distributes energy between the sources and the sinks

Energy storage: Sites where generated energy may be retained for later use

Socioeconomics: The impact of city inhabitants on energy supply and demand.

3.2.5 SUI Scope The scope of the Sustainable Urban Indicators relates to two key areas, the first is their feasible area of spatial applicability and the second related to the manner in which the interventions are captured and represented as a unit of measurement with an associated range of effectiveness in line with the goal stated above. The spatial applicability of the indicators for the purposes of the indicators drafted by the INDICATE project are outlined below.

23

Morse, S., 2003 Meadows, D.H., 1998 25 DSCWG 2001 24

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City Level: Indicators at this scale provide a high-level assessment of the performance of urban environments in respect of energy consumption, generation and potential for efficiency focused enhancements. District Level: Indicators at this scale provide a more focused and detailed assessment of energy generation and consumption at the sub city scale. This focus is valuable as urban environments are composed of sub city districts, which are distinctive in terms of their energy characteristics. Developing metrics at this spatial scale requires cognisance of the fact that the definition of a “district” or sub city unit varies from country to country. As such the functionality of the INDICATE decision support will need to have regard to the need for flexibility in defining study areas at the sub city scale. Building Level: Indicators at this scale are geared toward the direct assessment of energy related interventions on a building or small cluster of buildings.

The spatial scales outlined above are not mutually exclusive in terms of indicators as some indicators maybe applicable across each spatial boundary. The spatial scale at which the SUIs are applicable (as outlined in Section 4 and Appendix A of this deliverable) is indicative. The scalability of the SUI can be facilitated through the availability of data to support its operation at sub city and building level. In addition to the spatial scale of the SUIs and their applicability, there scope is required to cover the elements of the built environment, which have a relationship to energy, as characterised in D2.1 and outlined in table 2 below. City subsystem Supply

Component  Centralised power stations (e.g., coal-fired, gas-fired and nuclear power stations)  Distributed power (e.g., localised photovoltaic, combined heat and power (CHP) plants)  Renewables (e.g., hydroelectric dams, wind farms) Demand  Buildings (residential, commercial, industrial)  Transport networks (electric rail, electric vehicles)  Public services (street lights, telecoms, water) Energy  Electricity (transmission, substations) networks  Gas (transmission lines, reservoirs) Energy storage  Bulk storage (e.g., pumped storage hydroelectricity, compressed air, fly wheels)  Micro-storage (e.g., PV batteries, electric vehicle batteries) Socioeconomics  Dynamic pricing (Time of Use tariffs, electricity peak demand)  User behaviour (occupants, energy consumers) Table 2 SUI Energy System Scope

3.2.6 SUI “Domains”/Framework In order to develop indicators which, align with the requirements of the end users and stakeholders as well as the rationale for the INDICATE tool, “domains” which reflect the priorities of both were considered. The “domains” which were decided upon are outlined below.

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Cost Reduction

Emissions Reduction

Increased Energy Efficiency

Figure 8 INDICATE Tool Domains

The high-level domains reflect the needs of decision makers, urban environment professionals as well citizens when it comes to cataloguing the impact of interventions in the urban environment, which generate savings, reduce carbon and other emissions into the atmosphere and enhance the overall energy efficiency of the urban environment. 3.2.7 SUI Identification Energy indicators, which relate to the domains outlined above, were extracted from a range of existing indices. At the initial phase of compilation process, the indicators taken from existing indices were cross-referenced in order to determine if they arose in more than one index. The rationale for this was to inform the compilation of the INDICATE list so as to ensure that standard and commonly used indicators were incorporated within the initial INDICATE suite of indicators. Niche or uncommon indicators amongst those selected were evaluated on their merits and capacities to contribute to the overall INDICATE decision support solution. Niche indicators found to be of merit were retained while those whose focus did not align with the project’s remit were culled. Past deliverables were also evaluated (specifically D1.4) in order to incorporate stakeholder desired indicators. D1.4, “Report on the data analysis of inputs from stakeholders” proved useful in terms of the contextualizing the requirements of stakeholders and end users. The findings of this deliverable guided the manner in which social, economic and environmental markers could be integrated with the established key objectives of Task 3.3 which prioritise energy efficiency, carbon reduction and cost reduction as the key categories by which indicators could be classified. In addition, this deliverable provided insights relating to the intersection between stakeholder perspectives on the urban environment and as well as the provision and use of energy within its system. The actions undertaken to compile D 1.4 resulted in the development of indicators, which reflect the interests of stakeholders with reference to their experiences of and interactions with the urban environment. The indicators arising from the stakeholder consultation were categorised under the headings below;     

Demographic dynamics, Accessibility to services and green areas, Urban mobility and transport, Health and safety, Awareness and behaviours.

D 1.4 proved useful in terms of informing the preliminary development of the indicators outlined in Appendix A. The focus of the indicators contained within D 1.4 however did not align congruently with the stated objective of D 3.4, which is to devise Sustainable Urban Indicators, which focus on the domains of cost reduction, energy efficiency and reducing carbon dioxide emissions. D2.1 “Characterization of the city as an overall integrated system” of WP 2 30/04/2016

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was employed in order to investigate the “systems of a system” approach to the urban environment. The deliverable was effective in the manner in which it considered the components of the built environment and as such, it facilitated the drafting of indicators which are attuned to the interrelated nature of the urban environment and as such the manner in which one indicator may be utilized to correlate the impact of interventions in a manner which is reflective of the interconnected nature of urban environment systems in relation provision and consumption of energy. In terms of key outputs, this deliverable identified key components within the urban environment, which influence energy performance. The characterisation of the city and its energy network in the manner outlined above assisted in the development of indicators, which align with the constituent components of the urban environment under the three objectives specified under T 3.3. D3.1 and D3.2 contributed significantly to the drafting and refinement of the indicators. The manner in which these deliverables contributed in terms of assessment metrics is detailed in this section. D 3.1, “Report on current energy efficiency monitoring and quantification methodologies” established the existing state of the art (SOTA) relating to the quantification of energy efficiency methodologies which are already in existence so as to establish a benchmark for the INDICATE tool to surpass. In addition, D 3.1 examined the requirements that the developed INDICATE tool would have surpassed in order to be considered an effective tool for the development of solutions to the challenges of urban energy efficiency. The basic and detailed requirements determined by D 3.1 are outlined below. Basic Requirements List:       

Methodology Objectives: State clear objectives for the tool Methodology Process: Create a coherent methodology framework Project Stages: Develop clear planning, design and operation stages Development Type: The tool should cover all development types (renovation/extensions/etc.) Development Use: The tool should cover all development uses (residential/commercial/etc.) Development Scale: Consider all necessary variables that influence energy use and performance in the urban area (weather/production levels/occupancy.) Assessment Criteria: The tool should cover all development scales in an urban environment (planning and design/operation management/retrofitting.)

Detailed Requirement List: 

Data Requirements: The INDICATE tool should include data requirements that are specific, measureable, achievable, realistic, and timely (SMART). Required evidence should strike an appropriate balance between prescriptive and subjective elements and draw on best practice aspects of such. The development of the INDICATE tool should consider opportunities for the development of common international metrics, having regard to the pan-European nature of the project (e.g. the ‘Common Carbon Metric’ for the measurement of a building’s carbon footprint); Innovation: The INDICATE tool should facilitate and encourage innovative practices in energy efficiency, to promote the continued evolution of sustainability in urban environments. Technological and social innovation is rapidly shaping the development of European urban environments. Relatively recently the idea of technological change was applied to Irish mutant building types such as the 1970’s office blocks built in places such as along Mount Street Lower in Dublin which mainly replaced Georgian terraces of

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houses. In many cases, this has involved seriously considering replacement rather than upgrading for energy efficiency or conversion back to the buildings original use. Solutions: The INDICATE tool should consider option development and the signposting and testing of energy efficiency solutions, as part of its use in the design process. Conducted research shows that existing methodologies are used on a ‘trial and error bases, and do not proactively signpost options or suggest solutions to address troubleshooting aspects of development design. As a decision support tool, INDICATE has the potential to address this shortcoming and add significant value to energy efficiency assessment processes; Timeliness: The INDICATE tool should be time effective to use, to enable the efficient determination of appropriate options and solutions. Research highlights that existing methodologies are time intensive to use. This can be a barrier to uptake and a more streamlined approach, which incorporates option development and solutions, will deliver improved efficiencies in approach; Education: The INDICATE tool should cater for the education of users with varying levels of knowledge and experience in relation to energy efficiency. Most methodologies are aimed at expert users and do not include direct educational elements. This represents an opportunity to distinguish the INDICATE tool from others by displaying and signposting best practice and educating about energy efficiency at different technical and non-technical levels. This is an identified chance to make this educational element an integral part of the tool at the design stage, rather than it functioning as an add-on. The ‘SPECIAL’ project (Spatial Planning and Energy for Communities In All Landscapes) aimed to foster the exchange of experience and competence building among national and regional TPAs, to demonstrate the integration of sustainable energy into spatial planning strategies at local and regional levels. A similar approach may be applicable to the INDICATE tool. Market Labelling: The INDICATE tool should include some element of green market labelling, having regard to the growing importance of smart and sustainable cities. All of the key energy efficiency methodologies in the market promote themselves as green market labels. Increased awareness of energy efficiency and its importance in the built environment have turned public attention to more efficient, “green” building. There is empirical evidence that “green” labels positively affect the financial performance of urban areas and cities in particular, are striving to transmit their green credentials. Within this, a green market-labelled INDICATE tool could be an attractive proposition, proactively fostering inward investment into areas. These labels may include; Cradle to Cradle awards; Green Seal; Forest Stewardship Council label; or the Energy Star certificate; Compatibility of Approach: The development of the INDICATE tool should consider other internationally recognised assessment tools, to foster potential synergies in approach and uptake in use. The potential value of establishing common international metrics has been outlined previously. It is important that the development of the INDICATE tool considers compatibility with other methodologies in an international context. It is not uncommon for buildings to seek dual certification or to use alternate methodologies for renovation/expansion, and general compatibility will help maximise related opportunities, as well as extending the geographic reach of the tool; Review: The INDICATE tool should include appropriate provisions, including carefully devised energy efficiency indicators, which monitor the success or otherwise of its application and performance, as part of any continuous improvement strategy. Methodological approaches to the assessment of energy efficiency exist in a cycle of continuous improvement and the ability to flexibly adapt to changing circumstances is

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vitally important. The smart cities field of research is evolving all the time and an effective plan-monitormanage approach to the review of the INDICATE tool will ensure that it maintains its ‘state of the art’ status. D3.2 resulted also in the delivery of the data catalogue which outlined the range of data types which would be of importance to the development of the INDICATE tool as well as the Sustainable Urban Indicators. The data catalogue was developed in a manner which recognised the requirement that INDICATE tool to be applicable across most urban contexts. A key requirement, in this regard, was the need for commonality and standardisation of data characteristics, associated attributes and accepted terminology in order to present a catalogue that represents most urban contexts within the EU while at the same time providing an extensive data coverage best suited to determine the efficiencies and potential solutions in energy generation, transmission and consumption. Accordingly, eight categories of data were identified as being an appropriate data classification that corresponds to these requirements. 

Data corresponding to these categories were presented in a manner that captured, where possible, the key characteristics, attributes, units, sources and reference standards. In addition, in keeping with the findings presented in D3.1, where possible each data type was delineated according to their spatial scale of applicability based on micro, mezzo and macro scales.

Key to the identification of SUIs was the review of existing international, European and national projects, indices and industrial standards in order to determine the range of existing indicators, which quantify the intersection of energy related considerations and the urban environment. The table below summarises the European projects, which were reviewed in order to generate the expanded list of SUIs.

Project

Goals

Summary

European Common Indicators (ECI) (19992003)

Monitor the EU Sustainable Development Strategy (EU SDS) in a report published by Eurostat every two years. The ECI consists of 155 indicators, presented in ten themes, for use at city or regional level

Intended to give an overall picture of whether the European Union has achieved progress towards sustainable development in terms of the objectives and targets defined in the strategy.

LASALA - Local Authorities’ SelfAssessment of Local Agenda 21 (1999-2002)

The evaluation of LA21 and of local SD across 230 local governments in Europe; to provide data for the European Sustainable Cities and Towns Campaign and assist in the future development of local SD policy

A Good Practices Report of 24 case studies of local authorities in Europe; this allows local authorities to selfassess their LA21 activities and to benchmark their individual responses against the LASALA database

IANUS - Indicators to Assess New Urban Services (2000-2003)

Evaluate public urban facilities and services in order to determine impact on performance indicators such as functionality, end user satisfaction, cost and environmental impact

A Handbook of Indicators Systems to assess new urban services was published

CRISP - A European Thematic Network on Construction and City Related Sustainability Indicators (2000-2003)

Develop indicators that could define and measure the performance of Europe’s construction industry and to give assessment tools to produce more sustainable building and urban development projects

Over 500 indicators along with a considerable number of issues related to sustainable construction were identified and developed

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PASTILLE - Indicators into Action (2000-2002)

To evaluate if and how specific SD indicators were influencing local decision-making in 4 European cities and towns

Creating an integrated process of urban governance

ECOPADEV -Development Strategies for ‘‘Eco’’ Industrial, Technology and Science Parks (2001-2003)

To define and collect data to build indicators of ecoefficiency that could transform industrial parks into ‘eco’ industrial parks

Resulted in a web-based tool which has been used by Europe’s urban planners, (online access is no longer available)

PROPOLIS - Planning and Research of Policies for Land Use and Transport (2000-2004)

To define indicators and create a virtual model to monitor transport and land-use policies and forecast future paths in 7 cities across 6 European countries

The PROPOLIS Final Report concluded that the approach developed could be transferable and similar strategies could work in other European cities

ECO DEV - SD at local and regional levels: methods and techniques to support eco-sites and monitor urban sustainability (2003-2004)

The aim was to produce monitoring tools and common indicators to evaluate sustainable development at the local level and to develop and implement the concept of eco-sites at the EU level

The project explicitly aimed to support the European Spatial Observatory Network and monitoring of environmental protection of Structural Funds

TISSUE - Trends and Indicators for Monitoring the EU Strategy on SD of the Urban Environment (2004-2005)

Analyse trends, determine progress and compare strategies towards urban SD. Define a harmonised set of indicators and analyse the conditions of how to increase the acceptance of harmonised indicator sets in cities through an online database

The 41 indicators in the Final Report are recommended for a harmonized application throughout Europe, through a gradual approach to develop a more comprehensive approach to define SDIs; assess feasibility more thoroughly

STATUS - Sustainability Tools and Targets for the Urban Thematic Strategy (2005-2006)

The STATUS project developed a package of local sustainability indicators for local governments to self-assess sustainable development progress

The project defined a set of 64 indicators under 10 themes to be usable by local authorities and to implement the Urban Thematic Strategy

INSURE - Flexible Framework for Indicators for SD in Regions using system dynamics modelling (2004-2007)

To develop a common flexible European framework for sustainable development indicators at a regional scale

The INSURE project sought to design a generic framework with the aim to determine SD of a region while allowing flexibility to include regional characteristics

Informed Cities (20092012)

Enhance the connectivity between research and policy-making in SD with a focus on two particular tools for urban management: the Local Evaluation 21 (LE21) and Urban Ecosystem Europe (UEE) - a set of 53 common indicators on urban SD

EU Reporting Mechanism for Urban Sustainability; 53 indicators were established to benchmark cities’ performance against each other. Common indicators are mostly environmental (air, water, noise, urban design, mobility, energy, waste, ecomanagement)

CAT-MED - Changing Mediterranean Metropolises Around Time (2009-present)

Highlight where Mediterranean cities’ ability to save natural resources and reduce CO2 emissions. A system of common indicators was developed representing a tool to evaluate urban policies in a

20 indicators were developed in common by the city partners, organized around four axes: territorial management and urban design,

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sustainability perspective. The current goal is to consolidate a common system of indicators which enables tracking the evolution of urban sustainability and analysing the effectiveness of the applied public policies

mobility and transport, natural resources management and social and economic cohesion

CDP Cities - Carbon Disclosure Project (2011)

In November 2010, through a partnership between C40 and CDP, New York Mayor and C40 Chair Michael Bloomberg invited the C40 cities (40 participating cities and 18 affiliate cities) to report their climate change-related data to CDP

The results from the CDP Cities 2011 report show an encouraging movement by many of the world’s largest cities; The results indicate a strong start but also indicate a number of areas where cities need more support

URBAN-NEXUS (20112014)

The ‘‘Integrated Information and Monitoring’’ theme tackles issues such as the databases and information availability, transparency, accuracy and accessibility, quality assessment and data harmonisation

It is closely linked with the Directive 02/2007/ EU-INSPIRE implementation in the urban management sector. This project is still under development

GCIF - Global City Indicator Facility (2007-2014)

The Global City Indicators Facility is a program of the Global Cities Institute. The aim is to establish a globally standardized methodology that allows the comparison among cities in terms of performance

All members cities can measure and report their 'performance' through a set of indicators structured around 22 themes related to the city services and the quality of life. A total of 70 indicators were established.

Table 3: European and International projects developing sustainable indicators

In addition to the projects examined above, existing indices were examined in order to further add to the expanded list of SUIs that would be considered by the INDICATE consortium and the end user community. Of particular interest was the Siemens Green City Index, which is based in Europe with similar aims to the INDICATE project therefore these indicators were deemed to be more significant than some of the other projects mentioned:

Project

Goals

Summary

SIEMENS GREEN CITY INDEX (2012)

Established in order to measure and rate the environmental performance of 30 leading European cities, both overall and across a range of specific areas

The cities were scored on the basis of 8 categories and 30 indicators; the results enabled to quantify and compare environmental performance

The Siemens Green City Index26 aims to measure and compare 30 leading European Cities as far as the environmental performance is concerned. The methodology was developed by the Economist Intelligence Unit in cooperation with Siemens, in order to help stakeholder groups to assess their city's performance against others. The European Green City Index differs from other researches because the data needed to create the index and the index itself was calculated independently, instead of waiting for voluntary submissions from Local Authorities. In general, the results show:

26

https://www.siemens.com/entry/cc/features/greencityindex_international/all/en/pdf/gci_report_summary.pdf

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    

The dominance of the Nordic Cities upon the others in the overall index; Copenhagen, Stockholm and Oslo are in the first three positions: Wealth and a high overall ranking on the index are strictly correlated; wealthier cities have more resources to invest in energy-efficient infrastructure and can afford specialist environmental managers; The Eastern European cities which perform best are Vilnius (13th place) and Riga (15th place); the other east European Cities rank at the bottom of the index; Little overall correlation between city size and performance is showed in the index; however, the leading cities are smaller, with populations of less than 1 million; City characterised by an active and strong civil society perform well in the index.

In this case, the index is calculated taking into account 30 indicators under 8 categories per city. CATEGORY CO2

Energy

INDICATOR CO2 emissions CO2 intensity

DEFINITION Total CO2 emissions Total CO2 emissions

CO2 reduction strategy

An assessment of the ambitiousness of CO2 emissions reduction strategy Total final energy consumption Total final energy consumption

Energy consumption Energy intensity

Renewable energy consumption Clean and efficient energy policies Buildings

Transport

Energy consumption of residential buildings

Energy-efficient buildings standards Energy-efficient buildings initiatives Use of non-car transport Size of non-car transport network

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The percentage of total energy derived from renewable sources, as a share of the city's total energy consumption, in terajoules An assessment of the extensiveness of policies promoting the use of clean and efficient energy Total final energy consumption in the residential sector,

An assessment of the extensiveness of cities' energy efficiency standards for buildings An assessment of the extensiveness of efforts to promote energy efficiency of buildings The total percentage of the working population travelling to work on public transport, by bicycle and on foot Length of cycling lanes and the public transport network

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UNIT OF MEASURE Tonnes per head Grams per unit of real GDP (2000 base year) -qualitative indicatorGJ per head MJ per unit of real GDP (in euros, base year 2000) %

-qualitative indicatorkJ per square meter of residential floor space -qualitative indicator-qualitative indicator%

km per square meter of city area

24


Water

Waste and land use

Green transport promotion Congestion reduction policies Water consumption Water system leakages Wastewater treatment Water efficiency and treatment policies Municipal waste production Waste recycling Waste reduction and policies Green land use policies

Air quality

Nitrogen dioxide Ozone Particulate matter Sulphur dioxide Clean air policies

Environmental Green action plan governance Green management

Public participation in green policy

An assessment of the extensiveness of efforts to increase the use of cleaner transport An assessment of efforts to reduce vehicle traffic within the city Total annual water consumption Percentage of water lost in the water distribution system Percentage of dwellings connected to the sewage system An assessment of the comprehensiveness of measures to improve the efficiency of water usage and the treatment of wastewater Total annual municipal waste collected

-qualitative indicator-qualitative indicatorm3 per head %

Percentage of municipal waste recycled An assessment of the extensiveness of measures to reduce the overall production of waste, and to recycle and reuse waste An assessment of the comprehensiveness of policies to contain the urban sprawl and promote the availability of green spaces Annual daily mean of NO2 emissions Annual daily mean of O3 emissions Annual daily mean of PM10 emissions Annual daily mean of SO2 emissions An assessment of the extensiveness of policies to improve air quality An assessment of the ambitiousness and comprehensiveness of strategies to improve and monitor environmental performance An assessment of the management of environmental issues and commitment to achieving international environmental standards An assessment of the extent to which citizens may participate in environmental decisionmaking

% -qualitative indicator-

% -qualitative indicatorkg per head

-qualitative indicatorμg/m3 μg/m3 μg/m3 μg/m3 -qualitative indicator-qualitative indicator-qualitative indicator-

-qualitative indicator-

Table 4: European Green City Index indicators

Indicators extracted from the projects list above are detailed in Appendix A of this deliverable. ISO standards, which intersect with the management of energy, sustainability and measuring efficiency and effectiveness, were also examined for the purposes of extracting indicators, which could be harnessed to explore the identified scope of the INDICATE SUI suite. These standards are briefly outlined below.

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ISO/Ts 37151 “Smart Community Infrastructures — Principles and Requirements for Performance Metrics” ISO/TS 37151:2015 gives principles and specifies requirements for the definition, identification, optimization, and harmonization of community infrastructure performance metrics, and gives recommendations for analysis, including smartness, interoperability, synergy, and resilience of community infrastructures. Community infrastructures include, but are not limited to, energy, water, transportation, waste, and ICT. The principles and requirements of ISO/TS 37151:2015 are applicable to communities of any size sharing geographic areas that are planning, commissioning, managing, and assessing all or any element of its community infrastructures. However, the selection and the importance of metrics or (key) performance indicators of community infrastructures is a result of the application of ISO/TS 37151:2015 and this depends on the characteristics of each community. ISO/TR 37150 “Smart Community Infrastructures — Review of Existing Activities Relevant to Metrics” ISO/TR 37150:2014 provides a review of existing activities relevant to metrics for smart community infrastructures. In ISO/TR 37150:2014, the concept of smartness is addressed in terms of performance relevant to technologically implementable solutions, in accordance with sustainable development and resilience of communities, as defined in ISO/TC 268. ISO/TR 37150:2014 addresses community infrastructures such as energy, water, transportation, waste and information and communications technology (ICT). It focuses on the technical aspects of existing activities, which have been published, implemented or discussed. Economic, political or societal aspects are not analysed in ISO/TR 37150:2014. ISO 37120 “Sustainable Development of Communities — Indicators for City Services and Quality of Life” SO 37120:2014 defines and establishes methodologies for a set of indicators to steer and measure the performance of city services and quality of life. It follows the principles set out and can be used in conjunction with ISO 37101: Sustainable development in communities, management systems, general principles and requirements, when published, and other strategic frameworks. ISO 37120:2014 is applicable to any city, municipality or local government that undertakes to measure its performance in a comparable and verifiable manner, irrespective of size and location. ISO 50001:2011 “Energy Management Certification” “Requirements with guidance for use is a specification created by the International Organization for Standardization (ISO) for an energy management system.” The ISO 50001 certification process requires a company to undergo a two-stage ISO 50001-audit process of its Energy Management System (EnMS);  

ISO 50001 Stage 1 (Pre-assessment) ISO 50001 Stage 2 (Certification)

The ISO 50001 Stage 1 pre-certification assessment involves the organisation's system being audited by Certification Europe energy system auditors to ensure the ISO 50001 meets the minimum requirements of the ISO 50001 Energy Management Certification standard. The ISO 50001 Stage 2 Certification assessment involves a close out of issues raised in the first ISO 50001 audit and requires the Certification Europe audit team to dig deeper into a company's energy management system. 30/04/2016

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This particular ISO standard aligns with the need for the INDICATE tool as research underpinning the standard’s operation indicates strongly on the impetus created by the desire to reduce the cost of energy for businesses (Johnson Controls, 2010). The indicators used to guide the operation of this energy management system align with the indicators in this deliverable as both monitor the factors and aspects of building usage that have an appreciable impact on the generation and consumption of energy. The evaluation of this energy management methodology facilitated the alignment of the SUIs with the needs of building energy managers and professionals who utilise existing standards for the quantification of energy use. This will facilitate the standardisation of the INDICATE tool during Work Package 8. 3.2.8 SUI Selection Criteria Indicator evaluation took place on an iterative basis. Section X.X of this report deals with the evaluation process in detail. The assembled indicators were evaluated in line with the following considerations    

Alignment with Existing Standards & Indices Stakeholder Input-refers to the solicited preferences of members of the end user community, as identified in Work Package 1, in terms of indicators best suited to reflect achievements arising from modelled Technical Feasibility-refers to the feasibility of technically representing a SUI in the decision support tool. Data Availability-refers to the availability of data to effectively support the operation of the SUI in the decision support tool.

As identified in D3.2, evidence shows that the selection and use of indicators is very much the product of social processes and political debates (Connolly et al., 1999; Jacobs et al., 2000; Astleithner, 2003; Barker and Wong, 2006). In addition, the restrictions of data availability and participatory processes mean that the selected indicators often provide a limited overview of urban sustainability, with several authors noting that more sophisticated views of sustainability issues are frequently neglected (Brugmann, 1997; Ooi, 2005). Furthermore, the applicability of some sustainability indices is further complicated by the sparse spatial coverage of such indices in often only ranking a limited sample of the largest metropolitan areas (Bieri, 2013). Spatial aggregation of these indices to the state level, for instance, is not only intrinsically complex (Custance and Hillier, 1998) but may also involve ethical considerations such as social justice (Permanyer, 2012). A mitigating factor against this criticism is the need for trusted metrics. According to Keirstead (2007), of the three indicator criteria noted by the OECD, policy relevance and measurability are given priority, with the validity of the metrics often assuming a secondary role thereby limiting their ability to provide meaningful insights into how the urban environment might be improved. To support this, Keirstead cites the development of London’s quality of life metrics as an example, whereby the Mayor’s Sustainable Development Commission noted that there were a number of issues which “the Commission would like to measure, but for which there are no available data” (Keirstead, 2007). The consequences of which led to the use of a reduced set of metrics supported by readily available data. The same issues were encountered during the development of this deliverable as a substantial number of indicators were found to be of theoretical and academic relevance to the INDICATE SUI yet were not implementable due to the constraints imposed by data availability. 3.2.9 SUI Performance Indicator performance will be assessed in Work Package 6, T6.6/D6.3. Indicator performance assessment will be completed in tandem with the final evaluation of the Graphic User Interface (GUI), the final Virtual City Model (VCM) as well as the Common Cities Index (CCI). 30/04/2016

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3.2.10 SUI Finalisation Indicator finalisation and integration with the INDICATE decision support solution will occur in Work Package 4 and their operation will be tested in Work Packages 6 in tandem with the ICCI. Every effort has been made to ensure that the SUI suite will be supported in terms of data and graphic visualisation through consultation with the consortium during the indicator development process. 3.2.11 SUI Weighting A system of default weightings will be applied to the SUIs in order to afford the end user to customise their selection. The operationalisation of the indicators in subsequent work packages requires that default weightings be applied in advanced of the final iteration employed within the INDICATE decisions support tool. Assigning a default weighting is congruent with the majority of composite indices, as stated in OECD, 2008. Section 4.4 deals with the weighting of the SUIs in detail. 3.2.12 Summary Through our initial compilation process, the indicators obtained were found across different relevant domains. Phase 1 of this research delivered 186 separate energy related indicators (appendix D). These indicators were taken from a combination of sources, including past deliverables, existing indices relating to the built environment as well from a study of industry standards in the management of energy. The structure, scope, framework and weighting of the indicators have been developed in line with academic practice relating to the formation of composite indicators. Once compiled, the indicators were advanced for consideration at the consultation phase of the methodology.

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3.3 Sustainable Energy Indicator Consultation and Validation Process 3.3.1 Overview

Figure 9 Consultation Overview

The purpose of this section is to detail the manner in which the refined list of indicators as detailed in Appendix A were derived via a refinement process of consultation and discussion with energy industry experts, end users and actors experienced with interacting with the community. The goal of this consultative exercise was to arrive at the optimum set of Sustainable Urban Indicators (SUIs) which could be employed to reflect the impact of energy related interventions in the urban environment. The delivery of the SUIs was at all times guided by the needs of the end user community. To that end, in order to select the refined list of key SUIs, the needs of the end user community were actively sought in order to guide the indicator refinement process. In addition, the expertise of the consortium members was applied to the refinement of the indicator list. Once the refined indicator list had been developed, the expertise of the INDICATE External Advisory Panel was brought to bear in terms of contributing advice on the manner in which the indicators might be optimised in order to make more accessible to end users and communities. With regard to the workflow as established in the INDICATE Description of Work, the drafting of the SUIs was undertaken as an exercise in continuous consultation with the INDICATE consortium. The development of the software and its cloud-based architecture necessitated the

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development of the indicators in line with the technical feasibility of the operationalising element while having regard to the need to push beyond those boundaries in terms of establishing an optimum range of Sustainable Urban Indicators. 3.3.2 Pre Consultation Review Prior to the commencement of the consultation process proper, a comprehensive review of the expanded list of SUIs was undertaken. In order to effectively engage with the consultees, it was deemed necessary to apply an initial test in order to reduce the total number of SUI’s down to a more manageable and effective number. 186 SUI has had been determined via the process detailed in 3.2.8. Indicators which were deemed to be outside of the remit of the project, which did not align with the requirements outlined in D3.1 and could not be supported in terms of data as per the consultation with consortium partners and their findings in D3.2 were taken out from the indicator evaluation process. Instances where indicators dealt with components of the built environment, which have an interaction yet energy, in an imprecise or ill-defined manner, were also discounted due to the obstacles that such indicators would present in terms of technical operationalisation. Indicators which were deemed to be qualitative in nature and poorly suited to normalisation and application across a number of contexts were discounted for incorporation in the INDICATE decision support tool. Duplication and overlap between indicators was also judged and where instances were detected, the lesserconsidered indicator, by way of definition, data source or unit of measurement was scaled down. The remaining 50 SUI’s were then categorised across the T3.3 objective areas and circulated for consultation. 3.3.3 Consultation and Validation Introduction Figure 9 outlines the general scheme of the consultation and validation exercise which was instrumental to the refinement of the expanded sustainable energy indicator list as compiled as described in section 3 down to the core selection which will go forward for application in the INDICATE tool. The consultation process was split into four distinct phases, each with a focus on optimising the selection of indicators with reference to the priorities and perspectives of different end user and stakeholder communities. On completion of the four phases, the final list of Sustainable Urban Indicators, as detailed in Section 4.0 of this deliverable was agreed. A selection of five SUIs was subsequently determined to go forward for application in the INDICATE prototype tool. 3.3.4 Phase One Consultation The first phase of the sustainable energy indicator refinement process was undertaken in conjunction with a selection of the INDICATE project consortium. Trinity College Dublin, IES and Dundalk Institute of Technology were selected due to the range of expertise available in this organisations and also with reference to the role of these partners later in the project in terms of implementing, designing and validating the use of the indicators in the INDICATE tool. To aid the collection of feedback and insights in relation to the Sustainable Urban Indicators, a consultation .xls spreadsheet was drafted. Trinity College Dublin evaluated the Sustainable Urban Indicators in terms of their robustness and academic quality in with reference to existing indices and manners of quantifying energy consumption and generation in the urban environment. IES evaluated and comment on the compatibility of the Sustainable Urban Indicators with the development of the cloud-based tool. Comment was also sought relating to the relevance of the indicators to

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professionals interacting with and assessing the impacts of energy related interventions in the built environment. Dundalk Institute of Technology was consulted, partly due to the overlap between the work undertaken to form the indicators and the subsequent bodywork, which would be initiated through the development of the Common Cities Index as per D3.3. Opinions relating to relevance applicability were also requested as this partner is located in the Dundalk case study area. D'Appolonia S.p.A was requested to examine the indicators and their suitability for application in an Italian context. The added benefit of soliciting this information from this partner also enabled us to tap into their understanding of end user and stakeholder requirements through their work on D1.4. The outputs of the first consultation phase were employed to refine the manner in which each indicator was structured and presented subsequently. This included the manner in which the indicators were categorised in initial sub domains. Where indicators overlapped to a substantial degree or were found not to be relevant, they were amalgamated or removed. 3.3.5 Phase Two Consultation Phase Two of the consultation process consisted of refining the indicator list by harnessing the insights of the end user community. While D1.4 and 1.5 entailed a comprehensive exercise in stakeholder engagement in order to determine end user needs in respect of the INDICATE suite of tools, specific feedback from this community was required in order to refine the indicators which would guide their use of an operational INDICATE tool in the context of monitoring the impacts of energy interventions in the built environment. In order to facilitate meetings and clear communication initial consultation was made with possible Irish end users. The end user communities identified as being relevant for consultation in an Irish context are outlined in the table below; Energy Experts

Sustainable Energy Authority of Ireland (SEAI) Eirgrid CODEMA – The Dublin Energy Agency Louth County Council South Dublin County Council Irish Planning Institute (IPI)

Municipal Authorities Professional Organisation Table 5: Irish Consultees

Each of the end user organisations listed above have unique perspectives of the interaction of the built environment and energy. The consultation exercise was undertaken by email to a known ranking member of each of the organisations listed above. SEAI- Sustainable Energy Authority of Ireland The Sustainable Energy Authority of Ireland was established as Ireland’s national energy authority under the Sustainable Energy Act 2002. SEAI’s mission is to play a leading role in transforming Ireland into a society based on sustainable energy structures, technologies and practices. The following individuals in this organisation were consulted. 

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    

Jim Scheer, Programme Manager Dr Denis Dineen, Energy Policy & Modelling Group Martin Howley Energy Policy Statistical Support Unit Matthew Clancy, SEAI Energy Modelling Group Mary Holland, Data Management Executive

Eirgrid is a state-owned company that manages and operates the transmission grid across the island of Ireland. The individual consulted in this body was Des Cox, Senior Co-ordinator, Public Planning. A summary of the feedback received is provided in Appendix X of this report. CODEMA- The Dublin Energy Agency Codema is Dublin’s Energy Agency and was set up as a not-for-profit limited company by Dublin City Council in 1997 under the SAVE II Programme of the European Union. Codema is committed to working with Dublin’s local authorities on improving the energy efficiency in Dublin in order to reduce the city’s CO2 emissions and achieve the “20-20-20” targets. The stakeholder consulted in this organisation was Donna Gartland, a qualified energy planner with experience managing energy efficiency and improvement programmes with Dublin City Council. IPI - Irish Planning Institute is the professional body representing the majority of professional planners engaged in physical, spatial and environmental planning in Ireland and Irish planners practicing overseas. The indicator list was referred to the Institute’s Policy and Research Group. The purpose of the Group is to enhance the Institute’s research capacity and that of the profession as a whole through independent and joint research, this is to be reinforced by and inform policy submissions and the Charter-ship and CPD programmes. The consultation undertaken in phase two validated in the 50 SUI’s from the perspectives of the energy experts who commented on them. They key messages arising from the consultation exercise arose with regard to the number of indicators that were present on the list, the availability of data to support their application and the manner in which energy interventions are modelled in the decision support tool. Individual feedback on the indicators, where provided, facilitated the refinement of the definition, scale and unit of measurement, which would be applied within the decision support tool. 3.3.6 Phase Three Consultation Leading on from the feedback received during the second consultation phase during which the SUI list was validated against the expectations of experts in the field of spatial planning and energy. The phase three-consultation stage was focused on the further refinement of the SUI list. The third phase of consultation utilised the INDICATE consortium using a workshop format held in Zurich on the 14th and 15th of September 2015. The purpose of this phase was refine the expanded list of key indicators down to an optimal number for application and eventual integration in the INDICATE decision support tool. Having validated the expanded Sustainable Urban Indicators list through consultation with the end user community as described in section 3.4.5 above. The SUIs were discussed in detail amongst the consortium in terms of the utility of each and the manner in which they would be integrated into the cloud based decision support tool. A ‘traffic light’ system, wherein indicators which were preferred by the consultees with reference to data availability and the scope of the INDICATE project were highlighted in green. Those indicators that were not accepted by the consortium were highlighted in red and after a final review were subsequently taken off the final indicator list.

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Once Phase 3(a) had been completed in Zurich, the discussion of the 32 remaining SUI’s turned to data availability in terms of the context in which the indicators would be applied within the INDICATE decision support tool. In order to confirm that data sources for modelling purposes could be sourced from the two test sites a version of the refined SUI list was circulate to Louth County Council and D'Appolonia. The responses are contained in Appendix C. In addition to consulting the two partners above, IES was also contacted with regard to the capacity of the stimulation tool to generate data to cover gaps, which may emerge. 3.3.7 Phase Four Consultation The fourth consultation phase entailed the presentation of SUIs to the INDICATE project’s External Advisory Panel. In terms of the key consultation points raised, a summary is provided here: Environment Impact Assessment: The compatibility of the indicators with the Environmental Impact Assessment process was raised. It was assessed that the likelihood was that most renewable technology interventions would be small scale and therefore not subject to environmental assessment in their own right. However, the issue of environmental impact assessments, and the implications for the tool may need to be considered in the future. Indicator Representation: Given the large number of indicators, the complex identification and selection process and the wide number of stakeholders involved, it would be good to map out and illustrate the overall process. It would also be good to produce a matrix that includes all indicators and summarises the following: how they have been arrived at; what stakeholders they are the aimed at; how they are to be used in the tool, etc. This would help make sense of the indicators, make the process more transparent, and allow this process to be used elsewhere. Urban Morphology: Indicators may also be required to characterise the urban morphology such as: roof space as a percentage of gross floor area (provides information about usable roof areas); average building height to average building width (provides information about urban canyon effect. (Note D3.1 contains much information in this regard that could be used). High Level Responses: Indicators are used to simplify and reduce the inputs and results to an easily identifiable level, and as such it, will be important for the tool to use indicators to provide high-level feedback about broad trends or overall changes in terms of improvements or decline in efficiency. It is also important to consider what benchmarks are used for comparison (i.e. code of compliance, typical similar building). In fact, it could also be that this methodology overtime establishes its own benchmark or uses reference models that become more informative as the tool is developed through ongoing use, and as more real-time data based city models come online. Sensitivity Analysis: Consider using the model (when it is ready to produce results) to do a sensitivity analysis to test the various indicators in terms of the three main indicator outputs of Cost reduction, Emissions reductions and Increased energy efficiency. These results would allow the prioritisation of the indicators to be used in the tool. 3.3.8 Summary The drafting of the Sustainable Urban Indicators adhered to the three phases outlined in figure 3. The constituent tasks listed under each of the headings are described in detail in the following subsections. 30/04/2016

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4.0 Refined Sustainable Urban Indicators The indicators outlined below have been determined to be the optimal selection arising out of consideration of existing indices and through stakeholder consultation as outlined in section 3.0 above. As outlined in section 3.0, composite indicators in newly emerging policy areas, e.g. competitiveness, sustainable development, e-business readiness, etc., might be very subjective, since the economic research in these fields is still being advanced. Transparency is thus essential in constructing credible indicators. The purpose of this section is to outline the rationale behind the selection of each SUI. Functional elements such as the spatial scale and unit of measurement of each of these indicators is outlined in Appendix A. 4.1 Carbon Emissions Reduction Indicator Rationale

Indicator Rationale 1 Indicator 1: Consumption of renewables

Source

EU SDI theme: Climate change and energy. EU SDI Level 1

Rational

This indicator has been included as it enables decision makers to determine the penetration of renewable energy sources into the urban energy mix.

Test Site 1: Dundalk

SEAI website has a figure for Ireland, however not broken down for Dundalk

Test Site 2: Galliera

Total Electricity, Fossil Fuel and Renewable Energies (Solar Thermal and Biomass) aggregated by category (public building/tertiary building/residential building/ public illumination). The ratio of these values gives us the percentage of renewable energy used. Average of 2005 (no temporal, no seasonal). New update within the end of 2015.

Data

Benchmark or Simulation Data Available Indicator 2: GHG emissions per sector (residential, industry, use type)

Source Rational Test Site 1: Dundalk Test Site 2: Galliera Data

EU SDI sub-theme: Climate change. EU SDI sub-theme: Climate change Level 2 This indicator has been included as the determination of GHG emissions is critical in order to marshal responses and develop solutions for sectors producing GHG in urban settings. This indicator has been expanded to reflect the totality of GHG’s which are emitted by activities in the SEAI website has a figure for Ireland, however not broken down for Dundalk Total CO2 emissions generated by the civil sector and by local transports divided by Electricity, Fossil Fuel and Renewable Energies (Solar Thermal and Biomass) aggregated by category (public building/tertiary building/residential building/ public illumination). Average of 2005 (no temporal, no seasonal). New update within the end of 2015. Table 4. Benchmark or Simulation Data Available Indicator 3: Renewable plants (managed by public/private authority) kWh produced

Source

EU SDI level 3 Electricity generation from renewable Urban Ecosystem Europe indicator, theme local to global: energy and climate change.

Rational

This indicator has been included as the location of such energy generating infrastructure in the urban environment may offset emissions

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Test Site 1: Dundalk Test Site 2: Galliera Data

No data for Private. LCC involved in a micro-generation project measuring solar energy generated from PV panels on Co. Museum in Dundalk Locally generated Electricity and Heat / Cold Table 2-3 Benchmark or Simulation Data Available Indicator 4: Energy consumption of public buildings

Source Rational Test Site 1: Dundalk Test Site 2: Galliera Data

Urban Ecosystem Europe indicator, theme local to global: energy and climate change. This indicator has been included because it has the potential to inform decision makers in municipalities as to the performance of buildings under their control and how interventions therein may enhance the energy consumption qualities of their building portfolio. In Public buildings LCC have live data measuring gas and heat co. library and electricity and solar output in co. museum. LCC have all data with regard to public buildings in Dundalk Total Electricity, Fossil Fuel and Renewable Energies (Solar Thermal and Biomass) aggregated by public building. Square meter of public building in GIS (http://geoportale.regione.liguria.it/). The ratio of these values gives us the energy consumption of Public Building. Average of 2005 (no temporal, no seasonal). New update within the end of 2015. Table 1. Benchmark or Simulation Data Available Indicator 5: Total waste generated per year per capita

Source

EU SDI sub-theme: Resource use and waste. EU SDI level 2

Rational

This indicator has been included in order to quantify the emissions equivalent of the waste volumes generated in the urban environment.

Test Site 1: Dundalk

344kg/inhabitant (national per capita, 2012)

Test Site 2: Galliera Data

530-550 kg / inhabitant (national per capita 2012) Benchmark or Simulation Data Available Indicator 6: Brownfield versus Greenfield development

Source Rational Test Site 1: Dundalk Test Site 2: Galliera Data

TISSUE CORE 1 This indicator has been included as it is a useful land use based metric which can inform decision makers as to the quantum of brownfield land within a defined area whose redevelopment would be less emissions intense than the development of greenfield sites Vacant Sites Register 4.368.000 m2 of brownfield area that can be transformed. Benchmark or Simulation Data Available Indicator 7: Roof Space available for PV

Source

Determined by Consultation

Rational

This indicator was selected for inclusion as it would enable decision makers to consider the viability of incentivising the development of available and suitable roof spaces for energy generation.

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Test Site 1: Dundalk Test Site 2: Galliera Data

To be estimated based on area of buildings (From GIS) To be estimated based on area of buildings (From GIS) Benchmark or Simulation Data Available Indicator 8: Roof Space Available for Solar Thermal

Source Rational Test Site 1: Dundalk Test Site 2: Galliera Data

Determined by Consultation This indicator was selected for inclusion as it would enable decision makers to consider the viability of incentivising the development of available and suitable roof spaces for energy generation. To be estimated based on area of buildings (From GIS) To be estimated based on area of buildings (From GIS) Benchmark or Simulation Data Available

4.2 Energy Efficiency Indicators Rationale

Domain 2: Energy Efficiency Indicator 9: Final energy consumption, by sector

Source

EU SDI sub-theme: Consumption patterns. EU SDI sub-theme: Consumption patterns level 3

Rational

This indicator has been selected for inclusion in the tool as it establishes a baseline for decision makers in order to facilitate the generation of interventions, which enhance energy efficiency.

Dundalk Case (LCC) Galliera Case (Dapp) IES Data

National Level Statistics Available. Total energy consumption in residential building per capita (2012) Benchmark or Simulation Data Available Indicator 10: Energy dependency

Source Rational Dundalk Case (LCC) Galliera Case (Dapp)

EU SDI sub-theme: Climate change. EU SDI sub-theme: Climate change Level 2

IES Data

Benchmark or Simulation Data Available

This indicator was brought forward for inclusion in the tool National Level Statistics Available. Total energy consumption in residential building per capita (2012)

Indicator 11: Energy consumption of public buildings II produced

Source

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DCC indicator

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Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

This indicator has been included because it has the potential to inform decision makers in municipalities as to the performance of buildings under their control and how interventions therein may enhance the energy consumption qualities of their building portfolio. LCC have conducted energy audits of its buildings within the last 4 years and drawings to match are available Not Available Benchmark or Simulation Data Available Indicator 12: Building stock energy efficiency

Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

Determined by consultation. The rationale for this indicator arises from the need of end users to assess the performance of existing buildings so that the impact of interventions can be assessed accurately. For residential BERS. Also drawings sent through for Co. Museum and Co. Library. Demand for heat and electrical power + Emission of CO2 [t/year] aggregated by category (public building/tertiary building/residential building (2005) Benchmark or Simulation Data Available Indicator 13: Residential Stock Energy Efficiency

Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

Determined by consultation. This indicator has been selected due to the importance of assessing the impact of interventions planned in residential developments given the energy consumption, which occurs in this building type. BERS. Site plans and elevations, XEML, Dwelling reports. Not Available. Benchmark or Simulation Data Available Indicator 14: Commercial Stock Energy Efficiency

Source Rational

Determined by consultation. This indicator has been selected due to the importance of assessing the impact of interventions planned in commercial developments given the energy consumption, which occurs in this building type.

Dundalk Case (LCC)

BERS can be accessed if the MPRN is known. Check the following link https://ndber.seai.ie/pass/ber/search.aspx

Galliera Case (Dapp)

Not Available.

IES Data

Benchmark or Simulation Data Available Indicator 15: Industrial Stock Energy Efficiency

Source Rational

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Dundalk Case (LCC)

BERS can be accessed if the MPRN is known. Check the following link https://ndber.seai.ie/pass/ber/search.aspx

Galliera Case (Dapp)

Not Available.

IES Data

Benchmark or Simulation Data Available Indicator 16: Leisure Stock Energy Efficiency

Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

Determined by Consultation This indicator has been selected due to the importance of assessing the impact of interventions planned in Leisure developments given the energy consumption, which occurs in this building type. To be estimated based on area of buildings (From GIS) To be estimated based on area of buildings (From GIS) Benchmark or Simulation Data Available Indicator 17: Public Stock Energy Efficiency (Health) I

Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

Determined by Consultation This indicator has been selected due to the importance of assessing the impact of interventions planned in health sector given the pattern of energy consumption, which occurs in this building type. Not Available. Not Available. Benchmark or Simulation Data Available Indicator 18: Public Stock Energy Efficiency (Education) II

Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

Determined by Consultation This indicator has been selected due to the importance of assessing the impact of interventions planned in the education sector given the pattern of energy consumption, which occurs in this building type. Not Available. Not Available. Benchmark or Simulation Data Available Indicator 19: Special Heritage Status

Source Rational Dundalk Case (LCC)

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Determined by Consultation The purpose of this indicator is to examine the impact of interventions relating to the enhancement of energy interventions in structures and buildings, which have specific heritage related designations attached. Information available.

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Galliera Case (Dapp) IES Data

Information available. Benchmark or Simulation Data Available Indicator 20: Electricity Exported to Grid

Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

Determined through literature research. The purpose of this indicator is to examine the manner in which surplus energy is exploited in an urban environment. Not Available. Not Available. Benchmark or Simulation Data Available Indicator 21: Residential population density

Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data Source Rational Dundalk Case (LCC) Galliera Case (Dapp) IES Data

Source Rational

TISSUE CORE 1 This indicator was advanced as a support to decision makers as residential density has a key role to play in the assessment of energy consumption in urban environments. Information available. Density 2.509 ab/km2 Benchmark or Simulation Data Available Indicator 22: Percentage of buildings assessed under a Building Energy Rating Scheme. Discovery This indicator was advanced as it outlines the penetration of energy efficiency assessments in an urban area. BERS can be accessed if the MPRN is known. Check the following link https://ndber.seai.ie/pass/ber/search.aspx Not Available: any information on private buildings, very few datasets on public buildings. Benchmark or Simulation Data Available Indicator 23: Population living within 300 metres to basic public services This Indicator has been removed from implementation Indicator specified in D1.4 The purpose of this indicator is to assess the density of population proximate to basic public services as an indicator of the efficiency of urban form.

Dundalk Case (LCC)

LCC would have info showing basic public facilities and dwellings close by.

Galliera Case (Dapp)

Building locations only, not residential density.

IES Data

Benchmark or Simulation Data Available

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4.3 Cost Reduction Indicator Rationale

Indicator Rationale 3 Indicator 24: Heat Demand Density

Source Rational Test Site 1: Dundalk Test Site 2: Galliera IES Data

Determined by consultation This indicator has been included as it will facilitate end users to examine the viability of district heating as a measure for application in the urban environment. Density of residential dwellings and proximity to sources of heat. Energy demand mapping is used as a tool in energy planning to define energy character areas. The individual energy characteristics of an area are used by planners to define the appropriate energy solutions or planning policies to be considered for strategic development zones, local area plans or county-wide development plans. Density of residential dwellings and proximity to sources of heat. Energy demand mapping is used as a tool in energy planning to define energy character areas. The individual energy characteristics of an area are used by planners to define the appropriate energy solutions or planning policies to be considered for strategic development zones, local area plans or county-wide development plans. Benchmark or Simulation Data Available Indicator 25: Occupancy

Source

Determined by consultation

Rational

This metric is of importance for decision makers as it informs them as to the availability of data and the capacity of buildings within the urban environment to have a more dynamic relationship with the energy grid.

Test Site 1: Dundalk

Rates office for commercial and Industrial premises. Link: http://www.geohive.ie/gallery.html#gallery

Test Site 2: Galliera Data

Occupied: 273.807 - vacant 28.088 units - density 2.509 ab/km2 Benchmark or Simulation Data Available Indicator 26: Smart Metering

Source Rational Test Site 1: Dundalk Test Site 2: Galliera Data

Determined by consultation. This metric is of importance for decision makers as it informs them as to the availability of data and the capacity of buildings within the urban environment to have a more dynamic relationship with the energy grid. Pilot Buildings Not Available Benchmark or Simulation Data Available Indicator 27: Capital Expenditure on Energy Infrastructure

Source

Determined by consultation.

Rational

This indicator is of use as it enables decision makers to temper interventions in the urban environment to the availability of funds to undertake them.

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Test Site 1: Dundalk

CSO website See link http://www.cso.ie/en/census/census2011smallareapopulationstatisticssaps/ and the GIS boundary datasets can be downloaded here: http://www.cso.ie/en/census/census2011boundaryfiles/

Test Site 2: Galliera

Not Available

Data

Benchmark or Simulation Data Available Indicator 28: Total employment rate

Source Rational Test Site 1: Dundalk Test Site 2: Galliera Data

EU SDI sub-theme: Employment, level 2 Employment and unemployment patterns have a quantifiable impact on the profile of energy consumption which may take place in at the city scale as well as at sub city/building level. Revenue website Data Available - [10% (2014)] Benchmark or Simulation Data Available Indicator 29: Retrofitted Elements (Generation)

Source Rational

Determined through literature research. This indicator was deemed to be significant as it can enhance the accuracy of the modelled interventions in the urban environment by reflecting the impact of pre-existing interventions. In addition, this indicator was deemed to be of importance to end users as it reflects the uptake of interventions prompted by previous initiatives to promote the enhancement of energy efficiency.

Test Site 1: Dundalk

For County Museum

Test Site 2: Galliera

Not Available.

Data

Benchmark or Simulation Data Available Indicator 30: Retrofitted Elements (Insulation)

Source Rational Test Site 1: Dundalk Test Site 2: Galliera Data

Determined through literature research This indicator was deemed to be significant as it can enhance the accuracy of the modelled interventions in the urban environment by reflecting the impact of pre-existing interventions. For Public buildings and Housing stock. Not Available. Benchmark or Simulation Data Available Indicator 31: Retrofitted Elements (Glazing)

Source

Determined through literature research.

Rational

This indicator was deemed to be significant as it can enhance the accuracy of the modelled interventions in the urban environment by reflecting the impact of pre-existing interventions.

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Test Site 1: Dundalk Test Site 2: Galliera Data

For Public buildings and Housing stock. Not Available Benchmark or Simulation Data Available Indicator 32: Retrofitted Elements (Heating)

Source Rational

Determined through literature research. This indicator was deemed to be significant as it can enhance the accuracy of the modelled interventions in the urban environment by reflecting the impact of pre-existing interventions.

Test Site 1: Dundalk

For Public buildings and Housing stock.

Test Site 2: Galliera

Not Available.

Data

Benchmark or Simulation Data Available

4.4 Sustainable Urban Indicators Weightings There are strong links between this deliverable, D3.4 and D3.3 which details the INDICATE Common City Index (ICCI) compilation methodology. This deliverable, D3.4, identifies 32 indicators in three domains, namely, carbon emissions reduction, energy efficiency and cost reduction as well as the data that will be used to calculate values for the indicators. This deliverable is the foundation on which D3.3 will be implemented in the INDICATE tool. In applying D3.3 in practice, the consortium will first normalize the indicators so that each indicator has values in the same range from 1 to 100. This is so that an indicator such as residential population density, which has values in the thousands, does not implicitly contribute more to the index than an indicator such as total unemployment rate, which has values from 0 to 100. This range has been chosen as it is easier for end users to interpret numbers between 1 and 100 and we do not want to allow zero values as this would mean that in a geometric aggregation, if any of the indicators had value zero, the whole index would have a value of zero. Once the indicators have been normalized, an explicit weighting can be applied to them. The weightings are a value judgement on the relative importance of each indicator within its domain and each domain within the ICCI. Initially a default weighting will be used giving equal weights to each indicator within its domain and each domain within the index. The implication with this default weighting is that each indicator has equal importance within its domain and each domain has equal importance within the ICCI. In D5.3, customized displays for various stakeholders and end users, which will be linked to the type of indicators preferred by individual stakeholders, are being developed. Normal users of the application will not be given the option to adjust the weightings of indicators as it is a complex task and no users have requested this feature in D1.5. Pending the results of user testing in D6.2 we way allow an advanced option where the weightings of the indicators can be changed. Once all of the indicators have been normalized to values between 1 and 100 a geometric mean is used to combine the indicators first into their domain index and then the domain indices into the ICCI. The default setting is that all indicators will have the same weighting within their domain and each domain will have the same weighting within the ICCI. For example, in the carbon emissions reduction domain, there are eight indicators each of which would be weighted 12.5% in an equal weighting scenario.

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In order to facilitate customized weighting of the indicators users will be able to distribute weights totalling 100% between the indicators within a domain. Now if a user thought the consumption of renewables indicator was three times as important as any of the other seven indicators within the carbon emissions reduction index they would give this indicator a weighting of 30% and the other seven indicators a weighting of 10%. Then the weight-adjusted geometric mean of the individual indicators can then be calculated to give the domain index. The overall ICCI index is generated in a similar way. The default will be that each domain has an equal weighting (33.333%) and a geometric mean of the individual domains is used. Custom weightings of each domain may be facilitated if requested by the users in the user testing. 4.4.1 INDICATE ICCI Calculation There are 32 indicators spread across three different domains of Carbon Emissions Reduction, Energy Efficiency and Cost Reduction. Step 1: Normalise the raw indicator values. There are two types of indicator values – those such as consumption of renewables where a high value is good and those such as GHG emissions where a high value is bad. In the normalization step, we normalize so that for all indicators 1 means worst and 100 means best. The formulae are:  

High means good Normalized Value = (Observed-Min/(Max-Min))*(99) + 1 High means bad = Normalized Value = 100 – ((Observed-Min/(Max-Min))*(99) + 1)+1

Note: When there are only two cites in the calculation the one with the best value will get a value of 100 and the one with the worst value with get a value of 1 for each indicator. Where they both had the same value, they would both get a value of one Step 2: In step two we can apply a weighting to each indicator within its domain. There are two options for the weightings. In the first we use default weightings. There are 8 indicators in the Carbon Reduction domain, 15 in the Energy Efficiency Domain and 9 in the Cost Reduction domain. So their default weighting will be for Carbon Reduction each indicator gets a weight of (1/8), Energy Efficiency each indicator gets a weight of (1/15) and Cost Reduction each indictar gets a default weight of (1/9). So the calculation for the Carbon Reduction domain with default weights is: (I1)^(1/8)* (I2)^(1/8)* (I3)^(1/8)* (I4)^(1/8)* (I5)^(1/8)* (I6)^(1/8)* (I7)^(1/8)* (I8)^(1/8) where I1 stands for the normalized value of indicator 1 within this domain. Users should also be able to customize the weights assigned to each indicator. In the example attached in the spreadsheet in the Carbon Reduction Domain Consumption of Renewables and Energy Consumption of Public Buildings are given a weighting twice that of everything else. In this case there are 8 indicators so if two indicators are given double weightings (2x) the total weighting involved is 6x+2*2x = 10x and this must sum to 1 so the weightings for 6 of the indicators are 0.1 and the other two have weighting 0.2. Then the domain index is worked out in the same way as we did with default weightings, just applying the custom weightings. Step 3: In step three, the three domain indices are combined into the ICCI first with default weightings and then with custom weightings. The weighting process works exactly as it does for the domain indices.

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The application of the INDICATE Common Cities Index (ICCI) is best undertaken in Task 6.6 which relates to the validation and testing of the SUIs as they relate to the Dundalk and Genoa test sites. Furthermore, this task will validate the Common Cities index through an evaluation of benchmarking between the test sites.

4.5 Excluded Sustainable Urban Indicators Of the 32 indicators listed in this deliverable, two of these have since been excluded as it was not deemed practical to develop them into the prototype. The indicator “Population living within 300 metres to basic public services” has been removed from implementation: This is reliant on GIS functionality being available, and this is not part of the CityEngine software. Also the indicator, “Capital Expenditure on Energy Infrastructure” has been removed as there is a lack of relevant data available. Based on preliminary implementation of the indicators, these two proved to be problematic for the reasons outlined above. They have however been noted for consideration as a possible future enhancement of the INDICATE SUIs.

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5.0 Indicator Operationalisation The purpose of this section is outline the manner in which the INDICATE SUIs will be operationalised over the remainder of the project and afterward on foot of commercialisation and further end user requirements. The subsections below outline the tasks in which the SUIs will be brought forward into operation in the INDICATE tool. The SUIs provide a means of approximating the ability of a city to maintain or increase their sustainability in terms of energy efficiency, emission reduction and cost reduction. The SUIs will provide information regarding aspects of city and their management that can make the system more sustainable. Such information can aid planners in prioritising the creation of policy or programs to increase the long-term sustainability of the system. The new SUIs will allow architects to identify areas of weakness where additional action could be taken to increase system sustainability. Specifically, the SUIs will take into consideration how various factors affects the building’s ability to maintain a given level of sustainability into the future. Our research has concluded that beyond the project indicators and the aggregation to the ICCI there is a large set of supporting SUIs, detailed in the D3.2 Indicate Data Dictionary, which adds richness and foundation to the city summary scale Sustainable Urban Indicators. These supporting indicators are spread across a number of technical domains and vary in both detail and scale. They also align with recent draft ISO standards. We envisage they will be used, not just to support the projects’ goals, but for detail analysis, design, optimisation, integration and planning purposes and to thus build-up a holistic view of the city at different scales in an exploitable product. The SUIs will help with the process of creating a definition for a concept of sustainability that can be observed and measured. Further to this they will aid in the development of specific research procedures that will result in empirical observations, which will improve system sustainability. As demonstrated through the application of the SUIs to the case cities of Dundalk and Genoa, the indicators will be particularly useful in highlighting areas of concern that are not currently being addressed. Consequently, the SUIs may identify potential problems that differ from the main challenges identified by the city. This difference occurs because steps being taken by the city to adapt are accounted for in the sustainability analysis, and may make the system more robust in that area. Whereas, other aspects of the system that are key to sustainability may be overlooked because they are not currently the city’s primary concern. Our intention in creating the SUIs is to provide a starting point for re-conceptualising existing static indicators of sustainability so that they reflect new technologies. Assessing the sustainability of a system requires data that may be easily collected and evaluated (e.g. current supply) as well as data that may be difficult to measure, highly uncertain, or a subjective evaluation of the system (e.g. future demand, control over land-use planning). Incorporating the experiences of a diverse set of stakeholders may add new observations of system needs and shortcomings. However, making these improvements requires overcoming challenges associated with time and resource cost-effectiveness and with standardisation; and doing so may be impossible in some contexts. The task at hand is how to best incorporate the concept of sustainability, into a normalised evaluation framework that can be broadly applied. There is a high level of uncertainty about what makes city systems sustainable and the indicators reflect a synthesis of the best knowledge available about these city systems. As knowledge of sustainable smart cities increases, the indicator data could be updated. Cross-sectional studies could be performed to better

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identify the extent to which each of the criteria assessed lead to increased sustainability and point assignments could be weighted accordingly. In developing any indicator, a balance must always be struck between cost, availability of data, scope, complexity, and accuracy. Since sustainability involves the capacity to deal with the unknown, we chose to err on the side of providing a straightforward assessment of sustainability rather than a data intensive or complex quantitative assessment of resilience. The purpose of this section is outline the manner in which the INDICATE SUIs will be operationalised over the remainder of the project and afterward on foot of commercialisation and further end user requirements. The subsections below outline the tasks in which the SUIs will be brought forward into operation in the INDICATE tool.

5.1 Remaining Work Packages 5.1.1 Work Package Four WP4 will develop the Virtual City Model. This will include modelling of the city using Dynamic Simulation Modelling to include the buildings, renewables, and energy conservation and retrofit measures, and the electricity grids. It will integrate the algorithms developed in WP2 and will integrate the refined list of SUIs defined in this deliverable. The incorporation of the SUIs into the VCM will be undertaken in Task 4.5. The data required for each indicator will be mapped with the corresponding logic test to calculate the value of the indicator and this information will then be exported to the GUI, developed in WP5. As per Task 3.4, each Indicator will be given a marker to ensure that it is represented by the correct customised view for the specific stakeholder using the interactive decision support tool. For WP4 the indicators have led to some revisions in the data dictionary, namely:  

Some additional attributes added An ID reference system in order to define the indicator calculation methods effectively

WP4 data dictionary work has fed back to the indicator work ensuring that the indicators can be delivered and have appropriate denominators. In terms of the prototype the indicators have:   

Finalised the dashboard needs Played a role in testing including, in one instance, showing up a constraint in City Engine that has led to additional attributes being devised and in another instance a revision to a data dictionary subtype list Raised questions during testing about tool workflow; ESRI have identified improvements for example needed in being to show indicator values for selection sets rather than only the whole model 5.1.2 Work Package Five

WP5 will develop the interactive cloud based platform to display the information from the VCM in a customised and user-friendly manner. Task 5.3 will deal with the development of a Basic Dashboard User Interface (UI), based on the input of the end user stakeholders as defined in Work Package 1. A key element of the operationalisation of the indicators will be the creation of a UI, which intuitively represents the KPIs associated with modelling particular interventions or indeed the status quo in terms of energy generation and consumption in the urban environment. The utility of the 30/04/2016

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INDICATE tool and by extension, the SUIs contained therein will be predicated on the manner in which the UI reflects the possibilities open to decision makers in terms of their actions in relation to the management of energy in the urban environment. 5.1.3 Work Package Six WP6 will demonstrate and validate the INDICATE project tools in the demonstration sites in Italy and Ireland. The validation phase will be used to feedback information to the tool and Indicator development in WP2, 3 and 4 to ensure that improvements are made based on empirical findings. Task 6.6 directly relates to the validation of the SUIs in the decision support tool. This task will also enable the testing of the ICCI by benchmarking the performance of the case study sites. 5.1.4 Work Package Seven WP7 will disseminate the results to the wider community. The activities of this WP will utilise the Virtual City Model (VCM) developed in WP4 to encourage and support the drive towards the achievement of the ‘Smart’ City concept in practice. 5.1.5 Work Package Eight WP8 comprises all activities relating to the project management, including financial, technical, communication and risks; as well as quality assurance of its deliverables (e.g. reports, software, experimental results, guidelines etc). This WP also deals with the standardisation of the INDICATE decision support suite, including the SUIs and ICCI with existing international sectoral standards relating to the management of energy use in Ireland. 5.2 Post Project Commercialisation and End User Demand It is possible that the end user community is quite diverse and as a consequence, many have differing views and requirements associated with the use of the INDICATE decision support tool. Should such a scenario occur and there is an interest in additional indicators, the contents of this deliverable will provide and range of SUIs, which may satisfy demand of the market environment.

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6.0 Summary and Conclusions This report summarises the influences, methodological approach and key Sustainable Urban Indicators (SUIs) which will be operationalised and applied in the INDICATE decision support tool. Central to the development of this research has been the work already completed in D3.1 and D3.2, which evaluated existing energy efficiency methodologies and entailed the compilation of a data catalogue. Flexibility was identified as being a key requirement in both D3.1 and D3.2 and consequently, the development of the indicators contained in this deliverable was guided by the need to retain such flexibility.

6.1 Limitations I.

II.

III.

IV.

V.

This deliverable relies upon a consultation process with members of the end user community in order to validate the reasoning for the selection of key SUIs from an expanded list. The range of end users consulted over the course of the project were largely from Ireland and may not provide a wide enough variety of sources for a European wide tool. This geographical limitation of the consultation and selection process might therefore mean that its use in other geographical regions might be limited or that the indicators might need refining before they could be applied. The suite of indicators that form the starting basis for the SUI selection is based on the indicators put forward in the academic and research literature. The SUIs developed in this deliverable are therefore limited to the available lists. Furthermore, the SUI selection process is limited to those which specifically address the limited INDICATE overview goals of cost and CO2 reduction, and enhancement of urban energy efficiency. Other relevant and important sustainability criteria might therefore not be captured. The theoretical framework which underpins the construction of the composite indicators is supposed to clearly define all the components (and sub-components) of all the major systems and activities. In reality, some of these components might not be properly captured, and hence not duly reflected in the eventual indicators. As indicated in previous sections in this deliverable, despite the intention that the SUIs proposed for use in the INDICATE toolkit will be positioned for users with varying levels of knowledge and experience in relation to energy efficiency, the SUIs proposed in this document might require some specialised level of understanding before it can be operationalised. The time effectiveness of the use of the selected SUIs might still require demonstration, especially about existing methodologies.

6.2 Possible Solutions I. II.

III.

Demonstration of the tool may be applicable in a jurisdiction with different climatic, geographic and cultural considerations in order to enable the testing of Sui’s transferability. A broader more inclusive tool or a supporting tool which would work in conjunction with the INDICATE tool may be required to address other areas of sustainable development, however the indicators put forward in this deliverable were developed with the aim of meeting the objectives set out in the description of work. The operationalisation of the indicators in the decision support tool and the development of the wider apparatus may be able to compensate for any detected or undetected issues with the indicators theoretical framework. Customisable versions of the tool may use different

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IV.

V. VI.

The preparation of an explanatory memorandum/training element would address this and potentially contribute to the formation of an INDICATE package incorporating the tool and training as a commercial activity. Standardisation, incorporating the alignment of the INDICATE tools scope and content, including the SUIs with existing industry standards (e.g. ISO standards) will be undertaken in Work Package 8. Future additions may reconsider the “Population living within 300 metres to basic public services” and “Capital Expenditure on Energy Infrastructure” SUIs which have been removed from implementation for the practical reasons outlined in section 4.5 of this report.

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References Arksey, H. and O'Malley, L., 2005. Scoping studies: towards a methodological framework. International journal of social research methodology, 8(1), pp.19-32. Bell, S. and Morse, S., 1999. Measuring the immeasurable. The Theory and Use of Sustainability Indicators in Development, Earthscan, London. Brundtland, G.H. and Mansour, K., The World Commission on Environment and Development (WCED). 1987. Our common future. Crabtree, B. and Bayfield, N., 1998. Developing sustainability indicators for mountain ecosystems: a study of the Cairngorms, Scotland. Journal of Environmental Management, 52(1), pp.1-14. Developing a methodology to measure the sustainability of urban wastewater systems. The myth of cycles versus sustainable water and material flux management. In 11th Junior workshop, Wildpark Eekholt, Germany DSCWG (Douglas Shire Community Working Group) 2001, Douglas Shire Sustainable Futures Draft Strategy. Sherlock, K. (Ed). Douglas Shire Council: Mossman. Hardi, P. and Zdan, T. 1997. Pronciples in Practice; Assessing Sustainable Development. Available from https://www.iisd.org/pdf/bellagio.pdf last accessed 28/01/2016 Haughton, G. and Hunter, C., 1994. Sustainable cities, regional policy and development series 7. Regional Studies Association. London and Bristol, Pennsylvania. Keirstead, J (2007) “Selecting sustainability indicators for urban energy systems” International Conference on Whole Life Urban Sustainability and its Assessment Kelly, G. and Baker, B.L., 2002. An evaluative framework and performance measures for the sustainable regions programme. CSIRO Sustainable Ecosystems. Meadows, D.H., 1998. Indicators and information systems for sustainable development. Mitcham, C., 1995. The concept of sustainable development: its origins and ambivalence. Technology in Society, 17(3), pp.311-326. Morse, S., 2003. For better or for worse, till the human development index do us part. Ecological Economics 45 (2), 281–296. Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A. and Giovannini, E., 2005. Handbook on constructing composite indicator OECD, 2003, Environmental Indicators Development, measurement and use. Available from http://www.oecd.org/env/indicators-modelling-outlooks/24993546.pdf Last accessed 28/01/2016 Pearce, D.W., Markandya, A. and Barbier, E., 1989. Blueprint for a green economy (Vol. 1). Earthscan. Roderick, M.L., Hobbins, M.T. and Farquhar, G.D., 2009. Pan evaporation trends and the terrestrial water balance. II. Energy balance and interpretation. Geography Compass, 3(2), pp.761-780. 30/04/2016

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Smart Cities: Intelligent Information and Communications Technology Infrastructure in the Government, Buildings, Transport, and Utility Domains Smeets, E. and Weterings, R., 1999. Environmental indicators: Typology and overview (p. 19). Copenhagen: European Environment Agency. Stoeckl, N., Walker, D., Mayocchi, C. and Roberts, B., 2004. Douglas shire sustainable futures: Strategic planning for implementation project report. Tang, T. S. K., 2011, Building Journal; Sustainable Systems Integrated Model; Modelling Techniques for LowCarbon Cities. Available from http://www.building.com.hk/forum/2011_0719modeling.pdf last accessed 28/01/2016 United Nations (2012) World Urbanization Prospects: The 2011 Revision United Nations, New York. United Nations Framework Convention on Climate Change, available from http://unfccc.int/meetings/paris_nov_2015/meeting/8926.php last accessed 25/01/2016 Waldron, D. and Williams, P.W., 2002. Steps towards sustainability monitoring: the case of the resort municipality of Whistler. Sustainable tourism: A global perspective, pp.180-194. WCED, U., 1987. Our common future. World Commission on Environment and Development Oxford University Press. Whate V., McCrum G., Blackstock K.L., and Scott A., 2006. The Macaulay Institute: Indicators and Sustainable Tourism: Literature Review, Available from http://www.macaulay.ac.uk/ruralsustainability/LiteratureReview.pdf last accessed 28/01/2016 Worden, K., Bullough, W.A. and Haywood, J. eds., 2003. Smart technologies. World Scientific. World Commission on Environment and Development, 1987; Our Common Future, available from http://www.undocuments.net/our-common-future.pdf last accessed 28/01/2016

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Appendix A: Final List of Indicators No.

Indicator

Scale

Definition

Unit of Measurement

Weighting

Pattern of Use

(1/8)

Temporal + Seasonal

Domain: Emissions Reduction Consumption of renewables

City Level

GHG emissions per sector (residential, industry, use type)

City Level

Renewable plants (managed by public/private authority) kWh produced

City Level

City Level

4.

Energy consumption of public buildings

City Level

5.

Total waste generated per year per capita

6.

Brownfield versus greenfield development

City/Sub City Level

Proportion on new development on brownfield sites. Ratio of new developments on brownfield to new developments on Greenfields.

Building Level

Area of roof space suitable for PV.

7.

Roof Space available for PV

1.

2.

3.

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Renewable energy consumption as a % of total energy consumption in the urban area.

% of renewable energy consumed by the city

The per capita emissions (Tonnes of Emissions eq. per individual).

C02/CH4/N2O/O3/CFC’s emissions per unit GDP (g/₏) (GHG emissions in tonnes per capita)

(A high value is negative)

Renewable electricity produced by LA/PA (kWh). (managed by public/private authority)

kWh per annum

(1/8)

The energy consumption of municipal buildings per sq. m measure. Municipal waste per capita

(A high value is positive)

(1/8)

Temporal + Seasonal

N/A

(A high value is positive)

average energy consumption of public buildings for both heating and electricity

(A high value is negative)

kg/inhabitant

(1/8)

(1/8)

Temporal + Seasonal

N/A

(A high value is negative)

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Ratio of brownfield to greenfield development

m2

(1/8)

(1/8)

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N/A

(A high value is positive) N/A


(A high value is positive)

8.

Roof Space Available for Solar Thermal

Building Level

Area of roof space suitable for Solar Thermal.

m2

(1/8)

N/A

(A high value is positive)

Domain: Energy Efficiency 9.

Final energy consumption, by sector

City Level

Energy dependency

City Level

10. City Level

11.

Energy consumption of public buildings II

City Level

12.

Building stock energy efficiency

City Level

13.

Residential Stock Energy Efficiency

14.

Commercial Stock Energy City Level Efficiency

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The total electricity consumption per capita (kWh/individual) Trends in electricity consumption. The percentage of total electricity consumption per capita generated elsewhere and imported.

Energy consumption per capita (GJ/inhabitant) % of energies utilised

(1/15)

Temporal + Seasonal N/A

(A high value is negative)

% of public buildings that have been audited in terms of their energy usage (i.e. building energy rating/efficiency assessment) New buildings and renovations assessed in terms of environmental sustainability. % of sustainably classified buildings (both new and renovated). Assessment of Energy Efficiency of Housing Stock based on unit type and year of construction.

Energy consumption of residential buildings (MJ/m2)by building type residential, public, commercial as % of total stock

Assessment of Energy Efficiency of Commercial Stock based on unit type and year of construction.

Energy consumption of structure (MJ/m2) with regard to adjusted environmental norms

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(1/15) (A high value is negative)

% of public buildings audited

(1/15) (A high value is positive)

Energy consumption of structure (MJ/m2) with regard to adjusted environmental norms

54

(1/15)

Temporal + Seasonal

N/A

(A high value is negative)

(1/15) (A high value is negative)

(1/15) (A high value is negative)

Temporal + Seasonal

Temporal + Seasonal


City Level

15.

Industrial Stock Energy Efficiency

City Level

16.

Leisure Stock Energy Efficiency

City Level

17.

Public Stock Energy Efficiency (Health) I

City Level

18.

Public Stock Energy Efficiency (Education) II Special Heritage Status

City/Sub City Level

Building with heritage designation attached.

20.

Electricity Exported to Grid

Building Level

Amount of surplus energy exported to the national grid.

City Level

Total resident population per km 2 of built up area.

Population per km2

21.

Residential population density Percentage of buildings assessed under a Building Energy Rating Scheme

City Level

This indicator defines the percentage of buildings classified among A+ and D.

% of total

19.

22.

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Assessment of Energy Efficiency of Industrial Stock based on unit type and year of construction.

Energy consumption of structure (MJ/m2) with regard to adjusted environmental norms

Assessment of Leisure Stock Energy Efficiency based on unit type and year of construction.

Energy consumption of structure (MJ/m2) with regard to adjusted environmental norms

Assessment of Public (or private) healthcare facility energy efficiency

Energy consumption of structure (MJ/m2) with regard to adjusted environmental norms Energy consumption of structure (MJ/m2) with regard to adjusted environmental norms Y/N-Specification

Assessment of public (or private) educational facility energy efficiency

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(1/15) (A high value is negative)

(1/15) (A high value is negative)

(1/15) (A high value is negative)

(1/15) (A high value is negative)

(1/15)

Temporal + Seasonal

Temporal + Seasonal

Temporal + Seasonal Temporal + Seasonal N/A

(A high value is negative) Kwh

(1/15) (A high value is positive)

(1/15)

Temporal + Seasonal N/A

(A high value is positive)

(1/15) (A high value is positive)

55

Temporal + Seasonal


23.

Population living within 300 metres to basic public services (indicator excluded, per rational advanced in section 4.5.)

Sub City Level

This considers the availability and vicinity of basic services.

% of the population

(1/15)

n/a

(A high value is positive)

Domain: Cost Reduction Sub City Level

Heat density demand informs viability of District Heating.

City/Sub City Level

Percentage of buildings occupied/vacant.

Smart Metering

City/Sub City Level

Number of Buildings with Smart Meters installed.

Capital Expenditure on Energy Infrastructure (indicator excluded, per rational advanced in section 4.5.) Total employment rate

City Level

Amount expended on the management, upkeep and development of energy infrastructure.

Heat Demand Density 24. Occupancy 25. 26. 27.

City Level

28.

% of working aged population employed in the locality.

Kwh/m2

(1/9) (A high value is positive)

%Buildings Occupied/Vacant

(1/9)

N/A

â‚Ź per head of population per annum

(1/9)

N/A

City unemployment rate and % of people in full time employment

Presence of specific interventions designed to generate energy (micro) at building level.

Y/N-Specification

29.

Building Level Building Level

Presence of specific interventions designed to reduce heating loss.

Y/N-Specification

30.

Retrofitted Elements (Insulation)

Grant No. 608775

Temporal + Seasonal

% of buildings equipped (A high value is positive)

Retrofitted Elements (Generation)

30/04/2016

(1/9) (A high value is positive)

Temporal + Seasonal

(A high value is positive)

(1/9)

N/A

(A high value is positive)

(1/9)

N/A

(A high value is positive)

(1/9) (A high value is positive)

56

N/A


Building Level

Presence of specific interventions designed to reduce heating loss.

Y/N-Specification

31.

Retrofitted Elements (Glazing)

Building Level

Presence of specific interventions designed to efficiently generate heat.

Y/N-Specification

32.

Retrofitted Elements (Heating)

30/04/2016

Grant No. 608775

(1/9)

N/A

(A high value is positive)

(1/9) (A high value is positive)

59

N/A


Appendix B: ‘Zurich List of Indicators’ Appendix 1 Determination Colour Key: Indicator accepted Indicator accepted pending viability Indicator rejected

Number

Indicator 1. Emissions Reduction

1

Consumption of renewables

2

GHG emissions per sector (residential, industry, use type)

3

Renewable plants (managed by public/private authority) kWh produced

4

Fuels Consumption (Transport)

5

Carbon Sequestering

6 7 8 9 10 11 12

Modal split of passenger transport Km of high capacity public transit system per 100,000 population GHG emissions by transport, by mode Public transport use Green mobility Private vehicle use Recycling rate

Determination

2. Energy Efficiency 13

Final energy consumption, by sector

14

Projections of GHG emissions

15

Energy dependency

16

Energy consumption of public buildings I

17

Energy consumption of public buildings II

18

Building stock energy efficiency

19

Residential Stock Energy Efficiency

20

Commercial Stock Energy Efficiency

21

Industrial Stock Energy Efficiency

22

Leisure Stock Energy Efficiency

23

Public Stock Energy Efficiency (Health) I

24

Public Stock Energy Efficiency (Education) II

25

Energy Storage Capacity

26

Peak Kw fuels or elec summer & winter

30/04/2016

Grant No. 608775

58


27

Generation of total waste by economic activity and GDP

28

Domestic water consumption

29

% of the city's solid waste that is recycled

30

Brownfield versus greenfield development

31

Special Heritage Status

32

Electricity Exported to Grid

33

Spatial Orientation

34

Roof Space available for PV

35

Retrofitted Elements

36

Residential population density

37

Accessibility to public transport stops

38

Percentage of buildings assessed under a Building Energy Rating Scheme.

39

Water consumption

40

Historic listed buildings and sites

41

Population living within 300 metres to basic public services

42

Commercial density 3. Cost Reduction

43

Heat Demand Density

44

Occupancy

45

Smart Metering

46

Average price per m2 for an apartment and a house

47

Average energy class efficiency of buildings in the city

48

Domestic water consumption

49

Capital Expenditure on Energy Infrastructure

50

Total employment rate

30/04/2016

Grant No. 608775

59


Appendix D: 186 ‘Long’ SUI List Indicator

Origin

Consumption of renewables

EU SDI theme: Climate change and energy

EU SDI Level 1

Final energy consumption, by sector

EU SDI sub-theme: Consumption patterns

EU SDI subtheme: Consum ption patterns level 3

Trends in electricity consumpt ion

Total electricity consumption per capita (kWh/individu al)

GHG emissions per sector

EU SDI sub-theme: Climate change

EU SDI subtheme: Climate change Level 2

Per capita CO2 emissions (tonnes CO2 eq. per individual ) and reduction targets are used as indicators

Total CO2e emissions per capita

Energy dependency

EU SDI sub-theme: Energy

EU SDI Level 2

30/04/2016

EU SDI

Informe d Cities

STATUS

TISSUE

Siemens Green City Index

Share of energy consumption produced by renewable resources

Renewable energy consumption as a % of total energy consumption in the urban area

% of renewabl e energy consumed by the city

Grant No. 608775

Energy consumpti on per capita (GJ/inhabi tant)

Tonnes of CO2e per capita per year

C0² emissions per unit GDP (g/€)

CDP for cities

Total amount of fuel consum ed by (in energy units) local govern ment annuall y GHG emissio ns for your local govern ment’s operati ons, in metric tonnes CO2e and whole commu nity

Global City Indicator

total electrical used per capita (kW/hr).

GHG emissions in tonnes per capita

60


Inhabitants connected to district heating system as a % of total population

Urban Ecosystem Europe indicator, theme local to global: energy and climate change

Energy consumption of public buildings (% of public buildings audited and average energy consumption of public buildings for both heating and electricity) % of buildings that receive an A or B BER, by building type residential, public, commercial as % of total stock Number of dwellings at risk of flooding Projections of GHG emissions

Urban Ecosystem Europe indicator, theme local to global: energy and climate change.

Energy consumption of municipal buildings per sq. m measure

DCC indicator

New buildings and renovations assessed in terms of environmenta l sustainability

30/04/2016

EU SDI sub-theme: Climate change

measures total volumes in m3 served, heat produced in kWh and electricity produced in kWh as well as what fuel is used by district heating

% of sustainably classified buildings (both new and renovated)

Energy consumpti on of residentia l buildings (MJ/m2)

EU SDI level 3

Grant No. 608775

61


Renewable plants (managed by public authority) kWh produced

Urban Ecosystem Europe indicator, theme local to global: energy and climate change.

Number of CHP units within the private housing and commercial sectors, assessed against an annual target Proposed Actions Global surface average temperature Gross inland energy consumption by fuel Energy generation from renewables.

DCC Climate Change Strategy

30/04/2016

EU SDI level 3 Electricit y generati on from renewab les

Certified green electricity produced by LA (kWh)

How much electrici ty, heat, steam, and cooling (in energy units) has your local govern ment purchas ed for its own consum ption during the reporti ng year?

EU SDI sub-theme: Climate change

EU SDI sub-theme: Energy

EU SDI sub-theme: Energy

Grant No. 608775

62


Need to be broken down into % heat, % electricity and % CHP Implicit tax rate on energy Local contribution to global climatic change An assessment the extensivenes s of cities' energy efficiency standards for buildings An assessment of the extensivenes s of efforts to promote energy efficiency of buildings. An assessment of the extensivenes s of policies promoting the use of clean and efficient energy An assessment of the ambitiousnes s of CO2 emissions

30/04/2016

EU SDI sub-theme: Energy European Common Indicator

Siemens Green City Index Qualitative measure scored on a scale of 0 - 10

Siemens Green City Index Qualitative measure scored on a scale of 0 - 10

Siemens Green City Index Qualitative measure scored on a scale of 0 - 10

Siemens Green City Index Qualitative measure scored on a scale of 0 - 10

Grant No. 608775

63


reduction strategy

Generation of total waste by economic activity and GDP (proxy Municipal waste generated kg per inhabitant). Enterprises with a registered environment al management system

EU SDI sub-theme: Resource use and waste.

EU SDI level 2

Househol d waste per capita.

Per capita amount of waste and share of municipal waste collected separately.

Annual kg per capita

EU SDI sub-theme: Production patterns

EU SDI level 2

Environm ental certificati on of public authoritie s

Adoption of EMP and EMS

Domestic water consumption (L/individual/ day)

Urban Ecosystem Europe indicator and Global City Indicator (GCIF per capita measure)

Domestic water consumpt ion

Number of Local Authority departments with certified EMS, also number of private companies with EMS. Domestic water consumption

Water network's leakages

Urban Ecosystem Europe

UEE indicator

Green public procurement, procedures and purchasing

Urban Ecosystem Europe indicator, theme responsible consumption and lifestyle choices

Green public procurem ent, procedur es and purchasin g

% of the city's solid waste that is recycled

Global City Indicator

30/04/2016

water loss in pipelines

Grant No. 608775

Domestic water consumption per capita (m3/yr/capita )

Municipal waste per capita (kg/inhabi tant)

Annual water consumpti on per capita (m3/inhab itant) Water system leakages (%)

Domestic water consumpti on per capita

Share of waste recycled (%)

% of the city's solid waste that is recycled

% of water loss

64


Quality of potable water supply service

Global City Indicator

Proportion of total/biodegr adable waste production sent to landfill Proportion of population connected to a wastewater treatment plant

STATUS

Proportion of urban water supplies subject to water metering Waste disposal levies Total amount of waste exported

STATUS

30/04/2016

STATUS

% compliance with drinking water standards

EU SDI level 3 % of total populati on connecte d to a wastewa ter treatme nt plant

% of total populatio n connecte d to a wastewat er treatment plant and % of wastewat er treated at primary, secondary and tertiary levels of treatment

STATUS indicator

% of city population served by wastewater collection

Compliance with EU standards on wastewater treatment.

% compliance with urban waste water standards

% of the city population with sustainabl e access to an improved water source. % of dwellings connected to sewage system

% of dwellings connected to sewage system

% of city population served by wastewate r collection

STATUS indicator

MONET

DCC indicator

Grant No. 608775

65


Motorisation rate

Components of Domestic Material Consumption Litter pollution Eco-label awards Area under agrienvironment al commitment Area under organic farming Re-use of wastewater by sector (as a % of wastewater generated) Re-use of rainwater (number of households with rainwater collection systems) Resource productivity

Environment al impact of material consumption (proxy: Domestic Material

30/04/2016

EU SDI sub-theme: Consumption patterns contextual indicator EU SDI sub-theme: Resource use and waste

EU SDI level 3

Number of registered cars

EU SDI level 3

Number of personal automobil es per capita Domestic consumption

Local authority services indicator EU SDI sub-theme: Production patterns EU SDI sub-theme: Production patterns

EU SDI level 3

EU SDI sub-theme: Production patterns

EU SDI level 3

EU SDI level 3

Urban Ecosystem Europe indicator

Urban Ecosystem Europe indicator

EU SDI theme: Sustainable consumption and production EU SDI sub-theme: Resource use and waste

EU SDI level 1

EU SDI level 3

Househol d and municipal waste produced

Grant No. 608775

66


Consumption , by material)

Consumption of certain foodstuffs per inhabitant Number of households Household expenditure per inhabitant, by category (food and non-alcoholic beverages) Livestock density index % of city population with regular solid waste collection Percentage of city population with authorized electrical service Dwelling completions by region. % of buildings occupied. Cycle paths and lanes (in km)

30/04/2016

EU SDI sub-theme: Consumption patterns

EU SDI sub-theme: Consumption patterns EU SDI sub-theme: Consumption patterns

EU SDI sub-theme: Production patterns Global City Indicator

Global City Indicator

Spatial planning: Maguire and Curry 2007 b

Urban Ecosystem Europe indicator could also be considered in transport theme.

Meters of cycle paths and lanes per 100 individual s

Length of dedicated cycle lanes

Grant No. 608775

Total length of cycle paths divided by total city surface area (km/km2)

Length of cycle lanes (km/km2)

67


Pedestrian areas (streets in km, areas in Ha)

Urban Ecosystem Europe indicator could also be considered in transport theme.

Public green areas

Urban Ecosystem Europe indicator.

Job/Housing ratio

Global City Indicator

Number of broadband internet connection per 100,000 population Brownfield versus greenfield development

Global City Indicator

Residential population density

TISSUE CORE 1

30/04/2016

TISSUE CORE 1

Total length of pedestrian, car free and calming streets divided by total city surface area (km/km2) Public green areas (m2 per individual ), also green areas as a % of total municipal area

Proportion of population living within 300m of public open area

Number of inhabitants living within 300 m from open areas (> 5000 m2) divided by total population to get %

Green area in hectares per 100,000 population

Total number of jobs divided by the total number of inhabitants of population living in houses within the boundary of the city neighbourhoo d

GCIF indicator

GCIF indicator

Proportion on new development on brownfield sites

Grant No. 608775

Ratio of new developments on brownfield to new developments on greenfields Total resident population per km 2 of built up area

68


Ratio (%) of inhabitants within 300 m from basic services to all inhabitants

TISSUE CORE 2 and STATUS

STATUS indicator

Percentage of total population/h ouseholds living in substandard/ unfit housing Average living area in m2 per person Fragmentatio n of natural and semi natural habitats Conversion of land/land use changes Soil sealing (m2 per citizen) and the changes in five years periods Number of contaminate d sites identified and remediated Built up areas

TISSUE CORE 2

Proportion of dwelling classes as adequate or decent standard

Sq m of public indoor

Global City Indicator

30/04/2016

Inhabitants living within 300m of basic services divided by total inhabitants to get %

Urban audit

MONET

MONET

TISSUE CORE 2

Spatial planning: Maguire and Curry 2007 b. Eurostat 2007 SDIs in EU NSDS - Built-up areas as % of total land area

Grant No. 608775

69


recreation facility space per capita Sq m of public outdoor recreation facility space per capita Sq m of private outdoor space per capita Number of business clusters, industrial parks, Sizes IE zones % population living in slums Ratio (%) of the surface of urbanised areas to the total municipal area. Average price per m2 for an apartment and a house Developed land per capita Modal split of passenger transport

30/04/2016

Global City Indicator

Global City Indicator TISSUE CORE 2

Urban audit

MONET key indicator EU SDI sub-theme: Transport growth

EU SDI subtheme: Transpor t growth (level 2)

Modal split of journeys to work

Grant No. 608775

Share of each transport mode on the total number of trips as %

share of people walking or cycling to work (%), and share of people taking public transport (%)

70


Energy consumption, by transport mode

EU SDI sub-theme: Transport growth

EU SDI subtheme: Transpor t growth (level 3)

People killed in road accidents per mode/per 10,000 inhabitants/p er year

EU SDI sub-theme: Social and environmental impact of transport

EU SDI level 2

Km of high capacity public transit system per 100,000 population

Global City Indicator

Accessibility to public transport stops

TISSUE CORE 2

Average waiting time for a different

Urban audit

30/04/2016

Number of pedestrian and cyclist fatalities as a result of road traffic accidents/yea r/10000 inhabitants and number or car fatalities/year /10000 cars

TISSUE CORE 2 - energy consumption for transport per tonne-km (freight transport) – (MJ/tonnevkm) − energy consumption for transport per passenger-km (passenger transport) – (MJ/pkm). Death per million car km

Meters of undergro und and tramlines per 100 individual s

Transporta tion fatalities per 100,000

Length of public transport network (km/km2)

Share of population living within 300 m from an hourly (or more frequent) public transport service

Grant No. 608775

Km of light passenger transit system per 100,000 population .

Inhabitants living within 300m of public transport access divided by total number of inhabitants to get %

71


modes of public transport in rush hour Mean travel times to work/school Accessibility of public transport to people with disabilities Modal split of freight transport Passenger transport demand (average distance km/per person/per day) Proportion of all journeys under 5 km by private car use Volume of freight transport and GDP Volume of passenger transport and GDP Price indices for transport

GHG emissions by transport, by mode

30/04/2016

RPG indicator

NTA indicator

EU SDI sub-theme: Transport growth TISSUE CORE 1

STATUS

EU SDI sub-theme: Transport growth

EU SDI sub-theme: Transport growth

EU SDI sub-theme: Transport prices contextual indicator EU SDI sub-theme: Social and environmental impact of transport

Grant No. 608775

72


Average CO2 emissions per km from new passenger cars Emissions of ozone precursors from transport Emissions of particulate matter from transport Low emission public transport fleet number of vehicles) Underground and tram lines in the urban area An assessment of the extensivenes s of efforts to increase the use of cleaner transport. An assessment of efforts to reduce vehicle traffic within the city.

30/04/2016

EU SDI sub-theme: Social and environmental impact of transport EU SDI sub-theme: Social and environmental impact of transport EU SDI sub-theme: Social and environmental impact of transport Urban Ecosystem Europe indicator, theme planning, design and better mobility, less traffic Urban Ecosystem Europe indicator, theme planning, design and better mobility, less traffic Siemens Green City Index Qualitative measure scored on a scale of 0 - 10

Proportion of public transportatio n classed as low emission

Siemens Green City Index Qualitative measure scored on a scale of 0 - 10

Grant No. 608775

73


Population trends of key species (e.g. bird) in the local authority or region

EU SDI sub-theme: Biodiversity

Common bird index (level 1) and red list index for EU species (level 3)

Biochemical oxygen demand (BOD) in rivers Forest increment and fellings Forest trees damaged by defoliation Proportion of waterways classified at least as of "good" status (according to EU classifications ) Number of designated protected sites Surface and groundwater abstraction

EU SDI sub-theme: Fresh water resources

EU SDI level 3

Use of fertilisers and pesticides Common Bird Index

UNECE common indicator

Fish catches taken from

EU SDI theme: Natural resources

30/04/2016

Trend in locally relevant species of habitats. Data on consistency of populations (Data should be available from monitoring for SACs and SCIs)

Types and numbers of threatened/pr otected species. Types and numbers of bird species and/or other relevant species.

EU SDI sub-theme: Land use EU SDI sub-theme: Land use STATUS

STATUS indicator

EU SDI sub-theme: Biodiversity

EU SDI sub-theme: Fresh water resources

EU SDI theme: Natural resources

Grant No. 608775

74


stocks outside safe biological limits Deadwood on forest land Concentratio n of mercury in fish and shellfish Size of fishing fleet Critical load excedance for nitrogen % of the city's wastewater that has received no treatment Healthy lifeyears and life expectancy at birth, by gender Death rate due to chronic diseases, by age group Suicide death rate, by gender and by age group Self reported unmet need for medical examination or treatment by income quintile Overweight people, by age group

30/04/2016

EU SDI sub-theme: Biodiversity EU SDI sub-theme: Marine ecosystems EU SDI sub-theme: Marine ecosystems EU SDI sub-theme: Land use Global City Indicator

EU SDI theme: Public health

EU SDI level 1

EU SDI sub-theme: Health and health inequalities

EU SDI level 2

EU SDI sub-theme: Health and health inequalities

EU SDI level 3

Average life expectanc y

EU SDI sub-theme: Health and health inequalities

EU SDI sub-theme: Determinants of health

EU SDI level 3

Grant No. 608775

75


Present smokers, by gender and by age group Population exposure to air pollution by particulate matter

EU SDI sub-theme: Determinants of health

EU SDI level 3

EU SDI sub-theme: Determinants of health

EU SDI level 3

Population exposure to air pollution by ozone

EU SDI sub-theme: Determinants of health

Population living in households considering that they suffer from noise

EU SDI sub-theme: Determinants of health

NO2 concentratio ns (µg/m3)

Urban Ecosystem Europe Indicator, theme local action for health and natural common goods

Average daily SO2 emissions (ug/m3) Number of in-patient hospital beds per 100,000 population

Siemens Green City Index

30/04/2016

EU SDI level 3

Highest annual means (μg/mc ) and number of daily means exceeding 50 μg/mc Daily exceedan ce in a year (n. days recording a 8h mean value > 120 µg/m3). People exposed to noise

Concentration and exceedance values (n. days recording a mean value > 50 µg/m3 )

Population exposed to (Day (Lden) > 55 dB(A) and Night (Lnight) > 45 dB(A)

Share of population exposed to (Day (Lden) > 55 dB(A) and Night (Lnight) > 45 dB(A)

UEE indicator

Average mean NO2 concentration

annual average concentration of NO2.

Global City Indicator

Daily excedance in a year values used by TISSUE CORE 1

PM10 concentra tions (µg/m3)

Ozone concentration (µg/m3)

Ozone concentra tion (µg/m3)

PM10 concentrat ions (µg/m3)

GCIF indicator

Grant No. 608775

76


% of population aged 15 and over with high level of mental wellbeing Contentment with life Adolescent birth rate Proportion of population who are members of sport association or club International comparison of healthcare Persons with a disability by age % number of services for disabled people available % number of services for older people available Healthy lifeyears and life expectancy at age 65, by gender Salmonellosis incidence rate in human beings Serious accidents at work

30/04/2016

MONET key indicator

MONET MDG indicators DCC indicator

DCC indicator

CSO QoL report indicator Suggested measure during the workshop

Suggested measure during the workshop EU SDI sub-theme: Health and health inequalities

EU SDI sub-theme: Determinants of health

EU SDI sub-theme: Determinants of health

Grant No. 608775

77


Under age five mortality per 1000 live births Number of physicians per 100,00 population Availability of person to rely upon Index of production of chemicals, by toxicity class Transposition of Community law, by policy area Level of citizens' confidence in EU institutions Egovernment on-line availability Voter participation (as a percent of eligible voters)

Global City Indicator

GCIF indicator

Global City Indicator

GCIF indicator

% of women employed in the city government workforce

Global City Indicator

Number of serious crimes per

Global City Indicator

30/04/2016

MONET

EU SDI sub-theme: Determinants of health EU SDI sub-theme: Policy coherence and effectiveness

EU SDI level 3

EU SDI sub-theme: Policy coherence and effectiveness contextual indicator

contextu al

EU SDI sub-theme: Openness and participation

EU SDI level 3

Global City Indicator

Voter turnout in national and EU parliame ntary elections EU SDI level 2

Proportio n of registered electorate voting in city elections

% of elected city represent atives who are women.

Voter participati on in last municipal election (as % of eligible voters)

Share of women in leading local positions

total number of incidents of crime per

Grant No. 608775

Violent crime rate

78


1000 population

100,000 population Measure of gang related activity and juvenile crime Percentage of residents who feel safe whilst outside during the day / after dark Existence of regular forums between local government and local business representativ es on issues of local concern Citizen satisfaction with the local community Inequality of tax burden New infringement cases, by policy area Egovernment usage by individuals Shares of environment al and labour taxes in total tax revenues

30/04/2016

per 100,000

Global City Indicator

STATUS

STATUS

European Common Indicator

MONET EU SDI sub-theme: Policy coherence and effectiveness EU SDI sub-theme: Openness and participation

EU SDI level 3

EU SDI sub-theme: Economic instruments

EU SDI level 2

Grant No. 608775

79


Sustainable management of the local authority and local business The highest level of responsibility for climate change (SD) in the local authority Regular use of a second language Population disposing sufficiently of spare time Number of police officers per 100,000 Number and proportion of citizens (i) engaged in environment al and sustainability oriented activities and/or (ii) average time in hours spent per year and inhabitant in such activities.

30/04/2016

European Common Indicator

CDP for cities

MONET

MONET

Global City Indicator

TISSUE CORE 2

Grant No. 608775

80

INDICATE Sustainable Urban Indicators  

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