D3.4 - Tools on the avoided damages and benefits per demo

` Tools on the avoided damages and benefits per demo Deliverable 3.4 Accelerating and upscaling transformational adaptation in Europe: demonstration of water-related innovation packages This project has received funding from the European Union’s Horizon H2020 innovation action programme under grant agreement 101036683. TransformAR Deliverable 3.4 2 www.transformar.eu Deliverable Number and Name D3.4 - Tools on the avoided damages and benefits per demo Work Package WP3 – Envisioning transformative pathways for the demonstrators Dissemination Level Public Author(s) Stelios Karozis, Ioannis Zarikos, Athanasios Sfetsos Primary Contact and Email Stelios Karozis, [email protected] Date Due July 2023 Date Submitted Version 5 (31/07/2023) Version 6 (02/07/2025) - After addressing comments from the external reviewers. File Name TransformAr_WP3_D3.4_Tools_on_the_avoided_damages _and_benefits_per_demo_final Status Version 5 (31/07/2023) Version 6 (02/07/2025) - After addressing comments from the external reviewers. Reviewed by (if applicable) J. Cool, A. Trabucco, A. Bjornavold, R. Nagy (Version 5) Fred Hattermann (Version 6) Suggested citation S. Karozis, I. Zarikos, A. Sfetsos (2025) Tools on the avoided damages and benefits per demo. TransformAR Deliverable 3.4, H2020 grant no. 101036683 © TransformAR Consortium, 2021 This deliverable contains original unpublished work except when indicated otherwise. Acknowledgement of previously published material and of the work of others has been made through appropriate citation, quotation, or both. Reproduction is authorised if the source is acknowledged. This document has been prepared in the framework of the European project TransformAR. This project has received funding from the European Union’s Horizon 2020 innovation action programme under grant agreement no. 101036683. The sole responsibility for the content of this publication lies with the authors. It does not necessarily represent the opinion of the European Union. Neither the EASME nor the European Commission are responsible for any use that may be made of the information contained therein. TransformAR Deliverable 3.4 3 www.transformar.eu TransformAR Deliverable 3.4 4 www.transformar.eu TABLE OF CONTENTS ABBREVIATIONS ..................................................................................... 5 EXECUTIVE SUMMARY .............................................................................. 6 INTRODUCTION ...................................................................................... 7 TRANSFORMAR AVOIDED DAMAGE FRAMEWORK .......................................... 8 Overall concept and method ............................................................... 8 High data availability - KPI based approach ........................................... 9 Sparse data – High level approach ..................................................... 10 Avoided damages estimation ............................................................ 13 TRANSFORMAR AVOIDED DAMAGE APPLICATION ....................................... 15 High data availability - KPI based approach web app ............................ 15 Sparse data – High level approach code ............................................. 17 INTEGRATION IN TRANSFORMAR AND BEYOND .......................................... 18 ANNEX A: APPLICATION PER DEMO .......................................................... 19 ANNEX B: KEY PERFORMANCE INDICATORS .............................................. 32 TransformAR Deliverable 3.4 5 www.transformar.eu ABBREVIATIONS Abbreviations Description TADF TransformAr Avoided Damaged Framework TADA TransformAr Avoided Damaged Application DSS Decision Support System WP Work Package CEI Choice Experiment for Investors URB Urban runoff system CAF Crowdsourcing Citizen app ICW Integrated Constructed Wetlands RES Renewable Energy Sources ICWM Integrated Constructed Wetlands Monitoring GB Green Bonds NBS Nature-Based Solution AF Local Adaptation Fund NUDG Nudging MRM Mussel-Raft Monitoring INTERM Intertidal monitoring RI Resilience Index INSUR Insurance scheme SCS Smart Climate Stations CAE Citizen App Engagement AWAR Awareness-raising modules CIH Climate Innovation Hub SG Smart Grid and gates COAST Coastal contract DSI Demand analysis for social Services/Infrastructures DB Database CEI Choice experiment TransformAR Deliverable 3.4 6 www.transformar.eu EXECUTIVE SUMMARY The current deliverable is type “Other” and this document is functioning as a summary presentation of two main elements of Task 3.3 - Analysis of avoided damages and other direct benefits of pathways at demonstrator scale: 1. The TransformAr Avoided Damages Framework (TADF) 2. The TransformAr Avoided Damages web-based Application (TADA) The TADF includes and integrates the steps that demonstrators followed in order to decide the climate hazards of interest, the solutions that address them and a way to quantify the effectiveness via the calculation of KPIs before and after the implementation of the solution. On the other hand, TADA is a web-based application that functions as a presentation of tools and solutions used for the TransformAr project, and at the same time as potential replicator to find the most relevant solution based on a multicriteria selection. D3.4 serves as an information baseline to communicate on the project impacts, support policy making, and serve as a basis for Task 3.4. Moreover, the experience and knowledge gained from the demonstrators, will be used to produce a guideline of good practices, to disseminate results and render them usable and useful in other cases (D3.5). As a follow-up to the recommendations received in the context of the second project review (February 2025), the document was restructured complementary to D3.5. D3.4 is focusing on the methodologies developed to assess the avoided damages, whereas D3.5 focuses on the application and best practices. As such, another method was developed to tackle the problem of data availability (sparse data approach) and make a stronger connection with WP2 more obvious. As a result, the avoided damages assessment can follow a data intensive approach (High data availability approach – KPIs) or a simplified approach whereas the effectiveness of solutions and high level changes in the climate condition of the futures are needed. Both methods end with the same type and format of results for consistency and have been integrated in the web application final version (due end of the project). TransformAR Deliverable 3.4 7 www.transformar.eu Introduction In the current deliverable, the TransformAr Avoided Damages Framework (TADF) and the TransformAr Avoided Damages web-based application (TADA) are presented for evaluating and assessing effectiveness or avoided damages of the adaptation pathways produced in Task 3.2 per demonstrator. The term Avoided Damages could have different interpretations depending on the context. However, in general terms, it refers to taking measures or actions to prevent or minimize damage from occurring hazards. In the existing literature there is absence of an “Avoided damages” approach. The general approach is the cost-benefit analysis of adaptation efforts, based mainly on the economic impact (losses), by the various hazards. The majority of the approaches applied to date are focused on the post-disaster analysis and adaptation of disasters, without prevention planning and analysis of the potential associated economic and environmental hazards. An attempt, similar to the approach of TADF, of a pre-disaster framework is published by UNESCO 1 . In addition, Valverde, M. J., et al., 2022 2 proposed an avoided damages due to floods that are directly correlated to climate change and it is aiming to bridge the gap between preand post-hazards assessment. More precise, a series of suggested steps, from defining the cost of inaction to monetize the adaptation costs, are presented, alongside the cases of Austria and France. As it is stated, the data of aforementioned cases cannot extrapolated to European level. In the context of the TransformAr project and Task 3.3 - Analysis of avoided damages and other direct benefits of pathways at demonstrator scale, Avoided Damages are the quantification of potential effectiveness of solutions implemented at demonstrator level to cope with climate change risks. The solutions have been proposed by the demonstrators of the TransformAr project during the compilation of the proposal and have been discussed and agreed upon with stakeholders during the demonstrators’ workshops (Task 3.2). The adaptation pathways defined in Task 3.2 were derived to be elaborated in the context of Avoided Damages and utilizing the tools and data compiled in WP2 to estimate the effectiveness of the solutions. Towards the latter, the TADF was compiled and applied to the demonstrators. In addition, TADA works as a presentation of tools used by the demonstrators, their descriptions and the presentation of results of the solution using Key Performance Indicators (KPIs) 3 via an online interface. Moreover, a multicriteria function is accommodating possible replicators to find information on the project impacts at demonstrator level, and the most relevant solutions for their region / hazard / type of solution. The good practices and guidelines for avoiding damages and other direct costs in regional governance scale will be derived from TADA and described in D3.5. 1 https://unesdoc.unesco.org/ark:/48223/pf0000384487 2 Valverde, M. J., et al., 2022, Costs of adaptation vs costs of inaction 3 Key Performance Indicators (KPIs) are measurable values that organizations use to assess the success or effectiveness of specific actions, processes, or strategies. KPIs help monitoring progress, identify areas for improvement, and evaluate the overall performance of an action. TransformAR Deliverable 3.4 8 www.transformar.eu TransformAr Avoided Damage Framework Overall concept and method In the context of the TransformAr project, the concept of Damages and Avoid Damages from climate change is developed and defined based on the current literature. As such, damages from climate change encompass a broad range of adverse impacts that are not adequately mitigated or adapted to, while avoided damages represent the benefits of effective mitigation and adaptation efforts, preventing potential future impacts. Following the definitions, an assessment framework was introduced that provides generalized quantification of avoided damages. The framework is based on estimating the current situation (baseline) and the potential effectiveness of solutions implemented at demonstrator level to cope with climate change impacts. The difference between the baseline and the effectiveness of the solutions describes the level of the damages that have been avoided. The same can be applied for the future climate scenarios, thus, estimating the avoided damages from climate change. Important and noted is that the framework needs to be applied for each climate stressor / hazard separately. In addition, to accommodate the potential lack of available data, two version of the approach is introduced; (i) High data availability - KPI based approach and (ii) Sparse data – High level approach (see Section below). For both cases, the impact quantification can be extracted via tools and models from WP2 or by expected estimation from experts. The expert input can be a percentage estimation of the amount of change in the KPI used, based on their experience, knowledge, literature review or best practices. It is noted, that in D3.5, that concerns the good practices and guidelines for avoiding damages and other direct costs in regional governance scale, will include an update of TADF based on the TADA data and TransformAr Demonstrators feedback during the implementation. The updated version will be based on the feedback from implementing in the demonstrators of TransformAr and incorporating the knowledge, tools and data from WP2. Figure 2.1 Avoided damages High data and sparse data availability approaches. TransformAR Deliverable 3.4 9 www.transformar.eu High data availability - KPI based approach Methodology The demonstrators of TransformAr were very diverse in terms of climate stressors / climate hazards, sector impacted, regional properties and solution implemented. To deliver a generalized and easy to replicate avoided damaged framework, the core element of the assessment is an extensive list of Key Performance Indicators (KPIs). In ANNEX A: Application per demo, the implementation of the framework per hazard and the data gathered from the demonstrators of the TransformAr are presented, whereas in ANNEX B: KEY PERFORMANCE INDICATORS presents a series of KPIs that demonstrators and replicators can choose from. The potential user of the framework should: • Estimate the climate stressors / climate hazards that are relevant for the region under study • Choose the KPIs that are relevant to: o the region o the potential solutions o the categories of impact under study o the data that are available or can be provided The KPIs are grouped into 5 categories of impacts: • Physical • Social • Environmental • Health • Economics KPI quantification can be derived from models, datasets available at the regional or national level, expert opinion, and sensors (e.g., Internet of Things (IoT) devices). In the case of TransformAr, sensor solutions, locally available information, and datasets (provided by WP2) were amended by models. The impacts that have been quantified via the KPIs are the basis to estimate the damages in three categories: • Direct damages: Includes the Physical impacts • Indirect damages: Consist of Economic and Environmental impacts • People damages: Represents the Health and Social Impacts In order to group the impacts into damages’ categories, the estimated 𝐾𝑃1,…,𝐾𝑃𝑛 for each category, are scaled to 𝐾𝑃𝑛∈{0,1} and the importance of each one is assessed. The latter is accomplished with the end-user opinion together with expert consulting. The importance is depicted in a scale between 1 and 5, thus, for each 𝐾𝑃𝑛 a scoring is correlated 𝑎𝑛where 𝑎𝑛∈{1,5}. Then, the damage is estimated as follows: 𝐷 =∑(𝑎𝑛 5×𝐾𝑃𝑛) 𝑛 1 Formula 2.1 In Figure 2.2, the overall process is illustrated, from the KPIs estimation to direct, indirect and People damages. TransformAR Deliverable 3.4 16 www.transformar.eu Figure 3.2 TADA main page. Figure 3.3 TADA multi-criteria interface. TransformAR Deliverable 3.4 17 www.transformar.eu Figure 3.4 TADA, High availability approach. The main application comprises of two parts. The multicriteria section on the left, where the user can choose the type of hazard, type of environment, and applied solution. In addition to that, the application allows the user to import new data to the database. Based on the multicriteria selection, the results are presented on the right-hand section on the app. The results comprise of: • Impact category • KPI category • KPI name • KPI definition • KPI equation/source Sparse data – High level approach code For the sparse data case, a python code has been developed that can be utilized in order to apply the TADF with small data availability. The code with a dummy dataset can be found in https://doi.org/10.5281/zenodo.15324264 (Karozis, S., & Zarikos, I. (2025). Avoided Damages estimation in Climate Resilience concept - High level approach (0.5). Zenodo.) In addition, the code was integrate in the updated version of the TADA. TransformAR Deliverable 3.4 18 www.transformar.eu Figure 3.5 TADA, Sparse data approach. Integration in TransformAr and beyond The current deliverable serves as a summary presentation of two essential components of Task 3.3 - Analysis of avoided damages and other direct benefits of pathways at the demonstrator scale. The TransformAr Avoided Damages Framework (TADF) is a framework encompasses the steps undertaken by demonstrators to identify climate hazards, select appropriate solutions, and quantify their effectiveness through Key Performance Indicators (KPIs) before and after implementation. The TransformAr Avoided Damages web-based Application (TADA) serves as both a showcase of tools and solutions utilized in the TransformAr project and a potential replicator, allowing users to find relevant solutions based on a multicriteria selection process. Under the TransformAr project, TADF and TADA will provide a comprehensive and replicable workflow to estimate the effectiveness of the solutions implemented during the project. At the same time, they will function as DB for all solutions and best practices of the TransformAr project, that will help potential replicators to choose and assess their solution beyond TransformAr. TransformAR Deliverable 3.4 19 www.transformar.eu ANNEX A: Application per demo Annex A presents the available solutions and the linked KPIs for each impact category for each case study (shown in Section 2). Municipality of Egaleo Heatwaves Physical Social Environmental Health Economic KPI per catego ry Increased integration of RES Global Climate Risk Index Fire Weather Index Safe sanitation access Resilience Index Risk exposure Access to energy Imports of goods and services (% of GDP) GDP Growth Contribution Unemployment Rate Increased integration of RES Global Climate Risk Index Fire Weather Index Mortality Rate Quality of health services Death rate Safe sanitation access Reduced emissions Global Climate Risk Index Fire Weather Index Air Quality Index Air pollution Resilience Index Risk exposure Global Climate Risk Index Fire Weather Index Air Quality Index Health impacts of exposure to noise from transport Mortality Rate Life expectancy rates Quality of health services Death rate Air pollution Healthy life expectancy GDP deflator Exports of goods and services (% of GDP) Imports of goods and services (% of GDP) GDP Growth Contribution Productionbased CO2 intensity, energy-related CO2 per capita Unemployment Rate Reduced emissions Increased integration of RES Global Climate Risk Index Fire Weather Index TransformAR Deliverable 3.4 20 www.transformar.eu Healthy life expectancy Resilience Index Local risk perception Risk exposure Risk perception Resilience Index Risk exposure Health impacts of exposure to noise from transport Resilience Index Risk exposure Access to energy Solutio n Climate Innovation Hub Demand analysis for social services/infrast ructures (DSI) Smart climate stations (SCS) Citizen app (CAE) Climate Innovation Hub Demand analysis for social services/infrast ructures (DSI) Smart climate stations (SCS) Citizen app (CAE) Climate Innovation Hub Demand analysis for social services/infrast ructures (DSI) Smart climate stations (SCS) Citizen app (CAE) Climate Innovation Hub Demand analysis for social services/infrast ructures (DSI) Smart climate stations (SCS) Citizen app (CAE) Climate Innovation Hub Demand analysis for social services/infrast ructures (DSI) Smart climate stations (SCS) Citizen app (CAE) Percen tage affecte d due to CC [%] TransformAR Deliverable 3.4 21 www.transformar.eu Guadeloupe Archipelago Drought Physical Social Environmental Health Economic KPI per category Global Climate Risk Index Water stress level Safe sanitation access Drinking water access GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Water stress level Safe sanitation access Drinking water access Risk perception Global Climate Risk Index Global Climate Risk Index Water stress level Drinking water access GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Solution Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Percentage affected due to CC [%] TransformAR Deliverable 3.4 22 www.transformar.eu Coastal erosion Physical Social Environmental Health Economic KPI per category Global Climate Risk Index GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Risk perception Global Climate Risk Index Global Climate Risk Index GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Solution Adaptation Fund (AF) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Adaptation Fund (AF) Adaptation Fund (AF) Percentage affected due to CC [%] Flood Physical Social Environmental Health Economic KPI per category Global Climate Risk Index Water stress level Safe sanitation GDP Growth Contribution Unemployment Rate Global Climate Risk Index Resilience Index Global Climate Risk Index Water stress level GDP Growth Contribution Unemployment Rate Import value index TransformAR Deliverable 3.4 23 www.transformar.eu access Drinking water access Resilience Index Import value index GDP per capita Global Climate Risk Index Water stress level Death rate Safe sanitation access Drinking water access Resilience Index Risk perception Death rate Drinking water access Resilience Index GDP per capita Global Climate Risk Index Resilience Index Solution Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Percentage affected due to CC [%] Hurricane Physical Social Environmental Health Economic KPI per category Global Climate Risk Index Imports of goods and services (% of GDP) Global Climate Risk Index Global Climate Risk Index Exports of goods and services (% of GDP) TransformAR Deliverable 3.4 24 www.transformar.eu Safe sanitation access Drinking water access Resilience Index GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Death rate Safe sanitation access Drinking water access Resilience Index Risk perception Resilience Index Death rate Drinking water access Resilience Index Imports of goods and services (% of GDP) GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Resilience Index Solution Adaptation Fund (AF) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Adaptation Fund (AF) Adaptation Fund (AF) Percentage affected due to CC [%] TransformAR Deliverable 3.4 25 www.transformar.eu Rising temperatures Physical Social Environmental Health Economic KPI per category Global Climate Risk Index Water stress level GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Water stress level Risk perception Global Climate Risk Index Global Climate Risk Index Water stress level GDP Growth Contribution Unemployment Rate Import value index GDP per capita Global Climate Risk Index Solution Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Adaptation Fund (AF) Nudging (NUDG) Adaptation Fund (AF) Percentage affected due to CC [%] ` ANNEX B: KEY PERFORMANCE INDICATORS Annex B presents each KPI used in this framework to quantify the effectiveness of a single or the combination of multiple solutions. Category KPI Name KPI Definition KPI Units | Formula Indicative source (if any) Inflation GDP deflator The GDP price deflator shows how much a change in GDP relies on changes in the price level. Percentage | Directly from data https://stats.oecd.org/Index.aspx?DataSetCode=GREEN_GROWTH# Trade Exports of goods and services (% of GDP) Transactions in goods and services (sales, barter, and gifts) from residents to nonresidents. Percentage | Directly from data https://stats.oecd.org/Index.aspx?DataSetCode=GREEN_GROWTH# Trade Imports of goods and services (% of GDP) Transactions in goods and services (sales, barter, and gifts) from residents to nonresidents. Percentage | Directly from data https://stats.oecd.org/Index.aspx?DataSetCode=GREEN_GROWTH# Economic Growth GDP Growth Contribution Variation in total GDP Growth once the policy is implemented, compared to a no-policy scenario Dimensionless | Growth GDP (with policy) / Growth GDP (no-policy) Based on previous indicators and applying effectiveness logic TransformAR Deliverable 3.4 33 www.transformar.eu CO2 Productivity Productionbased CO2 intensity, energy-related CO2 per capita Production-based CO2 intensity is calculated as CO2 emissions per capita (tonnes/person). Included a Tonnes | Directly from data https://stats.oecd.org/Index.aspx?DataSetCode=GREEN_GROWTH# Energy productivit y Renewable energy supply, % total energy supply Renewable energy supply is calculated as a share of renewable sources in TES (expressed as percentage). Percentage | Directly from data https://stats.oecd.org/Index.aspx?DataSetCode=GREEN_GROWTH# Economic Growth Unemployme nt Rate Percentage of the labour force unemployed (working-age residents without work divided by total labour force) % of unemployment | Directly from data Economic Growth Import value index Import value index | Directly from data https://data.worldbank.org/indicator/TM.UVI.MRCH.XD.WD Economic Growth GDP per capita Local currency | Directly from data http://wdi.worldbank.org/table/WV.1 Carbon Footprint Reduced emissions Variation of annual total carbon dioxide equivalent emissions from energy production, transportation and industry. Total annual emissions (%) | Directly from data https://ghgprotocol.org/greenhouse-gas-protocol-accountingreporting-standard-cities TransformAR Deliverable 3.4 34 www.transformar.eu Energy transition Increased integration of RES Variation of the share of capacity from renewable energy sources Total RES capacity (%) | Directly from data Land use Deforestation rate The total forest surface area that is cut down each year Ha/year of forest loss | Directly from data Schokker, J., Kamilaris, A., & Karatsiolis, S. (2021). A Review on Key Performance Indicators for Climate Change. Advances and New Trends in Environmental Informatics: A Bogeyman or Saviour for the UN Sustainability Goals?, 273-292. Climate Hazards Global Climate Risk Index The Global Climate Risk Index shows the level of exposure and vulnerability to extreme weather events Number of deaths – Weight: 1/6, Number of deaths per 100,000 inhabitants – Weight: 1/3, Sum of losses in purchasing power parity (PPP) – Weight: 1/6, Losses per unit of Gross Domestic Product (GDP) – Weight: 1/3 | Directly from data Schokker, J., Kamilaris, A., & Karatsiolis, S. (2021). A Review on Key Performance Indicators for Climate Change. Advances and New Trends in Environmental Informatics: A Bogeyman or Saviour for the UN Sustainability Goals?, 273-292. Climate Hazards Fire Weather Index Assess fire risk based on meteorological conditions Based on 24-hour accumulated precipitation and daily values of air temperature, relative humidity, https://www.eea.europa.eu/ims#c0=10&c12-operator=or&b_start=0 TransformAR Deliverable 3.4 35 www.transformar.eu and wind speed | Directly from data Climate Hazards Monitors trends in average sea surface temperature anomalies T °C | Directly from data https://www.eea.europa.eu/ims#c0=10&c12-operator=or&b_start=0 Resource efficiency (Water) Water stress level The ability to meet a region’s demand for water Low-high ability to meet a region’s demand for water | Directly from data Schokker, J., Kamilaris, A., & Karatsiolis, S. (2021). A Review on Key Performance Indicators for Climate Change. Advances and New Trends in Environmental Informatics: A Bogeyman or Saviour for the UN Sustainability Goals?, 273-292. Pollution Air Quality Index Ranking of cities/countries based on annual average PM2.5 concentration (µg/m³) Annual average of PM2.5 concentration (µg/m³) | Directly from data Schokker, J., Kamilaris, A., & Karatsiolis, S. (2021). A Review on Key Performance Indicators for Climate Change. Advances and New Trends in Environmental Informatics: A Bogeyman or Saviour for the UN Sustainability Goals?, 273-292. Pollution Health impacts of exposure to noise from transport Chronic exposure to environmental noise significantly affects physical and mental health and well-being Range and magnitude of chronic high annoyance and high sleep disturbance due to noise from transport | Directly from data https://www.eea.europa.eu/ims#c0=10&c12-operator=or&b_start=2 TransformAR Deliverable 3.4 36 www.transformar.eu Health & Safety Mortality Rate The mortality rate is calculated by dividing the number of total deaths by the population size for a defined population or geographical area over a specified period. Tot deaths/population | Directly from data Health Life expectancy rates An indicator that can help measure a person’s health in a community Life expectancy rates | Directly from data Zare Mehrjerdi, Y., Alemzadeh, R. & Hajimoradi, A. Dynamic analysis of health-related factors with its impacts on economic growth. SN Appl. Sci. 2, 1440 (2020). https://doi.org/10.1007/s42452-020-03203-1 Health Quality of health services Level of progress in the field of medical equipment and improvement in therapeutic methods Zare Mehrjerdi, Y., Alemzadeh, R. & Hajimoradi, A. Dynamic analysis of health-related factors with its impacts on economic growth. SN Appl. Sci. 2, 1440 (2020). https://doi.org/10.1007/s42452-020-03203-3 Health Death rate It is a measure that affects the population Death rate | Directly from data Zare Mehrjerdi, Y., Alemzadeh, R. & Hajimoradi, A. Dynamic analysis of health-related factors with its impacts on economic growth. SN Appl. Sci. 2, 1440 (2020). https://doi.org/10.1007/s42452-020-03203-4 Health Air pollution Health impacts of air pollution: air pollutants and greenhouse gases Years of life lost or Premature death in [Number] or [rate] | Directly from data Eurostat Human needs satisfaction Safe sanitation access Percentage of population with access to improved sanitation facilities/ People using % of population | Directly from data World Bank, 2020 TransformAR Deliverable 3.4 37 www.transformar.eu safely managed sanitation services Human needs satisfaction Drinking water access People using safely managed drinking water services) (%) % of population | Directly from data World Bank, 2020 Human needs satisfaction Healthy life expectancy The indicator Healthy Life Years (HLY) at birth measures the number of years that a person at birth is still expected to live in a healthy condition. HLY is a health expectancy indicator which combines information on mortality and morbidity. The data required are the agespecific prevalence (proportions) of the population in healthy and unhealthy conditions and agespecific mortality information. A healthy condition is defined by the absence of age-specific prevalence (proportions) of the population in healthy and unhealthy conditions and agespecific mortality information | Directly from data IHME GBD (2019); Eurostat (2020): https://vizhub.healthdata.org/gbdresults/ | https://ec.europa.eu/eurostat/databrowser/view/tps00150/default/ta ble?lang=en TransformAR Deliverable 3.4 38 www.transformar.eu limitations in functioning/disability. Human needs satisfaction Sufficient nourishment Percentage of population meeting dietary energy requirements (%) calculated as reverse of prevalence of undernourishment (rescaled onto scale from 0%-100%) Ratio | Directly from data WB WDI 2020; Eurostat SDG Vulnerabilit y and Resilience Resilience Index Data on safety and risk collected in the World Risk Poll from over 125,000 people in 121 countries. The Resilience Index is an average of 4 domains: Individual, Survey | Directly from data World Risk Poll TransformAR Deliverable 3.4 39 www.transformar.eu Household, Community, Society. Behavioral Change Local risk perception Perception of risk that one's local area will be affected by climate change Survey | Directly from data Behavioral Change Risk exposure A person's actual exposure to environmental hazards, such as noise or pollution. Behavioral Change Risk perception perceptions about threats through climate change and environmental catastrophes and how likely they are or will be prevented Survey | Directly from data European Social Survey 2016; International Social Survey Programme: Environment IV - 2020; Attitudes of Europeans towards Biodiversity. Special Eurobarometer 481, 2018 Vulnerabilit y and Resilience Access to energy Access to electricity, urban Access to electricity, rural % of population | Directly from data https://databank.worldbank.org/source/world-developmentindicators ` Climate change impacts are here and now. The impacts on people, prosperity and planet are already pervasive but unevenly distributed, as stated in the new EU Blueprint strategy (European Commission-EC, 2019). To reduce climate-related risks, the EC and the IPCC agree that transformational adaptation is essential. The TranformAr project aims to develop and demonstrate products and services to launch and accelerate large-scale and disruptive adaptive process for transformational adaptation in vulnerable regions and communities across Europe. The 6 TransformAr lighthouse demonstrators face a common challenge: water-related risks and impacts of climate change. Based on existing successful initiatives, the project will develop, test and demonstrate solutions and pathways, integrated in Innovation Packages, in 6 territories. Transformational pathways, including an integrated risk assessment approach are co-developed by means of 9 Transformational Adaptive Blocks. A set of 22 tested actionable adaptive solutions are tested and demonstrated, ranging from nature-based solutions, innovative technologies, financing, insurance and governance models, awareness and behavioral change solutions. This project has received funding from the European Union’s Horizon H2020 innovation action programme under grant agreement 101036683.