accounting for EUR 16 and EUR 15 billion, respectively. Under the severe RCP8.5 scenario, Poland, France, Germany, and the Czechia would face much higher repair costs, with Poland's reaching EUR 204 billion, France - EUR 131 billion, Germany - EUR 104 billion, and Czechia - EUR 85 billion.

6. The extreme RCP8.5 emission scenario is expected to trigger corrosion process sooner, than the moderate emission scenario RCP4.5. Under the RCP8.5 scenario, carbonation of buildings would be evident in Cyprus and Spain already in 2050; Italy, Greece, Malta and Portugal will follow between 2052 and 2054. In this scenario, countries like Germany, Poland, and Ireland would not experience start of corrosion before 2080. Alternatively, under the RCP4.5 scenario, the corrosion is expected to start in most of the countries after 2100, while in others, like Spain and Cyprus, the onset is expected sooner - in 2062.

7. Welfare loss in this study is calculated as the ratio of the projected annual repair cost to the 2022 GDP. For RCP4.5, countries such as Cyprus, Portugal, and Greece would be subjected to a higher impact of potential annual repair costs on their GDP, with mean values of 0.12%, 0.11%, and 0.8% of their GDP, respectively. Under RCP 8.5, Croatia, Czech Republic and Poland will be exposed to highest impact on the country's GDP, with values reaching 0.87%, 0.46% and 0.42%. It is notable the case of Croatia that exhibit less total repair cost with regard to the other two countries, while the impact on the economy and GDP of the country is significantly higher (0.87% of the country's GDP). These examples are highlighting the varying degrees of economic impact that different emission scenarios could have on EU Member States.

8. The impact on the concrete building stock was performed considering over 30 million buildings in the EU Member States. Under the moderate scenario RCP4.5 more than 4 million buildings (14%) would need repair of the corrosion before 2100, and the countries the most impacted would be Portugal and Italy with more than 1 million buildings needing repair, and Greece with 0.85 million buildings. The extreme scenario RCP8.5 would trigger the need to repair 27 million buildings (90%) across EU before 2100. Under this scenario, repair of corrosion will be needed in all EU Member States, and the most impacted countries would be Poland and Germany with over 4 billion buildings to repair, and Italy with 3.7 billion buildings.

9. PESETA IV study qualified welfare losses for seven climate impact categories: river floods, coastal floods, agriculture, energy supply, droughts, windstorms and human mortality. PESETA IV predicts that a 3°C rise by 2100 may result in yearly losses of more than EUR 175 billion (1.38% GDP) of the EU-27 Member States and UK, with France, Italy, and Spain bearing the brunt of these costs. Yearly losses might be cut to EUR 83 billion (0.65% GDP) if global warming is kept to 2°C, and to EUR 42 billion (0.33% GDP) if it is kept to 1.5°C. Current study qualified the projected annual expenditures to repair the carbonation-triggered corrosion of the EU-27 Member States by the year 2100 as EUR 1.2 billion (0.01% GDP) under the moderate RCP4.5 climate scenario (global warming is kept to 2°C). The projected annual expenditures increase to EUR 14.8 billion (0.09% GDP) under the more extreme scenario RCP8.5 forced by a 3.7°C rise by 2100. This comparison shows that the carbonation-triggered corrosion of the concrete building stock could be a substantial contributor to the yearly welfare losses due to the climate change.

10. The influence of the condition of the built environment on the Member States' economy is profound. The findings of the study necessitate development of guidance and regulations to mitigate the consequences of the climate change induced carbonation, possibly at the same time as other renovation interventions. Adaptation strategies during the service life of existing structures shall encompass both, reparative actions for the damaged reinforced concrete, and protection measures against corrosion after the repair. The on-going renovation of the facades of the buildings to improve their energy efficiency provides a good opportunity to inspect the state of carbonation of the concrete. For the new building stock a resilience-centric framework can be adopted, that involves a dual approach: (i) design-phase adaptation measures aligned with a set confidence level in climate change projections, and (ii) preventive maintenance strategy set at the design stage that will be adjusted with the evolving climate change data throughout the structure's service life.

Finally, it shall be underlined that the study presents a generalised evaluation of the consequences of the climate change-triggered carbonation of the concrete building stock. To perform this analysis, assumptions were introduced regarding the age of the buildings, the durability parameters of the buildings constructed
accounting for EUR 16 and EUR 15 billion, respectively. Under the severe RCP8.5 scenario, Poland, France, Germany, and the Czechia would face much higher repair costs, with Poland's reaching EUR 204 billion, France - EUR 131 billion, Germany - EUR 104 billion, and Czechia - EUR 85 billion.

6. The extreme RCP8.5 emission scenario is expected to trigger corrosion process sooner, than the moderate emission scenario RCP4.5. Under the RCP8.5 scenario, carbonation of buildings would be evident in Cyprus and Spain already in 2050; Italy, Greece, Malta and Portugal will follow between 2052 and 2054. In this scenario, countries like Germany, Poland, and Ireland would not experience start of corrosion before 2080. Alternatively, under the RCP4.5 scenario, the corrosion is expected to start in most of the countries after 2100, while in others, like Spain and Cyprus, the onset is expected sooner - in 2062.

7. Welfare loss in this study is calculated as the ratio of the projected annual repair cost to the 2022 GDP. For RCP4.5, countries such as Cyprus, Portugal, and Greece would be subjected to a higher impact of potential annual repair costs on their GDP, with mean values of 0.12%, 0.11%, and 0.8% of their GDP, respectively. Under RCP 8.5, Croatia, Czech Republic and Poland will be exposed to highest impact on the country's GDP, with values reaching 0.87%, 0.46% and 0.42%. It is notable the case of Croatia that exhibit less total repair cost with regard to the other two countries, while the impact on the economy and GDP of the country is significantly higher (0.87% of the country's GDP). These examples are highlighting the varying degrees of economic impact that different emission scenarios could have on EU Member States.

8. The impact on the concrete building stock was performed considering over 30 million buildings in the EU Member States. Under the moderate scenario RCP4.5 more than 4 million buildings (14%) would need repair of the corrosion before 2100, and the countries the most impacted would be Portugal and Italy with more than 1 million buildings needing repair, and Greece with 0.85 million buildings. The extreme scenario RCP8.5 would trigger the need to repair 27 million buildings (90%) across EU before 2100. Under this scenario, repair of corrosion will be needed in all EU Member States, and the most impacted countries would be Poland and Germany with over 4 billion buildings to repair, and Italy with 3.7 billion buildings.

9. PESETA IV study qualified welfare losses for seven climate impact categories: river floods, coastal floods, agriculture, energy supply, droughts, windstorms and human mortality. PESETA IV predicts that a 3°C rise by 2100 may result in yearly losses of more than EUR 175 billion (1.38% GDP) of the EU-27 Member States and UK, with France, Italy, and Spain bearing the brunt of these costs. Yearly losses might be cut to EUR 83 billion (0.65% GDP) if global warming is kept to 2°C, and to EUR 42 billion (0.33% GDP) if it is kept to 1.5°C. Current study qualified the projected annual expenditures to repair the carbonation-triggered corrosion of the EU-27 Member States by the year 2100 as EUR 1.2 billion (0.01% GDP) under the moderate RCP4.5 climate scenario (global warming is kept to 2°C). The projected annual expenditures increase to EUR 14.8 billion (0.09% GDP) under the more extreme scenario RCP8.5 forced by a 3.7°C rise by 2100. This comparison shows that the carbonation-triggered corrosion of the concrete building stock could be a substantial contributor to the yearly welfare losses due to the climate change.

10. The influence of the condition of the built environment on the Member States' economy is profound. The findings of the study necessitate development of guidance and regulations to mitigate the consequences of the climate change induced carbonation, possibly at the same time as other renovation interventions. Adaptation strategies during the service life of existing structures shall encompass both, reparative actions for the damaged reinforced concrete, and protection measures against corrosion after the repair. The on-going renovation of the facades of the buildings to improve their energy efficiency provides a good opportunity to inspect the state of carbonation of the concrete. For the new building stock a resilience-centric framework can be adopted, that involves a dual approach: (i) design-phase adaptation measures aligned with a set confidence level in climate change projections, and (ii) preventive maintenance strategy set at the design stage that will be adjusted with the evolving climate change data throughout the structure's service life.

Finally, it shall be underlined that the study presents a generalised evaluation of the consequences of the climate change-triggered carbonation of the concrete building stock. To perform this analysis, assumptions were introduced regarding the age of the buildings, the durability parameters of the buildings constructed
before the year 2000, exposed surfaces, uniform repair costs across all countries and an prolonged useful life of buildings. The methodology considered in this study can be applied for refined assessment of the repair cost for distinct categories of buildings or individual buildings, using precise data on their construction period, durability characteristics, type of structure, building dimension and basic elements such as windows, price of repair, and location. The methodology could be also applied to assess the climate change-triggered carbonation of reinforced concrete transport infrastructure.

This study underscores the significant economic and structural health challenges posed by climate change-
induced carbonation and the urgent need for adaptive measures across the EU Member States. On the basis of
the above findings, the following **policy recommendations** can be put forward:

1. Developing and implementing guidance and regulations to mitigate the effects of climate change-induced carbonation, and integrating adaptation strategies into building renovation and maintenance practices. The on-going renovation of the facades of the buildings to improve their energy efficiency provides a good opportunity to inspect the state of carbonation of the concrete and implement adaptive measures, where needed.

2. Encouraging adaptation strategies during the service life of existing buildings that include reparative actions for the damaged reinforced concrete, and protection measures against future corrosion.

3. Promoting the adoption of resilience-centric framework for new buildings, based on a dual approach: (i) design-phase adaptation measures based on the level of confidence we have in climate change predictions, and (ii) preventive maintenance strategy that evolves with climate change data.

4. Supporting refined assessments of repair costs for specific building categories or individual buildings, considering their unique features and local repair prices.

5. Advocating for assessments of climate change impacts on carbonation in reinforced concrete transport infrastructure.
before the year 2000, exposed surfaces, uniform repair costs across all countries and an prolonged useful life
of buildings. The methodology considered in this study can be applied for refined assessment of the
repair cost for distinct categories of buildings or individual buildings, using precise data on their
construction period, durability characteristics, type of structure, building dimension and basic elements such as
windows, price of repair, and location. The methodology could be also applied to assess the climate change-
triggered carbonation of reinforced concrete transport infrastructure.

This study underscores the significant economic and structural health challenges posed by climate change-
induced carbonation and the urgent need for adaptive measures across the EU Member States. On the basis of
the above findings, the following **policy recommendations** can be put forward:

1. Developing and implementing guidance and regulations to mitigate the effects of climate change-induced carbonation, and integrating adaptation strategies into building renovation and maintenance practices. The on-going renovation of the facades of the buildings to improve their energy efficiency provides a good opportunity to inspect the state of carbonation of the concrete and implement adaptive measures, where needed.

2. Encouraging adaptation strategies during the service life of existing buildings that include reparative actions for the damaged reinforced concrete, and protection measures against future corrosion.

3. Promoting the adoption of resilience-centric framework for new buildings, based on a dual approach: (i) design-phase adaptation measures based on the level of confidence we have in climate change predictions, and (ii) preventive maintenance strategy that evolves with climate change data.

4. Supporting refined assessments of repair costs for specific building categories or individual buildings, considering their unique features and local repair prices.

5. Advocating for assessments of climate change impacts on carbonation in reinforced concrete transport infrastructure.
Declaration of AI assisted technologies in the writing process:

During the preparation of this work the author(s) used, OpenAI's GPT-35-turbo version, November 2023 (Model code: gpt-35-turbo-1106 / Service: GPT@JRC) to proofread and enhance the text in various sections of the document. After using this tool, the author(s) thoroughly reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
Declaration of AI assisted technologies in the writing process:

During the preparation of this work the author(s) used, OpenAI's GPT-35-turbo version, November 2023 (Model code: gpt-35-turbo-1106 / Service: GPT@JRC) to proofread and enhance the text in various sections of the document. After using this tool, the author(s) thoroughly reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
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Croce, P., Formichi, P., Landi, F., Mercogliano, P., Bucchignani, E., Dosio, A., Dimova, S., 'The snow load in Europe and the climate change', *Climate Risk Management*, Volume 20, 2018, pp. 138-154, ISSN 2212-0963, https://doi.org/10.1016/j.crm.2018.03.001.

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Al-Khaiat, H. and Fattuhi, N., 'Carbonation of concrete exposed to hot and arid climate', *Journal of materials in civil engineering*, 2002, 4(2), pp. 97-107, doi:10.1061/(ASCE)0899-1561(2002)14:2(97)-107.

Athanasopoulou, A., Sousa, M.L., Dimova, S., Guido, R., Mercogliano, P., Villani, V., Croce, P., Landi, F., Formichi, P. and Markova, J., *Thermal design of structures and the changing climate*, Athanasopoulou, A., Sousa, M.L, Dimova, S., Dyngeland, T. and Pinto, A. editor(s), EUR 30302 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-20777-4, doi:10.2760/128894, JRC121351.

Ban, N., et al., 'The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation', *Climate Dynamics*. 57(1), 2021, pp. 275-302, https://doi.org/10.1007/s00382-021-05708-w.

Bandhauer, M., Isotta, F., Lakatos, M., Lussana, C., Baserud, L., Izsak, B., Szentes, O., Tveito, O.E., Frei, C., 'Evaluation of daily precipitation analyses in E-OBS (v19.0e) and ERAS by comparison to regional high-resolution datasets in European regions', *International Journal of Climatology*, 2021, pp. 1-21, doi: 10.1002/joc.7269.

Bastidas-Arteaga, E., Rianna, G., Gervasio, H., & Nogal, M., 'Multi-region lifetime assessment of reinforced concrete structures subjected to carbonation and climate change', *Structures*, Vol. 45, Elsevier, 2022, pp. 886-899, https://doi.org/10.1016/j.istruc.2022.09.061.

Bastidas-Arteaga, E. and Stewart, M.G., 'Damage risks and economic assessment of climate adaptation strategies for design of new concrete structures subject to chloride-induced corrosion', *Structural Safety*, 52, 2015, pp.40-53, doi:10.1016/j.strusafe.2014.10.005.

Bastidas-Arteaga, E. and Stewart, M., 'Economic assessment of climate adaptation strategies for existing reinforced concrete structures subjected to chloride-induced corrosion', *Structure and Infrastructure Engineering* 12 (4), 2016, pp. 432-449, doi:10.1080/15732479.2015.1020499.

Brzev, S., Scawthorn, C., Charleson, et al., GEM building taxonomy version 2.0, Report 2013-02 v1.0.0., GEM Foundation, Pavia, 2013, doi:10.13117/GEM.EXP-MOD.TR2013.02.

Cannon, A.J., Sobie, S.R., Murdock, T.Q., 'Bias correction of GCM precipitation by Quantile mapping: how well do methods preserve changes in quantiles and extremes?', *J. Climate*, 28, 2015, pp. 6938-6959, doi:10.1175/JCLI-D-14-00754.1.

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Dosio, A., 'Projections of climate change indices of temperature and precipitation from an ensemble of bias-adjusted high-resolution EURO-CORDEX regional climate models', *Journal of Geophysical Research: Atmospheres*, 121(10), 2016, pp. 5488-5511, doi:10.1002/2015JD024411.

Dosio, A., *Mean and extreme climate in Europe under 1.5, 2, and 3°C global warming*, EUR 30194 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN: 978-92-76-18430-0, doi:10.2760/826427, JRC120574.

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Stefanoni, M., Angst, U., Elsener, B., 'Corrosion Rate of Carbon Steel in Carbonated Concrete—A Critical Review', *Cem. Concr. Res.* 103, 2018, pp. 35-48.

Stewart, M. and Bastidas-Arteaga, E., 'Corrosion of concrete and steel structures in a changing climate', in: *Climate Adaptation Engineering*, Elsevier, 2019, pp. 99-125.

Stewart, M.G., Teply, B. and Kralova, H., 'The Effect of Temporal and Spatial Variability of Ambient Carbon Dioxide Concentrations on Carbonation of RC Structures', in *Proceedings of the 9th International Conference on Durability of Building Materials and Components, CSIRO*, 2002, Paper 246 (CD-ROM).
Stewart, M.G., Wang, X., Nguyen, M.N., 'Climate change impact and risks of concrete infrastructure deterioration', *Eng. Struct.*, 33, 2011, pp. 1326-1337. https://doi.org/10.1016/j.engstruct.2011.01.010.

Stewart, M., Wang, X., Nguyen, M. 'Climate change adaptation for corrosion control of concrete infrastructure', *Structural Safety*, 35, 2012, pp. 29-39.

Switanek, M.B., Troch, P.A., Castro, C.L., Leuprecht, A., Chang, H.-I., Mukherjee, R., Demaria, E.M.C., 'Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes', *Hydrol. Earth Syst. Sci.*, 21, 2017, pp. 2649-2666, doi:10.5194/hess-21-2649-2017.

Talukdar, S., Banthia, N., Grace, J. and Cohen, S., 'Carbonation in concrete infrastructure in the context of global climate change: Part 2– Canadian urban simulations', *Cement and Concrete Composites*, 34(8), 2012, pp. 931-935

Talukdar, S. and Banthia, N., 'Carbonation in concrete infrastructure in the context of global climate change: development of a service lifespan model', *Construction and Building Materials*, 40, 2013, pp. 775-782.

Taylor, K.E., Stouffer, R.J., Meehl, G.A., 'An Overview of CMIP5 and the Experiment Design', *Bulletin of the American Meteorological Society*, 93(4), 2012, pp. 485-498, doi:10.1175/BAMS-D-11-00094.1.

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Vacareanu, R., Radoi, R., Negulescu, C., Aldea, A., 'Seismic vulnerability of RC Buildings in Bucharest, Romania', In Proceedings of the 13th World Conference on Earthquake Engineering, Vancouver, B.C., Canada, 2004, Paper 1796.

Val, D. V., Yurchenko, D., Nogal, M., & O'Connor, A., 'Climate change-related risks and adaptation of interdependent infrastructure systems', *Climate adaptation engineering*, 2019, pp. 207-242.

Van der Schrier, G., Barichivich, J., Briffa, K.R., Jones, P.D., 'A scPDSI-based global data set of dry and wet spells for 1901-2009', *J. Geophys. Res. Atmos.*, 118, 2013, pp. 4025-4048, doi:10.1002/jgrd.50355.

Wang, Q., Wei, J., Dong, R., and Xu G., 'Numerical analysis of carbonation process for concrete structures', *Journal of Wuhan University of Technology*, vol. 36, no. 5, 2014, pp. 91-96, doi:10.3963/j.issn.1671-4431.2014.05.017.

Wilby, R. (2017). Climate Change in Practice: Topics for Discussion with Group Exercises. Cambridge: Cambridge University Press, doi:10.1017/9781316534588.

Xie, H., Wang, Y., Gong, J., Liu, M. and Yang, X., 'Effect of global warming on chloride ion erosion risks for offshore RC bridges in China'. *KSCE Journal of Civil Engineering*, 2018, pp. 1-7.

Yoon, I.-S., Çopuroğlu, O., Park, K.-B., 'Effect of global climatic change on carbonation progress of concrete', *Atmos. Environ.*, 41 (34), 2007, pp. 7274-7285.

Yoon, I.-S., Chang, C.-H., 'Time Evolution of CO2 Diffusivity of Carbonated Concrete'. *Appl. Sci.* 2020, *10*, 8910. https://doi.org/10.3390/app10248910
Stewart, M.G., Wang, X., Nguyen, M.N., 'Climate change impact and risks of concrete infrastructure deterioration', *Eng. Struct.*, 33, 2011, pp. 1326-1337. https://doi.org/10.1016/j.engstruct.2011.01.010.

Stewart, M., Wang, X., Nguyen, M. 'Climate change adaptation for corrosion control of concrete infrastructure', *Structural Safety*, 35, 2012, pp. 29-39.

Switanek, M.B., Troch, P.A., Castro, C.L., Leuprecht, A., Chang, H.-I., Mukherjee, R., Demaria, E.M.C., 'Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes', *Hydrol. Earth Syst. Sci.*, 21, 2017, pp. 2649-2666, doi:10.5194/hess-21-2649-2017.

Talukdar, S., Banthia, N., Grace, J. and Cohen, S., 'Carbonation in concrete infrastructure in the context of global climate change: Part 2– Canadian urban simulations', *Cement and Concrete Composites*, 34(8), 2012, pp. 931-935

Talukdar, S. and Banthia, N., 'Carbonation in concrete infrastructure in the context of global climate change: development of a service lifespan model', *Construction and Building Materials*, 40, 2013, pp. 775-782.

Taylor, K.E., Stouffer, R.J., Meehl, G.A., 'An Overview of CMIP5 and the Experiment Design', *Bulletin of the American Meteorological Society*, 93(4), 2012, pp. 485-498, doi:10.1175/BAMS-D-11-00094.1.

Teutschbein, C. and Seibert, J., 'Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods', *Journal of Hydrology*, 2012, pp. 456-457, 12-29, doi: 10.1016/j.jhydrol.2012.05.052.

Vacareanu, R., Radoi, R., Negulescu, C., Aldea, A., 'Seismic vulnerability of RC Buildings in Bucharest, Romania', In Proceedings of the 13th World Conference on Earthquake Engineering, Vancouver, B.C., Canada, 2004, Paper 1796.

Val, D. V., Yurchenko, D., Nogal, M., & O'Connor, A., 'Climate change-related risks and adaptation of interdependent infrastructure systems', *Climate adaptation engineering*, 2019, pp. 207-242.

Van der Schrier, G., Barichivich, J., Briffa, K.R., Jones, P.D., 'A scPDSI-based global data set of dry and wet spells for 1901-2009', *J. Geophys. Res. Atmos.*, 118, 2013, pp. 4025-4048, doi:10.1002/jgrd.50355.

Wang, Q., Wei, J., Dong, R., and Xu G., 'Numerical analysis of carbonation process for concrete structures', *Journal of Wuhan University of Technology*, vol. 36, no. 5, 2014, pp. 91-96, doi:10.3963/j.issn.1671-4431.2014.05.017.

Wilby, R. (2017). Climate Change in Practice: Topics for Discussion with Group Exercises. Cambridge: Cambridge University Press, doi:10.1017/9781316534588.

Xie, H., Wang, Y., Gong, J., Liu, M. and Yang, X., 'Effect of global warming on chloride ion erosion risks for offshore RC bridges in China'. *KSCE Journal of Civil Engineering*, 2018, pp. 1-7.

Yoon, I.-S., Çopuroğlu, O., Park, K.-B., 'Effect of global climatic change on carbonation progress of concrete', *Atmos. Environ.*, 41 (34), 2007, pp. 7274-7285.

Yoon, I.-S., Chang, C.-H., 'Time Evolution of CO2 Diffusivity of Carbonated Concrete'. *Appl. Sci.* 2020, *10*, 8910. https://doi.org/10.3390/app10248910
List of abbreviations and definitions

<table><tr><td>AA</td><td>Alkali-activated cements</td></tr><tr><td>CCMC</td><td>Euro-Mediterranean Centre on Climate Change</td></tr><tr><td>CDF</td><td>Cumulative distribution function</td></tr><tr><td>CDS</td><td>Copernicus Climate Datastore</td></tr><tr><td>CEB</td><td>Euro-International Committee for Concrete</td></tr><tr><td>CEN</td><td>European Committee for Standardization</td></tr><tr><td>CENELEC</td><td>European Committee for Electrotechnical Standardization</td></tr><tr><td>CMIP5</td><td>Coupled Model Intercomparison 5</td></tr><tr><td>CO2</td><td>Carbon dioxide</td></tr><tr><td>CORDEX</td><td>Coordinated Downscaling Experiment</td></tr><tr><td>CPR</td><td>Construction Products Regulation</td></tr><tr><td>DG CLIMA</td><td>European Commission's Directorate-General for Climate Action</td></tr><tr><td>DG GROW</td><td>European Commission's Directorate-General for Internal Market, Industry, Entrepreneurship & SMEs</td></tr><tr><td>DM</td><td>Decreto del Ministero delle infrastrutture (Italian Code)</td></tr><tr><td>ECA&amp;D</td><td>European Climate Assessment & Dataset</td></tr><tr><td>EED</td><td>Energy Efficiency Directive</td></tr><tr><td>EFEHR</td><td>European Facilities for Earthquake Hazard and Risk</td></tr><tr><td>EN</td><td>from German name Europäische Norm ('European Norm')</td></tr><tr><td>E-OBS</td><td>Daily gridded land-only observational dataset over Europe</td></tr><tr><td>ESS</td><td>European Statistical System</td></tr><tr><td>EU</td><td>European Union</td></tr><tr><td>EU-27</td><td>European countries: From 1 February 2020, the 27 European Union countries after the UK left the EU</td></tr><tr><td>EUCRA</td><td>European Climate Risk Assessment</td></tr><tr><td>EUR</td><td>Euro</td></tr><tr><td>fib</td><td>International Federation for Structural Concrete</td></tr><tr><td>GCMs</td><td>Global Climate Models</td></tr><tr><td>GDP</td><td>Gross domestic product</td></tr><tr><td>GEM</td><td>Global earthquake Model</td></tr><tr><td>GHG</td><td>Global greenhouse gas emissions</td></tr><tr><td>GWL</td><td>Global warming level</td></tr><tr><td>IPPC</td><td>Intergovernmental Panel on Climate Change</td></tr><tr><td>JCSS</td><td>Joint Committee on Structural Safety</td></tr><tr><td>JRC</td><td>Join Research Centre</td></tr><tr><td>LTRS</td><td>Long-term building renovation strategies</td></tr><tr><td>MFHs</td><td>Multi-family homes</td></tr><tr><td>MOS</td><td>Model Output Statistics</td></tr><tr><td>NDCs</td><td>Nationally Determined Contributions</td></tr><tr><td>NECPs</td><td>Integrated national energy and climate plans</td></tr></table>
List of abbreviations and definitions

<table><tr><td>AA</td><td>Alkali-activated cements</td></tr><tr><td>CCMC</td><td>Euro-Mediterranean Centre on Climate Change</td></tr><tr><td>CDF</td><td>Cumulative distribution function</td></tr><tr><td>CDS</td><td>Copernicus Climate Datastore</td></tr><tr><td>CEB</td><td>Euro-International Committee for Concrete</td></tr><tr><td>CEN</td><td>European Committee for Standardization</td></tr><tr><td>CENELEC</td><td>European Committee for Electrotechnical Standardization</td></tr><tr><td>CMIP5</td><td>Coupled Model Intercomparison 5</td></tr><tr><td>CO2</td><td>Carbon dioxide</td></tr><tr><td>CORDEX</td><td>Coordinated Downscaling Experiment</td></tr><tr><td>CPR</td><td>Construction Products Regulation</td></tr><tr><td>DG CLIMA</td><td>European Commission's Directorate-General for Climate Action</td></tr><tr><td>DG GROW</td><td>European Commission's Directorate-General for Internal Market, Industry, Entrepreneurship & SMEs</td></tr><tr><td>DM</td><td>Decreto del Ministero delle infrastrutture (Italian Code)</td></tr><tr><td>ECA&amp;D</td><td>European Climate Assessment & Dataset</td></tr><tr><td>EED</td><td>Energy Efficiency Directive</td></tr><tr><td>EFEHR</td><td>European Facilities for Earthquake Hazard and Risk</td></tr><tr><td>EN</td><td>from German name Europäische Norm ('European Norm')</td></tr><tr><td>E-OBS</td><td>Daily gridded land-only observational dataset over Europe</td></tr><tr><td>ESS</td><td>European Statistical System</td></tr><tr><td>EU</td><td>European Union</td></tr><tr><td>EU-27</td><td>European countries: From 1 February 2020, the 27 European Union countries after the UK left the EU</td></tr><tr><td>EUCRA</td><td>European Climate Risk Assessment</td></tr><tr><td>EUR</td><td>Euro</td></tr><tr><td>fib</td><td>International Federation for Structural Concrete</td></tr><tr><td>GCMs</td><td>Global Climate Models</td></tr><tr><td>GDP</td><td>Gross domestic product</td></tr><tr><td>GEM</td><td>Global earthquake Model</td></tr><tr><td>GHG</td><td>Global greenhouse gas emissions</td></tr><tr><td>GWL</td><td>Global warming level</td></tr><tr><td>IPPC</td><td>Intergovernmental Panel on Climate Change</td></tr><tr><td>JCSS</td><td>Joint Committee on Structural Safety</td></tr><tr><td>JRC</td><td>Join Research Centre</td></tr><tr><td>LTRS</td><td>Long-term building renovation strategies</td></tr><tr><td>MFHs</td><td>Multi-family homes</td></tr><tr><td>MOS</td><td>Model Output Statistics</td></tr><tr><td>NDCs</td><td>Nationally Determined Contributions</td></tr><tr><td>NECPs</td><td>Integrated national energy and climate plans</td></tr></table>
NUTS Nomenclature of Territorial Units for Statistics

PC Portland cement

RC Reinforced concrete

RCMs Regional Climate Models

RCP Representative Concentration Pathway

RH Relative Humidity

SFHs Single-family homes

TC250 Technical Committee 250 CEN (CEN/TC250) 'Structural Eurocodes'

UK United Kingdom

USA United States of America

WCRP World Climate Research Programme

WMO World Meteorological Organization
NUTS Nomenclature of Territorial Units for Statistics

PC Portland cement

RC Reinforced concrete

RCMs Regional Climate Models

RCP Representative Concentration Pathway

RH Relative Humidity

SFHs Single-family homes

TC250 Technical Committee 250 CEN (CEN/TC250) 'Structural Eurocodes'

UK United Kingdom

USA United States of America

WCRP World Climate Research Programme

WMO World Meteorological Organization
List of figures

<table><tr><td>Figure 1. Influence of RH in the carbonation depth (Elsalamawy et al., 2019)</td><td>19</td></tr><tr><td>Figure 2. Flowchart to assess the total normalized repair costs per square meter</td><td>23</td></tr><tr><td>Figure 3. Example of carbonation depths</td><td>24</td></tr><tr><td>Figure 4. Probability for corrosion initiation in function of the estimated carbonation depth</td><td>28</td></tr><tr><td>Figure 5. Probability of corrosion initiation over the time for two scenarios: with and without climate change</td><td>28</td></tr><tr><td>Figure 6. Illustration of assessment of times to repair</td><td>29</td></tr><tr><td>Figure 7. Flowchart to assess the total normalized repair costs per category</td><td>30</td></tr><tr><td>Figure 8. Idealized reinforced concrete building for the estimation of the exposed building surface façades</td><td>31</td></tr><tr><td>Figure 9. Global values of CO₂ concentrations for historic periods (1765-2005) and in scenario mode (2006-2100) under RCP4.5 and RCP8.5 scenarios; Source: elaboration by authors using data provided by https://tntcat.iiasa.ac.at/RcpDb/dsd?Action=htmlpage&page=about#intro</td><td>35</td></tr><tr><td>Figure 10. Map of annual temperature provided by E-OBSv10.0 over 1981-2010 (a); bias of annual temperature in-between E-OBS v10.0 and E-OBS v23.1 over the same period (b). Source: Developed by authors</td><td>38</td></tr><tr><td>Figure 11. Empirical Cumulative Distribution Function of annual temperature bias</td><td>39</td></tr><tr><td>Figure 12. Evolution of annual mean temperature derived from E-OBSv10.0 and E-OBSv23.1 over 1981-2010</td><td>39</td></tr><tr><td>Figure 13. Delimitation of NUTSO Country (blue line). This area identifies in this work the European domain. Source: Developed by authors</td><td>40</td></tr><tr><td>Figure 14. Map of variation of annual temperature given by E-OBS v10.0 over 1981-2010 against 1951-1980. Source: Developed by authors</td><td>40</td></tr><tr><td>Figure 15. Two sample Kolmogorov Smirnov test over Europe comparing yearly temperature values from E-OBSv10 for 1951-1980 and 1981-2010. Green areas reject the null hypothesis while red areas do not. Source: Developed by authors</td><td>41</td></tr><tr><td>Figure 16. Map of annual temperature anomaly 2071-2100 vs 1981-2010 as derived from the Ensemble Mean of 11 Bias-Adjusted RCMs for RCP4.5 scenario. Source: Developed by authors</td><td>42</td></tr><tr><td>Figure 17. Map of annual temperature anomaly 2071-2100 vs 1981-2010 as derived from the Ensemble Mean of 11 bias-adjusted RCMs for RCP8.5 scenario. Source: Developed by authors</td><td>42</td></tr><tr><td>Figure 18. Trend of annual temperature over Europe. Shaded areas represent the inter-model variability assessed as ±σ</td><td>42</td></tr><tr><td>Figure 19. Trend of annual temperature at country level (part 1). Shaded areas represent the inter-model variability assessed as ±σ</td><td>44</td></tr><tr><td>Figure 20. Trend of annual temperature at country level (part 2). Shaded areas represent the inter-model variability assessed as ±σ</td><td>45</td></tr><tr><td>Figure 21. Trend of annual temperature in Helsinki (top figure) and Nicosia (bottom figure), observations, historical and projections scenarios</td><td>46</td></tr><tr><td>Figure 22. Density of RC buildings in the 27 Member States; pie graphs showing the distribution of buildings occupancy type (residential or commercial buildings) crosswise with age group (old or recent) in each Member State</td><td>52</td></tr><tr><td>Figure 23. Concrete cover, c<sub>t</sub> (mm), adopted for the 27 Member States; left: old buildings, right: recent buildings (Dimova et al. 2023)</td><td>54</td></tr><tr><td>Figure 24. Water-to-cement (w/c) ratio, adopted for the 27 Member States; left: old buildings, right: recent buildings</td><td>54</td></tr></table>
List of figures

<table><tr><td>Figure 1. Influence of RH in the carbonation depth (Elsalamawy et al., 2019)</td><td>19</td></tr><tr><td>Figure 2. Flowchart to assess the total normalized repair costs per square meter</td><td>23</td></tr><tr><td>Figure 3. Example of carbonation depths</td><td>24</td></tr><tr><td>Figure 4. Probability for corrosion initiation in function of the estimated carbonation depth</td><td>28</td></tr><tr><td>Figure 5. Probability of corrosion initiation over the time for two scenarios: with and without climate change</td><td>28</td></tr><tr><td>Figure 6. Illustration of assessment of times to repair</td><td>29</td></tr><tr><td>Figure 7. Flowchart to assess the total normalized repair costs per category</td><td>30</td></tr><tr><td>Figure 8. Idealized reinforced concrete building for the estimation of the exposed building surface façades</td><td>31</td></tr><tr><td>Figure 9. Global values of CO₂ concentrations for historic periods (1765-2005) and in scenario mode (2006-2100) under RCP4.5 and RCP8.5 scenarios; Source: elaboration by authors using data provided by https://tntcat.iiasa.ac.at/RcpDb/dsd?Action=htmlpage&page=about#intro</td><td>35</td></tr><tr><td>Figure 10. Map of annual temperature provided by E-OBSv10.0 over 1981-2010 (a); bias of annual temperature in-between E-OBS v10.0 and E-OBS v23.1 over the same period (b). Source: Developed by authors</td><td>38</td></tr><tr><td>Figure 11. Empirical Cumulative Distribution Function of annual temperature bias</td><td>39</td></tr><tr><td>Figure 12. Evolution of annual mean temperature derived from E-OBSv10.0 and E-OBSv23.1 over 1981-2010</td><td>39</td></tr><tr><td>Figure 13. Delimitation of NUTSO Country (blue line). This area identifies in this work the European domain. Source: Developed by authors</td><td>40</td></tr><tr><td>Figure 14. Map of variation of annual temperature given by E-OBS v10.0 over 1981-2010 against 1951-1980. Source: Developed by authors</td><td>40</td></tr><tr><td>Figure 15. Two sample Kolmogorov Smirnov test over Europe comparing yearly temperature values from E-OBSv10 for 1951-1980 and 1981-2010. Green areas reject the null hypothesis while red areas do not. Source: Developed by authors</td><td>41</td></tr><tr><td>Figure 16. Map of annual temperature anomaly 2071-2100 vs 1981-2010 as derived from the Ensemble Mean of 11 Bias-Adjusted RCMs for RCP4.5 scenario. Source: Developed by authors</td><td>42</td></tr><tr><td>Figure 17. Map of annual temperature anomaly 2071-2100 vs 1981-2010 as derived from the Ensemble Mean of 11 bias-adjusted RCMs for RCP8.5 scenario. Source: Developed by authors</td><td>42</td></tr><tr><td>Figure 18. Trend of annual temperature over Europe. Shaded areas represent the inter-model variability assessed as ±σ</td><td>42</td></tr><tr><td>Figure 19. Trend of annual temperature at country level (part 1). Shaded areas represent the inter-model variability assessed as ±σ</td><td>44</td></tr><tr><td>Figure 20. Trend of annual temperature at country level (part 2). Shaded areas represent the inter-model variability assessed as ±σ</td><td>45</td></tr><tr><td>Figure 21. Trend of annual temperature in Helsinki (top figure) and Nicosia (bottom figure), observations, historical and projections scenarios</td><td>46</td></tr><tr><td>Figure 22. Density of RC buildings in the 27 Member States; pie graphs showing the distribution of buildings occupancy type (residential or commercial buildings) crosswise with age group (old or recent) in each Member State</td><td>52</td></tr><tr><td>Figure 23. Concrete cover, c<sub>t</sub> (mm), adopted for the 27 Member States; left: old buildings, right: recent buildings (Dimova et al. 2023)</td><td>54</td></tr><tr><td>Figure 24. Water-to-cement (w/c) ratio, adopted for the 27 Member States; left: old buildings, right: recent buildings</td><td>54</td></tr></table>
<table><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>Figure 25. Cement content, C<sub>e</sub> (kg/m<sup>3</sup>), adopted for the 27 Member States; left: old buildings, right: recent buildings</td><td>55</td></tr><tr><td>Figure 26. Carbonation depth in Helsinki (top figure) and Nicosia (bottom figure)</td><td>57</td></tr><tr><td>Figure 27. Percentage of increase of carbonation depth in EU-27 capital cities. To note the varying scale for each scenario while maintaining the same range of colours in the maps for consistency</td><td>59</td></tr><tr><td>Figure 28. Percentage of increase of carbonation depth in EU-27 capital cities for old buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>61</td></tr><tr><td>Figure 29. Percentage of increase of carbonation depth in EU-27 capital cities for recent buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>62</td></tr><tr><td>Figure 30. Absolute increase of carbonation depth in EU-27 capital cities for old buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>64</td></tr><tr><td>Figure 31. Absolute increase of carbonation depth in EU-27 capital cities for recent buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>65</td></tr><tr><td>Figure 32. Percentage of increase of carbonation depth in EU-27 Member States for the RC building stock for the years 2050 (top) and 2085 (bottom) due to two climate change scenarios with respect to two control scenarios; left: RCP4.5 scenario, right RCP8.5 scenario</td><td>67</td></tr><tr><td>Figure 33. Probability of corrosion initiation in Helsinki (top figure) and Nicosia (bottom figure) for two climate change scenarios, RCP4.5 and RCP8.5 initiated in 2011, and two classes of buildings, old and recent buildings; Shaded areas are derived from the temperature inter-model variability and assessed between ±2σ</td><td>68</td></tr><tr><td>Figure 34. Distribution of the repair time relative intervals relative to 2020 since 2100 in the EU-27 Member States, considering the percentage of buildings starting corrosion before 2100. On the right, the RCP4.5 scenario; on the left, the RCP8.5 scenario</td><td>70</td></tr><tr><td>Figure 35. Total normalized repair costs per square meter and year (€/(year m<sup>2</sup>) for old RC buildings in the EU-27 Member States</td><td>73</td></tr><tr><td>Figure 36. Annual normalized repair costs (10<sup>6</sup> € / year) for old RC buildings in the EU-27 Member States</td><td>74</td></tr><tr><td>Figure 37. Total repair costs (10<sup>9</sup> €) due to climate change induced carbonation for the RC building stock (old buildings) of the EU-27 Member States by the year 2100</td><td>75</td></tr><tr><td>Figure 38. Total repair costs by year (billion euro, B€) and percentage impact on GDP by country, analysed in relation to RCP4.5 and RCP8.5 scenarios</td><td>82</td></tr></tbody></table>
<table><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>Figure 25. Cement content, C<sub>e</sub> (kg/m<sup>3</sup>), adopted for the 27 Member States; left: old buildings, right: recent buildings</td><td>55</td></tr><tr><td>Figure 26. Carbonation depth in Helsinki (top figure) and Nicosia (bottom figure)</td><td>57</td></tr><tr><td>Figure 27. Percentage of increase of carbonation depth in EU-27 capital cities. To note the varying scale for each scenario while maintaining the same range of colours in the maps for consistency</td><td>59</td></tr><tr><td>Figure 28. Percentage of increase of carbonation depth in EU-27 capital cities for old buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>61</td></tr><tr><td>Figure 29. Percentage of increase of carbonation depth in EU-27 capital cities for recent buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>62</td></tr><tr><td>Figure 30. Absolute increase of carbonation depth in EU-27 capital cities for old buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>64</td></tr><tr><td>Figure 31. Absolute increase of carbonation depth in EU-27 capital cities for recent buildings, absolute temperature for a given year and temperature variation relative to the reference scenario</td><td>65</td></tr><tr><td>Figure 32. Percentage of increase of carbonation depth in EU-27 Member States for the RC building stock for the years 2050 (top) and 2085 (bottom) due to two climate change scenarios with respect to two control scenarios; left: RCP4.5 scenario, right RCP8.5 scenario</td><td>67</td></tr><tr><td>Figure 33. Probability of corrosion initiation in Helsinki (top figure) and Nicosia (bottom figure) for two climate change scenarios, RCP4.5 and RCP8.5 initiated in 2011, and two classes of buildings, old and recent buildings; Shaded areas are derived from the temperature inter-model variability and assessed between ±2σ</td><td>68</td></tr><tr><td>Figure 34. Distribution of the repair time relative intervals relative to 2020 since 2100 in the EU-27 Member States, considering the percentage of buildings starting corrosion before 2100. On the right, the RCP4.5 scenario; on the left, the RCP8.5 scenario</td><td>70</td></tr><tr><td>Figure 35. Total normalized repair costs per square meter and year (€/(year m<sup>2</sup>) for old RC buildings in the EU-27 Member States</td><td>73</td></tr><tr><td>Figure 36. Annual normalized repair costs (10<sup>6</sup> € / year) for old RC buildings in the EU-27 Member States</td><td>74</td></tr><tr><td>Figure 37. Total repair costs (10<sup>9</sup> €) due to climate change induced carbonation for the RC building stock (old buildings) of the EU-27 Member States by the year 2100</td><td>75</td></tr><tr><td>Figure 38. Total repair costs by year (billion euro, B€) and percentage impact on GDP by country, analysed in relation to RCP4.5 and RCP8.5 scenarios</td><td>82</td></tr></tbody></table>
List of tables

**Table 1.** Summary of standard recommendations concerning durability of RC structures in France.................. 25

**Table 2.** Design cover for existing structures subjected to carbonation-induced corrosion in France.................. 26

**Table 3.** Direct repair costs estimated based on the repair of the Agri-foodstuffs terminal of the Nantes Saint-Nazaire Port (Srifi 2012; Bastidas-Arteaga and Stewart 2016)................................................................................... 26

**Table 4.** Adopted concrete cover values for existing buildings in France.................................................................................. 28

**Table 5.** Categories for building height.................................................................................................................................................. 31

**Table 6.** Reduction factor fw according to buildings lateral load resisting system and height.................................................. 32

**Table 7.** List of climate model chains used in Dosio (2016).................................................................................................................. 36

**Table 8.** Statistics about bias of annual temperature (1981-2010 vs 1951-1980) over Europe as provided by E-OBSv10.0.................................................................................................................................................................................. 41

**Table 9.** 30-year annual temperature anomalies at country level; the blue-red palette compares the country anomalies with those assessed over Europe; blue (red) values mean areas colder (hotter) than the European average value.................................................................................................................................................................................. 43

**Table 10.** Temperature disparities between the reference baseline temperature for old (constructed 1965) and recent buildings (constructed 2000) and the years 2050 and 2085 in European capital cities analysed under RCP4.5 and RCP8.5 scenarios.................................................................................................................................................. 48

**Table 11.** Attributes in the exposure model (Crowley et al, 2021, Gkatzogias et al., 2022).................................................. 50

**Table 12.** Default durability parameters.................................................................................................................................................. 53

**Table 13.** Repair year, time to repair and uncertainties due to climate change prediction for old buildings in capital cities.................................................................................................................................................................................................................. 69

**Table 14.** Distribution of median time to repair relative to the year 2020, and the percentage of the buildings to repair in time intervals, in the EU Member States; right RCP4.5 scenario (green colour); left RCP8.5 scenario (blue colour).................................................................................................................................................. 71

**Table 15.** Increase in total repair cost by 2100 due to climate change induced carbonation in European countries in billions of Euros, (B€, 10⁹ €).................................................................................................................................................. 76

**Table 16.** Total repair cost per year (annual repair cost) due to climate change induced carbonation in European countries in billions of euro (B€, 10⁹ €)................................................................................................................................................... 77

**Table 17.** Annual repair cost, by year 2100, due to climate change-induced carbonation in EU-27 countries, expressed as a percentage of the respective country's GDP (latest value 2022) and number of buildings with corrosion starting before and after 2100.................................................................................................................................................. 78

**Table 18.** Summary of the considered durability parameters for exposure class XC4 and for an intended working life of at least 50 years, used in the calculations. The choice is explained in Chapter 5, section 5.2 and values of the durability parameters are depicted in Figure 23, Figure 24, and Figure 25 of the report.................. 130

**Table 19.** Percentage of increase of carbonation depth in 27-EU capital cities.................................................................................. 131
List of tables

**Table 1.** Summary of standard recommendations concerning durability of RC structures in France. 25

**Table 2.** Design cover for existing structures subjected to carbonation-induced corrosion in France. 26

**Table 3.** Direct repair costs estimated based on the repair of the Agri-foodstuffs terminal of the Nantes Saint-Nazaire Port (Srifi 2012; Bastidas-Arteaga and Stewart 2016). 26

**Table 4.** Adopted concrete cover values for existing buildings in France. 28

**Table 5.** Categories for building height. 31

**Table 6.** Reduction factor fw according to buildings lateral load resisting system and height. 32

**Table 7.** List of climate model chains used in Dosio (2016). 36

**Table 8.** Statistics about bias of annual temperature (1981-2010 vs 1951-1980) over Europe as provided by E-OBSv10.0. 41

**Table 9.** 30-year annual temperature anomalies at country level; the blue-red palette compares the country anomalies with those assessed over Europe; blue (red) values mean areas colder (hotter) than the European average value. 43

**Table 10.** Temperature disparities between the reference baseline temperature for old (constructed 1965) and recent buildings (constructed 2000) and the years 2050 and 2085 in European capital cities analysed under RCP4.5 and RCP8.5 scenarios. 48

**Table 11.** Attributes in the exposure model (Crowley et al, 2021, Gkatzogias et al., 2022). 50

**Table 12.** Default durability parameters. 53

**Table 13.** Repair year, time to repair and uncertainties due to climate change prediction for old buildings in capital cities. 69

**Table 14.** Distribution of median time to repair relative to the year 2020, and the percentage of the buildings to repair in time intervals, in the EU Member States; right RCP4.5 scenario (green colour); left RCP8.5 scenario (blue colour). 71

**Table 15.** Increase in total repair cost by 2100 due to climate change induced carbonation in European countries in billions of Euros, (B€, 10⁹ €). 76

**Table 16.** Total repair cost per year (annual repair cost) due to climate change induced carbonation in European countries in billions of euro (B€, 10⁹ €). 77

**Table 17.** Annual repair cost, by year 2100, due to climate change-induced carbonation in EU-27 countries, expressed as a percentage of the respective country's GDP (latest value 2022) and number of buildings with corrosion starting before and after 2100. 78

**Table 18.** Summary of the considered durability parameters for exposure class XC4 and for an intended working life of at least 50 years, used in the calculations. The choice is explained in Chapter 5, section 5.2 and values of the durability parameters are depicted in Figure 23, Figure 24, and Figure 25 of the report. 130

**Table 19.** Percentage of increase of carbonation depth in 27-EU capital cities. 131
# Annexes

<figure><img src="image_52.png" /><figcaption>## Annex 1. Temperature scenarios for the capital cities of the 27 EU Member States</figcaption></figure>

<figure><img src="image_53.png" /></figure>
# Annexes

<figure><img src="image_54.png" /><figcaption>## Annex 1. Temperature scenarios for the capital cities of the 27 EU Member States</figcaption></figure>
<figure><img src="image_54.png" /></figure>

<figure><img src="image_55.png" /></figure>

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<figure><img src="image_79.png" /><figcaption>Annex 2. Annual carbonation depths for the capital cities of the 27 EU Member States</figcaption></figure>
<figure><img src="image_80.png" /><figcaption>Annex 2. Annual carbonation depths for the capital cities of the 27 EU Member States</figcaption></figure>
Carbonation depth in Bratislava

<figure><img src="image_80.png" /></figure>

Carbonation depth in Brussels

<figure><img src="image_81.png" /></figure>

Carbonation depth in Bucharest

<figure><img src="image_82.png" /></figure>
Carbonation depth in Bratislava

<figure><img src="image_81.png" /></figure>

Carbonation depth in Brussels

<figure><img src="image_82.png" /></figure>

Carbonation depth in Bucharest

<figure><img src="image_83.png" /></figure>
Carbonation depth in Budapest

<figure><img src="image_83.png" /></figure>

Carbonation depth in Copenhagen

<figure><img src="image_84.png" /></figure>

Carbonation depth in Dublin

<figure><img src="image_85.png" /></figure>
Carbonation depth in Budapest

<figure><img src="image_84.png" /></figure>

Carbonation depth in Copenhagen

<figure><img src="image_85.png" /></figure>

Carbonation depth in Dublin

<figure><img src="image_86.png" /></figure>
Carbonation depth in Helsinki

<figure><img src="image_86.png" /></figure>

Carbonation depth in Lisbon

<figure><img src="image_87.png" /></figure>

Carbonation depth in Ljubljana

<figure><img src="image_88.png" /></figure>
Carbonation depth in Helsinki

<figure><img src="image_87.png" /></figure>

Carbonation depth in Lisbon

<figure><img src="image_88.png" /></figure>

Carbonation depth in Ljubljana

<figure><img src="image_89.png" /></figure>
Carbonation depth in Luxembourg

<figure><img src="image_89.png" /></figure>

Carbonation depth in Madrid

<figure><img src="image_90.png" /></figure>

Carbonation depth in Nicosia

<figure><img src="image_91.png" /></figure>
Carbonation depth in Luxembourg

<figure><img src="image_90.png" /></figure>

Carbonation depth in Madrid

<figure><img src="image_91.png" /></figure>

Carbonation depth in Nicosia

<figure><img src="image_92.png" /></figure>
Carbonation depth in Paris

<figure><img src="image_92.png" /></figure>

Carbonation depth in Prague

<figure><img src="image_93.png" /></figure>

Carbonation depth in Riga

<figure><img src="image_94.png" /></figure>
Carbonation depth in Paris

<figure><img src="image_93.png" /></figure>

Carbonation depth in Prague

<figure><img src="image_94.png" /></figure>

Carbonation depth in Riga

<figure><img src="image_95.png" /></figure>
Carbonation depth in Rome

<figure><img src="image_95.png" /></figure>

Carbonation depth in Sofia

<figure><img src="image_96.png" /></figure>

Carbonation depth in Stockholm

<figure><img src="image_97.png" /></figure>
Carbonation depth in Rome

<figure><img src="image_96.png" /></figure>

Carbonation depth in Sofia

<figure><img src="image_97.png" /></figure>

Carbonation depth in Stockholm

<figure><img src="image_98.png" /></figure>
Carbonation depth in Tallinn

<figure><img src="image_98.png" /></figure>

Carbonation depth in Valletta

<figure><img src="image_99.png" /></figure>

Carbonation depth in Vienna

<figure><img src="image_100.png" /></figure>
Carbonation depth in Tallinn

<figure><img src="image_99.png" /></figure>

Carbonation depth in Valletta

<figure><img src="image_100.png" /></figure>

Carbonation depth in Vienna

<figure><img src="image_101.png" /></figure>
Carbonation depth in Vilnius

<figure><img src="image_101.png" /></figure>

Carbonation depth in Warsaw

<figure><img src="image_102.png" /></figure>

Carbonation depth in Zagreb

<figure><img src="image_103.png" /></figure>
Carbonation depth in Vilnius

<figure><img src="image_102.png" /></figure>

Carbonation depth in Warsaw

<figure><img src="image_103.png" /></figure>

Carbonation depth in Zagreb

<figure><img src="image_104.png" /></figure>
<figure><img src="image_104.png" /><figcaption>Annex 3. Probability of corrosion initiation for the capital cities of the 27 EU Member States</figcaption></figure>

<figure><img src="image_105.png" /></figure>

<figure><img src="image_106.png" /></figure>
<figure><img src="image_105.png" /><figcaption>Annex 3. Probability of corrosion initiation for the capital cities of the 27 EU Member States</figcaption></figure>
Probability of corrosion initiation in Bratislava

<figure><img src="image_107.png" /></figure>

Probability of corrosion initiation in Brussels

<figure><img src="image_108.png" /></figure>

Probability of corrosion initiation in Bucharest

<figure><img src="image_109.png" /></figure>
Probability of corrosion initiation in Bratislava

<figure><img src="image_106.png" /></figure>

Probability of corrosion initiation in Brussels

<figure><img src="image_107.png" /></figure>

Probability of corrosion initiation in Bucharest

<figure><img src="image_108.png" /></figure>
Probability of corrosion initiation in Budapest

<figure><img src="image_110.png" /></figure>

Probability of corrosion initiation in Copenhagen

<figure><img src="image_111.png" /></figure>

Probability of corrosion initiation in Dublin

<figure><img src="image_112.png" /></figure>
Probability of corrosion initiation in Budapest

<figure><img src="image_109.png" /></figure>

Probability of corrosion initiation in Copenhagen

<figure><img src="image_110.png" /></figure>

Probability of corrosion initiation in Dublin

<figure><img src="image_111.png" /></figure>
Probability of corrosion initiation in Helsinki

<figure><img src="image_113.png" /></figure>

Probability of corrosion initiation in Lisbon

<figure><img src="image_114.png" /></figure>

Probability of corrosion initiation in Ljubljana

<figure><img src="image_115.png" /></figure>
Probability of corrosion initiation in Helsinki

<figure><img src="image_112.png" /></figure>

Probability of corrosion initiation in Lisbon

<figure><img src="image_113.png" /></figure>

Probability of corrosion initiation in Ljubljana

<figure><img src="image_114.png" /></figure>
Probability of corrosion initiation in Luxembourg

<figure><img src="image_116.png" /></figure>

Probability of corrosion initiation in Madrid

<figure><img src="image_117.png" /></figure>

Probability of corrosion initiation in Nicosia

<figure><img src="image_118.png" /></figure>
Probability of corrosion initiation in Luxembourg

<figure><img src="image_115.png" /></figure>

Probability of corrosion initiation in Madrid

<figure><img src="image_116.png" /></figure>

Probability of corrosion initiation in Nicosia

<figure><img src="image_117.png" /></figure>
Probability of corrosion initiation in Paris

<figure><img src="image_119.png" /></figure>

Probability of corrosion initiation in Prague

<figure><img src="image_120.png" /></figure>

Probability of corrosion initiation in Riga

<figure><img src="image_121.png" /></figure>
Probability of corrosion initiation in Paris

<figure><img src="image_118.png" /></figure>

Probability of corrosion initiation in Prague

<figure><img src="image_119.png" /></figure>

Probability of corrosion initiation in Riga

<figure><img src="image_120.png" /></figure>
Probability of corrosion initiation in Rome

<figure><img src="image_122.png" /></figure>

Probability of corrosion initiation in Sofia

<figure><img src="image_123.png" /></figure>

Probability of corrosion initiation in Stockholm

<figure><img src="image_124.png" /></figure>
Probability of corrosion initiation in Rome

<figure><img src="image_121.png" /></figure>

Probability of corrosion initiation in Sofia

<figure><img src="image_122.png" /></figure>

Probability of corrosion initiation in Stockholm

<figure><img src="image_123.png" /></figure>
Probability of corrosion initiation in Tallinn

<figure><img src="image_125.png" /></figure>

Probability of corrosion initiation in Valletta

<figure><img src="image_126.png" /></figure>

Probability of corrosion initiation in Vienna

<figure><img src="image_127.png" /></figure>
Probability of corrosion initiation in Tallinn

<figure><img src="image_124.png" /></figure>

Probability of corrosion initiation in Valletta

<figure><img src="image_125.png" /></figure>

Probability of corrosion initiation in Vienna

<figure><img src="image_126.png" /></figure>
Probability of corrosion initiation in Vilnius

<figure><img src="image_128.png" /></figure>

Probability of corrosion initiation in Warsaw

<figure><img src="image_129.png" /></figure>

Probability of corrosion initiation in Zagreb

<figure><img src="image_130.png" /></figure>
Probability of corrosion initiation in Vilnius

<figure><img src="image_127.png" /></figure>

Probability of corrosion initiation in Warsaw

<figure><img src="image_128.png" /></figure>

Probability of corrosion initiation in Zagreb

<figure><img src="image_129.png" /></figure>
Annex 4. Informative tables

<table><caption>**Table 18.** Summary of the considered durability parameters for exposure class XC4 and for an intended working life of at least 50 years, used in the calculations. The choice is explained in Chapter 5, section 5.2 and values of the durability parameters are depicted in Figure 23, Figure 24, and Figure 25 of the report.</caption><thead><tr><th rowspan="2">Country</th><th rowspan="2">Capital City</th><th colspan="2">Concrete cover c<sub>t</sub> (mm)</th><th colspan="2">Max. W/C</th><th colspan="2">MCC Ce (kg/m<sup>3</sup>)</th></tr><tr><th>Low code</th><th>High code</th><th>Low code</th><th>High code</th><th>Low code</th><th>High code</th></tr></thead><tbody><tr><td>AUT</td><td>Vienna</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>BEL</td><td>Brussels</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>320</td></tr><tr><td>BGR</td><td>Sofia</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>CYP</td><td>Nicosia</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>CZE</td><td>Prague</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>DEU</td><td>Berlin</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>310</td><td>310</td></tr><tr><td>DNK</td><td>Copenhagen</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>ESP</td><td>Madrid</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>250</td><td>290</td></tr><tr><td>EST</td><td>Tallinn</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>FIN</td><td>Helsinki</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>FRA</td><td>Paris</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>310</td><td>310</td></tr><tr><td>GRC</td><td>Athens</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>HRV</td><td>Zagreb</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>HUN</td><td>Budapest</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>IRL</td><td>Dublin</td><td>20</td><td>40</td><td>0.50</td><td>0.55</td><td>280</td><td>320</td></tr><tr><td>ITA</td><td>Rome</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>LTU</td><td>Vilnius</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>LUX</td><td>Luxembourg</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>320</td></tr><tr><td>LVA</td><td>Riga</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>MLT</td><td>Valletta</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>NLD</td><td>Amsterdam</td><td>20</td><td>40</td><td>0.55</td><td>0.55</td><td>280</td><td>320</td></tr><tr><td>POL</td><td>Warsaw</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>PRT</td><td>Lisbon</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>250</td><td>290</td></tr><tr><td>ROU</td><td>Bucharest</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>SVK</td><td>Bratislava</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>SVN</td><td>Ljubljana</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>SWE</td><td>Stockholm</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr></tbody></table>

Source: Developed by authors.

<footnote n="1">¹ Note: Similar colours indicate equal values in different countries. Only small differences have been found in The Netherlands, particularly with regard to the maximum water-cement ratio (W/C) in comparison to Luxembourg and Belgium, where it is 0.55 instead of 0.50 for high and low code specifications.</footnote>
Annex 4. Informative tables

<table><caption>**Table 18.** Summary of the considered durability parameters for exposure class XC4 and for an intended working life of at least 50 years, used in the calculations. The choice is explained in Chapter 5, section 5.2 and values of the durability parameters are depicted in Figure 23, Figure 24, and Figure 25 of the report.</caption><thead><tr><th colspan="2">EU-27</th><th colspan="2">Concrete cover c<sub>t</sub> (mm)</th><th colspan="2">Max. W/C</th><th colspan="2">MCC Ce (kg/m<sup>3</sup>)</th></tr><tr><th>Country</th><th>Capital City</th><th>Low code</th><th>High code</th><th>Low code</th><th>High code</th><th>Low code</th><th>High code</th></tr></thead><tbody><tr><td>AUT</td><td>Vienna</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>BEL</td><td>Brussels</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>320</td></tr><tr><td>BGR</td><td>Sofia</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>CYP</td><td>Nicosia</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>CZE</td><td>Prague</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>DEU</td><td>Berlin</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>310</td><td>310</td></tr><tr><td>DNK</td><td>Copenhagen</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>ESP</td><td>Madrid</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>250</td><td>290</td></tr><tr><td>EST</td><td>Tallinn</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>FIN</td><td>Helsinki</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>FRA</td><td>Paris</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>310</td><td>310</td></tr><tr><td>GRC</td><td>Athens</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>HRV</td><td>Zagreb</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>HUN</td><td>Budapest</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>IRL</td><td>Dublin</td><td>20</td><td>40</td><td>0.50</td><td>0.55</td><td>280</td><td>320</td></tr><tr><td>ITA</td><td>Rome</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>LTU</td><td>Vilnius</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>LUX</td><td>Luxembourg</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>320</td></tr><tr><td>LVA</td><td>Riga</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr><tr><td>MLT</td><td>Valletta</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>NLD</td><td>Amsterdam</td><td>20</td><td>40</td><td>0.55</td><td>0.55</td><td>280</td><td>320</td></tr><tr><td>POL</td><td>Warsaw</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>PRT</td><td>Lisbon</td><td>20</td><td>40</td><td>0.60</td><td>0.60</td><td>250</td><td>290</td></tr><tr><td>ROU</td><td>Bucharest</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>SVK</td><td>Bratislava</td><td>20</td><td>45</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>SVN</td><td>Ljubljana</td><td>20</td><td>40</td><td>0.50</td><td>0.50</td><td>280</td><td>300</td></tr><tr><td>SWE</td><td>Stockholm</td><td>20</td><td>35</td><td>0.55</td><td>0.55</td><td>180</td><td>200</td></tr></tbody></table>

Source: Developed by authors.

<footnote n="1">¹ Note: Similar colours indicate equal values in different countries. Only small differences have been found in The Netherlands, particularly with regard to the maximum water-cement ratio (W/C) in comparison to Luxembourg and Belgium, where it is 0.55 instead of 0.50 for high and low code specifications.</footnote>
<table><caption>**Table 19.** Percentage of increase of carbonation depth in 27-EU capital cities.</caption><thead><tr><th rowspan="3">Scenario</th><th rowspan="3">City /Year</th><th colspan="4">Old buildings (constructed 1965)</th><th colspan="4">Recent buildings (constructed 2000)</th></tr><tr><th colspan="2">RCP4.5</th><th colspan="2">RCP8.5</th><th colspan="2">RCP4.5</th><th colspan="2">RCP8.5</th></tr><tr><th>2050</th><th>2085</th><th>2050</th><th>2085</th><th>2050</th><th>2085</th><th>2050</th><th>2085</th></tr></thead><tbody><tr><td>AUT</td><td>Vienna</td><td>30</td><td>38</td><td>39</td><td>77</td><td>18</td><td>26</td><td>26</td><td>61</td></tr><tr><td>BEL</td><td>Brussels</td><td>28</td><td>36</td><td>37</td><td>76</td><td>19</td><td>27</td><td>27</td><td>64</td></tr><tr><td>BGR</td><td>Sofia</td><td>30</td><td>39</td><td>39</td><td>78</td><td>19</td><td>26</td><td>27</td><td>62</td></tr><tr><td>CYP</td><td>Nicosia</td><td>32</td><td>41</td><td>41</td><td>81</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>CZE</td><td>Prague</td><td>30</td><td>38</td><td>38</td><td>77</td><td>18</td><td>26</td><td>26</td><td>61</td></tr><tr><td>DEU</td><td>Berlin</td><td>28</td><td>36</td><td>37</td><td>77</td><td>19</td><td>27</td><td>27</td><td>64</td></tr><tr><td>DNK</td><td>Copenhagen</td><td>31</td><td>39</td><td>40</td><td>80</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>ESP</td><td>Madrid</td><td>30</td><td>38</td><td>38</td><td>77</td><td>19</td><td>26</td><td>27</td><td>61</td></tr><tr><td>EST</td><td>Tallinn</td><td>28</td><td>36</td><td>37</td><td>73</td><td>17</td><td>25</td><td>25</td><td>58</td></tr><tr><td>FIN</td><td>Helsinki</td><td>33</td><td>43</td><td>43</td><td>84</td><td>21</td><td>30</td><td>30</td><td>68</td></tr><tr><td>FRA</td><td>Paris</td><td>32</td><td>39</td><td>40</td><td>78</td><td>18</td><td>25</td><td>25</td><td>59</td></tr><tr><td>GRC</td><td>Athens</td><td>35</td><td>43</td><td>44</td><td>86</td><td>19</td><td>27</td><td>27</td><td>65</td></tr><tr><td>HRV</td><td>Zagreb</td><td>30</td><td>39</td><td>39</td><td>79</td><td>19</td><td>26</td><td>26</td><td>63</td></tr><tr><td>HUN</td><td>Budapest</td><td>33</td><td>41</td><td>42</td><td>83</td><td>19</td><td>27</td><td>28</td><td>65</td></tr><tr><td>IRL</td><td>Dublin</td><td>28</td><td>36</td><td>37</td><td>75</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>ITA</td><td>Rome</td><td>30</td><td>38</td><td>39</td><td>77</td><td>18</td><td>26</td><td>26</td><td>61</td></tr><tr><td>LTU</td><td>Vilnius</td><td>30</td><td>38</td><td>39</td><td>78</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>LUX</td><td>Luxembourg</td><td>33</td><td>42</td><td>42</td><td>83</td><td>20</td><td>28</td><td>28</td><td>64</td></tr><tr><td>LVA</td><td>Riga</td><td>30</td><td>37</td><td>38</td><td>76</td><td>18</td><td>25</td><td>26</td><td>61</td></tr><tr><td>MLT</td><td>Valletta</td><td>37</td><td>45</td><td>46</td><td>89</td><td>19</td><td>27</td><td>28</td><td>65</td></tr><tr><td>NLD</td><td>Amsterdam</td><td>33</td><td>43</td><td>43</td><td>83</td><td>20</td><td>29</td><td>29</td><td>65</td></tr><tr><td>POL</td><td>Warsaw</td><td>35</td><td>44</td><td>44</td><td>87</td><td>21</td><td>30</td><td>30</td><td>67</td></tr><tr><td>PRT</td><td>Lisbon</td><td>35</td><td>45</td><td>45</td><td>88</td><td>20</td><td>28</td><td>28</td><td>66</td></tr><tr><td>ROU</td><td>Bucharest</td><td>30</td><td>38</td><td>39</td><td>78</td><td>19</td><td>26</td><td>26</td><td>62</td></tr><tr><td>SVK</td><td>Bratislava</td><td>33</td><td>41</td><td>42</td><td>82</td><td>20</td><td>28</td><td>28</td><td>65</td></tr><tr><td>SVN</td><td>Ljubljana</td><td>31</td><td>40</td><td>40</td><td>80</td><td>19</td><td>27</td><td>27</td><td>63</td></tr></tbody></table>

Source: Developed by authors.

<footnote n="2">² Note: In bold black colour, maximum values of the selected range by column; in bold grey colour minimum values of the selected range by column.</footnote>
<table><caption>**Table 19.** Percentage of increase of carbonation depth in 27-EU capital cities.</caption><thead><tr><th rowspan="3">Scenario</th><th rowspan="3">City /Year</th><th colspan="4">Old buildings (constructed 1965)</th><th colspan="4">Recent buildings (constructed 2000)</th></tr><tr><th colspan="2">RCP4.5</th><th colspan="2">RCP8.5</th><th colspan="2">RCP4.5</th><th colspan="2">RCP8.5</th></tr><tr><th>2050</th><th>2085</th><th>2050</th><th>2085</th><th>2050</th><th>2085</th><th>2050</th><th>2085</th></tr></thead><tbody><tr><td>AUT</td><td>Vienna</td><td>30</td><td>38</td><td>39</td><td>77</td><td>18</td><td>26</td><td>26</td><td>61</td></tr><tr><td>BEL</td><td>Brussels</td><td>28</td><td>36</td><td>37</td><td>76</td><td>19</td><td>27</td><td>27</td><td>64</td></tr><tr><td>BGR</td><td>Sofia</td><td>30</td><td>39</td><td>39</td><td>78</td><td>19</td><td>26</td><td>27</td><td>62</td></tr><tr><td>CYP</td><td>Nicosia</td><td>32</td><td>41</td><td>41</td><td>81</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>CZE</td><td>Prague</td><td>30</td><td>38</td><td>38</td><td>77</td><td>18</td><td>26</td><td>26</td><td>61</td></tr><tr><td>DEU</td><td>Berlin</td><td>28</td><td>36</td><td>37</td><td>77</td><td>19</td><td>27</td><td>27</td><td>64</td></tr><tr><td>DNK</td><td>Copenhagen</td><td>31</td><td>39</td><td>40</td><td>80</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>ESP</td><td>Madrid</td><td>30</td><td>38</td><td>38</td><td>77</td><td>19</td><td>26</td><td>27</td><td>61</td></tr><tr><td>EST</td><td>Tallinn</td><td>28</td><td>36</td><td>37</td><td>73</td><td>17</td><td>25</td><td>25</td><td>58</td></tr><tr><td>FIN</td><td>Helsinki</td><td>33</td><td>43</td><td>43</td><td>84</td><td>21</td><td>30</td><td>30</td><td>68</td></tr><tr><td>FRA</td><td>Paris</td><td>32</td><td>39</td><td>40</td><td>78</td><td>18</td><td>25</td><td>25</td><td>59</td></tr><tr><td>GRC</td><td>Athens</td><td>35</td><td>43</td><td>44</td><td>86</td><td>19</td><td>27</td><td>27</td><td>65</td></tr><tr><td>HRV</td><td>Zagreb</td><td>30</td><td>39</td><td>39</td><td>79</td><td>19</td><td>26</td><td>26</td><td>63</td></tr><tr><td>HUN</td><td>Budapest</td><td>33</td><td>41</td><td>42</td><td>83</td><td>19</td><td>27</td><td>28</td><td>65</td></tr><tr><td>IRL</td><td>Dublin</td><td>28</td><td>36</td><td>37</td><td>75</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>ITA</td><td>Rome</td><td>30</td><td>38</td><td>39</td><td>77</td><td>18</td><td>26</td><td>26</td><td>61</td></tr><tr><td>LTU</td><td>Vilnius</td><td>30</td><td>38</td><td>39</td><td>78</td><td>19</td><td>26</td><td>27</td><td>63</td></tr><tr><td>LUX</td><td>Luxembourg</td><td>33</td><td>42</td><td>42</td><td>83</td><td>20</td><td>28</td><td>28</td><td>64</td></tr><tr><td>LVA</td><td>Riga</td><td>30</td><td>37</td><td>38</td><td>76</td><td>18</td><td>25</td><td>26</td><td>61</td></tr><tr><td>MLT</td><td>Valletta</td><td>37</td><td>45</td><td>46</td><td>89</td><td>19</td><td>27</td><td>28</td><td>65</td></tr><tr><td>NLD</td><td>Amsterdam</td><td>33</td><td>43</td><td>43</td><td>83</td><td>20</td><td>29</td><td>29</td><td>65</td></tr><tr><td>POL</td><td>Warsaw</td><td>35</td><td>44</td><td>44</td><td>87</td><td>21</td><td>30</td><td>30</td><td>67</td></tr><tr><td>PRT</td><td>Lisbon</td><td>35</td><td>45</td><td>45</td><td>88</td><td>20</td><td>28</td><td>28</td><td>66</td></tr><tr><td>ROU</td><td>Bucharest</td><td>30</td><td>38</td><td>39</td><td>78</td><td>19</td><td>26</td><td>26</td><td>62</td></tr><tr><td>SVK</td><td>Bratislava</td><td>33</td><td>41</td><td>42</td><td>82</td><td>20</td><td>28</td><td>28</td><td>65</td></tr><tr><td>SVN</td><td>Ljubljana</td><td>31</td><td>40</td><td>40</td><td>80</td><td>19</td><td>27</td><td>27</td><td>63</td></tr></tbody></table>

Source: Developed by authors.

<footnote n="2">² Note: In bold black colour, maximum values of the selected range by column; in bold grey colour minimum values of the selected range by column.</footnote>
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# Getting in touch with the EU

## In person

All over the European Union there are hundreds of Europe Direct centres. You can find the address of the centre nearest you online (european-union.europa.eu/contact-eu/meet-us_en).

## On the phone or in writing

Europe Direct is a service that answers your questions about the European Union. You can contact this service:

- by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls),

- at the following standard number: +32 22999696,

- via the following form: european-union.europa.eu/contact-eu/write-us_en.

# Finding information about the EU

## Online

Information about the European Union in all the official languages of the EU is available on the Europa website (european-union.europa.eu).

## EU publications

You can view or order EU publications at op.europa.eu/en/publications. Multiple copies of free publications can be obtained by contacting Europe Direct or your local documentation centre (european-union.europa.eu/contact-eu/meet-us_en).

## EU law and related documents

For access to legal information from the EU, including all EU law since 1951 in all the official language versions, go to EUR-Lex (eur-lex.europa.eu).

## EU open data

The portal data.europa.eu provides access to open datasets from the EU institutions, bodies and agencies. These can be downloaded and reused for free, for both commercial and non-commercial purposes. The portal also provides access to a wealth of datasets from European countries.
Science for policy

The Joint Research Centre (JRC) provides
independent, evidence-based knowledge
and science, supporting EU policies to
positively impact society

<figure><img src="image_131.png" /></figure>

EU Science Hub

joint-research-centre.ec.europa.eu

<figure><img src="image_132.png" /></figure>

Publications Office
of the European Union
Science for policy

The Joint Research Centre (JRC) provides
independent, evidence-based knowledge
and science, supporting EU policies to
positively impact society

<figure><img src="image_130.png" /></figure>

EU Science Hub

joint-research-centre.ec.europa.eu

<figure><img src="image_131.png" /></figure>

Publications Office
of the European Union