MARIA ISABEL TOUCEDA GOMEZ FRAMEWORK APPLIED TO HOUSING RETROFITTING LIFE CYCLE SUSTAINABILITY ASSESSMENT

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IMPLEMENTATION OF SOCIOECONOMIC CRITERIA IN A

LIFE CYCLE SUSTAINABILITY ASSESSMENT

FRAMEWORK APPLIED TO HOUSING RETROFITTING

THE BRUSSELS-CAPITAL REGION CASE STUDY

MARIA ISABEL TOUCEDA GOMEZ

DOCTORAL THESIS

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IMPLEMENTATION OF SOCIOECONOMIC CRITERIA IN

A LIFE CYCLE SUSTAINABILITY ASSESSMENT

FRAMEWORK APPLIED TO HOUSING RETROFITTING:

THE BRUSSELS-CAPITAL REGION CASE STUDY

María Isabel Touceda Gómez

Doctoral thesis

DOCTORAT À L’ECOLE POLYTECHNIQUE DE BRUXELLES EN ART DE

BATIR ET URBANISME. UNIVERSITE LIBRE DE BRUXELLES

4MAT RECYCLING & ENVIRONMENT

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Title: Implementation of socioeconomic criteria in a life cycle

sustainability assessment framework applied to housing retrofitting. The Brussels-Capital region case study.

Institution: Doctorat à l’Ecole Polytechnique de Bruxelles. Art de bâtir et

urbanisme. Université Libre de Bruxelles.

PhD student: María Isabel Touceda Gómez, Architect by the Universitat

Politècnica de Catalunya. UPC-BARCELONA TECH.

Supervisor: Professor. Marc Degrez. 4MAT recycling & environment. Université

Libre de Bruxelles ULB

Deposit: June 2016

Private defense: 15 September 2016, at the Université Libre de Bruxelles.

Public defense: 10 October 2013, at the Université Libre de Bruxelles.

President of the jury:

Philippe Bouillard, BATIR, Université Libre de Bruxelles.

Members of the jury:

Wouter Achten, IGEAT, Université Libre de Bruxelles.

Irene Cuerda Barcaiztegui, ABIO-UPM, Universidad Politécnica de Madrid, Espagne.

Marc Degrez, 4MAT Recycling & Environment, Université Libre de Bruxelles.

Marie-Françoise Godart, Université Libre de Bruxelles.

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ACKNOWLEDGEMENTS

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Acknowledgements

MARC DEGREZ Direction | production | promotion | original idea |

logistics | daily chat | Belgian culture |

ELVIRA GOMEZ Logistics | catering | chat |

FRANCISCO TOUCEDA Model of integrity |

VANESSA, ALIENOR, LOUISE Daily assistance | coaching | supervision | reading |

mechanical assistance

ANESTOS, GEMMA BROWN Subtitles |

SHAIN AND 4MAT Daily assistance | catering |

COLLECTIF IPÉ+ Prospective |

JAVIER NEILA Logics | reasoning assistance |

FEDERICO G. ERVITI LCC assistance|

INNOVIRIS 2-year funding |

BLAUW Entertaining activities | atrezzo |

FAMILIA TOUCEDA Photography |

IRENE CUERDA Reading | logical reasoning | coaching | jury

PATXI HERNANDEZ Reading | jury

PHILIPPE BOUILLARD Reading | advisory committee| jury

MARIE-FRANCOISE

GODART Reading | advisory committee| jury

WOUTER ACHTEN Reading | jury

BERNARD DEPREZ Advice |

PAOLA MICHIALINO AND

C.A. LE FOYER JETTOIS Data |

THIERRY CLAES Data |

BUREAU FEDERAL DU PLAN Data |

IBGE Data|

CATHERINE BOULAND Advice |

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ABSTRACT (ENGLISH)

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Abstract (English)

Most of the housing stock in European cities needs to be updated to fulfill current requirements. Although energy and climate have been prioritized in European policies, other sustainable development challenges are sometimes disregarded. Retrofitting plays a part in addressing social concerns such as unemployment and poverty. Therefore, these issues also need to be tackled during the decision-making process.

Decision makers need assessment methods to help them to comprehensively address complex processes such as retrofitting on a territorial scale. Several tools are available to address certain aspects of building sustainability, but these often disregard social inclusion aspects. The life cycle sustainability assessment (LCSA) methodology seems to be an appropriate framework, but it needs further adaptation and development for the intended application; that is, to guide policy-making related to housing retrofitting in a given territory towards a more sustainable model of development.

This PhD thesis develops an assessment tool in the framework of LCSA. The proposal combines environmental assessment methods with a set of specifically developed socioeconomic models. The socioeconomic models address social and socioeconomic concerns, which are relevant in housing retrofitting processes, for which a cause-effect relationship can be established. The so-called characterization

models result from the identification, combination and adaptation of available

methods developed within various research fields. These methods analyze damages to the health of workers involved in the life cycle and to the health of the household living in the retrofitted dwelling. Impacts on human well-being and dignity are addressed through prosperity, in terms of fair employment, alleviation of fuel poverty of households, and contribution to economic growth.

Two retrofits are analyzed and compared in multiple scenarios of household and housing conditions. The impacts of the retrofitting on sustainable development are calculated considering their remaining life period and taking into account the reference situation where retrofitting would not be undertaken. Some of the results are unexpected, whereas others were more predictable, and the tool helps to properly quantifying them. However, the tool does not provide a unique solution: the “best-performing” scenarios regarding natural environment are the “less-performing” scenarios regarding health and well-being, and vice versa. Decisions therefore need to be adjusted and aim for a combination of job creation, meeting environmental targets, overcoming poverty thresholds and using available public resources. This LCSA proposal helps to adapt measures which promote retrofitting to housing typologies, household type and dwelling conditions. This tool also serves to identify scenarios to prioritize and quantify the potential improvements in the retrofitting process.

 Keywords

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ABSTRACT (FRANÇAIS)

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Abstract (Français)

En Europe, la plupart du parc bâti de logements doit être rénové en accord avec les besoins actuels. Dans les politiques européennes, la priorité est donnée à l’énergie et au climat et d’autres défis liés au développement durable semblent être négligés. La rénovation parait pouvoir atténuer des problèmes sociaux tels que le taux de chômage, la pauvreté ou l’exclusion sociale et doit donc aussi être considérées.

Les décideurs publics ont besoin de méthodes d’analyse qui leur permettent d’aborder des processus complexes comme la rénovation de logements au niveau du territoire. Il y plusieurs outils à disposition pour analyser certains aspects de la

durabilité des bâtiments mais, souvent, ces outils ne prennent pas en compte des

aspects d’inclusion sociale. La méthodologie d’analyse de la durabilité du cycle de vie (LCSA en anglais) s’avère un cadre approprié pour aborder cette problématique mais il est encore nécessaire de la développer et de l’adapter pour l’appliquer à l’objet de cette étude , c’est-à-dire, guider la prise de décisions publiques, en relation avec la rénovation de bâtiments à l’échelle du territoire, vers un développement plus durable.

Cette recherche développe « sur mesure » un outil d’analyse dans le cadre du LCSA. La méthodologie proposée combine des méthodes d’analyse environnementale avec un ensemble de modèles socioéconomiques, dits modèles de caractérisation. Ces derniers, spécifiquement développés, ciblent des préoccupations sociales et socioéconomiques qui concernent le processus de rénovation du logement et dont la relation cause-effet peut être établie. Ils résultent de l’identification, la combinaison et l’adaptation de méthodes existantes développées dans différents domaines. Ces méthodes analysent les impacts sur la santé des travailleurs impliqués dans tout le cycle de vie et sur la santé du ménage qui habite le logement. Les impacts sur le bien-être et la dignité humaine sont analysés au moyen de la prospérité, en termes de

travail juste, de la lutte contre la précarité énergétique et de la contribution au développement économique.

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ABSTRACT (ESPAÑOL)

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Abstract (Español)

La mayor parte del parque de viviendas en Europa debe actualizarse acorde a las necesidades actuales. Aspectos energéticos y climáticos se han priorizado hasta la actualidad en las directivas europeas, mientras que otras barreras al desarrollo sostenible son en cierta manera ignorados. La rehabilitación de vivienda puede mitigar problemas sociales como el desempleo o la pobreza y exclusión social, y por tanto deben ser integradas en las políticas de rehabilitación.

Los responsables públicos necesitan herramientas de análisis que les permitan enfrentarse a problemas complejos como la rehabilitación de viviendas a escala territorial. Existen muchas herramientas para analizar algunos aspectos de la

sostenibilidad de los edificios, pero a menudo estos no tienen en cuenta aspectos de inclusión social. La metodología de análisis de la sostenibilidad del ciclo de vida (LCSA

en inglés) es un enfoque metodológico apropiado para afrontar esta problemática pero que necesita cierto desarrollo para poder ser aplicado al objeto de este estudio: la ayudar en la toma de decisiones relacionadas con las políticas e incentivo de la rehabilitación a escala territorial para un desarrollo más sostenible.

La presente investigación desarrolla a medida una herramienta de análisis basado en el LCSA. La propuesta combina métodos de análisis de impacto ambiental con un conjunto de modelos socioeconómicos específicamente desarrollados. Estos modelos tratan preocupaciones sociales y socioeconómicas relacionadas con el proceso de renovación de vivienda para los que la relación causa-efecto puede ser establecida. Los así llamados modelos de caracterización resultan de la identificación, combinación y adaptación de métodos que ya existen, desarrollados cada uno en disciplinas diversas. Estos métodos analizan los impactos sobre la salud de los

trabajadores implicados en el ciclo de vida de una vivienda rehabilitada, así como los

impactos sobre la salud de los hogares que la habitan. Los impactos sobre el bienestar y dignidad humana son analizados desde el punto de vista de la prosperidad, en términos de trabajo justo, lucha contra la pobreza energética y de la contribución al

desarrollo económico.

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Scientific impacts

Publication in indexed journals

 2016, Touceda, M., Richard, A., Neila, J., Degrez, M. “Modelling socioeconomic

pathways to assess sustainability: a tailored development for housing retrofit ”.

The International Journal of Life Cycle Assessment, special issue on “life cycle sustainability assessment: from LCA to LCSA”. September 2016.

International conferences

 2015, Touceda, M., Richard, A., Neila, J., Degrez, M. "Life cycle sustainability assessment to improve retrofitting policies? A case study in Brussels" Doctoral Seminar on Sustainability Research in the Built Environment. 29th-30th April 2015, VUB, Brussels, Belgium.

 2014, Touceda, M., Richard, A., Neila, J., Degrez, M. “Implementation of socioeconomic criteria for the life cycle sustainability assessment of housing

retrofit”. 4th_{International Seminar in Social LCA. 19}th_{- 21}st_{November 2014 in}

Montpellier (France).

 2014, Touceda, M., Richard, A., Neila, J., Degrez, M. “Methodology proposal for the socio‐economic Life Cycle Assessment applied to retrofitting in a local context”. World Sustainable Building Conference WSB14 Barcelona, 28th-30th October 2014.

 2014, Touceda, M., Richard, A., Neila, J, Degrez, M. “Optimizing public instruments for boosting sustainable retrofitting: a methodology development.”

CONSTEC 2014 11th_-13th_{June Madrid, Spain 2014.}

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TABLE OF CONTENTS

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Tables

Table 1. Taxable average and median income, Belgium and big cities (2012 income, 2013 declarations).

Adapted from DGS-Statistics Belgium. ... 15

Table 2. Some housing-related indicators in EU-SILC statistics (Eurostat), Belgium 2014. ... 19

Table 3. Poverty risk threshold and amount of minimum allowances (per month), on 14/06/2013. Source: baromètre social 2013, source: EU-SILC. (Comma is used as decimal mark in this table) ... 21

Table 4. Classification of the housing typologies of Brussels (Inventaire du patrimoine architectural) ... 27

Table 5. Constructions costs /m2 of _{some BATEX-awarded renovation projects ... 31}

Table 6. Overview of objectives in housing renovation policies (Haines et al, 2009) ... 31

Table 7. Main working groups and reference documents in LC methodologies ... 49

Table 8. Social performance categories included in standard EN 15643-3:2012 ... 51

Table 9. Extract of the checklist for the informative module B1 (use stage)– reporting table, adapted from annex A (normative) of the standard EN 16309:2014. Thermal characteristics ... 52

Table 10. Summary of some aspects of the Inventory analysis (Ciroth and Franze 2011) ... 72

Table 11. Some relevant applications of social LCA and LCSA to case studies. ... 74

Table 12. BREEAM –Refurbishment: categories included and aspects related to social performance ... 77

Table 13. BREEAM: requirements for social aspects ... 78

Table 14. HQE certification of housing retrofitting: “Technical quality” criteria. ... 78

Table 15. Valideo for sustainable construction: subjects assessed ... 79

Table 16. Valideo: detail of criteria related to comfort and social value ... 79

Table 17. LEED requirements for social aspects. ... 80

Table 18. DGNB certification system: criteria related to socioeconomic issues. ... 81

Table 19. SBTool: categories related to socioeconomic assessment ... 81

Table 20. OpenHOUSE: social and economic issues considered. ... 82

Table 21. SuPerBuildings: indicators proposed to assess sustainability. ... 83

Table 22. SuPerBuildings: detail of indicators proposed to assess social aspects. ... 84

Table 23: European voluntary eco labels related to indoor air quality (EU research project report ECA n.24) 85 Table 24. FSC certification principles. ... 87

Table 25. Main requirements of the PEFC certification (social issues in bold) ... 87

Table 26. Socioeconomic aspects identified in the literature review and analysis of the context. ... 100

Table 27. Inventory indicators proposed for the LCI (own elaboration) ... 101

Table 28. Indicators and characterization rules of “damages to labor rights and decent work” (SHDB). ... 113

Table 29. Weighting factors of effects on well-being produced by poverty ... 117

Table 30. Weighting factors of effects of anxiety created by unemployment on well-being ... 117

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Table 32. Prices of energy and water, and hypotheses of price evolution (nominal discount rate). ... 161

Table 33. Prices of energy and water, and hypotheses of price evolution (real discount rate). ... 161

Table 34. Maximum rent depending on the number of bedrooms (left) and on the income (right) (SLRB). .. 162

Table 35. Requirements for passive, very low and low energy in Brussels-Capital Region. ... 162

Table 36. Equivalence factors used by EUROSTAT according to the OECD modified scale ... 163

Table 37. Household equivalized disposable income per quartiles of population. ... 164

Table 38. Allowances provided by the regional government to retrofitting in 2014. ... 164

Table 39. Number of deaths in Belgium between August 2012 and July2013 ... 165

Table 40. Scale of correspondence between incidence rate and level of risk in the SHDB. ... 166

Table 41. Options considered in the scenario definition ... 150

Table 42. Variables considered for the sensitivity assessments ... 152

Table 43: Description of the buildings. FLORAIR I & IV ... 155

Table 44. Number of dwellings and occupants (actual and total capacity). ... 157

Table 45. Maximum revenues per household for social housing eligibility, 2014 (SLRB). ... 157

Table 46. Estimations of social rentals, Florair ... 158

Table 47. Social rent increase of a 3-member typical apartment after the “very low energy” retrofitting. ... 158

Table 48. Repair and maintenance foreseen for the retrofit, Florair. ... 160

Table 49. Repair and maintenance hypotheses for the no retrofitting scenario, Florair. ... 161

Table 50: Summary of the technical building description and retrofitting works, Florair. ... 163

Table 51: Summary of the focus of the assessment ... 164

Table 52. Scenarios scheduled for the LCSA of Florair. ... 167

Table 53. Variables considered for the sensitivity assessment, Florair. ... 168

Table 54. Summary of characteristics, scenario 1A, and variables of the assessment. ... 168

Table 55. Socioeconomic inventory indicators and results per household (Hh), scenario 1A, Florair. ... 170

Table 56. Midpoint impact indicators and results per household (Hh), scenario 1A, Florair. ... 171

Table 57. Endpoint impacts (left) and aggregated results (right), scenario 1A, Florair. ... 172

Table 58. Damages to labor rights and decent work: working hours with low risk in background activities (SHDB, detail in annex III)... 174

Table 59. Determination of fuel poverty under the “Low income, high costs” indicator, scenario 1A, Florair ... 175

Table 60. Fuel poverty gap calculation in the no-retrofitting situation, scenario 1A, Florair. ... 176

Table 61. Scenario comparison: of damages to natural resources and natural environment. ... 179

Table 62. Scenario comparison: detail of damages on health. ... 180

Table 63. Scenario comparison: working hours on-site and background activities. ... 182

Table 64. Scenario comparison: detail before retrofit and after retrofit. ... 182

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Table 66. Aggregated endpoint results, all scenarios, Florair. ... 185

Table 67. Hypotheses for the analyses of sensitivity to the energy performance achieved ... 188

Table 68. Determination of fuel poverty with the passive retrofit, scenario 1Ater, Florair ... 189

Table 69. Hypotheses taken to assess the sensitivity of results to the materials employed. ... 191

Table 70. Scenario comparison, working hours associated to on-site and background activities in the case of no-retrofitting, retrofitting, and the difference of both (∆), in scenario 1A. ... 191

Table 71. Aids to unemployment avoided depending on the ratio “unemployment avoided/work demand”. ... 192

Table 72. Hypotheses of inflation and energy price increase ... 193

Table 73. Environmental impacts assessed with the Egalitarian (E), Hierarchist (H) or Individualist (I) perspective. Scenarios of thermal comfort and heating deprivation, Florair. ... 195

Table 74. Impacts on well-being associated to avoided fuel poverty, and to the fair employment generated with different weighting factors ... 195

Table 75. Description of the dwelling, Hankar. ... 199

Table 76. Technical description of building and of the retrofitting, Hankar. ... 202

Table 77. Repair, replacement and maintenance foreseen for the retrofit, Hankar. ... 202

Table 78. Repair and maintenance hypotheses for the no-retrofitting scenario, Hankar. ... 203

Table 79. Energy and water consumption, Hankar. ... 204

Table 80. Summary of the focus of the assessment. ... 205

Table 81. Scenarios scheduled for the LCSA, Hankar... 207

Table 82. Variables for the sensitivity assessment, Hankar. ... 207

Table 83. Summary of characteristics, scenario 1, Hankar. ... 208

Table 84. Socioeconomic inventory indicators and results, scenario 1, Hankar. ... 210

Table 85. Midpoint impact indicators and results, scenario 1, Hankar. ... 211

Table 86. Endpoint impacts and results (left) and aggregated results (right), scenario 1, Hankar. ... 212

Table 87. Damages to labor rights and decent work: detail of working hours with low risk, scenario 1. ... 214

Table 88. Scenario comparison: damages to natural resources and natural environment. ... 219

Table 89. Scenario comparison: detail of damages on health. ... 220

Table 90. Scenario comparison: damages to labor rights and decent work: working hours associated to foreground and background activities ... 221

Table 91. Scenario comparison: fuel poverty gap. ... 222

Table 92. Scenario comparison: detail of the costs and avoided costs for the State. ... 223

Table 93. Scenario comparison: aggregated endpoint results, Hankar. ... 224

Table 94. Hypotheses for the analyses of sensitivity to the energy performance achieved. ... 226

Table 95. Hypotheses to assess the sensitivity of results to the materials employed. ... 228

Table 96. Scenario comparison: working hours on-site and in background activities. ... 229

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Figures

Figure 1. The region of Brussels-Capital ... 11

Figure 2. Population increase in Brussels 1991-2014 and prospective 2015-2060. Source RN-DGS, BFP ... 13

Figure 3. Average household expenditure. Source: Household budget survey, 2014 SPF Economie. ... 16

Figure 4. Average housing-related costs (left) and expenditure in utility bills (right), both per household and income quartile in Brussels. Own elaboration based on the Household budget survey 2014 (SPF Economie). 17 Figure 5. Expenditure per household and year in heating, lighting and domestic water per income quartile in Brussels, 2010. Own elaboration based on the Household budget survey (SPF Economie). ... 17

Figure 6. Evolution of subsidized consumers in Brussels-Capital region. Source: annual reports SIBELGA, ... 18

Figure 7. Number of households attending for a social housing, Brussels 2006-2012 (PANind). Source: société de logements de la Région bruxelloise. ... 22

Figure 8. Variables of energy consumption and interactions in the residential sector (Haas 1997) ... 24

Figure 9. Main facades of some common typologies of Brussels ... 26

Figure 10. 2015 PEB energy requirements. Source: IBGE ... 29

Figure 11. Terminology in life cycle methodologies (own elaboration). ... 41

Figure 12. Impact pathway terminology and structure in LCA (own elaboration) ... 43

Figure 13. Options 1 and 2 of the life cycle sustainability assessment (LCSA) (klöpffer 2008). ... 48

Figure 14: Concept of sustainability assessment of buildings (EN 16309). ... 50

Figure 15: Work program of CEN TC 350 ... 51

Figure 16. UNEP/SETAC publications: The Guidelines, Methodological sheets, Towards a LCSA. ... 54

Figure 17. Impact categories and stakeholders included in the UNEP/SETAC Guidelines 2009 ... 55

Figure 18. Impact subcategories classified by stakeholder in the UNEP/SETAC guidelines, 2013 ... 56

Figure 19. Example of indicators suggested in The Methodological Sheets to assess the subcategory Child labor (2013). ... 57

Figure 20. Classic LCA structure (ISO 14040/44) ... 59

Figure 21. Comparison characterization models “type 1 and 2” (adapted from UNEP, 2009 based on Parent, 2010) ... 63

Figure 22 “Single Issue Risk Maps” screenshot of SHDB Web Portal User (tutorial). New Earth30 ... 69

Figure 23: Extract of the indicators concerning stakeholder “worker” (PSILCA, March 2016). ... 70

Figure 24. Impact subcategories (left), classified by stakeholder. Darker colors represent negative, and lighter are positive effects (Ciroth and Franze 2011). ... 72

Figure 25. Life cycle stages involved in the assessment of a retrofitting... 94

Figure 26 Top-down and bottom-up approach to define the inventory ... 95

Figure 27. Impact pathway terminology and structure in LCSA (own elaboration). ... 96

Figure 28. The concept of life cycle sustainability assessment (own elaboration). ... 97

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Figure 30. Relationship between LCI parameters (left), midpoint indicator (middle) and endpoint indicators

(right) in ReCiPe (adapted from ReCiPe main report 2013). ... 103

Figure 31. Example of impact pathways for the emission to air of two gases, the global warming potential and effects on health and on ecosystems (adapted from ReCiPe report). ... 104

Figure 32. Overview of the steps in modelling effects of greenhouse gases with respect to climate change (ReCiPe main report). ... 104

Figure 33. Impact pathways related to health (own elaboration) ... 105

Figure 34. Connections between indoor environment and health (Wilkinson et al. 2009) ... 108

Figure 35. Impact pathways related to poverty and prosperity (own elaboration) ... 111

Figure 36. Rubric for risk characterization rules for Freedom of association, collective bargaining, right to strike (SHDB). ... 113

Figure 37. Mapping the supply chain of a retrofit in Brussels (own elaboration). ... 151

Figure 38. Example: condensing boiler. Extract from « Generador de precios Cype » database (own translation). ... 152

Figure 39. Florair buildings: situation (dossier architecture Philippe Segui for the Foyer Jettois). ... 155

Figure 40. Florair I. East and West façade. Source: Philippe Segui architecture website and Foyer Jettois. .. 156

Figure 41. Florair IV. East and West façade. Source: Philippe Segui architecture website and Foyer Jettois. 156 Figure 42. Number of households per member composition (left), and per disposable income (right). Source: Foyer Jettois. ... 157

Figure 43. Costs (initial investment) of retrofitting works (VAT included), Florair I&IV ... 160

Figure 44. Boundaries of the assessment of the workforce involved. ... 162

Figure 45. Housing type floor type, apartment N09-5 Florair IV. Source: dossier architecture Philippe Segui. ... 165

Figure 46. Stages included and boundaries of assessment ... 165

Figure 47. Endpoint damages to natural resources (left) and natural environment (right) in scenario 1A. ... 173

Figure 48. Detail of damages to human health in scenario 1A (endpoint results). ... 173

Figure 49. Total working hours (left), and associated QALY (right) in scenario 1A. ... 175

Figure 50. Fuel poverty diagram, scenario 1 before and after retrofit ... 175

Figure 51. Evolution of the average income in FLORAIR after discounting housing and required fuel costs.. 176

Figure 52. Evolution of the average income in FLORAIR after discounting housing and required fuel costs.. 176

Figure 53. Detail of contribution to growth. ... 177

Figure 54. Aggregated endpoint LCSA results (∆retrofit-no retrofit) ... 177

Figure 55. Endpoint LCSA results of scenario 1A. Detail of impacts on health and well-being (∆retrofit-no retrofit). ... 178

Figure 56. Detail of impacts on the prosperity of society. ... 178

Figure 57. Scenario comparison of damages to natural resources and natural environment (endpoint results). ... 180

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Figure 59. Detail of the damages on health of the three scenarios: moldy apartment, under-heat apartment

(but not moldy) and apartment experiencing very low temperatures and mold. ... 181

Figure 60. Scenario comparison of the fuel poverty gap before and after retrofit. Representation per quadrants of vulnerability, being (I) the most and (IV) the less vulnerable. ... 183

Figure 61. Scenario comparison of the contribution to the growth of the State ... 184

Figure 62. Scenario comparison of aggregated endpoint results. Florair-social housing ... 185

Figure 63. Scenario comparison of aggregated endpoint results. Florair-private housing. ... 186

Figure 64. Detail of the aggregation of endpoint results into Contribution to prosperity ... 186

Figure 65. Detail of the aggregation of endpoint results into Health and well-being (not at the same scale). ... 187

Figure 66. Impacts to natural resources, natural environment and human health associated to the passive, very low energy and low energy retrofitting of Florair. ... 188

Figure 67. Damages to health and well-being: passive, very low energy, low energy hypotheses ... 189

Figure 68. Costs for the State associated to the passive, very low energy and low energy retrofitting. ... 190

Figure 69. Environmental impacts associated to the retrofit (in % units), detail of the impacts of the envelope and detail of the impacts associated to windows (Sima Pro). ... 190

Figure 70. Sensitivity of environmental results to the materials used in the retrofit. ... 191

Figure 71. Sensitivity of the net present cost of the retrofit for the State (left), years of fair employment (middle) and health & well-being (right) to the local or conventional supply. ... 192

Figure 72. After house costs (AHC) income (-) fuel costs. Comparison 3 % inflation (continuous line) and 1.5 % (pointed line) ... 193

Figure 73. Fuel poverty gap after retrofitting. ... 194

Figure 74. Environmental impacts assessed with the Egalitarian (E), Hierarchist (H) or Individualist (I) perspective. Scenarios thermal comfort and heating deprivation ... 194

Figure 75. Sensitivity of damages on human health and well-being to the well-being weighting factor (ration QALY/ year of poverty avoided. ... 196

Figure 76. Main Façade, copyright-MBHG-MRBC. Rear façade before and after retrofitting, provided by the owner ... 199

Figure 77. Project drawings: main façade, section, main and first floor plans, Source: owner ... 201

Figure 78. Boundaries of the assessment of the workforce involved. Own elaboration. ... 205

Figure 79 Stages included and boundaries of assessment ... 206

Figure 80. Damages to natural resources, natural environment in scenario 1 (endpoint results). ... 213

Figure 81. Damages to natural resources, natural environment in scenario 1 (endpoint results). ... 213

Figure 82. Detail of damages to human health in scenario 1 (endpoint results). ... 213

Figure 83. Detail of years of fair employment generated in the no-retrofitting scenario (left), retrofitting scenario (middle) and the difference of both (right bar). ... 215

Figure 84. Fuel poverty diagram, scenario 1 before and after retrofit ... 216

Figure 85. Detail of the costs for the State, with and without considering the financial incentives ... 216

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Figure 87. Aggregated endpoint LCSA results, maison Hankar scenario 1 ... 217 Figure 88. Endpoint LCSA results of scenario 1A. Detail of impacts on health and well-being (∆retrofit-no retrofit)

... 218 Figure 89. Endpoint LCSA results of scenario 1A. Detail of impacts on the prosperity of society (∆retrofit-no retrofit)

... 218 Figure 90. Scenario comparison of damages to natural resources and natural environment (endpoint results). ... 219 Figure 91. Scenario comparison of damages to human health (endpoint results in DALY). ... 220 Figure 92. Detail of damages to health in scenarios 1,1bis and 1ter ... 221

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List of abbreviations

AHC: After housing costs (income) BFP: Federal planning bureau

CEN: European Committee for Standardization DALY: Disability-adjusted life years

GBD: Global burden of disease

IBGE: Institut Bruxellois pour la gestion de l’environnement LC: Life cycle (methodologies)

LCA: (Environmental) Life cycle assessment LCC: Life cycle costing

LCI: Life cycle inventory assessment LCIA: Life cycle impact assessment LCSA: Life cycle sustainability assessment NPC: Net present value

PEB: Building energy performance

Q25, Q50, Q75: Quartile of population regarding income QALY: Quality-adjusted life years

RBC: Brussels-Capital Region

s-LCA, SLCA, social LCA: Social life cycle assessment

SPF: Public finance Belgian service (Service public de finances) SHDB: Social Hotspots Database

SLRB: Social housing society for the Brussels-Capital region YLL: Years of life lost

VATC: VAT taxes comprised

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Introduction

Justification

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INTRODUCTION

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Introduction and justification

Large-scale retrofitting processes are taking place throughout Europe to update housing to current requirements. The majority of the stock, which was built before 1970, is in bad condition and lacks sufficient insulation. As part of its quest for “smart, sustainable and inclusive growth” (European Commission 2014), Europe has set targets for employment, energy and climate, and combating poverty by 2020. The retrofitting of housing helps towards reaching these targets through reducing the energy consumption, creating jobs and reducing the burden of energy bills on households.

Improving the energy performance of buildings and the resulting CO2 reduction

have so far been addressed and prioritized by the EPBD directive (European Union 2010), and this has been transposed to national regulations and programs. These have been developed for new buildings and their application has been extended to retrofitting. But the latter is more complex; retrofitting is not as a catalogue of energy efficient measures since these are interrelated, often constricted by multiple factors of the existing building. To name an example, the implementation of some measures such as improving the air-tightness might worsen the indoor air quality if adequate ventilation is not ensured. Energy efficiency is often analyzed from the private perspective of investment and savings (European Commission 2012a), whereas the joint benefits of retrofitting are not considered (Ferreira and Almeida 2015). These are presumed or acknowledged, but often considered side-effects rather than main objectives.

Retrofitting contributes significantly to employment due to the labor intensity of the works, although this contribution is not easy to quantify. Most of the jobs created in the new sectors related to energy efficiency are assumed by other sectors with slowed activity, and the increased retrofitting demand might imply less new constructions. On the other hand, the construction sector must deal with the issue s of illegal workforce and social dumping, which introduce a bias on the estimation of the actual benefits of the increased turnover.

The risk of poverty or social exclusion is related to income poverty, living in jobless households, or experiencing material deprivation. The concept of fuel (or energy)

poverty encompasses the indicators of material deprivation related to housing. It is

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INTRODUCTION

4

Social Committee 2013, Tirado Herrero et al. 2012). This target seems though not addressed yet by European or national programs. The real situation of households in relation to the conditions of the housing stock is far to be known in the region of Brussels, and no specific measures seem to have been taken to improve the living conditions of vulnerable households other than subsidizing energy or social housing, more difficult to sustain in the long run.

One major barrier to undertaking retrofitting is the high investment costs that discourage private owners, particularly when owners rent their properties as they do not benefit from energy savings (known as the tenant-owner dilemma). Davies and Oreszczyn (2012) highlight the risk of increasing social inequalities, since low-income households cannot afford to renovate their homes. Most governments have implemented measures to boost retrofitting which include financial incentives, mandatory requirements and associated penalties. The financial resources of countries are limited and it seems that the trend is to decrease. Allowance, subsidy and social security systems risk of being the first to undergo the repercussions. It seems more suitable to deal with the population in hardship through mechanisms that enable their development and social inclusion with a lower dependency on social allowances. And this is perfectly applicable in the problem of housing and in housing retrofit. For these reasons, the measures to encourage retrofitting must be optimized, to better invest in order to obtain better results. But the optimization of measures is challenging: the housing stock is diverse in typology, household composition and income. Moreover, the interests of the different actors involved might differ, and these inter-related targets might lead to contradictions. For example, potential for

CO2 reductions seems to be higher in the homes of wealthy households (which

consume more), but there is more potential to improve health in poorer homes (Wilkinson et al. 2009).

In large-scale retrofitting processes, all these factors are to be taken into account in a cross-cutting manner, but this is not easy. Each one is tackled by different disciplines of research, professional, or even political. Industries are in the forefront of innovation and the necessary societal discussion on the urban process of retrofitting seems rather to be reduced to technological solutions. Decision-makers need tools that enable to undertake this discussion and to identify priorities, be it certain housing typologies, household profiles or a combination of both (Sánchez-Guevara et al. 2014).

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INTRODUCTION

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Life cycle methodologies seem an appropriate methodological framework for this research, since the recently developed concept of life cycle sustainability assessment (henceforth “LCSA”) integrates environmental, social and economic aspects, although the methodology is not yet ready to be applied (Tritthart and Hamans 2013, UNEP/SETAC 2011). Further development is needed to adapt the existing methodologies to guide decision making related to retrofitting in a given territory, but the potential seems great: the methodological bases of life cycle methodologies are harmonized and widely used to assess environmental impacts. It seems thus appropriate trying to develop the tailored tool based on existing well -accepted methodologies rather than creating new ones.

On the other hand, it might be questioned whether the methodological choice might limit the approach. It must be highlighted though that the life cycle methodologies encompass different methods of assessment developed in their corresponding research fields (climate change, health, biodiversity, etc.) The methodological approach of life cycle methodologies must be understood as the

framework that enables harmonizing the basis for comparison and the presentation

of results rather than an assessment method. This is actually the case in environmental life cycle assessment and is also the approach in this research. Life cycle sustainability assessment is the methodological framework to develop the tool presented in this work. By matching methods of assessment of a very different nature, this tool provides guidance on policy making related to large scale retrofitting processes.

The analysis at the territorial scale cannot be made on a case-by case basis, but on models that represent the diversity of the stock. This implies certain generalizations given the diversity of households, housing and user behavior. The tool of assessment proposed, as well as the applications to case studies, might be considered as screening analyses. Each of the aspects analyzed is complex and particular studies must address them exhaustively. Far from being exclusive, this tool can be considered as a basis to be completed by further developments. Rather than aiming at the exhaustive study of each of the concerns identified, this PhD thesis paper provides a more complete overview on the contribution of retrofitting the housing stock to sustainable development.

The case of Brussels-Capital region is particularly addressed in this PhD. This is motivated by the research framework but also for the particular characteristics of this region, presented in Chapter 1.

Hypothesis

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INTRODUCTION

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Main & partial objectives

The main objective of this work is to develop a tool on the basis of the life cycle sustainability assessment (LCSA) methodology to assist decision making in the process of retrofitting the housing stock of Brussels-Capital towards more sustainable development.

Therefore, some partial objectives have been pursued, being each of these a relevant result of the research:

 Selection and development of models to assess socio-economic impacts related to the retrofitting of housing.

 Identification of the representative housing typologies and scenarios wherein the retrofitting are undertaken.

 Assessment of part of the housing stock in order to provide clues about the potential use of the tool by policy-makers.

Research framework

This research started in the framework of the LCBUILD project, funded by the Brussels Capital Region through the INNOVIRIS Strategic Platform Brussels Retrofit XL for the period 2013-2014. This platform addressed extending the knowledge base on building retrofitting actions, stimulating renovation initiatives and mapping retrofitting opportunities for the Brussels context. As well as the environmental evaluation of some retrofitting concepts, LCBUILD project addressed the socioeconomic assessment from a life cycle perspective. The objectives included verifying the feasibility of social life cycle assessment in retrofitting activities, and improving the current existing methodology in order to adapt it to the context of housing retrofitting.

This research has been supported and funded for the period 2015-2016 by the 4MAT recycling & environment research team. Their expertise in environmental life cycle assessment has been the basis to develop the socioeconomic part of the life cycle methodology, to name only one of their multiple contributions in the scientific and personal domains.

Research methodology

 Analysis of the context

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INTRODUCTION

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The available tools and methodologies that address the assessment of sustainability or aspects of sustainability are reviewed, with a particular focus on the methodologies based on a life cycle thinking approach, as well as on the tools specifically developed for buildings. The review aims at identifying existing methods suitable to address aspects relevant in the particular context.

 Methodology proposal

After the review of existing tools and methods of assessment, a tool based on the life cycle sustainability assessment methodology adapted to the intended application is defined. This includes the adaptation of the methodology to the specific stakeholders, stages and particularities of retrofitting. The tool of assessment encompasses a set of environmental and socioeconomic assessment methods specifically defined. The final proposal results from the adjustment after verifying the feasibility of the application.

 LCSA of case studies in the scheduled scenarios

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1. Analysis of the context

Regional prospective

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ANALYSIS OF THE CONTEXT

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Introduction

This research deals with the large-scale retrofitting process that is currently taking place in Europe, but focuses on the particular case of Brussels-Capital. Although most of the concerns are similar to other European cities, it seems that the local particularities must be specifically addressed; even more so in the case of Brussels, recognized to be unique. The ambiguous term local is deliberately used: the boundaries of the specific context in terms of housing retrofitting are diffused since these might differ from the geopolitical limits depending on the addressed aspect . For instance, environmental targets are defined at the European level, the consequent regulations at the national level, and the subsidy management depends on the regional government.

Brussels-Capital is one of the three Belgian regions, also considered Capital of Europe in institutional terms. Brussels is a city-region, composed by 19 districts or communes (Figure 1), characterized by the diversity of its population regarding origin, language, culture, socioeconomic status, etc. This diversity results from the significant immigration across decades on the one hand but also from the internationalization derived from the settlement of European institutions. Regional competences such as “housing”, deal with a complex situation marked by the multiple administration levels (district, Region, State) that may overlap regarding retrofitting (regulations, subsidies) and that are economically interrelated (tax income and compensation mechanisms).

Figure 1. The region of Brussels-Capital

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difficulties to deal with social needs (e.g. the lacking social housing stock, but also the social revenues).

The fact that the diversity and complexity of Brussels may hinder undertaking integrated measures, added to the current limitation of resources might risk of disregarding the impoverished population. Moreover, about the half of the tax income received by the region is some way related to the real estate market (Corijn and Vloeberghs 2009). It seems suitable to provide tools that clarify the overview on complex processes such as urban renovation. This chapter analyzes the aspects of the context that are someway related to retrofitting, to housing and to the construction sector, in order to understand the research framework.

1.1. Regional prospective

The region of Brussels must deal with several challenges for the years coming, identified both by the regional government but also in the framework of regional studies. Some of these main challenges are listed below. Some of the challenges are common to other European cities and some are specific.

 The government of Brussels-Capital Region adopted in December 2013 the Regional plan for sustainable development (Plan Régional de Dévéloppement Durable or PRDD) (2013) that addressed five main challenges for Brussels: demographic increase, education and employment, social cohesion, internationalization, and the transversal challenges of mobility and integrated territory management.

 Jean de Salle1_{highlighted as well the need for the regional government to address}

social insertion, the decoupling between growth and employment, the concurrency and economic competition of emergent countries, the climate change constraints, resource decrease, energy price increase, international migrations, etc. (Corijn et al. 2013)

 In this line, the FGTB-ABVV2_{highlighted three main challenges. One is the right to}

the city as the right to live where working, in good conditions and with accessible services, and this right is threatened by the real estate speculation, the under-funding of social housing, and the demographic explosion. The second is about the economic transition towards and integrated, sustainable and endogenous development. The last is the situation of precariousness of jobs due to subcontracted services, offshoring, and the massive increase of unemployment that deteriorates working conditions (FGTB Bruxelles 2013).

Multiple relationships exist between all these concerns and the retrofitting of housing, though some are not obvious. The links are explored and analyzed in this chapter, grouped by the following topics:

1_{President of the « Commission régionale du développement, Bruxelles »}

2_{Fédération Générale du Travail de Belgique. Symposium 7 mai 2013 « Richesse et pauvreté à Bruxelles.}

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13  Population (1.2)

 Employment (1.3)

 Environment & energy (1.4)

 Retrofitting the housing stock (1.5)

1.2. Population

1.2.1. Demography

The region undergoes a continuous demographic increase (Figure 2), by 1 % more in 2014 than in 2013, reaching 1.175 M population by the first of January 2015 (“Accroissement population” in Figure 2). This is mainly due to an important international immigration by + 16,106 increase of residents, 37 % more in 2014 than 2013 (“Solde migratoire externe” in Figure 2), but also to the high birth rate mostly within the main immigration groups, and to the mortality rate decrease after 2000 (“Solde naturel” in the Figure). Population is getting younger (37.4 years old average) due to the age of newcomers (22 to 33 years old), and to the birth rate, despite the significant internal emigration (36,795 people left Brussels versus the 23,375 that came in from the other Belgian regions). The internal emigration mainly concerns families with young children that, as a consequence of the increasing prices of real estate, move from the city to periphery in order to own a property with more space and more green (Hermia 2015). The balance of this internal emigration and immigration is represented in Figure 2 as “Solde migratoire interne”.

Figure 2. Population increase in Brussels 1991-2014 and prospective 2015-2060. Source RN-DGS, BFP

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retrofitting seems a good strategy to provide the region with appropriate housing (Corijn and Vloeberghs 2009), (Corijn et al. 2013). The transformation of unoccupied office buildings into housing is currently a common practice in the Region, but out of the boundaries of this work, which only focus the renovation of housing wi thout change of use.

The difficulties to afford retrofitting works and the speculation with renovated assets may imply the increase of social inequalities and the “exodus” to periphery. Since public authorities might prioritize middle class families to stay in the region (since these are supposed to activate the economy the most), the most disadvantaged population might be disregarded. Indeed, the latter might benefit the most of retrofitting their homes.

1.2.2. Distribution of wealth

The international framework is defined by the slowdown of the economic increase after the recession (3% in 2013). In the euro zone, the recession was about 0.4% on average in 2013 and the European Commission had foreseen (in February 2014) a positive increase in 2014 of 1.2%. After the decrease of the Belgian economy (- 0.1% in 2012), and an almost zero increase in 2013 (0.3 %) and 2014 (1.1 %), expecting more significant increases after 2015. The main sector affected was the industries related to asset production (and services associated), reduced in 2012 due to the lower external demand mainly from Germany, Holland and France (Bureau fédéral du Plan et al. 2013). The population is affected by this economic context.

“While GDP [gross domestic product] and wealth have continued to increase overall, inequality has risen in Europe – as in other developed countries – since the mid-1980s (…) The crisis is expected to have led to a further rise in inequality and to have constrained redistributive systems even more. The issue of distributional fairness, in turn, increases the difficulty of addressing the challenges faced by Europe's economies” (European Commission 2014).

The last sentence refers to the European target to “lifting at least 20 million people out of the risk of poverty and social exclusion by 2020”, from which Europe has “drifted further away” due to the aggravated situation of poverty after the crisis and it is observed “no sign of rapid progress to remedy this situation” (European Commission 2014).

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income inequality is often defended to be necessary in a growing economy, it s eems that less inequality fosters more growth (Standard & Poor’s 2014).

Table 1. Taxable average and median income, Belgium and big cities (2012 income, 2013 declarations)3_.

Adapted from DGS-Statistics Belgium. Average income per fiscal declaration (a)

Median income per fiscal declaration (b) Difference between (a)-(b) Average income per capita Brussels-Capital Region 26,463 € 18,526 € 42.8 % 13,312 € Antwerpen 26,653 € 20,763 € 28.4 % 14,834 € Gent 29,252 € 22,527 € 29.8 % 17,189 € Liège 23,898 € 18,049 € 32.4 % 13,921 € Charleroi 22,630 € 17,875 € 26.6% 12,497 € Belgium 30,012 € 22,610 € 32.7 % 16,651 €

1.2.3. Poverty and housing costs

In the European context, the risk of poverty or social exclusion is related to income poverty, living in jobless households, or experiencing material deprivation.

 Income poverty

The term poverty is often used to refer to the concept of income or monetary poverty. Indeed, the income is the reference indicator used for social housing accessibility or to provide subsidies for retrofitting. The at-risk-of-poverty threshold is commonly set at 60 % of the national median equivalized disposable income after social transfers. In European statistics (EU-SILC survey) this is often expressed in purchasing power standards (PPS) in order to take account of the differences in the cost of living across countries. In Belgium, this threshold corresponded to 13,023 €/year or 1,085 €/month for a single person, or 2,279 € for a couple with two children in 2014. The report 2015 on regional poverty (Observatoire de la Santé et du Social de Bruxelles-Capitale 2015) highlighted that in 2014 (based on 2013 income), the risk of poverty in Brussels (38.4 %) was much higher than in Flanders (15.3 %) or Wallonia (26.3 %). The 23.5 % of the population in active age (15‐64) depended on a social allowance.

 Material deprivation

Material deprivation is defined by the “inability to afford some items considered by most people to be desirable or even necessary to lead an adequate life” (EU-SILC). Some examples are the inability to afford unexpected expenses, eating meat or proteins regularly, going on holiday once a year, etc., and some other directly related to housing, as inability to pay their rent, mortgage or utility bills or inability to keep their home adequately warm.

Housing can lead to material deprivation (thus to poverty or social exclusion) to the extent that the associated costs required to ensure decent living conditions are available without limiting the income disposable for other needs. This is the case of

3_{The sources written in French use the dot as thousand separation and comma as decimal mark, in opposition to}

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the costs of rent or loans (including the maintenance, repair, and renovation), the cost of utility bills, property taxes, etc. The main source for the compilation of statistics on income, social inclusion and living conditions is the EU-Statistics on Income and Living Conditions (EU-SILC). Some of the housing-related indicators used to characterize households are presented in Table 2, but these are only available at the national level. Housing costs are considered by EUROSTAT as an overburden when these represent more than 40 % of the household disposable income. Expenditure in utility bills exceeding the 10 % of income is often considered to indicate fuel poverty, but this concept is more complex and needs further explanation (1.2.4).

Based on the Survey on Household budget data, 34.8 % of the average household expenses are related to housing in Belgium (Figure 4), 29 % for the housing itself (rent or estimation for the owners, the utility bills, repair and maintenance), and 5 .8 % for furnishing and regular maintenance. Rental prices in Brussels are increasing: by 45% between 2000 and 2011 (4 % between 2011 and 2012), whereas health index only by 25 % (3.2 % between 2011 and 2012). In the case of lone parents, the rent expenditure amounts to the 40 % average (Observatoire de la Santé et du Social de Bruxelles-Capitale 2015).

Figure 3. Average household expenditure. Source: Household budget survey, 2014 SPF Economie.

The detailed analysis per income level shows that income is the main factor related to the level of expenses but also to the structure of these. Figure 4 shows that housing related costs, as well as costs related to water, electricity, gas and other fuels linearly increase with income. This can be easily explained by the fact that wealthier households use to live in bigger, under-occupied housing, whereas the poorest use to occupy smaller, over occupied dwelling, but also by the fact that households in hardship self-restrict their heating in order to reduce the energy bills.

13.10% 2.00% 4.60% 29.00% 5.80% 4.60% 11.90% 3.00% 8.20% 0.50% _6.50% 10.80%

Food and non-alcoholic beverages Alcoholic beverages, tobacco and narcotics Clothing and footwear

Housing, water, electricity, gas and other fuels

Furnishings, household equipment and routine household maintenance Health

Transport Communications Recreation and culture Education

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Figure 4. Average housing-related costs (left) and expenditure in utility bills (right), both per household and income quartile in Brussels. Own elaboration based on the Household budget survey 2014 (SPF Economie).

In 2014, the (private) average household in Brussels allocated 4.5 % of their income to heating, lighting and domestic water costs, which amounted to the 8.3 % in the case of the poorest households (Figure 5). It must be noticed that the average expenditure is higher than many social allowances. The report on energy appraisal of

Brussels-Capital 20114_{indicated that the 53 % of energy bills of the average}

household corresponds to main heating.

Average expenditure per household and year (€) in Brussels-Capital Region 2014 (Q=quartile)

Regional average

Income < Q25 (first quartile) Bills Income Bills Income (€) (€) (€) (€) Water, electricity, gas, and other fuels 1,48 8 33,042 1,063 12,806

Figure 5. Expenditure per household and year in heating, lighting and domestic water per income quartile in Brussels, 2010. Own elaboration based on the Household budget survey (SPF Economie).

1.2.4. Fuel poverty

According to the European Economic and Social Committee, fuel (or energy) poverty is recognized as one serious form of poverty and social exclusion, “affecting at least 10 % of Europeans”. Although the definition might vary depending on the country, fuel poverty can be defined as the “difficulty or inability to ensure adequate heating in the dwelling and to have access to other essential energy services at a reasonable price" (European Economic and Social Committee 2013). Fuel poverty is directly related to three factors:

 price of energy,  household income,

4_{Bilan énergétique de la région de Bruxelles-capitale 2011 bilan énergie Région Bruxelles Capitale 2011 (Institut}

de conseil et d’études en développement durable asbl June 2013)

1488 1063 1280 1661 1945 611 444 527 661 812 0 € 500 € 1,000 € 1,500 € 2,000 € 2,500 €

Utility bills gas 10208 6919 8694 11283 13906 33,042 12,806 21,064 32,661 65,414 0 € 10,000 € 20,000 € 30,000 € 40,000 € 50,000 € 60,000 € 70,000 €

Total housing costs Average income

1488 1063 1280 1661 1945 611 444 527 661 812 0 € 500 € 1,000 € 1,500 € 2,000 € 2,500 €

Utility bills gas 10208 6919 8694 11283 13906 33,042 12,806 21,064 32,661 65,414 0 € 10,000 € 20,000 € 30,000 € 40,000 € 50,000 € 60,000 € 70,000 €

MARIA ISABEL TOUCEDA GOMEZ FRAMEWORK APPLIED TO HOUSING RETROFITTING LIFE CYCLE SUSTAINABILITY ASSESSMENT

IMPLEMENTATION OF SOCIOECONOMIC CRITERIA IN A

LIFE CYCLE SUSTAINABILITY ASSESSMENT

FRAMEWORK APPLIED TO HOUSING RETROFITTING

THE BRUSSELS-CAPITAL REGION CASE STUDY

MARIA ISABEL TOUCEDA GOMEZ

DOCTORAL THESIS

IMPLEMENTATION OF SOCIOECONOMIC CRITERIA IN

A LIFE CYCLE SUSTAINABILITY ASSESSMENT

FRAMEWORK APPLIED TO HOUSING RETROFITTING:

THE BRUSSELS-CAPITAL REGION CASE STUDY

María Isabel Touceda Gómez

Doctoral thesis

DOCTORAT À L’ECOLE POLYTECHNIQUE DE BRUXELLES EN ART DE

BATIR ET URBANISME. UNIVERSITE LIBRE DE BRUXELLES

4MAT RECYCLING & ENVIRONMENT

Acknowledgements

Abstract (English)

Abstract (Français)

Abstract (Español)

Scientific impacts

Publication in indexed journals

International conferences

Table of contents

Tables

Figures

List of abbreviations

Introduction

Justification

Introduction and justification

Hypothesis

Main & partial objectives

Research framework

Research methodology

1. Analysis of the context

Regional prospective

Introduction

1.1. Regional prospective

1.2. Population

1.2.1. Demography

1.2.2. Distribution of wealth

1.2.3. Poverty and housing costs

1.2.4. Fuel poverty