Session 1 - Montefiore

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Our classification of buildings currently includes 72 types of houses. The most common type in the Walloon region is the single-family detached house built on a large plot (1000 m² (1,196 sq. yd) or more), with one ground floor and one story under the attic and with a surface area in the range of 120 m² (143 sq. yd) to 150 m² (179 sq. yd). This type of house, which has spread rapidly since the 1950s, still constitutes the ideal housing standard for many suburban households. Renovations and improvements made by home owners are then captured. Cadastre mentions, at the individual scale, the buildings that have undergone significant upgrades together with the year of construction and the year of the improvement work. The most common upgrades consist in adding insulation in the roof and replacing windows. Following Verbeek and Hens (2005), insulation of the roof is the most effective and durable measure for energy performance increase of Belgian households. As adding insulation in the slab and the walls is pretty rare (MRW 2007) retrofitted buildings energy consumption is improved but do not reach the actual standard. Using this classification, an energy consumption analysis is performed with thermal simulation software (Pleiades + Comfie) that includes a three-dimensional modeler and an interface for the input of thermal information (climate conditions, building materials, internal conditions and periods of use of the house). We modeled the energy required to heat each type of building as well as potential solar gains on vertical façades and roofs. The energy requirements for heating at the neighborhood scale were calculated by adding the results from the energy consumption analysis for each type of house according to their distribution in the neighborhood. Cooling requirements were neglected because they are minimal in Belgium. Indeed, the Belgian climate is a temperate climate. The mean temperature for the typical year used in the simulations is 10.3°C (50.5°F) and the cooling degree hours amount to 2548°Ch per year (if the considered inner temperature is 18°C (64.4°F)). Moreover, the overheating indicator defined in the European energy Performance of Building Directive (EP 2002) and transposed into the regional laws (MB 2008) has been calculated. It remains, for all the typical buildings considered in this analysis, under the threshold value proposed in the Directive (17500 Kh), which indicate that the overheating is not unacceptable and do not requires the installation of cooling system. In the worst of our cases, the overheating indicator raises 12274 Kh. AF. Marique and S. Reiter, 2012. A Method to evaluate the energy consumption of suburban neighborhoods, HVAC&R Research 18 (1-2), 88-99. 5
In addition, energy consumption relating to hot water, electrical appliance and cooking were added in the overall consumption to give a more complete image of energy consumption relating to buildings in suburban areas. As these items are not strictly linked to the characteristics of the buildings and the neighbourhoods but mainly depend upon the behavior of the households and the user habits, we considered in our calculation the regional average consumption (53 kWh/m².year; Kints 2008, see Figure 1, part a). We assumed that this value remains unchanged when the building envelope is improved. Life cycle assessments (LCA) for several types of houses were also performed using the software Equer, which was linked with the thermal simulation tool (Peuportier 2001). An LCA analyzes the environmental impacts of a given product, system or service over its entire life cycle by quantifying resource use and emissions to the environment (ISO 2006a, 2006b). The transportation component The approach developed to assess energy consumption in the transportation sector comprises two parts. The first one deals with home-to-work and home-to-school travels and is based on empirical data available at the census block level, the smallest geographical unit in which data are available in Belgium. These data come from the national censuses, which are carried out every ten years in Belgium. In this study, we used one-day travel diary data from male and female heads of households from the 1991 and 2001 censuses. For these households, information about demographics, socioeconomic status, car ownership, travel distances, main mode of transportation used and the number of working days per week and per worker is available at the census block level. These data were also used by Boussauw and Witlox (2009) to develop a commute- energy performance index for Flanders and the Brussels Capital Region of Belgium that investigates the link between spatial structure and energy consumption for home-to-work travel at the regional scale. Unlike our method, this index is not context-specific; it uses standardized values for all types of urban fabrics (urban, suburban and rural) and does not include home-to-school and home-to-station travel. To determine the total number of kilometers logged annually by various modes of transportation (car, bus, train, motorbike, bicycle or on foot) for home-to-work travel in each district, our method first combines the number of workers in a census block with the number of trips per week (determined by repartitioning the number of working days per week in the census block), the one-way distance from home AF. Marique and S. Reiter, 2012. A Method to evaluate the energy consumption of suburban neighborhoods, HVAC&R Research 18 (1-2), 88-99. 6
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Session 1 - Supervisors : Pierre De
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Session 3 - Supervisors : Damien Er
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Session 5 - Supervisors : Nathalie
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Session 11 - Supervisors : Damien E
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Session 13 - Supervisors : Nathalie
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Session 15 - Supervisors : Sigrid R
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Appendix A : Sigrid Reiter Appendix
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EEA Report No 10/2006 Urban sprawl
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Contents Contents Acknowledgements
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Urban sprawl — a European challen
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from city centres, while retaining
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growth as mentioned in Chapter 1. R
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The extent of urban sprawl in Europ
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esidential density, sprawl is equal
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The extent of urban sprawl in Europ
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3 The drivers of urban sprawl 3.1 C
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The drivers of urban sprawl Figure
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also clearly demonstrate city spraw
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Box 4 Portugal and Spain: threats t
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Box 5 (cont.) Map Development scena
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Box 6 (cont.) The drivers of urban
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emote locations and requiring trans
Page 50 and 51: 4.1.2 Natural and protected areas T
Page 52 and 53: Box 7 (cont.) The impacts of urban
Page 54 and 55: the societal cost of asthma has bee
Page 56 and 57: Box 8 Effects of residential areas
Page 58 and 59: 5.2 The European spatial developmen
Page 60 and 61: European regional forces generating
Page 62 and 63: Box 9 (cont.) Responses to urban sp
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Page 66 and 67: Box 10 (cont.) Responses to urban s
Page 68 and 69: Annex: Data and methodological appr
Page 70 and 71: C Assessing urban sprawl at the Eur
Page 72 and 73: References and further reading Ambi
Page 74 and 75: European Commission, 1990. Green Pa
Page 76 and 77: European Environment Agency Urban s
Page 78 and 79: Appendix A.2 78
Page 80 and 81: Section 2 presents a brief review o
Page 82 and 83: intervention in these specific type
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Page 86 and 87: The majority of those districts are
Page 88 and 89: which were calculated with the same
Page 90 and 91: The last type of sensitivity analys
Page 92 and 93: (INSEE) in France, the Office for N
Page 94 and 95: Kints C. La rénovation énergétiq
Page 96 and 97: A Method to Evaluate the Energy Con
Page 98 and 99: application in many other suburban
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Page 104 and 105: energy consumption of a neighborhoo
Page 106 and 107: transportation represents 11.8% to
Page 108 and 109: most important. Insulating only the
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Page 114 and 115: Hilderson, W., E. Mlecnik and J. Cr
Page 116 and 117: FIGURE CAPTIONS AND TABLE TITLES Fi
Page 118 and 119: PLEA2012 - 28th Conference, Opportu
Page 126 and 127: ENERGY REQUIREMENTS AND SOLAR AVAIL
Page 128 and 129: year are 34.9 °C and -9,1°C. The
Page 130 and 131: The new built density of the neighb
Page 132 and 133: Appendix A.6 132
Page 134 and 135: uilding” approach. A large amount
Page 136 and 137: C. Comparison of our classification
Page 138: In fact, as cavity walls became wid
Page 141 and 142: METHODS, TOOLS, AND SOFTWARE Keywor
Page 143 and 144: approaches. These methodologies hav
Page 145 and 146: travel through the urban area of Li
Page 147 and 148: METHODS, TOOLS, AND SOFTWARE Figure
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Appendix A.8 151
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consumption is rarely taken into ac
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interdependences between urban stru
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These data were also used by Boussa
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and energy consumption in the resid
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Mean modal share (train) 14,0% 12,7
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Figure 4: Annual transport energy c
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23,0%, even if the annual energy co
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or commercial purposes. “Type-pro
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Beevers SD and Carslaw DC (2005) Th
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Lavadinho S and Lensel B (2010) Imp
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Appendix A.9 173
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NOTICE The submitted manuscript has
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Using ZEB design goals takes us out
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Boulder, Colorado has a solar acces
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(Mermoud 1996) to calculate the exp
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energy is used. TDVs have been deve
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Net Zero Energy Emissions Building
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combined with selecting a favorable
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Appendix A.10 189
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Life Cycle Assessment of Buildings
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PRe, SimaPro., 2000. Life Cycle Ass
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Appendix A.11 209
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396 buildings [17,26]. This review
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398 2.2. Embodied energy and carbon
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400 using photovoltaic panels will
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Appendix A.12 217
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assumptions, the indicators (Embodi
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Table 3 Distribution of the steel w
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the three case studies exhibit a st
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PLEA 2011 - 27 th Conference on Pas
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Appendix B : Pierre Dewallef Append
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When writing your presentation, you
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Status of Solar Tower Power Plant t
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Appendix B.3 237
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Status of biomass combustion power
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Appendix B.5 243
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Status of ocean thermal energy conv
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Appendix B.7 249
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Status of Natural Gas Combined Cycl
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Appendix B.9 255
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Status of Integrated coal Gazeifica
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Appendix B.11 261
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Status of Carbon Capture and Storag
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Appendix B.13 267
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Status of Carbon Capture and Storag
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Session 1 - Montefiore

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