Session 1 - Montefiore

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agglomeration), constituted the “alternating migrants area.” Remaining areas were regrouped under the “other areas” term and represent rural and less dense areas located far away from main city centres as well as secondary centres. Urban sprawl is linked to the suburbs and the alternating migrants areas (Brück, 2002). Finally note that the influence of neighbouring countries and regions was not taken into account in Van der Haegen and Van Hecke’s classification. Figure 1: Urban type classification (Sporck et al., 1985; Van der Haegen et al., 1996) The Method A quantitative method was developed to assess the energy efficiency of home-to-work and home-to- school trips. The complete methodology and data set are presented in detail by Marique and Reiter (2012a). This method uses empirical data from Belgium’s national census, which is carried out every ten years. We used one-day travel diary data collected from male and female heads of households from the two last surveys, respectively carried out in 1991 and 2001. For these households, information about demographics, socioeconomic status, car ownership, travel distances, the main mode of transportation used and the number of days worked per week and per person is available at the individual (desegregated) scale. These data are available for both home-to-work and home-to- school trips. Marique AF, Dujardin S, Teller J & Reiter S (In press) Urban sprawl, commuting and travel energy consumption. Proceedings of the Institution of Civil Engineers – Energy. 7
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. To build a locally specific index that is tailored to suburban areas, in addition to Boussauw and Witlox (2009) data, we took into account local characteristics of the public transport network in suburban areas (as significant differences exist between cities and suburban neighbourhoods), the type of vehicles used and the number of working days of the population in the neighbourhood. In this paper, we applied this method to the entire regional territory to investigate the relationships between the spatial structure of the Walloon region of Belgium and the transport energy consumption for home-to-work and home-to- school trips. Three indexes are derived from this method. The energy performance index (expressed in kWh/travel.person) for a territorial unit represents the mean energy consumption for home-to- work/home-to-school trips for one worker/student living within a particular census block (district). This index takes into account the distances travelled, the means of transport used and their relative consumption rates, expressed by equation (1). In the equation, i represents the territorial unit; m the mean of transport used (diesel car, petrol car, train, bus, bike, on foot); Dmi the total distance travelled by the means of transport m in the district i for home-to-work (or home-to-school) trips; fm the consumption factor attributed to means of transport m and Ti the number of workers (or students) in the territorial unit i. (1) Energy performance index (i) = (∑m Dmi * fm) /Ti Consumption factors fm were calculated by Marique and Reiter (2012a) on the basis of regional and local data. Consumption factors are worth 0,56 kWh/person.km for a diesel car, 0,61 kWh/person.km for a petrol car, 0,45 kWh/person.km for a bus, and 0 for non-motorised means of transportation because these do not consume any energy. The consumption factor for a train was recalculated, following Teller et al. (2010). It depends on the production of electricity as trains in Belgium are electric and was calculated by dividing the total energy used to operate trains in Belgium by the total number Marique AF, Dujardin S, Teller J & Reiter S (In press) Urban sprawl, commuting and travel energy consumption. Proceedings of the Institution of Civil Engineers – Energy. 8
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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
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4.1.2 Natural and protected areas T
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Box 7 (cont.) The impacts of urban
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the societal cost of asthma has bee
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Box 8 Effects of residential areas
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5.2 The European spatial developmen
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European regional forces generating
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Box 9 (cont.) Responses to urban sp
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urban development plan and focused
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Box 10 (cont.) Responses to urban s
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Annex: Data and methodological appr
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C Assessing urban sprawl at the Eur
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References and further reading Ambi
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European Commission, 1990. Green Pa
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European Environment Agency Urban s
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Appendix A.2 78
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Section 2 presents a brief review o
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intervention in these specific type
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electricity as trains in Belgium ar
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The majority of those districts are
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which were calculated with the same
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The last type of sensitivity analys
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(INSEE) in France, the Office for N
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Kints C. La rénovation énergétiq
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A Method to Evaluate the Energy Con
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application in many other suburban
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Our classification of buildings cur
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to work and the mode of transportat
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energy consumption of a neighborhoo
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Page 112 and 113: measurements because of high variat
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Page 116 and 117: FIGURE CAPTIONS AND TABLE TITLES Fi
Page 118 and 119: PLEA2012 - 28th Conference, Opportu
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Page 128 and 129: year are 34.9 °C and -9,1°C. The
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Page 134 and 135: uilding” approach. A large amount
Page 136 and 137: C. Comparison of our classification
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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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Page 161 and 162: Mean modal share (train) 14,0% 12,7
Page 163 and 164: Figure 4: Annual transport energy c
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Page 167 and 168: or commercial purposes. “Type-pro
Page 169 and 170: Beevers SD and Carslaw DC (2005) Th
Page 171 and 172: Lavadinho S and Lensel B (2010) Imp
Page 175 and 176: NOTICE The submitted manuscript has
Page 177 and 178: Using ZEB design goals takes us out
Page 179 and 180: Boulder, Colorado has a solar acces
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Page 185 and 186: Net Zero Energy Emissions Building
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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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Status of Natural Gas Combined Cycl
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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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