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An approach for estimating the carbon emissions associated with office lighting with a daylight contribution

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  • Jenkins, David
  • Newborough, Marcus

Abstract

A method is proposed for estimating the electricity consumption (and associated carbon emissions) of a defined electrical-lighting configuration in an office building, accounting for the daylight contribution from windows and rooflights. Heat gains due to lighting for an average day in each month may be used to aid assessments of the effect of lighting systems on the cooling load, known to be high for office environments. For a typical 6-storey office building, annual energy savings for lighting of 56-62% and a reduction in CO2 emissions of nearly 3 tonnes are predicted by changing the lighting and daylighting specifications for a defined "2005" scenario to those of a low-carbon "2030" scenario. The associated reduction in peak lighting-load, and hence heat gain due to lighting, is 3Â W/m2.

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  • Jenkins, David & Newborough, Marcus, 2007. "An approach for estimating the carbon emissions associated with office lighting with a daylight contribution," Applied Energy, Elsevier, vol. 84(6), pages 608-622, June.
    • Handle: RePEc:eee:appene:v:84:y:2007:i:6:p:608-622
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    References listed on IDEAS

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    1. Betman, Ernesto, 2005. "Daylight calculations using constant luminance curves," Renewable Energy, Elsevier, vol. 30(2), pages 241-257.
    2. Greenup, P & Bell, J.M & Moore, I, 2001. "The importance of interior daylight distribution in buildings on overall energy performance," Renewable Energy, Elsevier, vol. 22(1), pages 45-52.
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    11. Mangkuto, R.A. & Wang, S. & Meerbeek, B.W. & Aries, M.B.C. & van Loenen, E.J., 2014. "Lighting performance and electrical energy consumption of a virtual window prototype," Applied Energy, Elsevier, vol. 135(C), pages 261-273.
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    13. Salata, Ferdinando & Golasi, Iacopo & di Salvatore, Maicol & de Lieto Vollaro, Andrea, 2016. "Energy and reliability optimization of a system that combines daylighting and artificial sources. A case study carried out in academic buildings," Applied Energy, Elsevier, vol. 169(C), pages 250-266.
    14. Carlucci, Salvatore & Causone, Francesco & De Rosa, Francesco & Pagliano, Lorenzo, 2015. "A review of indices for assessing visual comfort with a view to their use in optimization processes to support building integrated design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 1016-1033.
    15. Chel, Arvind & Tiwari, G.N. & Chandra, Avinash, 2009. "A model for estimation of daylight factor for skylight: An experimental validation using pyramid shape skylight over vault roof mud-house in New Delhi (India)," Applied Energy, Elsevier, vol. 86(11), pages 2507-2519, November.
    16. Evangelos-Nikolaos D. Madias & Lambros T. Doulos & Panagiotis A. Kontaxis & Frangiskos V. Topalis, 2022. "Multicriteria decision aid analysis for the optimum performance of an ambient light sensor: methodology and case study," Operational Research, Springer, vol. 22(2), pages 1333-1361, April.
    17. Chel, Arvind & Tiwari, G.N. & Singh, H.N., 2010. "A modified model for estimation of daylight factor for skylight integrated with dome roof structure of mud-house in New Delhi (India)," Applied Energy, Elsevier, vol. 87(10), pages 3037-3050, October.
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