IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v46y2012icp359-369.html
   My bibliography  Save this article

Modelling the impact of urban form on household energy demand and related CO2 emissions in the Greater Dublin Region

Author

Listed:
  • Liu, Xiaochen
  • Sweeney, John

Abstract

This study aims to investigate the relationship between household space heating energy use and urban form (land use characteristics) for the Greater Dublin Region. The geographical distributions of household energy use are evaluated at the Enumeration Districts (ED) level based on the building thermal balance model. Moreover, it estimates the impact of possible factors on the household space heating consumption. Results illustrate that the distribution profile of dwellings is a significant factor related to overall heating energy demand and individual dwelling energy consumption for space heating. Residents living in compact dwellings with small floor areas consume less energy for space heating than residents living in dwellings with big floor areas. Moreover, domestic heating energy demand per household was also estimated for two extreme urban development scenarios: the compact city scenario and the dispersed scenario. The results illustrate that the compact city scenario is likely to decrease the domestic heating energy consumption per household by 16.2% compared with the dispersed city scenario. Correspondingly, the energy-related CO2 emissions could be significantly decreased by compact city scenario compared with the dispersed city scenario.

Suggested Citation

  • Liu, Xiaochen & Sweeney, John, 2012. "Modelling the impact of urban form on household energy demand and related CO2 emissions in the Greater Dublin Region," Energy Policy, Elsevier, vol. 46(C), pages 359-369.
  • Handle: RePEc:eee:enepol:v:46:y:2012:i:c:p:359-369
    DOI: 10.1016/j.enpol.2012.03.070
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421512002753
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2012.03.070?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sumita Ghosh & Robert Vale & Brenda Vale, 2006. "Domestic energy sustainability of different urban residential patterns: a New Zealand approach," International Journal of Sustainable Development, Inderscience Enterprises Ltd, vol. 9(1), pages 16-37.
    2. Vine, Edward L. & Misuriello, Harry & Hopkins, Mary Ellen, 1994. "A research agenda for demand-side management impact measurement," Energy, Elsevier, vol. 19(11), pages 1103-1111.
    3. John Randolph, 2008. "Comment on Reid Ewing and Fang Rong's “The impact of urban form on U.S. residential energy use”," Housing Policy Debate, Taylor & Francis Journals, vol. 19(1), pages 45-52, January.
    4. Erling Holden & Ingrid T. Norland, 2005. "Three Challenges for the Compact City as a Sustainable Urban Form: Household Consumption of Energy and Transport in Eight Residential Areas in the Greater Oslo Region," Urban Studies, Urban Studies Journal Limited, vol. 42(12), pages 2145-2166, November.
    5. Haas, Reinhard & Biermayr, Peter, 2000. "The rebound effect for space heating Empirical evidence from Austria," Energy Policy, Elsevier, vol. 28(6-7), pages 403-410, June.
    6. Reid Ewing & Fang Rong, 2008. "The impact of urban form on U.S. residential energy use," Housing Policy Debate, Taylor & Francis Journals, vol. 19(1), pages 1-30, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Parshall, Lily & Gurney, Kevin & Hammer, Stephen A. & Mendoza, Daniel & Zhou, Yuyu & Geethakumar, Sarath, 2010. "Modeling energy consumption and CO2 emissions at the urban scale: Methodological challenges and insights from the United States," Energy Policy, Elsevier, vol. 38(9), pages 4765-4782, September.
    2. Silva, Mafalda C. & Horta, Isabel M. & Leal, Vítor & Oliveira, Vítor, 2017. "A spatially-explicit methodological framework based on neural networks to assess the effect of urban form on energy demand," Applied Energy, Elsevier, vol. 202(C), pages 386-398.
    3. Huang, Wen-Hsiu, 2015. "The determinants of household electricity consumption in Taiwan: Evidence from quantile regression," Energy, Elsevier, vol. 87(C), pages 120-133.
    4. Ivan Muñiz & Andrés Dominguez, 2020. "The Impact of Urban Form and Spatial Structure on per Capita Carbon Footprint in U.S. Larger Metropolitan Areas," Sustainability, MDPI, vol. 12(1), pages 1-19, January.
    5. Ala-Mantila, Sanna & Heinonen, Jukka & Junnila, Seppo, 2014. "Relationship between urbanization, direct and indirect greenhouse gas emissions, and expenditures: A multivariate analysis," Ecological Economics, Elsevier, vol. 104(C), pages 129-139.
    6. Estiri, Hossein, 2015. "The indirect role of households in shaping US residential energy demand patterns," Energy Policy, Elsevier, vol. 86(C), pages 585-594.
    7. Xu, Chao & Haase, Dagmar & Su, Meirong & Yang, Zhifeng, 2019. "The impact of urban compactness on energy-related greenhouse gas emissions across EU member states: Population density vs physical compactness," Applied Energy, Elsevier, vol. 254(C).
    8. Davide Burgalassi & Tommaso Luzzati, 2015. "Urban spatial structure and environmental emissions: a survey of the literature and some empirical evidence for Italian NUTS-3 regions," Discussion Papers 2015/199, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    9. Yanchun Yi & Sisi Ma & Weijun Guan & Ke Li, 2017. "An Empirical Study on the Relationship between Urban Spatial Form and CO 2 in Chinese Cities," Sustainability, MDPI, vol. 9(4), pages 1-12, April.
    10. Kaza, Nikhil, 2010. "Understanding the spectrum of residential energy consumption: A quantile regression approach," Energy Policy, Elsevier, vol. 38(11), pages 6574-6585, November.
    11. Xia, Linlin & Zhang, Yan & Sun, Xiaoxi & Li, Jinjian, 2017. "Analyzing the spatial pattern of carbon metabolism and its response to change of urban form," Ecological Modelling, Elsevier, vol. 355(C), pages 105-115.
    12. Li, Peilin & Zhao, Pengjun & Brand, Christian, 2018. "Future energy use and CO2 emissions of urban passenger transport in China: A travel behavior and urban form based approach," Applied Energy, Elsevier, vol. 211(C), pages 820-842.
    13. Ouyang, Jinlong & Long, Enshen & Hokao, Kazunori, 2010. "Rebound effect in Chinese household energy efficiency and solution for mitigating it," Energy, Elsevier, vol. 35(12), pages 5269-5276.
    14. Estiri, Hossein, 2014. "Building and household X-factors and energy consumption at the residential sector," Energy Economics, Elsevier, vol. 43(C), pages 178-184.
    15. Jun Li & Michel Colombier, 2011. "Economic instruments for mitigating carbon emissions: scaling up carbon finance in China’s buildings sector," Climatic Change, Springer, vol. 107(3), pages 567-591, August.
    16. Papafragkou, Anastasios & Ghosh, Siddhartha & James, Patrick A.B. & Rogers, Alex & Bahaj, AbuBakr S., 2014. "A simple, scalable and low-cost method to generate thermal diagnostics of a domestic building," Applied Energy, Elsevier, vol. 134(C), pages 519-530.
    17. Curtis, John & Pentecost, Anne, 2015. "Household fuel expenditure and residential building energy efficiency ratings in Ireland," Energy Policy, Elsevier, vol. 76(C), pages 57-65.
    18. Zhang, Junyi & Teng, Fei & Zhou, Shaojie, 2020. "The structural changes and determinants of household energy choices and energy consumption in urban China: Addressing the role of building type," Energy Policy, Elsevier, vol. 139(C).
    19. Bereitschaft, Bradley, 2020. "Gentrification and the evolution of commuting behavior within America's urban cores, 2000–2015," Journal of Transport Geography, Elsevier, vol. 82(C).
    20. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.

    More about this item

    Keywords

    Household energy demand; CO2 emissions; Urban form;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:46:y:2012:i:c:p:359-369. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.