Open Access
Issue
E3S Web Conf.
Volume 111, 2019
CLIMA 2019 Congress
Article Number 02003
Number of page(s) 9
Section Indoor Environment Quality and Others
DOI https://doi.org/10.1051/e3sconf/201911102003
Published online 13 August 2019
  1. L. D. Pereira, D. Raimondo, S.P. Corgnati and M. Gameiro da Silva, "Energy consumption in schools – A review paper," Renewable and Sustainable Energy Reviews, vol. 40, pp. 911-922 (2014). [CrossRef] [Google Scholar]
  2. "Alliance to save energy" Date of access October/2018, www.ase.org. [Google Scholar]
  3. D.F. Motta Cabrera and H. Zareipour, “Data association mining for identifying lighting energy waste patterns in educational institutes,” Energy and Buildings, vol. 62, pp. 210-216 (2013). [CrossRef] [Google Scholar]
  4. K. Ahmed, E. Sistonen, R. Simson, J. Kurnitski, J. Kesti and P. Lautso, “Radiant panel and air heating performance in large industrial building,” Building Simulation, vol. 11, no. 2, pp. 293-303 (2018). [CrossRef] [Google Scholar]
  5. K. Ahmed, J. Kurnitski and P. Sormunen, “Demand controlled ventilation indoor climate and energy performance in a high performance building with air flow rate controlled chilled beams,” Energy and Buildings, vol. 109, pp. 115-126 . [CrossRef] [Google Scholar]
  6. J. Kurnitski, K. Ahmed, R. Simson and E. Sistonen, “Temperature distribution and ventilation in large industrial halls,” Proceedings of the 9th Windsor conference: making comfort relevant, Cumberland Lodge, UK., pp. 340-348 (2016). [Google Scholar]
  7. Y. Allab, M. Pellegrino, X. Guo, E. Nefzaoui and A. Kindinis, “Energy and comfort assessment in educational building: Case study in a French university campus,” Energy and Buildings, vol. 143, pp. 202-219 (2017). [CrossRef] [Google Scholar]
  8. S.A. Ghita and T. Catalina, “Energy efficiency versus indoor environmental quality in different Romanian countryside schools,” Energy and Buildings, vol. 92, pp. 140-154 (2015). [CrossRef] [Google Scholar]
  9. E.G. Dascalaki and V.G. Sermpetzoglou, “Energy performance and indoor environmental quality in Hellenic schools,” Energy and Buildings, vol. 43, no. 2, pp. 718-727 (2011). [CrossRef] [Google Scholar]
  10. W. Vornanen C., K. Järvi, S. Toomla, K. Ahmed, A. Andersson M., R. Mikkola, T. Marik, L. Kredics, H. Salonen and J. Kurnitski, “Ventilation Positive Pressure Intervention Effect on Indoor Air Quality in a School Building with Moisture Problems,” Int. J. Environ. Res. Public Health, vol. 15, no. 2, pp. 230-252 (2018). [CrossRef] [Google Scholar]
  11. C. Vornanen-Winqvist, S. Toomla, K. Ahmed, J. Kurnitski, R. Mikkola and H. Salonen, “The effect of positive pressure on indoor air quality in a deeply renovated school building – a case study,” Energy Procedia, vol. 132, pp. 165-170 (2017). [CrossRef] [Google Scholar]
  12. P. de Wilde, “The gap between predicted and measured energy performance of buildings: A framework for investigation,” Automation in Construction, vol. 41, pp. 40-49 (2014). [CrossRef] [Google Scholar]
  13. L. La Fleur, B. Moshfegh and P. Rohdin, “Measured and predicted energy use and indoor climate before and after a major renovation of an apartment building in Sweden,” Energy and Buildings, vol. 146, pp. 98-110 (2017). [CrossRef] [Google Scholar]
  14. U. Dar I., L. Georges, I. Sartori and V. Novakovi, “Influence of occupant’s behavior on heating needs and energy system performance: A case of well-insulated detached houses in cold climates,” Building Simulation, vol. 8, no. 5, pp. 499-513 (2015). [CrossRef] [Google Scholar]
  15. Z. Wang, Z. Zhao, B. Lin, Y. Zhu and Q. Ouyang, “Residential heating energy consumption modeling through a bottom-up approach for China’s Hot Summer–Cold Winter climatic region,” Energy and Buildings, vol. 109, pp. 65-74 (2015). [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.