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Assessment of spatial and temporal distribution of thermal comfort and IAQ in low energy houses

Maria del Carmen Bocanegra-Yanez, Paul Strachan, Paul Tuohy, Jon Hand, Tim Sharpe, 2015
thermal comfort | indoor air quality | Passivhaus | modelling
Bibliographic info: 36th AIVC Conference " Effective ventilation in high performance buildings", Madrid, Spain, 23-24 September 2015.
Languages: English

According to the International Energy Agency, buildings represent over one-third of total final energy consumption. Thus, a more sustainable future begins with low energy buildings which must combine comfort and function using passive systems and new evolving technologies. Policies to reduce building energy consumption and carbon emissions have been developed worldwide during the last decades. As a consequence, Building Regulations and Standards require more insulated and air tight buildings which may lead to indoor environment issues when not designed appropriately or systems are not used as designed. Detailed building modelling and simulation can provide an indication of building performance and furthermore, it can be used to assess indoor environment issues. Although there have been several previous studies of the indoor environmental quality in low energy buildings, this research is focused on the variability of overheating risk and poor indoor air quality (IAQ) at different locations in the building at different times. The impact that different occupancy profiles and ventilation strategies has on the distribution of thermal comfort levels and IAQ in low-energy houses has been assessed using the detailed thermal simulation program, ESP-r.

The first part of the research involved developing a model of a low energy house in accordance with the Passivhaus (PH) standard. Comparison of modelling results and the results from the Passive House Planning Package (PHPP) confirmed that the modelling results were in good agreement with the PH Standard in terms of monthly heat gains and losses of the building. Secondly, more realistic assumptions were formulated so modelling results could be compared with measured data in terms of temperature, humidity and CO2 distribution within various rooms of the building. Then a number of scenarios were formed, varying occupancy numbers and profiles with different ventilation regimes, which included natural ventilation, mechanical ventilation and mechanical ventilation with heat recovery options. These parametric variations were compared in terms of energy demand, plus temporal variation of indoor environment metrics (thermal comfort and IAQ).

The general conclusion arising from the analysis is that, contrary to the usual assumption of even distribution of the indoor environmental conditions, there can be significant variations in the internal distribution. Important factors are number and location of occupants and the movement of air within the building. Although this study was focused on climate representative of conditions in Scotland, similar variations would be expected in other climates.


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