ASHRAE 55 (2004). Thermal Environmental Conditions for Human Occupancy. Atlanta, USA: ASHRAE.
AG Barnett, S Tong, ACA Clements (2010). What measure of temperature is the best predictor of mortality. Environmental Research, 110: 604-611.
S Carlucci, L Pagliano (2012). A review of indices for the long-term evaluation of the general thermal comfort conditions in buildings. Energy and Buildings, 53: 194-205.
EN 15251 (2007). Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics. Brussels, Belgium: European Committee for Standardization.
JA Clarke (2001). Energy simulation in building design, 2nd edn. Oxford, UK: Butterworth Heinemann.
S Coles (2001). An Introduction to Statistical Modeling of Extreme Values. London: Springer.
PO Fanger (1970). Thermal Comfort. Copenhagen: Danish Technical Press.
ISO 7730 (2005). International Standard, Ergonomics of the thermal environment—Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria.
J Kravchenko, AP Abernethy, M Fawzy, HK Lyerly (2013). Minimization of heatwave morbidity and mortality. American Journal of Preventive Medicine, 44: 274-282.
MR Leadbetter, G Lindgren, H Rootzén (1983). Extremes and Related Properties of Random Sequences and Processes. Berlin: Springer.
KJ Lomas, R Giridharan (2012). Thermal comfort standards, measured internal temperatures and thermal resilience to climate change of free-running buildings: A case-study of hospital wards. Building and Environment, 55: 57-72.
A Mavrogianni, P Wilkinson, M Davies, P Biddulph, E Oikonomou (2012). Building characteristics as determinants of propensity to high indoor summer temperatures in London dwellings. Building and Environment, 55: 117-130.
MA McGeehin, M Mirabelli (2001). The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States. Environmental Health Perspectives, 109: 185-189.
JC Montero, IJ Mirón, JJ Criado, C Linares, J Díaz (2010). Comparison between two methods of defining heat waves: A retrospective study in Castile-La Mancha (Spain). Science of the Total Environment, 408: 1554-1550.
S Patidar, D Jenkins, P Banfill, D Gibson (2014). Simple statistical model for complex probabilistic climate projections: Overheating risk and extreme events. Renewable Energy, 61: 23-28.
AD Peacock, DP Jenkins,, D Kane, (2010). Investigating the potential of overheating in UK dwellings as a consequence of extant climate change. Energy Policy, 38: 3277-3288.
R-D Reiss, M Thomas (2007). Statistical Analysis of Extreme Values, 3rd edn. Basel: Birkhäuser Verlag AG.
A Roetzel, A Tsangrassoulis, U Dietrich, S Busching (2010). On the influence of building design, occupants and heat waves on comfort and greenhouse gas emissions in naturally ventilated offices. A study based on the EN 15251 adaptive thermal comfort model in Athens, Greece. Building Simulation, 3: 87-103.
Z Sadovský, O Koronthályová, P Mihálka, P Matiašovský, K Mikulová (2014). Probabilistic study of overheating discomfort in residential building. In: et al. (ed), Proceedings of Safety, Reliability and Risk Analysis: Beyond the Horizon, ESREL 2013. London: Taylor & Francis, pp. 1629-1635.
L Van Gelder, H Janssen, S Roels (2014). Probabilistic design and analysis of building performances: Methodology and application example. Energy and Buildings, 79: 202-211.
JL White-Newsome, BN Sánchez, O Jolliet, Z Zhang, EA Parker, JT Dvonch, MS O'Neill (2012). Climate change and health: Indoor heat exposure in vulnerable populations. Environmental Research, 112: 20-27.
