Climate change impacts local and regional atmospheric conditions, including air quality and thermal conditions. The aim of this study is to evaluate the connections between the diurnal variation of the Predicted Mean Vote (PMV) index and local climate change using the least representative day technique. The least representative day is composed of actual data from the day in the period considered, where the sum of the mean-square differences among its monitored quantities, averaged within each hour, and the same quantities for all other days at the same hour, is maximized. The least representative day generally corresponds to an anomalous situation of meteorological conditions. Local climate change scenarios usually include significant increases in temperature and frequent extreme heat events or abundant rains, with associated increases in the predicted percentage of the dissatisfied index (PPD absolute value). Some case studies have been analysed and a comparison with CFD code, namely ENVI-MET, is reported. This technique can prove to be a very important tool for identifying anomalous behaviour of comfort indices within the selected period in outdoor urban places. Keywords: Least Representative Day, Predicted Mean Vote, Predicted Percentage of Dissatisfied, Outdoor thermal comfort, Thermo fluid dynamic analysis

Outdoor thermal comfort and local climate change: exploring connections

COCCI GRIFONI, ROBERTA;Tascini, Simone;PIERANTOZZI, MARIANO
2012-01-01

Abstract

Climate change impacts local and regional atmospheric conditions, including air quality and thermal conditions. The aim of this study is to evaluate the connections between the diurnal variation of the Predicted Mean Vote (PMV) index and local climate change using the least representative day technique. The least representative day is composed of actual data from the day in the period considered, where the sum of the mean-square differences among its monitored quantities, averaged within each hour, and the same quantities for all other days at the same hour, is maximized. The least representative day generally corresponds to an anomalous situation of meteorological conditions. Local climate change scenarios usually include significant increases in temperature and frequent extreme heat events or abundant rains, with associated increases in the predicted percentage of the dissatisfied index (PPD absolute value). Some case studies have been analysed and a comparison with CFD code, namely ENVI-MET, is reported. This technique can prove to be a very important tool for identifying anomalous behaviour of comfort indices within the selected period in outdoor urban places. Keywords: Least Representative Day, Predicted Mean Vote, Predicted Percentage of Dissatisfied, Outdoor thermal comfort, Thermo fluid dynamic analysis
2012
9786124057892
273
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11581/267994
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