Adaptive model for outdoor thermal comfort assessment in an Oasis city of arid climate
One of the determining factors for the use of outdoor spaces is the experienced thermal comfort by people. There is a wide range of thermal indices. However, previous studies in Mendoza Metropolitan Area, Argentina, revealed that the predictive ability from six thermal comfort indices of internation...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/37627 |
| Acceso en línea: | http://hdl.handle.net/11336/37627 |
| Access Level: | acceso abierto |
| Palabra clave: | Adaptive Model Arid Climate Iza Oasis City Outdoor Thermal Comfort Predictive Ability https://purl.org/becyt/ford/2.7 https://purl.org/becyt/ford/2 |
| Sumario: | One of the determining factors for the use of outdoor spaces is the experienced thermal comfort by people. There is a wide range of thermal indices. However, previous studies in Mendoza Metropolitan Area, Argentina, revealed that the predictive ability from six thermal comfort indices of international spread is less than 25%. This high contrast reveals the need for proposing an adaptive model to predict the thermal comfort conditions of the adapted population to this "oasis city" of arid climate. For this purpose, monitoring of microclimatic parameters and field surveys about the perception of the people on a pedestrian street were carried out in both winter and summer. Fourteen Multiple Linear Regressions were performed and the Akaike's information criterion was used to the model selection. As a result, a new model has been developed: the "Thermal comfort Index for cities of Arid Zones (IZA)". The formula considers air temperature, relative humidity and wind speed, all significant, independent each other and readily available variables. We found that the IZA's predictive ability is 73%, demonstrating the efficiency of the proposed model. Designers and urban planners may use the IZA as a simple and useful tool to improve the design of outdoor spaces. |
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