| 1. |
|
|
| 2. |
- Gao, Chuansi, et al.
(author)
-
Occupational heat stress assessment and protective strategies in the context of climate change
- 2018
-
In: International Journal of Biometeorology. - : Springer Science and Business Media LLC. - 1432-1254 .- 0020-7128. ; 62:3, s. 359-371
-
Journal article (peer-reviewed)abstract
- Global warming will unquestionably increase the impact of heat on individuals who work in already hot workplaces in hot climate areas. The increasing prevalence of this environmental health risk requires the improvement of assessment methods linked to meteorological data. Such new methods will help to reveal the size of the problem and design appropriate interventions at individual, workplace and societal level. The evaluation of occupational heat stress requires measurement of four thermal climate factors (air temperature, humidity, air velocity and heat radiation); available weather station data may serve this purpose. However, the use of meteorological data for occupational heat stress assessment is limited because weather stations do not traditionally and directly measure some important climate factors, e.g. solar radiation. In addition, local workplace environmental conditions such as local heat sources, metabolic heat production within the human body, and clothing properties, all affect the exchange of heat between the body and the environment. A robust occupational heat stress index should properly address all these factors. This article reviews and highlights a number of selected heat stress indices, indicating their advantages and disadvantages in relation to meteorological data, local workplace environments, body heat production and the use of protective clothing. These heat stress and heat strain indices include Wet Bulb Globe Temperature, Discomfort Index, Predicted Heat Strain index, and Universal Thermal Climate Index. In some cases, individuals may be monitored for heat strain through physiological measurements and medical supervision prior to and during exposure. Relevant protective and preventive strategies for alleviating heat strain are also reviewed and proposed.
|
|
| 3. |
- Gudmundsson, Anders, et al.
(author)
-
Dust in Buildings - A Method for Identifying Particle Sources
- 2005
-
In: Environmental ergonomics XI : proceedings of the 11th International Conference, 22-26 May, 2005, Ystad, Sweden - proceedings of the 11th International Conference, 22-26 May, 2005, Ystad, Sweden. - 9163170620 ; , s. 507-510
-
Conference paper (peer-reviewed)
|
|
| 4. |
- Martinez, Natividad, et al.
(author)
-
Validation of the thermophysiological model by Fiala for prediction of local skin temperatures
- 2016
-
In: International Journal of Biometeorology. - : Springer Science and Business Media LLC. - 1432-1254 .- 0020-7128. ; 60:12, s. 1969-1982
-
Journal article (peer-reviewed)abstract
- The most complete and realistic physiological data are derived from direct measurements during human experiments; however, they present some limitations such as ethical concerns, time and cost burden. Thermophysiological models are able to predict human thermal response in a wide range of environmental conditions, but their use is limited due to lack of validation. The aim of this work was to validate the thermophysiological model by Fiala for prediction of local skin temperatures against a dedicated database containing 43 different human experiments representing a wide range of conditions. The validation was conducted based on root-mean-square deviation (rmsd) and bias. The thermophysiological model by Fiala showed a good precision when predicting core and mean skin temperature (rmsd 0.26 and 0.92 °C, respectively) and also local skin temperatures for most body sites (average rmsd for local skin temperatures 1.32 °C). However, an increased deviation of the predictions was observed for the forehead skin temperature (rmsd of 1.63 °C) and for the thigh during exercising exposures (rmsd of 1.41 °C). Possible reasons for the observed deviations are lack of information on measurement circumstances (hair, head coverage interference) or an overestimation of the sweat evaporative cooling capacity for the head and thigh, respectively. This work has highlighted the importance of collecting details about the clothing worn and how and where the sensors were attached to the skin for achieving more precise results in the simulations.
|
|
