Purpose: This paper investigates the thermal conditions inside a passenger car driven after it was left a few hours in a shade-less parking lot, and the related implications for the driving performance. Materials and methods: Experimental results for twelve tests carried out in four different vehicles are presented and discussed. Each test is characterized by means of the predicted core temperature t_core of the driver after 60 minutes, as calculated by a heat stress model. The fractional performance loss is calculated by adjusting existing algorithms for office tasks to accommodate literature data on driving-related tasks, and then re-casting the algorithm as a function of t_core instead of the air temperature t_a. Results: Based on measured temperatures and humidities, fractional performance losses up to 50% are predicted even for relatively simple tasks such as keeping the vehicle on a straight course. Performance losses in excess of 75% are predicted, under the most extreme thermal conditions, for demanding tasks, such as correctly identifying a signal and reacting in due time. Conclusions: The implementation in technical standards on heat stress assessment of two new thresholds is recommended. The lower threshold, to be set at t_core ≅ 37.1 °C, is aimed at ensuring that the subject is able to carry out demanding mental tasks without appreciable performance loss, while the higher threshold, to be set at t_core ≅ 37.2 °C applies to simpler tasks.

As a part of their very wide range of applications, international standards also represent an excellent technical support to the legislation on comfort and health at the workplace. The existing standards on thermal comfort and on indoor air quality both include limits of acceptability which strongly depend on the category chosen for the investigated work environment. Therefore, the same situation can easily meet compliant or largely exceed specified limits depending on which category is applied. Unfortunately, no clue is currently provided on how to select the appropriate category, and the end-user is left uninformed. In this paper, we present a method to assign limits of acceptability to any work situation whose thermal comfort and indoor air quality must be assessed. The method extends previous work developed specifically for thermal comfort and is based on an algorithm which takes into account three quantities that provide a comprehensive description of the work environment, the activity which is carried out and the sensitivity of individuals. The scheme’s simple modular structure can easily accommodate both changes and additions, should other hypothetical elements be identified to be as relevant to the classification scheme.

Introduction: In order to establish the acceptability of a hearing protector device (HPD) used in a given noisy environment, two key elements must be known with the highest possible accuracy: the insertion loss of the HPD and the associated variability. Methods leading to objective field measurements of insertion loss have become widely available in the last decade and have started to replace the traditional subjective "Real-Ear Attenuation at Threshold" (REAT) laboratory measurements. The latter have long been known to provide a gross overestimate of the attenuation, thus leading to a strong underestimate of the worker's exposure to noise. Methods: In this work we present objective measurements of the insertion loss of an ear plug, carried out using the E-A-Rfit procedure by 3M on a large sample of 36 female and 64 male subjects. This large number of independent measurements has been exploited to calculate the distribution function of effective noise levels, that is noise levels that take into account the use of the HPD. The knowledge of the distribution function has in its turn allowed the calculation of the uncertainty on the effective noise levels. Results: This new estimate of uncertainty (6 to 7 dB) is significantly larger than most previous estimates, which range between 4 and 5 dB when using objective data but with an improper uncertainty propagation, and around 3 dB when using REAT subjective data. We show that the revised new estimate of uncertainty is much more realistic as it includes contributions that are missed by the other methods. Conclusions: By plugging this revised estimate of uncertainty into the criterion for checking the acceptability of the HPD, a better assessment of the actual protection provided by the HPD itself is possible.

Objectives: The purpose of this article is to develop a method for the statistical inference of the maximum peak sound pressure level and of the associated uncertainty. Both quantities are requested by the EU directive 2003/10/EC for a complete and solid assessment of the noise exposure at the workplace. Methods: Based on the characteristics of the sound pressure waveform, it is hypothesized that the distribution of the measured peak sound pressure levels follows the extreme value distribution. The maximum peak level is estimated as the largest member of a finite population following this probability distribution. The associated uncertainty is also discussed, taking into account not only the contribution due to the incomplete sampling but also the contribution due to the finite precision of the instrumentation. Results: The largest of the set of measured peak levels underestimates the maximum peak sound pressure level. The underestimate can be as large as 4 dB if the number of measurements is limited to 3–4, which is common practice in occupational noise assessment. The extended uncertainty is also quite large (~2.5 dB), with a weak dependence on the sampling details. Conclusions: Following the procedure outlined in this article, a reliable comparison between the peak sound pressure levels measured in a workplace and the EU directive action limits is possible. Non-compliance can occur even when the largest of the set of measured peak levels is several dB below such limits.

Optimization of resources is the key to improve our ability to perform multiple tasks with limited time and money. In the context of thermal comfort assessment, optimization becomes important in large rooms where tens of individuals perform similar tasks. This work focuses on the identification of the minimum number of measurement points that allows an accurate description of the thermal environment. Accuracy of description is assumed if no significant loss of information is associated to the transition from the ‘primary’ thermal map based on all available measurement points to a ‘secondary’ thermal map based on a reduced set of measurement points. The concept of ‘no significant loss’ is quantified by requiring that the difference in PMV (Predicted Mean Vote) between the two maps is kept <0.1 in the vast majority (95%) of points. PMV is a standardized synthetic index that is used worldwide for quantifying thermal comfort (ISO 7730, 2005) taking into account both environmental (thermo-hygrometric) and personal (activity, clothing) quantities. We show that the uncertainty induced by the degraded resolution of the thermal map has a limited impact on the overall uncertainty on PMV. Application of the method to a few test environments shows that the room size perpendicular to the main window and the windows orientation play the largest role in determining spatial inhomogeneity in thermal maps. A minor concurring factor is the room area.