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The purpose of this paper is to examine the seasonal performance, occupants’ comfort and cold stress in cross-laminated timber school buildings located in the USA (Northeast region).

The Fall survey was done from October–November 2017. In the Winter, it was considered from December 2017–February 2018. The study measured environmental parameters in the chosen spaces. The research applied the wet-bulb globe temperature (WBGT) model to determine the indexes in various seasons.

In the Fall, the average inside temperature was 21.2°C, the average RH was 50.7 per cent, and the mean dew-point was 9.3°C. The mean inside temperature was 20.5°C in the Winter while the mean RH was 23.9 per cent and the average dew-point was −1.9°C. The overall mean inside temperatures in both seasons were within the ASHRAE comfort temperature limits for cold seasons. During the surveys, higher average values of temperature, RH and dew-point were measured in the offices than the other spaces.

The research showed people might be subject to lower temperatures in the hall than the other spaces. Some design parameters and occupation hours may contribute to the lower temperatures reported in the hall than the different spaces.

The study proposes the WBGT of 16.0°C and 13.7°C as the stress indexes in the Fall and Winter seasons correspondingly. Last, the research suggests a WBGT of 14.9°C as the overall mean stress index within the spaces considered in this study.

The purpose of this paper is to examine the Summer performance, comfort, and heat stress in structural timber buildings. The research utilises building simulation as a tool to investigate the performance of the case study buildings under non-extreme weather conditions.

The research explores three UK sites using the test reference year (TRY) weather files for the current and future weather conditions. The study focuses on the Summer performance and heat stress in non-extreme weather conditions; therefore, the Design Summer Year (DSY) weather files are not used for the simulations. The simulation data are calibrated and validated using the measured data from the field study.

The results revealed the mean predicted temperatures varied from 20.2–20.8°C for the 2000s. The mean temperatures for the 2030s ranged from 23.1 to 24.2°C. Higher temperatures are predicted at the buildings in the Southeast site than the Midlands and the Northwest sites. The results revealed that there is no significant improvement in the thermal environment when the floor area and the floor-to-ceiling height are increased. However, the study showed that the integration of different design interventions can improve the future performance and resilience of the buildings in various weather conditions.

By applying the wet-bulb globe temperature (WBGT) and the Universal Thermal Comfort Index (UTCI) mathematical models to calculate the heat stress at the buildings, the study proposes the WBGT of 20.0°C and the UTCI of 24.1°C as possible heat stress indicators for occupants of the buildings in the 2030s.

On the one hand, the results revealed the maximum temperatures in some of the case study buildings exceed the comfort threshold (28°C). On the other hand, the study showed that occupants of the buildings are not prone to extreme Summertime overheating and heat stress under moderate weather conditions. However, different outcomes may be predicted if DSY weather files for the selected sites are considered.

This study is the first reported work to explore building simulation and mathematical equations to investigate Summer performance, comfort and heat stress indexes in timber buildings under moderate weather conditions in different regional sites in the UK.

Agricultural workers represent an important part of the population exposed to high heat-related health and productivity risks. This study aims to estimate the heat-related productivity loss (PL) for moderate work activities in sun and shady areas and evaluating the economic cost locally in an Italian farm and generally in the whole province of Florence. Benefits deriving by working in the shade or work-time shifting were provided. Comparisons between PL estimated in Mediterranean (Florence, Italy) and subtropical (Guangzhou, China) areas were also carried out.

Meteorological data were collected during summers 2017–2018 through a station installed in a farm in the province of Florence and by two World Meteorological Organization (WMO)‐certified meteorological stations located at the Florence and Guangzhou airports. These data were used to calculate the wet-bulb globe temperature and to estimate the hourly PL and the economic cost during the typical working time (from 8 a.m. to 5 p.m.) and by advancing of 1 h and 2 h the working time. Significant differences were calculated through nonparametric tests.

The hourly PL and the related economic cost significantly decreased (p < 0.05) by working in the shade and by work-time shifting. Higher PL values were observed in Guangzhou than in Florence. The decrease of PL observed by work-time shifting was greater in Florence than in Guangzhou.

Useful information to plan suitable heat-related prevention strategies to counteract the effects of heat in the workplace are provided. These findings are essential to quantify the beneficial effects due to the implementation of specific heat-related adaptation measures to counter the impending effects of climate change.

Heat stress, having caused preventable and lamentable deaths, is hazardous to construction workers in the hot and humid summers of Hong Kong. The purpose of this paper is to develop a heat stress model, based on the Wet Bulb Globe Temperature (WBGT) index.

Field studies were conducted during the summer time in Hong Kong (July to September 2010). Based upon 281 sets of synchronized meteorological and physiological data collected from construction workers in four different construction sites between July and September 2010, physiological, work‐related, environmental and personal parameters were measured to construct and verify the heat stress model.

It is found that drinking habit, age and work duration are the top three significant predictors to determine construction workers' physiological responses. Other predictors include percentage of body fat, resting heart rate, air pollution index, WBGT, smoking habit, energy consumption, and respiratory exchange rate. The accuracy of the model is verified against data which have not been used in developing the model. The accuracy of the heat stress model is found to be statistically acceptable (Mean Absolute Percentage Error=5.6 percent, Theil's U inequality coefficients=0.003).

Based on these findings, appropriate work‐rest pattern can be designed to safeguard the well being of workers when working in a hot and humid environment.

The model reported in this paper provides a more scientific and reliable prediction of the reality which may benefit the industry to produce solid guidelines for working in hot weather.

Raise in temperatures due to climate change is likely to increase the heat stress in occupations that are physically exerting and performed outdoors which might potentially have adverse health and productivity consequences. The purpose of this paper is to estimate the productivities in construction work under the influence of heat stress using the predicted mean vote (PMV) index.

Field studies were conducted during May 2014 which is summer time in Chennai. Continuous heart rate of workers and wet bulb globe temperature measurements are conducted for workers engaged in different jobs in construction. Metabolic rates and the workload of the workers from heart rate were calculated using the ISO method 8996 and the PMV values are calculated using the tool developed by Malchaire based on the method ISO 7730. Direct observations and personal interviews were conducted to substantiate the productivity estimations.

The results showed that workers working outdoors with moderate and heavy workload exceeded the threshold limit value of 28°C and had adverse productivity impacts (18-35 per cent productivity loss), whereas the workers engaged in light indoor work was not affected by heat stress and consequent productivity losses. The productivity estimations using the PMV index is found to be statistically significant for three types of construction works (Pearson correlation coefficient value of −0.78) and also correlated well with the observations and self-reported productivities of the workers.

The method used in this paper provides a scientific and reliable estimation of the productivities which may benefit the industry to set realistic project completion goals in hot weather and also implement interventions and policies to protect workers’ health. Developing adaptive strategies and implementing control measures are the need of the hour to protect worker’s health and economic losses in the face of climate change.

There are many safety hazards in construction workplaces, and inattention to the hazards is the main reason why construction workers failed to identify the hazards. Reasonably allocating attention during hazard identification is critical for construction workers’ safety. However, adverse working environments in job sites may undermine workers’ attention. Previous studies failed to investigate the impacts of environmental factors on attention allocation, which hinders taking appropriate measures to eliminate safety incidents when encountering adverse working environments. This study aims to examine the effects of workplace noise and heat exposure on workers’ attention allocation during construction hazard identification to fill the research gap.

This study applied an experimental study where a within-subject experiment was designed. Fifteen construction workers were invited to perform hazard identification tasks in panoramic virtual reality. They were exposed to three noise levels (60, 85 and 100 dBA) in four thermal conditions (26°C, 50% RH; 33°C, 50% RH; 30°C, 70% RH; 33°C, 70% RH). Their eye movements were recorded to indicate their attention allocation under each condition.

The results show that noise exposure reduced workers’ attention to hazardous areas and the impacts increased with the noise level. Heat exposure also reduced the attention, but it did not increase with the heat stress but with subjects’ thermal discomfort. The attention was impacted more by noise than heat exposure. Noise exposure in the hot climate should be more noteworthy because lower levels of noise would lead to significant changes. These visual characteristics led to poorer identification accuracy.

This study could extend the understanding of the relationship between adverse environmental factors and construction safety. Understanding the intrinsic reasons for workers' failed identification may also provide insights for the industry to enhance construction safety under adverse environments.

Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many tropical countries are expected to be the most areas affected by accelerated climate change and global warming, which may have a severe impact on labour health and productivity. The purpose of this paper is to assess whether the existing models can be used to predict labour productivity based on weather conditions in the tropics.

Five models are identified from the literature for evaluation. Using real labour productivity data of a high-rise building project in Malaysia, the actual productivity rate was compared with predicted productivity rates generated using the five models. The predicted productivity rates were generated using weather variables collected from an adjusting weather station to the project.

Compared with other models evaluated in this paper, the United States Army Corps of Engineers (USACE) was found to be the best model to predict productivity based on the case study data. However, the result shows only a 57% accuracy level of the USACE model indicating the need to develop a new model for the tropics for more accurate prediction.

The result of this study is perhaps the first to apply meteorological variables to predict productivity rates and validate them using actual productivity data in the tropics. This study is the first step to developing a more accurate productivity model, which will be useful for project planning and more accurate productivity rate estimation.

The purpose of this paper shows the effect of hot and humid weather conditions (HHWCs) on workers that has resulted in considerable loss in the construction industry, especially during the hottest periods due to decline in worker productivity (WP). Until the last few decades, there is very limited research on construction WP in HHWCs. Nevertheless, these studies have sparked interests on seeking for the most appropriate methods to assess the impact of HHWCs on construction workers.

This paper begins by reviewing the current measuring methods on WP in HHWCs, follows by presenting the potential impact of HHWCs on WP. The paper highlights the methodological deficiencies, which consequently provides a platform for scholars and practitioners to direct future research to resolve the significant productivity loss due to global warming. This paper highlights the need to identify the limitations and advantages of the current methods to formulate a framework of new approaches to measure the WP in HHWCs.

Results show that the methods used in providing real-time response on the effects of HHWCs on WP in construction at project, task and crew levels are limited. An integration of nonintrusive real-time monitoring system and local weather measurement with real-time data synchronisation and analysis is required to produce suitable information to determine worker health- and safety-related decisions in HHWCs.

The comprehensive literature review makes an original contribution to WP measurements filed in HHWCs in the construction industry. Results of this review provide researchers and practitioners with an insight into challenges associated with the measurements methods and solving practical site measurements issues. The findings will also enable the researchers and practitioners to bridge the identified research gaps in this research field and enhance the ability to provide accurate measures in HHWCs. The proposed research framework may promote potential improvements in the productivity measurements methods, which support researchers and practitioners in developing new innovative methods in HHWCs with the integration of the most recent monitoring technologies.

The purpose of this paper was to investigate the physiological cost of concrete construction activities.

Five concrete construction workers were recruited. The workers’ three-week heart rate (HR) data were collected in summer and autumn. In this paper, several HR indexes were used to investigate the physiological cost of work in concrete construction trades, including average working HR, relative HR and ratio of working HR to resting HR.

This paper measures how absolute and relative HRs vary throughout a workday and how working HR compares to resting HR for individual workers.

Field observations are usually extremely difficult as researchers need to overcome a number of barriers, including employers’ resistance to perceived additional liabilities, employees’ fear that their level of activity will be reported to managers and many other practical and technical difficulties. As these challenges increase exponentially with the number of employers, subjects and sites, this study was limited to a small number of subjects all working for the same employer on the same jobsite. Still, challenges are often unpredictable and lessons learned from this study are expected to guide both our and other researchers’ continuation of this work.

The time effect on the physiological cost of work has not been considered in previous studies. Thus, this study is noteworthy owing to the depth of the data collected rather than the breadth of the data.

Some manufacturing processes generate extreme temperatures, noise and other irritating environmental conditions. These environmental factors can have a negative impact on workers’ performance and health. The purpose of this paper is to investigate the impact of temperature, noise and lighting on factory workers’ productivity and day-to-day health in a rubber compound manufacturing plant.

Secondary data on productivity, measurements of factory environmental conditions, and records of medical advice and treatments over a period of three months were used in this study. Causal analysis was performed using statistical techniques ANOVA and regression analysis in SPSS statistical package.

The results revealed that higher levels of temperature and noise inside the factory can cause lower productivity levels. High temperature may not only reduce the productivity but also contribute to illnesses or heat-stress symptoms such as headaches. The results further suggested that both noise and lighting level do not have a statistically significant impact on workers’ health. No statistical evidence was found on lighting level having an impact on workers’ productivity.

The study was particularly focused on a rubber compound manufacturing plant. However, the results were consistent with the results obtained in similar studies which focused on leather and shoe industry and automobile assembly industry.

The impact of environmental conditions on workers’ performance and health has been studied with respect to few industries and regions. This is the first of that kind carried out in Sri Lanka. Clear evidence of productivity losses and health impacts caused by high temperatures, raises the need for improving the working conditions.