Quantification Methods for Employee Health and Productivity Rates based on Indoor Environmental Quality

Review Article ISSN 2278 1331 International Journal of Environmental Engineering Research, Volume 1, Issue 3, 2012, 104-114 Copyright 2012, All rights reserved Research Publishing Group www.rpublishing.org Quantification Methods for Employee Health and Productivity Rates based on Indoor Environmental Quality Matthew Franchetti and Ghorban Komaki Department of Mechanical, Industrial, and Manufacturing Engineering, The University of Toledo, Toledo, Ohio 43606, USA matthew.franchetti@utoledo.edu Abstract:Many people spend the majority of their time in an indoor environment; even the most active people spend a minimum of 12 hours per day inside the home or work office. Indoor Environmental Quality (IEQ) considers the quality of all comfort and health factors in the indoor environment. This paper investigates the relationship between IEQ and productivity rates for manufacturers, service companies, and educational institutions. This paper analyzes several recent studies that examined IEQ and its relationship to productivity and health of employees or students. A 1995 analysis by the US General Accounting Office of 80,000 public elementary and secondary schools found that over 8 million students are attending 15,000 schools with severe indoor air quality problems. These indoor air quality problems can be effectively addressed through simple design strategies, the result being improved health, increased attendance, and better grades for this group. This paper discusses these relationships, methodologies, and design strategies to justify IEQ improvement projects. Key words: Indoor environmental quality, productivity. Received 29 October 2012; received in revised form 29 December 2012; accepted 31 December 2012 1 Introduction Several research studies have been conducted on the relationship between IEQ and health/performance; a few of these studies have focused on the measurement of the productivity impact of various improvement actions concerning indoor environments.these studies examined the existence of a linkage between IEQ and productivity.the goal of this study was to compare these studies and the associated implications for companies in terms of employee health, productivity rates, and operating costs. A simple way of defining productivity is to describe it as a ratio between the output (such as, products, services, and activities) and the input (such as, materials, labor, capital, and energy) that is used to generate the output. Productivity can be improved by making more output in relation to the amount of input and by making output with better quality (Antikainen, et al., 2008). Indoor air can affect productivity through many different ways. In order to determine the impact of indoor air on productivity, it is necessary to uncover the mechanism behind the relationship. In the workplace, there are several indoor elements (physical, chemical, and biological) that may sometimes cause health effects among workers (respiratory, skin, nervous, nasal, and related problems), and they can also hinder the fluency of work. In extreme cases, usually when serious indoor-air problems have occurred for a long time, they can also decrease employees motivation. These effects on employees may, in turn, cause changes in business outcomes. These changes may be realized in various ways, in input usage, output quantities, work quality, expenses, for example, which are well-known factors of productivity (Antikainen, et al., 2008). To estimate the effects of indoor air quality, most of researchers measure the performance of occupants on specific tasks such as standardized test score, text typing, proof-reading, and addition in the controlled condition. Until recently, there was no standard procedure to measure the office work productivity, so it was difficult to present the relationship between the productivity and IEQ. A neurobehavioral approach is proposed by Lan (Lan, et al., 2009) to systematically and quantitatively evaluate the effects of IEQ on office worker s productivity by several neurobehavioral tests, which assessed four classes of neurobehavioral functions involved in office work, including perception, learning and memory, thinking, and executive functions. The effect of IEQ on health, well-being and productivity is important topic and recently many researchers have addressed this topic. IEQ as is defined by the National Institute of Occupational Safety and Health (NIOSH) and includes: 104

Indoor Air Quality (IAQ) which depends on high levels of well-filtered fresh outside air, a low contaminant load, and minimization of particulates and mold spores. Thermal comfort is affected by air temperature, humidity, mean radiant temperature and air speed, as well as human variables, such as clothing and activity levels. Most complaints from building occupants relate to their inability to control the temperature of the space. Visual comfort depends on many variables, including lighting quality, minimization of glare, variable light levels, lighting controls, such as local switching and dimmers, visual connection with the exterior, and access to natural lighting. Acoustical quality involves the minimization of noise levels and vibration to achieve appropriate physical comfort and sound isolation levels for work and speech intelligibility. According to the U.S. Census Bureau, people complain about noise in their neighborhoods more than any other problem. It is widely accepted that Indoor Environmental is important for public health. 2. Experimental Methods For this study, a review of recent literature related to IEQ and performance was conducted. The intention of this study was to identify research methods that quantified the relationship between IEQ to health and productivity measures in an industrial, service, or educational setting. Special emphasize was placed on studies that developed mathematical relationships or quantified outcomes related to IEQ and performance in terms of health or productivity. Based on the findings of the literature review, several common areas IEQ related to health or performance identified. The majority of the studies focused on one of the common areas of IEQ to establish performance or health relationships. These common areas of IEQ were: Indoor air quality Thermal comfort Ventilation Visual comfort Acoustic quality The analysis section of this paper will address each of these areas of IEQ in terms of performance and health. In total, 49 IEQ studies were analyzed and summarized for this research. 3. Analysis 3.1 Indoor Air Quality Indoor air quality (IAQ) is one of the most important areas of IEQ, particularly in terms of the impact of a building on the health of occupants. IAQ refers to the presence or absence of air pollutants in buildings. There are many different types of pollutants that can affect indoor air, and they come from a wide range of sources. The American Society of Heating, Refrigerating, and Air-Conditioning Engineers recommendsthe following (ASHRACE, 2004): Relative humidity- 30% to 60% (ASHRAE 55-1992) Temperature- 68 degrees to 78 degrees (ASHRAE 55-1992) Ventilation Rate- minimum of 15 cubic feet per minute per person (ASHRAE 62-1989) Carbon Dioxide- Maximum 1000 parts per million (ASHRAE 62-1989) Poor IAQ leads to a variety of health risks that have significant costs for the people affected directly, as well as for their family members, employers and society at large. Since individuals spend a lot of their times in indoor environments, IAQ has become a concern because indoor pollutant levels frequently exceed outdoor levels. The air contamination level indoors is between four and ten times higher than what can be found outdoors (Woods, 1989). Since people spend about 90% of their time in the indoor environment, they are strongly affected by indoor air quality and the condition of indoor environment becomes closely linked to their performance. Unfortunately, Sick Building Syndrome (SBS) is becoming commonplace and results in short and long term health problems such as: Short-term impacts: Asthma episodes Allergy symptoms Irritated eyes, nose, or throat 105

Congestion and coughing Shortness of breath or wheezing Fevers or chills Fatigue, lethargy Headache Nausea Drowsiness Dizziness Skin rashes Long-term impacts: Asthma onset Increased severity of asthma Recurrent pneumonia and bronchitis Frequent upper respiratory infections Lung and other cancers Hearing loss Cognitive impairment Personality change Neurological damage Reproductive disorders Fanger (Fanger, 2006) discussed the impact of indoor-air quality on productivity in offices, learning in schools, and the growth of allergic and asthmatic diseases. He went on to discuss solutions, including air cleaning, personalized ventilation, and the need for cool (21 o C) dry air. Other work suggests that relative humidity below 40% can increasingly give rise to dry throats, and below 20% it may have negative effects on the eye blinking rate. A range of 40 60% is acceptable. Bakó-Biró and Olesen (2005) concluded that (i) indoor-air quality can significantly improve the performance of people, (ii) according to laboratory studies a 10% increase in dissatisfaction decreases performance by 1%, (iii) field studies also show significant improvements in performance with improved indoor-air quality (fewer pollution sources, higher ventilation rates), and (iv) with improved indoor-air quality significant savings in health care costs are possible sick building syndrome, sick leaves, etc.). Fisk (Fisk et al., 2011) studied the cost and benefit of different scenario about IEQ and its effect on employees in US offices. They run several scenarios including increasing ventilation rates when they are below 10 or 15 l/s per person, adding outdoor air economizers and controls when absent, eliminating winter indoor temperatures >23 C, and reducing dampness and mold problems. The estimated benefits of the scenarios analyzed are substantial in magnitude, including increased work performance, reduced Sick Building Syndrome symptoms, reduced absence, and improved thermal comfort for millions of office workers. Hoskins (Hoskins, 2003) identified the factors that affects indoor air quality and numerated them as ventilation, temperature, humidity, artificial light, noise and vibration, chemical pollutants, combustion. Moreover, important sources of chemical pollutants indoors include not only outdoor air, but also human body and human activities, plus emissions from building materials, furnishings and appliances and use of consumer products. Microbial contamination is mostly related to the presence of humidity. The heating, ventilating and air conditioning system can also act as a pollutant source, especially when it is not properly maintained. For example, improper care of filters can lead to re-emission of particulate contaminants. Biological contamination can proliferate in moist components of the system and be distributed throughout the building. One of the most important causes of indoor pollution is combustion which its level depends on the fuel that is burnt and how it is burnt. In this study, Hoskins also studied the effect of these items on human health. Most indoor air pollutants directly affect the respiratory and cardiovascular systems and the severity of effect varies according to both the intensity and the duration of exposure, and also with the health status of the population exposed. So people who spend most of their time indoor such as infant and elderly people, they are more susceptible to the health effect of indoor pollutant (Hoskins, 2003). Also he considered the effect of Carbon Monoxide, Nitrogen Dioxide, Volatile Organic Compounds (VOCs), Radon on health. The productivity of work forces can be increased up to 20% simply by increasing the air quality (Woods, 1989). 3.2 Thermal Comfort Indoor temperature is one of the fundamental factors of the IEQ and in several recent studies (Li et al., 2011; Seppanen et al., 2009; Seppanen, el al., 2010; Tanabe el al., 2009; Wijewardane and Jayasinghe, 2008) it is shown that indoor temperature influences health and productivity in many ways. It can affect several human 106

responses including thermal comfort, perceived air quality, SBS and performance at work. Room temperature can affect the performance indirectly through its impact on the prevalence of SBS symptoms or dissatisfaction with the air quality (Seppänen et al., 2009 and Seppänen et al., 2010). Various metrics of performance are used in studies about effects of temperature on office workers performance. Laboratory studies typically measure performance in a single or combined task and in field studies measure single task (Seppänen et al., 2009). One of the most studied offices is call center such as (Federspiel et al., 2004; Liu and Lahiff, 2002; Niemelä et al, 2001;Niemelä et al, 2002; Tanabe et al., 2009; Tham and Willem, 2005; Wargocki et al., 2003) and the considered performance criteria are the talk time or the handling time per. The talk-time can be used as a measure of productivity, because the number of operators on duty would have to be increased if talk-time became longer under adverse environmental working conditions (Wyon, 2004). Niemelä (Niemeläet al., 2001) studied the effect of temperature on call center workers and reported that when the temperature was above 25 C, workers productivity decreased 1.8% per C. Later, the same authors (Niemelä et al., 2002) performed another experiment in the same call center and reported that by increasing the temperature above 25 C the productivity decreases 2.2% per C. Federspiel (Federspielet al., 2004) ran a field study in call center and measured the workers performance in the US. They reported that there is no significant relation between temperature and productivity in the comfort zone but they found a 15% decrease in productivity as the temperature increased from 24.8 to 26 C. Link and Pepler (Link and Pepler, 1970) measured productivity in an cloth factory and found a reduction of 8% in productivity in sewing work as the temperature increased from 23.9 to 32.2 C. Tham and Willem (Tham and Willem, 2005) have conducted surveys on call centers and reported that reducing the temperature by 2 C from 24.5 C to 22.5 C might improve the talk time of operators by 5 13%. They also reported that doubling outdoor air supply rate at 24.5 C significantly improved talk time by 7 9%. Niemelä ( Niemelä, 2002) reported, from the surveys conducted at two call centers, that labor productivity in the call center decreased 5 7% when the air temperature exceeded 25 C. Tanabe (Tanabe et al., 2009) studied a call center over one year to evaluate the effect of temperature on performance of workers through seasonal and year-round analysis. Their results are as below: The relationship between indoor air temperature and call response rate differ from season to season. In spring and winter, increase of the air temperature resulted in the decrement of call response rate, while there was no significant change in call response rate related to the air temperature in summer. From the regression model of indoor air temperature and call response rate, the increase in air temperature by 1.0 C was related to the decrease in call response rate by 0.15calls/h. In particular, raising indoor air temperature by 1.0 C from 25.0 to 26.0 C would lead to the decrement in performance by 1.9%. Physical measurements on thermal environment from the survey were mostly within the range of the comfort zone. However, the effects and changes on performance were observed in the comfort zone, and the possibility of improvement in productivity was implied even within this range. Seppänen (Seppänenet al., 2009) showed that by increasing the temperature 1 C in the range of 25-32 C, performance decreased by 2% and temperature range of 21-25 C had no effect on performance. Seppänen (Seppänenet al., 2003) analyzed the earlier studies about effect of temperature on task performance and they concluded that the workers performance increased by temperature up to 21-22 C and decreased with the temperature above 23-24 C. They also reported that the highest productivity was at temperature 22 C. In recently completed experimental study, the average speed of completing academic work, based on monitoring of performance of eight simulated school work tasks, decreased by approximately 1.1% per each 1 F as temperatures increased from 68 F to 77 F. The number of errors in school work was not significantly affected by temperature changes in this temperature range (US Department of Energy, 2012). The performance (speed and accuracy) of office work tasks is maximized when the air temperature is approximately 71 F. As the indoor air temperature rises above or falls below 71 F, performance decreases. As the indoor air temperature decreases between 71 F and 65 F, performance drops, on average, by 0.37% per each 1 F drop in temperature. As indoor air temperature increases between 71 F and 80 F, performance drops, on average, by 0.43% per each 1 F increase in temperature. However, temperature changes near the optimum temperature of 71 F have a smaller impact on performance. These numbers are estimates of the average relationship of temperature with work performance based on a statistical analysis of published data for a range of types of work and these estimates have considerable uncertainty (US Department of Energy, 2012). Johansson (Johansson, 1975) studied the performance level at different temperatures, 24, 27 and 30 C, and based on several tests reported that performance result in learning, addition and multiplication tests were 10 14% worse at the temperatures of 27 and 29 C than in 24 C.Pepler and Warner (Pepler and Warner,1968) performed experiments with 36 female and 36 male students in a climate chamber. They found an inversed U- shape relationship between time to complete a task and temperature, with the longest time to complete assignments work at 26.7 o C. However, the error rate was lowest at 26.7 o C. 107

Several studies support the hypothesis that there is a temperature range with no significant effect on productivity. Federspiel (Federspiel and Lahiff, 2002) reported that temperature variations between 21.5 and 24.75 C in call center study did not significantly affect work speed. Also Federspiel (Federspiel, 2001) in a study of the relationship of air temperatures with occupants hot or cold complaints found that the complaint rate was very low in the temperature range of 22.2-23.9 C and concluded that avoiding complaints might prevent productivity reductions. Moreover, Witterseh (Witterseh, 2001) ran several experiments in simulated offices work such as multiplication, text typing and addition tests at 22 C and 25 C in laboratory and he didn t find significant differences in performance levels. Some researchers have proposed model about relation of temperature and workers performance (Seppanen et al., 2002 and Wyon, 2004).Seppanen (Seppanenet al., 2002) concluded that there is a temperature range, 21 to 25 C, which productivity does not change by variation the temperature in this range. The proposed relationship between decrement in productivity (P) in % and temperature (T) in C by Seppanen (Seppanenet al., 2002) is as Equation 1. [2 (T, C)] 50 25 < C P(%) = < 33 0 21 < C < 25 Equation 1 Also Wyon (Wyon, 2004) based on his earlier experimental work developed a relationship to estimate the productivity reduction in office work from tests which measured thinking, and typing skills and speed. He considered equal weigh to each skill and proposed a relationship between an over-all decrement of performance in office work as a function of the difference between the actual temperature and the temperature for thermally neutrality. Based on Wijewardane and Jayasinghe study (Wijewardane and Jayasinghe, 2008) the extreme level of temperature that factory workers involved in light works could feel reasonably comfortable is 30 C when there is no significant air movement. This comfort temperature limit can be increased up to 34 C when indoor air velocities are maintained as high as 0.6ms-1. It is also shown that these studies validate the earlier predictions of adaptive models for warm humid climates (WijewardaneandJayasinghe, 2008). Lan (LanandLian, 2010)studied the effects of air temperature on office workers productivity based on the neurobehavioral approach. Volunteers were asked to do computerized neurobehavioral tests and meanwhile their heart rate variation (HRV) and electroencephalograph (EEG) were measured. They found that participants well-being is negatively affected by the warm discomfort and HRV is increased from low frequency to high frequency. In the moderately uncomfortable environment, the workload imposed by tasks increased and participants had to exert more effort to maintain their performance and they also had lower motivation to do work. The results indicate that thermal discomfort caused by high or low air temperature had negative influence on office workers productivity and the subjective rating scales were useful supplements of neurobehavioral performance measures when evaluating the effects of IEQ on productivity. The thermal perceptions of the occupants are influenced by the factors such as demographics (gender, age, economic status), context (building design, building function, season, climate, semantics, social conditioning), and cognition (attitude, preference, and expectations) (Wijewardane and Jayasinghe, 2008). Schellen et al (Schellen et al., 2010) conducted a study to find the effect of temperature on response of young and elderly people and they were exposed to two different conditions, controlled condition where temperature was constant at 21.5 C, and transient condition where temperature was in range 17 25 C. The concluded that thermal sensation of the elderly was, in general, 0.5 scale units lower in comparison with their younger counterparts. 3.3 Ventilation Ventilation removes air pollutants originating inside the building, its main characteristic is creating healthy indoor environment by removing bio-effluents, COx, NOx, and so on. Increasing of ventilation rate (VR) usually results in better perceived air quality and a lower concentration of indoor generated pollutants. Low ventilation rates generally lead to higher prevalence of adverse health effects, including SBS symptoms and air borne infectious diseases (Seppänen et al., 2006). The earliest estimation of ventilation requirements is made by Tredgold (Tredgold, 1836). He estimated a minimum required VR of about 2 l/s (4 cfm) per person by considering 2 l/s (4 cfm) per person generated CO2 per occupants, moisture, and required oxygen for lamps and candles. Later Billings (Billings, 1893) based on the human organic exhalations theory calculated a ventilation requirement of about 15 l/s (30 cfm) per person. Recently ASHRAE Standard 62, Ventilation for Acceptable Indoor Air Quality, has in the past adopted a minimum of 8 l/s-person of outdoor air per person for classroom environments. 108

Several literature reviews have been published on the effects of ventilation on health and most of them verify that lower VR can significantly affect health mainly SBS (Fisk et al., 2009), short term absenteeism (Milton et al., 2000 and Sheldon et al., 2004), and respiratory infections (Li et al., 2007). In 1999, the results of first experiments carried out at the Technical University of Denmark showed that indoor air pollution may reduce productivity, either in addition to or instead of having negative effects on comfort and health (Wyon, 2004). Sundell (Sundell et al., 2007) proposed a comprehensive review on the available literature about direct effect of ventilation on health and they concluded that based on the peer-reviewed scientific literature on health outcomes there is an association between ventilation rates and SBS symptoms in offices, where higher ventilation rates, up to about 25 l/s per person, are associated with reduced symptoms. Fisk (Fisk, 2009) proposed a quantitative relation between VR and SBS symptoms. Most studies indicated typically a 1 3% improvement in average performance per 10 l/s-person increase in VR. The performance increase per unit increase in ventilation was bigger with ventilation rates below 20 l/s-person and almost negligible with ventilation rates over 45 l/s-person. The performance increase was statistically significant with increased ventilation rates up to 15 l/s-person with 95% CI and up to 17 l/s-person with 90% C (Fisk, 2011). Shaughnessy (Shaughnessy, 2006) studied the correlation of VR (CO2 concentrate) and students performances and they reported that there is a significant association between classrooms VR and test result in Math. Also Seppanen (Seppanen et al, 2006) proposed the quantitative relation between VR and work performance. Milton (Milton et al., 2000) in a study of 40 buildings to estimate the quantitative relationship of office VR with shortterm absence found that a 12 l/s per person increase in VR was associated with a 35% reduction in short-term absence in office workers. To investigate the effect of ventilation of performance, SBS symptoms and short-term absenteeism, Fisk et al. (Fisk et al., 2011) increased the VRs to 10 and 15 l/s per person when VRs are below than target level. The result showed that by increasing the VR to 10, the performance of workers increased in average 0.7%, the SBS symptoms reduced by 13.2% and 4.5 million days of short-term absence avoided. In financial terms, they estimated $5.6 billion annual benefits for increasing VR to 10 l/s per person and for other one $13.5 billion while the estimated annual energy cost was $0.04 billion. Fisk (Fisk et al., 2002) studied the effect of ventilation on performance of advice nurses working in a call center. They manipulated the ventilation rate and monitored temperatures, humidity, and CO2 concentrations were monitored. They collected the worker performance data within 30 minutes. The result showed that the effect of ventilation rate on worker performance in this call center was very small (probably less than 1%) or nil, over most of the range of ventilation rate (roughly 12 L s-1 to 48 L s-1 per person). However, there is some evidence of performance improvements of 2% or more when the ventilation rate per person is very high, as indicated by indoor CO2 concentrations exceeding outdoor concentrations by less than 75 ppm. In a study of 35 Norwegian classrooms, higher concentrations of CO2, which indicate lower rates of outside air ventilation per person, were associated with poorer performance in computerized tests of reaction time Myhrvold and Olsen, 1996).In a study by Seppanen, workers who reported building-related health symptoms, known to be associated with lower ventilation rates (Seppanen et. al. 1999), took 7% longer to respond in a computerized neurobehavioral test of sustained visual attention and had 30% higher error rates in a test of symbol-digit substitution test of speed and coding ability. In laboratory experiments by Wargocki et al. (Wargocki et al.,2000) increasing the ventilation rate with a carpet from a complaint building present was associated with improvements of a few percent in speed or accuracy of several simulated work tasks such as text typing, addition, proof reading, and creative thinking. Seppänen (Seppänenet al., 2006) ran several studies to examine the effect of ventilation on performance. They cited that, in only a few cases, objective measures have been used. It seems to be easier to use them when clerical-type work is studied, but subjective methods seem applicable to more diverse work. They also stated that relevant objective measures are rare. The most used of them seems to be speed of work (e.g., average time per certain task), but it does not fit jobs in which tasks regularly differ from each other. However, they argued that the use of subjective methods expose productivity measurement to expectations. Seppänen (Seppänenet al., 1999) and Wargocki (Wargockiet al., 2000) have made a comprehensive review of over 20 studies with over 30000 persons and found that VRs below 10 L/s per person results in lower air quality and aggravate health problems. By increasing the VR from 10 L/s to about 20 L/s per person, the risk of the SBS was reduced, and perceived air quality was improved. The work also indicated that CO2 concentrations below 800 ppm were preferable. Myhrvold (Myhrvoldetal., 1999) found a significant negative correlation between increasing concentration of CO2 (range,1,000 4,000 ppm) and the performance of pupils on three psychological tests measuring simple 109

reaction time, choice reaction time and the color-word test of vigilance. Assuming that the concentration of CO2 is a good indicator of ventilation rate in occupiedrooms, they showed that performance monotonically decreases when ventilation rates are reduced from above 8 L/s per person down to 1 L/s per person. No decrease in the performance of simulated office work had been observed in the classical series of studies performed by the New York State Commission on Ventilation (1923) even though ventilation rates were reduced until the CO2 concentration had risen to 3,000 4,000 ppm, that is to the highest concentrations measured in classrooms by Myhrvold (Myhrvoldet al., 1999). Ventilation Rates and Absences in Offices and Schools: In offices, a 35% decrease in short term absence was associated with a doubling of ventilation rate from 25 to 50 cfm per person. In an elementary grade classroom study, on average, for each 100 ppm decrease in the difference between indoor and outdoor CO2 concentrations there was a 1% to 2% relative decrease in the absence rate. Given the relationship of CO2 concentrations with ventilation rates, for each 1 cfm per person increase in ventilation rate, it is estimated that the relative decrease in absence rates is approximately 0.5% to 2%. This relationship applies over an estimated ventilation rate range of 5 to 30 cfm per person, and should not be applied outside those limits. Data relating building ventilation rates and absence rates are very limited. For initial ventilation rates between 14 and 30 cfm per person, the average performance increases by approximately 0.8% per 10 cfm per person increase in ventilation rate. At higher ventilation rates, the average performance increase is smaller, approximately 0.3% per 10 cfm per person increase in ventilation rate. For ventilation rates less than 14 cfm per person, performance increases with ventilation rate seem likely; however, sufficient data are not yet available to confirm this hypothesis (US Department of Energy, 2012). Increases of 5% to 10% in aspects of student performance may be associated with doubling the ventilation rate when rates are at or below minimum ventilation standards (15 cfm per student). However, data relating ventilation rate with school performance are not extensive (US Department of Energy, 2012). 3.4 Visual Comfort A change in the lighting can be effected by modifying the artificial light as well as the quality ofnatural daylight. Many previous studies show the effect of a change of illumination on worker performance level. There is some evidence that more daylight or a view to outdoors improves office and school work performance, but the available data are limited and findings are inconsistent (US Department of Energy, 2012). Available data are too limited to draw conclusions about the impacts of typical changes in indoor lighting levels and lighting quality on performance of office and school work. Significant impacts on performance are most likely for subjects with poor or uncorrected vision (US Department of Energy, 2012). A study by Untimanon (Untimanonet al. 2006) concluded that visual strain problems are most common among vision intensive industrial workers. The study measured the visual performance of electronic and jewelry, manufacturing workers working on tiny visual tasks over near distances. When lighting conditions were improved, short breaks introduced and visual performance problems corrected, they found that performance increased significantly among the electronic but not the jewelry workers.juslén (Juslénet al., 2004) reported two case studies in industrial environment and concluded that a change and improvement in lighting can have an effect on productivity and it is possible that increasing illumination levels increase a person s productivity. Also Juslén (Juslénet al., 2004) added that prediction of exact amount of this effect is difficult due to starting conditions, the final installation, the people involved, the nature of the work and the process of change all influence the result. Moreover Juslén (Juslénet al., 2004) suggested some recommendations to conduct future studies. Ismail (Ismail et al., 2009) studied the effect of luminance (lux), relative humidity (%) and Wet Bulb Globe Temperature on the operators productivity at Malaysian electronic industry and they concluded that there are a multiple linear relation between considered factors and productivity. They reported this linear relation as following: Productivity = 657.248 26.561 relative humidity + 1.343 Wet Bulb Globe Temperature Juslen (Juslen and Tenner, 2005) measured employee productivity (speed and quality) in a factory electronic assembly line in the Netherlands after changing the horizontal luminance per work shift between 800 and 1200 lux. Conducting their research in the summer and the winter, they found a significant effect of luminance, such that, the speed of production in the summer was 2.9% higher in the 1200 lux condition than the 800 lux condition. In the winter it was 3.1% higher. No effect of luminance on error rate was found. Juslen (Juslenand Tenner, 2005) showed that in industrial settings employees will systematically choose different levels of lighting throughout the day in summer and winter. Their research participants exhibited different weekly rhythms in their preferred luminance, tending to use lower lighting on Fridays than Thursdays during the summer, and the 110

reverse in winter. Overall lower levels of light were preferred in the summer. The researchers also showed that when factory workers could control the level of light their productivity increased by 4.5%. Similar increases in productivity were observed amongst workers on a manual assembly in an electronics factory. Finally, Niemela (Niemela et al., 2002) concluded that improving thermal climate and lighting conditions, and reducing contaminant concentrations and better lighting conditions for workers in a storage building, could all improve employee productivity. There is some evidence that lighting in schools can impact on the work performance of teachers and pupils via its effect on learning. Whilst learning is an important feature of all workplaces, it is the central activity in schools. Successful student learning involves acquisition of knowledge, and development of skills, behavior and attitudes necessary for students to become socially adept and independent. Teacher performance involves supporting student learning. Most studies involving students have focused on the impact of lighting on school achievement. It is now widely accepted that lighting in the learning environment impacts on students learning experience and school achievement (Dunn et al., 1985; Schneider, 2002; Heath &Medell, 2002). In a report for the US Department of Education Lyons (Lyons, 2000) reviewed the impact of school facilities on a child s education. The report strongly advocates the case for sufficient and adequate lighting that is diffused throughout the room, while noting that, despite its benefits, daylight may increase glare and be unevenly distributed. Lyons and several other researchers have concluded that improved artificial lighting solutions can improve significantly the learning experience. For example, although daylight is considered important (Heschong et al., 2002; Lyons, 2000), Benya (Benya, 2001) reviewed the psychological and physiological benefits of both daylight and artificial light, and concluded that a mix of the two can offer a healthy and cost efficient solution to lighting in schools. Dunn (Dunn et al., 1985) showed that children have strong preferences over the level of lighting. In their study, they built on the premise that eye sensitivity will determine the level and type of lighting that an individual finds comfortable. They found evidence of individual differences, such that students who could concentrate better under bright light reported feeling lethargic when the light was not bright enough, whereas students who preferred dimmer lighting claimed that bright light made them nervous and fidgety. The study concluded that individual preferences may have a profound influence on student school achievement. Despite a wealth of studies about how student performance is affected by lighting conditions, relatively little is known about lighting and teacher performance, and there are also very few published studies that have examined the influence of lighting on teacher and student well-being. One exception is work by Buckley (Buckley et al., 2008), which documents the high turnover rates of school teachers in the US and suggests that the quality of the school facilities (including lighting) can be an important contributory factor in teacher retention levels. 3.5 Acoustic Comfort Jensen (Jensenand Arens, 2005) analyzed acoustic satisfaction in office environments in buildings surveyed by The Center For The Built Environment (CBE). A total of 23,450 respondents from 142 buildings were included in the analysis. Acoustic satisfaction in the CBE survey is a function of satisfaction with both noise and speech privacy. In the database people are significantly more dissatisfied with speech privacy than noise level (P < 0.01). Occupants in private offices are significantly more satisfied with the acoustics than occupants in cubicles (P<0.01). The results shows also that occupants in open office environments are significantly more satisfied with noise level and speech privacy than occupants working in cubicles (P<0.01). Among occupants dissatisfied with acoustics the most prevalent problems are: People talking on the phone, People overhearing private conversations and People talking in surrounding offices. Over 50% of cubicle occupants think acoustics interfere with their ability to get their job done. The same experimental approach demonstrated that noise distraction in open offices at 55 dba has negative effects on the performance of complex office tasks, although it may increase the rate of performance of simpler office tasks (Wyon, 2004). 4. Conclusions In practice, the connection between indoor air and productivity is complicated. Several studies examining different elements of indoor air and their effects on productivity have been carried out. Also in assessing productivity, it should be determined which factors cause alterations in the productivity level. In addition to the indoor environment, there are several different aspects that influence productivity management and organization, job content, motivation, and training. A great deal of research on the health effects of indoor air pollution concentrates on a single pollutant, for example, sulphur dioxide, particulate matter, carbon monoxide or nitrogen dioxide has been conducted. Field intervention experiments in two call-centers demonstrate that the decrement in performance can be larger in practice than it is in realistic laboratory simulation experiments (Wyon, 2004). Negative indoor environmental effects on performance were accompanied by negative effects on general symptoms such as headache and concentration (Wyon, 2004).When the quality of indoor air is altered in real- 111

life situations, other alterations may also take place. For example, changes in customer demand or the implementation of a new production technology may have a dramatic impact on productivity. In such cases, it may be difficult to determine which part of a productivity change is caused by indoor-air aspects and which is the result of other factors. Thus there is the problem of eliminating the other aspects when the effect of alterations on indoor air is evaluated. The most common method of dealing with this problem is the assessment of productivity effects in laboratory settings. They allow many of the affecting aspects to be controlled, such as environmental conditions, the work environment, workload, and, in some cases, also personal factors. In field studies, these factors are much more difficult to control. Another problem related to this situation is the inability to conduct studies in which several aspects of the indoor environment can be taken into account at the same time. It is argued that many studies focus on single aspects of the indoor environment, and, if they deal with multiple aspects, they are often too general and qualitative. Second, it may take some time before the impact of an intervention is realized. An improvement in air quality (eg, reduction in detrimental particles in the air) may not take place immediately after the development actions. This delay may cause problems with productivity assessment, especially if it is done in real premises and not in laboratory settings. This lag may also lead to situations in which the observed alterations in productivity are caused by changes in some other factors, which are just not detected. On the other hand, the changes caused by improvements in indoor air may not have been realized before the assessment of its effects on productivity. Therefore the actual implications cannot be noted until later. Third, differences in jobs can impose another problem for productivity measurement. The effects of changes in indoor air may vary in different jobs. In addition, the generalization of the results is limited in such studies because they are performed for too specific a population. Also many studies on the relationship between IAQ and worker productivity suffer from the Hawthorne effect (Roethlisberger and Dickson, 1939) in which the subject's awareness of being studied influences the outcome. References ASHRAE. (2004). Ventilation for Acceptable Indoor Air Quality. ASHRAE Standard 62.1-2004. Atlanta, GA, American Society of Heating, Refrigerating and Air Conditioning Engineers. Bakó-Biró Z, Olesen B.W. (2005). Effects of indoor air quality on health, comfort and productivity: overview report January 2005. Copenhagen: International Centre for Indoor Environment and Energy, Technical University of Denmark. Benya, J. R. (2001). Lighting for Schools. Paper produced for the National Clearinghouse for Educational Facilities, Washington DC. Billings, J.S. (1893) Ventilation and Heating, New York, The Engineering Record. Buckley, J., Schneider, M. and Shang, Y. (2008). Fix it and they might stay: School facilities quality and teacher retention in Washington DC, Teachers College Record, Vol. 107, Issue 5, pp. 1107-1123. Dunn, R., Krimsky, J. S., Murray, J. B. and Quinn, P. J. (1985). Light up their lives: a review of research on the effects of lighting on children s achievements and behaviour, The Reading Teacher, Vol. 38, Issue 9,pp 863-869. Fanger P.O. (2006). What is IAQ? Indoor Air. Vol. 16, pp328 34. Federspiel C. (2001). Estimating the Frequency and Cost of Responding to Building Complaints In: Spengler, J. Sammet J. and McCarthy, J. eds. Indoor Air Quality Handbook, McGraw Hill Federspiel C. Liu and G. Lahiff. M. (2002). Worker performance and ventilation: of individual data for callcenter workers. Proceeding of Indoor Air, Vol. 22, Issue 6, pp. 796-801. Fisk W.J., D. Black, G. (2011). Benefits and costs of improved IEQ in U.S. offices, Indoor Air 2011.Vol. 21, pp. 357 367. Fisk, W.J., Mirer, A.G. and Mendell, M.J. (2009). Quantitative relationship of sick building syndrome symptoms with ventilation rates, Indoor Air. Vol. 19, pp. 159 165. Fisk W.J., P Price, D Faulkner, D Sullivan, D Dibartolomeo, C Federspiel, G Liu, and M Lahiff, productivity and ventilation rate: analyses of time-series data for a group of call-center workers, (2002).Proceedings of the Indoor Air Conference, Monterey, CA, Indoor Air, Santa Cruz, CA, Vol. 1, pp.790-795. Health and Safety Executive (2005). Management competencies for preventing and reducing stress at work: Identifying and developing the management behaviours necessary to implement the HSE Management Standards. 112

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