Indoor air quality of non-residential urban buildings in Delhi, India

Indoor air quality of non-residential urban buildings in Delhi, India

International Journal of Sustainable Built Environment (2017) xxx, xxx–xxx H O S T E D BY Gulf Organisation for Research and Development Internatio...

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International Journal of Sustainable Built Environment (2017) xxx, xxx–xxx

H O S T E D BY

Gulf Organisation for Research and Development

International Journal of Sustainable Built Environment ScienceDirect www.sciencedirect.com

Original Article/Research

Indoor air quality of non-residential urban buildings in Delhi, India Arindam Datta a,⇑, R. Suresh a, Akansha Gupta b, Damini Singh b, Priyanka Kulshrestha b a

Center for Environmental Studies, Earth Sciences and Climate Change Division, The Energy and Resources Institute, New Delhi, India b Department of Resource Management and Design Application, Lady Irwin College, University of Delhi, New Delhi, India Received 3 November 2016; received in revised form 2 June 2017; accepted 1 July 2017

Abstract Nearly 30% of total population and over 2 million students of Delhi spent above 1/3rd of their daily time in different office buildings and educational institutions of Delhi, of which the ambient air quality is reportedly worst in the globe. However, studies on indoor air quality of non-residential buildings are scarce in India. Present study was conducted in two office buildings and one educational building in Delhi during pre-monsoon. CO2, PM2.5 and VOCs were measured inside each building at every 5 min interval between 9:30 AM and 5:30 PM for 5 days every week. The average CO2 concentration in both office buildings (1513 ppm and 1338 ppm) was recorded much higher than the ASHRAE standard. Ductless air-conditioning system couple with poor air-circulation and active air-filtration could be attributed to significantly higher concentration of PM2.5 in one of the office buildings (43.8 lg m3). However, there was significant variation in the concentration of different pollutants at different locations in a building. Among different non-residential buildings, significantly lower concentration of all pollutants was recorded in the educational building (CO2: 672 ppm; PM2.5: 22.8 lg m3 and VOC: 0.08 ppm). Total hazard ratio analysis ranks one of the office buildings as most hazardous to workers health compared to others. Ó 2017 The Gulf Organisation for Research and Development. Production and hosting by Elsevier B.V

Keywords: Indoor air quality; Non-residential building; PM2.5; Carbon dioxide; Total VOCs; Delhi

1. Introduction People spend more than 90% of their daily life in indoor environments either inside office, school, college, commercial, industrial buildings or inside residential houses. Study suggests that the concentration of pollutants in the indoor environment is much higher than that of the urban outdoor ambient environment with average traffic (EPA Indoor air quality, 2013). However, the indoor air quality received ⇑ Corresponding author. Fax: +91 11 24682144.

E-mail address: [email protected] (A. Datta). Peer review under responsibility of The Gulf Organisation for Research and Development.

considerably less attention than that of the outdoor air quality until last decade. Poor indoor air quality can be especially harmful to vulnerable groups such as children, elderly, and those with cardiovascular and chronic respiratory diseases viz. asthma. Apart from its profound effect on health, the indoor air pollution reduces the comfort, and productivity of occupants of the building. On the other side, the indoor air quality (IAQ) in educational and office buildings may affect the health of the children and workers as well as indirectly affect their learning ability and productivity. Surprisingly, given the magnitude of the educational institutional population, information on IAQ in educational buildings is very limited.

http://dx.doi.org/10.1016/j.ijsbe.2017.07.005 2212-6090/Ó 2017 The Gulf Organisation for Research and Development. Production and hosting by Elsevier B.V

Please cite this article in press as: Datta, A. et al. Indoor air quality of non-residential urban buildings in Delhi, India. International Journal of Sustainable Built Environment (2017), http://dx.doi.org/10.1016/j.ijsbe.2017.07.005

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The particulate matter (especially PM2.5) concentration in the ambient air of Delhi is the highest among 1600 cities around the world (World Health Organization, 2014). Most outdoor pollutants enter into the indoor environment and their concentration increases many folds owing to inefficient air-circulation. Long-term exposure to PM2.5 is associated with reduction in average life-expectancy from 8.5 to 20 months and increase in the long-term risk of cardiopulmonary mortality by 6–13% per 10 mg m3 of PM2.5 (Krewski et al., 2009). This indicates the importance of the assessment of IAQ of different buildings in the capital city. However, apart from the outdoor air, there are other factors which affect the IAQ e.g. cooking, cleaning products, different building materials like plywood, flame retardants, aerosol pesticides and even the exhaled air contains significant amount of carbon dioxide (CO2). Concentrations of CO2 inside buildings range from outdoor levels up to several thousand parts per million (Persily and Gorfainm, 2008). The indoor CO2 level is one commonly used approach which has been referred as an IAQ indicator (Lin and Deng, 2003) for inefficient and ill-functioning air-filtration system. Effects of CO2 on human health range from physiologic (e.g., ventilatory stimulation) to toxic (e.g., cardiac arrhythmias and seizures) and anaesthetic (significantly depressed CNS activity) to lethal (severe acidosis and anoxia) (Rice, 2004). Prior research has documented direct human health effects of CO2 at concentrations much higher than those found in normal indoor settings (Lipsett et al., 1994). Signs of asphyxia are evident when the atmospheric O2 is 16% (HSDB, 2003). Kajtar et al. (2006) have reported adverse impact of CO2 concentration between 2180 and 5455 ppm on proof reading ability of exposed persons from a research trial conducted in Hungary. In a controlled research study in USA, Satish et al. (2012) have reported that at 1091 ppm CO2, decision-making performance was significantly diminished on six of nine metrics compared to the 600 ppm concentration. When the concentration was increased to 2730 ppm CO2, decision making performance was further reduced to seven of nine metrics of performance, with percentile ranks for some performance metrics decreasing to levels associated with marginal or dysfunctional performance. This indicates that direct adverse effects of CO2 on human decision making performance may be economically important. On the other side, the chronic health effects provoked by VOCs can be classified as either non-carcinogenic or carcinogenic. The carcinogenic effects of VOCs are primarily visible in lung, blood, liver, kidney and biliary tract. The International Agency for Research on Cancer (IARC) has classified benzene as a Group 1 human carcinogen, while other VOCs such as tetrachloroethylene and ethylbenzene are considered as probable carcinogens for humans (ACS, 2016). Additionally, some VOCs may be associated with the symptoms of asthma, different allergic reactions, mucous membrane irritation and diseases of the central nervous system symptoms. The indoor

concentrations of many VOCs were recorded higher than outdoor concentrations due to indoor sources (Weisel et al., 2008). In another study, in different naturally ventilated academic buildings in Italy, Gennaro de et al. (2013) have concluded that the indoor concentration of most of the VOCs are significantly higher than their outdoor concentrations during the activity hours. Significantly higher concentrations of different VOCs (e.g. benzene, toluene, ethyl benzene, xylene etc.) than their standard ambient concentrations were recorded in the fine arts faculty building of Anadolu University, Turkey (Can et al., 2015). However, in spite of their reported higher concentrations in the indoor environment, there are not many studies on the indoor concentrations of VOCs in office and academic buildings. VOCs are a broad range of compounds with boiling points from less than 0 °C to about 400 °C. Several 100 compounds of VOCs are present in the indoor air (WHO, 1989). The energy conservation measures in the office buildings rapidly increased the use of synthetic building materials. Building materials like vinyl floor, particle board, sealant, gypsum board, carpet, paint, varnish, thermal insulation, etc. also act as sources of different VOCs inside the office building. Apart from these, building elevator and ventilation system also act as the source of VOCs (C13 to C18 alkanes and broad spectrum VOCs respectively) in the office buildings (Wolkoff et al., 1995). Additionally, technological advancement increased the use of modern machines inside the office premises. Studies suggest that the use of electronics equipments (ECMA Standardizing Information and Co, 2006), PCBs (Kemmlein et al., 2003), notebook computer (Hoshino et al., 2003), Desktop computer/VDT (Nakagawa et al., 2003), copier machine (Leovic et al., 1998), carbon paper, copier paper, power cable (Shields and Weschler, 1992), correction fluid, cleaning agent, etc. in offices are indoor sources of VOCs. Commercial primary energy consumption in India has grown by about 700% in the last four decades (UNDP, 2011). The commercial and institutional building area in India is expected to grow from 659 million m2 in 2010 to 1900 million m2 in 2030 (Kumar, 2011). This increases the energy demand for the sector. Heating and cooling of the outside air for the comfort of the building occupants, requires a significant amount of energy. Considerable energy saving is possible by minimizing the outdoor air used for ventilation. However, this deteriorates the indoor air quality if active air-filtration systems are not installed. This leads to compromising the health and comfort of the occupants (Turiel et al., 1983). The indoor air quality of the office and institutional buildings thus become the subject of much attention. Daisey et al. (2003) have reported strong positive association between the mixing ratio of CO2 and ventilation level in classrooms in an institutional building in USA. They have reported asthma and ‘sick building syndrome’ among the students. In another study, from Denmark, Wargocky and Wycon (2013) have reported the CO2 as 1092 ppm during the working hours

Please cite this article in press as: Datta, A. et al. Indoor air quality of non-residential urban buildings in Delhi, India. International Journal of Sustainable Built Environment (2017), http://dx.doi.org/10.1016/j.ijsbe.2017.07.005

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in the institutional buildings due to low level of ventilation. De Guili et al. (2012) have also reported very high concentration of CO2 inside the academic buildings of Italy due to insufficient air exchange through windows. On the other side, in a naturally ventilated educational building in Chennai, India, it was reported that the PM10 and PM2.5 concentrations inside the classrooms are often higher than the national ambient air quality standard (Chitra and Nagendra, 2012). There are number of reports on the indoor air quality in office building and academic buildings from different parts of the world (Jaakkola et al., 1991; Kats, 2006; Pansoni et al., 2010; Pegas et al., 2010., 2011; Dorizas et al., 2015). However, there are not many studies on the IAQ of the office and academic buildings in India (Habil et al., 2013; Samal et al., 2013; Indraganti et al., 2014). In the preparation of road map for IAQ in India, Goyal et al. (2012) have concluded that there is a need for a thorough assessment to identify the gaps in present research space of indoor air quality related to pollutant emission, health risk and exposure at the academic level. As mentioned earlier that Delhi is the most polluted city in the world and on the other hand, Delhi is the second largest populated city in India, it becomes important to measure the IAQ of different office and academic buildings around the city to assess the health risk of working young population of the capital city. The aim of the present study is to characterize IAQ in different office and academic buildings located in densely build-up area of New Delhi, India. PM2.5, CO2 and VOCs were measured simultaneously in the indoor environment of different types of buildings during the pre-monsoon season. Integrated IAQ Total Hazardous Ratio Indicator (THRI) was introduced to compare the health effects of different studied indoor environments. 2. Materials and methods The study was conducted in three non-residential (two commercial/official (O1 and O2) and one educational/office (A1)) buildings in Delhi during the month of June–July 2015 (before the onset of monsoon). In general, monsoon starts in Delhi during late July and prevails till September. The ambient temperature of Delhi reaches minimum (13 °C) during the month of January and maximum during May (44 °C). The relative humidity in the ambient atmosphere varies between 14% (During April–May) and 70% (During August–September). During the month of June–July, both ambient temperature (36–40 °C) and relative humidity (30–55%) over Delhi remain at optimum level, so the study was conducted during the period to avoid extreme weather conditions. The density of buildings in Delhi is higher in the central, eastern and south-eastern sides covering Central, New Delhi, West, South, South-East, East, Shahdara, NorthEast and part of the North districts compared to other areas of the state. Office buildings of the state are mainly located in the Central, New Delhi, East and South-east

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Delhi. During the present study three buildings (O1, O2 and A1) were selected one each in Central, New Delhi and East Delhi (Fig. 1). Ambient air quality over the study area remains as ‘poor’ in most of the period of the year as indicated by SAFAR air quality data (http://safar.tropmet. res.in/). Buildings O1 and A1 were located near busy roads while building O2 was inside a commercial complex, away from busy traffic (Fig. 1). All selected buildings were brick-walled with concrete floor assembly. All buildings were 2–5 years old. All three buildings were having airconditioning systems in operation during the period of sampling. Building O1 was a three storey building and monitoring was conducted in all floors (F1, F2, F3) of the building, while the building O2 was a 10 storey building and monitoring was conducted at three different places (B1, B2, B3) in the 8th floor (Fig. 2), as this floor was highly crowded among other floors in the building. The educational building (A1) was located near the road, but there was adequate green cover around it. All three buildings were having regular office activities like using desktop computers, photocopier, printers etc. during the monitoring period. 8 h (9:00–18:00 h) monitoring of PM2.5, VOC and CO2 was conducted every day in each building during the study period using low volume sampling pump (Model 224PCXR8, SKC Inc., USA) with PEM impactor, UltraRAE3000 (RAE Systems, USA) and Q-Track-7575 (TSI, USA) monitor respectively. Indoor concentrations of PM2.5, VOC and CO2 were recorded at every 5 min interval. The air flow rate in the low volume sampling pump, UltraRAE3000 and Q-TRAK was maintained at 1.67, 0.5 and 0.3 LPM during the sampling period. An electronic calibrator was used to calibrate the flow rate of samplers. The difference between the initial and final flow rate was maintained below ±10%. The PEM impactor allows particles with aerodynamic diameter <2.5 mm and thus the pump-impactor assembly can measure PM2.5. Preweighed (XPE Micro analytical balance; Mettler-Toledo, Switzerland), pre-conditioned (glass microfiber filter papers were kept in a desiccator filled with baked silica gel for 24 h before weighing them) 37 mm glass-fibre filter paper (pore size: 1 mm) was used in the impactor and the final weight of the filter paper was measured in the same balance after 8 h sampling period. A field blank filter paper was maintained at each location of sampling on each day. Before taking the final weight of the exposed filter papers, they were kept in a desiccator with baked silica gel for 24 h. The difference of pre and final weight of the exposed filter paper after subtracting the difference of pre and final weight of the field blank filter paper was the PM2.5 concentration in the sampled air volume. All filter weighing was carried out in a controlled environment (temperature: 20–23 °C and RH: 30–40%). The UltraRAE3000 and Q-TRAK were electrochemical sensor based equipment. UltraRAE3000 uses a photoionization detector to measure the total VOCs in the air sample after separation by a gas sampling tube.

Please cite this article in press as: Datta, A. et al. Indoor air quality of non-residential urban buildings in Delhi, India. International Journal of Sustainable Built Environment (2017), http://dx.doi.org/10.1016/j.ijsbe.2017.07.005

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A. Datta et al. / International Journal of Sustainable Built Environment xxx (2017) xxx–xxx

Fig. 1. Delhi district map showing location of sampling buildings.

The operating range of the instrument was 50 ppb to 5000 ppm with a resolution of 50 ppb and 3% accuracy. The instrument was calibrated and certified annually with three-point calibration in the factory (RAE Systems, USA) with standard benzene (5 ppm) and isobutylene (100 ppm). The CO2 measurement range of the Q-TRAK instrument was 0–5000 ppm with ±50 ppm accuracy and 1.0 ppm resolution. Both UltraRAE3000 and Q-TRAK were zero calibrated with zero air (20.9% oxygen/nitrogen; GASCO, USA) before the starting of monitoring on each day. Ambient CO2 concentration was measured continuously outside each building at 5 m height using another Q-TRAK instrument during the measurement period inside the buildings. The data related to number of people in each floor were collected during the sampling period. IAQ Total Hazard Ratio Indicator (THRI) was calculated based on the comparison of the daily ambient concentrations with their respective chronic permissible inhalation level (reference concentrations). Mean reference concentration of VOCs for this study was taken as 0.31 ppm (Gennaro de et al., 2013; Bruno et al., 2008). The reference concentration of PM2.5 was taken as 25 lg m3 (WHO, 2006); whereas, that of CO2 was considered as

1111.4 ppm (Prill, 2000). The hazard ratio (HR) of each compound (i) was calculated by dividing its average concentration by its corresponding reference concentration (RfC), both expressed in same unit: HRi ¼ Ci=RfCi Moreover, the total hazard ratio of each site (THRsite) was calculated to assess the global inhalation exposure risk, for each building separately, as a sum of the single HRi determined for each pollutant measured at the same sample site X THRsite ¼ HRi 2.1. Statistical analysis Daily mean value of each pollutant at each sampling site was used as one replicate for the statistical analysis. SPSS analytical tool (IBM SPSS Statistics 22) was used for the analysis of variance (ANOVA). In cases where the ANOVA results indicated a significant difference among the mean values, Fisher’s Least Significant Difference (LSD) test was employed to identify the sites which are significantly different from others. The significance level was set to 0.05 for both ANOVA and LSD tests.

Please cite this article in press as: Datta, A. et al. Indoor air quality of non-residential urban buildings in Delhi, India. International Journal of Sustainable Built Environment (2017), http://dx.doi.org/10.1016/j.ijsbe.2017.07.005

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S

Fig. 2. Sampling location in different buildings. A: Building O1 (Ground floor); B: Building O1 (First floor); C: Building O1 (Second floor), D: Building O2; E: Building A1. F1 to F3, B1 to B3 and S indicate sampling locations in each building.

3. Results and discussion During the sampling period the average inside temperature of O1, O2 and A1 buildings were 25 °C, 20 °C and 30 °C, respectively. However, the average temperature (28.2 °C) and relative humidity (60%) of the F1 floor of the O1 building was comparatively higher than others dur-

ing the sampling period. This might be attributed to regular opening of the floor door for visitors and close proximity of the building to the metal road. Similarly, average temperature (24.3 °C) and relative humidity (72.9%) were higher at the B1 area of the O2 building during the sampling period due to its close proximity to the floor entry door. Seppa¨nen et al. (2006) have also reported tempera-

Please cite this article in press as: Datta, A. et al. Indoor air quality of non-residential urban buildings in Delhi, India. International Journal of Sustainable Built Environment (2017), http://dx.doi.org/10.1016/j.ijsbe.2017.07.005

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ture variation in different parts of office building during office hours. 3.1. CO2 concentration inside buildings Monitoring the CO2 concentration in the air inside the building is a relatively inexpensive and easy way to address the level of missing of the outside air with the re-circulated air inside a building. CO2 is produced inside the building when people breathe. Each exhaled air contains about 100 times higher CO2 than that in the inhaled. The CO2 concentration in an occupied indoor space indicates whether the building’s air exchange balance is appropriate i.e., whether the optimal amount of filtered outside air is being mixed with air that has been circulating in the building. The American Society of Heating, Refrigerating, and Air Conditioning Engineer Inc. (ASHRAE), recommends that indoor air CO2 levels be less than 645 ppm above the outdoor air concentration of CO2 (ASHRAE, 2002). Average ambient concentration of CO2 outside O1, O2 and A1 buildings during the sampling period of each building was recorded as 445, 414 and 410 ppm respectively. According to the ASHRAE method, the average CO2 concentrations inside O1, O2 and A1 buildings should not exceed 1090, 1059 and 1054 ppm respectively. The study suggests that the average CO2 concentration in the O1 and O2 buildings were much higher than that of the ASHRAE recommendation for each building (Fig. 3). However, the average CO2 concentration inside the A1 building was well within the recommended limit (711 ppm) during the study period (Fig. 3). Well ventilation and lesser number of occupant per unit area (0.07 person m2) at the A1 site, might have facilitated significantly lower CO2 concentration (711 ppm) inside the building compared to the other buildings in the study. Among the O1 and O2 buildings, significantly higher average CO2 concentration was recorded in the former (1514 ppm) during the study (Fig. 3) although the concentration of occupant per unit area was at par in the O1 and O2 sites (0.15 person m2). The time-scale plot of CO2 concentration inside the O1 and O2 buildings shows different pattern (Fig. 4) as the working hours are different in two offices. The office hours in the O1 building was from 9:30 AM to 5:30 PM; whereas, the office hour in the O2 building was from 6:00 AM to 2:00 PM and 2:00 PM to 10:00 PM. The movement of visitors inside the O2 building increases in the afternoon hours, which might have resulted in higher CO2 concentration in all the sampling locations inside the O2 building during the afternoon hours (Fig. 4). The concentration of CO2 (ppm) inside the O2 building followed the order: B2 (1556) > B3(1218) > B1 (1105). Significantly higher concentration of CO2 at the B2 location might be attributed to confined nature of the workplace, whereas significantly lower concentration at B1 might be attributed to comparatively lower density of staff (0.09 person m2) in the area during the sampling period. Again, B1 area was near to the entry of the floor, regular opening of the floor entry door might also have added

to the dilution of the CO2 concentration at this location. On the other side, the time-scale plot represents that the CO2 concentration in different floor of O1 building was increased during the office hours (9:30 AM to 5:30 PM) (Fig. 4). Comparatively lower staff density in F3 might be attributed to lower concentration of CO2 in the floor. In both F2 and F3 floors, the concentration of CO2 reached a peak around 11 AM as all the office staff were inside the office around that time, and then the concentration went down to a day low around 1 PM as that was the lunch time and staff move out of office for lunch. The post lunch concentration of CO2 started to increase after 2 PM and continues till 5 PM. The concentration of CO2 gradually reaches the baseline level (before the starting of the office hours at 9 AM) around 1800 h after the office hour. Among different floors of the O1 building, significantly higher CO2 concentration was recorded in the floor F1, which may attribute to the near proximity of the building to busy road. The hourly pattern of the CO2 concentration in the floor (F1) was not similar to the other two (F2 and F3), indicating clear influence of road on the CO2 concentration. 3.2. PM2.5 concentration inside buildings Apart from higher CO2 concentration, the concentration of PM2.5 was also recorded significantly higher in O1 compared to other buildings during the study period (Fig. 3). In all floors of the building O1, the PM2.5 concentration was recorded more than the WHO guideline value for 24-h period (WHO, 2006). There was no significant difference in average PM2.5 concentration in O2 (22.7 lg m3) and A1 (22.9 lg m3) during the study period (Fig. 3). Ductless air conditioning system was installed at the O1 building, whereas central air conditioning system was installed at the O2 building. It has been studied that the ductless air conditioning system reduces the overall circulation of air in a building compared to that of the ducted central air conditioning system (Landwehr, 2013). This suggests that the ductless air-conditioning system might have lead to comparatively poor air-circulation in the O1 building. Among different floors of the O1 building, air-circulation was comparatively very poor in the F3 floor, as the windows and doors of the floor remained closed throughout the sampling period. On the other hand, air-circulation was comparatively better in the F2 and F1 floor due to frequent opening of the floor doors for the entry of visitors. The building was located aside a busy road in central Delhi, which may have contributed to higher concentration of PM2.5 in the F1 floor (46.7 lg m3), compared to that of F2 (16.7 lg m3). However, ductless air conditioning system was also installed at site A1, but the building was surrounded with green cover and the PM2.5 around the A1 building was comparatively lower than other two sites. These might have resulted into significantly lesser PM2.5 concentration (22.2 lg m3) inside the building compared to the O1 building (Fig. 3). The PM2.5 concentration inside the ducted centrally air conditioned O2 building was significantly different at different sampling

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was recorded in the O1 (Fig. 3). Significantly lower wooden furniture density in the A1 building compare to others might have attributed to lower VOC concentration in that building. Additionally, there was no copier and only one desktop computer and printer was present inside the A1 building compare to large number of computers, printers and copier machines in the O1 and O2 buildings. As mentioned earlier computers and copier machines can be an important source of VOCs in O1 and O2 buildings. A time-series analysis of VOC concentration in different floors of the O1 building indicates that the concentration of VOC was increased in all floors of the building during the afternoon hours (Fig. 5). Use of personal care products and fragrances by the office staffs of the O1 office might have attributed to the increase of VOC concentration in the afternoon. Earlier studies have also suggested that the use of these products gradually increases the VOC concentration in an ill-ventilated room (Wolkoff et al., 1992, 1995). The morning hours dip in the VOC concentration in all floors may attribute to the opening of floor doors for the entry of office staffs. This might have diluted the VOC concentration inside the floor due to temporary increase in ventilation. The VOC concentration was recorded significantly higher in the F3 floor of the O1 building (0.5 ppm) (Fig. 3), which might be attributed to comparatively larger number of newly varnished wooden

Fig. 3. Indoor concentration of CO2, PM2.5 and VOCs in different buildings during the study period. Bar indicates mean of daily samples collected during the sampling period. Error bar indicates standard deviation of the mean. Dotted line indicates the reference concentration of pollutant. Bars followed by a common alphabet are not significantly different at p < 0.05 using Fisher’s least significant difference (LSD) test.

locations inside the floor. Significantly lower concentration of PM2.5 was recorded at B1 (3.8 lg m3) which might be attributed to its close proximity to the floor entry door and as a result the area was well ventilated. On the other side, significantly higher concentration of PM2.5 was recorded at B3 (46.7 lg m3). The sampling area was located completely at the opposite side of the floor entry door and not directly exposed to the door. As the building was centrally air conditioned all windows in the floor was closed. There was no duct of the air-circulation system in the B3 area. These indicate lesser air-circulation at B3 area which might have lead to a trap for the PM2.5 and increased its concentration. A sensitivity analysis of the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) residential indoor model indicates that air exchange rate, deposition rate and penetration factor affect indoor PM2.5 concentration strongly, whereas indoor volume is less sensitive (Deshpande et al., 2009). 3.3. VOC concentration inside buildings Among three buildings, significantly lower VOC concentration (0.08 ppm) was recorded in the A1 building, whereas, significantly higher (0.40 ppm) concentration

Fig. 4. Time-series plot of CO2 inside the O1 building. Each point in the time-series is the mean of 12  22 values collected at 5 min interval over the study period.

Please cite this article in press as: Datta, A. et al. Indoor air quality of non-residential urban buildings in Delhi, India. International Journal of Sustainable Built Environment (2017), http://dx.doi.org/10.1016/j.ijsbe.2017.07.005

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compared to other buildings in the study. This is attributed to significantly higher HRPM2.5 and HRVOC at F3 of the O1 office compared to other study sites. The calculated values of THR at all study sites were much higher than earlier reported study Gennaro et al. (2013) in a school in Italy. 4. Conclusion

Fig. 5. Time-series plot of VOCs inside the O1 building. Each point in the time-series is the mean of 3  22 values collected at 5 min interval over the study period.

Table 1 Total hazard ratio at different study sites. Site

O1

Total O2

Total A1

Location

F1 F2 F3 B1 B2 B3

HRi*

THR

CO2

PM2.5

VOC

1.9c 0.7 b 2.7 d 5.3C 0.7 b 1.9c 0.2a 2.7B 0.9A

1.3 b 1.5c 1.3 b 4.1C 1.0a 1.5c 1.1a 3.6B 0.6A

0.4a 1.6c 1.6c 3.6C 0.2a 1.0 b 0.4a 1.6B 0.3A

3.5 b 3.8 b 5.6 d 12.9C 1.9a 4.3c 1.7a 7.9B 1.8A

THR: Total Hazard Ratio. In a column mean followed by a common alphabet is not significantly different by Fisher’s least significant difference test at p < 0.05. * Mean of 10 data at each site for CO2; mean of 3 data at each site for PM2.5 and mean of 24 data for VOC. Bold value indicates the average HRi and THR for the entire building.

Working people and students spend most of their daytime in different non-residential buildings. It is important to maintain the IAQ in the non-residential buildings from the perspective of maximum output and health of the people working inside the building. Study indicates that the occupant density in the air-conditioned non-residential buildings play vital role in controlling indoor air pollution level inside the building. Significant concentrations of different air pollutants (PM2.5, CO2 and VOC) were recorded in all three buildings under the present study. Study suggests that the indoor concentration of PM2.5 plays a major role in the total hazard ratio of each site and CO2 contributes minor role among three pollutants. Significantly higher THRsite at O1 building indicates immediate action is required to reduce the PM2.5 concentration inside the building. However, apart from the THR, further calculation of cancer risk assessment of VOCs may indicate their specific contribution to the occupant of each building. Detail analysis of individual VOC concentrations is required for that study. This study also indicates that there is a need of regular study of air-circulation inside the air conditioned building to improve its indoor air quality. However, a year-long study of IAQ can support to develop seasonal plan to improve the air quality inside the buildings. References

furniture and wooden cubicles per unit area of the floor during the sampling period than other floors of the building. Additionally, dusting and pesticide spray (aerosols) inside the O1 and O2 offices also attribute to higher concentration of VOCs compared to that in the A1 building. Wolkoff and Wilkins (1994) have reported the presence of branched aldehyde and 2-ketones on the office room dust. The floors were wiped with disinfectants after the lunch hour around 14:00 h, this might have attributed to increase in the VOC concentration in the afternoon hours (Fig. 5). 3.4. Total hazard ratio indicator Total hazard ratio of indoor air pollution at each of the studied location was calculated with the reference concentration of the particular pollutant for daily 8 h exposure. The HR of PM2.5 was significantly higher in the F3 of the O1 building among different pollutants in three different study sites. However, the HR of CO2 was significantly higher at the B2 location of O2 building (Table 1). Average THRsite was significantly higher at the O1 building (3.94)

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Please cite this article in press as: Datta, A. et al. Indoor air quality of non-residential urban buildings in Delhi, India. International Journal of Sustainable Built Environment (2017), http://dx.doi.org/10.1016/j.ijsbe.2017.07.005