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The influence of opening windows and doors on the natural ventilation rate of a residential building.

Introduction

Infiltration of outdoor air is reduced when building envelope tightness is increased, most often for energy conservation purposes. Infiltration occurs due to leakage via cracks and crevices in the building envelope and when building windows and entrances are opened. Indoor-to-outdoor temperature differences, opening size and duration, outdoor wind effects, and window geometry (Jong and Bot 1992) have been shown to directly affect the air exchange rate (AER) of a building (Wallace et al. 2002; Howard-Reed et al. 2002; Jordan et al. 1963). Of these factors, window and door openings can often be controlled by residents and have been shown to significantly affect AERs. Johnson et al. (2004) measured a test house AER with multiple openings (windows and doors) and found the geometric mean to change from 0.76 [h.sup.-1] for no openings to 1.51 [h.sup.-1] for one opening, 2.30 [h.sup.-1] for two openings, and 2.75 [h.sup.-1] for three or more openings. During wind tunnel testing for a scaled building model, Meroney et al. (1995) found an order of magnitude increase in AER when both a door and window were opened compared to window only. In 1945, Hartmann et al. published data showing an increase by a factor of four in AER when windows were opened by a few centimeters in small apartment buildings. Howard-Reed et al. (2002) presented a compilation of data including multiple open areas in two buildings, demonstrating a maximum increase of greater than one air change per hour for the largest opening area (OA) and two to three air changes per hour for multiple window openings under a variety of different window opening combinations. Vatistas et al. (2007) found a significant effect of indoor-to-outdoor temperature difference on AERs in a building where automatic doors cycled between the open and closed positions. Limited data exists for door openings of specific frequency. The data presented here provides this information for a specific residential building and a direct comparison to the natural ventilation rate cause by opening a window to different heights.

Presented here are residential AERs for an unoccupied research test house (RTH) in the case of a window with multiple OAs and a repeatedly opened exterior door. Measured AERs are independently discussed for each dataset due to the differences in measurement time of year and changes made to the building leakage area between 2000 and 2005 when the window and door data acquisition respectively occurred. The AER ratio (fully open versus fully closed) for the two datasets are compared as a means of determining the most effective method to increase the relative AER in a residential building and the primary parameters that impact residential natural ventilation. These data points are important as they directly impact the use of natural ventilation in existing standards, such as ASHRAE 62.2 (ASHRAE 2007), which defines ventilation requirements for low-rise residential buildings. The continued development of existing standards relies on data that include consideration of all factors impacting the natural ventilation rate. The datasets presented do not include a discussion of seasonal variation due to the time frame of the measurements.

[FIGURE 1 OMITTED]

Methods

Measurements were acquired in the U.S. EPA RTH located in Cary, NC, shown in Figure 1. The RTH is a detached single-floor residential property with a floor area of approximately 121 [m.sup.2] (1300 [ft.sup.2]) and a volume of 292.6 [m.sup.3] (10,330 [ft.sup.3]) excluding the garage, crawlspace, and attic. The RTH is surrounded by dense tree cover on the SE-S-SW sides, and moderate to no tree cover on the W-N-E sides, as shown an overhead view in Figure 2 (Google 2010). The surrounding trees are nominally four times the height of the RTH. Outdoor wind speeds were measured by a raised metrology tower using a Vaisala anemometer with a calibrated uncertainty of [+ or -]0.20 [ms.sup.-1] (0.66 ft.[s.sup.-1]).

The tracer gas decay method with sulfur hexafluoride (S[F.sub.6]) was used to measure the building AER using concentration measurements every 6 min, with injection via Teflon tubing from a tank located in the attached garage. A Bruel & Kjaer model 1302 (B&K 1302) infrared photo acoustic multigas analyzer was used to sample the real-time air concentrations of S[F.sub.6] in the den, master bedroom, front middle bedroom, and front corner bedroom. This measurement system has an accuracy of [+ or -]25.0% and a precision of [+ or -]5.0%. S[F.sub.6] was injected in the hallway near the return air grill and distributed throughout the house by the air handler, ceiling fans, and auxiliary fans used for additional mixing.

[FIGURE 2 OMITTED]

Window

Tracer gas concentration data was acquired for the window open events during warmer outdoor conditions of June and July, 2000. The scenario involved the opening of a window in the RTH den, indicated at the top of Figure 1. For a measure of building leakage during window AER data acquisition, blower door testing was conducted one month after measurements providing a value of 14.5 [ACH.sub.50], indicating a fairly leaky building envelope as discussed by Sherman and Chan (2004). This can be compared to the median values of 6 and 9 across 33 residential buildings in two climate zones for Madison and Knoxville, respectively (Antretter et al. 2007). As shown in Figure 2, the outdoor wind direction was predominantly from the southwest during data collection (raw data from Weather Underground 2010). Effects of low to moderate outdoor wind speeds on the RTH AER were not anticipated since the open window was located in the back of the house adjacent to the predominant tree cover.

Tracer gas injection occurred every 6 h, for a total of 65 injection cycles. AER calculations incorporate a 2.5-h time frame, beginning 1 h after measured peak concentrations, repeating every 6 h following injection of S[F.sub.6] throughout the duration of the experiments. Five different window openings were used (width 89 cm [35 in.], height 2.5, 5, 10, 20, and 40 cm [1, 2, 4, 8, and 16 in.]), corresponding to 226, 452, 903, 1806, and 3613 [cm.sup.2] [35, 70, 140, 280, and 560 [in.sup.2]] OAs, respectively) in addition to the closed window condition. For context, Offermann (2009) showed that 108 occupied homes in California had a median window opening of 46 [ft.sup.2]-hrs, equivalent to 1765 [cm.sup.2] of OA for an entire day, with a wide range and seasonal variation. Outdoor temperatures were measured using a local outdoor temperature sensor, and indoor temperatures were maintained at 22[degrees]C (72[degrees]F) by the HAC system using the "auto" setting during window related AER data acquisition. The RTH does not have mechanical ventilation capability. Outdoor wind velocities were recorded during this measurement period, although measured magnitudes were frequently on the order of the measurement system uncertainty (average measured value 0.19 [ms.sup.-1] [0.62 ft.[s.sup.-1]], combined measurement uncertainty [+ or -]0.20 [ms.sup.-1] [0.66 ft.[s.sup.-1]]). It is anticipated that these local velocity measurements are directly affected by the surrounding tree cover that acts as a natural wind barrier. The hourly mean wind speed reported at the local Raleigh Durham International Airport (RDu) airport, located ten miles north of the RTH, during the same time period was 3.4 [ms.sup.-1] (11 ft.[s.sup.-1]), which is suggestive of a tree cover impact on locally measured wind speed, although there was also a poor correlation in time between wind speeds at the two locations ([r.sup.2] = 0.20, representing the square of the correlation). Local wind and temperature measurements were recorded every 5 min.

Door

AERs were acquired for a series of door opening frequencies in late April and early May of 2005. The main entrance of the RTH was used, as indicated at the bottom of Figure 1, located on the most northern side of the RTH. The door has nominal dimensions of 90 cm x 200 cm (35 x 80 in.), resulting in an open area of 18,000 [cm.sup.2] (2800 [in.sup.2]), approximately five times the largest window open area. As shown in Figure 3, during data acquisition, most of the wind was from the NNE and SSW directions as reported by the local RDU airport. While the quantitative impact of local wind conditions on door opening AER is unknown, it is possible that outdoor wind conditions raised the indoor-to-outdoor pressure difference.

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]

For each test, the door was opened for an average of 6.2 sec at a steady rate of 3, 4, 6, 12, and 60 openings per hour, respectively. The time in which the door remained open was recorded by a boolean switch and data logger. An effort was made to open and close the door in a normal manner of building entry or exit. To provide a measure of AERs, the RTH was injected with S[F.sub.6], followed by 20 to 30 min of HAC recirculation fan use to mix the gas throughout the structure, after which point the HAC system was turned off for the remainder of the test. Tracer gas mixing was followed by 2 h of door openings, 2 h of closed-door conditions, 2 h of additional door opening, and a final 2 h of closed-door conditions, as shown in Figure 4. In this way, an injection of tracer gas provided four measures of AER due to an opening and closing door (based on an hourly AER analysis) and another four measures of building AER during closed-door conditions. AERs are based on tracer gas decay measurements in six rooms of interest. Indoor-to-outdoor temperature differential was relatively modest. For this reason, the HAC system was not used during door AER testing aside from the initial mixing period as discussed.

Results and discussion

Window

AERs during open-window conditions were found to be dependent on multiple parameters. Figure 5 presents the correlation coefficient (r), determined using Equation 1, between the AER and the measured parameters, including outdoor temperature (air exchange due to differences between the indoor and outdoor air densities), window OA, time of day, and outdoor wind speed:

r = [1 / [n - 1]] [n.summation over (i=1)] ([[x.sub.i] - [bar.x]] / [s.sub.x])([[y.sub.i] - [bar.y]] / [s.sub.y]), (1)

where n is the number of data points, x and y are the datasets for comparison, s is standard deviation, and an over bar represents the mean. Similar to results presented by Howard-Reed et al. (2002), the outdoor-to-indoor temperature difference had the greatest effect on the AER. While window OA did affect the AER, it was not as significant as outdoor-to-indoor temperature difference. Cross correlations, such as hour of day with outdoor temperature, are not considered here. Window OA, hour of day, and wind speed affected AERs to a lesser degree. The increase in AER with increasing indoor-to-outdoor temperature difference supports the existing findings that open windows can be used as a means of increasing natural residential ventilation, although Offermann (2009) showed that in California, occupants are less likely to open windows during periods of increased indoor-to-outdoor temperature difference.

[FIGURE 5 OMITTED]

[FIGURE 6 OMITTED]

Room specific AERs were calculated from time-dependent tracer gas decay measurements. Figure 6 shows the AER in individual rooms for both the window fully open (3613 [cm.sup.2] [560 [in.sup.2]] window OA, single window in den) and closed conditions. While the AER in the den is 5% greater than the mean of all four rooms due to its open window, this 5% value is still significantly less than the individual room standard deviation (0.08 [hr.sup.-1], or about 20%), so it is reasonable to consider individual room results as an indicator for the whole building AER, excluding the crawlspace, attic, and garage, which are not considered. The high mixing level is likely due to the building interior doors being open during testing and the intermittent use of the HAC house fan associated with seasonal cooling.

[FIGURE 7 OMITTED]

The direct effect of outdoor temperature is seen in Figure 7a, where AERs are presented for a series of outdoor temperature bins. As expected, increased deviation from indoor temperature settings (22[degrees]C [72[degrees]F]) resulted in the greatest AER.

As discussed previously, the wind speed had a reduced correlation with the RTH AER, given in Figure 7b, when compared to that of the outdoor-to-indoor temperature difference. To remove the effects of wind speed on AER in the fully closed scenario, exchange rates are corrected for outdoor wind speed using the empirical model of Guo et al. (1995) based on the ASHRAE Handbook (ASHRAE 2009) flow rate relationships, given in Equation 2, with results presented in Table 1 along with uncorrected measurements during open window conditions:

N = A + B[DELTA]T + Cv, (2)

where N is the AER ([hr.sup.-1]), v is the outdoor wind speed in [ms.sup.-1], and A, B, and C are building specific values, given for the EPA RTH as A = 0.184 [+ or -] 0.005, B = 0.0129 [+ or -] 0.004, and C = 0.0882 [+ or -] 0.0030. These values for A, B, and C are only appropriate for use in the RTH under fully closed conditions, as they are directly dependent on the building open area and will vary if windows or doors are opened.

While an increase in AER is seen between the smallest and largest window OAs, the pattern is not always consistent with each step increase in window size. This is likely due to local weather effects and the resulting number of measurements across the variable ranges.

Percent increases in AER shown in Table 1 are similar to those of Johnson et al. (2004), where a near doubling of the building AER was found for a single building opening. Results are of the same order as AERs presented by Howard-Reed et al. (2002), who found an AER increase from 0.30 to 0.56 between a 0 [cm.sup.2] and 3822 [cm.sup.2] (560 [in.sup.2]) window OA case in a California house. These AERs can be compared to those reported by Guo et al. (1995), who measured the air change rate in the EPA RTH with all windows open under two separate occasions in October of 1989 (reported average outdoor temperature of 21[degrees]C [70[degrees]F]) and found AER values of 2.06 and 4.20 [h.sup.-1] under wind speeds of 0.33 and 0.83 [ms.sup.-1] (1.1 and 2.7 ft.[s.sup.-1]), respectively.

Door

AER increased with increasing door opening frequency, as shown in Figure 8. Due to changes made to the RTH to reduce leakage prior to AER measurements for door openings (see Mosley et al. 2002), the results are normalized by AERs from the case of a fully closed door. The building AER rate increase is minimal for three, four, and six door openings per hour, increasing to nearly 400% of the closed-door scenario in the living room when the front door is opened every minute, as seen in Table 2. This door opening frequency is not realistic for the residential environment but may be more prominent in population dense buildings, such as high-rise complexes. AERs would be expected to differ for population dense properties due to mechanical ventilation, stack effects, and infiltration associated with revolving doors, which are often employed for control over building AERs.

[FIGURE 8 OMITTED]

While the AERs between the window and door datasets cannot be directly compared due to differences in building leakage areas, a comparison of the AER ratios is considered. As the door opening frequency approaches 60 [hr.sup.-1], the RTH-averaged AER doubles when compared to the fully closed scenario. The ratio of fully open to fully closed conditions for the window, shown in Figure 6, is of the same order but slightly less than that of the high-frequency to fully closed door AER ratio, shown in Figure 8. This is somewhat surprising as the total area-open time of the window (when fully opened) is nearly twice that of the door (during the greatest opening frequency) due to its constantly opened state. It is possible that the slightly greater AER for the door opening scenario at the largest opening frequency is due to local weather effects associated with heavy tree cover near the den window and the minimal tree cover by the RTH front door. Another potential explanation for an elevated AER at high frequency is the motion of the door itself, which, due to the low-inducing motion alone, may act to increase air transport between the indoor and outdoor environment.

Conclusions

AERs were found to be affected by physical processes with the greatest impact occurring during the opening of a residential window when indoor-to-outdoor temperature differences are at a maximum. For the door opening scenario, a measurable effect of door opening on the AER was not seen until the door open frequency was increased to 12 openings per hour. These data indicate that open windows are a more effective method of increasing natural residential ventilation rates compared to the impact of continuously opening doors, although local parameters have a significant impact on the final value. This information is invaluable in the estimation of natural ventilation rates from natural physical processes of a residential building.

DOI: 10.1080/10789669.2011.585423

References

Antretter, F., A. Karagiozis, A. Ten Wolde, and A. Holm. 2007. Effects of air leakage of residential buildings in mixed and cold climates. Proceedings, Thermal Performance of the Exterior Envelopes of Whole Buildings X: U.S. Department of Energy, Oak Ridge National Laboratory: Buildings X Conference, Atlanta, Ga. American Society for Heating, Refrigerating, and Air-Conditioning Engineers, Inc.

ASHRAE. 2007. ASHRAE Standard 62.2, ventilation and acceptable indoor air quality in low-rise residential buildings, Atlanta, GA: American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc.

ASHRAE. 2009. Handbook of Fundamentals, pp. 16.13-16.15. Atlanta, GA: American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc.

ASTM. 2006. E741 Standard test method for determining air change in a single zone by means ofa tracer gas dilution. West Conshohocken, PA: American Society for Testing and Materials.

Google. 2010. http://maps.google.com/.

Guo, Z., L.E. Sparks, and M.R. Bero. 1995. Air exchange rate measurements in an IAQ test house. EPA/AWMA Conference, 'Engineering Solutions to Indoor Air Quality Problems', Research Triangle Park, NC, July 24-26, 1995.

Hartmann, P., I. Pfiffner, and S. Bargetzi. 1945. Results of air change rate measurements in Swiss residential buildings. 1978 Technical Translation NRC/CNR TT-1945, Ki Klima Kalte Ingenieur, Sonderdruck, Switzerland.

Howard-Reed, C., L.A. Wallace, and W.R. Ott. 2002. The effect of opening windows on air change rates in two homes. Journal of Air & Waste Management Association 52:147-59.

Johnson, T., J. Myers, T. Kelly, A. Wisbith, and W. Ollison. 2004. A pilot study using scripted ventilation conditions to identify key factors affecting indoor pollutant concentration and air exchange rate in a residence. Journal of Exposure Analysis and Environmental Epidemiology 14:1-22.

Jong, T., and G.P.A. Bot. 1992. Air exchange caused by wind effects through (window) openings distributed evenly on a quasi-infinite surface. Energy and Buildings 19:93-103.

Jordan, R.C., G.A. Erickson, and R.R. Leonard. 1963. Infiltration measurements in two research houses. ASHRAE Journal 5:344-50.

Meroney, R.N., D.E. Neff, and J.B. Birdsall. 1995. Wind-tunnel simulation of infiltration across permeable building envelopes: energy and air pollution exchange rates. 7th International Symposium on Measurement and Modeling of Environmental Flows, San Francisco, CA.

Mosley, R.B., and C. Whitfield. 2002. The influence of building features on air exchange rate and particulate penetration. Proceedings of Indoor Air 2002, Monterey, CA.

Offermann, B. 2009. Ventilation and IAQ in new homes with and without mechanical outdoor air systems. Proceedings of Healthy Buildings 2009, Syracuse, NY.

Sherman, M.H., and R. Chan. 2004. Building airtightness: Research and practice. report no. LBNL-53356, Lawrence Berkeley National Laboratory, Berkeley, CA.

Vatistas, G.H., D. Chen, T.F. Chen, and S. Lin. 2007. Prediction of infiltration rates through an automatic door. Applied Thermal Engineering 27:545-50.

Wallace L.A, S.J. Emmerich, and C. Howard-Reed. 2002. Continuous measurements of air change rates in an occupied house for 1 year: The effect of temperature, wind, fans and windows. Journal of Exposure Analysis and Environmental Epidemiology 12:296-306.

Weather underground. 2010. http://www.wunderground.com/ history/airport/KRDu/.

Received December 15, 2010; accepted April 18, 2011

David Marr, PhD, Member ASHRAE, is Mechanical Engineer, and Post-Doc. Mark Mason is Environmental Scientist. Ron Mosley, PhD, is Physicist. Xiaoyu Liu, PhD, is Environmental Scientist.

David Marr, * Mark Mason, Ron Mosley, and Xiaoyu Liu

U.S. EPA, 109 TW Alexander Dr., Research Triangle Park, NC, USA

Corresponding author e-mail: david.marr@carrier.utc.com
Table 1. RTH AER([hr.sup.-1]) measured in the master bedroom
due to an open window, indoor temperature HAC setting =
22 [degrees]C (72[degrees]F), cooling mode. Data format: AER, number of measurements (n), one standard deviation.

 Indoor-to-outdoor temperature
 difference, [degrees]C([degrees]F)

Den window OA, 0-2 2-4 4-6
[cm.sup.2] (32-35.6) (35.6-39.2) (39.2-42.8)
([in.sup.2])

0 0.17, 6, 0.03 0.20, 1, NA (b) 0.28, 3, 0.02
0 (a) 0.15, 6, 0.03 0.20, 1, NA 0.26, 3, 0.02
226 (35) 0.11, 1, NA NA, 0, NA 0.40, 2, 0.02
452 (70) 0.19, 3, 0.03 0.23, 1, NA 0.27, 1, NA
903 (140) 0.22, 3, 0.03 0.27, 1, NA 0.34, 1, NA
1806 (280) 0.32, 1, NA NA, 0, NA 0.45, 1, NA
3613 (560) 0.38, 2, 0.06 0.42, 3, 0.06 0.47, 1, NA

 Indoor-to-outdoor temperature
 difference, [degrees]C([degrees]F)

Den window OA, 6-8 8-10
[cm.sup.2] (42.8-46.4) (46.4-50)
([in.sup.2])

0 0.31, 2, 0.03 0.35, 1, NA
0 (a) 0.27, 2, 0.01 0.31, 1, NA
226 (35) NA, 0, NA 0.55, 2, 0.02
452 (70) 0.24, 1, NA 0.34, 1, NA
903 (140) NA, 0, NA NA, 0, NA
1806 (280) NA, 0, NA 0.67, 2, 0.02
3613 (560) 0.61, 1, NA 0.73, 2, 0.01

(a) Corrected for outdoor wind speed.

(b) NA = not available.

Table 2. AER ([hr.sup.-1]) by room for door openings by
frequency. Reported values: average, standard deviation.

 Zone of measurement

 Front
Door openings, Middle Master corner
[hr.sup.-1] Hall bedroom bedroom bedroom

3 0.11,0.03 0.10,0.01 0.10, 0.02 0.10,0.02
0 (a) 0.10,0.02 0.10,0.02 0.10, 0.02 0.10,0.02
Normalized 1.11 1.02 1.00 0.95
4 0.23, 0.01 0.22, 0.02 0.23, 0.02 0.22, 0.01
0 (a) 0.20, 0.01 0.22, 0.02 0.20, 0.02 0.21,0.01
Normalized 1.15 1.02 1.13 1.08
6 0.14,0.01 0.14,0.02 0.14, 0.01 0.14,0.01
0 (a) 0.14,0.02 0.13,0.03 0.13,0.02 0.13,0.03
Normalized 0.99 1.07 1.09 1.06
12 0.15,0.02 0.16,0.04 0.16, 0.02 0.15,0.02
0 (a) 0.11,0.02 0.12,0.02 0.12, 0.01 0.12,0.01
Normalized 1.36 1.30 1.33 1.27
60 0.27, 0.06 0.22, 0.04 0.22, 0.02 0.22, 0.02
0 (a) 0.10,0.02 0.16,0.03 0.16, 0.02 0.16,0.03
Normalized 2.61 1.40 1.42 1.45

 Zone of measurement

Door openings, Living RTH
[hr.sup.-1] Den room average

3 0.10,0.03 0.12, 0.03 0.10
0 (a) 0.10,0.03 0.10, 0.03 0.10
Normalized 0.99 1.15 1.03
4 0.21,0.03 0.23, 0.02 0.22
0 (a) 0.20, 0.02 0.20, 0.01 0.20
Normalized 1.04 1.17 1.09
6 0.13,0.02 0.15,0.01 0.14
0 (a) 0.15,0.02 0.13,0.03 0.13
Normalized 0.89 1.15 1.03
12 0.15,0.03 0.17, 0.04 0.16
0 (a) 0.11,0.00 0.11,0.01 0.12
Normalized 1.33 1.62 1.37
60 0.26, 0.03 0.32, 0.06 0.25
0 (a) 0.14,0.02 0.08, 0.05 0.13
Normalized 1.87 3.97 1.90

(a) Acquired during conditions of test in immediately preceding
row. RTH averaged AER values were computed using a volume
weighted approach.
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Author:Marr, David; Mason, Mark; Mosley, Ron; Liu, Xiaoyu
Publication:HVAC & R Research
Geographic Code:1U9CA
Date:Jan 1, 2012
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