UPSTATE NY WEATHERIZATION AND EFFECTS ON INDOOR AIR QUALITY

Transcription

1 UPSTATE NY WEATHERIZATION AND EFFECTS ON INDOOR AIR QUALITY A Thesis Presented to the Faculty of the Graduate School of Cornell University in Partial Fulfillment of the Requirements for the Degree of Master of Engineering by Siddarth Govindarajan May 2014

2 c 2014 Siddarth Govindarajan ALL RIGHTS RESERVED

3 ABSTRACT Energy consumption for buildings account for forty percent of energy consumed in the United States, but this energy consumption can be considerably mitigated through building weatherization, which reduces the leakage flow of indoor air. This study aims to ascertain the effects of weatherization onto indoor air quality. The study measured key physical parameters associated with air quality, including particle number concentrations, particle mass concentrations, and indoor air radon levels, in five homes (three control homes, two case homes) in Ithaca, New York. The homes were sampled twice: pre-weatherization in the fall and winter of 2013, and post-weatherization in the spring of The results show that the weatherization process caused a decrease in the air exchange rate in the weatherized case homes, but the limited sample size makes it difficult to come to conclusions about indoor air quality trends.

4 BIOGRAPHICAL SKETCH Siddarth Govindarajan completed his B.S. in Biological Engineering in the College of Agriculture and Life Sciences at Cornell University. He is currently pursuing his M.Eng. degree in the same program. iii

5 ACKNOWLEDGEMENTS The author would like to thank Denina Hospodsky for her help and mentorship; Dr. Lars Angenent for advising, funding, and feedback; the Angenent Laboratory for resources and feedback; Tompkins County Action for helping to identify weatherization homes; and the home owners who graciously allowed the researches access into their homes for this study. iv

6 TABLE OF CONTENTS Biographical Sketch iii Acknowledgements iv Table of Contents v List of Tables vi List of Figures vii 1 Introduction 1 2 Background Test Environment Materials and Methods Carbon Dioxide Release and Air Exchange Rates Particulate Matter Temperature and Relative Humidity Indoor Air Radon Correlation Analysis Results CO 2 Measurements Particle Numbers Particle Mass Indoor Air Radon Levels Conclusions 23 6 Bibliography 24 v

7 LIST OF TABLES 2.1 Sampling Site characteristics of the five sampled homes Summary of air exchange rate results. Standard deviations are reported in parentheses Summary of particle mass concentration results. Data reported is summation of mass in all four size bins vi

8 LIST OF FIGURES 3.1 Carbon dioxide tank and release timer apparatus An example of linearized carbon dioxide decay with plotted best-fit line for the first decay in the first sampling of Home E. The air exchange rate for this specific event is calculated to be Airborne particle behavior trends with changing particle diameter. Figures adapted from Nazaroff [4] and Thatcher [5] GGOBI software used for determining correlations between measured variables. Correlations can be clearly seen between small and medium particle size bins in this matrix for Home B An example graph displaying carbon dioxide measurements during the first sampling event in Home E Indoor particle counts from the first sampling event in Home E Indoor particle counts for the 0.5 to 2 µm particle size bin. 1 indicates the first sampling event, while 2 indicates the second sampling event. The boxes represent interquartile range, while the error bars represent the range of the data after outlier removal. A P* indicates a significant difference of 0.05, while P** indicates a significant difference of The three control homes, A, B, and C, are denoted by diagonal fillings, while the two case homes, D and E, are denoted by dot fillings Indoor counts for the 2 5 µm particle size bin Indoor counts for the > 5µm particle size bin I/O ratios from the first sample of Home E I/O ratios for the 0.5to2µm particle size bin I/O ratios for the 2to5µm particle size bin I/O ratios for the > 5µm particle size bin Particle mass concentrations for all five homes. Blue lines indicate indoor sampling, while red lines indicate outdoor sampling. Solid lines correspond to the first sampling event, while dashed lines correspond to the second sampling event I/O ratios for particle mass concentrations for all five homes. The first sampling event is shown in blue, while the second sampling event is shown in yellow Range hood temperatures for Home C. Range hood temperatures are correlated with cooking events. The first sampling event is shown in blue, while the second sampling event is shown in yellow Radon distribution for the first sampling event of Home E vii

9 4.14 Radon distribution for all five homes. The AccuStar basement radon level is shown as a red dash. There is no basement reading for A1 due to an error with the test kit viii

10 CHAPTER 1 INTRODUCTION In 2012, nearly forty percent of all United States energy consumption occurred in residential and commercial buildings, mainly for heating purposes [1]. Due to this energy consumption, buildings are also responsible for forty-nine percent of sulfur dioxide emissions, twenty-five percent of nitrous oxide emissions, and ten percent of all particulate emissions [2]. There also exists great potential for reducing this energy consumption via relatively simple practices, such as reducing the air leakage flow in buildings. The United States Department of Energy has established the Weatherization Assistance Programs (WAPs) to mitigate this high energy consumption across the country. These WAPs are carried out on state levels by appointed agencies and employ weatherization techniques, such as crack sealing, insulation, fixture repairs, and a variety of other procedures to reduce air leakage, at a reduced cost to qualifying households. This weatherization results in an average energy cost saving of 20 percent [3]. However, there is some concern that the reduction in ventilation due to weatherization techniques may decrease the quality of indoor air, with regards to the accumulation of airborne particles and mass. This ventilation reduction may also negatively affect human health by increasing exposure time to harmful particulates or pathogens. This study aims to analyze if the reduction of air exchange rates due to the weatherization process decreases indoor air quality in 15 homes (5 control homes, 10 case homes) by measuring physical parameters, including particle number concentrations, particle mass concentrations, and indoor air radon levels. In this thesis, preliminary results from the analysis of five of these homes (3 control homes, 2 case homes) will be presented. 1

11 CHAPTER 2 BACKGROUND 2.1 Test Environment The full study aims to sample fifteen houses in the Northeastern United States, but in this preliminary analysis, five houses were chosen for indoor air quality assessment sampling in Ithaca, New York. Sampling was conducted twice in events that were scheduled between three and five months apart for each home. The five homes were first sampled in fall and winter 2013, and were subsequently resampled in spring and summer Each home was sampled for approximately 4 to 5 days. Out of the five homes, three homes were control homes without building alterations between sampling events. These homes are labeled as Homes A, B, and C. The remaining two homes were case homes that were weatherized for energy efficiency purposes, and are labeled as Homes D and E. The control homes were chosen by availability, and the case homes were chosen in collaboration with Tompkins Community Action, which is a Department of Energy-sanctioned WAP agency. All homes were picked to exhibit similar building characteristics, and they are all one family houses with basements. However, there still exist many differences between the five homes, including size, activity patterns, and number of occupants. A summary of the sampling site characteristics is shown in Table 2.1 below. Table 2.1: Sampling Site characteristics of the five sampled homes. Site A (control) B (control) C (control) D (case) E (case) Number of Occupants Volume (m 3 ) Carpet Area (% of total area) Number of Windows

12 CHAPTER 3 MATERIALS AND METHODS 3.1 Carbon Dioxide Release and Air Exchange Rates The air exchange rate (AER) in each sampling location was obtained through the deliberate release and measurement of carbon dioxide, used as a tracer gas. A tank containing compressed carbon dioxide was connected to a timer, which then released carbon dioxide in approximately eight hour intervals. The rate of carbon dioxide release varied across the homes, depending upon the home volume and proximity to the sampling instruments. Carbon dioxide levels were measured using two instruments a LI-COR LI-820 continuous carbon dioxide monitor, and a PP-Systems SBA5 continuous carbon dioxide gas analyzer. These two instruments were placed in different locations in each sampling site to analyze the mixing conditions within each home. 3

13 Figure 3.1: Carbon dioxide tank and release timer apparatus. The released carbon dioxide follows a first-order reaction decay (Equation 3.1), and can thus be linearized by taking the natural logarithm of the values minus the baseline carbon dioxide value for the home (Equation 3.2): d[co 2] dt = r (3.1) ln[co 2 baseline] = kt + ln[co 2 ] 0 (3.2) The slope of the best-fit line for the linearized carbon dioxide values yields 4

14 the air exchange rate for that specific carbon dioxide decay. Figure 3.2: An example of linearized carbon dioxide decay with plotted best-fit line for the first decay in the first sampling of Home E. The air exchange rate for this specific event is calculated to be Particulate Matter Indoor and outdoor aerosols were sampled in parallel at each sampling site. Particles were collected onto Whatman nucleopore track-etch membrane filters, placed in four-stage Tisch particle impactors. The impactors were then connected to two different air pumps, which allowed the impactors to sample indoor and outdoor air at rates ranging from 45 liters per minute to 70 liters per minute, depending on the sampling site. The impactor cutoff stages were 0.47 µm to 2.1 µm, 2.1 µm to 4.7 µm, 4.7 µm to 9.0 µm, and 9.0 µm to 20 µm. These 5

15 cutoff values were chosen because airborne particles exhibit differing behavior in air, depending on their diameter. Figure 3.3: Airborne particle behavior trends with changing particle diameter. Figures adapted from Nazaroff [4] and Thatcher [5]. As seen in Figure 3.3, smaller particles of interest for this study (0.45µm< dp< 2.1 µm) exhibit orders of magnitude smaller deposition rates than large particles do. Essentially, the larger the diameter of the airborne particle, the faster it deposits from the air, due mainly to gravitational settling. Similarly to deposition rates, smaller particles exhibit orders of magnitude smaller resuspension rates than larger particles do. This results in larger particles deposited on surfaces becoming more readily airborne than smaller sized particles. The upper cutoff for the initial stage was chosen to be 20 µm, as particles larger than 20 µm settle rapidly from the air [6]. The Tisch Impactors were run indoors and outdoors in parallel for 96 to 110 hours. Time-averaged mass concentrations were calculated by equilibrating the filters, and weighing before and after sampling using a Mettler-Toledo XP ppecision balance (± 0.001mg). Static was removed using a Staticmaster 2U500 Microbalance ionizer. 6

16 3.3 Temperature and Relative Humidity Temperature and relative humidity measurements were obtained with ten continuously logging HOBO UX100 Temperature and Relative Humidity data loggers. These loggers were placed in various indoor and outdoor locations at each sampling site, and sampled continuously per minute throughout the sampling period of 96 to 110 hours. Typical deployment locations included living rooms, kitchen range hoods, ovens, and bathrooms, to track activities such as showering and cooking events performed over the course of sampling. 3.4 Indoor Air Radon Indoor radon measurements in air were conducted through the use of a RAD- STAR RS-300 continuous radon monitor, as well as through an AccuStar Short Term Radon Test Kit. The RADSTAR device measures the air radon levels through the use of an ionization chamber, while the AccuStar kit measures radon using liquid scintillation. The RS-300 continuous radon monitor was placed in the main living area of the homes, while the AccuStar kit was placed in the basements of the homes. The purpose of the radon measurements was to track the chemical trace of an indoor pollutant whose concentration is known. 3.5 Correlation Analysis Correlation analysis was done through GGOBI. 7

17 Figure 3.4: GGOBI software used for determining correlations between measured variables. Correlations can be clearly seen between small and medium particle size bins in this matrix for Home B. Figure 3.4 shows a correlation matrix for the collected data in Home B. Each plot corresponds to one data metric being plot against another data metric, while the diagonals contain relative frequency histogram plots. GGOBI was used for preliminary correlation analysis; if a trend was observed in the GGOBI matrix, the data was then further analyzed. In this particular plot, this is best illustrated by correlation observed in the small and medium size binned particles. The found correlatons are outlined in the figure above. 8

18 CHAPTER 4 RESULTS 4.1 CO 2 Measurements Air exchange rates were calculated using the first-order decay method outlined in the method section. The air exchange rates in the five considered homes are summarized in Table 4.1 below. Table 4.1: Summary of air exchange rate results. Standard deviations are reported in parentheses. Site A (control) B (control) C (control) D (case) E (case) First Sample (0.26) (0.34) (0.55) (0.42) (0.94) Second Sample (0.28) (0.38) (0.63) (0.36) (0.37) As seen in Table 4.1, weatherization of case home E resulted in a reduction of the air exchange rates (p 0.1). Furthermore, measurements by Tompkins Community Action corroborate these results. In the control homes, there is no AER reduction trend a reduction in the air exchange rates in homes A and B was observed, and an increase in home C was also apparent, but these changes were not significant (p >0.1). There are significant differences between the five homes, as shown in the Background. With this small sample size of three homes, it is difficult to generalize air exchange trends in the control homes. 9

19 Figure 4.1: An example graph displaying carbon dioxide measurements during the first sampling event in Home E. Figure 4.1 shows an illustrative carbon dioxide measurement graph over the entire sampling time. The two measurement instruments allow for examining the mixing conditions in each home. Across all five homes, there exists approximately a 20% difference between the two measurement devices, largely due to the difference in instrument location. 4.2 Particle Numbers Air quality is often characterized by the particle number counts as a measure of how many particles per volume are present. Due to the varying behavior of particles with different aerodynamic diameter, measurements were conducted in three size bins outlined in the Methods. 10

20 Figure 4.2: Indoor particle counts from the first sampling event in Home E. Figure 4.2 shows the particle counts from all three sampled size bins for the first sample of Home E. There is approximately an order of magnitude difference between particle counts of each size bin. From Figure 3.2 in the Methods, the larger deposition loss rates of larger airborne particles (> 5µm) explain their more rapid removal from air compared to particles with a smaller diameter (2 to 5µm, 0.5 to 2µm). For the observation presented here, these differences in behavior explain the shorter residence times in air of those particles. When particle counts with a diameter greater than 5 µm were examined, there seems to be a large range and variance of particle counts; there exists a range of four orders of magnitude. Furthermore, there are time periods with low particle counts, and time periods with high particle counts. From Figure 3.2 in the methods, it is observed that large particles were affected by resuspension far more than smaller particles. Thus, the time periods of high particle counts were caused by activity, and the time periods of low particle counts were caused by inactivity. 11

21 Figure 4.3: Indoor particle counts for the 0.5 to 2 µm particle size bin. 1 indicates the first sampling event, while 2 indicates the second sampling event. The boxes represent interquartile range, while the error bars represent the range of the data after outlier removal. A P* indicates a significant difference of 0.05, while P** indicates a significant difference of The three control homes, A, B, and C, are denoted by diagonal fillings, while the two case homes, D and E, are denoted by dot fillings. Figure 4.4: Indoor counts for the 2 5 µm particle size bin. 12

22 Figure 4.5: Indoor counts for the > 5µm particle size bin. Figures 4.3 to 4.5 show the indoor particle counts for all three considered size bins in all five homes. The general observed trend is such that there was a decrease in indoor particle counts for the weatherized case homes, D and E. This is contrary to our hypothesis, but there is not enough literature to fully understand how weatherization affects indoor air quality. There are many factors that may govern indoor particle counts. These include the amount of activity in the home, the frequency of events like showering and cooking, as well as weather and environmental effects. Finally, the sample size of two weatherized homes is too small to generalize any trends. The full study, which will examine fifteen homes, may provide more conclusive data. Figures 4.3 to 4.5 also show that control Home B exhibits much higher particle numbers than the rest of the homes. This is due to the characteristics of Home B: it is the only home that we sampled that had an indoor wood fireplace. The Figures show the dominating effect of indoor combustion on particle 13

23 counts, especially on the smaller sized particles. It is further valuable to compare the indoor particle counts with outdoor particle count to help account for weather and environmental effects. These comparisons are called the indoor/outdoor (I/O) ratios. In this study, I/O ratios were derived on a per minute basis from continuous paralleled indoor and outdoor particle number measurements. Figure 4.6: I/O ratios from the first sample of Home E. Similarly to the particle counts, there is a large variance in the range and variability in the I/O ratios. The largest size bin seems to follow a diurnal pattern, and exhibits approximately a two order of magnitude range. This is likely associated with indoor resuspension events, and therefore, human activity. 14

24 Figure 4.7: I/O ratios for the 0.5to2µm particle size bin. Figure 4.8: I/O ratios for the 2to5µm particle size bin. 15

25 Figure 4.9: I/O ratios for the > 5µm particle size bin. In general, in Figures 4.7 to 4.9, we observe that the same trends follow between the indoor particle counts and the indoor/outdoor ratios. The dominating effect of indoor combustion can once again be seen in control Home B. In summary, the time-averaged I/O ratio comparisons might aid in generating general trends, however, on a per-house basis, I/O ratios may inform about activity patterns and occupancy levels, which will be of interest for further data evaluation, which extends the scope of this report. 16

26 4.3 Particle Mass Figure 4.10: Particle mass concentrations for all five homes. Blue lines indicate indoor sampling, while red lines indicate outdoor sampling. Solid lines correspond to the first sampling event, while dashed lines correspond to the second sampling event. Particle mass concentration graphs are shown in Figure Particle mass was measured indoors and outdoors in parallel. The same pattern as for particle number concentrations hold for particle mass concentrations; the smaller indoor particles are associated with cooking and combustion events, whereas resuspension is generally associated with the presence of larger indoor particles. Thus, the time-averaged particle mass size distribution measurements can help inform about particle generation mechanisms over the sampling time. The particle mass data is also summarized in Table

27 Table 4.2: Summary of particle mass concentration results. Data reported is summation of mass in all four size bins. Site (µgm 3 ) A (control) B (control) C (control) D (case) E (case) Indoors First Sample Indoors Second Sample Outdoors First Sample Outdoors Second Sample I/O Ratio First Sample I/O Ratio Second Sample There are some trends to take note of. In all cases except home D, the outdoor mass increased between the first and second sampling events. It is important to note that outdoor mass depends on a variety of factors even changes in traffic patterns can increase or decrease the particle mass observed outdoors. Thus, this increase seems to be due to environmental and weather effects. Furthermore, there does not seem to be much correlation between indoor and outdoor masses. Figure 4.11: I/O ratios for particle mass concentrations for all five homes. The first sampling event is shown in blue, while the second sampling event is shown in yellow. Figure 4.11 shows the indoor/outdoor particle mass concentration ratios across all five homes. By comparing the indoor mass concentration ratio to the 18

28 outdoor mass concentration ratio, it can be observed that each home exhibits a different I/O ratio pattern. Homes A and E exhibit low I/O ratios across all size bins, which may be indicative of low indoor generated airborne mass levels or high outdoor particle levels compared to parallel measured indoor particle mass levels. Homes B and C exhibit high I/O ratios in the µm size bin, which may be due to combustion or human activity. Home D exhibits high I/O ratios in µm size bin, which may also be due to combustion or cooking events. In two of the control homes and one of the case homes, overall indoor mass decreased from the first to second sampling event, while in control home B and case home D, overall indoor mass increased. As has been reiterated many times in this report, there are many factors and parameters that shape particle number and mass concentrations. For example, there is a large spike in the first sampled indoor particles in home C that is not seen in the second sample. However, when the range hood temperature data in Figure 4.12 is observed, it is seen that there are more and larger temperature spikes in the first sample when compared to second. It is possible that increasing the number of cooking events in the first sample could cause the large spike observed in the mass data. Because we cannot control activity in the cases and controls, there will be a high variance in the data. 19

29 Figure 4.12: Range hood temperatures for Home C. Range hood temperatures are correlated with cooking events. The first sampling event is shown in blue, while the second sampling event is shown in yellow. 4.4 Indoor Air Radon Levels Radon levels are another very useful indicator of indoor air quality. Radon is carcinogenic and dangerous at levels higher than 4.0 pci/l [7]. Furthermore, it has been feared that weatherization of houses for energy conservation, including weather stripping and caulking of cracks, would lead to high radon levels [8]. Figure 16 shows an example radon distribution from the RS-300 continuous radon monitor, placed in the living room. 20

30 Figure 4.13: Radon distribution for the first sampling event of Home E. It is important to note that the radon levels vary throughout the sampling period there is no constant radon level throughout the sampling time. Figure 4.14: Radon distribution for all five homes. The AccuStar basement radon level is shown as a red dash. There is no basement reading for A1 due to an error with the test kit. From Figure 4.17, a significant (p <0.05) decrease in living room radon con- 21

31 centrations was observed between the two sampling events in homes A and C. It is possible that this radon decrease is due to environmental and weather effects, but it cannot be determined with this sample size. In weatherized home E, the basement radon level decreased. In home E, the basement was insulated and weatherized; it is possible that the weatherization decreased the radon levels in indoor air by increasing the pressure differential between the indoor basement and the outdoors soil, thus lowering the radon concentration. 4.5 Correlation Analysis In general, correlations were found between the small and medium particle size bins. This seems to be because the behavior of particles in the largest size bins are dominated by resuspension, while particle behavior in the smaller size bins is more dominated by gravitational effects and settling. There were also correlations found between particles in the two smaller size bins and cooking events, as measured by temperature monitors. Finally, in the control home with indoor combustion, there was a correlation found between indoor combustion activity (measured by a temperature monitor) and particle counts. 22

32 CHAPTER 5 CONCLUSIONS It can be seen that weatherization did indeed cause a reduction in the air exchange rate in one of the two weatherized case homes. While it was hypothesized that particle number and mass concentrations would increase between sampling events in the case homes, this was not observed. Particle concentrations and generation patterns are influenced by a variety of factors, including occupants activity and indoor combustion, (not just air exchange rates), and because these confounding factors could not be controlled for within this study, the hypothesis could not be confirmed after data collection and evaluation. From the limited sample size of five homes, two of which were weatherized between the first sampling and second sampling, it is difficult to come to conclusions about trends in indoor air quality. The full study will examine two more control homes and eight more case homes. With the complete sample size, effects of weatherization onto indoor air quality trends may become clearer in the future. The full study will further examine biological levels and species abundance, which may aid in understanding sources and generation mechanisms of indoor airborne particles before and after home weatherization. 23

33 CHAPTER 6 BIBLIOGRAPHY [1] How Much Energy Is Consumed in Residential and Commercial Buildings in the United States? U.S. Energy Information Administration - EIA - Independent Statistics and Analysis. < [2] Senator Cardin (MD). American Green Building Act. Congressional Record 153:7 (April 19, 2007). [3] Weatherization Assistance Programs (WAP). New York State Homes and Community Renewal. < 83. [4] Nazaroff, W. W. Indoor Particle Dynamics. Indoor Air 14.S7 (2004): 175- [5] Thatcher, T., and D. Layton. Deposition, Resuspension, and Penetration of Particles within a Residence. Atmospheric Environment (1995): [6] Qian, J., D. Hospodsky, N. Yamamoto, W. W. Nazaroff, and J. Peccia. Size-resolved Emission Rates of Airborne Bacteria and Fungi in an Occupied Classroom. Indoor Air (2012). [7] Radon Publications: Home Buyer s and Seller s Guide to Radon. EPA. Environmental Protection Agency. < [8] Bodansky, David, M. A. Robkin, and David R. Stadler. Overview of the Indoor Radon Problem. Indoor Radon and Its Hazards. Seattle: U of Washington,