Grantee Research Project Results
Final Report: Combining Measurements and Models to Predict the Impacts of Climate Change and Weatherization on Indoor Air Quality and Chronic Health Effects in U.S. Residences
EPA Grant Number: R835750Title: Combining Measurements and Models to Predict the Impacts of Climate Change and Weatherization on Indoor Air Quality and Chronic Health Effects in U.S. Residences
Investigators: Stephens, Brent
Institution: Illinois Institute of Technology
EPA Project Officer: Chung, Serena
Project Period: November 1, 2014 through October 31, 2017 (Extended to July 31, 2019)
Project Amount: $499,974
RFA: Indoor Air and Climate Change (2014) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Climate Change , Air
Objective:
The objectives of this research are to use a combination of field measurements and a nationally representative set of dynamic residential indoor air quality models to predict indoor exposures and associated chronic health effects of several priority pollutants of both indoor and outdoor origin across (1) the current U.S. residential building stock; (2) the current U.S. residential building stock under future climate scenarios of 2050 and 2080; and (3) the future U.S. building stock under future climate scenarios of 2050 and 2080 considering a number of climate policy scenarios that lead to widespread application of weatherization retrofits and turnover of the existing building stock to more energy efficient homes.
Summary/Accomplishments (Outputs/Outcomes):
Climate change is expected to affect building energy use and indoor air quality (IAQ) through both building design (i.e., via our collective responses to climate change) and building operation (i.e., via changing meteorological and ambient air quality conditions). In terms of energy use, simply put, changing ambient temperature and/or moisture conditions will have a direct influence on building energy use for space conditioning purposes by changing heating, cooling, and ventilation loads while also indirectly influencing energy use by changing the conditions at which heating and cooling equipment operates. The magnitude of impacts in individual buildings will vary by building type, system types, and the extent of climate changes in the building’s location. The magnitude of impacts across the building stock is expected to be influenced by changes in the underlying future building stock characteristics, population demographics, and the magnitude and distribution of climate changes across the U.S.
Climate change is expected to impact the concentrations of airborne pollutants inside buildings in both direct and indirect ways, which may have implications for human exposures and public health. The predicted impacts of climate change on IAQ and health can be grouped into three general categories: (1) climate change is expected to lead to changes in some outdoor pollutant concentrations, particularly for ozone and possibly for particulate matter, which will also manifest as changes in indoor pollutant concentrations because outdoor pollutants can infiltrate into buildings with varying efficiencies; (2) climate change is expected to lead to changes in meteorological conditions that will impact existing building performance, operation, and human behaviors, including changes in air infiltration rates, air-conditioner operation, and window opening patterns, which have competing effects on indoor pollutant concentrations; and (3) climate change is expected to lead to widespread policy responses that influence the ways in which we design and construct buildings, including improving energy efficiency across the building stock by implementing energy efficient building practices in new construction and widespread application of weatherization retrofits in existing buildings. These practices are expected to decrease ventilation rates and increase concentrations of a number of indoor-generated pollutants, while subsequently decreasing concentrations of a number of outdoor-generated pollutants.
To date, more is understood about how climate change is likely to influence building energy use than IAQ, but no studies of which we are aware have combined these two aspects. In this work, we combine both measurements and models to demonstrate the likely impact of a combination of expected changes in future meteorological conditions, ambient air quality, the U.S. housing stock, and population demographics on indoor air quality and building energy use.
In the field measurements portion of this project, we first conducted pilot field measurements in an unoccupied apartment unit on the main campus of Illinois Institute of Technology (IIT) to refine our measurement techniques and make novel measurements of envelope penetration factors for ozone (Zhao and Stephens, 2016), particulate matter (Zhao and Stephens, 2017), and oxides of nitrogen (Zhao et al., 2019), as well as novel measurements of size-resolved particle removal efficiency for different heating, ventilating, and air-conditioning (HVAC) filters (Fazli et al., 2019), each of which has provided novel measured data and also informed our modeling efforts. We also conducted field measurements in 13 single-family residential field sites both before and after weatherization retrofits occurred (resulting in 11 successful tests), as well as 7 multi-family residential field sites without retrofits, to measure envelope airtightness (via blower door), outdoor pollutant infiltration factors and, when possible, outdoor pollutant penetration factors and indoor deposition loss rate constants while the homes were unoccupied for several hours. Figure 1 shows changes in envelope airtightness (i.e., ACH50) measured in the 11 homes that were successfully tested before and after retrofits. Retrofits commonly included: installing attic insulation, sealing air leaks in the building envelope, and installing weather-stripping. The average change was a 13% reduction in airtightness, ranging from a negligible change (i.e., +4%) to a 46% reduction.
Figure 1. Changes in airtightness after energy retrofits
Figure 2 shows estimates of penetration factors for (i) ultrafine particles (UFPs), (ii) PM2.5, and (iii) ozone made in the 11 homes both before and after retrofits were conducted. Estimates of UFP penetration factors (mean ± SD) were 0.74±0.13 before retrofits and 0.70±0.11 after retrofits, ranging from 0.46±0.03 to 0.88±0.09. Estimates of PM2.5 penetration factors (mean ± SD) were 0.81±0.11 before retrofits and 0.85±0.10 after retrofits, ranging from 0.65±0.11 to 1.02±0.06. Estimates of ozone penetration factors (mean ± SD, in only 8 homes) were 0.77±0.11 before retrofits and 0.70±0.20 after retrofits, ranging from 0.46±0.07 to 0.97±0.07. These data provide some of the first known measurements of penetration factors for these pollutants (a) during natural conditions in homes and (b) before and after energy efficiency retrofits. They also suggest that penetration factors may increase or decrease slightly after retrofits, in part because they are influenced not only by retrofits but also by climate conditions during testing and other factors.
Figure 2. Penetration factor estimates made using data collected before and after retrofits
Figure 3 shows estimates of UFP, PM2.5, and ozone penetration factors measured in 7 multi-family homes compared to 11 single-family homes measured pre-retrofit. Estimates for UFP, PM2.5, and ozone penetration factors in single-family homes (mean ± SD) were 0.70±0.11, 0.80±0.09, and 0.73±0.16, respectively, while the same parameters were 0.75±0.16, 0.90±0.12, and 0.71±0.23 in the multi-family homes. These first known measurements of penetration factors in multi-family housing units suggest that they may allow greater infiltration of PM2.5 and UFPs than single-family homes, but ozone infiltration is relatively similar.
Figure 3. Estimates of PM2.5, UFP, and ozone penetration factors measured in single-family (SF) vs. multi-family (MF) units
Results from the field work provide some of the first known measurements of envelope penetration factors for PM2.5, ultrafine particles, ozone, and nitrogen oxides (each of which when applicable/possible) made in residences operating under normal conditions using newly developed rapid test methods, as well as the first known measurements of how these parameters change (or do not change) after weatherization retrofits have occurred and also how they vary between single-family and multi-family units. Interestingly, we did not observe significant changes in pollutant infiltration factors or penetration factors in the homes for which pre/post retrofit measurements were successfully conducted, suggesting that typical energy efficiency retrofits do not appear to drastically alter infiltration airflow pathways in these homes such that penetration factors are not meaningful altered (although decreased infiltration through increased airtightness will reduce the rate of ambient pollutant infiltration to the indoors). We also find similar distributions of pollutant penetration factors between single- and multi-family homes for particulate matter, but slightly lower penetration factors in multi-family homes for ozone, on average.
In the modeling portion of this project, the three main tasks of the IAQ model development and application were successfully completed, including: (1) building and refining a nationally representative set of residential IAQ models; (2) applying the model set to predict statistical distributions of hourly indoor concentrations of both indoor and outdoor generated pollutants for both typical and future meteorological years across the residential building stock; and (3) predicting exposures, doses, and chronic health effects based on these models. We originally proposed to use multi-zone airflow and contaminant transport modeling software (CONTAM) to conduct these simulations, but in our QAPP we decided to first test the validity of using a custom package that allows for more flexibility and automation by combining a custom dynamic mass balance model (built in Python) to off-the-shelf building energy simulation software (EnergyPlus). Outputs from these two approaches were sufficiently similar for the purposes of the project such that we decided to construct a custom model so we could explore a greater number of scenarios and homes with greater ease and similar accuracy to CONTAM. We first built and applied this new model framework for the current housing stock (current as of the late 1990s or early 2000s at first) (i.e., Tasks 1 and 2), and then refined the model set for both the current housing stock (as of ~2015) and the future housing stock (as of ~2050s).
For the 2015 model set, 215 model home geometries that represent ~80% of homes in the U.S. were first built in BEopt using the U.S. Department of Energy (DOE) Residential Energy Consumption Survey (RECS) database to generate 4,085 unique XML files representing over 4,000 homes across 19 cities in the U.S., which were then used to generate EnergyPlus input files. EnergyPlus models were run to generate hourly estimates of heating and cooling energy use, infiltration/ventilation rates, HVAC runtimes, and other parameters, which were then fed to a custom mass balance model to calculate time-varying concentrations of several pollutants of both indoor and outdoor origin. We made several assumptions for both constant (time-averaged) and intermittent indoor emissions of pollutants (e.g., median constant emission rates of volatile organic compounds (VOCs) and aldehydes and once-per-day UFP, PM2.5, and NO2 emissions during cooking, etc.). These predictions of time-varying pollutant concentrations were then summarized on an annual basis for each home, and finally, population-weighting factors were applied to each of the 4,085 unique home models to weight for approximately how many homes they represent across the country. The ~2015 model set was run for the most current year for which outdoor pollutant and weather data were available at the time (year 2012) and the ~2050s model set was run using combined climate and air quality model outputs for the year ~2055. Hourly climate and air quality model outputs for ~2055 were obtained directly from EPA STAR grantee Dr. Joshua Fu at the University of Tennessee.
Baseline year (2012) results for total residential heating and cooling energy use (on a site energy basis) are shown in Figure 4, with model results compared to both Energy Information Administration(EIA) 2009 and 2015 RECS data for the housing stock. Climate and air quality inputs are from year 2012; the building stock model set is current as of ~2015. Model results for total heating and cooling energy use are within 9-13% of EIA data, which is to be reasonably expected given that 2012 in the U.S. was one of the hottest years on record and hotter than both 2009 and 2015. As such, heating energy would be expected to be lower and cooling energy higher than adjacent years.
Figure 4. Total annual residential space conditioning site energy consumption in the U.S. in the baseline year (2012). Model results are compared to EIA 2009 and 2015 RECS data.
Figure 5 shows IAQ model results for several pollutants (modeled again for the baseline year, 2012) compared to data from the existing literature on residential pollutant concentrations. Results suggest that the model set indeed accurately represents reality, with similar indoor concentrations, indoor/outdoor concentration ratios, and infiltration factors to those reported in field studies and nationwide surveys.
Figure 5. Annual hourly averages of (A) indoor concentrations of all modeled pollutants (on a log scale), (B) infiltration factors (Finf) for PM2.5, UFP, NO2, and O3, and (C) indoor-outdoor ratios for PM2.5, UFP, and NO2 (split by homes with gas and electric stoves) for the 4085 model homes in the baseline year (2012) compared to values reported in an extensive literature review for each parameter.
Energy and IAQ prediction results for future model years compared to the baseline year (2012) are shown in Figure 6 and Figure 7. Note that the predicted future building stock model set includes our best estimates of changes in the building stock that are likely to occur from 2015 through ~2050s, as well as predicted changes in population demographics and changes in ambient weather and pollutant concentrations.
Figure 6 shows estimate energy use for heating and cooling across the U.S. residential building stock on a (a) site energy basis and (b) source energy basis for future years (~2050s) compared to current years (~2012). The model set predicts site energy use and then source-to-site conversion factors of 3.00 and 2.72 are used for electricity generation in ~2012 and ~2050s based on predictions in Donohoo-Vallett, 2016, Accounting Methodology for Source Energy of Non-Combustible Renewable Electricity Generation. Due to combined influences of changes in climate, housing stock, and demographics, we predict that total site and source energy consumption for space conditioning in U.S. residences will decrease by ~35% and ~18% by mid-century (~2050s) compared to 2012, respectively, driven by large decreases in heating energy use and large (but not as large on an absolute basis) increases in cooling energy use in warmer climates, in addition to greater numbers of people moving to warmer climate zones.
Figure 6. Predicted annual residential space conditioning (a) site and (b) source energy consumption in the U.S. for 2012 and ~2050s model sets
Figure 7 shows population weighted annual average indoor pollutant concentrations predicted in both the baseline year (2012) and the future climate scenario (2050s). Model results are divided into predicted contributions from indoor sources and from ambient (i.e., outdoor) sources. General trends are as follows: concentrations of most ambient pollutants are predicted to decrease in the future, which leads to a decrease in concentrations of ambient-infiltrated pollutants, on average. These changes have less to do with climate factors and more to do with the expectation of increasing emissions controls that will lower many ambient pollutant concentrations by 2050s. One notable exception is ozone, however, which is expected to increase in future climate scenarios, thereby increasing the amount of ozone that infiltrates and persists in homes.
For those pollutants with significant intermittent indoor sources but that are not greatly affected by the type of fuel used in buildings (e.g., PM2.5 and UFPs, each primarily assumed to be from cooking sources), indoor concentrations are expected to experience small to moderate decreases in future climate scenarios (i.e., 1.5% for PM2.5 and 7.5% for UFPs) due in part to slight differences in emission rates resulting from an expected increase in the number of homes with electric stoves rather than gas stoves, with smaller impacts resulting from small changes in predicted infiltration and ventilation (i.e., window opening) conditions based on both climate and building stock changes. Larger reductions in indoor concentrations are predicted for NO2 (i.e., ~31%), primarily due to an expected increase in the number of homes with electric stoves rather than gas stoves, again with smaller impacts resulting from small changes in predicted infiltration and ventilation (i.e., window opening) conditions based on both climate and building stock changes.
For those pollutants with assumed constant or near-constant (i.e., time-averaged) indoor sources (e.g., VOCs and aldehydes), moderate to large increases in indoor concentrations are predicted by mid-century (e.g., 15% for formaldehyde and 45% for acetaldehyde, acrolein, benzene, and other VOCs). This is primarily due to the predicted impacts of climate change in future years on reducing infiltration and ventilation rates due to a combination of changing meteorological driving forces and also a changing housing stock and demographics (i.e., more people moving into greater numbers of tighter homes). For reference, the average air change rate and HVAC runtimes predicted for the U.S. housing stock are 0.43 per hour and 16% in 2012 and 0.34 per hour and 20% in 2050s, respectively.
Figure 7. Population weighted annual average indoor pollutant concentrations in 2012 and 2050s model sets
Finally, Figure 8 shows estimates of disability-adjusted life-years (DALYs) lost per 100,000 residents due to chronic air pollutant inhalation in U.S. residences for the current building stock (~2012) and the future building stock (~2050s). DALYs loss estimates are made using the methodology described in Logue et al. (2012) Environmental Health Perspectives 120(2):216-222. The total number of DALYs lost across the population is predicted to be similar between current and future climate scenarios (i.e., 189 per 100,000 persons in 2012 and 186 per 100,000 persons in 2050s). However, the distribution among pollutants is expected to vary, with lower PM2.5 exposures leading to lower DALYs lost but higher exposures to VOCs of indoor origin (especially acrolein) leading to higher DALYs lost. The net impact is the same, but attribution among pollutants is expected to vary, which underscores the importance of having accurate inputs for the health impact modeling approach used herein.
Figure 8. Estimated disability-adjusted life-years (DALYs) lost due to chronic air pollutant inhalation in U.S. residences for the current building stock (~2012) and the future building stock (~2050s)
These findings are particularly insightful for the scientific community, as to date we are not aware of any studies that have combined predictions of future meteorological conditions, ambient air quality, housing stock changes, and demographic changes to investigate the potential impact of climate change on indoor air quality and building energy use. Overall, results suggest that site and source energy use are both expected to decrease in future climates (i.e., by ~35% and ~18% by ~2050s compared to 2012, respectively), which may be counterintuitive, but does not eliminate the need to switch to low-carbon renewable energy resources, as the magnitude of predicted differences are not large compared to what decarbonization of the U.S. energy mix could achieve. Moreover, our findings that indoor pollutant exposures are expected to decrease for some pollutants (especially those with substantial outdoor sources that infiltrate indoors) but increase for others (especially those with predominant indoor sources) are also novel; yet, the net impacts on long-term health outcomes are predicted to be negligible because trade-offs among different pollutants balance each other. Finally, we also provide novel measurements of pollutant infiltration and penetration factors in real homes, including in a sample of multi-family buildings and in a sample of mostly single-family buildings before and after retrofits. Through these measurements, we find that typical energy efficiency retrofits do not appear to drastically alter infiltration airflow pathways in these homes such that penetration factors are not meaningful altered. We also find similar distributions of pollutant penetration factors between single- and multi-family homes for particulate matter, but lower penetration factors in multi-family homes for ozone.
References:
Fazli, T., Zeng, Y., Stephens, B. (2019). Fine and ultrafine particle removal efficiency of new residential HVAC filters. Indoor Air, doi:10.1111/ina.12566.
Zhao, H., Stephens, B. (2016). A method to measure the ozone penetration factor in residences under infiltration conditions: application in a multifamily apartment unit. Indoor Air 26, 571–581.
Zhao, H., Stephens, B. (2017). Using portable particle sizing instrumentation to rapidly measure the penetration of fine and ultrafine particles in unoccupied residences. Indoor Air 27, 218–229.
Zhao, H., Gall, E.T., Stephens, B. (2019). Measuring the penetration factor for ambient nitrogen oxides through the building envelope. Environmental Science and Technology, doi:10.1021/acs.est.9b02920.
Journal Articles on this Report : 9 Displayed | Download in RIS Format
Other project views: | All 24 publications | 9 publications in selected types | All 9 journal articles |
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Azimi P, Stephens B. A framework for estimating the US mortality burden of fine particulate matter exposure attributable to indoor and outdoor microenvironments. Journal of Exposure Science and Environmental Epidemiology 2018 |
R835750 (2018) R835750 (Final) |
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Fazli T, Dong X, Fu J, Stephens B. Predicting Residential Building Energy Use and Indoor Pollutant Exposures in the Mid-21st Century. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021;555(5):3219-3228. |
R835750 (Final) |
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Fazli T, Dong X, Fu JS, Stephens B. Predicting US residential building energy use and indoor pollutant exposures in the mid-21st century. Environ Sci Technol 2021;55(5):3219-3228 |
R835750 (Final) |
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Zhao D, Azimi P, Stephens B. Evaluating the long-term health and economic impacts of central residential air filtration for reducing premature mortality associated with indoor fine particulate matter (PM2.5) of outdoor origin. International Journal of Environmental Research and Public Health 2015;12(7):8448-8479. |
R835750 (2015) R835750 (2016) R835750 (2018) R835750 (Final) |
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Zhao H, Stephens B. A method to measure the ozone penetration factor in residences under infiltration conditions: application in a multifamily apartment unit. Indoor Air 2016;26(4):571-581. |
R835750 (2015) R835750 (2016) R835750 (2018) R835750 (Final) |
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Zhao H, Stephens B. Using portable particle sizing instrumentation to rapidly measure the penetration of fine and ultrafine particles in unoccupied residences. Indoor Air 2017;27(1):218-229. |
R835750 (2015) R835750 (2016) R835750 (2018) R835750 (Final) |
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Zhao H, Gall ET, Stephens B. Measuring the building envelope penetration factor for ambient nitrogen oxides. Environmental Science \amp& Technology 2019;53:9695–704 |
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Fazli T, Stephens B. Development of a nationally representative set of combined building energy and indoor air quality models for US residences. Building and Environment 2018; 136:192-212; |
R835750 (2018) R835750 (Final) |
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Fazli T, Zeng Y, Stephens B. Fine and ultrafine particle removal efficiency of new residential HVAC filters. Indoor Air 2019;29:656–69 |
R835750 (Final) |
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Supplemental Keywords:
Indoor exposures, ozone, particulate matter, housing, nitrogen dioxide, black carbon, ventilation, infiltration, modelingRelevant Websites:
The Built Environment Research Group Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
- 2018 Progress Report
- 2017 Progress Report
- 2016 Progress Report
- 2015 Progress Report
- Original Abstract
9 journal articles for this project