IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2023i1p177-d1306590.html
   My bibliography  Save this article

Infiltration of Outdoor PM 2.5 Pollution into Homes with Evaporative Coolers in Utah County

Author

Listed:
  • Darrell B. Sonntag

    (Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA)

  • Hanyong Jung

    (Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA)

  • Royce P. Harline

    (Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA)

  • Tyler C. Peterson

    (Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA)

  • Selah E. Willis

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

  • Taylor R. Christensen

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

  • James D. Johnston

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

Abstract

Global use of energy-inefficient mechanical vapor-compression air conditioning (AC) is increasing dramatically for home cooling. Direct evaporative coolers (EC) offer substantial energy savings, and may provide a sustainable alternative to AC for homes in hot, dry climates. One drawback of ECs is the potential for infiltration of outdoor air pollution into homes. Prior studies on this topic are limited by small sample sizes and a lack of comparison homes. In this study, we used aerosol photometers to sample indoor and outdoor fine particulate matter (PM 2.5 ) from 16 homes with AC and 14 homes with EC in Utah County, Utah (USA) between July 2022 and August 2023. We observed a significantly larger infiltration factor (F in ) of outdoor PM 2.5 in EC vs. AC homes (0.39 vs. 0.12, p = 0.026) during summer. F in significantly increased during a wildfire smoke event that occurred during the study. During the wildfire event, EC homes offered little to no protection from outdoor PM 2.5 (F in = 0.96, 95% confidence interval (CI) 0.85, 1.07), while AC homes offered significant protection (F in = 0.23, 95% CI 0.15, 0.32). We recommend additional research focused on cooling pad design for the dual benefits of cooling efficiency and particle filtration.

Suggested Citation

  • Darrell B. Sonntag & Hanyong Jung & Royce P. Harline & Tyler C. Peterson & Selah E. Willis & Taylor R. Christensen & James D. Johnston, 2023. "Infiltration of Outdoor PM 2.5 Pollution into Homes with Evaporative Coolers in Utah County," Sustainability, MDPI, vol. 16(1), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:177-:d:1306590
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/1/177/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/1/177/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    2. Jomehzadeh, Fatemeh & Nejat, Payam & Calautit, John Kaiser & Yusof, Mohd Badruddin Mohd & Zaki, Sheikh Ahmad & Hughes, Ben Richard & Yazid, Muhammad Noor Afiq Witri Muhammad, 2017. "A review on windcatcher for passive cooling and natural ventilation in buildings, Part 1: Indoor air quality and thermal comfort assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 736-756.
    3. Sutyajeet Soneja & Chen Chen & James M. Tielsch & Joanne Katz & Scott L. Zeger & William Checkley & Frank C. Curriero & Patrick N. Breysse, 2014. "Humidity and Gravimetric Equivalency Adjustments for Nephelometer-Based Particulate Matter Measurements of Emissions from Solid Biomass Fuel Use in Cookstoves," IJERPH, MDPI, vol. 11(6), pages 1-17, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Montazeri, H. & Montazeri, F., 2018. "CFD simulation of cross-ventilation in buildings using rooftop wind-catchers: Impact of outlet openings," Renewable Energy, Elsevier, vol. 118(C), pages 502-520.
    2. Damianakis, Nikolaos & Mouli, Gautham Ram Chandra & Bauer, Pavol & Yu, Yunhe, 2023. "Assessing the grid impact of Electric Vehicles, Heat Pumps & PV generation in Dutch LV distribution grids," Applied Energy, Elsevier, vol. 352(C).
    3. Hu, Maomao & Xiao, Fu & Wang, Lingshi, 2017. "Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model," Applied Energy, Elsevier, vol. 207(C), pages 324-335.
    4. Dongjun Suh & Seongju Chang, 2012. "An Energy and Water Resource Demand Estimation Model for Multi-Family Housing Complexes in Korea," Energies, MDPI, vol. 5(11), pages 1-20, November.
    5. John Curtis & Brian Stanley, 2016. "Analysing Residential Energy Demand: An Error Correction Demand System Approach for Ireland," The Economic and Social Review, Economic and Social Studies, vol. 47(2), pages 185-211.
    6. Omar Shafqat & Elena Malakhatka & Nina Chrobot & Per Lundqvist, 2021. "End Use Energy Services Framework Co-Creation with Multiple Stakeholders—A Living Lab-Based Case Study," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    7. Wei Yu & Baizhan Li & Yarong Lei & Meng Liu, 2011. "Analysis of a Residential Building Energy Consumption Demand Model," Energies, MDPI, vol. 4(3), pages 1-13, March.
    8. Y, Kiguchi & Y, Heo & M, Weeks & R, Choudhary, 2019. "Predicting intra-day load profiles under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 173(C), pages 959-970.
    9. Anna Kipping & Erik Trømborg, 2017. "Modeling Aggregate Hourly Energy Consumption in a Regional Building Stock," Energies, MDPI, vol. 11(1), pages 1-20, December.
    10. Raúl Arango-Miranda & Robert Hausler & Rabindranarth Romero-López & Mathias Glaus & Sara Patricia Ibarra-Zavaleta, 2018. "An Overview of Energy and Exergy Analysis to the Industrial Sector, a Contribution to Sustainability," Sustainability, MDPI, vol. 10(1), pages 1-19, January.
    11. Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
    12. Estiri, Hossein, 2014. "Building and household X-factors and energy consumption at the residential sector," Energy Economics, Elsevier, vol. 43(C), pages 178-184.
    13. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    14. Ijaz Ul Haq & Amin Ullah & Samee Ullah Khan & Noman Khan & Mi Young Lee & Seungmin Rho & Sung Wook Baik, 2021. "Sequential Learning-Based Energy Consumption Prediction Model for Residential and Commercial Sectors," Mathematics, MDPI, vol. 9(6), pages 1-17, March.
    15. Nouha Dkhili & David Salas & Julien Eynard & Stéphane Thil & Stéphane Grieu, 2021. "Innovative Application of Model-Based Predictive Control for Low-Voltage Power Distribution Grids with Significant Distributed Generation," Energies, MDPI, vol. 14(6), pages 1-28, March.
    16. Wang, Manyu & Wei, Chu, 2024. "Toward sustainable heating: Assessment of the carbon mitigation potential from residential heating in northern rural China," Energy Policy, Elsevier, vol. 190(C).
    17. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    18. Sung-Chin Chung & Yi-Pin Lin & Chun Yang & Chi-Ming Lai, 2019. "Natural Ventilation Effectiveness of Awning Windows in Restrooms in K-12 Public Schools," Energies, MDPI, vol. 12(12), pages 1-14, June.
    19. Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2015. "Long term outlook of primary energy consumption of the Italian thermoelectric sector: Impact of fuel and carbon prices," Energy, Elsevier, vol. 87(C), pages 153-164.
    20. Xavier Faure & Tim Johansson & Oleksii Pasichnyi, 2022. "The Impact of Detail, Shadowing and Thermal Zoning Levels on Urban Building Energy Modelling (UBEM) on a District Scale," Energies, MDPI, vol. 15(4), pages 1-18, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:177-:d:1306590. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.