IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i22p14848-d968881.html
   My bibliography  Save this article

Assessment of Outdoor Design Conditions on the Energy Performance of Cooling Systems in Future Climate Scenarios—A Case Study over Three Cities of Texas, Unites States

Author

Listed:
  • Alireza Karimi

    (Instituto Universitario de Arquitectura y Ciencias de la Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, 41012 Sevilla, Spain)

  • You Joung Kim

    (Department of Landscape and Architecture, Texas A&M University, College Station, TX 77843, USA)

  • Negar Mohammad Zadeh

    (Department of Architecture, Faculty of Art, Tarbiat Modares University, Tehran 13145-1696, Iran)

  • Antonio García-Martínez

    (Instituto Universitario de Arquitectura y Ciencias de la Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, 41012 Sevilla, Spain)

  • Shahram Delfani

    (Department of Building Installations, Building and Housing Research Center (BHRC), Tehran 13145-1696, Iran)

  • Robert D. Brown

    (Department of Landscape and Architecture, Texas A&M University, College Station, TX 77843, USA)

  • David Moreno-Rangel

    (Instituto Universitario de Arquitectura y Ciencias de la Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, 41012 Sevilla, Spain)

  • Pir Mohammad

    (Department of Earth Sciences, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India)

Abstract

The excessive use of energy in buildings due to increased populations and economic development leads to more greenhouse gas emissions, which affect climate change and global warming. Changes in prevailing outdoor weather conditions significantly affect the energy systems of buildings through increased cooling and decreased heating. In this paper, 30 years of data of dry and wet bulb temperatures (1990–2020) with a time interval of 3 h were considered in order to estimate the climatic outdoor design conditions in the cities of Dallas–Fort Worth, Houston, and San Antonio in the state of Texas. The results suggest that the dry bulb temperature (DBT) had significantly higher increases in Dallas–Fort Worth (2.37 °C) than the wet bulb temperature (WBT) in Houston (4.1 °C) during the study period. Furthermore, this study analyzed the effects of climate change on cooling degree hours (CDH) and heating degree hours (HDH) and the results suggest the most significant drop in HDH in Dallas–Fort Worth with a maximum CDH fluctuation as compared to other two cities. The effect of climate change on the performance of cooling systems is also investigated in this study via direct evaporative coolers (DECs) and direct-indirect evaporative coolers (IDEC), which do not perform well in the selected cities. In contrast, absorption system (Abs) and vapor compression (VC) systems show an increase in the number of additional loads. The second part of this study is related to the future projection using the ARIMA model, which suggests that DBT would rise significantly in Houston (from 37.18 °C to 37.56 °C) and Dallas–Fort Worth (39.1 °C to 39.57 °C) while diminishing in San Antonio (from 34.81 °C to 33.95 °C) from 2020 to 2030. In contrast, WBT will experience an upward trend in Houston (from 36.06 °C to 37.71 °C) and Dallas–Fort Worth (from 31.32 °C to 31.38 °C) and a downward trend in San Antonio (from 32.43 °C to 31.97 °C) during 2020–2030. Additionally, the future performance prediction of Abs and VC systems is also performed, which reveals that the amount of additional load required is significantly higher in 2030 compared to 2020 and is more prominent in Houston. Conversely, amount of additional load required for cooling systems in San Antonio shows a decreasing trend in 2030.

Suggested Citation

  • Alireza Karimi & You Joung Kim & Negar Mohammad Zadeh & Antonio García-Martínez & Shahram Delfani & Robert D. Brown & David Moreno-Rangel & Pir Mohammad, 2022. "Assessment of Outdoor Design Conditions on the Energy Performance of Cooling Systems in Future Climate Scenarios—A Case Study over Three Cities of Texas, Unites States," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14848-:d:968881
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/22/14848/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/22/14848/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Troup, Luke & Eckelman, Matthew J. & Fannon, David, 2019. "Simulating future energy consumption in office buildings using an ensemble of morphed climate data," Applied Energy, Elsevier, vol. 255(C).
    2. Raúl Castaño-Rosa & Roberto Barrella & Carmen Sánchez-Guevara & Ricardo Barbosa & Ioanna Kyprianou & Eleftheria Paschalidou & Nikolaos S. Thomaidis & Dusana Dokupilova & João Pedro Gouveia & József Ká, 2021. "Cooling Degree Models and Future Energy Demand in the Residential Sector. A Seven-Country Case Study," Sustainability, MDPI, vol. 13(5), pages 1-25, March.
    3. Gouveia, João Pedro & Fortes, Patrícia & Seixas, Júlia, 2012. "Projections of energy services demand for residential buildings: Insights from a bottom-up methodology," Energy, Elsevier, vol. 47(1), pages 430-442.
    4. Zhou, Yuyu & Clarke, Leon & Eom, Jiyong & Kyle, Page & Patel, Pralit & Kim, Son H. & Dirks, James & Jensen, Erik & Liu, Ying & Rice, Jennie & Schmidt, Laurel & Seiple, Timothy, 2014. "Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework," Applied Energy, Elsevier, vol. 113(C), pages 1077-1088.
    5. Page Kyle & Leon Clarke & Fang Rong & Steven J. Smith, 2010. "Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 145-172.
    6. Yuyu Zhou & Jiyong Eom & Leon Clarke, 2013. "The effect of global climate change, population distribution, and climate mitigation on building energy use in the U.S. and China," Climatic Change, Springer, vol. 119(3), pages 979-992, August.
    7. Chakraborty, Debaditya & Alam, Arafat & Chaudhuri, Saptarshi & Başağaoğlu, Hakan & Sulbaran, Tulio & Langar, Sandeep, 2021. "Scenario-based prediction of climate change impacts on building cooling energy consumption with explainable artificial intelligence," Applied Energy, Elsevier, vol. 291(C).
    8. Lam, Tony N.T. & Wan, Kevin K.W. & Wong, S.L. & Lam, Joseph C., 2010. "Impact of climate change on commercial sector air conditioning energy consumption in subtropical Hong Kong," Applied Energy, Elsevier, vol. 87(7), pages 2321-2327, July.
    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. James McFarland & Yuyu Zhou & Leon Clarke & Patrick Sullivan & Jesse Colman & Wendy Jaglom & Michelle Colley & Pralit Patel & Jiyon Eom & Son Kim & G. Kyle & Peter Schultz & Boddu Venkatesh & Juanita , 2015. "Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison," Climatic Change, Springer, vol. 131(1), pages 111-125, July.
    2. Scott, Michael J. & Daly, Don S. & Zhou, Yuyu & Rice, Jennie S. & Patel, Pralit L. & McJeon, Haewon C. & Page Kyle, G. & Kim, Son H. & Eom, Jiyong & Clarke, Leon E., 2014. "Evaluating sub-national building-energy efficiency policy options under uncertainty: Efficient sensitivity testing of alternative climate, technological, and socioeconomic futures in a regional integr," Energy Economics, Elsevier, vol. 43(C), pages 22-33.
    3. Cui, Ying & Yan, Da & Hong, Tianzhen & Xiao, Chan & Luo, Xuan & Zhang, Qi, 2017. "Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China," Applied Energy, Elsevier, vol. 195(C), pages 890-904.
    4. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
    5. Zhou, Yuyu & Clarke, Leon & Eom, Jiyong & Kyle, Page & Patel, Pralit & Kim, Son H. & Dirks, James & Jensen, Erik & Liu, Ying & Rice, Jennie & Schmidt, Laurel & Seiple, Timothy, 2014. "Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework," Applied Energy, Elsevier, vol. 113(C), pages 1077-1088.
    6. Yuanzheng Li & Wenjing Wang & Yating Wang & Yashu Xin & Tian He & Guosong Zhao, 2020. "A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling," IJERPH, MDPI, vol. 18(1), pages 1-18, December.
    7. Jaglom, Wendy S. & McFarland, James R. & Colley, Michelle F. & Mack, Charlotte B. & Venkatesh, Boddu & Miller, Rawlings L. & Haydel, Juanita & Schultz, Peter A. & Perkins, Bill & Casola, Joseph H. & M, 2014. "Assessment of projected temperature impacts from climate change on the U.S. electric power sector using the Integrated Planning Model®," Energy Policy, Elsevier, vol. 73(C), pages 524-539.
    8. Dirks, James A. & Gorrissen, Willy J. & Hathaway, John H. & Skorski, Daniel C. & Scott, Michael J. & Pulsipher, Trenton C. & Huang, Maoyi & Liu, Ying & Rice, Jennie S., 2015. "Impacts of climate change on energy consumption and peak demand in buildings: A detailed regional approach," Energy, Elsevier, vol. 79(C), pages 20-32.
    9. Zheng, Yuanfan & Weng, Qihao, 2019. "Modeling the effect of climate change on building energy demand in Los Angeles county by using a GIS-based high spatial- and temporal-resolution approach," Energy, Elsevier, vol. 176(C), pages 641-655.
    10. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
    11. De Masi, Rosa Francesca & Gigante, Antonio & Ruggiero, Silvia & Vanoli, Giuseppe Peter, 2021. "Impact of weather data and climate change projections in the refurbishment design of residential buildings in cooling dominated climate," Applied Energy, Elsevier, vol. 303(C).
    12. Wenliang Li, 2020. "Quantifying the Building Energy Dynamics of Manhattan, New York City, Using an Urban Building Energy Model and Localized Weather Data," Energies, MDPI, vol. 13(12), pages 1-22, June.
    13. Yu, Sha & Eom, Jiyong & Zhou, Yuyu & Evans, Meredydd & Clarke, Leon, 2014. "Scenarios of building energy demand for China with a detailed regional representation," Energy, Elsevier, vol. 67(C), pages 284-297.
    14. Feijoo, Felipe & Iyer, Gokul C. & Avraam, Charalampos & Siddiqui, Sauleh A. & Clarke, Leon E. & Sankaranarayanan, Sriram & Binsted, Matthew T. & Patel, Pralit L. & Prates, Nathalia C. & Torres-Alfaro,, 2018. "The future of natural gas infrastructure development in the United states," Applied Energy, Elsevier, vol. 228(C), pages 149-166.
    15. Tamer, Tolga & Gürsel Dino, Ipek & Meral Akgül, Cagla, 2022. "Data-driven, long-term prediction of building performance under climate change: Building energy demand and BIPV energy generation analysis across Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    16. Hong, Lixuan & Zhou, Nan & Feng, Wei & Khanna, Nina & Fridley, David & Zhao, Yongqiang & Sandholt, Kaare, 2016. "Building stock dynamics and its impacts on materials and energy demand in China," Energy Policy, Elsevier, vol. 94(C), pages 47-55.
    17. Jianhua Huang & Kevin Robert Gurney, 2016. "Impact of climate change on U.S. building energy demand: sensitivity to spatiotemporal scales, balance point temperature, and population distribution," Climatic Change, Springer, vol. 137(1), pages 171-185, July.
    18. Chaturvedi, Vaibhav & Kim, Sonny & Smith, Steven J. & Clarke, Leon & Yuyu, Zhou & Kyle, Page & Patel, Pralit, 2013. "Model evaluation and hindcasting: An experiment with an integrated assessment model," Energy, Elsevier, vol. 61(C), pages 479-490.
    19. Li, Xiaoma & Zhou, Yuyu & Yu, Sha & Jia, Gensuo & Li, Huidong & Li, Wenliang, 2019. "Urban heat island impacts on building energy consumption: A review of approaches and findings," Energy, Elsevier, vol. 174(C), pages 407-419.
    20. Plaga, Leonie Sara & Bertsch, Valentin, 2023. "Methods for assessing climate uncertainty in energy system models — A systematic literature review," Applied Energy, Elsevier, vol. 331(C).

    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:14:y:2022:i:22:p:14848-:d:968881. 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.