IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i9p2223-d1388735.html
   My bibliography  Save this article

Quantitative Study on the Effects of Street Geometries and Tree Configurations on the Outdoor Thermal Environment

Author

Listed:
  • Jindong Wu

    (China National Engineering Research Center for Human Settlements, China Architecture Design & Research Group, Xicheng District, Beijing 100044, China
    School of Architecture, Tsinghua University, Haidian District, Beijing 100084, China)

  • Yu Wang

    (China National Engineering Research Center for Human Settlements, China Architecture Design & Research Group, Xicheng District, Beijing 100044, China)

  • Shuhua Li

    (School of Architecture, Tsinghua University, Haidian District, Beijing 100084, China)

  • Qitao Wu

    (School of Design, Silla University, Sasang-gu, Busan 46958, Republic of Korea)

  • Taecheol Lee

    (Department of Architecture, Pusan National University, Geumjeong-gu, Busan 46241, Republic of Korea)

  • Seonghwan Yoon

    (Department of Architecture, Pusan National University, Geumjeong-gu, Busan 46241, Republic of Korea)

Abstract

Global warming and the urban heat island effect has aroused the attention of research on the outdoor thermal environment. As outdoor spaces often used by citizens, streets play an important role in improving the thermal environment. In this study, six factors relating to street geometries and tree configurations in Busan are measured and quantified to form 32 typical scenarios. The degree of importance of these six factors is evaluated based on ENVI-met simulation results, and GeoDetector is introduced to evaluate the interactions between the factors and their impacts on the outdoor thermal environment. This study confirms the significantly higher impact of street geometry factors on the air temperature and physiological equivalent temperature compared to tree configuration factors. Particularly, H b /W s shows the most significant impact during the research period. The impact of interactions between any two factors of street geometry is much higher than that of interactions between the geometry and tree configuration factors and that of interactions between the tree configuration factors. We recommend dynamically adjusting the relationship between street geometry and tree configurations in different situations to improve the outdoor thermal environment, especially at noon and in the afternoon.

Suggested Citation

  • Jindong Wu & Yu Wang & Shuhua Li & Qitao Wu & Taecheol Lee & Seonghwan Yoon, 2024. "Quantitative Study on the Effects of Street Geometries and Tree Configurations on the Outdoor Thermal Environment," Energies, MDPI, vol. 17(9), pages 1-24, May.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:9:p:2223-:d:1388735
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/9/2223/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/9/2223/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    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. Vicente Rios Ibañez, 2014. "What drives regional unemployment convergence?," ERSA conference papers ersa14p924, European Regional Science Association.
    2. Burhan Can Karahasan & Firat Bilgel, 2018. "Economic Geography, Growth Dynamics and Human Capital Accumulation in Turkey: Evidence from Regional and Micro Data," Working Papers 1233, Economic Research Forum, revised 10 Oct 2018.
    3. Ageliki Anagnostou & Ioannis Panteladis & Maria Tsiapa, 2015. "Disentangling different patterns of business cycle synchronicity in the EU regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 615-641, August.
    4. Marrocu, Emanuela & Paci, Raffaele, 2013. "Different tourists to different destinations. Evidence from spatial interaction models," Tourism Management, Elsevier, vol. 39(C), pages 71-83.
    5. Sanglim Yoo & John E. Wagner, 2016. "A review of the hedonic literatures in environmental amenities from open space: a traditional econometric vs. spatial econometric model," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(1), pages 141-166, March.
    6. Ilenia Epifani & Rosella Nicolini, 2013. "On The Population Density Distribution Across Space: A Probabilistic Approach," Journal of Regional Science, Wiley Blackwell, vol. 53(3), pages 481-510, August.
    7. Dubey, Subodh & Sharma, Ishant & Mishra, Sabyasachee & Cats, Oded & Bansal, Prateek, 2022. "A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 63-95.
    8. Thomas M. Fullerton & Arturo Bujanda, 2018. "Commercial property values in a border metropolitan economy," Asia-Pacific Journal of Regional Science, Springer, vol. 2(2), pages 337-360, August.
    9. Bhat, Chandra R. & Pinjari, Abdul R. & Dubey, Subodh K. & Hamdi, Amin S., 2016. "On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 240-263.
    10. Tingzhu Li & Ran Liu & Wei Qi, 2019. "Regional Heterogeneity of Migrant Rent Affordability Stress in Urban China: A Comparison between Skilled and Unskilled Migrants at Prefecture Level and Above," Sustainability, MDPI, vol. 11(21), pages 1-26, October.
    11. Jenn, Alan & Azevedo, Inês L. & Ferreira, Pedro, 2013. "The impact of federal incentives on the adoption of hybrid electric vehicles in the United States," Energy Economics, Elsevier, vol. 40(C), pages 936-942.
    12. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2014. "Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices," Journal of Urban Economics, Elsevier, vol. 80(C), pages 76-86.
    13. Han Yue & Tao Hu, 2021. "Geographical Detector-Based Spatial Modeling of the COVID-19 Mortality Rate in the Continental United States," IJERPH, MDPI, vol. 18(13), pages 1-16, June.
    14. Raffaele Paci & Emanuela Marrocu, 2014. "Tourism and regional growth in Europe," Papers in Regional Science, Wiley Blackwell, vol. 93, pages 25-50, November.
    15. Ye, Xinyue & Yue, Wenze, 2014. "Comparative analysis of regional development: Exploratory space-time data analysis and open source implementation," Economics Discussion Papers 2014-20, Kiel Institute for the World Economy (IfW Kiel).
    16. J. Paul Elhorst & Katarina Zigova, 2011. "Evidence of Competition in Research Activity among Economic Department using Spatial Econometric Techniques," Working Paper Series of the Department of Economics, University of Konstanz 2011-04, Department of Economics, University of Konstanz.
    17. Blázquez Gomez, Leticia M. & Filippini, Massimo & Heimsch, Fabian, 2013. "Regional impact of changes in disposable income on Spanish electricity demand: A spatial econometric analysis," Energy Economics, Elsevier, vol. 40(S1), pages 58-66.
    18. Jorge Luis Casanova Ferrando, 2019. "The Airbnb Effect on theRental Market: the Case of Madrid," Studies on the Spanish Economy eee2019-34, FEDEA.
    19. Gábor Békés & Péter Harasztosi, 2018. "Grid and shake: spatial aggregation and the robustness of regionally estimated elasticities," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 143-170, January.
    20. Srikant Devaraj & Marcus T. Wolfe & Pankaj C. Patel, 2021. "Creative destruction and regional health: evidence from the US," Journal of Evolutionary Economics, Springer, vol. 31(2), pages 573-604, April.

    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:jeners:v:17:y:2024:i:9:p:2223-:d:1388735. 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.