Abstract
New construction has resulted in impervious surfaces increasingly replacing natural landscapes, altering surface radiation, thermal properties, and humidity in urban areas. Based on Landsat-8 data, the temporal and spatial impacts of the construction of Dalian Jinzhouwan Airport and Beijing Daxing Airport on the thermal environment were studied. The local thermal gradient (LTG) of the airport before and after construction is compared. The results showed that after the completion of the airport, the LTG value of Daxing Airport increased by 0.033 and that of Jinzhou Bay Airport increased by 0.009. After the airport operation, LTG values increase again. Daxing Airport added another 0.053, and Jinzhou Bay Airport added another 0.127. Two land classification models (land use type, LUT; local climate zone, LCZ) were used to explore the relationship between land use type and LTG. The results show that the increase of alloy buildings after the completion of the airport has a great influence on the thermal environment of the two study areas. The operation of airports will further enhance this effect. Our study can provide a reference for the influence of large-scale traffic construction on the urban thermal environment.
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All data, models, and code generated or used during the study appear in the submitted article.
References
Aboelata A (2020) Vegetation in different street orientations of aspect ratio (H/W 1:1) to mitigate UHI and reduce buildings’ energy in arid climate. Build Environ 172(1):1–12
Bouyer J, Inard C, Musy M (2011) Microclimatic coupling as a solution to improve building energy simulation in an urban context. Energy and Buildings 43(7):1549–1559
Connors JP, Galletti CS, Chow WTL (2012) Landscape configuration and urban heat island effects: assessing the relationship between landscape characteristics and land surface temperature in Phoenix Arizona. Landscape Ecology 28(2):271–283
Demuzere M, Kittner J, Bechtel B (2021) LCZ generator: a web application to create local climate zone maps. Front Environ Sci 9(2021)
Dong P, Jiang SD, Zhan WF et al (2022) Diurnally continuous dynamics of surface urban heat island intensities of local climate zones with spatiotemporally enhanced satellite-derived land surface temperatures. Building and Environment 218:109105
Feyisa GL, Dons K, Meilby H (2014) Efficiency of parks in mitigating urban heat island effect: an example from Addis Ababa. Landsc Urban Plan 123(1):87–95
Imhoff ML, Zhang P, Wolfe RE et al (2010) Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sens Environ 114(3):504–513
Kong FH, Yin HW, Wang CZ et al (2014) A satellite image-based analysis of factors contributing to the green-space cool island intensity on a city scale. Urban Forestry & Urban Greening 13(4):846–853
Li J, Zhan W, Hong F et al (2021) Similarities and disparities in urban local heat islands responsive to regular-, stable-, and counter-urbanization: a case study of Guangzhou China. Building and Environment 199(1):1–14
Lin P, Lau SSY, Qin H et al (2017) Effects of urban planning indicators on urban heat island: a case study of pocket parks in high-rise high-density environment. Landsc Urban Plan 168(1):48–60
Lin Y, Jim CY, Deng J et al (2018) Urbanization effect on spatiotemporal thermal patterns and changes in Hangzhou (China). Build Environ 145(1):166–176
Ma DX, Wang YP, Zhou D L et al (2022) The renew plans of urban thermal environment optimization for traditional districts in Xi’an, China
Meng Q, Zhang L, Sun Z et al (2018) Characterizing spatial and temporal trends of surface urban heat island effect in an urban main built-up area: a 12-year case study in Beijing China. Remote Sensing of Environment 204(1):826–837
Mohammad P, Goswami A, Bonafoni S (2019) The impact of the land cover dynamics on surface urban heat island variations in semi-arid cities: a case study in Ahmedabad City, India, using multi-sensor/source data. Sensors (Basel) 19(17)
Renard F, Alonso L, Fitts Y et al (2019) Evaluation of the effect of urban redevelopment on surface urban heat islands. Remote Sensing 11(1):1–13
Salvati A, CochRoura H, Cecere C (2017) Assessing the urban heat island and its energy impact on residential buildings in Mediterranean climate: Barcelona case study. Energy and Buildings 146(1):38–54
Schwarz N, Lautenbach S, Seppelt R (2011) Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures. Remote Sens Environ 115(12):3175–3186
Sekertekin A, Bonafoni S (2020) Sensitivity analysis and validation of daytime and nighttime land surface temperature retrievals from Landsat 8 using different algorithms and emissivity models. Remote Sensing 12(17):2776
Seto KC, Christensen P (2013) Remote sensing science to inform urban climate change mitigation strategies. Urban Climate 3(1):1–6
Taslima S, Parapari Danial Monsefi, Shafaghat Arezou (2015) Urban design guidelines to mitigate urban heat island (UHI) effects in hot dry cities. Jurnal Teknologi (Sciences & Engineering) 74(4):119–124
Wan J, Zhu M (2021) Contribution degree of different surface factors in urban interior to urban thermal environment. Advances in Meteorology 1:1–14
Wan J, Zhu M, Ding W (2021) Accuracy evaluation and parameter analysis of land surface temperature inversion algorithm for Landsat-8 data. Advances in Meteorology 1:1–16
Wan J, Yong B, Zhou XF (2022) Spatial and temporal analysis of the increasing effects of large-scale infrastructure construction on the surface urban heat island. Ecotoxicol Environ Saf 237(1):1–13
Wu SS, Zhan WF, Du HL et al (2022) Identifying analogs of future thermal comfort under multiple projection scenarios in 352 Chinese cities. Sustain Cities Soc 82:103889
Wu JS, Li XC, Li S et al (2022) Spatial heterogeneity and attribution analysis of urban thermal comfort in China from 2000 to 2020. Int J Environ Res Public Health 19(9):5683
Yusuf YA, Pradhan B, Idrees MO (2014) Spatio-temporal assessment of urban heat island effects in Kuala Lumpur metropolitan city using Landsat images. Journal of the Indian Society of Remote Sensing 42(4):829–837
Zhang Y, Zhang C, Yang K et al (2022) Temporal and spatial effects of urbanization on regional thermal comfort. Land 11(5):688
Zhao C, Fu G, Liu X et al (2011) Urban planning indicators, morphology and climate indicators: a case study for a north-south transect of Beijing China. Build Environ 46(5):1174–1183
Zhou D, Xiao J, Bonafoni S et al (2018) Satellite remote sensing of surface urban heat islands: progress, challenges, and perspectives. Remote Sensing 11(1)
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The program underpinning this work is the National Key Research and Development Project of China (2021YFB3900015) and the National Natural Science Foundation of China (92047301).
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J K.W proposed the initial idea for the study and conducted the study design. J K. W and Y. Liu are responsible for programming and data processing. B.Y and X F. Z supervised and validated the experiment, and J K.W organized and drafted the manuscript.
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Wan, J., Liu, Y., Yong, B. et al. Temporal and spatial effects of large airport construction and operation on the local thermal environment. Environ Sci Pollut Res 30, 13788–13800 (2023). https://doi.org/10.1007/s11356-022-23161-y
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DOI: https://doi.org/10.1007/s11356-022-23161-y