Analysis of urban heat island and human thermal comfort in a Mediterranean city: A case study of Lecce (Italy)

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 98, P. 104849 - 104849

Published: Aug. 6, 2023

Language: Английский

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A state-of-the-art review of studies on urban green infrastructure for thermal resilient communities

Building and Environment, Journal Year: 2024, Volume and Issue: 257, P. 111524 - 111524

Published: April 12, 2024

Language: Английский

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Urban microclimate prediction based on weather station data and artificial neural network

Energy and Buildings, Journal Year: 2024, Volume and Issue: 314, P. 114283 - 114283

Published: May 13, 2024

Urban microclimate has a significant impact on building energy consumption. Building modeling (BEM) requires accurate local weather conditions near target building, whereas Typical Meteorological Year (TMY) inputs often use remote airport data. An artificial neural network (ANN) model is presented in this study to predict urban microclimates based long-term measurements from stations buildings and their significance analyzing By utilizing only few months of data, the ANN could connect meteorological parameters for whole year. The 20-year historical data at was then used generate TMY. Based original TMYs, compared heating cooling loads. This method evaluated five within city Montreal assess consumption buildings. locations, contributed an additional 2 % 14 reduction 1 10 winter

Language: Английский

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Modeling the impact of land use/land cover (LULC) factors on diurnal and nocturnal Urban Heat Island (UHI) intensities using spatial regression models

Urban Climate, Journal Year: 2024, Volume and Issue: 55, P. 101971 - 101971

Published: May 1, 2024

Language: Английский

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Understanding the impact of heatwave on urban heat in greater Sydney: Temporal surface energy budget change with land types

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 903, P. 166374 - 166374

Published: Aug. 26, 2023

The impact of heatwaves (HWs) on urban heat island (UHI) is a contentious topic with contradictory research findings. A comprehensive understanding the response and rural areas to HWs, considering underlying cause surface energy budget changes, remains elusive. This study attempts address this gap by investigating 2020 HW event in Greater Sydney Area using Advanced Weather Research Forecasting (WRF) model 250-m high resolution. Findings indicate that intensifies nighttime UHI approximately 4 °C. An analysis budgets reveals store more during due receiving solar radiation less evapotranspiration compared areas. maximum storage flux can be around 200 W/m2 higher than post-HW. stored released at nightime, raising air temperature Forests savannas have relatively lower fluxes transpiration albedo, only 50 In contrast, negative synergistic effect detected between 2-m HW. may because other meteorological conditions including wind substantial impacts pattern. strong hot dry winds coming from west resulted western district, intra-city disparities are higher. Meanwhile, forest area also experiences temperatures westward winds. addition, changes direction alter distribution northern region. findings present provide some insights into mitigation

Language: Английский

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Towards an improved representation of the urban heat island effect : A multi-scale application of XGBoost for madrid

Urban Climate, Journal Year: 2024, Volume and Issue: 55, P. 101982 - 101982

Published: May 1, 2024

Cities are considered local "hotspots" of climate change, therefore, the improvement urban present description as well future projections is paramount for designing adaptation and mitigation strategies. Physically-based numerical models often have coarse resolutions do not parametrisations to adequately represent physical processes at scale. This article presents an innovative application XGBoost (a machine learning approach) alternative explore improve Madrid. XGBoost's ability reproduce 2-m air temperature land surface (LST), heat island (UHI) effect, was assessed. trained with a set ERA5 predictors (0.25°) calibrated observations from ground stations (2000−2022) remote sensing data (2004–2022). Several sensitivity cases were performed assess results dependency their resolution. evaluated daily scale maximum minimum temperatures (Tmax Tmin, respectively) LST, hourly LST. Overall, reveals good performance significant added value against all variables both UHI UHI. study promising technology describe climate.

Language: Английский

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Spatio-temporal dynamics of land use transitions associated with human activities over Eurasian Steppe: Evidence from improved residual analysis

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 905, P. 166940 - 166940

Published: Sept. 9, 2023

Language: Английский

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The heat island effect, digital technology, and urban economic resilience: Evidence from China

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 209, P. 123802 - 123802

Published: Oct. 14, 2024

Language: Английский

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Study on urban heatwave characteristics and thermal stress scenarios based on China's heatwave hazard zoning

Urban Climate, Journal Year: 2024, Volume and Issue: 55, P. 101957 - 101957

Published: May 1, 2024

Language: Английский

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Exploring the influence of block environmental characteristics on land surface temperature and its spatial heterogeneity for a high-density city

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 118, P. 105973 - 105973

Published: Nov. 9, 2024

Language: Английский

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