Impact of urban heat island effect on the heating and cooling loads of residential buildings in Tianjin City, China

Meng, Fanchao; Ren, Guoyu; Jun, Guo; Zhang, Lei; Zhang, Ruixue

doi:10.18306/dlkxjz.2020.08.005

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…Air temperature change has a direct and strong correlation with energy consumption. Previous studies examined the relationships between UHIs and the energy consumption of cities in northern China, indicating that for every increase of 1°C in UHII, the average annual heating loads of the city will be decreased by 4.01 kWh/m 2 in winter, while the annual average cooling loads will be increased by 1.05 kWh/m 2 in summer (Meng, Guo, et al., 2020; Meng, Ren, et al., 2020). In our present work, it is can be concluded that local climate zones organized by anthropogenic factors largely modulate the dominant spatial pattern of CUHII, while different SWPs influence the temporal variation in strength of CUHII during winter in Beijing.…”

Section: Discussionmentioning

confidence: 99%

Modulation of Wintertime Canopy Urban Heat Island (CUHI) Intensity in Beijing by Synoptic Weather Pattern in Planetary Boundary Layer

et al. 2022

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Studying the spatiotemporal variations of the urban heat island (UHI) effect and its cause is important towards understanding urban climate change, planning and green development, and disaster mitigation. In this paper, by using surface observations and reanalysis data with objective classification of synoptic weather patterns (SWPs), we analyze the associations between canopy UHI intensity (CUHI) and SWPs in the planetary boundary layer (PBL) and their potential drivers during wintertime of the period 2012–2017. Six dominant types of SWP are identified as follows: In the case of Types 3, 4, and 6, weak high‐pressure systems exist to the south of Beijing, resulting in weak southerly winds with low PBL height, large cloud coverage and high relative humidity (RH). These conditions are generally conducive to a strengthening of the CUHII. In contrast, under Types 1, 2, and 5, high‐pressure systems are located to the northwest of Beijing, and the associated strong northwesterly flows of dry and cold air strengthen the boundary layer mixing process, resulting in large wind speed and low RH. This is conducive to a weakening of the CUHII. In general, our work reveals the impacts of SWPs on the strength of CUHII mainly via the modulation of local weather conditions at diurnal and interannual scales, while spatial pattern of CUHII is largely dominated by local climate zones. Our findings have implications for CUHII forecasts, as well as impact assessments and policymaking in the context of UHI‐related energy conservation in winter over high‐density urban areas on the synoptic scale.

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Section: Discussionmentioning

confidence: 99%

Modulation of Wintertime Canopy Urban Heat Island (CUHI) Intensity in Beijing by Synoptic Weather Pattern in Planetary Boundary Layer

et al. 2022

Self Cite

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“…By using the "Morphing" deformation method [31], the meteorological parameters, such as dry bulb temperature, relative humidity, and solar radiation, in the location of the building are revised, and Energy Plus is applied to simulate the office building to study the influence of the urban heat island effect on building energy consumption. In general, the increase in urban heat island intensity and the decrease in relative humidity and wind speed lead to a decrease in the heating load and an increase in the cooling load of residential buildings [32]. The average annual heating load in urban areas decreased by 10.29% and the average annual cooling load increased by 7.48% compared with rural areas.…”

Section: Introductionmentioning

confidence: 99%

Research on Air-Conditioning Cooling Load Correction and Its Application Based on Clustering and LSTM Algorithm

Cheng-wang

et al. 2023

Applied Sciences

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Climate change and urban heat island effects affect the energy consumption of buildings in urban heat islands. In order to meet the requirements of engineering applications for detailed daily design parameters for air conditioning, the 15-year summer meteorological data for Beijing and Shanghai and the corresponding average heat island intensity data were analyzed. Using the CRITIC objective weighting method and K-means clustering analysis, the hourly change coefficient, β, of dry bulb temperature was calculated, and the LSTM algorithm was used to predict the changing trends in β. Finally, the air conditioning load model for a hospital was established using DeST (version DeST3.0 1.0.2107.14 20220712) software, and the air conditioning cooling load in summer was calculated and predicted. The results show that, compared with the original design days, regional differences in the new design days are more obvious, the maximum temperature and time have changed, and the design days parameters are more consistent with the local meteorological conditions. Design day temperatures in Shanghai are expected to continue rising for some time to come, while those in Beijing are expected to gradually return to previous levels. Among hospital buildings, the cooling load of outpatient buildings in Beijing and Shanghai will decrease by 0.69% and increase by 12.61% and by 12.12% and 15.51%, respectively, under the influence of the heat island effect. It is predicted to decrease by 1.35% and increase by 29.75%, respectively, in future. The cooling load of inpatient buildings in Beijing and Shanghai increased by 0.27% and 6.71%, respectively, and increased by 7.13% and 8.09%, respectively, under the influence of the heat island effect, and is predicted to decrease by 0.93% and increase by 16.07%, respectively, in future.

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Urban ventilation planning and its associated benefits based on numerical experiments: A case study in beijing, China

Zheng

Ren²,

Gao³

et al. 2022

Building and Environment

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Impact of urban heat island effect on the heating and cooling loads of residential buildings in Tianjin City, China

Cited by 4 publications

References 15 publications

Modulation of Wintertime Canopy Urban Heat Island (CUHI) Intensity in Beijing by Synoptic Weather Pattern in Planetary Boundary Layer

Modulation of Wintertime Canopy Urban Heat Island (CUHI) Intensity in Beijing by Synoptic Weather Pattern in Planetary Boundary Layer

Research on Air-Conditioning Cooling Load Correction and Its Application Based on Clustering and LSTM Algorithm

Urban ventilation planning and its associated benefits based on numerical experiments: A case study in beijing, China

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