The Interactive Impact of Building Diversity on the Thermal Balance and Micro-Climate Change under the Influence of Rapid Urbanization
Abstract
:1. Introduction
2. Materials and Methods
2.1. Long-Term and Mobile Observational Study Using SRST and GIS Analysis Together with the CFD Approach
- (a)
- Firstly, long-term observation [38] of meteorological data [39,40], climate factors [41], and remote sensing images [42] during the period 1980–2016 were applied and analyzed. For this purpose, raster maps of Wuhan City (8573 km2) at ten-yearly intervals from 1980 to 2016 were established and carefully analyzed using specified raster information. Afterwards, SRST coupled with GIS [43] approaches were used and data analyzed by ArcMap 10.4.1 (Esri China Information Technology Co. Ltd, Beijing, China) with the property of cell size (X, Y) and value 30, 30, and a spatial reference system of one meter. Accordingly, land-use changes were carefully assessed and measured due to the long-term impact of rapid urbanization [44]. In 2016, the urban land cover area was 709.9 km2, a 3.21 times increase from 220.5 km2 (1980) to about 489.3 km2 (2016) and the water surfaces (WS) [45] declined by 145.64 km2 (16% of the total range) in the urban area of Wuhan. As it was predicted [3], the rate of urbanism may reach 84% and the population of the built-up spaces will be 5.02 million, where the total population will increase by about 11.8 million. If the growth of the city continues on this trend, by 2020, the decrease has been predicted to be about 204.45 km2 (22%). On this point, we aimed to determine the long-term impact of the urbanization process on climate factors (Ta; air temperature, RH; relative humidity) to get the accrued data, which is needed to find the significant changes that have been linked with the greatest climate and land-use changes [46] over time during urban transformation.
- (b)
- As the second step, data collection for the long-term observational study [47] (1980–2016) was conducted from the weather stations at Huangpi (黄陂; 30°52′55.7″ N, 114°22′32.4″ E), Xinzhou (新洲; 30°50′26.2″ N, 114°48′03.2″ E), Caidian (蔡甸; 30°34′54.5″ N, 114°01′45.6″ E), and Jiangxia (江夏; 30°22′29.8″ N, 114°19′15.8″ E), which are available in the metrological bureau of Wuhan. Due to the long-term observation, tipping points were selected to represent the most significant changes regarding the transformation of water surfaces into urban construction land. Accordingly, and due to the major objective of this study, quantitative evaluation and measurement of these changes on the urban microclimate were undertaken in different residential urban blocks under the impact of UHII. These were classified as A, B and C; high-rise buildings (10–34 stories), mid-rise buildings (7–9 stories), and low-rise buildings (1–3 stories), respectively [36]. All the changes discovered in land-use transformation during Wuhan City’s urbanization from 1980 to 2016 can be seen in Figure 1.
- (c)
- The third step involved the mobile observation [48] of meteorological data, remote sensing images, and climate factors focusing on air temperature (Ta), relative humidity (RH), solar radiation, and wind. Therefore, in order to study the influence of block morphology (form and height) on urban microclimates, fixed and mobile observation was adopted [49]. The main equipment and instruments included a small weather station that included a wind speed and direction indicator, anemometer (placed 1.5 m above ground and using JTSOFT Meter V1.3 software to extract the data—(JT Technology, Beijing, China), a small portable temperature and humidity meter (data-logger using TRLog software to extract the data), mobile camcorder, and a handheld global positioning system (HhGPS). For the mobile observation approach, a walking method at a speed of 3 km/s for all blocks was used in the morning (5:30–6:30 am), at noon (13:00–14:00 pm), and in the evening (21:00–22:00 pm). Observations and measurements were recorded at the same time for all blocks within the area of 1 km.
- (d)
- The fourth step was a simulation method using CFD [50,51,52,53] analysis in which digital models of low-rise, mid-rise, and high-rise residential blocks were generated (using AutoCAD 2018—AUTODESK, California, USA) and a CFD domain [54] was set up after adding proper mesh [55] on models by ICEM-CFD 15. The study was performed to evaluate urban microclimates with the interactive impact of building diversity on the thermal balance that involves wind flow.
2.2. Modeling Using the CFD Technique
2.2.1. RANS Equation System (Setting up the Standard k-ε Model)
2.2.2. Computational Domain Size within the Urban Block Scale
3. Study Area and Setting
3.1. Study Area
3.2. Case Settings
3.3. Data Source
4. Results
4.1. The Impact of Land Use Change on UHII
4.2. The Impact of Urban Block Morphology on Urban Microclimates
4.3. CFD Simulation Results
- (a)
- The air change rates in cases A, B, and C are 3 m/s, 2.4 m/s, and 1.2 m/s, respectively. It shows that high-rise buildings with a high-value plot ratio can increase the air movement around the building and force the wind at the top of the buildings downwards to the earth.
- (b)
- The low-rise building model in the compact and dense area shows that heat gained during the day increases, but cannot be released efficiently and so increases the air temperature because of a lack of ventilation.
- (c)
- By reducing the air movement in the dense area in case C, relative humidity will decline substantially and increase UHII.
- (d)
- In the mid-rise building model, the air movement is almost at the average rate with a larger comfort zone, which is related to the proportion rate between building density and plot ratio.
- (e)
- Overall, building density is the most important morphological indicator to increase UHII compared with open spaces which, according to the plot ratio indicator, can reinforce air movement and increase natural ventilation to mitigate the negative effects of UHIIs.
5. Discussion
6. Conclusions
- (1)
- The UHII increased by 2 °C as a result of a 16% decrease in water surface area within the developed regions of Wuhan, and the wind speed decreased substantially because of an increase in urban land cover and a reduction in water surfaces in urban areas. This change in water surface area also caused a decline in both natural ventilation and air movement that could have alleviated UHII.
- (2)
- Wuhan urban land cover area has turned over three-fold compared to that of 1980, which consequently has enlarged the SUHI. This increase, with reduction in water surfaces in developed areas, has caused more heat gain, which has led to the destruction of the ecosystem and changed the heat balance and microclimate within urban blocks.
- (3)
- Investigations have shown that Wuhan is developing rapidly with more of a tendency to develop in the urban fringe, and if the city develops along the same lines, UHII will progressively increase and natural ventilation will dramatically decrease by 2020.
- (4)
- Urban morphology and block morphological indicators have a significant impact on microclimate and heat balance within the urban blocks, in which building density has the strongest effect on the environment, and plot ratio is another indicator that can intensify the air movement within the blocks. Depending on the combination of changes for the indicators, various changes can be found for air temperature and UHII. These indicators can mitigate UHII by controlling the air movement around the building.
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Constant | Value |
---|---|
Cµ | 0.09 |
Ce1 | 1.44 |
Ce2 | 1.92 |
σk | 1.0 |
σε | 1.3 |
Cases | Observation Technique | Building Types | Building Density (Built-up Area/Total Site Area) (%) | Plot Ratio (Gross Floor Area/Total Site Area) | Greenery Ratio (Green Area/Total Site Area) (%) | Water Area Reduction (km2) |
---|---|---|---|---|---|---|
A | Mobile observation | High-rise (10~34 story building) | 19 | 16.6 | 19 | - |
B | Mid-rise (7~9 story building) | 21 | 5.6 | 25 | - | |
C | Low- rise (1~3 story building) | 23 | 2.1 | 13 | - | |
D | Fixed observation | Park | - | 1.6 | 80 | 4.5 (7.2%) |
Wuhan (LU/LC) | Long-term observation (1980–2016) | Building/urban morphology | - | - | 136.4 reduction | 145.64 (16% of the total range) |
Cases | Categories/Types | Time Record | Moring (5:30–6:30) | Noon (1:00–2:00) | Night (9:00–10:00) |
---|---|---|---|---|---|
A | High-rise Building | SR | 18 | 28.1 | 23.8 |
ER | 18.4 | 27 | 21.4 | ||
B | Mid-rise Building | SR | 18 | 29.5 | 23 |
ER | 17.2 | 27.7 | 22.2 | ||
C | Low-rise Building | SR | 17.8 | 27.6 | 25.5 |
ER | 18.9 | 28.4 | 22.9 | ||
D | Park | SR | 13.2 | 26.7 | 24.4 |
ER | 11.8 | 26.4 | 22.7 | ||
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Makvandi, M.; Li, B.; Elsadek, M.; Khodabakhshi, Z.; Ahmadi, M. The Interactive Impact of Building Diversity on the Thermal Balance and Micro-Climate Change under the Influence of Rapid Urbanization. Sustainability 2019, 11, 1662. https://doi.org/10.3390/su11061662
Makvandi M, Li B, Elsadek M, Khodabakhshi Z, Ahmadi M. The Interactive Impact of Building Diversity on the Thermal Balance and Micro-Climate Change under the Influence of Rapid Urbanization. Sustainability. 2019; 11(6):1662. https://doi.org/10.3390/su11061662
Chicago/Turabian StyleMakvandi, Mehdi, Baofeng Li, Mohamed Elsadek, Zeinab Khodabakhshi, and Mohsen Ahmadi. 2019. "The Interactive Impact of Building Diversity on the Thermal Balance and Micro-Climate Change under the Influence of Rapid Urbanization" Sustainability 11, no. 6: 1662. https://doi.org/10.3390/su11061662
APA StyleMakvandi, M., Li, B., Elsadek, M., Khodabakhshi, Z., & Ahmadi, M. (2019). The Interactive Impact of Building Diversity on the Thermal Balance and Micro-Climate Change under the Influence of Rapid Urbanization. Sustainability, 11(6), 1662. https://doi.org/10.3390/su11061662