Evaluating the Impact of Heat Mitigation Strategies Using Added Urban Green Spaces during a Heatwave in a Medium-Sized City
Abstract
:1. Introduction
2. Data and Methods
2.1. Land Use Classification by Local Climate Zone System
2.2. Study Area and the Investigated Land Cover Scenarios
2.3. Thermal Sensation Modeling
3. PT Pattern of Original Land Cover and Difference in PT Patterns under Different Land Cover Scenarios
3.1. PT Patterns under NE Wind in Daytime (05.08.2015 at 14 LST)
3.2. PT Patterns under NE Wind at Night (06.08.2015 at 1 LST)
3.3. PT Patterns under S Wind in Daytime (08.08.2015 at 14 LST)
3.4. PT Patterns under S Wind at Night (09.08.2015 at 1 LST)
4. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Oke, T.R. Boundary Layer Climates; Routledge: London, UK, 1987. [Google Scholar]
- Lehnert, M.; Geletic, J.; Dobrovolný, P.; Jurek, M. Temperature differences among local climate zones established by mobile measurements in two central European cities. Clim. Res. 2018, 75, 53–64. [Google Scholar] [CrossRef]
- Oke, T.R.; Mills, G.; Christen, A.; Voogt, J.A. Urban Climates; Cambridge University Press: Cambridge, UK, 2017. [Google Scholar]
- Buchholz, S.; Kossmann, M. Visualization of summer heat intensity for different settlement types and varying surface fraction partitioning. Landsc. Urban Plan. 2015, 144, 59–64. [Google Scholar] [CrossRef]
- Bowler, D.E.; Buyung-Ali, L.; Knight, T.M.; Pullin, A.S. Urban greening to cool towns and cities: A systematic review of the empirical evidence. Landsc. Urban Plan. 2010, 97, 147–155. [Google Scholar] [CrossRef]
- Loughner, C.P.; Allen, D.J.; Zhang, D.L.; Pickering, K.E.; Dickerson, R.R.; Landry, L. Roles of urban tree canopy and buildings in urban heat island effects: Parametrization and preliminary results. J. Appl. Meteorol. Climatol. 2012, 51, 1775–1793. [Google Scholar] [CrossRef]
- Lee, H.; Mayer, H.; Chen, L. Contribution of trees and grasslands to the mitigation of human heat stress in a residential district of Freiburg, Southwest Germany. Landsc. Urban Plan. 2016, 148, 37–50. [Google Scholar] [CrossRef]
- Geletič, J.; Lehnert, M.; Dobrovolný, P.; Žuvela-Aloise, M. Spatial modelling of summer climate indices based on local climate zones: Expected changes in the future climate of Brno, Czech Republic. Clim. Chang. 2019, 152, 487–502. [Google Scholar] [CrossRef]
- Žuvela-Aloise, M.; Koch, R.; Buchholz, S.; Früh, B. Modelling the potential of green and blue infrastructure to reduce urban heat load in the city of Vienna. Clim. Chang. 2016, 135, 425–438. [Google Scholar] [CrossRef]
- Shashua-Bar, L.; Pearlmutter, D.; Erell, E. The influence of trees and grass on outdoor thermal comfort in a hot-arid environment. Int. J. Climatol. 2011, 31, 1498–1506. [Google Scholar] [CrossRef]
- Song, J.; Wang, Z.H. Impacts of mesic and xeric urban vegetation on outdoor thermal comfort and microclimate in Phoenix, AZ. Build. Environ. 2015, 94, 558–568. [Google Scholar] [CrossRef]
- Coutts, A.M.; White, E.C.; Tapper, N.J.; Beringer, J.; Livesley, S.J. Temperature and human thermal comfort effects of street trees across three contrasting street canyon environments. Theor. Appl. Climatol. 2016, 124, 55–68. [Google Scholar] [CrossRef]
- Upreti, R.; Wang, Z.H.; Yang, J. Radiative shading effect of urban trees on cooling the regional built environment. Urban For. Urban Green. 2017, 26, 18–24. [Google Scholar] [CrossRef]
- Chen, X.; Zhao, P.; Hua, Y.; Ouyang, L.; Zhua, L.; Ni, G. Canopy transpiration and its cooling effect of three urban tree species in a subtropical city- Guangzhou, China. Urban For. Urban Green 2019, 43, 126368. [Google Scholar] [CrossRef]
- Wang, C.; Wang, Z.H.; Wang, C.; Myint, S.W. Environmental cooling provided by urban trees under extreme heat and cold waves. Rem. Sens. Environ. 2019, 227, 28–43. [Google Scholar] [CrossRef]
- Shaw, R.H.; Pereira, A.R. Aerodynamic roughness of a plant canopy: A numerical experiment. Agric. Meteorol. 1982, 26, 51–65. [Google Scholar] [CrossRef]
- Gál, T.; Mahó, S.I.; Skarbit, N.; Unger, J. Numerical modelling for analysis of the effect of different urban green spaces on urban heat load patterns in the present and in the future. Comp. Environ. Urban Syst. 2021, 87, 101600. [Google Scholar] [CrossRef]
- Jendritzky, G.; Staiger, H.; Bucher, K.; Graetz, A.; Laschewski, G. The Perceived Temperature—The Method of the Deutscher Wetterdienst for the Assessment of Cold Stress and Heat Load for the Human Body. In Proceedings of the Workshop on Windchill, Hosted by Environment Canada, Offenbach, Germany, 3–7 April 2000. [Google Scholar]
- De Freitas, C.R.; Grigorieva, E.A. A comprehensive catalogue and classification of human thermal climate indices. Int. J. Biometeorol. 2015, 59, 109–120. [Google Scholar] [CrossRef] [PubMed]
- Koppe, C.; Kovats, S.; Jendritzky, G.; Menne, B. Heat-Waves: Risks and Responses; Health and Global Environmental Change Series, No. 2; World Health Organization: Geneva, Switzerland, 2004. [Google Scholar]
- De Freitas, C.R.; Grigorieva, E.A. A comparison and appraisal of a comprehensive range of human thermal climate indices. Int. J. Biometeorol. 2017, 61, 487–512. [Google Scholar] [CrossRef] [PubMed]
- Fanger, P.O. Thermal Comfort, Analysis and Application in Environment Engineering; Danish Technical Press: Copenhagen, Denmark, 1970. [Google Scholar]
- Kim, J.; Kim, K.R.; Choi, B.-C.; Lee, D.-G.; Kim, J.-S. Regional distribution of perceived temperatures estimated by the human heat budget model (the Klima-Michel model) in South Korea. Adv. Atmos. Sci. 2009, 26, 275–282. [Google Scholar] [CrossRef]
- Staiger, H.; Laschewski, G.; Grätz, A. The perceived temperature—A versatile index for the assessment of the human thermal environment. Part A: Scientific basics. Int. J. Biometeorol. 2012, 56, 165–176. [Google Scholar] [CrossRef]
- Sinsel, T.; Simon, H.; Ouyang, W.; dos Santos Gusson, C.; Shinzato, P.; Bruse, M. Implementation and evaluation of mean radiant temperature schemes in the microclimate model ENVI-met. Urban Clim. 2022, 45, 101279. [Google Scholar] [CrossRef]
- Fröhlich, D.; Gangwisch, M.; Matzarakis, A. Effect of radiation and wind on thermal comfort in urban environments—Application of the RayMan and SkyHelios model. Urban Clim. 2019, 27, 1–7. [Google Scholar] [CrossRef]
- Stewart, I.D.; Oke, T.R. Local Climate Zones for urban temperature studies. Bull. Am. Meteorol. Soc. 2012, 93, 1879–1900. [Google Scholar] [CrossRef]
- Brousse, O.; Martilli, A.; Foley, M.; Mills, G.; Bechtel, B. WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid. Urban Clim. 2016, 17, 116–134. [Google Scholar] [CrossRef]
- Hammerberg, K.; Brousse, O.; Martilli, A.; Mahdavi, A. Implications of employing detailed urban canopy parameters for mesoscale climate modelling: A comparison between WUDAPT and GIS databases over Vienna, Austria. Int. J. Climatol. 2018, 38, e1241–e1257. [Google Scholar] [CrossRef]
- Verdonck, M.-L.; Demuzere, M.; Hooyberghs, H.; Beck, C.; Cyrys, J.; Schneider, A.; Dewulf, R.; Van Coillie, F. The potential of local climate zones maps as a heat stress assessment tool, supported by simulated air temperature data. Landsc. Urban Plan. 2018, 178, 183–197. [Google Scholar] [CrossRef]
- Huang, F.; Jiang, S.; Zhan, W.; Bechtel, B.; Liu, Z.; Demuzere, M.; Huang, Y.; Xu, Y.; Ma, L.; Xia, W.; et al. Mapping local climate zones for cities: A large review. Rem. Sens. Environ. 2023, 292, 113573. [Google Scholar] [CrossRef]
- Bechtel, B.; Alexander, P.J.; Böhner, J.; Ching, J.; Conrad, O.; Feddema, J.J.; Mills, G.; See, L.; Stewart, I.D. Mapping local climate zones for a worldwide database of the form and function of cities. ISPRS Int. J. Geo Inf. 2015, 4, 199–219. [Google Scholar] [CrossRef]
- Geletič, J.; Lehnert, M.; Savić, S.; Milošević, D. Modelled spatiotemporal variability of outdoor thermal comfort in local climate zones of the city of Brno, Czech Republic. Sci. Total Environ. 2018, 624, 385–395. [Google Scholar] [CrossRef]
- Giannaros, C.; Agathangelidis, I.; Papavasileiou, G.; Galanaki, E.; Kotroni, V.; Lagouvardos, K.; Giannaros, T.M.; Cartalis, C.; Matzarakis, A. The extreme heat wave of July–August 2021 in the Athens urban area (Greece): Atmospheric and human-biometeorological analysis exploiting ultra-high resolution numerical modeling and the local climate zone framework. Sci. Total Environ. 2023, 857, 159300. [Google Scholar] [CrossRef]
- Köppen, W. Klassifikation der Klimate nach Temperatur, Niedershlag und Jahreslauf. Pet. Mitt. 1918, 64, 194–203. [Google Scholar]
- Beck, H.E.; Zimmermann, N.E.; McVicar, T.R.; Vergopolan, N.; Berg, A.; Wood, E.F. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 2018, 5, 180214. [Google Scholar] [CrossRef] [PubMed]
- Skarbit, N.; Stewart, I.D.; Unger, J.; Gál, T. Employing an urban meteorological network to monitor air temperature conditions in the ‘local climate zones’ of Szeged, Hungary. Int. J. Climatol. 2017, 37, 582–596. [Google Scholar] [CrossRef]
- Sievers, U. Das kleinskalige Strömungsmodell MUKLIMO_3 Teil 1: Theoretische Grundlagen, PC-Basisversion und Validierung; Deutschen Wetterdienstes: Offenbach am Maine, Germany, 2012.
- Sievers, U. Das kleinskalige Strömungsmodell MUKLIMO_3. Teil 2: Thermodynamische Erweiterungen; Deutschen Wetterdienstes: Offenbach am Maine, Germany, 2016.
- Bokwa, A.; Geletič, J.; Lehnert, M.; Žuvela-Aloise, M.; Hollósi, B.; Gál, T.; Skarbit, N.; Dobrovolný, P.; Hajto, M.J.; Kielar, R.; et al. Heat load assessment in Central European cities using an urban climate model and observational monitoring data. Energy Build. 2019, 201, 53–69. [Google Scholar] [CrossRef]
- Staiger, H.; Bucher, K.; Jendritzky, G. Gefühlte Temperatur. Die physiologisch gerechte Bewertung von Wärmebelastung und Kältestress beim Aufenthalt im Freien in der Maßzahl Grad Celsius. Ann. Meteorol. 1997, 33, 100–107. [Google Scholar]
- Matzarakis, A. Hitze in Städten—Quantifizierung, Warnsysteme und Hitzeaktionspläne zum Schutz der menschlichen Gesundheit. Promet 2023, 106, 61–70. [Google Scholar] [CrossRef]
PT Ranges (°C) | Thermal Perception Categories | Thermo-Physiological Stress Categories |
---|---|---|
PT ≥ 38 | Very hot | Extreme heat stress |
32 ≤ PT < 38 | Hot | Great heat stress |
26 ≤ PT < 32 | Warm | Moderate heat stress |
20 ≤ PT < 26 | Slightly warm | Slight heat stress |
0 < PT < 20 | Comfortable | Comfort possible |
−13 < PT ≤ 0 | Slightly cool | Slight cold stress |
−26 < PT ≤ −13 | Cool | Moderate cold stress |
−39 < PT ≤ −26 | Cold | Great cold stress |
PT ≤ −39 | Very cold | Extreme cold stress |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Skarbit, N.; Unger, J.; Gál, T. Evaluating the Impact of Heat Mitigation Strategies Using Added Urban Green Spaces during a Heatwave in a Medium-Sized City. Sustainability 2024, 16, 3296. https://doi.org/10.3390/su16083296
Skarbit N, Unger J, Gál T. Evaluating the Impact of Heat Mitigation Strategies Using Added Urban Green Spaces during a Heatwave in a Medium-Sized City. Sustainability. 2024; 16(8):3296. https://doi.org/10.3390/su16083296
Chicago/Turabian StyleSkarbit, Nóra, János Unger, and Tamás Gál. 2024. "Evaluating the Impact of Heat Mitigation Strategies Using Added Urban Green Spaces during a Heatwave in a Medium-Sized City" Sustainability 16, no. 8: 3296. https://doi.org/10.3390/su16083296