PLANT’S HEALTH AND MICROCLIMATE IN A WARMING WORLD MSc Daniel Felipe Outa Yoshida PhD Candidate Luiza Sobhie Muñoz
ENTRY ENVI-met Unilab Awards 2023
Plant’s health and microclimate in a warming world Climate change and the role of cities Cities play an important role on climate change adaptation and mitigation. Beside being great sources of Greenhouse gases (GHG), their boundaries have been expanding and their population increasing continually. Moreover, cities have been expanding rapidly in a horizontal and dispersed manner. According to WMO (2019), the physical extension of the urban areas is expanding faster than the population growth, which leads to an increase in the energy consumption and in the GHG emissions, and affects climate change and the natural systems. It is important to highlight that, in general, the urban sprawling models are based on the depletion of natural resources and on suppressing the vegetation. The alterations caused by urban expansion processes aggravate some environmental risks, like heat stress, droughts, storms, extreme precipitation, floods, landslides, pollution and others (IPCC, 2021), and affect most and in a more severe way those groups of vulnerable people (IPCC, 2018). Due to its impacts on the urban energy balance, especially provided by shading and evapotranspiration mechanisms, the presence of vegetation within the urban fabric is essential to promote climate adaptation. Depending on the evapotranspiration processes and on the local climate conditions, green coverage and water features can decrease the temperature peaks during the day. Thus, this process is related to the associated loss of water, which occurs both during the evaporation process from the soil surface, and also by plant metabolism provided by stomatal and cuticular transpiration of the plants. In a nutshell, the evapotranspiration “steals” heat from the environment and depends on soil moisture conditions as well as sunlight, since the process is related to the opening of stomata in leaves (Oke, 1978). Some of the effects provided by the vegetation are: (1) reduction of longwave exchange between buildings surfaces; (2) reduction of dry bulb temperature through evaporation processes; (3) cooling effects due to the increase of water in the air through transpiration (Ng, 2012). Urban green spaces, therefore, are essential for reducing the urban heating and improving comfort conditions for their occupants. Figure 1 (left) : People under tree shading in Beriin. Figure 2 (right): Liberdade Neighborhood, São Paulo.
Figure 3: São Paulo city Skyline.
Plant’s health and extreme temperatures Beyond aspects related to climate change and extreme temperatures impacts on human beings, their effects on plants’ health also should be verified. Urban trees must deal with a series of additional stresses not present in the forests (Brune, 2016). The urban environment conditions are extreme, tends to be hotter, drier and has less space available for vegetation development and, in general, can cause the loss of vitality and the increase of mortality of these arboreal individuals (Gillner et al., 2014). Besides this hostile environment to their development, urban trees suffer from thermal stress and the urban moisture regime often approaches drought conditions (Roloff et al., 2019). However, the opposite also occurs in terms of urban floods and heavy rains induced by the cities itself (Shepherd, 2006). Leaf temperature is connected with vegetative functioning at all spatial scales, from individual plants to forest ecosystems. At the individual level, leaf temperature regulates plant ecophysiology through both direct controls on photosynthetic metabolism (Farquhar et al., 1980; Bernacchi et al., 2013) When temperatures are high, the evapotranspiration process can be interrupted by leaves, affecting the energy balance and increasing their temperature. For most tropical or subtropical trees, when the leaf temperature is close to 47ºC and higher than 50ºC, its structure can present initial and permanent damage, respectively. More recently, some assessments of the urban plants’ health under extreme heat were carried out (Eppel et al., 2012; Gillner et al., 2013, 2016; Moore, 2013; Savi et al., 2015). They showed that the most common urban trees present in temperate zones - such as oaks, tília, áceres and platanos - are under both hydrical and thermal stresses already and the effects of climate change can cause situations even more severe. Moreover, these species might not be able to deal with even more extreme climate conditions (Eppel et al., 2012; Savi et al., 2015).
Figure 4: Theoretical pathways connecting leaf traits and associated process variables within the leaf energy balance equation that infers leaf-to-air temperature difference (ΔT). Source: Guo et al, 2022.
Figure 5: Differnt enviroment conditions between urban trees and natural enviroments ones. Source: Brune, 2016.
Why São Paulo? The city of São Paulo has approximately 1500 km², shelters almost 12 million people and it is one of the biggest cities in Latin America. Beside this, the city of São Paulo presents an unequal distribution of green coverage, since some large and densely populated urban areas have less vegetation than some smaller less populated areas. The relation between the lack of green and urban heating is clear when land surface temperature and the presence of vegetation are compared (Ferreira; Duarte, 2019) (Figure 1). In general, vegetated areas presented lower temperatures than those densely built areas. Moreover, the city presents a complex morphology and patterns of built density, presenting a high variation on its landscape (Figure 6). The most recurrent LCZ types present in the city of São Paulo were verified (Figure 8), which supported the assessment of extreme temperatures impacts on plants’ health in different urban morphologies and contexts.
Figure 6: Mean annual diurnal LST and mean annual NDVI for the Metropolitan Region of São Paulo in 2016. Source: Ferreira and Duarte, 2019
Figure 7: São Paulo, differnt skylines and regions view.
Figure 8: LCZ percentage distribuction in São Paulo. Source: Yoshida, 2022.
São Paulo climate The city of São Paulo is located in Southeastern Brazil (23°32S, 46°37W), is 60 km far from the sea, its altitude varies from 720m to 850m and the climate is classified as cfa, according to Koppen. The city presents warm and wet summers, with the temperatures varying between 22ºC and 30ºC, and mild winters, with the temperatures varying from 10ºC to 22ºC. The average precipitation is around 1400mm, unequally distributed throughout the year. December, January, February and March are the rainiest months, while June, July and August are the drier ones (thermal inversion occurrences are common during this period). Solar radiation can exceed 1000w/m² under clear sky conditions during summer periods, when storms are frequent at the end of the afternoon.
Main Goal This work aims to assess the effects of the built environment on plant’s health under three conditions: a) the current climate, b) the future climate (RCP 8.5, December 2079-2099) and c) the hottest day under RCP 8.5 projection (23/11/2099) in different urban morphology patterns found in Sao Paulo, Brazil. Methodology - Simulations of leaf temperature, vapor flux and stomatal resistance of the most common urban tree in the city, with a LAD of 0,67/m²/m³, were carried out on ENVI-met V5.1.0 and developed for Local Climate Zones 1, 3, 6 and 8.
Figure 9: Monthly average temperature and precipitation of São Paulo city. Source: climate-data.org.
METHODOLOGY This work aims to analyze the impact of urban morphology on plant health within the context of the city of São Paulo, using the ENVI-met computational model. To model this context, information on the urban morphology of the city of São Paulo was collected through Local Climate Zones (LCZ); climatic data from Shinzato et al (2019) were gathered for simulating current climate conditions; climate projection data from the Projeta CPTEC/INPE platform* were collected for simulating future climate scenarios; vegetation data from the Technical Manual for Urban Tree Planting in the City of São Paulo, provided by researcher Dr. Paula Shinzato, and Leaf Area Index (LAI) measurements were conducted in the field using non-destructive methods with hemispherical photos; building material data from Gusson (2020) were also collected. With these data, it was possible to simulate three climate scenarios in ENVI-met (current climate, the December monthly average for the period of 2079 to 2099, and the hottest day found in the database, which is on November 23, 2099) within four different Local Climate Zones corresponding to the three main typologies of the city of São Paulo (LCZ 3, LCZ 6, and LCZ 8), and LCZ-1 was added to the simulations to analyze the impact of taller urban geometry.
Figure 10: Simplified methodology chart
Local Climate Zones
This research utilized LCZ data mapped by Ferreira (2019) for the Metropolitan Region of São Paulo (RMSP) using LANDSAT8 satellite imagery, with training areas sourced from Google Earth, and the Local Climate Zones Classification classifier. This methodology is based on Bechtel et al (2015) and was originally proposed by the World Urban Database and Access Portal Tool (WUDAPT) at the time. The original data from Ferreira (2019) were processed for this study using the Quantum GIS (QGIS) geoprocessing software, allowing us to visualize the distribution, identify the main LCZs within the city of São Paulo, and quantify their sizes within the municipality. As a result of this processing, the predominance of LCZ 3 (40%), LCZ 6 (14.5%), and LCZ 8 (16.1%) within the built typologies in the urban fabric of the city of São Paulo was identified. Together, these LCZs make up approximately 70% of the built areas in the city of São Paulo. LCZ1 accounts for only 3.4% of the city’s built area. With the exception of LCZ6, LCZ 1, LCZ 3, and LCZ 8 are LCZ typologies that have very little vegetation within their blocks. Therefore, street tree planting was added to these models. This work, therefore, deals with the analysis of the impact of urban morphology on plant health. The block shape, building geometry, soil, surface, and material parameterizations were carried out following Kropp (2018) and Kropp et al (2018). Together with researchers from LABAUT, they adapted the LCZ standards of Stewart and Oke (2012) to be more in line with those found in the city of São Paulo. All these LCZ blocks have a size of 100m x 100m. 100
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Climate Data (Forcings) Current Climate Full forcing climate data was used for simulations of the current climate. These data are from Shinzato et al, 2019, who collected on-site data using Campbell weather stations in the Parque Trianon (Parque Tenente Siqueira Salles) region during various periods from 2016 to 2018. From the Shinzato et al, 2019 data, the hotte st day data (April 3, 2016) was selected.
Future Projections December (2079-2099) The period of 2079-2099 represents a climate period of high temperatures, according to Projeta/INPE* data. This work aimed to analyze the climatic conditions during this period and, therefore, used the average air temperature and relative humidity values for the month of December for assessing how vegetation will respond within the context of higher average temperatures. This period has an average temperature of 31°C, which is 7°C above the current average in the city of São Paulo, and an average relative air humidity of 54%. Worst-Case Scenario Within the PROJETA/INPE data, it was identified that November 23, 2099, is the hottest day within the period from 2006 to 2099. This date has average temperatures of 39°C, approximately 15°C hotter than the current average in the city of São Paulo, and an average relative air humidity of 63%. To adequate the climate data from Projeta/Inpe to Envi-met standarts, a simplified interpolation is need. To do so, it was utilyzed IAG/USP** mean hourly curve of temperature and air umidity of São Paulo for each month of simulation. A new hourly curve is forced following a new mean values of air temperature and humidity. This new data can now be introduced on simulations by simple forcing. Figure 13 and Figure 14 describes the results of interpolation.
Vegetation Modeling The vegetation type used in the simulations was street trees, and the tree type was modeled using Albero, based on the Sibipiruna (Caesalpinia pluviosa), one of the main tree species used for urban tree planting in the city of São Paulo. It is an average-sized tree with a height of 15 meters and a diameter of 9 meters. The values of leaf area density (LAD) cells were defined as 1m2/m3.
Figure 12: Sibipiruna tree and Albero modelling. Source: Yoshida (2022)
Simulation Format To avoid edge effects, the LCZ simulations were in the form of 3x3 blocks, and only the values of the central block were analyzed
Figure 13: LCZ1, LCZ3, LCZ6 and LCZ8 .
*Note: Projeta/INPE is a future projection database from National Institute for Space Research **Institute of Astronomy, Geophysics and Atmospheric Sciences of University of São Paulo.
Figure 14: Hourly values of air temperature and air humidity from IAG/USP and forced values for december 2079-2099 simulations
Figure 15: Hourly values of air temperature and air humidity from IAG/USP and forced values for december 23.11.2099 simulations
Input configuration Current Climate
Table 1: Current Climate Imput
Future Climate Projections Worst Case Scenario
Table 2: Future Climate Imput - Worst Case Scenario
December 2079-2099 - Monthly Average
15.12.2085
Table 3: Future Climate Imput - Monthly Average
Results and Conclusions
LCZ1 - COMPACT HIGH RISE Compact high-rise buildings Predominance of Impervious surfaces (Concrete and asphalt) Few or inexistence of greening Materials: Walls/Roof: Concrete (Albedo: 0,4) Sidewalks: Concrete (Albedo: 0,4) Roads: Asphalt (Albedo: 0,1) Implemented vegetation: Tree: Sibipiruna (Caesalpinia pluviosa) (LAD:0,67m²/ m³)
Figure 16: Aerial view of São Paulo LCZ1 Av. Paulista Venue region. Source: Google Maps.
Current climate conditions
Open stomata daytime (Low stomata resistance) Leaves are not under heat stress Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 December (2079-2099) monthly average)
Open stomata daytime (Low stomata resistance) Leaves are not under heat stress. Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 23.11.2099 (Worst Case Scenario)
Open stomata daytime (Low stomata resistance) Leaves are not under heat stress Vegetation is potentialy capable to reduce air temperature. Leaves under normal temperature conditions. Tleaf<Tair
High-rise urban geometry provides more shading for vegetation, resulting in smaller leaf temperatures. The predominance of impermeable surfaces and high heat concentration materials results in higher leaf temperatures values.
LCZ3 - COMPACT LOW-RISE Compact low-rise buildings Predominance of Impervious surfaces (Concrete and asphalt) Few or inexistence of greening Materials: Walls/Roof: Concrete (Albedo: 0,4) Sidewalks: Concrete (Albedo: 0,4) Roads: Asphalt (Albedo: 0,1) Implemented vegetation: Tree: Sibipiruna (Caesalpinia pluviosa) (LAD:0,67m²/ m³)
Figure 17: Aerial view of São Paulo LCZ3. Pinheiros neighborhood region. Source: Google Maps.
Current climate conditions
Open stomata daytime (Low stomata resistance) Leaves are not under heat stress. Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 December (2079-2099) monthly average)
Open stomata daytime (Low stomata resistance). Leaves are not under heat stress. Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 23.11.2099 (Worst Case Scenario)
Closed stomata daytime (High stomata resistance) Leaves are under heat stress Vegetation has its potential to reduce air temperature reduced. Temperatures near to critical values (Heat damage). Tleaf>Tair
Low height urban geometry provides little shading for vegetation, resulting in higher leaf temperatures.
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The predominance of impermeable surfaces and high heat concentration materials results in higher leaf temperatures values.
LCZ6 - OPEN LOW-RISE Open low-rise buildings Predominance of porous surface (Grass and soil) Existence of greening (Trees, grass, shrubs) Materials: Walls/Roof: Concrete (Albedo: 0,4) Sidewalks: Concrete (Albedo: 0,4) Roads: Asphalt (Albedo: 0,1) Grass: Soil Implemented vegetation: Tree: Sibipiruna (Caesalpinia pluviosa) (LAD:0,67m²/m³)
Figure 18: Aerial view of São Paulo LCZ6. Jd Europa neighborhood. Source: Google Maps.
Current climate conditions
Open stomata daytime (Low stomata resistance) Leaves are not under heat stress. Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 December (2079-2099) monthly average)
Open stomata daytime (Low stomata resistance) Leaves are not under heat stress Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 23.11.2099 (Worst Case Scenario)
Closed stomata daytime (High stomata resistance) Leaves are under heat stress Vegetation has its potential to reduce air temperature reduced. Temperatures near to critical values (Heat damage). Tleaf>Tair Note: In this case there is some stomata resistance reduction daytime indicating some stomata opening, but the values still high.
Low height urban geometry provides low shading for vegetation, resulting in higher leaf temperatures.
The predominance of permeable surfaces and low heat concentration results in lower leaf temperatures values.
LCZ8 - LARGE LOW-RISE Compact large low-rise buildings Predominance of Impervious surfaces (Concrete and asphalt) Few or inexistence of greening. Materials: Walls/Roof: aConcrete (Albedo: 0,4) Sidewalks: Concrete (Albedo: 0,4) Roads: Asphalt (Albedo: 0,1) Implemented vegetation: Tree: Sibipiruna (Caesalpinia pluviosa) (LAD:0,67m²/m³) Figure 19 Aerial view of São Paulo LCZ8. Industrial warehouses in east region of São Paulo. Source: Google Maps.
Current climate conditions
Open stomata daytime (Low stomata resistance) Leaves are not under heat stress Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 December (2079-2099) monthly average)
Open stomata daytime (Low stomata resistance). Leaves are not under heat stress. Vegetation is potentialy capable to reduce air temperature. Tleaf<Tair
RCP 8.5 23.11.2099 (Worst Case Scenario)
Closed stomata daytime (High stomata resistance) Leaves are under heat stress Vegetation has its potential to reduce air temperature reduced. Temperatures near to critical values (Heat damage). Tleaf>Tair
Low height urban geometry provides low shading for vegetation, resulting in higher leaf temperatures.
The predominance of impermeable surfaces and high heat concentration materials results in higher leaf temperatures values.
Current climate conditions Leaf Temperature x Air Temperature
Open of stomata
Figure 20: Leaf and Air temperature from simulations in current climate condition.
No heat stress on leaves in all simulations: Leaf temperature < Air temperature daytime
Stomata Resistance
Opening of stomata start point.
Close of stomata.
Figure 21: Stomata resistance values from simulations in current climate condition.
High values of stomata resistance indicate the closure of stomata. During the daytime, these values decrease, signifying the opening of stomata and the exchange of gases between the leaf and the environment.
Vapour flux on leaves
Figure 22: Vapour flux on leaves - Current Climate.
Vapor flux illustrates the process of evapotranspiration on the leaf, which plays a role in regulating leaf temperature. An increase in vapor flux correlates with a reduction in stomatal resistance, and elevated values of this parameter lead to a decline in vapor flux on leaves. In this scenario, the graph curves from each simulation depict the daily average evapotranspiration.
RCP 8.5 December (2079-2099) Monthly average Leaf Temperature x Air Temperature
Open of stomata
Figure 23: Leaf and Air temperature from december (2079-2099) monthly average climate condition.
No heat stress on leaves in all simulations: Leaf temperature < Air temperature daytime
Stomata Resistance
Opening of stomata start point.
Close of stomata.
Figure 24: Stomata resistance values from december (2079-2099) monthly average climate condition.
High values of stomatal resistance indicate stomatal closure. During daytime, these values decrease, signifying stomatal opening and the exchange of gases between the leaf and the environment.
Vapour flux on leaves
Figure 25: Vapour flux on leaves - December (2079-2099)
Even with higher temperatures, there is almost no effect in the evapotranspiration on leaves. Evapotranspiration regulates the leaf temperature.
RCP 8.5 23.11.2099 (Worst Case Scenario) Leaf Temperature x Air Temperature
Leaf temperature reduction only on LCZ1.
Figure 26: Leaf and Air temperature from simulations of 23.11.2099 (worst case scenario) climate condition.
No heat stress on leaves in all simulations: Leaf temperature < Air temperature daytime
Stomata Resistance
High stomata resistance
Opening of stomata start point.
Figure 27: Stomata resistance values from from simulations of 23.11.2099 (worst case scenario) climate condition.
Vapour flux on leaves
Figure 28: Vapour flux on leaves - Worst Case Scenario
The evapotranspiration curve in this scenario, with high temperatures, shows that the vapor flux curve is very different from the previous scenarios. For LCZ 3, LCZ 6, and LCZ 8, there is a decrease in vapor flux from 13 hours (01 PM), indicating an increase in stomatal resistance or the closing of stomata. Evapotranspiration affects the leaf energy balance and may be the cause of high leaf temperatures
CONCLUSIONS This work assessed some parameters related to plants’ health under urban heating for the most recurrent urban morphologies in the city of São Paulo (LCZs 1, 3, 6 and 8) in current and future climate conditions. Results showed similar tendencies. For the current, maximum leaf temperature was up to 29ºC, while for the future these values were up to 33 ºC. For both, the lowest mean values were registered in LCZ-1 and were always lower than the air temperature, a direct consequence of urban morphology and evapotranspiration, expressed by the decrease in stomatal resistance and an increase in vapour flux of the leaves, showing that vegetation is not under heat stress. The stomatal resistance was kept low during the day for both conditions, meaning higher conductance between the leaves and environment, confirming the presence of evapotranspiration process. Vapour fluxes were slightly higher under future climate conditions. On the hottest day, the mean leaf temperature was higher than the air temperature, indicating that the vegetation is no longer able to evapotranspirate, except in LCZ-1. The values registered in LCZ-3 and LCZ-6 were higher than 45ºC, close to 50ºC in LCZ-8 and up to 41ºC in LCZ 1. In LCZ-3, LCZ-6 and LCZ-8, vegetation is under heat stress, which can cause irreversible damages to its leaf structure and health. In LCZ-1, the leaves are not under heat stress. The difference among LCZ tipologies highlights the influence of both permeable surfaces and urban morphology, in LCZ-6 and LCZ-1, respectively, on plant’s health, since these features are related to lower values of mean radiant and air temperatures registered. Due to shading, there is a difference up to 10ºC between leaves temperature in LCZ-1 and LCZ-8. Despite the tendency of losing their potential to reduce air temperature during a period of extreme heat, trees are still able to mitigate surface and mean radiant temperatures. Part of this work is from a master’s research and further improvements will be carried out in the future. The next step will be realize new simulations using ENVI-met’s new resources, such as IVS (e Indexed View Sphere) , ACRT (Advanced Canopy Radiation Transfer Module), which should provide new details on how the environment affects vegetation, its vitality and performance. Finally, ENVI-met is an accurate instrument for simulating the microclimate and has great potential in analyzing the effect of the built environment on urban vegetation.
Exposed sun trees have higher leaf temperatures.
Shaded trees presents lower leaf temperature
High rise = More shading
Low rise = Less shading Figure 29: Simplified urban canyon dinamics and urban vegetation.
ACKNOWLEDGEMENTS Thanks to the São Paulo Research Foundation (FAPESP) grants #2023/03279-8, #2022/08401-3, #2021/11762-5, #2021/04751-7 and #2020/01610-0. Special thanks to our advisor PhD Denise Helena Silva Duarte, PhD Paula Shinzato for the support and LabAUT team (Laboratory of Environment Energy Studies).
REFERENCES 1. Bernacchi, C.J., Bagley, J.E., Serbin, S.P., UM, RUIZ-VERA, Rosenthal, D.M., Vanloocke, A. (2013). Modeling C3 photosynthesis from the chloroplast to the ecosystem. Plant Cell Environ, 36, 1641–1657. 2. Bruse, Michael. (2004). ENVI-Met 3.0: Updated Model Overview. (March): 1–12. 3. Bruse, Michael, and Heribert Fleer. (1998). Simulating Surface-Plant-Air Interactions inside Urban Environments with a Three-Dimensional Numerical Model. Environmental Modelling and Software, 13(3–4), 373–84. 4. Brune, Miriam. (2016). Urban Trees under Climate Change. Climate Service Center Germany, 123. 5. Ferreira, Luciana & Duarte, Denise. (2019). Exploring the relationship between urban form, land surface temperature and vegetation indices in a subtropical megacity. Urban Climate, 27, 105-123. https://doi.org/10.1016/j.uclim.2018.11.002. 6. Farquhar, G.D., von Caemmerer, Sv, Berry, J.A. (1980). A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, 149, 78–90. 7. Gusson, C. S., & Simon, H. (2020). Impact of Built Density and Surface Materials on Urban Microclimate for Sao Paulo, Brazil: Simulation of Different Scenarios Using ENVI-met Full Forcing Tool. In Planning Post Carbon Cities: 35th PLEA Conference on Passive and Low Energy Architecture, A Coruña, 1st-3rd September 2020: Proceedings, Vol. 1, 2020 (Technical Articles), ISBN 978-84-9749-794-7, Págs. 818-823. 8. Guo, Z., Yan, Z., Majcher, B., Lee, C., Zhao, Y., Song, G., Wang, B., Wang, X., Deng, Y., Michaletz, S., Ryu, Y., Ashton, L., Lam, H-M., Wong, M., Liu, L., & Wu, J. (2022). Dynamic biotic controls of leaf thermoregulation across the diel timescale. Agricultural and Forest Meteorology, 315, 108827. https://doi.org/10.1016/j.agrformet.2022.108827. 9. IAG/USP-USP. (2008). BOLETIM CLIMATOLÓGICO ANUAL DA ESTAÇÃO METEOROLÓGICA DO IAG/USP-USP, 12, 59. 10. IPCC. (2022). Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press. In Press. 11. IPCC. (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press. In Press. 12. Krasny, Marianne E., and Keith G. Tidball. (2009). Applying a Resilience Systems Framework to Urban Environmental Education. Environmental Education Research, 15(4), 465–82. 13. Kropp, Tim et al. (2018). Enhancement of the WuDapT Portal Tool WUDAPT2Envi-MET: Introducing Site-Specific Local Climate Zones to WUDAPt2Envi-MET. PLEA 2018 - Smart and Healthy within the Two-Degree Limit: Proceedings of the 34th International Conference on Passive and Low Energy Architecture, 1(December), 256–61. 14. Oke, Timothy, Gerald Mills, Christen A., and James Voogt. (2017). Urban Climates. New York: Cambridge University Press. 15. Santamouris, M. et al. (2001). On the Impact of Urban Climate on the Energy Consumption of Building. Solar Energy, 70(3), 201–16. 16. Santamouris, M. (2017). Passive and Active Cooling for the Outdoor Built Environment – Analysis and Assessment of the Cooling Potential of Mitigation Technologies Using Performance Data from 220 Large Scale Projects. Solar Energy, 154, 14–33. http://dx.doi.org/10.1016/j.solener.2016.12.006. 17. Shinzato, Paula et al. (2019). Calibration process and parametrization of tropical plants using ENVI-met V4 – Sao Paulo case study, Architectural Science Review, 62(2), 112-125. DOI: 10.1080/00038628.2018.1563522. 18. Simon, Helge. (2016). Modeling Urban Microclimate. Johannes Gutenberg Universitat Mainz. Ph.D. Thesis. 19. Slot, Martijn & Krause, G. & Krause, Barbara & Hernández, Georgia & Winter, Klaus. (2019). Photosynthetic heat tolerance of shade and sun leaves of three tropical tree species. Photosynthesis Research, 141. https://doi.org/10.1007/s11120-018-0563-3. 20. Stewart, I.D. & Oke, T.. (2012). Local Climate Zones for Urban Temperature Studies. Bulletin of the American Meteorological Society, 93, 1879-1900. https:// doi.org/10.1175/BAMS-D-11-00019.1. 21. Yoshida, D. F. O., Shinzato, P., & Duarte, D. (2022). The microclimate effects of urban green infrastructure under RCP 8.5 projection and plant vitality. Will plants be enough? (PLEA 2022).