Simulating and Comparing Different Vertical Greenery Systems Grouped into Categories Using EnergyPlus
Abstract
:1. Introduction
2. Classification
3. Literature Review
4. Methodology
4.1. Study of Plant Physiology
4.1.1. Radiation Balance
4.1.2. Sensible Heat Flux
4.1.3. Latent Heat Flux
4.1.4. Physical Parameters of Leaves
4.2. Integration in the EnergyPlus
4.2.1. The EMS Settings—The Solar Absorptance
4.2.2. The EMS Settings—The Sensible Heat Flux
4.2.3. The Advanced Settings—The Latent Heat Flux
4.2.4. The Advanced Settings—The Ventilated Façade
4.2.5. The Layers’ Properties
4.3. Mathematical and Geometrical Models
5. Results and Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Alexandri, E. Tackling the Heat Island Effect with Green Roofs and Green Walls: A Microclimatic Approach. In Proceedings of the WSA, 2nd Research Student Conference, Cardiff, Wales, May 2005. [Google Scholar]
- Alexandri, E.; Jones, P. Temperature decreases in an urban canyon due to green walls and green roofs in diverse climates. Build. Environ. 2008, 43, 480–493. [Google Scholar] [CrossRef]
- Djedjig, R.; Bozonnet, E.; Belarbi, R. Modeling green wall interactions with street canyons for building energy simulation in urban context. Urban Climate 2016, 16, 75–85. [Google Scholar] [CrossRef]
- Li, J.; Zheng, B.; Shen, W.; Xiang, Y.; Chen, X.; Qi, Z. Cooling and Energy-Saving Performance of Different Green Wall Design: A Simulation Study of a Block. Energies 2019, 12, 2912. [Google Scholar] [CrossRef] [Green Version]
- Rosenlund, H.; Kruuse, A.; Kronvall, J. Urban greenery in Sweden—Implications for microclimate and energy efficiency. In Proceedings of the World Green Roof Congress, London, UK, 3 September 2010. [Google Scholar] [CrossRef]
- Farid, F.; Ahmad, S.; Raub, A.; Shaari, M. Green “Breathing Facades” for Occupants’ Improved Quality of Life. Procedia Soc. Behav. Sci. 2016, 234, 173–184. [Google Scholar] [CrossRef] [Green Version]
- Stav, Y. Transfunctional Living Walls-Designing Living Walls for Environmental and Social Benefits. Ph.D. Thesis, Queensland University of Technology, Brisbane City, Australia, 2016. [Google Scholar]
- Malys, L.; Musy, M.; Inard, C. A hydrothermal model to assess the impact of green walls on urban microclimate and building energy consumption. Build. Environ. 2014, 73, 187–197. [Google Scholar] [CrossRef]
- Dahanayake, K.C.; Chow, C.L. Comparing reduction of building cooling load through green roofs and green walls by EnergyPlus simulations. Build. Simul. 2018, 11, 421–434. [Google Scholar] [CrossRef]
- Musy, M.; Malys, L.; Inard, C. Assessment of Direct and Indirect Impacts of Vegetation on Building Comfort: A Comparative Study of Lawns, Green Walls and Green Roofs. Procedia Environ. Sci. 2017, 38, 603–610. [Google Scholar] [CrossRef]
- Boeri, S. Un Bosco Verticale—Libretto di Istruzioni per il Prototipo di una Città Foresta; Corraini Edizioni: Mantova, Italy, 2015. [Google Scholar]
- Blanc, P. Vertical Gardens, the new Challenges. In Green Cities in the World, 2nd ed.; Briz, J., Köhler, M., de Felipe, I., Eds.; Editorial Agricola Espanola: Madrid, Spain, 2015; pp. 330–355. [Google Scholar]
- Aksamija, A. High-Performance Building Envelopes: Design Methods for Energy-Efficient Facades. In Proceedings of the BEST4 Conference, Kansas City, MO, USA, 13–15 April 2015. [Google Scholar]
- Safikhani, T.; Abdullah, A.; Ossen, D.; Baharvand, M. A review of energy characteristic of vertical greenery systems. Renew. Sust. Energ. Rev. 2014, 40, 450–462. [Google Scholar] [CrossRef]
- Manso, M.; Castro-Gomes, J. Green wall systems: A review of their characteristics. Renew. Sust. Energ. Rev. 2015, 41, 863–871. [Google Scholar] [CrossRef]
- Jim, C.Y. Greenwall classification and critical design-management assessments. Ecol. Eng. 2015, 77, 348–362. [Google Scholar] [CrossRef]
- Pérez, G.; Coma, J.; Martorell, I.; Cabeza, L.F. Vertical Greenery Systems (VGS) for energy saving in buildings: A review. Renew. Sust. Energ. Rev. 2014, 39, 139–165. [Google Scholar] [CrossRef] [Green Version]
- Jaafar, B.; Said, I.; Rasidi, M. Evaluating the Impact of Vertical Greenery System on Cooling Effect on High Rise Buildings and Surroundings: A Review. Rev. Urban. Archit. Stud. 2011, 9, 1–9. [Google Scholar] [CrossRef] [Green Version]
- Wong, N.H.; Tan, A.; Chen, Y.; Sekar, K.; Tan, P.; Chan, D.; Chiang, K.; Wong, N. Thermal evaluation of vertical greenery systems for building walls. Build. Environ. 2010, 45, 663–672. [Google Scholar] [CrossRef]
- Bit, E. Il Nuovo Verde Verticale: Tecnologie, Progetti, Linee Guida; Wolters Kluwer Italia S.r.l.: Assago (Milan), Italy, 2012. [Google Scholar]
- Balogun, A.; Morakinyo, T.; Adegun, O. Effect of tree-shading on energy demand of two similar buildings. Energy Build. 2014, 81, 305–315. [Google Scholar] [CrossRef]
- Giometto, M.; Christen, A.; Egli, P.; Schmid, M.F.; Tooke, R.T.; Coops, N.C.; Parlange, M. Effects of trees on mean wind, turbulence and momentum exchange within and above a real urban environment. Adv. Water Resour. 2017, 106, 154–168. [Google Scholar] [CrossRef]
- Hes, D.; Dawkins, A.; Jensen, C.; Aye, L. A modelling method to assess the effect of tree shading for building performance simulation. In Proceedings of the Building Simulation 2011, 12th Conference of International Building Performance Simulation Association, Sydney, New South Wales, Australia, 14–16 November 2011. [Google Scholar]
- Lin, B.-S.; Lin, Y.-J. Cooling effect of shade trees with different characteristics in a subtropical urban park. HortScience 2010, 45, 83–86. [Google Scholar] [CrossRef] [Green Version]
- Pandit, R.; Laband, D. A hedonic analysis of the impact of tree shade on summertime residential energy consumption. Arboric. Urban For. 2010, 36, 73–80. [Google Scholar]
- Simpson, J.R.; McPherson, E.G. Simulation of tree shade impacts on residential energy use for space conditioning in Sacramento. Atmos. Environ. 1998, 32, 69–74. [Google Scholar] [CrossRef]
- Akbari, H.; Kurn, D.; Bretz, S.; Hanford, J. Peak power and cooling energy savings of shade trees. Energy Build. 1997, 25, 139–148. [Google Scholar] [CrossRef] [Green Version]
- Yoshimi, J.; Altan, H. Thermal simulations on the effects of vegetated walls on indoor building environments. In Proceedings of the Building Simulation 2011, 12th Conference of International Building Performance Simulation Association, Sydney, New South Wales, Australia, 14–16 November 2011. [Google Scholar]
- Coma, J.; Perez, G.; Solé, C.; Castell, A.; Cabeza, L.F. New Green Facades as Passive Systems for Energy Savings on Buildings. Energy Procedia 2014, 57, 1851–1859. [Google Scholar] [CrossRef] [Green Version]
- Kontoleon, K.; Eumorfopoulou, E. The effect of the orientation and proportion of a plant-covered wall layer on the thermal performance of a building zone. Build. Environ. 2010, 45, 1287–1303. [Google Scholar] [CrossRef]
- Flores Larsen, S.; Filippín, C.; Lesino, G. Thermal Simulation of a Double Skin Façade with Plants. Energy Procedia 2014, 57, 1763–1772. [Google Scholar] [CrossRef] [Green Version]
- Stec, W.; Paassen, A.; Maziarz, A. Modelling the double skin façade with plants. Energy Build. 2005, 37, 419–427. [Google Scholar] [CrossRef]
- Chen, Q.; Li, B.; Xioahu, L. An experimental evaluation of the living wall system in hot and humid climate. Energy Build. 2013, 61, 298–307. [Google Scholar] [CrossRef]
- Dahanayake, K.; Chow, C. Studying the Potential of Energy Saving through Vertical Greenery Systems: Using EnergyPlus Simulation Program. Energy Build. 2016, 138. [Google Scholar] [CrossRef]
- Djedjig, R.; El Ganaoui, M.; Belarbi, R.; Bennacer, R. Thermal effects of an innovative green wall on building energy performance. Mech. Ind. 2017, 18. [Google Scholar] [CrossRef]
- Scarpa, M.; Mazzali, U.; Peron, F. Modeling the energy performance of living walls: Validation against field measurements in temperate climate. Energy Build. 2014, 79, 155–163. [Google Scholar] [CrossRef]
- Stanghellini, C.; van Meurs, W.T.M. Environmental control of greenhouse crop transpiration. J. Agric. Eng. Res. 1992, 51, 297–311. [Google Scholar] [CrossRef]
- Allen, R.; Pereira, L.; Smith, M. Crop Evapotranspiration—Guidelines for Computing Crop Water Requirements; FAO: Rome, Italy, 1998. [Google Scholar]
- DOE. EnergyPlus Energy Simulation Software. 2015. Available online: https://energyplus.net/ (accessed on 31 March 2021).
- Sailor, D.J. A green roof model for building energy simulation programs. Energy Build. 2008, 40, 1466–1478. [Google Scholar] [CrossRef]
- Frankenstein, S.; Koenig, G. Fast All-Season Soil Strength (FASST); Cold Regions Research and Engineering Laboratory: Hanover, NH, USA, 2004. [Google Scholar]
- Anderson, R.; Zhang, X.; Skaggs, T. Measurement and Partitioning of Evapotranspiration for Application to Vadose Zone Studies. Vadose Zone J. 2017, 16, 1–9. [Google Scholar] [CrossRef] [Green Version]
- Del Barrio, E.P. Analysis of the green roofs cooling potential in buildings. Energy Build. 1998, 27, 179–193. [Google Scholar] [CrossRef]
- Gutschick, V.P. Leaf Energy Balance: Basics, and Modeling from Leaves to Canopies. In Canopy Photosynthesis: From Basics to Applications; Hikosaka, K., Niinemets, Ü., Anten, N., Eds.; Springer: Dordrecht, The Netherlands, 2016; pp. 23–58. [Google Scholar]
- Jayalakshmy, M.S.; Philip, J. Thermophysical Properties of Plant Leaves and Their Influence on the Environment Temperature. Int. J. Thermophys. 2010, 31, 2295–2304. [Google Scholar] [CrossRef]
- Merzlyak, M.N.; Chivkunova, O.B.; Melø, T.B.; Naqvi, K.R. Does a leaf absorb radiation in the near infrared (780–900 nm) region? A new approach to quantifying optical reflection, absorption and transmission of leaves. Photosynth. Res. 2002, 72, 263–270. [Google Scholar] [CrossRef] [PubMed]
- Oke, T.R. Boundary Layer Climates, 2nd ed.; Routledge Taylor & Francis Group: London, UK, 1987; pp. 1–157. [Google Scholar]
- Šuklje, T.; Medved, S.; Arkar, C. On detailed thermal response modeling of vertical greenery systems as cooling measure for buildings and cities in summer conditions. Energy 2016, 115 Pt 1, 1055–1068. [Google Scholar] [CrossRef]
- Davis, M.M.; Hirmer, S. The Potential for Vertical Gardens as Evaporative Coolers: An Adaptation of the ‘Penman Monteith Equation’. Build. Environ. 2015, 92. [Google Scholar] [CrossRef]
- Monteith, J.L.; Unsworth, M.H. Principles of Environmental Physics: Plants, Animals, and the Atmosphere, 4th ed.; Elsevier: Oxford, UK, 2013. [Google Scholar]
- Monteith, J.L. Principles of Environmental Physics; Edward Arnold Limited: London, UK, 1973. [Google Scholar]
- Defraeye, T.; Blocken, B.; Carmeliet, J. Convective heat transfer coefficients for exterior building surfaces: Existing correlations and CFD modelling. Energy Convers. Manag. 2011, 52, 512–522. [Google Scholar] [CrossRef] [Green Version]
- Asner, G.P.; Scurlock, J.M.O.; Hicke, J.A. Global synthesis of leaf area index observations: Implications for ecological and remote sensing studies. Glob. Ecol. Biogeogr. 2003, 12, 195–205. [Google Scholar] [CrossRef] [Green Version]
- Goswami, S.; Gamon, J.; Vargas Zesati, S.; Tweedie, C. Relationships of NDVI, Biomass, and Leaf Area Index (LAI) for six key plant species in Barrow, Alaska. PeerJ Prepr. 2015. [Google Scholar] [CrossRef]
- Candelari, E. Caratterizzazione Sperimentale della Prestazione Termica e Acustica di un Living Wall. Ph.D. Thesis, Politecnico di Torino, Torino, Italy, 2015. [Google Scholar]
- Gu, L. Airflow network modeling in energyplus. In Proceedings of the 10th International Building Performance Simulation Association, Conference and Exhibition, Beijing, China, 3–6 September 2007. [Google Scholar]
- Peci-López, F.; Jensen, R.; Heiselberg, P.; Ruiz de Adana, M. Experimental analysis and model validation of an opaque ventilated facade. Build. Environ. 2012, 56, 265–275. [Google Scholar] [CrossRef]
- Le, S.; Chen, Y.; Bi, Y.; Lu, X. Modeling and Simulation of Ventilated Double-Skin Facade Using EnergyPlus. In Proceedings of the 8th International Symposium on Heating, Ventilation and Air Conditioning, Sydney, New South Wales, Australia, 16–17 July 2014; Lecture Notes in Electrical Engineering. Li, A., Zhu, Y., Li, Y., Eds.; Springer: Berlin/Heidelberg, Germany, 2014; Volume 263, pp. 241–252. [Google Scholar] [CrossRef]
- Abu-Hamdeh, N.H.; Reeder, R.C. Soil thermal conductivity: Effects of density, moisture, salt concentration and organic matter. Soil Sci. Soc. Am. J. 2000, 64, 1285–1290. [Google Scholar] [CrossRef]
- Akpabio, G.T.; Ituen, E.E.; Ikot, A.N. A Comparative Study of the Thermal Properties of Different Soil Samples for Moulding Blocks for a Passively Cooled Building Design. Int. J. Pure Appl. Phys. 2010, 6, 517–521. [Google Scholar]
- Clauser, C.; Huenges, E. Thermal conductivity of rocks and minerals. In Rock Physics & Phase Relations: A Handbook of Physical Constants; Ahrens, T.J., Ed.; American Geophysical Union: Washington, DC, USA, 1995; pp. 105–126. [Google Scholar]
- Fuchs, M. Energy Balance. In Encyclopedia of Soils in the Environment, 1st ed.; Hillel, D., Ed.; Elsevier: Amsterdam, The Netherlands, 2005; pp. 438–441. [Google Scholar]
- Han, S.; Chun, S.; Kim, K.; Lawrence, A.; Tia, M.; Said, Z. Evaluation of Soil Insulation Effect on Thermal Behavior of Drilled Shafts as Mass Concrete. Cogent Eng. 2018, 5. [Google Scholar] [CrossRef]
- Nikoosokhan, S.; Nowamooz, H.; Chazallon, C. Effect of dry density, soil texture and time-spatial variable water content on the soil thermal conductivity. Geomech. Geoeng. 2015, 11, 1–10. [Google Scholar] [CrossRef]
- Pitts, L. Monitoring Soil Moisture for Optimal Crop Growth. 2016. Available online: https://observant.zendesk.com/hc/en-us/articles/208067926-Monitoring-Soil-Moisture-for-Optimal-Crop-Growth (accessed on 31 March 2021).
- EnergyPlus. Weather Data by Region. Available online: https://energyplus.net/weather-region/europe_wmo_region_6/ITA%20%20 (accessed on 31 March 2021).
- Perra, C.; Arenghi, A.; Caffi, M. Verde Verticale: Analisi Termoigrometriche in Regime Dinamico. DICATAM Tech. Rep. 2020, 7, 1–199. [Google Scholar]
- Perez, G.; Rincon, L.; Vila, A.; Gonzalez, J.M.; Cabeza, L.F. Green vertical systems for buildings as passive systems for energy savings. Appl. Energy 2011, 88, 4854–4859. [Google Scholar] [CrossRef]
- Mazzali, U.; Fabio, P.; Romagnon, P.; Pulselli, R.M.; Bastianoni, S. Experimental investigation on the energy performance of Living Walls in a temperate climate. Build. Environ. 2013, 64, 57–66. [Google Scholar] [CrossRef]
- Cameron, R.W.F.; Taylor, J.; Emmett, M. A Hedera green façade –energy performance and saving under different maritime-temperate, winter weather conditions. Build. Environ. 2015, 92, 111–121. [Google Scholar] [CrossRef] [Green Version]
- Haggag, M.; Hassan, A.; Elmasry, S. Experimental study on reduced heat gain through green façades in a high heat load climate. Energy Build. 2014, 82, 668–674. [Google Scholar] [CrossRef]
- Hoelscher, M.-T.; Nehls, T.; Jänicke, B.; Wessolek, G. Quantifying cooling effects of facade greening: Shading, transpiration and insulation. Energy Build. 2015, 114, 283–290. [Google Scholar] [CrossRef]
- Perini, K.; Ottelé, M.; Fraaij, A.L.A.; Haas, E.; Raiteri, R. Vertical greening systems and the effect on air flow and temperature on the building envelope. Build. Environ. 2011, 46, 2287–2294. [Google Scholar] [CrossRef]
Reference | Author/ Year | Considered Terms in Thermal Balance | Model/ Software Used | Category Analized/Method | ||
---|---|---|---|---|---|---|
Shading | Convection | ETP | ||||
Green Barrier Systems (GBS) | ||||||
[32] | Stec et al. (2005) | YES | YES | YES | Simulink | Green Climbing Barrier (GCB) Radiative and convective thermal balances were mathematically represented through the definition of radiation absorption coefficient and convective heat transfer coefficient, respectively. The first one was found to be equal to 0.42, according to laboratory tests taken on the species Hedera helix. The second one was determined using the formula proposed by Stanghellini [37]: Evapotranspiration (EPT) effect was represented through the FAO Penman Monteith formula [38]: |
[23] | Hes et al. (2011) | YES | NOT | NOT | IES-VE | Green Tree Barrier (GTB) Two methods to simulate tree shading were proposed. The first one was modeling simplified objects, compatible with the shape of a tree. The changing density of the foliage was simulated through three models, with 0%, 50% and 100% of shading properties, a bare model, a perforated model and an opaque one, respectively. Instead, with the second method, an adjusted solar absorptance coefficient was introduced directly in the shaded wall properties. The adjustment considers a hypothetical shadowing, as shown in the following formula: Adjusted Solar Absorptance = 0.6 * (1 − SC) Where SC is Shading Coefficient. |
[31] | Larsen et al. (2014) | YES | YES | NOT | EnergyPlus | Green Climbing Barrier (GCB) Two different shading elements were used: Building Shading Object (BS) and Window Shading Device Object (WSD). To consider the wind barrier effect of the model, the convective heat exchange coefficient is calculated as proposed by [32]: The modification of the view factor of the walls and windows is also proposed to take into account the diffused solar radiation reflected from the ground. |
Green Coating Systems (GCS) | ||||||
[28] | Yoshimi and Altan (2011) | YES | YES | NOT | ECOTECT | Green Climbing Coating (GCC) The evapotranspiration effect was greatly simplified, by modeling a layer of water vapor above the leaf layer that represents the water evaporated from the leaves. The thermal model of the species Hedera helix (Common Ivy) species is composed of 5 layers: water vapour, leaves, air gap, softwood (stem) and another air gap; the thermal properties are defined for each one. (ECOTECT Is not available any more as a stand alone tool) |
Green Walls (GW) | ||||||
[8] | Malys et al. (2014) | YES | YES | YES | Self-developed model in SOLENE-Microclimate | Heavy System (HS) The hydrothermal model, validated with field measurements, represents each layer as a node and each node is associated with a thermal or water balance. In addition, a parametric study was conducted: nine variable parameters were used to characterize the substrate and leaf layer. The quality of the combinations of parameters was determined by calculating the root of the mean square error. |
[36] | Scarpa et al. (2014) | YES | YES | YES | Self-developed mathematical model | Mur Vegetal (MV) The Green Wall was divided into 11 thermal nodes; the behavior of each one was described with a thermal balance equation. The thickness of the cavity behind the system was also considered, evaluating its type (ventilated or not). The model shows a good agreement with the field measurement realized. |
[34] | Dahana-yake e Chow (2017) | YES | YES | YES | Self-developed model integrated in EnergyPlus | Light System (LS) The heat balance equations of the model are based on the Green Roof module present in the EnergyPlus [39,40], on the FASST model proposed by Frankenstein and Koenig [41] and on the hydrothermal model validated by Malys et al. [8]. The correlation coefficients are close to unity, showing a good match between the simulation results and those of the experimental case. |
[35] | Djedji et al. (2017) | YES | YES | YES | Self-developed model integrated in TRNSYS | Heavy System (HS) The mathematical model used was developed on the basis of a green roof model, analyzed by the authors in a previous study [42], analyzing solar and infrared radiation, convection and evapotranspiration. The validation of the analytical model of the green wall is based on the comparison of the external surface temperature of the substrate with that of a monitored green roof. |
Properties | Units | Bergenia Crassifolia | Geranium Macrorrhizum |
---|---|---|---|
Single leaf thickness | 0.25 | 0.21 | |
Canopy layer thickness | 5 | 5 | |
Thermal conductivity | 0.34 | 0.35 | |
Density | 656 | 627 | |
Specific heat | 2252 | 2232 | |
Thermal effusivity | 714 | 702 | |
Thermal diffusivity | 0.23 | 0.25 |
Properties | Units | Bergenia Crassifolia | Geranium Macrorrhizum | ||||
---|---|---|---|---|---|---|---|
Sandy loam | Loam | Clay loam | |||||
% Saturation | - | min 10 | max 20 | min 20 | max 30 | min 30 | max 40 |
Density | 1700 | 1800 | 1800 | 1900 | 1900 | 2000 | |
Thermal conductivity | 1.26 | 2.03 | 1.02 | 1.22 | 1.34 | 1.45 | |
Specific heat | 1125 | 1328 | 1080 | 1209 | 1324 | 1465 |
VGS | Maximum Reduction of the External Surface Temperature Compared to the Reference Sample | Maximum Reduction of the Operative Temperature Compared to the Reference Sample | Main Effects Involved |
---|---|---|---|
GTB | −1.5 °C (−4%) | −4 °C (−11%) | Shading |
GCB | −1.5 °C (−4%) | −4 °C (−11%) | Shading |
GCC | −5 °C (−12%) | −6 °C (−17%) | Shading/transpiration |
GMC | −6 °C (−15%) | −7.5 °C (−21%) | Shading/evapotranspiration |
MV | −10 °C (−26%) | −8 °C (−23%) | Evapotranspiration/Ventilated façade |
LS | −13 °C (−32.5%) | −8 °C (−23%) | Evapotranspiration/Ventilated façade |
HS | −13 °C (−32.5%) | −9 °C (−26%) | Evapotranspiration/Ventilated façade |
VGS | Maximum Increase of the External Surface Temperature Compared to the Reference Sample | Maximum Increase of the Operative Temperature Compared to the Reference Sample | Main Effects Involved |
---|---|---|---|
GTB | ±0 °C (±0%) | ±0 °C (±0%) | Wind barrier |
GCB | ±0 °C (±0%) | ±0 °C (±0%) | Wind barrier |
GCC | +1 °C (+13%) | +1 °C (+67%) | Wind barrier |
GMC | +1 °C (+13%) | +1 °C (+67%) | Wind barrier |
MV | +8 °C (+800%) | +4 °C (+200%) | PVC panel in the stratigraphy |
LS | +8 °C (+800%) | +1 °C (+100%) | Soil thermal conductivity |
HS | +8 °C (+800%) | +2 °C (+150%) | Soil thermal conductivity |
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Arenghi, A.; Perra, C.; Caffi, M. Simulating and Comparing Different Vertical Greenery Systems Grouped into Categories Using EnergyPlus. Appl. Sci. 2021, 11, 4802. https://doi.org/10.3390/app11114802
Arenghi A, Perra C, Caffi M. Simulating and Comparing Different Vertical Greenery Systems Grouped into Categories Using EnergyPlus. Applied Sciences. 2021; 11(11):4802. https://doi.org/10.3390/app11114802
Chicago/Turabian StyleArenghi, Alberto, Camilla Perra, and Marco Caffi. 2021. "Simulating and Comparing Different Vertical Greenery Systems Grouped into Categories Using EnergyPlus" Applied Sciences 11, no. 11: 4802. https://doi.org/10.3390/app11114802