Bassolino, E. (2016). Climate-adaptive design strategies for the built environment: metodologia per
il controllo tecnico-decisionale con strumenti IT del progetto dell’esistente nel contesto napoletano.
(Doctoral dissertation). University of Naples “Federico II”, Naples, Italy.
Gill, L., Hathway, E. A., Lange, E., Morgan, E., & Romano, D. (2013). Coupling real-time 3D land- scape models with microclimate simulations. International Journal of E-Planning Research, 2(1), 1–19. doi:10.4018/ijepr.2013010101
Huttner, S., Bruse, M., & Dostal, P. (2009), Using ENVI-met to simulate the impact of global warming on the microclimate in Central European cities. In Ber. Meteor. Inst. Univ. Freiburg, n. 18, Friburgo.
Thermal-Perception-Driven Adaptive Design for Wellbeing in Outdoor Public Spaces
Peng, C., & Elwan, A. (2012). Bridging Outdoor and Indoor Environmental Simulation for Assessing and Aiding Sustainable Urban Neighbourhood Design. Archnet-IJAR: International Journal of Archi-
tectural Research, 6(3).
Peng, C., & Elwan, A. (2014). An outdoor-indoor coupled simulation framework for climate Change– conscious urban neighborhood design. Simulation, 90(8), 874–891. doi:10.1177/0037549714526293 Pignatti, G. (2011). La vegetazione forestale di fronte ad alcuni scenari di cambiamento climatico in Italia. INFOR, 8, 1–12.
Ratti, C., & Claudel, M. (2014). Architettura open source. Verso una progettazione aperta. Torino: Einaudi. Ratti, C., & Mattei, M. G. (2013). Smart city, smart citizen. Meet the media guru. Milano: EGEA. Tedeschi A. (2014). Algorithms-aided design: parametric strategies using Grasshopper. Potenza: La Penseur.
Tersigni, E. (2012). Strumenti informatici di supporto alla progettazione per gli interventi di retrofit. In M. Bellomo & P. Ascione (Eds.), In Retrofit per la resistenza: Tecnologie per la riqualificazione del
patrimonio edilizio in Campania (pp. 153–160). Napoli: Clean Edizioni.
Trimmel, H. (2008). Using Microscale Climatological Simulation in Landscape Planning - an ENVI-met
3 User’s Perspective. Vienna: Universität für Bodenkultur Wien.
ENDNOTES
1 Heat accumulation that determines differences in temperature between areas of the city with dif-
ferent characteristics (Matzarakis, 2015).
2 The thirty years between 2040-2069 can be still considered as an intermediate stage to perform
predictive analysis of microclimatic comfort, referring to two climate projection representative scenarios RPC 8.5 and RPC 2.6, proposed by the IPCC.
3 For the city of Naples, July of 2015 was an extremely hot month, with an anomaly of about + 3.6
°C above the average for the reference period (1971-2000), making it the hottest July since the 1800, exceeding of about a degree that of July 2003 with + 2.6 °C compared with the same refer- ence period (source: National Oceanic and Atmospheric Administration of the United States).
4 The Roughness Length, is the length in meters of the surface roughness. Any urban context is
associated with a value of 0.1 for the city center, 0.01 for the periphery, 0,001 for rural areas.
5 On PMV values acts environmental variables such as air temperature (Ta), the mean radiant
temperatures (MRT), the vapor pressure and wind speed, and subjective variables such as insula- tion due to the clothing (clo factor), the mechanical energy produced by the body human (M), the mechanical work factor (η).
6 The exchange of energy within the human body is a combination of the metabolic rate and the
exchange of energy due to mechanical work. The PMV model using constant average values for the various activities, depending on personal characteristics (age, weight, etc.). These values can vary over a wide range.
Thermal-Perception-Driven Adaptive Design for Wellbeing in Outdoor Public Spaces
7 The heat balance of the human body depends on the clothes wears. The thermal resistance of
clothing is measured in clo, where 1 clo = 0.155 kW2/W (source: www.ENVI-met.com/documents/
onlinehelpv3/hs150.htm).
8 Predicted climate files were generated with CCWorldWeatherGen, a tool developed by the Uni-
versity of Southampton, based on IPCC Third Assessment Report model summary data of the HadCM3 A2 experiment ensemble.
9 Grasshopper is a visual programming language developed by David Rutten at Robert McNeel &
Associates. It runs within the Rhinoceros 3D CAD application. The definitions of Grasshopper are characterized by the appearance of a flow diagram. This plug-in allows to adopt a parametric and algorithmic approach, customizing the actions you can perform on the flow of information and/or 3D objects, and to make visible these processing in ambient RH.
10 Ladybug and Honeybee are two free and open source environmental plugins for Grasshopper to
help designers create an environmentally-conscious architectural design (rif. food4rhino.com).
11 Reduce Building Impact (Riduzione Impatto Edilizio, or RIE), it is an index of environmental
quality introduced by the City of Bolzano, which serves to certify the quality of the building in- tervention compared to the permeability of the soil and green.
12 The BAF expresses the ratio of the ecologically effective surface area respect to the total land area.
In this calculation, surfaces are weighted according to their “ecological significance.”
13 The assessment of the project proposal to resilience, through the generation module of climate files
CCWorldWeatherGen (developed by the University of Southampton) we simulated, theoretically, climatic conditions reporting relevant information of year 2050 in ENVI-met for the execution of microclimatic simulations.
Thermal-Perception-Driven Adaptive Design for Wellbeing in Outdoor Public Spaces
APPENDIX 1
Table 4. Physical and thermal properties of the materials detected in the study area: albedo, emissivity, roughness and thermal conductivity
Thermal-Perception-Driven Adaptive Design for Wellbeing in Outdoor Public Spaces
Table 5. Physical and thermal properties of the materials of meta-design alternatives: albedo, emissivity, roughness and thermal conductivity
Thermal-Perception-Driven Adaptive Design for Wellbeing in Outdoor Public Spaces
APPENDIX 2
Figure 12. Area of the 800’s of Naples: results of microclimatic analysies and comparison of values of SVF, PMV and air temperatures.
Thermal-Perception-Driven Adaptive Design for Wellbeing in Outdoor Public Spaces
Figure 13. Area of the contemporary city of Naples: results of microclimatic analysies and comparison of values of SVF, PMV and air temperatures.
Thermal-Perception-Driven Adaptive Design for Wellbeing in Outdoor Public Spaces
Figure 14. Interactions between different Information Technology Tools applied in the research