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Sustainability 2016, 8(9), 896; doi:10.3390/su8090896

A Parametric Optimization Approach to Mitigating the Urban Heat Island Effect: A Case Study in Ancona, Italy

School of Architecture and Design “E. Vittoria”, University of Camerino, Camerino 62032, Italy
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Academic Editor: Tan Yigitcanlar
Received: 22 June 2016 / Revised: 13 August 2016 / Accepted: 23 August 2016 / Published: 6 September 2016
(This article belongs to the Section Sustainable Urban and Rural Development)
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Abstract

The aim of this paper is to identify a parameterization method that considers existing connections and relationships between traditional indicators of environmental sustainability as a step in combating climate change via urban strategies. A typical Mediterranean city (Ancona, Italy) is investigated with a multi-objective optimization platform called modeFrontier, which uses Pareto optimality. This concept formalizes the trade-off between a given set of mutually contradicting objectives, such as high thermal comfort and low energy consumption, to identify a set of Pareto solutions. A solution is Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the others. The optimization process employs given constraints (for example, meteorological scenarios with high temperature and low winds or morphological building parameters), custom procedural algorithms (recursive algorithms to generate the set of all non-dominated objective parameters), and genetic algorithms (inspired by the natural selection process) to examine a wide urban space and identify interesting relationships among relevant variables for typical summer scenarios. Multi-objective optimizers involve many evaluations of two objectives (i.e., energy consumption and thermal comfort in this study) while considering many analytical constraints. This approach entails a considerably more exhaustive search of environmental variables that can help the urban planning process to mitigate the urban heat island (UHI) effect. Three quantitative metrics related to urban morphology and local climate conditions, as well as a thermal comfort indicator (the predicted mean vote), are defined and applied to Ancona to examine the potential for new sustainability in urban design. The results show that two parameters examined—compacity and a building-scale energy indicator—can offer insight when designing comfortable cities, while a citywide energy indicator shows that it is more difficult to find optimal solutions when dealing with the city as a whole. The research serves as a proof-of-concept and the possibility of identifying some local strategies in order to combat the UHI is verified. View Full-Text
Keywords: urban sustainability; urban planning; multi-objective optimization; Pareto optimality; predicted mean vote urban sustainability; urban planning; multi-objective optimization; Pareto optimality; predicted mean vote
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MDPI and ACS Style

Cocci Grifoni, R.; D’Onofrio, R.; Sargolini, M.; Pierantozzi, M. A Parametric Optimization Approach to Mitigating the Urban Heat Island Effect: A Case Study in Ancona, Italy. Sustainability 2016, 8, 896.

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