Abstract
As the world rapidly develops it becomes increasingly urbanized, and it is thus necessary to focus on achieving sustainability results within cities. Getting this goal requires not only to imagine sustainable cities and implementation strategies, but also to assess progress towards sustainable urban development. The present paper is aimed at evaluating urban sustainability through the analysis of the relationship between industrial production consequences and human activities. The case study presented concerns the city of Taranto, located in Southern Italy and characterized by the difficult relationship between the largest steel industry in Europe and a unique natural environment of great biological value. The presence of data in an adequate time scale allows the development of a holistic approach to the assessment of the policies of territorial governance in progress. Data from multiple sources are analyzed using multivariate statistical methods able to summarize the information to assess the first results of ongoing policies.
The authors collaborated in equal parts to the writing of the present essay.
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Notes
- 1.
Source: Istat data, censuses of 1881 and 1911. Data taken from the Istat website (www.istat.it). Web page visited as of 04/02/2019.
- 2.
Law 4 March 2015, n. 20, art. 5 (paragraph 1). The law provides for the activation of a permanent institutional table for the Taranto area (PIT), set up at the Prime Minister’s Office - Mission structure for the coordination of the reconstruction and development processes of the territories hit by the earthquake of 6 April 2009, development interventions in the area of Taranto and Managing Authority of the National Operational Program Cultural, natural and tourism attractors (decree president council ministry, 1 June 2014 and 23 June 2016) in charge of defining the operational content of the planning tool and coordinating its implementation.
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Perchinunno, P., Bilancia, M., Rotondo, F. (2019). Industrial Development and Environmental Sustainability: A Multivariate Statistical Analysis. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11622. Springer, Cham. https://doi.org/10.1007/978-3-030-24305-0_6
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