Industrial Development and Environmental Sustainability: A Multivariate Statistical Analysis

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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.

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Perchinunno, P., Bilancia, M., & Rotondo, F. (2019). Industrial Development and Environmental Sustainability: A Multivariate Statistical Analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11622 LNCS, pp. 62–77). Springer Verlag. https://doi.org/10.1007/978-3-030-24305-0_6

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