# DPSIR Model Applied to the Remediation of Contaminated Sites. A Case Study: Mar Piccolo of Taranto
## 10 Conclusions  
Considering the case study of the Mar Piccolo in Taranto, the existing information and knowledge were synthesized in order to understand the major issues affecting this marine basin in the last half-century and how to respond to them. Following the DPSIR approach, used as global framework of the analysis, it was possible to gauge the potential responses to be implemented, although they are strongly constrained by the new development strategy for the investigated areas. The revised data revealed how the Mar Piccolo is a strongly anthropized environment, as a final receptor of a series of pollutants coming from all urban, industrial and agricultural activities, municipal wastewater treatment plants, and other anthropic activities, especially due to its natural hydrogeological network conformation. Mussel farming represents a historical economic activity for Taranto but also, unfortunately, a critical impact on the ecosystem due to subsequent marine litter. The mobility of contaminants from sediments to the water column showed the potential risk related to the bioaccumulation of organisms from different trophic levels, posing a threat of unacceptable magnitude to human safety. Some responses, already taken by the Apulia Region and the Special Commissioner of the Italian Government, were reported, while others have been hypothesized and, above all, related to the reclamation interventions. Together with the adoption of appropriate remediation solutions, which, however, require site-specific in-depth studies based on lab scale and pilot scale investigations, it is necessary to redesign a new development strategy of the area under investigation. The control and regulation of the driving forces, such as wastewater discharges, assumes a fundamental role to ensure that the results of the remediation can last over time. While generalizing in order to provide reliable environmental decision support tools, consistent cause-effect relationships should be developed. Future lines of research should include the development of tools operating in the individual parts (e.g., state, impacts, responses), and the development of relations between the different parts of DPSIR. Figure 17: (**a**) Total dataset projection of Score plot (samples) and Loading plot (variables) on space PC1/PC2; (**b**) Arsenal dataset projection of Score plot (samples) and Loading plot (variables) on space PC1/PC2 (S = Surficial = layers 0–10 cm (**a**), 10–30 cm (**b**), 30–50 cm (**c**); I = Intermediate = layers 100–120 cm; P = Deep = layers 180–200 cm, 280–300 cm) [1]. **Supplementary Materials:** The following are available online at [[http://www.mdpi.com/2076-3417/10/15/5080/s1](http://www.mdpi.com/2076-3417/10/15/5080/s1)]([http://www.mdpi.com/2076-3417/10/15/5080/s1](http://www.mdpi.com/2076-3417/10/15/5080/s1)), Figure S1: Population trend in cities falling into Mar Piccolo catchment area from 1861 to 2019 and (b) population density index (ratio between the number of inhabitants and area of town); Figure S2: Localization of treatment and disposal sites for special waste, hydrogeological network, and lithotypes; Figure S3: Metal concentrations (mg/kg) for As, Cd, Cu, Hg, Ni, Pb, V, Zn, and organic contaminants concentrations (ug/kg) for PAHs and PCBs in sediments (blue bars are used for samples taken at 0-1.5 m below the seafloor and red bars for samples taken at 1.5-3.0 m below seafloor). The red dashed lines indicate the site-specific law (ICRAM, 2004) [45]; Figure S4: (a) Localization of investigation stations and (b) percentages of Vibrio species isolated in water samples [47]; Figure S5: (a) Ex situ bioaccumulation tests and (b) in situ bioaccumulation tests (Adapted from [30]); Figure S6: (a) Dendogram for 20 variables with identification of two main clusters and (b) first cluster correlations (TOC, As, Cd, Hg, Pb, Cu, Zn) [1]. **Author Contributions:** Conceptualization, S.D.G., F.T. and M.N. ; methodology, S.D.G. and F.T. ; software, C.L. ; validation, M.N. and S.D. ; formal analysis, C.L. and F.T. ; investigation, C.L. and F.T.