Development and application of an innovative expert decision support system to manage sediments and to assess environmental risk in freshwater ecosystems

Abstract

With the aim of supporting decision makers to manage contamination in freshwater environments, an innovative expert decision support system (EDSS) was developed. The EDSS was applied in a sediment quality assessment along the Bormida river (NW, Italy) which has been heavily contaminated by an upstream industrial site for more than a century. Sampling sites were classified by means of comparing chemical concentrations with effect-based target values (threshold and probable effect concentrations). The level of each contaminant and the combined toxic pressure were used to rank sites into three categories: (i) uncontaminated (8 sites), (ii) mildly contaminated (4) and (iii) heavily contaminated (19). In heavily contaminated sediments, an environmental risk index (EnvRI) was determined by means of integrating chemical data with ecotoxicological and ecological parameters (triad approach). In addition a sediment risk index (SedRI) was computed from combining chemical and ecotoxicological data. Eight sites exhibited EnvRI values ≥0.25, the safety threshold level (range of EnvRI values: 0.14-0.31) whereas SedRI exceeded the safety threshold level at 6 sites (range of SedRI values: 0.16-0.36). At sites classified as mildly contaminated, sublethal biomarkers were integrated with chemical data into a biological vulnerability index (BVI), which exceeded the safety threshold level at one site (BVI value: 0.28). Finally, potential human risk was assessed in selected stations (11 sites) by integrating genotoxicity biomarkers (GTI index falling in the range 0.00-0.53). General conclusions drawn from the EDSS data include: (i) in sites classified as heavily contaminated, only a few exhibited some significant, yet limited, effects on biodiversity; (ii) restrictions in re-using sediments from heavily contaminated sites found little support in ecotoxicological data; (iii) in the majority of the sites classified as mildly contaminated, tested organisms exhibited low response levels; (iv) preliminary results on genotoxicity biomarkers indicate possible negative consequences for humans if exposed to river sediments from target areas.

Screening Risk Assessment of Agricultural Areas under a High Level of Anthropopressure Based on Chemical Indexes and VIS-NIR Spectroscopy

“…In most cases, hazard screening, prioritisation and subsequent risk assessment are performed on a chemical-by-chemical basis. As a first screening, the following indexes are frequently used: hazard quotient (HQ), toxic units (TU), toxic pressure (TP) or toxicity equivalency factor (TEF) methodology [ 3 , 14 , 15 , 16 , 17 ].…”

Intelligent Decision Support Systems

“…Finally, potential human risk was assessed in selected stations (11 sites) by integrating genotoxicity biomarkers (GTI index falling in the range 0.00-0.53). General conclusions drawn from the EDSS data include: (i) in sites classified as heavily contaminated, only a few exhibited some significant, yet limited, effects on biodiversity; (ii) restrictions in re-using sediments from heavily contaminated sites found little support in ecotoxicological data; (iii) in the majority of the sites classified as mildly contaminated, tested organisms exhibited low response levels and (iv) preliminary results on genotoxicity biomarkers indicate possible negative consequences for humans if exposed to river sediments from target areas (Dagnino et al 2013). …”

“…Further several examples are provided regarding the integration of the recommender system (Wang and Wu 2009), advisory system Hejlesen et al 1997) and expert system (Dagnino et al 2013) with decision support systems. Wang and Wu (2009) developed a recommender system by focusing on the online decision support module with respect to customers' characteristics and supplier's profits.…”

Contamination and genotoxicity biomarker responses in bivalve mussels from the major Lithuanian rivers

“…On the other hand, biomarker responses of indigenous, sentinel organisms in the areas with long history of contamination may be not sufficiently informative because of adaptation and elimination of the most sensitive individuals (Large et al ; Baršienė et al ). Therefore, integrated assessment of biomarker responses and chemical contamination could provide more accurate and comprehensive information about the ecological status of aquatic ecosystems (Chapman ; Štambuk et al ; Kolarević et al , ; Dagnino et al ).…”