Application of rough sets analysis to identify polluted aquatic sites based on a battery of biomarkers: a comparison with classical methods

The evaluation of toxicological effects at the cellular and molecular levels in organisms are often used to determine sites subjected to contamination problems that pose a threat to the long-term survival of organisms. However, the integration of multiple measurements on the health status of organisms into a model for site discrimination is challenging. This study compares two discrimination methods which are based on rule inference: rough sets (RS) analysis and classification trees (CT) with classical multivariate discriminant analysis (DA). Site classification was attempted with six biomarkers of effects: metallothionein levels, lipid peroxidation, DNA damage, levels of lipophosphoproteins (i.e., vitellins), phagocytosis activity and haemocyte cell viability on clam (Mya arenaria) populations from the Saguenay River fjord (Quebec, Canada). Rule based methods have the advantage of complete independence from data distribution constraints in contrast to the classification methods from multivariate analysis that are more commonly used in ecotoxicology. Results show that RS and CT gave better classifications than DA because they do not require strong distributional assumptions. Moreover, RS provided classification rules that could identify the most important biomarker(s) for site discrimination. RS and CT were shown to be simple and efficient methods for classifying multivariable ecotoxicological data. This methodology would be especially useful when freedom from distributional assumptions is required.     

Distribution and relationships of trace metals in soft tissue,byssus and shells of Mytilus edulis trossulus from the southern Baltic

Concentrations of Hg, Cd, Pb, Ag, Cu, Zn, Cr, Ni, Co, Mn, and Fe in soft tissues, shells and byssus of blue mussel (Mytilus edulis trossulus) from 23 sites along the Polish coast of the Baltic Sea were determined by AAS method. Byssus, as compared with the soft tissue, concentrated more effectively Pb, Cu, Cr, and especially Ag, Ni, Mn and Fe, moderately Hg and Zn and less effectively Cd. Significant inter-regional and inter-size differences in metal concentrations in both soft tissues and byssus were recorded. Highly significant correlations (P<0.01, P<0.05) were observed between tissue and byssal concentrations of Cd, Pb, Ni and Ag. Factor analysis showed clear separation of both the tissue and byssi samples based on their geographic distribution, possibly reflecting a different rate of deposition of clay minerals at the head of the Pomeranian Bay and the Gulf of Gdańsk. The Pomeranian Bay differs from the Gulf of Gdańsk in respect to geological structure of bottom sediments as a substrata for the M. edulis trossulus as well as in relation to various sources of metallic pollutants. From the data obtained in the present study and those reported previously the soft tissue and especially byssus of M. edulis, in contrast to shells, appear to be a significantly better bioindicator for identification of coastal areas exposed to metallic contaminants.     

Bioavailability of HOC depending on the colloidal state of humic substances: a case study with PCB-77 and Daphnia magna

Condensed organic matter with higher affinity for hydrophobic organic compounds (HOC) is currently held responsible for slow desorption and concomitant lower bioavailabilities of HOC in sediments and soils. In an experiment with Daphnia magna and IHSS Peat Humic Acid (PHA), we showed that the bioconcentration factor (BCF) of 3,3',4,4'-tetrachlorobiphenyl (PCB-77) was directly related to the charge of the humic colloid, as predicted by the metal-humic binding model WHAM. Consistent with the type of binding to the humic acid (counter-ion accumulation vs. specific binding), increasing the concentration of Na+ and Ca2+ ions generated opposite effects on colloid charge and HOC binding by the humic acid. Condensation as a colloidal phenomenon in solution as well as on surfaces needs to be addressed as a contributor to lower bioavailabilities and, possibly, to slower desorption kinetics.     

Optimising reverse logistics network to support policy-making in the case of Electrical and Electronic Equipment

Due to the rapid growth of Waste Electrical and Electronic Equipment (WEEE) volumes, as well as the hazardousness of obsolete electr(on)ic goods, this type of waste is now recognised as a priority stream in the developed countries. Policy-making related to the development of the necessary infrastructure and the coordination of all relevant stakeholders is crucial for the efficient management and viability of individually collected waste. This paper presents a decision support tool for policy-makers and regulators to optimise electr(on)ic products’ reverse logistics network. To that effect, a Mixed Integer Linear Programming mathematical model is formulated taking into account existing infrastructure of collection points and recycling facilities. The applicability of the developed model is demonstrated employing a real-world case study for the Region of Central Macedonia, Greece. The paper concludes with presenting relevant obtained managerial insights.     

Method for quantitative assessment of the domino effect in industrial sites

Accidents caused by the domino effect are the most destructive accidents related to industrial sites. The most typical primary incidents for a domino effect sequence are explosions (57%), followed by fires (43%) (Abdolhamidzadeh et al., 2010). These former can generate three escalation vectors (heat load, overpressure, and fragments), and may affect the surrounding equipments and/or facilities. If the affected targets are damaged, they may also explode and generate other threats to other surrounding facilities and so on. These chains of accidents may lead to catastrophic consequences and may affect not only the industrial sites, but also people, environment and economy. This paper presents a methodology for quantitative assessment of domino effects caused by fire and explosion on storage areas. The individual and societal risks are also estimated.     

Depth of manual dismantling analysis: A cost–benefit approach

This paper presents a decision support tool for manufacturers and recyclers towards end-of-life strategies for waste electrical and electronic equipment. A mathematical formulation based on the cost benefit analysis concept is herein analytically described in order to determine the parts and/or components of an obsolete product that should be either non-destructively recovered for reuse or be recycled. The framework optimally determines the depth of disassembly for a given product, taking into account economic considerations. On this basis, it embeds all relevant cost elements to be included in the decision-making process, such as recovered materials and (depreciated) parts/components, labor costs, energy consumption, equipment depreciation, quality control and warehousing. This tool can be part of the strategic decision-making process in order to maximize profitability or minimize end-of-life management costs. A case study to demonstrate the models’ applicability is presented for a typical electronic product in terms of structure and material composition. Taking into account the market values of the pilot product’s components, the manual disassembly is proven profitable with the marginal revenues from recovered reusable materials to be estimated at 2.93–23.06 €, depending on the level of disassembly.