AI Article Synopsis

  • The paper introduces a fuzzy logic-based methodology to evaluate the risk of water pollutants from wastewater treatment plants (WWTPs), focusing on handling uncertainty in environmental data.
  • The study analyzed pollution data from 22 WWTPs in Catalonia, identifying key contaminants such as nickel, diuron, and endocrine disruptors like nonyl and octylphenol, with most pollutants posing medium or low risks.
  • The fuzzy logic approach proved to be more conservative than the established COMMPS procedure, incorporating expert weightings and accounting for chemical persistence, while still aligning closely with COMMPS findings.

Article Abstract

This paper presents a new methodology to assess the risk of water effluents from waste-water treatment plants (WWTPs) based on fuzzy logic, a well-known theory to deal with uncertainty, especially in the environmental field where data are often lacking. The method has been tested using the effluent's pollution data coming from 22 waste-water treatment plants (WWTPs) located in Catalonia (NE Spain). Thirty-eight pollutants were analyzed along three campaigns performed yearly from 2008 to 2010. Whereas 9 compounds have been detected in more than 70% of the samples analyzed, 7 compounds have been found at levels equal or higher than the river Environmental Quality Standards set by the Water Framework Directive. Upon combination of both criteria (presence and concentration), compounds of greatest environmental concern in the WWTP studied are nickel, the herbicide diuron, and the endocrine disruptors nonyl and octylphenol. It is remarkable the low variability of the pollutant concentration just differing for the case of nickel and zinc. These low values of exposure together with other pollutants' characteristics provide a medium or low risk assessment for all the WWTPs. The results of this new method have been compared with COMMPS procedure, a solid method developed in the context of the Water Framework Directive, and they show that the fuzzy model is more conservative than COMMPS. This is due to different reasons: the fuzzy model takes into account the persistence of chemical compounds whereas COMMPS does not; the fuzzy model includes the weights provided by an expert group inquired in previous works and also considers the uncertainty of the environmental data, avoiding the crisp values and offering a range of overlapping between the different fuzzy sets. However, the results even if being more conservative with fuzzy logic, are in good agreement with a solid methodology such as the COMMPS procedure.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2012.09.008DOI Listing

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