Assessing the environmental impact of wastewater treatment plants by chemometric approach

  • J. Bayo /
  • D. Ruiz-Martínez /
  • J. Carpe /
  • J. López-Castellanos
Journal ar
International Journal of Sustainable Development and Planning
  • Volumen: 11
  • Número: 2
  • Fecha: 01 January 2016
  • Páginas: 203-211
  • ISSN: 1743761X 17437601
  • Source Type: Journal
  • DOI: 10.2495/SDP-V11-N2-203-211
  • Document Type: Article
  • Publisher: WITPress
© 2016 WIT Press. This paper presents the results of principal factor analysis technique (PFA) developed for a 3-year study (2010-2012) on two urban wastewater treatment plants (WWTPs) situated in Murcia, Southeast of Spain. One of them receives wastewater for a medium-sized city (WWTP1), with an important industrial area, and the other one treats only domestic wastewater from a small-sized town (WWTP2), with slightly different treatment systems between them. Process performance and operation of WWTP are carried out to ensure their compliance with legislative requirements imposed by European Union. Because high amounts of variables are daily measured, a coherent and structured approach of such a system is required to understand its inherent behavior and performance efficiency. In this sense, PFA as a chemometric technique allowed us to investigate and propose a data reduction that allowed to group water-quality variables into selected factors with common features to describe the behavior of both plants, and their similarities and differences. Four main factors were extracted for WWTP1, associated with the presence of nutrients, the ionic component, the organic load to the plant, and the efficiency of the whole process, with an explaining variance of 62.12%. For WWTP2, also four main components were extracted, explaining 63.82% of the variance. These factors were pollution load to the plant, pollution output, marine intrusion, and, finally, the ionic component of water. The geochemical background composition of water in this zone and the important use of fertilizers in agriculture appeared to be two significant factors driving the results.

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