Olive mill wastewater characteristics: modelling and statistical analysis

Authors

  • Luísa C. Davies Centre of Biological and Chemical Engineering, Instituto Superior Técnico
  • André M. Vilhena Centre of Biological and Chemical Engineering, Instituto Superior Técnico
  • Júlio M. Novais Centre of Biological and Chemical Engineering, Instituto Superior Técnico
  • Susete Martins-Dias Centre of Biological and Chemical Engineering, Instituto Superior Técnico

DOI:

https://doi.org/10.3989/gya.2004.v55.i3.171

Keywords:

Chemical Oxygen Demand (COD), Modelling, Olive Mill Wastewater (OMW), OMW characteristics, Phenolic compounds

Abstract


A synthesis of the work carried out on Olive Mill Wastewater (OMW) characterisation is given, covering articles published over the last 50 years. Data on OMW characterisation found in the literature are summarised and correlations between them and with phenolic compounds content are sought. This permits the characteristics of an OMW to be estimated from one simple measurement: the phenolic compounds concentration. A model based on OMW characterisations accounting 6 countries was developed along with a model for Portuguese OMW. The statistical analysis of the correlations obtained indicates that Chemical Oxygen Demand of a given OMW is a second-degree polynomial function of its phenolic compounds concentration. Tests to evaluate the regressions significance were carried out, based on multivariable ANOVA analysis, on visual standardised residuals distribution and their means for confidence levels of 95 and 99 %, validating clearly these models. This modelling work will help in the future planning, operation and monitoring of an OMW treatment plant.

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Published

2004-09-30

How to Cite

1.
Davies LC, Vilhena AM, Novais JM, Martins-Dias S. Olive mill wastewater characteristics: modelling and statistical analysis. Grasas aceites [Internet]. 2004Sep.30 [cited 2024Mar.28];55(3):233-41. Available from: https://grasasyaceites.revistas.csic.es/index.php/grasasyaceites/article/view/171

Issue

Section

Research