Abstract

A scientific basis is given to the traditional method of inferring effluent quality based on visualization of samples in transparent flasks. A scale of 1–6, with different printed grey intensities, is placed behind transparent PET bottles containing the sample, and gives an indication of the range of turbidity in the sample (1 is the most transparent and can only be visualized if the effluent is well clarified; in the other spectrum, 6 is the darkest and indicates highly turbid effluents). Turbidity has been correlated with total suspended solids (TSS), particulate biochemical oxygen demand (BOD) and particulate chemical oxygen demand (COD) based on thousands of monitored data collected in the effluent from seven different treatment processes in Brazil: UASB reactor, trickling filters, activated sludge, horizontal wetland, vertical wetland, polishing ponds and coarse filter after pond. The method is simple and instantaneous, can be used in virtually all places and in every visit of the operator to the remote treatment plant, allows recording of the image in smartphones, does not use any equipment, chemicals or energy, and showed to represent well the effluent quality of existing treatment plants. This essay is complementary and does not substitute specific traditional sampling and analysis, but allows easy inference of deterioration of effluent quality.

HIGHLIGHTS

  • A scientific basis is given to the traditional method of inferring effluent quality based on visualization of effluent samples in transparent flasks.

  • A scale of 1–6, with stripes with different printed grey intensities, is placed behind transparent PET bottles containing the sample, and gives an indirect indication of the range of turbidity in the sample.

  • Turbidity was correlated with TSS, particulate BOD and particulate COD based on thousands of monitored data collected in seven different treatment processes.

  • The method is simple and instantaneous, can be used in virtually all places and in every visit of the operator, allows recording of the image in smartphones, does not use any equipment, chemicals or external energy, and showed to represent well the effluent quality of existing treatment plants.

Graphical Abstract

Graphical Abstract
Graphical Abstract
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Supplementary data