Monitoring the characteristics of wastewater can enable a better choice of the options available for its treatment and also provide a rational basis for the surveillance of the spread of waterborne diseases. Our work focused on bringing down the costs associated with the estimation of the biological and physico-chemical parameters of wastewater at a common wavelength of 600 nm. We demonstrated the advantages of using the Dye Reduction-based Electron-transfer Activity Monitoring (DREAM) assay to estimate bacterial activity as an alternative to the bacterial colony count method. This assay relies on the colorimetric measurement of the extent of reduction of methylene blue in response to bacterial electron transfer. We also present the results of estimating chemical oxygen demand (COD) and turbidity, using the standard methods of wastewater analysis, at the same wavelength of 600 nm for samples having known values of COD and turbidity. Our results open up the possibility of replacing expensive spectrophotometers with LED-based, microcontroller-enabled colorimeters that can be easily automated. The results of our study set the stage for the establishment of a greater number of wastewater analysis laboratories in economically backward regions which can in turn support measures to improve sanitation facilities.

  • Bacterial activity can substitute bacterial count for assessment of bacterial load in domestic wastewater.

  • Bacterial activity is estimated using the DREAM assay at 600 nm.

  • Colorimetric tests for estimation of chemical oxygen demand and turbidity were optimized at 600 nm.

  • Single-wavelength characterization of domestic wastewater simplifies the process in terms of money, time and effort.

One in four people in the world rely on a drinking water source which is contaminated with fecal matter (WHO 2022a). In the year 2020, almost 494 million people in the world were still practising open defecation and around 90% of them were living in Central and Southern Asia and sub-Saharan Africa (JMP 2022). Poor sanitation practices are directly or indirectly associated with waterborne diseases and antimicrobial resistance (UNICEF & WHO 2020). In India, deaths due to waterborne diarrhoeal diseases are the second highest after those resulting from respiratory disorders and pose a national economic burden of approximately INR 4,800 crores per year (CBHI 2021). The United Nations General Assembly recognizes sanitation as a human right and the United Nations Sustainable Development Goal (UN SDG) target 6.2 emphasizes on ‘adequate and equitable sanitation for all’ (WHO 2022b). Since treated wastewater is used in water-starved regions for non-potable applications (Liao et al. 2021) – such as irrigation, toilet-flushing, and washing clothes – effective treatment of wastewater is essential for preventing unwarranted spread of disease and avoiding secondary complications. Bacterial load, chemical oxygen demand (COD), and turbidity can be commonly used to obtain valuable insights into the biological and physico-chemical characteristics of untreated wastewater.

Biological characteristics of wastewater are used as an indicator of the sanitary conditions of a water source and can help in deciding an optimal protocol for disinfection. Estimation of bacterial load in water or wastewater is commonly carried out using membrane filtration and viable plate count (APHA 2017b) or other colorimetric methods involving pH change and enzyme catalysis (Kim & Yoo 2022). Bacterial count involving serial dilution of the sample, membrane filtration, growth in sterile petriplates containing culture medium and counting of colonies after 24–48 h is a laborious, error-prone, and time-consuming approach.

As an alternative, the Dye Reduction-based Electron-transfer Activity Monitoring (DREAM) assay is a functional measure that estimates the activity of bacterial cells on the basis of their ability to convert the redox indicator dye methylene blue to its colorless form (Vishwanathan et al. 2015). Methylene blue gets reduced to its leuco form by accepting the electrons released from the microbial breakdown of organic substances. The extent of decolorization indicates the level of bacterial activity. This assay has been used previously to evaluate electron transfer activity in the anode chamber of microbial fuel cells (Vishwanathan et al. 2016) and antimicrobial activity of myco-synthesized nanoparticles (Rai et al. 2023). Our study presents a novel approach to estimate bacterial activity in raw domestic wastewater using the DREAM assay.

Organic load in wastewater is commonly estimated using COD. When studied in relation to biological oxygen demand (BOD), it gives an estimate of the biologically degradable components of wastewater (Eddy et al. 2014). Studies on microbial electrochemical systems for sustainable treatment of wastewater have reiterated the tight linkage between bacterial activity and the readily utilizable organic content (Saratale et al. 2017). Pre-calibrated colorimeters are often preferred for the sake of accuracy and convenience of COD determination (Ho et al. 2021) However, this method demands the use of proprietary reagent vials which makes the analysis very expensive.

The standard method for COD determination involves subjecting the sample to chemical oxidation in a closed glass vial at 150 °C for a duration of 2 h in the presence of a digestion solution containing potassium dichromate, sulfuric acid and silver sulfate (APHA 2017a). The electrons released in this process reduce the hexavalent chromium ions from potassium dichromate into trivalent chromium. Determination of COD can be carried out either by titration against ferrous ammonium sulfate or by colorimetry. Although cost-effective, the titrimetric method is not preferred because it is labor-intensive, time-consuming and prone to volumetric errors. In the colorimetric approach, COD is determined by colorimetrically estimating the concentration of chromium ions.

Turbidity of wastewater, also referred to as cloudiness, is attributed to suspended solids, colloidal matter such as clay and silt, finely divided organic and inorganic matter, and microorganisms. It is an expression of the optical property of the wastewater sample that causes scattering or absorption of light (Sawyer et al. 2003). Highly turbid water can cause clogging of filters or damage valves and taps due to deposition of mud and silt. Turbidity is also used as a quick indicator to estimate the efficiency of the treatment process because the determination of total suspended solids (TSS) or COD can be time consuming. Turbidity is estimated conventionally using a nephelometer or a turbidity meter (Owodunni et al. 2022).

Although pre-treatment characterization of raw wastewater is not given much importance due to the high costs and efforts involved, it must be carried out mandatorily to determine the mode and extent of treatment needed. Consequently, the establishment of a larger number of analytical laboratories for characterization of wastewater is of utmost importance in regions where treated wastewater can be potentially harnessed to successfully deal with water stress. Carreres-Prieto et al. (2023) present a comprehensive overview of the developments in spectrometric determination of physico-chemical parameters of wastewater at different wavelength ranges for increased accuracy of wastewater characterization. Our study presents an alternate approach to evaluate bacterial load in domestic wastewater using bacterial activity as a measure. The objective of our study is to make biological and physico-chemical characterization simpler and affordable by optimizing protocols for colorimetric estimation of bacterial activity, COD and turbidity of domestic wastewater samples at a common wavelength of 600 nm.

Source of wastewater

All experiments were performed using raw domestic wastewater collected from the sewage treatment plant located in the Prasanthi Nilayam township at Puttaparthi, Sri Sathya Sai District in the state of Andhra Pradesh, India.

Estimation of bacterial load

On the basis of the understanding that the total suspended solids (TSS) of domestic wastewater predominantly comprises organic matter that serves as a substrate for bacterial growth, we assumed TSS concentration to be an indicator of the bacterial load to prepare samples for the experiments. Raw domestic wastewater was diluted to obtain test samples A, B, C, D, E, and F having TSS concentrations of 0, 20, 40, 60, 80, and 100 mg/l having different levels of bacterial load. These samples were analyzed to compare the number of bacterial colonies obtained using the membrane filtration method (APHA 2017b) with the bacterial activity estimated using the DREAM assay (Vishwanathan et al. 2015) at 600 nm.

For the membrane filtration method, the test samples were subjected to 1010-fold serial dilutions using sterile distilled water. 100 ml of the diluted sample was filtered in a Millipore filtration apparatus using a 0.45-μm membrane filter and 20 ml of sterile distilled water was poured along the walls of the filtration cup to rinse. The filter was then placed in a sterile petriplate having an absorbent disc soaked in 2 ml of Luria Bertani (LB) broth. Following incubation at 37 °C for 24 h, bacterial colonies were counted using a microscope. These experiments were carried out in six replicates.

For the DREAM assay, 40 ml of LB broth was inoculated with 10 ml of the test sample and incubated in a temperature-controlled rotary shaker at 37 °C. 3 ml of the culture from the flask was taken in a cuvette after completion of 4 h and 5 μl of methylene blue (30 mM) was added to it. The cuvette was placed in a colorimeter (Systronics) and absorbance readings at 600 nm were recorded at 10-s intervals for a period of 150 s to determine the extent of decolorization of methylene blue. The decrease in absorbance (normalized to 1) was taken as the measure of bacterial activity. These experiments were carried out in 10 replicates. Bacterial activity was estimated for three samples from different locations and compared with the bacterial count to validate the colorimetric method.

Determination of COD

A stock solution having a COD of 1,000 mg/l was prepared by dissolving 850 mg of potassium sodium pthalate in 1 l of distilled water. It was then diluted to obtain test samples having COD of 120, 160, 200, 240, 280, 320, 360, 400, 440, and 480 mg/l. These samples were analyzed to compare the COD determined using a pre-calibrated colorimeter against the calculated values of COD determined using measurements with a simple colorimeter at 600 nm.

For the reference method using a pre-calibrated colorimeter, 2 ml of the test sample was added to a commercially available COD determination vial containing the digestion reagent. 2 ml of distilled water constituted the blank sample. The vials were then placed in a digestor (HACH DRB 200) for a period of 2 h at 150 °C. The vials were allowed to cool down to room temperature before COD was determined using a pre-calibrated colorimeter (HACH, DR/850). The experiments were carried out in triplicate.

For the laboratory-based colorimetric method, the test samples were processed as per the protocol prescribed in the standard methods for the examination of water and wastewater (APHA 2017a). 2.5 ml of the sample was added to a vial containing 1.5 ml of potassium dichromate solution and 3.5 ml of sulfuric acid reagent. 2.5 ml of distilled water constituted the blank sample which was used as a base reference for the colorimetric readings. The vials, with their screw caps closed tightly, were then placed in a digestor (HACH DRB 200) for a period of 2 h at 150 °C. The vials were allowed to cool down to room temperature before absorbance values were recorded at 600 nm using a colorimeter (Systronics). The experiments were carried out in 12 replicates. One-way analysis of variance (ANOVA) was performed to assess the variability within and across the samples. Simple linear regression was used to model the relationship between the COD values of the samples and the absorbance values. COD was determined for four domestic wastewater samples to compare the two methods.

Estimation of turbidity

Domestic wastewater was diluted to obtain test samples having turbidity of 20, 40, 60, 80, and 100 NTU. The test sample was taken in a vial and gently mixed. Turbidity readings for the samples recorded using a turbidity meter were compared against the calculated values estimated using measurements with a simple colorimeter at 600 nm.

Our work involved optimizing the protocols for simplified colorimetric estimation of bacterial activity, COD, and turbidity at a single wavelength (600 nm) to prepare the ground for facilitating the development of low-cost single-wavelength LED-based colorimeters for wastewater characterization prior to treatment. Since our main focus was to lower the cost of analysis, we acknowledge that there is a trade-off with respect to the accuracy of results compared to the reference methods currently being used for the estimation of these three parameters. However, since these tests are primarily meant to enable the determination of mode and extent of treatment for making treated wastewater usable for secondary non-potable applications, accuracy levels of around 95% should be acceptable.

Estimation of bacterial activity using the DREAM assay at 600 nm

Measurements of methylene blue decolorization in this study were carried out at an adjusted wavelength of 600 nm, which lies within the absorption peak of methylene blue. Multiple iterations of the methylene blue decolorization profile plotted every hour after inoculation of the LB broth with different dilutions of raw wastewater showed that the resolution of the difference in bacterial load across the samples was the best at the fourth hour, when the cells were in the midst of the exponential growth phase (Figure 1). This explains the reason for fixing the growth time of bacterial cultures for the DREAM assay in our study at 4 h.
Figure 1

Estimation of bacterial activity for six test samples of domestic wastewater at subsequent time points in the log phase shows that the resolution is best at the fourth hour after inoculation.

Figure 1

Estimation of bacterial activity for six test samples of domestic wastewater at subsequent time points in the log phase shows that the resolution is best at the fourth hour after inoculation.

Close modal
One-way ANOVA (p < 0.01) statistically confirmed the significance and reliability of the measurements using each of the methods individually. Figure 2 shows a significant correlation (r = 0.96, p < 0.01) between the bacterial activity estimated using the DREAM assay, reported as a normalized measure of decolorization in 150 s at the fourth hour after inoculation, and the bacterial counts estimated using the membrane filter method for the five samples. This validates the comparability of the two methods in evaluating the bacterial load in raw wastewater. However, it is essential to understand that bacterial count and activity are different measures which cannot be directly equated with each other because the DREAM assay additionally takes into account the metabolic state of the bacteria. As a result, the assay would ideally have to be optimized at a given site to ascertain the degree of correspondence between bacterial activity and count for that particular wastewater source because the metabolic state of bacteria can vary based on various factors. In our validation experiments, bacterial activity of the three domestic wastewater samples from different locations showed a similar correspondence to bacterial count as in the case of the six test samples (Table 1).
Table 1

Bacterial activity estimated using the DREAM assay and count determined by the membrane filter method for domestic wastewater samples collected from three different sources

S. No.Bacterial activity using the DREAM assayBacterial count (×1013)(CFU/100 ml)
Sample 1 0.679 2.22 
Sample 2 0.668 2.14 
Sample 3 0.059 0.036 
S. No.Bacterial activity using the DREAM assayBacterial count (×1013)(CFU/100 ml)
Sample 1 0.679 2.22 
Sample 2 0.668 2.14 
Sample 3 0.059 0.036 
Figure 2

Comparison between bacterial plate count for different dilutions of wastewater and the corresponding bacterial activity estimated at 600 nm using the DREAM assay at the fourth hour after inoculation. A, B, C, D, E, and F denote six samples of domestic wastewater diluted to contain 0, 20, 40, 60, 80, and 100 mg/l of TSS, respectively.

Figure 2

Comparison between bacterial plate count for different dilutions of wastewater and the corresponding bacterial activity estimated at 600 nm using the DREAM assay at the fourth hour after inoculation. A, B, C, D, E, and F denote six samples of domestic wastewater diluted to contain 0, 20, 40, 60, 80, and 100 mg/l of TSS, respectively.

Close modal

Advantages of using the DREAM assay to estimate the bacterial load

We chose to use the DREAM assay to estimate the bacterial load in wastewater in order to shorten the time taken to obtain bacterial colonies, eliminate the errors that could arise during serial dilutions and lower the costs associated with the filtration process. It takes around 24–48 h to estimate the number of bacterial colonies using membrane filtration, which is known to be expensive (Elmund et al. 1999), followed by the heterotrophic or standard plate count (Allen et al. 2004). On the other hand, bacterial activity can be estimated using the DREAM assay in less than 5 h, significantly bringing down the time taken. Bacterial count usually prolongs the compilation of wastewater analysis reports. Such delays could be avoided by the use of the DREAM assay for estimating bacterial activity instead. The elaborate and cumbersome membrane filter method involves serial dilution of the wastewater sample, filtration and plating, followed by microscopic count of the bacterial colonies in defined segments of the plate. Even a small inadvertent error in any of these steps would lead to a significant difference in the final estimation of the bacterial count due to the incorporation of a multiplication factor in the calculations. In contrast, the scope of introducing errors while performing the DREAM assay, which involves only culturing bacteria and recording colorimetric measurements, is almost negligible. Finally, the high costs associated with procurement and maintenance of the filtration apparatus and membranes can be totally eliminated if the DREAM assay is used (McClain 2014). The cost of assessing bacterial activity of a wastewater sample using the DREAM assay is almost 30 times cheaper than using the membrane filter method to estimate the bacterial count.

Colorimetric determination of COD at 600 nm

In the colorimetric approach, the composition and quantity of the digestion reagent are optimized such that the determination of COD higher than 100 mg/l is carried out by measuring the concentration of the resultant trivalent chromium ions at 600 nm (Li et al. 2009). Since the COD of domestic wastewater typically ranges from 250 to 800 mg/l, colorimetric measurements in our study were performed at 600 nm. The absorbance values at 600 nm obtained from the analysis of the test samples having known COD concentrations ranging from 120 to 480 mg/l using the colorimetric method were plotted to obtain a calibration curve. Simple linear regression analysis resulted in the following equation for calculating the COD of a sample based on the absorbance values:
formula
One-way ANOVA (p < 0.01) statistically confirmed the significance and reliability of the measurements using each of the methods individually. Figure 3 shows a significant correlation (r = 0.99, p < 0.01) between the COD values of the known test samples determined using the reference method and those calculated using the colorimetric method at 600 nm. Table 2 shows that the COD values of four random domestic wastewater samples estimated using the reference and colorimetric methods were comparable.
Table 2

Mean values of COD (with standard deviation) estimated using the reference method and colorimetric method at 600 nm for domestic wastewater samples

Unknown sampleCOD determined using the reference method (mg/l)COD calculated using the colorimetric method (mg/l)
104.5 ± 0.7 105.7 ± 7.4 
215 ± 6.4 221.3 ± 5.7 
283 ± 7.1 298.7 ± 5.1 
396 ± 1.4 391.7 ± 3.5 
Unknown sampleCOD determined using the reference method (mg/l)COD calculated using the colorimetric method (mg/l)
104.5 ± 0.7 105.7 ± 7.4 
215 ± 6.4 221.3 ± 5.7 
283 ± 7.1 298.7 ± 5.1 
396 ± 1.4 391.7 ± 3.5 
Figure 3

Comparison between COD values determination using the reference method and the calculated COD using the colorimetric method at 600 nm for test samples of different concentrations.

Figure 3

Comparison between COD values determination using the reference method and the calculated COD using the colorimetric method at 600 nm for test samples of different concentrations.

Close modal

The use of commercially available reagent vials enables the direct measurement of COD using a pre-calibrated colorimeter after digestion of the samples, albeit at a high cost. In order to offset the expenses associated with such sophisticated equipment, especially for routine assessment of wastewater in resource-limited settings, our study adopted the colorimetric method prescribed in the standard methods for the examination of water and wastewater (APHA 2017a). A single test using the colorimetric method would bring down the cost by about 90% compared to the reference method involving commercially available proprietary reagent vials and a pre-calibrated colorimeter.

Colorimetric estimation of turbidity at 600nm

The absorbance values at 600 nm obtained from the analysis of the test samples using the colorimetric method were plotted to obtain a calibration curve. Simple linear regression analysis resulted in the following equation for calculating the turbidity of a sample based on the absorbance values:
formula
Figure 4 shows a significant positive correlation (r = 0.99, p < 0.05) between the turbidity values measured for the test samples using a turbidity meter and those calculated from the absorbance values obtained using a colorimeter at 600 nm. A high positive correlation shows that the colorimetric readings can be used for estimation of wastewater turbidity. One-way ANOVA (p < 0.01) statistically confirmed the significance and reliability of the measurements using each of the methods. Table 3 shows that the turbidity values of four random domestic wastewater samples determined using a turbidity meter and calculated using the colorimetric method were comparable.
Table 3

Mean values of turbidity (with standard deviation) estimated using a turbidity meter and the colorimetric method at 600 nm for domestic wastewater samples

Unknown sampleTurbidity determined using turbidity meter (NTU)Turbidity estimated using colorimeter at 600 nm (NTU)
140.2 ± 5.4 142.9 ± 2.0 
156.1 ± 1.3 162.6 ± 2.0 
208 ± 5.7 209.9 ± 2.0 
127.4 ± 6.2 132.3 ± 0.8 
Unknown sampleTurbidity determined using turbidity meter (NTU)Turbidity estimated using colorimeter at 600 nm (NTU)
140.2 ± 5.4 142.9 ± 2.0 
156.1 ± 1.3 162.6 ± 2.0 
208 ± 5.7 209.9 ± 2.0 
127.4 ± 6.2 132.3 ± 0.8 
Figure 4

Comparison between the turbidity values estimated using a turbidity meter and the colorimetric method at 600 nm for different dilutions of wastewater.

Figure 4

Comparison between the turbidity values estimated using a turbidity meter and the colorimetric method at 600 nm for different dilutions of wastewater.

Close modal

Turbidity of wastewater can be used as an indicator of the suspended solids and COD (Joannis et al. 2008). Turbidity meters rely on absorbance measurement of light scattered by the wastewater sample over a broad range of wavelengths. Since it is not necessary for the turbidity assessment of raw wastewater to be highly accurate, measurements using commercially available, expensive, three-wavelength nephelometers can be replaced by a simple single-wavelength colorimetric procedure.

Characterization of raw wastewater is essential for adopting appropriate measures for treatment, surveillance, and energy recovery, especially in developing regions where financial resources for sanitation are hard to come by. We proposed the use of bacterial activity based on the DREAM assay as a simpler, quicker, and cost-effective alternative to the conventional plate count method to estimate the bacterial load in wastewater. The standard colorimetric methods for the determination of COD and turbidity were also aligned to a common wavelength of 600 nm to enable the assessment of all three parameters of raw domestic wastewater using a single-wavelength colorimeter rather than using expensive pre-calibrated, multi-function colorimeters. The outcome of our study paves the path for the development of low-cost LED-based single-wavelength colorimeters that can facilitate physico-chemical and biological characterization of raw domestic sewage prior to treatment. This system could be integrated with a microcontroller (McClain 2014) to automate some of the functions and further simplify the process.

This work is dedicated to Bhagawan Sri Sathya Sai Baba, the founder chancellor of the Sri Sathya Sai Institute of Higher Learning. Research facilities provided by the Central Research Instruments Facility, SSSIHL are gratefully acknowledged.

S.S.M. and A.S.V. contributed to the study conception and design. Material preparation, data collection, and analysis were performed by S.S.M. The first draft of the manuscript was written by both authors. Both authors reviewed and approved the final manuscript.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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