Experimental and optimization studies on phycoremediation of dairy wastewater and biomass production efficiency of Chlorella vulgaris isolated from Ganga River, Haridwar, India

Response surface methodology for process optimization in livestock wastewater treatment: A review

With increasing demand for meat and dairy products, the volume of wastewater generated from the livestock industry has become a significant environmental concern. The treatment of livestock wastewater (LWW) is a challenging process that involves removing nutrients, organic matter, pathogens, and other pollutants from livestock manure and urine. In response to this challenge, researchers have developed and investigated different biological, physical, and chemical treatment technologies that perform better upon optimization. Optimization of LWW handling processes can help improve the efficacy and sustainability of treatment systems as well as minimize environmental impacts and associated costs. Response surface methodology (RSM) as an optimization approach can effectively optimize operational parameters that affect process performance. This review article summarizes the main steps of RSM, recent applications of RSM in LWW treatment, highlights the advantages and limitations of this technique, and provides recommendations for future research and practice, including its cost-effectiveness, accuracy, and ability to improve treatment efficiency.

Application of ANN-MOGA for nutrient sequestration for wastewater remediation and production of polyunsaturated fatty acid (PUFA) by Chlorella sorokiniana MSP1

Chlorella bears excellent potential in removing nutrients from industrial wastewater and lipid production enriched with polyunsaturated fatty acids. However, due to the changing nutrient dynamics of wastewater, growth and metabolic activity of Chlorella are affected. In order to sustain microalgal growth in wastewater with concomitant production of PUFA rich lipids, RSM (Response Surface Methodology) followed by heuristic hybrid computation model ANN-MOGA (Artificial Neural Network- Multi-Objective Genetic Algorithm) were implemented. Preliminary experiments conducted taking one factor at a time and design matrix of RSM with process variables viz. Sodium chloride (1 mM-40 mM), Magnesium sulphate (100 mg-800 mg) and incubation time (4th day to 20th day) were validated by ANN-MOGA. The study reported improved biomass and lipid yield by 54.25% and 12.76%, along with total nitrogen and phosphorus removal by 21.92% and 18.72% respectively using ANN-MOGA. It was evident from FAME results that there was a significantly improved concentration of linoleic acid (19.1%) and γ-linolenic acid (21.1%). Improved PUFA content makes it a potential feedstock with application in cosmeceutical, pharmaceutical and nutraceutical industry. The study further proves that C. sorokiniana MSP1 mediated industrial wastewater treatment with PUFA production is an effective way in providing environmental benefits along with value addition. Moreover, ANN-MOGA is a relevant tool that could control microalgal growth in wastewater.

Nutrient sequestration and lipid production potential of Chlorella vulgaris under pharmaceutical wastewater treatment: experimental, optimization, and prediction modeling studies

The efficient management and treatment of pharmaceutical industry wastewater (PIWW) have become a serious environmental issue due to its high toxicity. To overcome this problem, the present study deals with the phycoremediation of PIWW using Chlorella vulgaris microalga isolated from the Ganga River at Haridwar, India. For this, response surface methodology (RSM) and artificial neural network (ANN) tools were used to identify the best reduction of total phosphorus (TP) and total Kjeldahl's nitrogen (TKN) based pollutants along with the lipid production efficiency of C. vulgaris. Three different concentrations of pharmaceutical wastewater (0, 50, and 100%), operating temperatures (20, 25, and 30 °C), and light intensity (2000, 3000, and 4000 lx) were used to design the phycoremediation experiments having 6:18 h of dark/light period and reactor functional volume of 15L. Findings revealed that C. vulgaris was good enough to remove maximum TP (90.35%), TKN (83.55%) along 20.88% of lipid yield at 25.62 °C temperature, 60.73% PIWW concentration, and 4000 lx of light intensity, respectively. Based on the model performance and validation results, ANN showed more accuracy as compared to the RSM tool. Therefore, the findings of this study showed that C. vulgaris is capable of treating PIWW efficiently along with significant production of lipid content which can further be used in various applications including biofuel production.

Efficient treatment of tannery wastewater through aeration, coagulation, and algal pond

BACKGROUND

Tannery wastewater effluents contain many toxic and carcinogenic heavy metals and physiochemical parameters that need to be removed before these effluents enter in the main water bodies or rivers. In this study, the effluents from the tannery industry are treated through aeration, coagulation, and Chlorella vulgaris pond treatment processes for the removal of physiochemical: parameters only.

METHODS

The effect of removal efficiencies (%) was studied on the physicochemical parameters, including salinity, electrical conductivity (EC), total dissolved solids (TDS), turbidity, total suspended solids (TSS), biochemical oxygen demand (BOD), and chemical oxygen demand (COD).

RESULTS

The key results showed that the removal of EC, TDS, turbidity, TSS, BOD, and COD was 80.2%, 67%, 81%, 80.8%, 68.6%, and 100%, respectively, in raw wastewater treatment having 25, 50, and 70 g of algae C. vulgaris doses. The removal efficiencies (%) of salinity, EC, TDS, turbidity, TSS, BOD, and COD were 83%, 87.1%, 77.1%, 80%, 40%, 97%, and 98%, respectively, during coagulated wastewater treatment with three doses of algae. The observed improvement in treated wastewater indicated that the removal efficiencies (%) of salinity, EC, TDS, turbidity, TSS, BOD, and COD were 85.7%, 39.3%, 81.3%, 67.8%, 50.3%, 97%, and 98%, with C. vulgaris.

CONCLUSION

This study confirmed that the treatment of tannery wastewater by these processes increased the pollutant removal efficiencies as all the physiochemical parameters were exceeding the permissible limits.

RESULTS CONTRIBUTION IN FUTURE

This research will be helpful to treat the industrial wastewaters or effluents before it further mixes up in the main water streams. In this way, water quality will be better, aquatic life will be saved, and further researchers can analyze more ways for efficient treatments as they have a baseline data through this study findings.

PRACTITIONER POINTS

One of the most pollutant sources in terms of both physical and chemical parameters is the produced wastewater from tannery industries. The effluents from tannery industry are treated through aeration, coagulation, and algae ponds treatment processes. These treatment made the tannery wastewater as environmental friendly.