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Removal of Emerging Contaminants Using Low-Cost and Advanced Treatment Technologies: Evidence from Six Indian Cities

International Journal for Research in Applied Science and Engineering Technology 2025 Score: 48 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Manish Bhupatsinh Sisodiya

Summary

Researchers monitored pharmaceuticals, PFAS, and microplastics across six major Indian urban-river systems and assessed seasonal dynamics and treatment efficiency at wastewater plants, finding that conventional treatment largely fails to remove these emerging contaminants.

Study Type Environmental

Emerging contaminants (ECs)—including pharmaceuticals, per- and polyfluoroalkyl substances (PFAS), and microplastics—pose significant risks to aquatic ecosystems and public health due to their persistence, bioactivity at trace levels, and resistance to conventional wastewater treatment processes. This study investigates the occurrence, seasonal dynamics, and treatment efficiency of selected ECs across six major Indian urban-river systems: Varanasi (Ganga), Delhi (Yamuna), Indore (Kahn), Kolkata (Hooghly), Nashik (Godavari), and Thiruvananthapuram (Killi River). Water samples were collected during pre-monsoon, monsoon, and post-monsoon seasons from four strategic points in each city, including upstream reference sites and downstream effluent receptors. Quantitative analysis was performed using LC-MS/MS for pharmaceuticals and PFAS, and FTIR spectroscopy for microplastic polymers. Results revealed widespread presence of ciprofloxacin (1.6–3.2 µg/L), diclofenac (0.8–1.6 µg/L), PFOS (92–145 ng/L), and microplastics (145–240 particles/L), with higher loads in densely urbanized areas. Seasonal trends indicated dilution during monsoon and contaminant mobilization post-monsoon. Bench-scale treatment trials using coagulation, UV/H₂O₂, activated carbon adsorption, and nanofiltration showed variable removal efficiencies, with nanofiltration achieving the highest (>90%) across all EC classes. Principal Component Analysis (PCA) distinguished high-risk zones based on EC clustering and hydrological influence. The findings underscore the urgent need for EC-inclusive regulatory frameworks, decentralized treatment upgrades, and seasonally adaptive monitoring protocols in India. This study provides a foundational dataset and a scalable methodology for future EC management and policy development.

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