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Pharmaceutical Active Compounds Contamination and Seasonal-Based Ecotoxicity Assessment of the Yamuna River for the Delhi stretch

Alsubih Majed, Khan Roohul Abad

Rocznik Ochrona Środowiska

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2024

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Tom 26

587--602

EN

Yamuna River is the only river in Delhi. This results in heavy reliance on Yamuna to meet Delhi Water demands. This has prompted several research works covering physicochemical, biological, heavy metal concentration, emerging pollutant occurrence, and their risk assessment. This study investigated occurrence, seasonal variation (pre-monsoon, monsoon, and post-monsoon), and risk assessment posed by 7 PhACs at five sampling locations along a 22 km stretch of Yamuna River in Delhi. The samples were collected and analysed in pre-monsoon, monsoon, and post-monsoon seasons. The seven PhACs, comprised of 2 antibiotics (Ciprofloxacin; CIP, sulfamethoxazole; SMZ), 2 NSAIDs (Paracetamol; PCM, Ketoprofen; KPF), 1 anxiety control (Lorazepam, LOR), 1 anticonvulsant (Carbamazepine; CBZ) and 1 statin (Fluvastatin; FUT). The PhACs range of occurrence across three seasons was PCM 75-589 ng L-1, KPF 31-238 ng L-1, CBZ 11-192 ng L-1, LOR 62-462 ng L-1, CIP 48-192 ng L-1, SMZ 192-1534 ng L-1, and FUT 0-421 ng L-1. The seasonal occurrence was in the order of post-monsoon> pre-monsoon> monsoon. PCM, CBZ FUT posed a negligible ecotoxicological risk, LOR posed a low-medium risk, and ketoprofen, ciprofloxacin, and sulfamethoxazole posed high risks. Based on the risk index, all seasons have high ecological risk at every sample point. Discharges of untreated sewage and insufficient and inefficient treated wastewater are the primary contributors of PhACs in the Yamuna River. This study concludes that existing WWTPs need drastic upgrades. Policies and measures should also be developed to prevent untreated wastewater from reaching the Yamuna River. This necessitates further studies to investigate processes suitable for installing and treating wastewater along the longitudinal section of the drain and assess their technical feasibility.

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Performance Evaluation of Horizontal Flow Constructed Wetland for Removal of Pharmaceuticals from Synthetic Wastewater

Mumtaj Zeba Ali, Khan Abdul Rahman, Alsubih Majed, Khan Saimah

Rocznik Ochrona Środowiska

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2024

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Tom 26

322--334

EN

The removal efficiency of pharmaceutical compounds in wastewater treatment can be significantly influenced by seasonal variations and the presence of vegetation. This study evaluates the removal efficiencies of five pharmaceutical compounds – Cefadroxil (CFL), Ciprofloxacin (CIP), Cefpodoxime (CFD), Atenolol (ATN) and Avil-25 (AVL) – in non-planted (CW2) and planted (CW1) constructed wetlands across various parameters including Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), Alkalinity, Nitrate, and Phosphate during winter and summer seasons. Results indicate that CW1 consistently outperforms CW2 in all parameters and seasons. For example, CW1 achieved 54.28% BOD removal for CFL in winter compared to CW2's 39.67%, with summer values reaching 79.6% and 69.7%, respectively. The superior performance of CW1 was also observed for COD and other parameters, with phosphate removal reaching 94% in summer. The results of HPLC analysis indicated that CW1 showed better removal efficiencies of Cefadroxil (56.94%), Ciprofloxacin (90%), and Avil-25 (99.7%) than CW2. Even though Cefpodoxime showed low removal efficiency in both systems, CW1 still performed slightly better (13.99% vs. 0.7%). Atenolol removal was particularly notable in CW1 (93.79%), significantly outperforming CW2. Hazard quotient assessments revealed lower risks associated with pharmaceutical residues in CW1. For example, Ciprofloxacin's hazard quotient was reduced from 16% in CW2 to 10% in CW1, underscoring the effectiveness of vegetation in mitigating environmental risks. Atenolol showed a significant hazard quotient reduction from 2% in CW2 to less than 0.5% in CW1, while Avil-25's hazard quotient was negligible in CW1 compared to 4% in CW2. It was also concluded that vegetation positively influenced the treatment efficacy of constructed wetlands for pharmaceuticals with reduced eco-toxicity and the associated risks.

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Evaluation of Sulphur Dioxide Hourly Prediction Using Long Short-term Memory for Summer and Winter Season

Bennis Mohammed, Mohamed Youssfi, El Morabet Rachida, Alsubih Majed, Prayanagat Muneer, Khan Roohul Abad

Rocznik Ochrona Środowiska

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2024

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Tom 26

313--321

EN

Increasing air pollution has necessitated the prediction of pollutants over time. Deterministic, statistical, and machine-learning methods have been adopted to predict and forecast pollutant levels. It aids in planning and adopting measures to overcome the adverse effects of air pollution. This study employs long short-term memory (LSTM). This study used the hourly data from a meteorological station in a low-town area, Mohammedia City, Morocco. The model prediction accuracy was evaluated based on hourly, weekly, and seasonal (summer and winter) readings for the summer and winter of 2019, 2020 and 2021. Root mean square error (RMSE), mean absolute error (MAE) and mean arctangent absolute percentage error (MAAPE) were calculated to evaluate the accuracy of the developed LSTM model. The MAE value of 0.026 was observed to be less in winter than 0.029 during summer in 2019. Also, it was observed that MAE values decreased from Year 2019-2021, indicating increased prediction accuracy. MAAPE also observed a similar trend. However, RMSE values indicated the opposite for 2019 and 2020; in 2021, the RMSE value was 0.21 for summer and 0.14 for winter for hourly readings. Based on the error calculation, the study found weekly hourly readings were the most accurate for predicting SO2 concentration. Also, the LSTM model was more accurate in predicting winter SO2 concentration than in the summer season. Further studies must incorporate local incidences affecting the SO2 concentration into the LSTM model to increase its accuracy.