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<p>Pharmaceutical residues, particularly non-steroidal anti-inflammatory drugs (NSAIDs), are increasingly detected in wastewater systems, especially in water-scarce Mediterranean regions where treated effluents are reused for irrigation. This study investigated the occurrence, removal efficiency, and ecological risk of three widely consumed NSAIDs—paracetamol, diclofenac, and ketoprofen—in five Tunisian wastewater treatment plants (WWTPs) operating under conventional treatment configurations. Influent concentrations ranged from 0.42 to 5.87&#xa0;µg/L for paracetamol, 0.31 to 2.14&#xa0;µg/L for diclofenac, and 0.18 to 1.63&#xa0;µg/L for ketoprofen. Removal efficiencies varied significantly among compounds and stations. Paracetamol exhibited the highest elimination rates, reaching 98.05%, 98.23%, and 99.78% in stations S1, S2, and S4, respectively, reflecting its high biodegradability. In contrast, diclofenac and ketoprofen showed variable and often limited removal (12–76%), depending on site-specific operational conditions. Ecological risk assessment was conducted using ECOSAR v2.2 predictions combined with Risk Quotient (RQ), mixture-based RQmix, and Toxic Unit (TU) approaches. Acute RQ values reached up to 1.62 for diclofenac, while chronic RQs peaked at 7.69, indicating high ecological risk in certain influents and moderate risk in some effluents. Risk classification revealed site-specific variability, with diclofenac presenting the highest concern in short-term exposure scenarios and paracetamol dominating long-term influent risk at specific stations. Mixture risk analysis (RQmix) suggested cumulative effects that may exceed single-compound assessments in selected cases. Principal Component Analysis (PCA) indicated that influent concentration, treatment configuration, and population served influenced removal performance. Overall, the integration of in silico toxicity prediction with mixture-based risk metrics provides a robust framework for screening pharmaceutical pollution in conventional WWTPs under reuse-driven Mediterranean conditions. These findings support improved wastewater management strategies aligned with SDGs 6, 12, and 14.</p> Graphical Abstract <p></p>

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Environmental Risk and Removal Efficiency of NSAIDs in Wastewater Treatment Plants in Sfax, Tunisia

  • 期刊论文

  • 发表日期：

    2026年4月15日

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  • Imen Ben Chabchoubi,
  • Bilel Moslah,
  • Ahmed Wali,
  • Abderazzek Hedhili,
  • Mohamed Ksibi,
  • Olfa Hentati

摘要

Pharmaceutical residues, particularly non-steroidal anti-inflammatory drugs (NSAIDs), are increasingly detected in wastewater systems, especially in water-scarce Mediterranean regions where treated effluents are reused for irrigation. This study investigated the occurrence, removal efficiency, and ecological risk of three widely consumed NSAIDs—paracetamol, diclofenac, and ketoprofen—in five Tunisian wastewater treatment plants (WWTPs) operating under conventional treatment configurations. Influent concentrations ranged from 0.42 to 5.87 µg/L for paracetamol, 0.31 to 2.14 µg/L for diclofenac, and 0.18 to 1.63 µg/L for ketoprofen. Removal efficiencies varied significantly among compounds and stations. Paracetamol exhibited the highest elimination rates, reaching 98.05%, 98.23%, and 99.78% in stations S1, S2, and S4, respectively, reflecting its high biodegradability. In contrast, diclofenac and ketoprofen showed variable and often limited removal (12–76%), depending on site-specific operational conditions. Ecological risk assessment was conducted using ECOSAR v2.2 predictions combined with Risk Quotient (RQ), mixture-based RQmix, and Toxic Unit (TU) approaches. Acute RQ values reached up to 1.62 for diclofenac, while chronic RQs peaked at 7.69, indicating high ecological risk in certain influents and moderate risk in some effluents. Risk classification revealed site-specific variability, with diclofenac presenting the highest concern in short-term exposure scenarios and paracetamol dominating long-term influent risk at specific stations. Mixture risk analysis (RQmix) suggested cumulative effects that may exceed single-compound assessments in selected cases. Principal Component Analysis (PCA) indicated that influent concentration, treatment configuration, and population served influenced removal performance. Overall, the integration of in silico toxicity prediction with mixture-based risk metrics provides a robust framework for screening pharmaceutical pollution in conventional WWTPs under reuse-driven Mediterranean conditions. These findings support improved wastewater management strategies aligned with SDGs 6, 12, and 14.

Graphical Abstract