Regional disparities in PPCPs contamination of urban wastewater treatment plants: Unveiling influential factors and ecological effects.

Summary

An extensive literature-based dataset of PPCPs in WWTPs across China was analyzed using correlation and four ML algorithms. Random forest models reliably predicted PPCPs concentrations and highlighted service population, treatment capacity, and economic development as key drivers. Ecological risk analysis flagged antibiotics such as norfloxacin and ofloxacin as high-risk to algae.

Key Findings

• Service population, treatment capacity, and economic development are major drivers of PPCPs emissions from WWTPs.
• Random forest models provided reliable predictions of PPCPs concentrations across regions.
• Antibiotics such as norfloxacin and ofloxacin pose high ecological risks to algae.

Clinical Implications

Informs public health and regulatory strategies to mitigate PPCPs exposure from wastewater, including prioritizing high-risk compounds and tailoring interventions by service population and treatment capacity.

Limitations

• Literature-derived data may be heterogeneous with reporting biases
• Not a PRISMA-registered systematic review; lacks standardized bias assessment

Future Directions

Prospective monitoring with harmonized protocols; extend ML models to integrate real-time plant operational data; translate findings into region-specific regulatory thresholds.