← Volver a resultados
Ficha bibliográfica · Consulta y acceso
Artículo

Modeling human-use antibiotics pollution in Chinese Rivers: A multi-scale analysis of drivers, pathways, and hotspots

Long Chen et al · Elsevier · 2026

Acceso abierto disponible
Lectura rápida. Revisá los datos básicos del recurso y luego accedé al contenido desde el botón principal. En esta ficha solo se muestra la información necesaria para identificar la obra, citarla y abrirla.

Acceso al recurso

Entrá al contenido desde la opción principal o elegí otra fuente disponible.

Acceso principal

Acceso abierto disponible

Recurso identificado como acceso abierto, sin confirmar automáticamente si es texto completo directo.
Abrir recurso

Resumen

Descripción general del contenido del recurso.

Emissions of human-use antibiotics in China pose a significant threat to aquatic ecosystems and accelerate the spread of antimicrobial resistance. Existing assessments lack the facility-level resolution required for effective policy-making and targeted mitigation. This study aims to enhance the understanding of the spatial distribution of human-use antibiotic emissions to water systems, pathways, risks, and associated mitigation strategies in China. We developed SEAAL-China to quantify emissions of 19 major antibiotics from sewered and unsewered populations across more than 10,000 wastewater treatment plants (WWTPs). The national analysis of the removal efficiencies showed significant differences among treatment technologies, ranging from approximately 30–90%. Additionally, over half (57%) of China’s WWTPs employ moderately effective technologies (removal rate <60%). We modeled a total of 3741 t of human-use antibiotic emissions to water systems in 2020, with 41% of the unsewered population accounting for more than half of the total. This highlights the need to expand basic sanitation infrastructure in rural and peri-urban areas to address the sanitation deficit. The emission hotspots are distributed in Guangdong, Shandong, and Henan, primarily driven by factors such as regional GDP and the imbalance in healthcare infrastructure. These areas cover 12% of the country’s area and account for more than half of the calculated antibiotic emissions, suggesting that management should prioritize upgrading treatment technologies in hotspot areas to close the efficacy gap. A further risk assessment of antibiotic resistance selection revealed that fluoroquinolones are the dominant class with co-occurring emission and risk hotspots (630 dual-hotspot counties, 21.8% of the national total). Collectively, the above findings may help to inform both region-specific and compound-specific management strategies for human-use antibiotic pollution.

Cómo citar

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

al, L. C. E. (2026). Modeling human-use antibiotics pollution in Chinese Rivers: A multi-scale analysis of drivers, pathways, and hotspots. https://doi.org/10.1016/j.ecoenv.2026.120138

MLA

al, Long Chen et. "Modeling human-use antibiotics pollution in Chinese Rivers: A multi-scale analysis of drivers, pathways, and hotspots." 2026. https://doi.org/10.1016/j.ecoenv.2026.120138.

Chicago

al, Long Chen et. 2026. "Modeling human-use antibiotics pollution in Chinese Rivers: A multi-scale analysis of drivers, pathways, and hotspots.". https://doi.org/10.1016/j.ecoenv.2026.120138.

Harvard

al, L. C. E. 2026, Modeling human-use antibiotics pollution in Chinese Rivers: A multi-scale analysis of drivers, pathways, and hotspots, Elsevier, available at: https://doi.org/10.1016/j.ecoenv.2026.120138 [Accessed 28 Jun. 2026].

Compartir e imprimir

Guardá la ficha, copiá su enlace permanente o imprimila como PDF.

Exportar referencia

Si usás un gestor bibliográfico, podés exportar el registro en los formatos más comunes.

Detalles del recurso

Información bibliográfica útil para confirmar que se trata del material correcto.

Título
Modeling human-use antibiotics pollution in Chinese Rivers: A multi-scale analysis of drivers, pathways, and hotspots
Autor / colaboradores
Long Chen et al
Editorial
Elsevier
Año de publicación
2026
ISSN
0147-6513
ISSN
0147-6513
Idioma
eng

Materias

Explorá otros recursos relacionados a partir de estas materias.

Copiado