Circular approaches to industrial wastewater and sludge management for minimizing eco toxicological risks: A regional analysis of Shandong Province

Industrial wastewater and sewage sludge management in rapidly industrializing regions faces growing pressure from stringent environmental standards and public concern about toxic contaminants. This article examines how circular approaches to wastewater and sludge management can reduce ecotoxicological risks in major industrial clusters of Shandong Province in eastern China. The analysis combines regional material flow data, plant-level monitoring of priority pollutants and life cycle oriented indicators for alternative treatment and reuse routes. Three management archetypes are compared: conventional linear treatment and disposal, energy and nutrient recovery with controlled land application and advanced product-based recycling of dewatered sludge into construction materials. Ecotoxicological risk indicators are derived from measured concentrations of metals and organic micropollutants in effluents, biosolids and receiving waters. Results show that well-designed circular strategies substantially reduce ecotoxicological risk while also lowering climate and resource footprints, but they require robust monitoring, strict quality standards and careful siting to avoid risk transfer between environmental compartments.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-06-16
DOI
https://doi.org/10.1051/e3sconf/202671903003/pdf
Primary Topic
Sustainable Industrial Ecology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Circular approaches to industrial wastewater and sludge management for minimizing eco toxicological risks: A regional analysis of Shandong Province

Lyudmila Сhesnyukova, T. B. Baranovskaya, Maria Vilacheva, Burkhon Boltaev et al.
Springer Link (Chiba Institute of Technology)
Sustainable Industrial Ecology
article

Circular approaches to industrial wastewater and sludge management for minimizing eco toxicological risks: A regional analysis of Shandong Province

Lyudmila Сhesnyukova, T. B. Baranovskaya, Maria Vilacheva, Burkhon Boltaev, Sun Qiming
article en

Abstract

Industrial wastewater and sewage sludge management in rapidly industrializing regions faces growing pressure from stringent environmental standards and public concern about toxic contaminants. This article examines how circular approaches to wastewater and sludge management can reduce ecotoxicological risks in major industrial clusters of Shandong Province in eastern China. The analysis combines regional material flow data, plant-level monitoring of priority pollutants and life cycle oriented indicators for alternative treatment and reuse routes. Three management archetypes are compared: conventional linear treatment and disposal, energy and nutrient recovery with controlled land application and advanced product-based recycling of dewatered sludge into construction materials. Ecotoxicological risk indicators are derived from measured concentrations of metals and organic micropollutants in effluents, biosolids and receiving waters. Results show that well-designed circular strategies substantially reduce ecotoxicological risk while also lowering climate and resource footprints, but they require robust monitoring, strict quality standards and careful siting to avoid risk transfer between environmental compartments.

Springer Link (Chiba Institute of Technology)
Clean water and sanitation
Openalex Percentile: Top 6%
Sustainable Industrial Ecology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.