Assessment of sustainable development based on source apportionment of hazardous elements and cost-effectiveness analysis in a watershed hosting two world-class industrial clusters

Industrial agglomeration in watersheds poses a significant challenge for accurately identifying pollution sources and effective environmental management. This study focused on a representative watershed hosting two world‑leading industrial centers: textile dyeing and printing, and e-waste recycling. Surface sediments were collected along the mainstream and tributaries, namely Beigang, Old Lianjiang, Chendian, Jinxi, Qiufeng, Xiashan, and Zhonggang rivers. Concentrations of hazardous elements (e.g., Cu, Sb, Cd, Pb, Hg, As) were quantified. The potential ecological risk index (RI) indicated that over 50 % of sampling sites posed high or extreme ecological risk, primarily associated with zones of intensive e-waste recycling and textile industrial discharge. We employed a combination of models with different principles to accurately apportion sources, including positive matrix factorization (PMF), principal component analysis (PCA), and correlation analysis. Results revealed that anthropogenic sources—e-waste recycling activities (characterized by Cu), textile wastewater (characterized by Sb), and urban non-point source pollution—were the dominant contributors, accounting for up to 70 % of the pollutant loads. The source profiles were further validated by comparing them with typical sludge samples from industrial facilities, confirming the distinct chemical fingerprints of each source. Notably, a cost-effectiveness analysis underscored the unsustainability of this development model: 0.48 USD per 1 USD of industrial added value were generated in latent environmental debt, primarily from ecosystem service degradation and remediation costs. This study provides a robust framework for source apportionment in complex industrial basins. It highlights the urgent need for targeted pollution control strategies in high-risk industries to mitigate environmental and economic losses. • Hg, Cd, Sb, Cu and Sn pose the primary ecological risks. • Up to 70 % of ecological risk is attributed to the textile and e-waste industries. • Validates source profiles by empirical comparison with industrial sludge samples. • Quantifies a latent environmental debt of 0.48 USD per 1 USD of industrial added value.