Comprehensive Analysis of the Relationship Between Yield Stress and Dewatering Performance in Sludge Conditioning: Insights from Various Treatment Methods

Wen-Hui Liu; Yun-Yan Gao; Yuan-Ping Zeng; Hao Zhang; Ping Sun; Hou-Feng Wang; Raymond Jianxiong Zeng

doi:10.1016/j.chemosphere.2024.143377

Comprehensive Analysis of the Relationship Between Yield Stress and Dewatering Performance in Sludge Conditioning: Insights from Various Treatment Methods

Chemosphere. 2024 Sep 19:143377. doi: 10.1016/j.chemosphere.2024.143377. Online ahead of print.

Authors

Wen-Hui Liu¹, Yun-Yan Gao¹, Yuan-Ping Zeng¹, Hao Zhang¹, Ping Sun¹, Hou-Feng Wang², Raymond Jianxiong Zeng¹

Affiliations

¹ Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China; Center of Wastewater Resource Reuse, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China.
² Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China; Center of Wastewater Resource Reuse, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China. Electronic address: wanghf@mail.ustc.edu.cn.

PMID: 39306100
DOI: 10.1016/j.chemosphere.2024.143377

Abstract

Understanding the relationship between sludge yield stress (σ_y) and dewatering performance is essential for optimizing sludge conditioning processes. This study systematically investigates the effects of various conditioning methods-including thermal hydrolysis (TH), freezing/thawing (FT), anaerobic digestion (AD), polyaluminum chloride (PAC), polyacrylamide (PAM), and Fenton treatment (Fenton)-on sludge yield stress and its correlation with dewatering efficiency. Using linear regression, partial least squares regression (PLSR), and correlation heatmap analyses, we reveal significant variations in the correlation between σ_y and dewatering indexes, including moisture content ( Mc), capillary suction time (CST), and bound water proportion (Wb/Wt), depending on the conditioning method and intensity. Under FT and PAM conditioning, σ_y shows a strong negative linear correlation with dewatering performance, with Pearson's r values exceeding -0.880, indicating that a decrease in σ_y corresponds to improved dewatering efficiency. Conversely, AD conditioning exhibits a positive linear correlation, with r values up to 0.993, suggesting that an increase in σ_y correlates with reduced dewatering efficiency. For TH, PAC, and Fenton treatments, the correlation between σ_y and dewatering metrics is highly sensitive to changes in treatment intensity. In the PLSR analysis, the VIP values, which quantify the importance of each predictor variable, indicate that Wb/Wt in TH conditioning (VIP = 1.649) and CST in PAC (VIP = 1.309) and Fenton (VIP = 1.299) conditioning strongly influence σ_y. This study highlights the significant impact of conditioning methods and intensities on the correlation between σ_y and dewatering performance. While σ_y provides valuable insights as a predictive indicator, its predictive power is limited in more complex conditioning scenarios. Therefore, optimizing conditioning intensity and incorporating multiple rheological parameters are essential for achieving superior sludge dewatering outcomes.

Keywords: Conditioning methods; Correlation analysis; Dewatering performance; Partial Least Squares Regression (PLSR); Sludge treatment; Sludge yield stress.