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	Synergistic effect of organic matter-floc size-bound water and multifactorial quantitative model of optimal reagent demand in sewage sludge conditioning process prior to dewatering
	Tan, Xun1,2; Zeng, Sidong1,2; Chen, Zhong1,2; Lv, Mingquan1,2; Tang, Xiaoya1,2; He, Xingxing3; Chen, Yijun4; Wan, Yong4; Zhang, Jingping5
	2024-03-01
摘要	The high amount of densely hydrated organic substance present in sewage sludge impedes its filterability, thus restricting sludge disposal. Although chemical conditioning can facilitate filtration, the diverse sludge properties complicate the quantitative control of conditioning process. Investigating how to accurately quantify the optimal reagent demand (ORD) based on the critical physicochemical properties of the target sludge is an effective way to address the current issue. This study focused on the sewage and stockpiled sludge with varying properties, and their ORD under different chemical conditioning. The results showed that organic content, floc size, and bound water synergistically influenced conditioning process. The quantitative models were established between their coupling indicators and ORD, with coupling indicators including the ratio of organic content to floc size, the ratio of flow viscosity to floc size, and the ratio of the product of organic content and bound water to floc size. The linear correlation of the coupling indicator with ORD was higher than that of the traditional single -factor indicator. Furthermore, the inherent filterability of the sludge was somewhat separate from the adjustability of its filtration. A "dual-system" impact model was proposed to characterized the conditioning and filtration processes. These results provide theoretical guidance for the quantitative regulation of conditioning and filtration processes of sludge with complex characteristics.
关键词	Sewage and stockpiled sludge Conditioning Filtration Multifactorial coupling Quantitative mode
DOI	10.1016/j.watres.2024.121108
发表期刊	WATER RESEARCH
ISSN	0043-1354
卷号	251页码:13
通讯作者	Zeng, Sidong(zengsidong@cigit.ac.cn)
收录类别	SCI
WOS记录号	WOS:001169706900001
语种	en