Diminished storage capacity of ponds caused by sedimentation weakens their nitrogen removal efficiency.

Though their small size, ponds play a disproportionately crucial role in eliminating nitrogen (N) transporting to downstream freshwaters. As significant water infrastructures, ponds are non-sustainable due to loss of storage capacity resulting from sedimentation. However, the effects of pond sedimentation on N removal is widely neglected in landscape N processing. The NUFER (Nutrient flows in Food chains, Environment and Resources use) model was employed to estimate N runoff from 1960 to 2018. We reconstructed the dynamic of number and storing capacity of about 14 million ponds due to construction and sedimentation from 1960 to 2018, projecting these trends into the year 2060. Our approach incorporated first-order kinetic reactions, including water residence time (HRT), to estimate N removal of ponds, utilizing data 6 monitoring ponds and 81 ponds from literature studies. Our analysis reveals a fourteen-fold increase in N runoff over the past six decades, rising from 0.8 Mt N in 1960 to 11.4 Mt N in 2018. Due to the initial rapid expansion of ponds, N removal by ponds increased from 6.4 % in 1960 to 13.6 % in 1990. Sedimentation is prevalent in ponds, particularly in small ponds with a sedimentation accumulation rate of 2.96 cm yr-1. Pond sedimentation, which reduces HRT, resulted in a decrease in pond N removal percentage to 11.2 % in 2018 and a projected 7.4 % by the year 2060, assuming similar sediment accumulation rates persist in the future. Overall, our findings underscore the non-negligible role of ponds as landscape nodes in N cycling. Urgent mitigation measures are needed to extend the lifetime of existing ponds and sustain their critical role in water quality management.

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.

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.