The recovery of C, N, and P elements by sludge biorefinery potentially reduces operation costs and increases the extra benefits. Herein, we analyzed the elemental stoichiometry of C, N, and P and functional microbiome involved in enzymatic anaerobic fermentation. Enzymatic hydrolysis was observed to increase the release of C, N, and P into the sludge supernatants by 21.8 %–26.3 %. Metatranscriptome analysis indicated that enzymatic pretreatment enhanced the metabolism of the organic carbon degradation, ammonium conversion, and P solubilization in subsequent fermentation. Specifically, enzymatic pretreatment enhanced endogenous carbon hydrolase activity by 48.4 %–72.7 % and upregulated intra-C metabolic pathways, such as glycolysis and pyruvate metabolism. Ammonium transport and conversion were significantly increased by 4–6 fold, stimulating the synthesis of glutamine and endogenous amino acids. Additionally, enzymatic hydrolysis promoted phosphatase secretion and enhanced bacterial P uptake. These effects improved the recovery of C, N, and P as dentification carbon source and struvite by 13.7 %–41.8 % and the dry sludge production was reduced by 24.3 %–28.1 %. Life cycle assessment (LCA) indicated the shift of CO₂ emissions from net positive to net negative levels as compared to the conventional A²/O process. This study offers valuable insights into the redistribution and metabolism of various elements involved in the enzymatic anaerobic fermentation, and proposes the potential strategy to recovery C, N, and P from sewage via sludge biorefinery.

Smart and personalized ventilation systems have been demonstrated with high performance in creating a healthy and energy-efficient indoor environment, but they have been rarely comprehensively summarized and explored in previous studies. With the progressive development of various terminal devices and control technologies, personalized ventilation based on intelligent control is potentially a promising way to achieve efficient control and energy savings in human micro-environments. This study comprehensively summarizes and analyzes the recent studies and common utilization forms of smart ventilation and PV systems that are based on CO₂ concentration control, to pave path and provide some guidelines for their integration application for reducing energy consumption and improving indoor thermal comfort. Research shows that the combination of personalized ventilation and smart ventilation is an essential development for ventilation systems. Smart ventilation with demand control logic based on CO₂ concentration has been mature enough to effectively improve the effectiveness and comfortable performance of personalized ventilation. However, switching from traditional air conditioning systems to personalized ventilation still requires improved sensors and intelligent control algorithms. In addition, this paper also summarizes the exploratory studies and potential application analysis of machine-learning theories to improve intelligent control of personalized ventilation. To this end, this paper identifies future tendencies for advanced theories, integrated systems, and devices in personalized ventilation systems.