Bacterial communities in biofilters can improve drinking water quality through the biodegradation of dissolved contaminants but also pose potential risks by harboring and shedding microbes into the drinking water distribution system. In this study, pilot-scale granular activated carbon (GAC)-sand and anthracite-sand pilot-scale biofilters were investigated to determine the effects of filter design and operation on the microbiome of the filter media and its relationship to the microbiome in the filter effluent water. Bacterial abundance in the biofilters was relatively stable over time. Bacterial community composition exhibited spatial variation (i.e., with bed depth) and temporal variation linked to water quality changes. Bacterial community composition was significantly affected by the media type (GAC vs anthracite) and backwashing strategy (chloraminated water vs nonchloraminated water). The biofilters reduced bacterial abundance in the water (∼70%) but had only a minor effect on the bacterial community composition in the filtrate. Overall, our results suggest that the bacterial communities growing on biofilters affect filtered water quality primarily through the biotransformation of pollutants and nutrients rather than by altering the microbial community composition of the water as it passes through the filter.Biosynthetic organic matters, such as humus, play important roles in iron and phosphorus cycling in soil and aquatic systems. As an important member of humus, fulvic acid (FA) is ubiquitous in different environmental media, such as water, soil, and sediments. In this study, we fabricated the network among phosphate supply, metabolism pathway of FA, iron reduction, and vivianite recovery at the batch scale. VBIT-12 chemical structure Both the vivianite recovery performance and the content of biosynthetic FA were positively related to the phosphorus dosage. The highest vivianite formation efficiency of 53% was obtained in the Fe/P = 1 batch, accompanied with the maximal iron reduction rate of 2.29 mM·day-1, which was 2.66 times higher than that of the Fe/P = 3 batch. Simultaneously, the highest content of FA was detected in extracellular polymeric substances (EPS) of the Fe/P = 1 batch. Metabolome analysis revealed that FA biosynthesis was mainly relevant to tricarboxylic acid (TCA) cycle, amino acid metabolism, and purine metabolism, with glutamate and aspartate as the precursors. Sufficient phosphate stimulated the FA biosynthesis by modulating the biosynthesis and transformation of glutamate and aspartate. After adding 10 mg L-1 FA in Fe/P = 1 batch, the maximal iron reduction rate increase by 35%, as well as 12% improvement of the vivianite formation efficiency. Transcriptome revealed that FA promotes iron reduction and vivianite recovery by upregulating the expression of metal ion binding-, flagella-, and electron transfer activity-related genes.This study developed an innovative process for the treatment of low-ammonium wastewater in a single-stage bioreactor over 250 days. Partial nitritation-anammox and partial denitritation-anammox (PN/A-PDN/A) processes were combined under aerobic/anoxic operation, and a high nitrogen removal efficiency (94.6%) was obtained at a nitrogen removal rate of 0.54 kg N m-3 d-1 and a chemical oxygen demand to total inorganic nitrogen (COD/TIN) ratio of 0.28. Mass balance analysis identified anammox as the dominant nitrogen removal pathway, achieving 88.3% nitrogen loss. The abundance of anammox bacteria and their bioactivity rapidly increased and were effectively maintained, as indicated by qPCR and bioactivity tests. The PN/A-PDN/A process provided two pathways of nitrite production for anammox, which favored the enrichment of anammox bacteria and stable processing. In addition, the enrichment of anammox bacteria was promoted by selective floc discharge since anammox bacteria are mainly located in granules (relative abundance of 29.64 ± 7.89%). Competitive organisms (including heterotrophic bacteria and nitrite oxidizing bacteria), enriched in flocs, were washed out. Overall, these findings confirmed anammox, sequentially combined with PN and PDN via aerobic/anoxic strategy, as a promising alternative for mainstream anammox.Food supply has been the central issue of human development for millennia and has become increasingly critical in an urbanizing world. However, the environmental footprints and associated mitigation strategies of food consumption have rarely been comprehensively characterized at urban or regional scales. Here, we analyze the water, carbon, reactive nitrogen, and phosphorus footprints of food consumption in Chinese urban regions and demonstrate how such information can help to formulate tailored mitigation strategies. The results show that in three of the largest urban regions of China, 44-93% of the four footprints are embodied in transboundary food supply. The size of the footprints and the effectiveness of mitigation measures in food supply chain vary across the environmental footprints and urban regions. However, targeting agriculture and food processing sectors in Hebei, Shandong, and Henan provinces can reduce these footprints by up to 47%. Our findings show that the analysis of the environmental footprints along the transboundary food supply chains could inform individualized and effective mitigation targets and strategies.Filtration via a porous medium is a ubiquitous process where high-fidelity physical models are needed. The classical cell model oversimplifies the filtration medium and results in biased and inaccurate predictions of the filter performance. This paper presents the discrete framework of a polydisperse cell model that can incorporate any measured pore size distribution. A new equation connecting the polydisperse cell efficiencies and the medium efficiency is derived from first principles. For ceramic filters, the discrete model demonstrates a generic prediction capability of the filtration efficiency with a root-mean-squared difference of 5.4%, while the counterpart of the classical cell model is 26.4%. In addition, the discrete model eliminates the biased predictions of the classical cell model on sub-100 nm particles.