Traditional ecotoxicology primarily investigates pollutant toxicity through physiological, biochemical, and single-molecular indicators. However, the limited data obtained through this approach constrain its application in the mechanistic analysis of pollutant toxicity. Omics technologies have emerged as a major research focus in recent years, enabling the comprehensive and accurate analysis of biomolecular-level changes. The integration of multi-omics technologies can holistically reveal the molecular toxicity mechanisms of pollutants, representing a primary emphasis in current toxicological research. This paper introduces the fundamental concepts of genomics, transcriptomics, proteomics, and metabolomics, while reviewing recent advancements in integrated omics approaches within aquatic toxicology. Furthermore, it provides a reference framework for the implementation of multi-omics strategies in ecotoxicological investigations. While multi-omics integration enables the unprecedented reconstruction of pollutant-induced molecular cascades and earlier biomarker discovery (notably through microbiome–metabolome linkages), its full potential requires experimental designs, machine learning-enhanced data integration, and validation against traditional toxicological endpoints within environmentally relevant models.

As important parameters in the characterization of aerobic granulation, the shape and average diameter were related to substrates. The previous studies disclosed that the morphology change in aerobic granules was the result of growth and the relatively strong hydrodynamic shear force. No further exploration of the size distribution of the aerobic granules has been conducted. To better understand the impact of toxic compounds on aerobic granules’ growth during their formation, the properties of aerobic granules were traced over 81 days in 3 sequencing batch reactors fed with acetate and berberine wastewater, especially the particle size and size distribution. The results showed that the aerobic granules were cultivated by the simulated acetate wastewater (R1), simulated berberine wastewater (R2), and effluent from an anaerobic baffled reactor (ABR) reactor which was fed with industrial berberine wastewater (R3). The reactors exhibited different COD removal efficiencies, and the MLSS and MLVSS values affected by the different substrates which were in an order of R1 > R2 > R3. However, the SVI and SOUR, which were affected by several factors, showed more complicated results. The aerobic granules had the lowest microbial activity (SOUR), while the aerobic granules in R3 had the lowest settling ability among the three kinds of granules. For the three reactors with different influent compositions, the aerobic granulation process displayed a three-stage process separately. Compared with the granules fed with berberine wastewater, the granules fed with acetate in a stable operation period showed more independence from other periods.The size distribution was affected by substrates. The aerobic granules with a range of 0.3–1.0 µm occupied 77.0%, 67.0%, and 35.7% of the volume for R1, R2, and R3, respectively. The biomass less than 0.3 µm occupied 59.1% volume in R3. The components of the substrate had a great influence on the growth of aerobic granules, not only on the diameter but also on the size distribution.

Total ammonia nitrogen (TAN) is a ubiquitous and critical pollutant in global surface waters. In China, regulatory oversight largely relies on static standard limits, often overlooking the influence of environmental factors on ammonia toxicity. Based on large-scale monitoring data from seven major river basins across China from 2021 to 2024, this study employed pH- and temperature-dependent Local Water Quality Criteria (LWQC) to identify the spatiotemporal decoupling between TAN concentrations and Risk Quotients (RQs). The results reveal a “double-peak” seasonal pattern in TAN concentrations nationwide, namely a primary peak in winter (December to February) and a secondary peak in summer (June to August), driven by low flow during the dry season and rainfall-induced non-point source runoff, respectively. Crucially, the study confirms a significant “concentration-risk paradox”: while TAN concentrations are highest in winter, ecological risk remains at an annual low due to the protective effect of low temperatures on toxicity. Conversely, despite lower total concentrations in summer, high temperatures and elevated pH trigger a sharp decline in LWQC and a surge in the proportion of highly toxic un-ionized ammonia (NH₃), marking summer as the peak period for ecological risk. Comparative analysis indicates that approximately 61.43% of river sections meeting the current Grade III water quality standards remain in a high-risk state. This underscores the inadequacy of static standards in providing sufficient protection during sensitive seasons. We suggest that water environmental management should shift from “concentration-based compliance” to “risk-based management,” implementing differentiated TAN control strategies specifically targeting the sensitive summer window.