Investigation of bacterial community dynamics across different time scales is important for understanding how environmental conditions drive community change over time. Bacterioplankton from the surface waters of a subtropical urban reservoir in southeast China were analyzed through high-frequency sampling over 13 months to compare patterns and ecological processes between short (0‒8 weeks), medium (9‒24 weeks) and long (25‒53 weeks) time intervals. We classified the bacterial community into different subcommunities: abundant taxa (AT); conditionally rare taxa (CRT); rare taxa (RT). CRT contributed > 65% of the alpha-diversity, and temporal change of beta-diversities was more pronounced for AT and CRT than RT. The bacterial community exhibited a directional change in the short- and medium-time intervals and a convergent dynamic during the long-time interval due to a seasonal cycle. Cyanobacteria exhibited a strong succession pattern than other phyla. CRT accounted for > 76% of the network nodes in three stations. The bacteria–environment relationship and deterministic processes were stronger for large sample size at station G (n = 116) than small sample size at stations C (n = 12) and L (n = 22). These findings suggest that a high-frequency sampling approach can provide a better understanding on the time scales at which bacterioplankton can change fast between being abundant or rare, thus providing the facts about environmental factors driving microbial community dynamics. Patterns and processes in alpha- and beta-diversities and community assembly of bacterioplankton differ among different time intervals (short-, medium- and long-time intervals) and different subcommunities (abundant, conditionally rare and rare taxa) in a subtropical urban reservoir, demonstrating the importance of temporal scale and high-frequency sampling in microbial community ecology.

Urban water, defined as water not used for agriculture or to support natural ecosystems, is increasingly impacted by anthropogenic pollution. Among the key concerns are emerging contaminants (ECs), a diverse group of largely unregulated chemical compounds that pose growing threats to both water and the life it supports. This review critically examines the challenges associated with the presence of ECs in urban water through two complementary approaches that together offer both scientific and policy-oriented insights. The first approach focuses on evaluating the difficulties in classifying, characterizing, detecting, monitoring, enforcing policies, and assessing the risks of ECs. The second approach focuses on assessing whether current efforts in research, public awareness, regulation, treatment, recycling, and international collaboration align with the United Nations Sustainable Development Goals (SDGs), particularly SDG 6 (clean water and sanitation), SDG 11 (sustainable cities and communities), and SDG 12 (responsible consumption and production). Current efforts to address the challenges posed by ECs and to achieve SDG targets remain insufficient, particularly in the areas of treatment and recycling. Globally, only 56% of household wastewater is treated safely, and industrial wastewater treatment in low-income countries remains severely lacking, with coverage under 30%. Globally, the effective management of ECs is hindered by outdated and inadequate treatment infrastructure, low recycling rates, and the technical complexity of handling multi-contaminant waste streams. In developing regions, these challenges are compounded by weak regulatory enforcement and limited public awareness. To effectively address ECs in urban water and fully meet the SDG targets, more integrated and globally coordinated efforts are necessary.

In the analysis of polystyrene nanoplastics (PSNs), a nonpolar polymer (NP), using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), silver salts were used as cationization reagents and simultaneously brought the potential problems of silver clusters that interfered with the PSN signal of MS. To detect PSNs, silver trifluoroacetate (AgTFA) and silver nitrate (AgNO₃) were mixed with five polar matrices, namely 2-(4-hydroxyphenylazo) benzoic acid (HABA), dithranol (DI), sinapic acid (SA), trans-3-indoleacrylic acid (IAA), and 2,5-dihydroxybenzoic acid (DHB), and three nonpolar matrices, namely pyrene (PRN), anthracene (ATH) and acenaphthene (ACTH). The results showed that silver salt cluster ions were detected in the range of m/z 1000–4000. Five polar matrices with silver salts produced silver clusters, which interfered with the signals in the mass spectrum of PSNs, but the combination of these matrices with copper II chloride (CuCl₂) salt did not produce copper-related clusters. However, the use of nonpolar matrices such as PRN, ATH or ACTH significantly decreased the signals of silver salt cluster ions, and this alteration of matrix types is considered a promising optimization approach for silver cluster ions. The nonpolar matrix conditions were optimized without producing silver cluster ions and the optimal detection conditions were found to be under nonpolar matrices (e.g., pyrene) with silver salts (e.g., AgTFA). The results suggest that when polar matrices, such as HABA, DI, SA, IAA, and DHB, are combined with silver salts in MALDI-TOF-MS analysis, silver-related clusters are detected in the range of m/z 1000–4000. Inhibition of the production of silver cluster ions can be achieved by the use of a nonpolar matrix (e.g., PRN) or polar matrix (e.g., DHB) with copper salts.