The persistence and ecotoxicity of carbendazim residues pose a potential risk to environmental ecology and human health. Here, a novel and highly efficient carbendazim-degrading bacterium Rhodococcus sp. CX-1, capable of utilizing carbendazim as its sole source of carbon and energy, was isolated from contaminated soil. The biodegradation characteristics and metabolic pathways were studied by mass spectrometry, genomic annotation, and transcriptome analysis. The degradation rate of carbendazim by strain CX-1 was 3.98-9.90 mg/L/h under different conditions, and the optimum degradation conditions were 40 °C and pH 7.0. The addition of carbon sources (glucose, fructose, and sucrose, 100 mg/L) could accelerate carbendazim degradation. HPLC-MS/MS identification suggested that carbendazim is first hydrolyzed into 2-aminobenzimidazole and then to 2-hydroxybenzimidazole, and is ultimately mineralized to carbon dioxide. The genome of strain CX-1 contained 6,511,628 bp nucleotides, 2 linear plasmids, 2 circular plasmids, and 6437 protein coding genes. Genome annotation and transcriptome analysis indicated that carbendazim degradation may be regulated by the degradation genes harbored in the chromosome and in plasmid 2, and two different degradation pathways of carbendazim by imidazole ring cleavage or benzene ring cleavage were predicted. This study provided new insight to reveal the biodegradation mechanism of carbendazim; furthermore, strain CX-1 is a promising bioresource for carbendazim bioremediation.While ecotoxicological impacts of microplastics on aquatic organisms have started to be investigated recently, impacts on ecosystem functions mediated by benthic biota remain largely unknown. We investigated the effect of microplastics on nitrogen removal in freshwater sediments where microorganisms and benthic invertebrates (i.e., chironomid larvae) co-existed. Using microcosm experiments, sediments with and without invertebrate chironomid larvae were exposed to microplastics (polyethylene) at concentrations of 0, 0.1, and 1 wt%. After 28 days of exposure, the addition of microplastics or chironomid larvae promoted the growth of denitrifying and anammox bacteria, leading to increased total nitrogen removal, in both cases. However, in microcosms with chironomid larvae and microplastics co-existing, nitrogen removal was less than the sum of their individual effects, especially at microplastics concentration of 1 wt%, indicating an adverse effect on microbial nitrogen removal mediated by macroinvertebrates. This study reveals that the increasing concentration of microplastics entangled the nitrogen cycling mediated by benthic invertebrates in freshwater ecosystems. These findings highlight the pursuit of a comprehensive understanding of the impacts of microplastics on the functioning in freshwater ecosystems.Global climate change is leading to a significant increase in flooding events in many countries. Current practices to prevent damage to downstream urban areas include allowing the flooding of upstream agricultural land. Earthworms are ecosystem engineers, but their abundances in arable land are already reduced due to pressure from farming practices. If flooding increases on agricultural land, it is important to understand how earthworms will respond to the dual stresses of flooding and agricultural land use. The earthworm populations under three land uses (pasture, field margin, and crops), across two UK fields, were sampled seasonally over an 18-month period in areas of the fields which flood frequently and areas which flood only rarely. Earthworm abundance in the crop and pasture soils and total earthworm biomass in the crop soils was significantly lower in the frequently flooded areas than in the rarely flooded areas. The relative percentage difference in the populations between the rarely and frequently flooded areas was greater in the crop soils (-59.18% abundance, -63.49% biomass) than the pasture soils (-13.39% abundance, -9.66% biomass). In the margin soils, earthworm abundance was significantly greater in the frequently flooded areas (+140.56%), likely due to higher soil organic matter content and lower bulk density resulting in soil conditions more amenable to earthworms. The findings of this study show that earthworm populations already stressed by the activities associated with arable land use are more susceptible to flooding than populations in pasture fields, suggesting that arable earthworm populations are likely to be increasingly at risk with increased flooding.Disinfection byproducts (DBPs) in swimming pool waters are receiving increasing attention because of their toxicity and widespread occurrence. Current studies rarely investigate the formation of DBPs from typical precursors in swimming pools under mixed exposure. They also rarely investigate the formation of carbonaceous DBPs (C-DBPs) and nitrogenous DBPs (N-DBPs) simultaneously. In this study, the formation of C-DBPs and N-DBPs were investigated during chlorination of mixed precursors (i.e., tryptophan, urea, creatinine, and ammonia). The effects of precursors and operation parameters were also investigated. Among the four precursors, tryptophan had the highest DBP formation potential. Urea and ammonia restrained the formation of C-DBPs but promoted the formation of more toxic N-DBPs. C-DBP yields were significantly higher than N-DBP yields under all experimental conditions. Longer reaction time and higher chlorine dosage promoted the formation of C-DBPs, while higher temperature decreased the concentration of N-DBPs. The presence of bromide not only improved the sum yields of DBPs, but also shifted chlorinated DBPs to brominated species.It is widely believed that setting a sensible carbon price can contribute to the mitigation of global warming, so it is particularly major to raise the precision of carbon price prediction. As such it has important implications not only for beautifying the environment but also for promoting the benign development of the carbon trading market in China. However, consideration is given to the high non-determinacy and non-linearity of the carbon price series, a single model cannot meet the prediction accuracy anymore. Since this is the case, this paper puts forward a novel hybrid forecasting model, consisting of the ensemble empirical mode decomposition (EEMD), the linearly decreasing weight particle swarm optimization (LDWPSO), and the wavelet least square support vector machine (wLSSVM). Innovatively, wLSSVM is utilized in the field of carbon price prediction for the first time. see more Firstly, EEMD decomposes the raw carbon price into several stable sub-sequences and a residual. Then, the inputs of each sequence are determined by the partial auto-correlation function (PACF).