Wastewater treatment plants (WWTPs) have been regarded as an important source of antibiotic resistance genes (ARGs) in environment, but out of municipal domestic WWTPs, few evidences show how environment is affected by industrial WWTPs. Here we chose Hangzhou Bay (HZB), China as our study area, where land-based municipal and industrial WWTPs discharged their effluent into the bay for decades. We adopted high-throughput metagenomic sequencing to examine the antibiotic resistome of the WWTP effluent and coastal sediment samples. And we proposed a conceptual framework for the assessment of antibiotic resistome risk, and a new bioinformatic pipeline for the evaluation of the potential horizontal gene transfer (HGT) frequency. Our results revealed that the diversity and abundance of ARGs in the WWTP’s effluent were significantly higher than those in the sediment. Furthermore, the antibiotic resistome in the effluent-receiving area (ERA) showed significant difference from that in HZB. For the first time, we identified that industrial WWTP effluent boosted antibiotic resistome risk in coastal sediment. The crucial evidences included: 1) the proportion of ARGs derived from WWTP activated sludge (WA) was higher (14.3 %) and two high-risky polymyxin resistance genes (mcr-4 and mcr-5) were enriched in the industrial effluent receiving area; 2) the HGT potential was higher between resistant microbiome of the industrial effluent and its ERA sediment; and 3) the highest resistome risk was determined in the industrial effluent, and some biocide resistance genes located on high-risky contigs were related to long-term stress of industrial chemicals. These findings highlight the important effects of industrial activities on the development of environmental antimicrobial resistance.
Forecast combination integrates information from various sources by consolidating multiple forecast results from the target time series. Instead of the need to select a single optimal forecasting model, this paper introduces a deep learning ensemble forecasting model based on the Dirichlet process. Initially, the learning rate is sampled with three basis distributions as hyperparameters to convert the infinite mixture into a finite one. All checkpoints are collected to establish a deep learning sub-model pool, and weight adjustment and diversity strategies are developed during the combination process. The main advantage of this method is its ability to generate the required base learners through a single training process, utilizing the decaying strategy to tackle the challenge posed by the stochastic nature of gradient descent in determining the optimal learning rate. To ensure the method’s generalizability and competitiveness, this paper conducts an empirical analysis using the weekly dataset from the M4 competition and explores sensitivity to the number of models to be combined. The results demonstrate that the ensemble model proposed offers substantial improvements in prediction accuracy and stability compared to a single benchmark model.
Flagella and their property would influence the initial attachment of bacteria onto plastics, yet their impacts have not been investigated. In present study, four types of E. coli with or without flagella as well as with normal or sticky flagella were utilized to investigate the effects of flagella and their property on the initial attachment behaviors of bacteria onto six types of plastics in freshwater systems. We found that E. coli with flagella exhibited better initial attachment performance onto all six types of plastics than strain without flagella. Flagella could help bacteria swim near to plastics, pierce the energy barrier, and subsequently attach onto plastics. With stronger adhesive force, sticky flagella could further facilitate bacterial attachment onto plastics. Moreover, flagella especially sticky flagella could help bacteria form more rigid attachment layer on plastics. Even with humic acid in suspensions or in river water, flagellar E. coli showed greater attachment onto plastics than E. coli without flagella. Humic acid might adsorb onto sticky flagella and thus decreased the attachment of bacteria with sticky flagella onto plastics. Obviously, flagella as well as their property would impact the initial attachment of bacteria onto plastics and the subsequent formation of plastisphere in freshwater.
This paper assesses mental health responses to information on environmental risks. We exploit the progressive implementation of a national program in China that introduces more comprehensive air pollution monitoring and provides real-time air-pollution information to the public. The program leads to a sharp increase in public awareness and attention to air pollution issues and results in a large increase in the sensitivity of individual’s mental health to changes in air quality, especially among those with more exposure to pollution information and those more susceptible to mental illnesses. Information of worsening air quality has a direct effect on mental health as a source of stressors and an indirect behavioral effect through reducing outdoor activities and social integration. Our findings shed light on the design and delivery of environmental information disclosure programs, especially for countries with pressing environmental threats.
Peracetic acid (CH3C(O)OOH, PAA)-based heterogeneous advanced oxidation process (AOP) has attacked intensive interests due to production of various reactive species. Herein, Co(OH)2 nanoparticles decorated biochar (Co(OH)2/BC) was fabricated by a simple and controllable method, which was used to degrade tetracycline hydrochloride (TTCH) in water through PAA activation. The results indicated that 100% TTCH (C0 = 10 µmol/L) degradation efficiency was realized within 7 min at pH 7, with a high kinetic rate constant (k1) of 0.64 min−1 by the optimized Co(OH)2/BC. Material characterizations suggested that Co(OH)2 nanoparticle was successfully decorated on biochar, leading to more active sites and electronic structure alteration of biochar, thus greatly promoting the catalytic cleavage of PAA for radicals production. Then, the reactive oxygen species (ROS) quenching experiments and electron paramagnetic resonance (EPR) analysis demonstrated the key species were alkoxyl radicals (R–O•, mainly CH3CO2• and CH3CO3•), HO• and 1O2 in this system. Besides, density functional theory (DFT) calculation on Fukui index further revealed that the vulnerable sites of TTCH and three possible degradation pathways were proposed. This study can provide a new strategy for synthesis functional materials in PAA activation AOPs for removal of antibiotics in water.
Sulfadiazine (SDZ), as a broad-spectrum pharmaceutical antibiotic, has drawn extensive attention owing to its wide application and persistence. Photocatalytic oxidation has been considered as a high-efficiency and environment-friendly technology for degrading organic contaminants. A novel BiOI/UiO-66 p-n heterojunction (BiU-x) was fabricated via the in-situ deposition of p-type BiOI nanoplates on n-type UiO-66 octahedrons with the aid of a controlled precipitation method. The optimizing BiU-9 heterojunction exhibited a remarkably enhanced photocatalytic efficiency in removing SDZ, in which the SDZ (5 mg/L) removal efficiency over BiU-9 (0.5 g/L) reached nearly 100 % within 90 min of visible light irradiation. The influence of some important environmental factors (e.g., photocatalyst dosage, pH, co-existing inorganic anions and real sunlight irradiation) were systematically investigated. Such improvement mechanism should be assigned to the following three factors. Firstly, the introduction of narrow gap semiconductor BiOI effectively improved photo adsorption capacity. Secondly, benefiting by the large specific surface area, the involvement of UiO-66 contributed to boost the surface active sites. Most importantly, an internal electric field at the contact interface between UiO-66 and BiOI accelerated the separation of photo-generated electrons and holes. Furthermore, ·O2− and photo-generated holes were identified as the dominating reactive species accounting for the SDZ removal. The decomposition pathways of SDZ and ecotoxicities of the intermediates were analyzed via combing with LC-MS/MS and T.E.S.T theoretical calculation. This work may provide an alternative way for enhanced photocatalytic performance of MOF-based materials through construction of p-n heterojunction with bismuth-based semiconductors.
In this study, an integrated treatment system was proposed and applied in situ, including detention tank, multistage constructed wetlands (CWs) and wastewater treatment plants (WWTPs), preventing nutrients flowing into Dianchi Lake, in which the treatment performance of multistage CWs were evaluated principally. Results skillfully realized the bypass purification of upstream river at dry reasons, as well as the effective management and treatment of the collected diffuse pollution at rainy reasons. The purified water flowing into water bodies could satisfy the Grade III of environmental quality standards for surface water in China with the average effluent concentrations of COD, NH4+-N, TN and TP decreased to 10 (51.2-72.7%), 0.5 (67.2-83.0%), 1.0 (71.2-79.6%) and 0.15 (72.3-89.4%) mg L-1, respectively. High-throughput sequencing results indicated that the application of poly-3-hydroxybutyrate-cohyroxyvelate-sawdust (PS) blends could enrich norank\_f\_Anaerolineaceae (7.95%) and Bradyrhizobium (10.2%), which were distinct from the dominant genera of Pleurocapsa (13.0%) in gravel -based CWs. Functional genes and metabolism analysis uncovered that the heterotrophic denitrification was the main pathway of nitrogen removal with the abundance of genes encoding TCA cycle, glycolysis and deni-trification process up-regulated. In addition, molecular ecological network (MEN) analysis suggested the deni-trification genes were positively correlated with the predominant microbes in PS-based CWs, favorable for denitrifiers to transfer and utilize electron donors during denitrification process. This study proved that the developed PS blends as carbon supplies in CWs and the proposed integrated treatment system are effective methods for watershed management, providing valuable reference to low-pollution wastewater treatment in practical engineering projects.
Interfacial modulation of catalysts for constructing active sites can greatly promote its catalytic activity, while the mechanism on reactive species production at different interfaces still needs to be revealed. In this study, Zr-S4 active sites were usefully constructed on ZnIn2S4 nanosheets, which effectively modulated the reaction interface and band structure, thus boosting the photocatalytic activity. The optimized material (Zr1.2-ZIS) showed a ∼3-fold kinetic rate constant for photocatalytic degradation of tetracycline compared with the pristine ZnIn2S4. Moreover, TC underwent a different degradation pathway over the modified catalyst due to regulation of reactive species after photo-activation. The Zr-S4 centers were energetically favorable for activating O2 into •O2- and •OH, as a more reactive d-band electron was obtained and the adsorption of •O2- as well as its further conversion into •OH was promoted. Theoretical calculations on Fukui index and toxicity also confirmed the dramatical toxicity reduction during TC degradation by Zr1.2-ZIS.
In the context of China's rapid population aging and internet expansion, this study examines the impact of information and communication technologies on the of older adults’ health. Using the China Health and Retirement Longitudinal Study 2011–2018, we find that internet access improves older adults' self-reported health, mental health, and activities of daily living (ADL). Further investigations provide evidence for several underlying mechanisms, including improving social participation, promoting healthy behaviors, and encouraging intergenerational interactions. Heterogeneity analyses show that disadvantaged groups, such as those with any ADL difficulty and without social participation or a spouse, benefit more from internet access.
Despite growing attention to Internet activity as a social determinant of depression in adolescents, few studies have focused on its diverse effects on depressive symptoms. Using data from the 2020 China Family Panel Study, this study employed logistic regression analysis to examine how Internet activity affects depressive symptoms in adolescents in China. The results indicated that adolescents with longer online duration using mobile phones tended to have higher levels of depression. Adolescents who engaged in online activities related to games, shopping, and entertainment had more severe depressive symptoms, but their time spent on online learning was not significantly associated with their level of depression. These findings suggest a dynamic link between Internet activity and adolescent depression and offer policy implications for addressing depressive symptoms in adolescents. Specifically, Internet and youth development policies and public health programs during the COVID-19 pandemic should be designed based on a comprehensive account of all aspects of Internet activity.
As global climate change intensifies, programs to promote green energy innovation are becoming increasingly urgent for humanity. However, academic debate on whether to prioritize industrial or regional policies continues, detracting the focus from programmes to promote green energy innovation. Using data from 3456 listed companies in China in 2020, this study aims to test intra-industry and spatial spillovers to provide empirical evidence to resolve the academic debate and investigate the impact of urban digital finance on corporate green energy innovation to assess the effectiveness of urban policies. Results show that firms' green energy innovations have significant intra-industry spillovers, but no significant spatial spillovers. Moreover, urban digital finance contributes significantly to green energy innovation. The impact of urban digital finance on green energy innovation varies by a firm's nature, internal controls, and external audits. Therefore, this study proposes a multilevel ecosystem for green energy innovation that theoretically supports a comprehensive and systematic understanding of corporate green energy innovation and guidelines for the precise implementation of policy portfolios.
