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Little information is available about the occurrence of neonicotinoid insecticides in surface water and sediment of the metropolitan regions around the rivers in China. Here we investigate the residual level of neonicotinoids in the Guangzhou section of the Pearl River. At least one or two neonicotinoids was detected in each surface water and sediment, and the total amount of neonicotinoids (∑ 5 neonics) in surface water ranged from 92.6 to 321 ng/L with a geometric mean (GM) of 174 ng/L. Imidacloprid, thiamethoxam and acetamiprid were three frequently detected neonicotinoids (100%) from surface water. As for the sediment, total concentration was varied between 0.40 and 2.59 ng/g dw with a GM of 1.12 ng/g dw, and acetamiprid and thiacloprid were the common sediment neonicotinoids. Western and Front river-route of the Guangzhou section of the Pearl River suffered a higher neonicotinoids contamination than the Rear river-route, resulting from more effluents of WWTPs receiving, and intensive commercial and human activities. Level of residual neonicotinoids in surface water was significantly correlated with the water quality (p < 0.01), especially items of pH, DO and ORP, and nitrogen and phosphorus contaminants. Compared with reports about residual neonicotinoids in water and sediment previously, the metropolitan regions of the Guangzhou could be confronted with a moderate contamination and showed serious ecological threats (even heavier than the Pearl Rivers). Our results will provide valuable data for understanding of neonicotinoids contamination in the Pearl River Delta and be helpful for further assessing environmental risk of neonicotinoids. Image 1 • Occurrence of neonicotinoids in the Guangzhou section of the Pearl River is examined. • At least one or two neonicotinoids was detected in each water and sediment sample. • IMI, THM and ACE were frequently detected (100%) neonicotinoids from surface water. • Western- and Front-suffered a higher neonicotinoids contamination than Rear river-route. • The Guangzhou section of the Pearl River could be confronted with a moderate neonicotinoid contamination. This article evaluates the residual level and distribution of neonicotinoids in the Guangzhou section of the Pearl River, South China. It is of great significance to fully understand the migration, transformation, contamination situation and ecological risk of neonicotinoid insecticides. [ABSTRACT FROM AUTHOR]

The social and ecological influence of Neonicotinoids (NEOs) usage in agriculture sector is progressively higher. There are seven NEOs insecticides widely used for the insects control. Among the NEOs, thiacloprid (THD) was extensively used for insect control during crop cultivation. This study targets to analyse the contamination levels of NEOs in agricultural soil and identify photo-biodegradation of THD degradation using pure isolates and mixed consortium. The photo degradation (PD), biodegradation (BD) and photo-biodegradation (PBD) of THD were compared. The corn field agricultural soils were polluted by four NEOs, among them THD had greater contamination level (surface soil: 3901.2 ± 0.04 μg/g) and (sub-surface soil: 3988.6 ± 0.05 μg/g). Three soil free enriched bacterial strains following Bacillus atrophaeus (PB-2), Priestia megaterium (PB-3) (formerly known as Bacillus megaterium), and Peribacillus simplex (PB-4) (formerly known as Bacillus simplex) were identified by microbiological and molecular 16s rRNA gene sequencing. The PD, BD and PBD of THD were conducted and degradation rate was detected by instrument UPLC-MS-MS. The PBD process with blue-LEDs showed better THD degradation efficiency than PD and BD, where the specific THD degradation rate was 85 ± 0.2%, 87 ± 0.5%, and 89 ± 0.3%, respectively for PB-2, PB-3 and PB-4. Then, the photo-biodegradation performance is greater at 150, 175, 200 rpm, pH 7.0–9.0, and temperature 30–35 °C. After the PBD system deliver four intermediate metabolites, the THD degradation process maybe through nitro reduction, hydroxylation and oxidative cleavage pathway. [Display omitted] • This study to assess soil contamination and neonicotinoids degradation investigated by different method. • The neonicotinoids pollution was detected on surface and sub-surface agriculture soil. • Imidacloprid and thiacloprid were abundant in soils, clothianidin and thiamethoxam were lesser. • Degradation of thiacloprid by blue-LEDs with bacteria had greater performance. • Four biotransformation metabolites was identified from thiacloprid photo-biodegradation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Diverse people groups are confronted with distinct risks of neonicotinoid intake. • Boiling has negligible effect on the elimination of neonicotinoids. • The most frequently detected neonicotinoid was imidacloprid in the tap water. • Human activity and weather play important roles in neonicotinoids in the tap water. • Humans in 9 months –2 years are subjected to the highest drinking neonicotinoids. Neonicotinoids (NEOs) are the most widely used pesticides and have posed a serious threat to human health. However, data on human exposure to NEOs are extremely scarce. To bridge this gap, human exposure potential of NEOs through drinking water consumption and percutaneous penetration was evaluated with the influences of 17 age groups, 4 seasons, 6 regions, and 2 genders. The results showed that drinking water in the present study had an upper middle level of NEO contamination. Anthropogenic activity and weather condition played important roles in the regional distribution of NEOs in tap water. For both children and adults, N EOs intake from d rinking water e xposure (NDE) and p ercutaneous e xposure (NPE) in the south regions of China are significantly higher than those in the north regions, while the order of NDE and NPE by season is summer > spring = autumn > winter. Furthermore, human age and gender also have remarkable impacts on NDE and NPE. The age groups of children subjected to the highest NDE and NPE were 9 months – 2 years old and 9–12 years old, respectively. This study provides insights into the role of seasonal and regional influence, age and gender in the risk of drinking water and percutaneous exposure to NEOs. [ABSTRACT FROM AUTHOR]

Developing monitoring system for paper industrial wastewater treatment system is an important route for wastewater reuse and recycling from wastewater, which are regarded as effective way for cleaner production. A novel hybrid deep leaning CLSTMA model, which based on sequential fusion convolutional neural network (CNN), long short term memory (LSTM) and attention mechanism (AM), was developed to monitor the water quality in a full-scale paper industrial wastewater treatment system for energy conservation and emissions reduction. The hybrid CLSTMA model for predicting water quality of paper industrial wastewater treatment system was divided into three steps: spatial information fusion by using CNN module, temporal information fusion by using LSTM module and variable weighted calculation by using AM module. Compare with other models (CNN, LSTM and CLSTM models), RMSE of CLSTMA model for the effluent chemical oxygen demand (COD eff) reduced by 23.3–31.55%, MAE of CLSTMA model reduced by 38.89–74.50%, R of CLSTMA model increased by 8.29–11.86%. For the effluent suspended solids (SS eff), compared with CNN and LSTM models, RMSE of CLSTMA model reduced by 10.26% and 9.92%, MAE of CLSTMA model reduced by 5.37% and 3.44%, R of CLSTMA model increased by 15.13% and 37.21%, respectively. While, R of CLSTMA was consistent with CLSTM model, but RMSE and MAE of CLSTMA model reduced by 16.07% and 7.49% than the CLSTM model. Simulation results demonstrate that the proposed CLSTMA model has a great potential in monitoring paper industrial wastewater treatment system for cleaner production. [Display omitted] • A new deep learning model was proposed for real-time estimation of water quality. • The new model was based on convolutional neural network, long-term short-term memory and attention mechanism. • The new model can guarantee wastewater reuse and reduce the wastewater treatment cost. [ABSTRACT FROM AUTHOR]

Recycling wastewater of the pulping and paper-making industry are widely considered for clean production, which heavily rely on the timely and accurate monitoring in paper-making wastewater treatment processes. A novel predicting model based on genetic-deep belief network algorithm was proposed to improve the predictive accuracy and reliability for process monitoring. Considering the deep belief networks (DBN) as a deep learning model is aiming to describe the relationship among variables in a complex process modeling, genetic algorithm (GA) was employed to reduce the input variables dimensionality, simplify the network structure and overcome the dynamic characteristic difficulties of process data in monitoring. Compared with DBN and back propagation neural network (BPNN), the GA-DBN effectively achieved a better predictive accuracy than other tests models in complex wastewater treatment processes. The value of the coefficient of determination of GA-DBN model is increased by 1.71–1.86% and 5.21–9.32%, respectively. The GA-DBN model can be structured with fewer variables or samples to describe the complex paper-making wastewater treatment process, obtaining the better model performance and predictive accuracy. [ABSTRACT FROM AUTHOR]

Coupling of methanogenesis and denitrification with elevated nitrate under the methanogenic condition shows potential advantages for (N-) heterocyclic compounds removal and methane recovery simultaneously. However, methane production, sludge characteristics and microbial evolution response to elevated nitrate were seldom reported. Here, an experiment lasing about 300 days under the methanogenic condition with sequential influent nitrate addition as COD/NO 3 −-N ratio from 486.03 to 8.00 was carried out. More than 50% decline of removal rate of COD was observed when the COD/NO 3 −-N ratio varied from 19.97 to 8.00 (232 d). At last, the removal rate of COD recovered to around 94% at the COD/NO 3 −-N ratio of 8.00. About 90% of nitrate was removed through denitrification, and a lower content of methane (40–45%) and effluent acetate and propionate (<10 mg/L) were observed with elevated nitrate. Damage of the granule-shaped and multi-layer structure of the sludge with the lift of nitrate addition was studied. Results of high-throughput sequencing hinted that bacteria accounted for about 70% of total microbes and Proteobacteria , Bacteroidetes , Firmicute and Chloroflexi were the dominant phyla shared with sludge at different COD/NO 3 −-N ratio. Pseudomonas genus and Enterobacteriaceae family (Gammaproteobacteria class, Proteobacteria phylum), Brachymonas genus and Rhodocyclaceae family (Betaproteobacteria class, Proteobacteria phylum) might be vital for the denitrification process under the methanogenic condition. An increase of Smithella and Syntrophobacterale genus with elevated nitrate could be partly contributed to denitrification from the transformation of intermediates as propionate and butyrate. Methanosaeta and Methanobacterium genus were two major methanogens, and Methanosaeta seemed to be less adaptable for elevated nitrate than Methanobacterium. A suitable nitrate addition as influent COD/NO 3 −-N ratio ranged from 121.43 to 15.18 was recommended for the coupling of methanogenesis and denitrification. The results of this work would enhance the understanding of the effects and adaptation with elevated nitrate under the methanogenic condition and instruct engineering practice for low COD/NO 3 −-N wastewater treatment and methane recovery. Image 1 • Structure and architecture of methanogenic sludge with elevated nitrate was studied. • Conversion of different nitrogen form and biomethane with elevated nitrate was explored. • The Archaeal and bacterial community were significantly influenced by elevated nitrate. • A sharp increase of Smithella and Syntrophobacterale with nitrate addition was observed. • Methanobacterium and Methanosaeta genera were two major methanogenic archaea. [ABSTRACT FROM AUTHOR]

• At least one neonicotinoid was detected in all soil, water and sediment samples. • Transport of raw agricultural products could be a source of NEOs in urban areas. • Pollution of NEOs in rural areas was significantly higher than that in urban areas. • Correlation and migration of NEOs residue in soil-water-sediment systems were studied. • Exposure to the current NEOs residue level of Guangzhou suggests a serious threat to sensitive non-target invertebrates. Residues and distribution of neonicotinoid insecticides (NEOs) in soil-water-sediment systems of the urban and rural areas of Guangzhou, South China were investigated. A total of 104 soil samples from 7 different functional zones and 29 water/sediment samples from creeks were collected. The results showed that at least one neonicotinoid insecticide was detected in all samples. The summed levels of five target neonicotinoids (∑ 5 neonics) were in the range of 0.003–229 ng/g dw for soil samples, 7.94–636 ng/L for water samples, and 0.017–31.3 ng/g dw for sediment samples, with a geometric mean of 0.59 ng/g dw, 153 ng/L and 1.11 ng/g dw, respectively. Soils from agricultural areas contained the highest residual NEOs, followed by commercial, traffic, residential, industrial, educational zones and parks. Among the seven different functional zones studied, imidacloprid was the most dominant NEO in the agricultural areas and commercial zones, whereas acetamiprid was dominant in the other five functional zones with different land-use types. Thiamethoxam and acetamiprid were the main NEOs in water and sediment samples collected from 29 creeks. The pollution of NEOs in soils, water and sediments from rural areas was higher than that in the counterparts from urban areas. Residual concentration of NEOs detected in soils, water and sediments showed significant correlations with each other. The distribution of NEOs in soil-water-sediment systems indicated that NEOs tended to concentrate in water, followed by sediments and soils, especially in urban areas. An evaluation of the exposure to the current level of the ∑ 5 NEOs in Guangzhou suggests a significant risk for aquatic and soil organisms, particularly under chronic exposures. The results of the present study offer valuable data to better understand the contamination and ecological risks of neonicotinoid insecticides in the rapidly developing urbanized region of South China. [ABSTRACT FROM AUTHOR]

Abstract Occurrence and distribution of five neonicotinoids (NEOs) in surface water and sediment were studied in the Pearl Rivers, including three trunk streams, Dongjiang, Beijiang, Xijiang River (DR, BR and XR), South China. At least one neonicotinoid was detected in surface water and sediment of the Pearl Rivers, with imidacloprid (IMI) and thiamethoxam (THM) being the frequently detected NEOs. Total amount of NEOs (∑ 5 neonics) in surface water and sediment ranged from 24.0 to 322 ng/L, and from 0.11 to 11.6 ng/g dw, respectively. Moreover, the order of contamination level of NEOs in the Pearl Rivers was as follows: XR > DR > BR for surface water, and BR > DR > XR for sediment. Local agricultural activities and effluents of wastewater treatment plants (WWTPs) could be major sources of NEOs in the Pearl Rivers. Solubilization and dilution of NEOs between surface water and sediment during different seasons (spring and summer) could be attributed to rainfall intensities or climate of the Pearl River Delta. An ecological risk assessment of the exposure to current environmental concentration of imidacloprid and ∑ 5 NEOs suggests a threat to sensitive non-target invertebrates, including aquatic invertebrates. Results would provide a better understanding of NEOs contamination in the Pearl Rivers, as well as being a reliable dataset for decision-making in contamination control and environmental protection. Graphical abstract Image 1 Highlights • At least one NEO was detected in water and sediment of the Pearl Rivers. • Imidacloprid and thiamethoxam were the most frequently detected NEOs. • Local agricultural runoff and effluents of WWTPs could be the main sources. • Seasonal differences of NEOs contamination could be attributed to rainfall intensities. • Exposure to current level would pose a potential threat to sensitive non-target invertebrates. [ABSTRACT FROM AUTHOR]

Abstract: A novel electrochemical sensing system for Pb2+ has been developed based on atypical icosahedral gold nanoparticle (AI-AuNPs) modification and the improved rolling circle amplification (RCA). The newly synthesized AI-AuNPs which were applied to modify the gold electrode surface greatly enhanced the sensitivity and expanded the detection range due to its large specific surface area and a large density of irrational kinks and step atoms on the particle surface. Additionally, the improved RCA introduced a manipulated circular template DNA which can be hybridized with the primer obtained from the DNAzymes catalysis reaction in the presence of Pb2+ as a cofactor to simplify the RCA procedure, and the largely elongated RCA products at the same time efficiently blocked the electron transfer at the electrode surface, thus significantly increased the electrochemical signal. The design of the label free electrochemical impendence sensing strategy was evidenced to be a highly sensitive and selective method for the lead ions monitoring compared with the previous reports and the detection range was 1pM–1μΜ with a detection limit of 290fM (3δ rule). Furthermore, the proposed detection system was also environmental-friendly and inexpensive, which can be successfully used in real serum sample detection. [Copyright &y& Elsevier]

This study assessed the usefulness of Pea Pisum sativum peels S-modified biochar (PPB–S) and Triethylenetetramine (TETA)-modified biochar (PPB-T) as improvers for biogas generation from green algae Ulva lactuca either individually or co-digested with Pea peels (PPs). BET, FTIR, TGA, XRD, XPS, SEM coupled with EDX were used to characterize the PPB-S and PPB-T biochars. EDX, FTIR, and XPS analyses proved the formation of sulphur and nitrogen groups on the surface of PPB-S and PPB-T. The kinetic study confirmed that the modified Gompertz model fits the experimental data satisfactorily, with R 2 ranging between 0.948 and 0.991. The results suggested that adding 50 mg/L of PPB-S significantly increased the biogas production yield compared to all other studied treatments, either individually or in co-digestion with PPs. The extreme biogas production (498 mL/g VS) was formed when 50 mg/L of PPB-S was added to U. lactuca. According to Response surface methodology (RSM), the maximum biogas production among all experiments is 460.91 (ml/g VS), achieved for U. lactuca and PPB-S treatment corresponds to 54 days contact time and 50 mg/L of PPB-S dose. The direct electron transfer mechanism has been investigated in detail, and it is confirmed that conductive PPB-S can support electron transfer and promote methane production, as proved by the XPS and FTIR analyses, which the creation of sulphur groups on the PPB-S surface may propose. In this study, the use of PPB-S in biogas production aligns with the principles of a circular economy. • Synthesis of S-doped biochar (PPB–S) and N-doped biochar (PPB-T) from Pisum sativum. • Investigation of PPB-S and PPB-T as improvers for biogas generation from U. lactuca. • The mechanism of DIET in biogas production processes via AD using PPB-S and PPB-T. • The extreme biogas production (498 mL/g VS) was produced using 50 mg/L of PPB-S. • The direct electron transfer mechanism of PPB-S and PPB-T has been studied in detail. [ABSTRACT FROM AUTHOR]

In this paper, a novel dynamic optimization control based on multi-objective ant lion optimization (DMOALO) and deep learning algorithm is proposed, which could optimize energy consumption (EC) and effluent quality (EQ) simultaneously in the wastewater treatment processes. In order to overcome the difficulty that there is no clear function relationship between the dynamic parameters and the performance indicators, a novel deep belief network (DBN) model for predicting EC and EQ as objective function is proposed. Then, this objective function with constraints is solved by DMOALO method, and the optimal solution would be selected by the intelligent decision system. Finally, Proportional Integral (PI) controllers would be used to track and control these optimal dynamic parameters. DBN-DMOALO-PI optimization control strategy is evaluated in benchmark simulation model 1(BSM1), the simulation results demonstrated this novel optimization control strategy could reduce the EC significantly while meeting the standards of effluent quality parameters. EC is decreased by 3.31% compared with PI optimization control strategy. Therefore, this novel method may reduce the cost of wastewater treatment process effectively, and realize the carbon neutrality in wastewater treatment process. [Display omitted] • A novel dynamic optimization control based on multi-objective ant lion optimization (DMOALO) and deep learning is proposed. • A deep learning model for predicting energy consumption (EC) and effluent quality (EQ) as objective function is proposed. • DMOALO algorithm was proposed to solve objective function overcame the dynamic characteristic difficulties of process data. • The optimization control can optimize EC and EQ simultaneously in the wastewater treatment processes. [ABSTRACT FROM AUTHOR]