N-glycosylation of the SARS-CoV-2 spike protein at Asn331 and Asn343 is involved in spike-ACE2 binding, virus entry, and regulation of IL-6.

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global public health crisis. The causative agent, the SARS-CoV-2 virus, enters host cells via molecular interactions between the viral spike protein and the host cell ACE2 surface protein. The SARS-CoV-2 spike protein is extensively decorated with up to 66 N-linked glycans. Glycosylation of viral proteins is known to function in immune evasion strategies but may also function in the molecular events of viral entry into host cells. Here, we show that N-glycosylation at Asn331 and Asn343 of SARS-CoV-2 spike protein is required for it to bind to ACE2 and for the entry of pseudovirus harboring the SARS-CoV-2 spike protein into cells. Interestingly, high-content glycan binding screening data have shown that N-glycosylation of Asn331 and Asn343 of the RBD is important for binding to the specific glycan molecule G4GN (Galß-1,4 GlcNAc), which is critical for spike-RBD-ACE2 binding. Furthermore, IL-6 was identified through antibody array analysis of conditioned media of the corresponding pseudovirus assay. Mutation of N-glycosylation of Asn331 and Asn343 sites of the spike receptor-binding domain (RBD) significantly reduced the transcriptional upregulation of pro-inflammatory signaling molecule IL-6. In addition, IL-6 levels correlated with spike protein levels in COVID-19 patients' serum. These findings establish the importance of RBD glycosylation in SARS-CoV-2 pathogenesis, which can be exploited for the development of novel therapeutics for COVID-19.

Identification and validation of circulating biomarkers for detection of liver cancer with antibody array.

The aim of this study was to find new protein biomarkers that could be used to detect hepatocellular carcinoma (HCC) in the serum. We identified 11 proteins in the tissue that could be used to classify samples from HCC and control subjects. The 11 identified tissue biomarkers were combined with 10 commonly used serum HCC biomarkers for further verification in a large number of serum samples from HCC patients and healthy controls. 17 of the 21 prospective serum biomarkers were determined to be differentially expressed through collinearity and significance analysis. Through the method of supervised learning, a random forest model was constructed to reduce the dimensionality of the number of differentially expressed proteins, and finally, 4 differentially expressed proteins were identified: AFP, GDF15, CEACAM-1, and MMP-9, and suggested to have potential application in clinical diagnosis of HCC.

Assessment of dynamic drought-induced ecosystem risk: Integrating time-varying hazard frequency, exposure and vulnerability.

Terrestrial ecosystems, occupying 28.26% of Earth's surface, are extensively at risk from droughts, which is likely to propagate into human communities owing to loss of vital services. Ecosystem risk also tends to fluctuate within anthropogenically-forced nonstationary environments, raising considerable concerns about effectiveness of mitigation strategies. This study aims to assess dynamic ecosystem risk induced by droughts and identify risk hotspots. Bivariate nonstationary drought frequency was initially derived as a hazard component of risk. By coupling vegetation coverage and biomass quantity, a two-dimensional exposure indicator was developed. Trivariate likelihood of vegetation decline was calculated under arbitrary droughts to intuitively determine ecosystem vulnerability. Ultimately, time-variant drought frequency, exposure and vulnerability were multiplied to derive dynamic ecosystem risk, followed by hotspot and attribution analyses. Risk assessment implemented in the drought-prevalent Pearl River basin (PRB) of China during 1982-2017 showed that meteorological droughts in eastern and western margins, although less frequent, were prolonged and aggravated in contrast to prevalence of less persistent and severe droughts in the middle. In 86.12% of the PRB, ecosystem exposure maintains high levels (0.62). Relatively high vulnerability (>0.5) occurs in water-demanding agroecosystems, exhibiting a northwest-southeast-directed extension. A 0.1-degree risk atlas unveils that high and medium risks occupy 18.96% and 37.99% of the PRB, while risks are magnified in the north. The most pressing hotspots with high risk continuing to escalate reside in the East River and Hongliu River basins. Our results provide knowledge of composition, spatio-temporal variability and driving mechanism of drought-induced ecosystem risk, which will assist in risk-based mitigation prioritization.

Analyzing the Biochemical Alteration of Green Algae During Chronic Exposure to Triclosan Based on Synchrotron-Based Fourier Transform Infrared Spectromicroscopy.

The study explored the chronic toxicity of triclosan to green microalga Chlorococcum sp. under multiple interactions among multiple environmental conditions. This is the first study on chronic algal toxicity to combine synchrotron-based Fourier transform infrared spectromicroscopy, factorial analysis, principal component analysis, and stepwise-cluster analysis. Such a combination helps to reveal the toxic mechanism at the molecular level and explore the inner correlationship among multiple environmental conditions. In the 120-h test, nitrogen content became the most significant factor of the physiochemical properties. Some insignificant factors in the 48-h test became significant in the 120-h test. Temperature * nitrogen content, temperature * phosphorus content, and pH * phosphorus content were the most significant two-order interactions. Temperature * pH * NaCl concentration and temperature * NaCl concentration * phosphorus content were the most significant three-order interactions. More high-order interactions became significant in the 120-h test, indicating the complexity and impacts of all the factors may increase when time was extended. The chronic toxicity of triclosan presented more distinguishable variations among treatments based on biochemical alterations. These results demonstrate that the sensitivity and fragility of algae to triclosan can be amplified with time extension. Long-term exposure can be applied to better evaluate and predict the environmental toxicity behavior of triclosan. It can also help with environmental evaluation and risk management of real-world triclosan toxicity.

Discovering endometriosis biomarkers with multiplex cytokine arrays.

BACKGROUND: Chronic pelvic pain is often overlooked during primary examinations because of the numerous causes of such "vague" symptoms. However, this pain can often mask endometriosis, a smoldering disease that is not easily identified as a cause of the problem. As such, endometriosis has been shown to be a potentially long-term and often undiagnosed disease due to its vague symptoms and lack of any non-invasive testing technique. Only after more severe symptoms arise (severe pelvic pain, excessive vaginal bleeding, or infertility) is the disease finally uncovered by the attending physician. Due to the nature and complexity of endometriosis, high throughput approaches for investigating changes in protein levels may be useful for elucidating novel biomarkers of the disease and to provide clues to help understand its development and progression. METHODS: A large multiplex cytokine array which detects the expression levels of 260 proteins including cytokines, chemokines, growth factors, adhesion molecules, angiogenesis factors and other was used to probe biomarkers in plasma samples from endometriosis patients with the intent of detecting and/or understanding the cause of this disease. The protein levels were then analyzed using K-nearest neighbor and split-point score analysis. RESULTS: This technique identified a 14-marker cytokine profile with the area under the curve of 0.874 under a confidence interval of 0.81-0.94. Our training set further validated the panel for significance, specificity, and sensitivity to the disease samples. CONCLUSIONS: These findings show the utility and reliability of multiplex arrays in deciphering new biomarker panels for disease detection and may offer clues for understanding this mysterious disease.

Insights into Long-Term Toxicity of Triclosan to Freshwater Green Algae in Lake Erie.

This study explored the long-term impacts of a pulse disturbance of triclosan on five nontarget green algae in Lake Erie. Comprehensive analyses were performed using multiple physiological end points at community and subcellular scales. The toxic mechanism of triclosan in a wide range of concentrations was analyzed. The diverse sensitivity of algae species and complex interrelationships among multiple end points were revealed. The results showed the taxonomic groups of algae were the key issue for sensitivity difference. High doses of triclosan caused irreversible damage on algae, and environmentally relevant doses initiated either inhibition or stimulation. Smaller cells had higher sensitivity to triclosan, while larger cells had a wider size variation after exposure. Colonial cells were less sensitive than unicells. For chlorophyll, there were better dose-response relationships in Chlorococcum sp., Chlamydomonas reinhardtii CPCC 12 and 243 than Asterococcus superbus and Eremosphaera viridis. For chlorophyll fluorescence, Fv/ Fm was the most sensitive parameter, and qN was more sensitive than qP. Triclosan showed long-term effects on biochemical components, such as lipids, proteins, and nucleic acids. The findings will be helpful for a systematic and complete assessment of triclosan toxicity in natural waters and the development of appropriate strategies for its risk management.

Interactive Toxicity of Triclosan and Nano-TiO2 to Green Alga Eremosphaera viridis in Lake Erie: A New Perspective Based on Fourier Transform Infrared Spectromicroscopy and Synchrotron-Based X-ray Fluorescence Imaging.

This study explored the toxicity of triclosan in the presence of TiO2 P25 to the green alga Eremosphaera viridis in Lake Erie. Multiple physicochemical end points were conducted to perform a comprehensive analysis of the toxic effects of individual and combined pollutants. Fourier transform infrared spectromicroscopy and synchrotron-based X-ray fluorescence imaging were first documented to be applied to explore the distribution variation of macromolecules and microelements in single algal cells in interactive toxicity studies. The results were different based on different triclosan concentrations and measurement end points. Comparing with individual pollutants, the toxicity intensified in lipids, proteins, and oxidative stress at 1000 and 4000 µg/L triclosan in the presence of P25. There were increases in dry weight, chlorophyll content, lipids, and catalase content when cells were exposed to P25 and 15.625 µg/L triclosan. The toxicity alleviated when P25 interacted with 62.5 and 250 µg/L triclosan compared with triclosan-only exposure. The reasons could be attributed to the combination of adsorption, biodegradation, and photocatalysis of triclosan by algae and P25, triclosan dispersion by increased biomass, triclosan adherency on algal exudates, and triclosan adsorption site reduction on algae surface owing to P25's taking over. This work provides new insights into the interactive toxicity of nanoparticles and personal care products to freshwater photosynthetic organisms. The findings can help with risk evaluation for predicting outcomes of exposure to mixtures and with prioritizing further studies on joint toxicity.

New Insights into the Tumor Microenvironment Utilizing Protein Array Technology.

The tumor microenvironment (TME) is a considerably heterogeneous niche, which is created by tumor cells, the surrounding tumor stroma, blood vessels, infiltrating immune cells, and a variety of associated stromal cells. Intercellular communication within this niche is driven by soluble proteins synthesized by local tumor and stromal cells and include chemokines, growth factors, interferons, interleukins, and angiogenic factors. The interaction of tumor cells with their microenvironment is essential for tumorigenesis, tumor progression, growth, and metastasis, and resistance to drug therapy. Protein arrays enable the parallel detection of hundreds of proteins in a small amount of biological sample. Recent data have demonstrated that the application of protein arrays may yield valuable information regarding the structure and functional mechanisms of the TME. In this review, we will discuss protein array technologies and their applications in TME analysis to discern pathways involved in promoting the tumorigenic phenotype.

Insight into sorption mechanism of phenanthrene onto gemini modified palygorskite through a multi-level fuzzy-factorial inference approach.

A multi-level fuzzy-factorial inference approach was proposed to examine the sorption behavior of phenanthrene on palygorskite modified with a gemini surfactant. Fuzzy set theory was used to determine five experimentally controlled environmental factors with triangular membership functions, including initial concentration, added humid acid dose, ionic strength, temperature, and pH. The statistical significance of factors and their interactions affecting the sorption process was revealed through a multi-level factorial experiment. Initial concentration, ionic strength, and pH were identified as the most significant factors based on the multi-way ANOVA results. Examination of curvature effects of factors revealed the nonlinear complexity inherent in the sorption process. The potential interactions among experimental factors were detected, which is meaningful for providing a deep insight into the sorption mechanisms under the influences of factors at different levels.

Municipal solid waste management planning considering greenhouse gas emission trading under fuzzy environment.

Waste management activities can release greenhouse gases (GHGs) to the atmosphere, intensifying global climate change. Mitigation of the associated GHG emissions is vital and should be considered within integrated municipal solid waste (MSW) management planning. In this study, a fuzzy possibilistic integer programming (FPIM) model has been developed for waste management facility expansion and waste flow allocation planning with consideration of GHG emission trading in an MSW management system. It can address the interrelationships between MSW management planning and GHG emission control. The scenario of total system GHG emission control is analyzed for reflecting the feature that GHG emission credits may be tradable. An interactive solution algorithm is used to solve the FPIM model based on the uncertainty-averse preferences of decision makers in terms of p-necessity level, which represents the certainty degree of the imprecise objective. The FPIM model has been applied to a hypothetical MSW planning problem, where optimal decision schemes for facility expansion and waste flow allocation have been achieved with consideration of GHG emission control. The results indicate that GHG emission credit trading can decrease total system cost through re-allocation of GHG emission credits within the entire MSW management system. This will be helpful for decision makers to effectively determine the allowable GHG emission permits in practices.

Toxicity and mechanism of nanoplastics to phytoplankton in high-latitude aquatic ecosystems of Canadian prairie: Effects of multiple environmental factors.

The potential ecological risks of nanoplastics (NPs) may be inaccurately assessed in some studies as they fail to consider the impact of environmental factors and their interactive effects. Here, the effects of six representative environmental factors (N, P, salinity, DOM (dissolved organic matter), pH and hardness) on NPs' toxicity and mechanism to microalgae are investigated based on the surface water quality data in Saskatchewan watershed, Canada. Our 10 sets of 26-1 factorial analysis reveal the significant factors and their interactive complexity towards 10 toxic endpoints from cellular and molecular levels. This is the first time to study the toxicity of NPs to microalgae under interacting environmental factors in high-latitude aquatic ecosystems of Canadian prairie. We find that microalgae become more resistant to NPs in N-rich or higher pH environments. Surprisingly, with the increase of N concentration or pH, the inhibitory effect of NPs on microalgae growth even became a promotion effect with the decreased inhibition rate from 10.5 % to -7.1 % or from 4.3 % to -0.9 %, respectively. Synchrotron-based Fourier transform infrared spectromicroscopy analysis reveals that NPs can induce alterations in the content and structure of lipids and proteins. DOM, N*P, pH, N*pH and pH*hardness have a statistically significant effect on NPs' toxicity to biomolecular. The toxicity levels of NPs across Saskatchewan watersheds are evaluated and we find that NPs could have the greatest inhibition on microalgae growth in Souris River. Our findings indicate that multiple environmental factors should be considered during the ecological risk assessment of emerging pollutants.

Rethinking the effects of micro/nanoplastics from the global environmental change and systematic perspective: An aquatic environmental system-based comprehensive assessment approach of micro/nanoplastic impacts.

The study on micro/nanoplastic pollution should embrace complexity. Here, we aim to develop an aquatic environmental system-based comprehensive assessment approach of micro/nanoplastic impacts (ACAM) to evaluate the effects of micro/nanoplastics on aquatic ecosystems from the global environmental change (GEC) and systematic perspective. A case study for freshwater systems in Saskatchewan, Canada was conducted to evaluate the comprehensive effects of multiple GEC factors (polystyrene-nanoplastics (PS-NPs), N, P, salinity, dissolved organic matter (DOM), pH, hardness) on Asterococcus superbus based on ten ecologically relevant endpoints. It is found that at the cellular level, PS-NPs and N had an antagonistic interaction on microalgal growth in the Saskatchewan freshwater ecosystem; at the molecular level, the PS-NP-induced changes in lipid composition in microalgae were regulated by P, DOM, and pH. The significance ranking of factor effects suggested that instead of PS-NPs pollution, the fluctuations in pH level, DOM and N concentrations should be paid attention to first in Saskatchewan. Under the combined impact of PS-NPs and other GEC factors, microalgae at station 14 (Qu'Appelle River near highway 56) might have the minimum growth rate with [-0.048, 0.094] d-1 in Saskatchewan. These findings demonstrate the efficacy of the developed ACAM in a more comprehensive and context-specific assessment of MNP risks, providing new insight for the management of MNP pollution.

Impact from the evolution of private vehicle fleet composition on traffic related emissions in the small-medium automotive city.

Understanding the emission characteristics in the evolution of private vehicle fleet composition has become a key issue to be addressed to develop appropriate emission mitigation strategies in transportation sector. In this study, the influence of such evolution on on-road emissions was investigated based on a comprehensive dataset encompassing vehicle fleet composition, demographic, economic, and energy features from a representative small-medium automotive city in North America. The decoupling analysis was carried out to assess the dynamic linkage between environmental pressure exerted by the transportation sector and economic growth at both city level and national level in North America. We also developed an approach that supports the long-term traffic-related air pollutant prediction and investigated the potential influence on urban air quality. A sharp upward trajectory was observed in the quantity of SUVs from 2001 to 2018, gradually replacing the dominance of the quantity of four-door cars. There was a significant shift in the GHG emissions emitted from vehicle types used for passenger transport: emissions from SUVs and trucks rose by 374.0% and 69.3%, respectively, whereas emissions from four-door cars, two-door cars, station wagons, and vans all decreased. The changes in vehicle composition, along with the steady trend in GHG emissions from private fleet and decrease in on-road air pollutant concentrations found in Regina, were a response to the establishment of federal fuel economy standards and improved fuel economy. Relative decoupling was observed in aggregate for Regina and Canada in most of the years while both experienced economic downturns and increases in environmental pressure in the form of emissions from 2014 to 2015. The predicted results also demonstrate the high capability of XGboost machine learning algorithm in predicting on-road air pollutant concentrations of CO, PM2.5, and NOX.

Review of aquatic toxicity of pharmaceuticals and personal care products to algae.

Pharmaceuticals and Personal Care Products (PPCPs) have been frequently detected in the environment around the world. Algae play a significant role in aquatic ecosystem, thus the influence on algae may affect the life of higher trophic organisms. This review provides a state-of-the-art overview of current research on the toxicity of PPCPs to algae. Nanoparticles, contained in personal care products, also have been considered as the ingredients of PPCPs. PPCPs could cause unexpected effects on algae and their communities. Chlorophyta and diatoms are more accessible and sensitive to PPCPs. Multiple algal endpoints should be considered to provide a complete evaluation on PPCPs toxicity. The toxicity of organic ingredients in PPCPs could be predicted through quantitative structure-activity relationship model, whereas the toxicity of nanoparticles could be predicted with limitations. Light irradiation can change the toxicity through affecting algae and PPCPs. pH and natural organic matter can affect the toxicity through changing the existence of PPCPs. For joint and tertiary toxicity, experiments could be conducted to reveal the toxic mechanism. For multiple compound mixture toxicity, concentration addition and independent addition models are preferred. However, there has no empirical models to study nanoparticle-contained mixture toxicity. Algae-based remediation is an emerging technology to prevent the release of PPCPs from water treatment plants. Although many individual algal species are identified for removing a few compounds from PPCPs, algal-bacterial photobioreactor is a preferable alternative, with higher chances for industrial applications.

Multi-regional industrial wastewater metabolism analysis for the Yangtze River Economic Belt, China.

Enormous wastewater discharges have significantly impeded the sustainable development. As several economic belt has been formed in China, systematic analysis of multi-regional wastewater metabolic system is required for advancing wastewater mitigation effectively and efficiently. In this study, a distributive environmental input-output model (DEIO) is developed for the Yangtze River Economic Belt (YREB) to provide bases for supporting sustainable development from inter-regional and inter-sectoral perspectives. The discharges and flows of wastewater and related pollutants (i.e., chemical oxygen demand (COD) and ammonia nitrogen (AN)) among sectors and regions are analyzed to providing solid bases for wastewater management within the YREB. The results show that the industrial wastewater mitigation in YREB is desired urgently. The industrial wastewater discharges in Jiangsu and Zhejiang provinces are numerous, while Hunan and Yunnan provinces are more inclined to suffer from serious COD and AN pollution. In addition, the manufacture of food, tobacco, chemical materials, and pharmaceutical are the typical sectors with a large amount of direct wastewater discharge, and the tertiary industry is ranked at the first in indirect wastewater discharge. According to the analysis, the implementation of the "Supply-side Structure Reform" and the "Replace Subsidies with Rewards" policy can benefit the wastewater mitigation in the YREB.

Exploring the biophysicochemical alteration of green alga Asterococcus superbus interactively affected by nanoparticles, triclosan and illumination.

Toxic effects on Asterococcus superbus were studied based on different combinations of P25-TiO2, nano-ZnO and triclosan under multiple illumination conditions. A full factorial design (2 × 2×2 × 3) was implemented to explore interactive effects, and to identify significant factors. The results showed illumination is the most important factor with significance and becomes one of the main reasons to affect chlorophyll pigments, photosynthesis activity, unsaturated fatty acids, mitochondria function, and cause oxidative stress. Triclosan considerably affects cell viability, photosynthesis activity, lipid peroxidation and protein structure, for which triclosan is more significant than nano-ZnO. P25 is significant for oxidative stress, antioxidant enzyme, and lipid peroxidation. P25 * nano-ZnO is the only significant interaction of pollutants, affecting macromolecules, lipid peroxidation, and photosynthesis activity. High-order interactions play significant roles in affecting multiple molecular components. Two groups of endpoints are best to reflect alga responses to interactively effects from P25, nano-ZnO, and triclosan. One is ROS, chlorophyll pigments, TBARS, area, MTT, and MMP, and the other one is chlorophyll pigments, ROS, TBARS, CAT, MTT and SOD. Our findings can be instructive for a comprehensive comparison among interactions of multiple pollutants and environmental factors in natural waters, such that more robust environmental toxicity analyses can be performed.

Functional PVDF ultrafiltration membrane for Tetrabromobisphenol-A (TBBPA) removal with high water recovery.

Tetrabromobisphenol-A (TBBPA) is one of the most important brominated flame retardants (BFRs), accounting for 60% of the total commercial BFR market. Increasing amounts of TBBPA and byproducts are released to the aquatic environment due to their extensive utilization in various sectors. However, research on the treatment of TBBPA contaminated wastewater using membrane filtration is still lacked. Herein, a PVDF10-PAA-ZrO2 membrane was successfully developed and applied for the treatment of high-concentration TBBPA wastewater with super-high water recovery. The membrane was obtained through surface functionalization with nano-ZrO2 from commercial PVDF ultrafiltration (UF) membrane. Compared to the commercial PVDF membrane, the developed membrane exhibited 4 times of permeate flux which was up to 200 L/m2 min with comparable TBBPA rejection rate. Furthermore, the mechanisms of membrane development and TBBPA rejection were explored through synchrotron-based ATR-FTIR and X-ray analyses. It was revealed that ZrO2 NPs were immobilized into membrane surface through binding with PAA layer, where the O of the carboxyl group combined with the Zr4+ on the ZrO2 NP surface to form C-O-Zr bond through monodentate and bridging-bidentate modes. The sieving function of membrane could be the main mechanism of TBBPA removal. This research demonstrated a practical route and solid insight toward the development of highly efficient membrane for TBBPA removal. The proposed PVDF10-PAA-ZrO2 membrane can also be promising for other industrial separation and purification applications.

Developing a periodontal disease antibody array for the prediction of severe periodontal disease using machine learning classifiers.

BACKGROUND: The aim of this study was to simultaneously and quantitatively assess the expression levels of 20 periodontal disease-related proteins in gingival crevicular fluid (GCF) from normal controls (NOR) and severe periodontitis (SP) patients with an antibody array. METHODS: Antibodies against 20 periodontal disease-related proteins were spotted onto a glass slide to create a periodontal disease antibody array (PDD). The array was then incubated with GCF samples collected from 25 NOR and 25 SP patients. Differentially expressed proteins between NOR and SP patients were then used to build receiver operator characteristic (ROC) curves and compare five classification models, including support vector machine, random forest, k nearest neighbor, linear discriminant analysis, and Classification and Regression Trees. RESULTS: Seven proteins (C-reactive protein, interleukin [IL]-1α, interleukin-1ß, interleukin-8, matrix metalloproteinase-13, osteoprotegerin, and osteoactivin) were significantly upregulated in SP patients compared with NOR, while receptor activator of nuclear factor-kappa was significantly downregulated. The highest diagnostic accuracy using a ROC curve was observed for IL-1ß with an area under the curve of 0.984. Five of the proteins (IL-1ß, IL-8, MMP-13, osteoprotegerin, and osteoactivin) were identified as important features for classification. Linear discriminant analysis had the highest classification accuracy across the five classification models that were tested. CONCLUSION: This study highlights the potential of antibody arrays to diagnose periodontal disease.

Wastewater treatment in amine-based carbon capture.

Amine-based CO2 capture (ACC) has become one cost-effective method for reducing carbon emissions in order to mitigate climate changes. The amine-rich wastewater (ARWW) generated from ACC may contain a series of degradation products of amine-based solvents (ABSs). These products are harmful for ecological environment and human health. Effective and reliable ARWW treatment methods are highly required for mitigating the harmfulness. However, there is a lack of a comprehensive review of the existing limited methods that can guide ARWW-related technological advancements and treatment practices. To fill this gap, the review is achieved in this study. All available technologies for treating the ARWW from washwater, condenser, and reclaimer units in ACC are examined based on clarification of degradation mechanisms and ARWW compounds. A series of significant findings and recommendations are revealed through this review. For instance, ARWW treatment methods should be selected according to degradation conditions and pollution concentrations. UV light can be only used for treating wastewater from washwater and condenser units in ACC. Biological activated carbon is feasible for removing nitrosamines from washwater and condenser units. Sequence batch reactors, microbial fuel cells, and the other techniques for removing amines and similar degradation products are applicable for treating ARWW. This review provides scientific support for the selection and improvement of ARWW treatment techniques, the mitigation of ACC's consequences in environment, health and other aspects, and the extensive development and applications of ACC systems.

Removal of Tetrabromobisphenol A by adsorption on pinecone-derived activated charcoals: Synchrotron FTIR, kinetics and surface functionality analyses.

This study explored the adsorption of Tetrabromobisphenol A (TBBPA) on pinecone-derived activated charcoal. The interactions between TBBPA and activated-charcoal surface, as well as the corresponding effects of functionality and adsorption capacities, were investigated through synchrotron FTIR, kinetics and surface functionality analyses. It was found that multiple acid functional groups and their interactive effects played important roles. The adsorption on activated charcoal from Yellow pinecone was favored by the surface with high polarity, low aromaticity, and low surface area. In comparison, adsorption on activated charcoal from Scot pinecone was favored by the surface with high aromaticity and high surface area. The adsorption capacity and removal efficiency were significantly dependent upon the contents of acid functional groups on charcoal surface. This study showed that the newly presented evidence of interactions between oxygen-containing functional groups and TBBPA will be helpful for exploring the treatment and transport of such a contaminant in the environment.