A carbon-neutrality-capactiy index for evaluating carbon sink contributions

The accurate determination of the carbon-neutrality capacity(CNC)of a region is crucial for developing policies related to emissions and climate change.However,a systematic diagnostic method for determining the CNC that considers the rock chemical weathering carbon sink(RCS)is lacking.Moreover,it is challenging but indispensable to establish a fast and practical index model to determine the CNC.Here,we selected Guizhou as the study area,used the methods for different types of carbon sinks,and constructed a CNC index(CNCI)model.We found that:(1)the carbonate rock chemical weathering carbon sink flux was 30.3 t CO_(2)km^(-2)yr^(-1).Guizhou accounted for 1.8%of the land area and contributed 5.4%of the carbonate chemical weathering carbon sink;(2)the silicate rock chemical weathering carbon sink and its flux were 1.44×10^(3)t CO_(2)and 2.43 t CO_(2)km^(-2)yr^(-1),respectively;(3)the vegetation-soil ecosystem carbon sink and its flux were 1.37×10^(8)t CO_(2)and 831.70 t CO_(2)km^(-2)yr^(-1),respectively;(4)the carbon emissions(CEs)were 280 Tg CO_(2),about 2.8%of the total for China;and(5)the total carbon sinks in Guizhou were 160 Tg CO_(2),with a CNCI of 57%,which is 4.8 times of China and 2.1 times of the world.In summary,we conducted a systematic diagnosis of the CNC considering the RCS and established a CNCI model.The results of this study have a strong implication and significance for national and global CNC determination and gap analysis.

Microalgae-based wastewater treatment:Mechanisms,challenges,recent advances,and future prospects

The rapid expansion of both the global economy and the human population has led to a shortage of water resources suitable for direct human consumption.As a result,water remediation will inexorably become the primary focus on a global scale.Microalgae can be grown in various types of wastewaters(WW).They have a high potential to remove contaminants from the effluents of industries and urban areas.This review focuses on recent advances on WW remediation through microalgae cultivation.Attention has already been paid to microalgae-based wastewater treatment(WWT)due to its low energy requirements,the strong ability of microalgae to thrive under diverse environmental conditions,and the potential to transform WW nutrients into high-value compounds.It turned out that microalgae-based WWT is an economical and sustainable solution.Moreover,different types of toxins are removed by microalgae through biosorption,bioaccumulation,and biodegradation processes.Examples are toxins from agricultural runoffs and textile and pharmaceutical industrial effluents.Microalgae have the potential to mitigate carbon dioxide and make use of the micronutrients that are present in the effluents.This review paper highlights the application of microalgae in WW remediation and the remediation of diverse types of pollutants commonly present in WW through different mechanisms,simultaneous resource recovery,and efficient microalgae-based co-culturing systems along with bottlenecks and prospects.

Carbon source recovery from waste sludge reduces greenhouse gas emissions in a pilot-scale industrial wastewater treatment plant

Carbon cycle regulation and greenhouse gas(GHG)emission abatement within wastewater treatment plants(WWTPs)can theoretically improve sustainability.Currently,however,large amounts of external carbon sources used for deep nitrogen removal and waste sludge disposal aggravate the carbon footprint of most WWTPs.In this pilot-scale study,considerable carbon was preliminarily recovered from primary sludge(PS)through short-term(five days)acidogenic fermentation and subsequently utilized on-site for denitrification in a wool processing industrialWWTP.The recovered sludge-derived carbon sources were excellent electron donors that could be used as additional carbon supplements for commercial glucose to enhance denitrification.Additionally,improvements in carbon and nitrogen flow further contributed to GHG emission abatement.Overall,a 9.1%reduction in sludge volatile solids was achieved from carbon recovery,which offset 57.4%of external carbon sources,and the indirect GHG emissions of the target industrial WWTP were reduced by 8.05%.This study demonstrates that optimizing the allocation of carbon mass flow within a WWTP has numerous benefits.

Immobilized microalgal system:An achievable idea for upgrading current microalgal wastewater treatment

Efficient wastewater treatment accompanied by sustainable“nutrients/pollutants waste-wastewaterresources/energy nexus”management is acting as a prominent and urgent global issue since severe pollution has occurred increasingly.Diverting wastes from wastewater into the value-added microalgalbiomass stream is a promising goal using biological wastewater treatment technologies.This review proposed an idea of upgrading the current microalgal wastewater treatment by using immobilized microalgal system.Firstly,a systematic analysis of microalgal immobilization technology is displayed through an in-depth discussion on why using immobilized microalgae for wastewater treatment.Subsequently,the main technical approaches employed for microalgal immobilization and pollutant removal mechanisms by immobilized microalgae are summarized.Furthermore,from high-tech technologies to promote large-scale production and application potentials in diverse wastewater and bioreactors to downstream applications lead upgradation closer,the feasibility of upgrading existing microalgal wastewater treatment into immobilized microalgal systems is thoroughly discussed.Eventually,several research directions are proposed toward the future immobilized microalgal system for microalgal wastewater treatment upgrading.Together,it appears that using immobilization for further upgrading the microalgae-based wastewater treatment can be recognized as an achievable alternative to make microalgal wastewater treatment more realistic.The information and perspectives provided in this review also offer a feasible reference for upgrading conventional microalgae-based wastewater treatment.

Assessing the contribution of global wildfire biomass burning to BaP contamination in the Arctic

Polycyclic aromatic hydrocarbons(PAHs)have become cause for growing concern in the Arctic ecosystems,partly due to their stable levels despite global emission reduction.Wildfire is considered one of the primary sources that influence PAH levels and trends in the Arctic,but quantitative investigations of this influence are still lacking.This study estimates the global emissions of benzo[a]pyrene(BaP),a congener of PAHs with high carcinogenicity,from forest and grassland fires from 2001 to 2020 and simulates the contributions of wildfire-induced BaP emissions from different source regions to BaP contamination in the Arctic.We find that global wildfires contributed 29.3%to annual averaging BaP concentrations in the Arctic from 2001 to 2020.Additionally,we show that wildfires contributed significantly to BaP concentrations in the Arctic after 2011,enhancing it from 10.1%in 2011 to 83.9%in 2020.Our results reveal that wildfires accounted for 94.2%and 50.8%of BaP levels in the Asian Arctic during boreal summer and autumn,respectively,and 74.2%and 14.5%in the North American Arctic for the same seasons.The source-tagging approach identified that local wildfire biomass emissions were the largest source of BaP in the Arctic,accounting for 65.7%of its concentration,followed by those of Northern Asia(17.8%)and Northern North America(13.7%).Our findings anticipate wildfires to play a larger role in Arctic PAH contaminations alongside continually decreasing anthropogenic emissions and climate warming in the future.

Bioplastic production in terms of life cycle assessment:A state-of-theart review

The current transition to sustainability and the circular economy can be viewed as a socio-technical response to environmental impacts and the need to enhance the overall performance of the linear production and consumption paradigm.The concept of biowaste refineries as a feasible alternative to petroleum refineries has gained popularity.Biowaste has become an important raw material source for developing bioproducts and biofuels.Therefore,effective environmental biowaste management systems for the production of bioproducts and biofuels are crucial and can be employed as pillars of a circular economy.Bioplastics,typically plastics manufactured from bio-based polymers,stand to contribute to more sustainable commercial plastic life cycles as part of a circular economy in which virgin polymers are made from renewable or recycled raw materials.Various frameworks and strategies are utilized to model and illustrate additional patterns in fossil fuel and bioplastic feedstock prices for various governments'long-term policies.This review paper highlights the harmful impacts of fossil-based plastic on the environment and human health,as well as the mass need for eco-friendly alternatives such as biodegradable bioplastics.Utilizing new types of bioplastics derived from renewable resources(e.g.,biowastes,agricultural wastes,or microalgae)and choosing the appropriate end-of-life option(e.g.,anaerobic digestion)may be the right direction to ensure the sustainability of bioplastic production.Clear regulation and financial incentives are still required to scale from niche polymers to large-scale bioplastic market applications with a truly sustainable impact.

Ceftriaxone sodium degradation by carbon quantum dots(CQDs)-decorated C-doped a-Bi_(2)O_(3) nanorods

A novel carbon quantum dots decorated C-doped a-Bi_(2)O_(3)photocatalyst(CBO/CQDs)was synthesized by solvothermal method.The synergistic effect of adsorption and photocatalysis highly improved contaminants removal efficiencies.The ceftriaxone sodium degradation rate constant(k)of CBO/CQDs was 11.4 and 3.2 times that of pure a-Bi2O3 and C-doped a-Bi_(2)O_(3),respectively.The interstitial carbon doping generated localized states above the valence band,which enhanced the utilization of visible light and facilitated the separation of photogenerated electrons and holes;the loading of CQDs improved the charge carrier separation and extended the visible light response;the reduced particle size of CBO/CQDs accelerated the migration of photogenerated carriers.The·O2-and ht were identified as the dominant reactive species in ceftriaxone sodium degradation,and the key role of·O2-was further investigated by NBT transformation experiments.The Fukui index was applied to ascertain the molecular bonds of ceftriaxone sodium susceptible to radical attack,and intermediates analysis was conducted to explore the possible degradation pathways.The toxicity evaluation revealed that some degradation intermediates possessed high toxicity,thus the contaminants require sufficient mineralization to ensure safe discharge.The present study makes new insights into synchronous carbon dopping and CQDs decoration on modification of a-Bi2O3,which provides references for future studies.

Brake wear-derived particles:Single-particle mass spectral signatures and real-world emissions

Brake wear is an important but unregulated vehicle-related source of atmospheric particulate matter(PM).The single-particle spectral fingerprints of brake wear particles(BWPs)provide essential information for understanding their formation mechanism and atmospheric contributions.Herein,we obtained the single-particle mass spectra of BWPs by combining a brake dynamometer with an online single particle aerosol mass spectrometer and quantified real-world BWP emissions through a tunnel observation in Tianjin,China.The pure BWPs mainly include three distinct types of particles,namely,Bacontaining particles,mineral particles,and carbon-containing particles,accounting for 44.2%,43.4%,and 10.3%of the total BWP number concentration,respectively.The diversified mass spectra indicate complex BWP formation pathways,such as mechanical,phase transition,and chemical processes.Notably,the mass spectra of Ba-containing particles are unique,which allows them to serve as an excellent indicator for estimating ambient BWP concentrations.By evaluating this indicator,we find that approximately 4.0%of the PM in the tunnel could be attributable to brake wear;the real-world fleet-average emission factor of 0.28 mg km
1 veh
1 is consistent with the estimation obtained using the receptor model.The results presented herein can be used to inform assessments of the environmental and health impacts of BWPs to formulate effective emissions control policies.

Converting textile waste into value-added chemicals:An integrated bio-refinery process

The rate of textile waste generation worldwide has increased dramatically due to a rise in clothing consumption and production.Here,conversion of cotton-based,colored cotton-based,and blended cotton-polyethylene terephthalate(PET)textile waste materials into value-added chemicals(bioethanol,sorbitol,lactic acid,terephthalic acid(TPA),and ethylene glycol(EG))via enzymatic hydrolysis and fermentation was investigated.In order to enhance the efficiency of enzymatic saccharification,effective pretreatment methods for each type of textile waste were developed,respectively.A high glucose yield of 99.1%was obtained from white cotton-based textile waste after NaOH pretreatment.Furthermore,the digestibility of the cellulose in colored cotton-based textile wastes was increased 1.38e1.75 times because of the removal of dye materials by HPAC-NaOH pretreatment.The blended cotton
PET samples showed good hydrolysis efficiency following PET removal via NaOHeethanol pretreatment,with a glucose yield of 92.49%.The sugar content produced via enzymatic hydrolysis was then converted into key platform chemicals(bioethanol,sorbitol,and lactic acid)via fermentation or hydrogenation.The maximum ethanol yield was achieved with the white T-shirt sample(537 mL/kg substrate),which was 3.2,2.1,and 2.6 times higher than those obtained with rice straw,pine wood,and oak wood,respectively.Glucose was selectively converted into sorbitol and LA at a yield of 70%and 83.67%,respectively.TPA and EG were produced from blended cotton
PET via NaOHeethanol pretreatment.The integrated biorefinery process proposed here demonstrates significant potential for valorization of textile waste.

Generative adversarial networks for detecting contamination events in water distribution systems using multi-parameter,multi-site water quality monitoring

Contamination events in water distribution networks(WDNs)can have a huge impact on water supply and public health;increasingly,online water quality sensors are deployed for real-time detection of contamination events.Machine learning has been used to integrate multivariate time series water quality data at multiple stations for contamination detection;however,accurate extraction of spatial features in water quality signals remains challenging.This study proposed a contamination detection method based on generative adversarial networks(GANs).The GAN model was constructed to simultaneously consider the spatial correlation between sensor locations and temporal information of water quality indicators.The model consists of two networksda generator and a discriminatordthe outputs of which are used to measure the degree of abnormality of water quality data at each time step,referred to as the anomaly score.Bayesian sequential analysis is used to update the likelihood of event occurrence based on the anomaly scores.Alarms are then generated from the fusion of single-site and multi-site models.The proposed method was tested on a WDN for various contamination events with different characteristics.Results showed high detection performance by the proposed GAN method compared with the minimum volume ellipsoid benchmark method for various contamination amplitudes.Additionally,the GAN method achieved high accuracy for various contamination events with different amplitudes and numbers of anomalous water quality parameters,and water quality data from different sensor stations,highlighting its robustness and potential for practical application to real-time contamination events.

Deep learning-based prediction of effluent quality of a constructed wetland

Data-driven approaches that make timely predictions about pollutant concentrations in the effluent of constructed wetlands are essential for improving the treatment performance of constructed wetlands.However,the effect of the meteorological condition and flow changes in a real scenario are generally neglected in water quality prediction.To address this problem,in this study,we propose an approach based on multi-source data fusion that considers the following indicators:water quality indicators,water quantity indicators,and meteorological indicators.In this study,we establish four representative methods to simultaneously predict the concentrations of three representative pollutants in the effluent of a practical large-scale constructed wetland:(1)multiple linear regression;(2)backpropagation neural network(BPNN);(3)genetic algorithm combined with the BPNN to solve the local minima problem;and(4)long short-term memory(LSTM)neural network to consider the influence of past results on the present.The results suggest that the LSTM-predicting model performed considerably better than the other deep neural network-based model or linear method,with a satisfactory R^(2).Additionally,given the huge fluctuation of different pollutant concentrations in the effluent,we used a moving average method to smooth the original data,which successfully improved the accuracy of traditional neural networks and hybrid neural networks.The results of this study indicate that the hybrid modeling concept that combines intelligent and scientific data preprocessing methods with deep learning algorithms is a feasible approach for forecasting water quality in the effluent of actual engineering.

Excess mortality associated with high ozone exposure:A national cohort study in China

Emerging epidemiological studies suggest that long-term ozone(O_(3))exposure may increase the risk of mortality,while pre-existing evidence is mixed and has been generated predominantly in North America and Europe.In this study,we investigated the impact of long-term O_(3)exposure on all-cause mortality in a national cohort in China.A dynamic cohort of 20882 participants aged
40 years was recruited between 2011 and 2018 from four waves of the China Health and Retirement Longitudinal Study.A Cox proportional hazard regression model with time-varying exposures on an annual scale was used to estimate the mortality risk associated with warm-season(Aprile September)O_(3)exposure.The annual average level of participant exposure to warm-season O_(3)concentrations was 100 mg m^(-3)(range:61 e142 mg m^(-3)).An increase of 10 mg m^(-3)in O_(3)was associated with a hazard ratio(HR)of 1.18(95%confidence interval[CI]:1.13e1.23)for all-cause mortality.Compared with the first exposure quartile of O_(3),HRs of mortality associated with the second,third,and highest exposure quartiles were 1.09(95%CI:0.95e1.25),1.02(95%CI:0.88e1.19),and 1.56(95%CI:1.34e1.82),respectively.A J-shaped concentration eresponse associationwas observed,revealing a non-significant increase in risk below a concentration of approximately 110 mg m^(-3).Low-temperature-exposure residents had a higher risk of mortality associated with long-term O_(3)exposure.This study expands current epidemiological evidence from China and reveals that high-concentration O_(3)exposure curtails the long-term survival of middle-aged and older adults.

The Digital Agricultural Knowledge and Information System(DAKIS):Employing digitalisation to encourage diversified and multifunctional agricultural systems

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems.We present the Digital Agricultural Knowledge and Information System(DAKIS)to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture.To develop the DAKIS,we specified,together with stakeholders,requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools.The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity,the capacity to foster communication and cooperation between farmers and other actors,and the ability to link multiple spatiotemporal scales and sustainability levels.To overcome these challenges,the DAKIS provides a digital platform to support farmers'decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources.The approach integrates remote and in situ sensors,artificial intelligence,modelling,stakeholder-stated demand for biodiversity and ecosystem services,and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design,including natural and agronomic factors,economic and policy considerations,and socio-cultural preferences and settings.Ultimately,the DAKIS embeds the consideration of ecosystem services,biodiversity,and sustainability into farmers'decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers'objectives and societal demands.

Extracellular polymeric substances-antibiotics interaction in activated sludge:A review

Antibiotics,the most frequently prescribed drugs,have been widely applied to prevent or cure human and veterinary diseases and have undoubtedly led to massive releases into sewer networks and wastewater treatment systems,a hotspot where the occurrence and transformation of antibiotic resistance take place.Extracellular polymeric substances(EPS),biopolymers secreted via microbial activity,play an important role in cell adhesion,nutrient retention,and toxicity resistance.However,the potential roles of sludge EPS related to the resistance and removal of antibiotics are still unclear.This work summarizes the composition and physicochemical characteristics of state-of-the-art microbial EPS,highlights the critical role of EPS in antibiotics removal,evaluates their defense performances under different antibiotics exposures,and analyzes the typical factors that could affect the sorption and biotransformation behavior of antibiotics.Next,interactions between microbial EPS and antibiotic resistance genes are analyzed.Future perspectives,especially the engineering application of microbial EPS for antibiotics toxicity detection and defense,are also emphatically stressed.

Algal community structure prediction by machine learning

The algal community structure is vital for aquatic management.However,the complicated environmental and biological processes make modeling challenging.To cope with this difficulty,we investigated using random forests(RF)to predict phytoplankton community shifting based on multi-source environmental factors(including physicochemical,hydrological,and meteorological variables).The RF models robustly predicted the algal communities composed by 13 major classes(Bray-Curtis dissimilarity=9.2±7.0%,validation NRMSE mostly<10%),with accurate simulations to the total biomass(validation R^(2)>0.74)in Norway's largest lake,Lake Mjosa.The importance analysis showed that the hydro-meteorological variables(Standardized MSE and Node Purity mostly>0.5)were the most influential factors in regulating the phytoplankton.Furthermore,an in-depth ecological interpretation uncovered the interactive stress-response effect on the algal community learned by the RF models.The interpretation results disclosed that the environmental drivers(i.e.,temperature,lake inflow,and nutrients)can jointly pose strong influence on the algal community shifts.This study highlighted the power of machine learning in predicting complex algal community structures and provided insights into the model interpretability.

Microplastics in landfill leachate:Sources,detection,occurrence,and removal

Due to the accumulation of an enormous amount of plastic waste from municipal and industrial sources in landfills,landfill leachate is becoming a significant reservoir of microplastics.The release of microplastics from landfill leachate into the environment can have undesirable effects on humans and biota.This study provides the state of the science regarding the source,detection,occurrence,and remediation of microplastics in landfill leachate based on a comprehensive review of the scientific literature,mostly in the recent decade.Solid waste and wastewater treatment residue are the primary sources of microplastics in landfill leachate.Microplastic concentration in raw and treated landfill leachate varied between 0-382 and 0-2.7 items L^(−1).Microplastics in raw landfill leachate are largely attributable to local plastic waste production and solid waste management practices.Polyethylene,polystyrene,and polypropylene are the most prevalent microplastic polymers in landfill leachate.Even though the colors of microplastics are primarily determined by their parent plastic waste,the predominance of light-colored microplastics in landfill leachate indicates long-term degradation.The identified morphologies of microplastics in leachate from all published sources contain fiber and fragments the most.Depending on the treatment method,leachate treatment processes can achieve microplastic removal rates between 3%and 100%.The review also provides unique perspectives on microplastics in landfill leachate in terms of remediation,final disposal,fate and transport among engineering systems,and source reduction,etc.The landfill-wastewater treatment plant loop and bioreactor landfills present unique difficulties and opportunities for managing microplastics induced by landfill leachate.

Reimagining safe lithium applications in the living environment and its impacts on human,animal,and plant system

Lithium's(Li)ubiquitous distribution in the environment is a rising concern due to its rapid proliferation in the modern electronic industry.Li enigmatic entry into the terrestrial food chain raises many questions and uncertainties that may pose a grave threat to living biota.We examined the leverage existing published articles regarding advances in global Li resources,interplay with plants,and possible involvement with living organisms,especially humans and animals.Globally,Li concentration(<10 e300 mg kg
1)is detected in agricultural soil,and their pollutant levels vary with space and time.High mobility of Li results in higher accumulation in plants,but the clear mechanisms and specific functions remain unknown.Our assessment reveals the causal relationship between Li level and biota health.For example,lower Li intake(<0.6 mM in serum)leads to mental disorders,while higher intake(>1.5 mM in serum)induces thyroid,stomach,kidney,and reproductive system dysfunctions in humans and animals.However,there is a serious knowledge gap regarding Li regulatory standards in environmental compartments,and mechanistic approaches to unveil its consequences are needed.Furthermore,aggressive efforts are required to define optimum levels of Li for the normal functioning of animals,plants,and humans.This review is designed to revitalize the current status of Li research and identify the key knowledge gaps to fight back against the mountainous challenges of Li during the recent digital revolution.Additionally,we propose pathways to overcome Li problems and develop a strategy for effective,safe,and acceptable applications.

Co-developing an international TLS network for the 3D ecological understanding of global trees:System architecture,remote sensing models,and functional prospects

Trees are spread worldwide,as the watchmen that experience the intricate ecological effects caused by various environmental factors.In order to better understand such effects,it is preferential to achieve finely and fully mapped global trees and their environments.For this task,aerial and satellite-based remote sensing(RS)methods have been developed.However,a critical branch regarding the apparent forms of trees has significantly fallen behind due to the technical deficiency found within their globalscale surveying methods.Now,terrestrial laser scanning(TLS),a state-of-the-art RS technology,is useful for the in situ three-dimensional(3D)mapping of trees and their environments.Thus,we proposed co-developing an international TLS network as a macroscale ecotechnology to increase the 3D ecological understanding of global trees.First,we generated the system architecture and tested the available RS models to deepen its ground stakes.Then,we verified the ecotechnology regarding the identification of its theoretical feasibility,a review of its technical preparations,and a case testification based on a prototype we designed.Next,we conducted its functional prospects by previewing its scientific and technical potentials and its functional extensibility.Finally,we summarized its technical and scientific challenges,which can be used as the cutting points to promote the improvement of this technology in future studies.Overall,with the implication of establishing a novel cornerstone-sense ecotechnology,the co-development of an international TLS network can revolutionize the 3D ecological understanding of global trees and create new fields of research from 3D global tree structural ecology to 3D macroecology.

Photocatalytic synergistic biofilms enhance tetracycline degradation and conversion

Tetracyclines are refractory pollutants that cause persistent harm to the environment and human health.Therefore,it is urgently necessary to develop methods to promote the efficient degradation and conversion of tetracyclines in wastewater.This report proposes a photobiocatalytic synergistic system involving the coupling of GeO_(2)/Zn-doped phosphotungstic acid hydrate/TiO_(2)(GeO_(2)/Zn-HPW/TiO_(2))-loaded photocatalytic optical hollow fibers(POHFs)and an algalebacterial biofilm.The GeO_(2)/Zn-HPW/TiO_(2) photocatalyst exhibits a broad absorption edge extending to 1000 nm,as well as high-efficiency photoelectric conversion and electron transfer,which allow the GeO_(2)/Zn-HPW/TiO_(2)-coated POHFs to provide high light intensity to promote biofilm growth.The resulting high photocatalytic activity rapidly and stably reduces the toxicity and increases the biodegradability of tetracycline-containing wastewater.The biofilm enriched with Salinarimonas,Coelastrella sp.,and Rhizobium,maintains its activity for the rapid photocatalytic degradation and biotransformation of intermediates to generate the O_(2) required for photocatalysis.Overall,the synergistic photocatalytic biofilm system developed herein provides an effective and efficient approach for the rapid degradation and conversion of water containing high concentrations of tetracycline.

Halomethoxybenzenes in air of the Nordic region

Halomethoxybenzenes(HMBs)are a group of compounds with natural and anthropogenic origins.Here we extend a 2002e2015 survey of bromoanisoles(BAs)in the air and precipitation at Rå€o on the Swedish west coast and Pallas in Subarctic Finland.New BAs data are reported for 2018 and 2019 and chlorinated HMBs are included for these and some previous years:drosophilin A methyl ether(DAME:1,2,4,5-tetrachloro-3,6-dimethoxybenzene),tetrachloroveratrole(TeCV:1,2,3,4-tetrachloro-5,6-dimethoxybenzene),and pentachloroanisole(PeCA).The order of abundance of HMBs at Råo was SBAs>DAME>TeCV>PeCA,whereas at Pallas the order of abundance was DAME>SBAs>TeCA>PeCA.The lower abundance of BAs at Pallas reflects its inland location,away from direct marine influence.Clausius-Clapeyron(CC)plots of log partial pressure(Pair)/Pa versus 1/T suggested distant transport at both sites for PeCA and local exchange for DAME and TeCV.BAs were dominated by distant transport at Pallas and by both local and distant sources at Rå€o.Relationships between air and precipitation concentrations were examined by scavenging ratios,SR=(ng m^(-3))precip/(ng m^(-3))air.SRs were higher at Pallas than Rå€o due to greater Henry's law partitioning of gaseous compounds into precipitation at colder temperatures.DAME is produced by terrestrial fungi.We screened 19 fungal species from Swedish forests and found seven of them contained 0.01e3.8 mg DAME per kg fresh weight.We suggest that the volatilization of DAME from fungi and forest litter containing fungal mycelia may contribute to atmospheric levels at both sites.