Innovative spiral electrode configuration for enhancement of electrocoagulation-flotation.

The performance of electrocoagulation-flotation (ECF) process can profoundly be affected by the reactor design and electrode configuration. These may, in turn, influence the removal efficiency, flow hydrodynamic, floc formation, and flotation/settling characteristics. The present work aimed at developing a new spiral electrode configuration to enhance the ECF process. To do so, the impacts of parameters such as energy consumption, removal efficiency of the contaminants from industrial wastewater with a composition of turbidity, emulsified oil, and heavy metals (Si, Zn, Pb, Ni, Cu, Cr, and Cd), as well as stirring speed and foaming have been investigated. Comparison was also made between the experimental results of the new electrode configuration with the conventional rectangular cell with plate electrode configuration with the same volume and electrode surface area. The findings revealed that energy consumption of the spiral electrode configuration within the operating times of 10, 20, 30, 32, 48, and 70 min, was approximately 20% lower compared to that of the conventional ECF. Moreover, the maximum and minimum removal efficiency of 97% and 60% were obtained for turbidity and TOC for the stirring speed of 500 rpm and Reynolds number of 10,035, respectively. Finally, the formed gas bubbles tilted toward the center due to the enhanced flow hydrodynamic which resulted in substantial reduction of foam formation.

Investigating non-point pollution mitigation strategies in response to changing environments: A cross-regional study in China and Germany.

Climate change and urbanization have altered regional hydro-environments. Yet, the impact of future changes on the pollution risk and associated mitigation strategies requires further exploration. This study proposed a hydraulic and water-quality modeling framework, to investigate the spatiotemporal characteristics of pollution risk mitigation by low impact development (LID) strategies under future Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP) scenarios. Results demonstrated that the LID strategies exhibited an effective performance of pollutant removal in the current hydro-environment, with the removal rates ranging from 33% to 56%. In future climate and urbanization scenarios, the LID performance declined and turned to be uncertain as the greenhouse gas (GHG) emissions increased, with the removal rates ranging from 12% to 59%. Scenario analysis suggested that the LID performance was enhanced by a maximum of 73% through the diversified implementation of LID practices, and the performance uncertainty was reduced by a maximum of 67% through the increased LID deployment. In addition, comparative analysis revealed that the LID strategies in a well-developed region (Dresden, Germany) were more resilient in response to changing environments, while the LID strategy in a high-growth region (Chaohu, China) exhibited a better pollutant removal performance under low-GHG scenarios. The methods and findings in this study could provide additional insights into sustainable water quality management in response to climate change and urbanization.

Bayesian-Based Approaches to Exploring the Long-Term Alteration in Trace Metals of Surface Water and Its Driving Forces.

Trace metal pollution poses a serious threat to the aquatic ecosystem. Therefore, characterizing the long-term environmental behavior of trace metals and their driving forces is essential for guiding water quality management. Based on a long-term data set from 1990 to 2019, this study systematically conducted the spatiotemporal trend assessment, influential factor analysis, and source apportionment of trace elements in the rivers of the German Elbe River basin. Results show that the mean concentrations of the given elements in the last 30 years were found in the order of Fe (1179.5 ± 1221 µg·L-1) ≫ Mn (209.6 ± 181.7 µg·L-1) ≫ Zn (52.5 ± 166.2 µg·L-1) ≫ Cu (5.3 ± 5.5 µg·L-1) > Ni (4.4 ± 8.3 µg·L-1) > Pb (3.3 ± 4.4 µg·L-1) > As (2.9 ± 2.3 µg·L-1) > Cr (1.8 ± 2.4 µg·L-1) ≫ Cd (0.3 ± 1.1 µg·L-1) > Hg (0.05 ± 0.12 µg·L-1). Wavelet analyses show that river flow regimes and flooding dominated the periodic variations in metal pollution. Bayesian network suggests that the hydrochemical factors (i.e., TOC, TP, TN, pH, and EC) chemically influenced the metal mobility between water and sediments. Furthermore, the source apportionment computed by the Bayesian multivariate receptor model shows that the given element contamination was typically attributed to the geogenic sources (17.5, 95% confidence interval: 13.1-17.6%), urban and industrial sources (22.1, 18.0-27.2%), arable soil erosion (24.2, 16.4-31.5%), and historical anthropogenic activities (35.2, 32.8-43.3%). The results provided herein reveal that both the hydrochemical influence on metal mobility and the chronic disturbance from anthropogenic activities caused the long-term variation in trace metal pollution.

Regional and temporal differences in the relation between SARS-CoV-2 biomarkers in wastewater and estimated infection prevalence - Insights from long-term surveillance.

Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of public health related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a complementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants in the region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third and fourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNA concentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression models quantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is site and time specific. Median loads per diagnosed case differed by a factor of 3-4 among sites during both waves and were on average 45 % higher during the third wave. In most cases, log-log-transformed data achieved better regression performance than non-transformed data and local calibration outperformed global models for all sites. The inclusion of lag/lead time, discharge and detection probability improved model performance in all cases significantly, but the importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher than 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation from individual testing statistics, but revealed pronounced differences throughout the epidemic waves and among the different sites.

Towards a decentralized solution for sewer leakage detection - a review.

Sewer pipelines often leak due to physical, operational, and environmental deterioration factors. Due to the hidden infrastructure of the sewer systems, leakage detection is often costly, challenging, and crucial at the city scale. Various sewer inspection methods (SIMs) have been developed and implemented at this time. This study evaluates the existing SIMs and categorizes them based on their area of impact (AoI) into three classes. Tier-one (T-I) methods, such as deterioration models and hotspot mapping, tend to grasp a broader and reliable understanding of the sewer systems' structural health and pinpoint the network sections that are more prone to leakage. As an intermediate solution, Tier-two (T-II) non-destructive methods, such as aerial thermal imagery (ATI) and electrical resistivity tomography (ERT), inspect the potential pipe clusters regardless of their material and visualize the leaked plume generated from defects and cracks. Tier-three (T-III) methods include in-pipe SIMs, such as visual and multi-sensory inspections, that can provide an in-depth understanding of the pipe and its deterioration stage. In this study, we suggest that a sustainable sewer inspection plan should include at least two SIMs belonging to different tiers to provide a dual investigation of precision and AoI, a balance between cost and time as well as an equilibrium between self-sufficiency and decentralization.

Occurrences, transport drivers, and risk assessments of antibiotics in typical oasis surface and groundwater.

Intensive use of antibiotics affects biogeochemical cycles and stimulates the evolution of antibiotic resistance, thus threatening global health and social development. The spatiotemporal distributions of antibiotics in single aqueous matrices have been widely documented; however, their occurrence in surface-groundwater systems has received less attention, especially in arid regions that usually have fragile ecosystems. Therefore, we investigated the occurrence of thirty-one antibiotics in the surface water and adjacent groundwater in the Xinjiang Uygur Autonomous Region, China. The results showed that the total concentrations of detected antibiotics varied from 17.37 to 84.09 ng L-1 and from 16.38 to 277.41 ng L-1 in surface and groundwater, respectively. The median concentration of antibiotics showed the pattern of norfloxacin (4.86 ng L-1) > ciprofloxacin (3.93 ng L-1) > pefloxacin (3.39 ng L-1) in surface water; whereas in groundwater, this was in the order of pefloxacin (6.30 ng L-1) > norfloxacin (4.33 ng L-1) > ciprofloxacin (2.68 ng L-1). Heatmap analysis indicated that vertical infiltration had limited effects on antibiotic exchange in surface-ground water systems because of the high potential evaporation and low water storage. Redundancy analysis suggested that the oxidation-reduction potential (p < 0.01) and dissolved oxygen (p < 0.05) jointly affected the distribution of antibiotics in surface water. Ecological risk assessment showed that antibiotics in 98.9% of surface water and 99.1% of groundwater did not pose significant risks to aquatic species. The findings of this study will help develop effective mitigation strategies for antibiotics in aquatic environments.

Global trade drives transboundary transfer of the health impacts of polycyclic aromatic hydrocarbon emissions.

International trade leads to a redistribution of pollutant emissions related to the production of goods and services and subsequently affects their severe health impacts. Here, we present a framework of emissions inventories, input-output model, numerical atmospheric chemistry model, and estimates of the global burden of disease. Specifically, we assess emissions and health impacts of polycyclic aromatic hydrocarbons (PAH), a carcinogenic byproduct of production activities, and consider income, production, final sale, and consumption stages of the global supply chain between 2012 and 2015. We find that in 2015, global anthropogenic PAH emissions were 304 Gg (95% CI: 213~421 Gg) and estimated related lifetime lung cancer deaths were 6.9 × 104 (95% CI: 1.8 × 104~1.5 × 105 deaths). The role of trade in driving the PAH-related health risks was greater than that in driving the emissions. Our findings indicate that international cooperation is needed to optimise the global supply chains and mitigate PAH emissions and health impacts.

Ecological risk and machine learning based source analyses of trace metals in typical surface water.

Surface water is threatened by trace metal pollution due to increasing anthropogenic activities. Therefore, an appropriate source identification was essential to reduce the ecological risk posed by the given pollutants. In this study, shallow and deep learning approaches trained by a registered environmental dataset of discharge sources were employed to classify the potential emission sources of trace metals in the Elbe River, Germany. The results showed that the overall concentration rank of the given metals was Zn (226.5 ± 526.5 µg·L-1) > Ni (5.6 ± 4.7 µg·L-1) > Cu (5.3 ± 5.8 µg·L-1) > As (3.3 ± 3.7 µg·L-1) > Pb (2.9 ± 5.2 µg·L-1) > Cr (1.8 ± 2.5 µg·L-1) > Cd (1.3 ± 3.1 µg·L-1) in seven tributaries and the mainstream of the Elbe River, among which the tributary Triebisch had the highest risk quotient over 86. Random Forest outperformed other algorithms with the highest Kappa median values of 0.59 and the lowest Hamming-loss values of 0.22 in extraction of the majority voted class. Then, the source apportionment conducted by random forest suggested that wastewater disposal and metal industrial emissions were the source contributors in the tributary Triebisch (probabilities: 0.39, 0.3), upstream segment (0.45, 0.25), and downstream segment (0.32, 0.23) of the given river. Additional sources of mineral industry emissions were found in the upstream segment (0.21) and downstream segment (0.22). The data provided herein suggest that random forest would be an effective approach to identify pollutants in aquatic environments and could assist source-oriented adaptive management.

Characterizing the long-term occurrence of polycyclic aromatic hydrocarbons and their driving forces in surface waters.

As carcinogenic and ubiquitous pollutants, an in-depth understanding of the long-term environmental behaviors of polycyclic aromatic hydrocarbons (PAHs) and their driving forces is crucial for reducing human health risks. Based on long-term monitoring data from 2001 to 2016, this study systematically investigated the temporal and seasonal trends, periodic oscillation, source apportionment, and human health risks of PAHs in eight rivers in the Free State of Saxony, Germany. The results showed that the annual average ∑16PAHs (sum of 16 PAH concentrations) ranged from 28.2 ng L-1 to 202 ng L-1. Using the Mann-Kendall test, a trend of decreasing PAH concentrations was determined (slope range: -0.103 to -0.0159). Wavelet analysis indicated that the most significant periodic oscillation of PAHs was 10-30 months, with more pollution in winter. Source apportionment analysis suggested that vehicular emissions and coal combustion contributed the most to PAH concentrations (20.6-40.3% and 21.7-41.4%, respectively) and related health risks (54.1-80.1% and 5.61-37.9%, respectively). Furthermore, the risks (oral lifetime: 4.24×10-7-1.34×10-6; dermal lifetime: 2.86×10-5-9.05×10-5) were determined to be low. The data revealed that the substitution of petroleum and coal with cleaner energy would facilitate the mitigation of PAHs.

Transmission risk of SARS-CoV-2 in the watershed triggered by domestic wastewater discharge.

The outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has already become an unprecedented global pandemic. However, the transmission of SARS-CoV-2, especially the protected SARS-CoV-2 RNA (pRNA) with infectious particles in waterways, is still largely unexplored. In this study, we developed a model to estimate SARS-CoV-2 transmission from the risk source in the excretion of patients to the final exposure in surface water. The model simulated the spatial and temporal distribution of the viral pRNA concentrations in the surface water of the Elbe watershed from March 2020 to January 2021. The results show that the WWTPs with the maximum capacity of >10,000 population equivalents were responsible for 95% of the viral load discharged into the surface water. We estimated the pRNA concentrations in surface water to be 1.33 × 10-2 copies·L-1 on average in the watershed based on the model simulation on viral transmission. It had considerable variations in spatial and temporal scales, which are dominantly controlled by epidemic situations and virus transport with decay in water, respectively. A quantitative microbial risk assessment was conducted to estimate the viral infection probability from surface water ingestion with consideration of the influence of toilet usage frequency and gender/age population groups. All the infection probabilities in the study period were lower than the reference risk levels of 10-4 and 10-5. The individuals aged 15-34 years had the highest infection probability of 4.86 × 10-9 on average from surface water ingestion during swimming activities. The data provided herein suggest that the low pRNA concentrations and infection probability reflected that the waterways were unlikely to be a significant transmission route for SARS-CoV-2.

Global Trends and Drivers in Consumption- and Income-Based Emissions of Polycyclic Aromatic Hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) are a class of the most hazardous substances. As unavoidable byproducts of petrogenic and pyrogenic processes, their emissions are dominantly linked to various economic sectors. In international trade, not only final consumption but also primary input can transfer the emissions among regions. Therefore, a long-term impact assessment of the international trade on PAH global emissions based on the final consumption and primary input could significantly benefit worldwide PAH mitigation strategies. This study investigated the changes in consumption- and income-based PAH emissions and interregional flows of worldwide regions, using the latest available data from 1999 to 2014. Results show that in 2014, 16.8 and 10.1% of global PAH emissions were transferred by consumption and primary input through international trade. Meanwhile, the production-, consumption-, and income-based emissions in most regions were decreasing. Furthermore, from the consumption-based perspective, sub-Saharan Africa surpassed China and became the largest net exporter of consumption-based emissions. From the income-based perspective, the net income-based outflows of India and the rest of Asia increased significantly, indicating the income-based emission leakage in emerging markets. From the socioeconomic perspective, emission intensity dominated the global decline in PAH emissions. As the two main factors driving the increase in emissions, the primary input structure (41%) had a larger effect than the final demand level (28%) from 1999 to 2014. Therefore, global cooperation, through the mitigation strategies of reducing emission factors and improving international trade patterns, is posited as an efficient strategy to reduce PAH pollution and related health risks.

Organic matter parameters in WWTP - a critical review and recommendations for application in activated sludge modelling.

This paper includes a comprehensive literature review of sludge composition data from wastewater treatment plants. 722 data sets from 249 sources were used to establish typical ratios between COD and solids-based parameters and to verify rule-of-thumb values, respectively. Confirmation of these typical ratios can also be accomplished by using biochemical composition data. It is shown that a correlation between data from proteins, lipids and carbohydrates analysis can be related to COD/VSS ratios. Finally, using the findings from the literature review, the organic and inorganic conversion factors of COD fractions in activated sludge models are adjusted to solids-based parameters. It was shown that with the adjustments of the factors and a partition of the particulate inert fraction into a fraction assigned to the influent and a fraction assigned to the endogenous products, a better agreement with the ratios of COD/VSS in the individual sludge streams can be established.

Growth of science in activated sludge modelling - a critical bibliometric review.

In this paper, the tool of bibliometric analysis is applied to the field of activated sludge modelling and its suitability as a first step of a literature analysis is assessed. The analysis is applied to the total dataset considered as well as a time-based classification. It can be shown that this tool is very well suited to filtering the relevant authors and publications, thus enabling a subsequent visual review. The methodology presented can also be applied to sub-disciplines or other subject areas. However, the sole use of the multiple statistical and visual tools is critically questioned. Thus, misinterpretations and apparent findings can result from structural problems in the data or parameters used. Not all of the metrics used are suitable for finding relevant publications, but rather for ranking the criteria studied. However, the latter represents the most widespread application of bibliometrics. From the analysis of the keywords, it could be deduced that there has been a temporal shift from fundamental model aspects to detailed questions such as the integration of sorption and adsorption processes or anaerobic digestion. The modelling of biological phosphorus removal has also surprisingly lost a great amount of importance in the scientific literature.

Consumption- and Income-Based Sectoral Emissions of Polycyclic Aromatic Hydrocarbons in China from 2002 to 2017.

China is the largest emitter of polycyclic aromatic hydrocarbons (PAHs) in the world. Because of their negative influences on human health, the characteristics and potential driving forces of PAH emissions should be evaluated to establish effective mitigation strategies for different economic sectors. This study is the first to quantify the embodied and enabled PAH emissions of 108 sectors in China in 2002, 2007, 2012, and 2017. The results show that the total sectoral emissions increased by 92% (from 28.0 to 53.7 kt) from 2002 to 2012 and decreased to 53.0 kt in 2017. The eight aggregated sectors had different characteristics according to their production-, consumption-, and income-based emissions. Both the embodied and enabled emission flows increased (from 13.8 to 29.2 kt and from 11.3 to 20.5 kt, respectively) with time. The influences of the major final demands and primary inputs reversed from increasing to decreasing emissions over time. In particular, the primary input structure had a stronger impact on decreasing emissions than the final demand structure. The results revealed that different mitigation policies should be applied to different sectors and that adjusting primary input behaviors might be a relatively efficient method to reduce PAH emissions.

Impact of green infrastructure on the mitigation of road-deposited sediment induced stormwater pollution.

As a vital stormwater pollution source, the pollutants associated with road-deposited sediment (RDS) have become a growing concern in urban water management. Green infrastructure has exhibited great potential in stormwater pollution mitigation, but is not comprehensively understood yet due to the influences of complex RDS-associated pollutant migration processes (i.e., build-up, wash-off, and discharge). In this study, a city-scale hydraulic and water quality model was used to analyze the migration and removal processes of four RDS-associated pollutants (total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP)) under different hydrological patterns, land-cover types, and green infrastructure installation locations. Results show that the antecedent dry-weather period was the main factor influencing RDS build-up, while the precipitation pattern strongly impacted RDS wash-off, discharge, and removal. The downstream-installed green infrastructures reduced the RDS-induced stormwater pollution by up to 68% and relieved the pollution-mitigation pressure of the studied drainage networks by almost 50%. The TSS and COD removal rates were higher (62.22-68.09%) near green space, while those of TN and TP were higher around buildings and roads (40.00-62.50%). Sensitivity analysis indicated that seven parameters regarding the surface layer characteristics and soil texture class strongly impacted the pollution-mitigation performance among the 31 technical parameters of green infrastructure. The results of this study would assist urban water management by optimizing green infrastructure for stormwater pollution mitigation.

Influence of synthetic wastewater on entrapped air on the isotactic and atactic polypropylene microplastic surfaces.

The municipal wastewater collection system is recognized as an initial point of interaction between microplastics (MPs) and the urban wastewater matrix. The raw wastewater contains a wide variety of organic and inorganic substances including chemicals and heavy metals. However, the fate of MPs in urban sewer systems is not yet well understood. In this work two types of virgin polypropylene (PP) samples, isotactic (iPP) and atactic (aPP), were exposed to two synthetic wastewater solutions in order to study their effects on the physical properties of the hydrophobic polymer surfaces. Particular attention was paid to the pollution adhesion at the air-liquid-solid interfaces of the surface air pockets entrapped on the polymer surfaces. The first wastewater solution consists of mixed fat, oil and grease (FOG) - surfactant and another which is an exclusively contained wastewater surfactant. The interaction experiment over a period of 10 min between the polymer's air pocket and solutions indicated that the size of the bubble in the mixed FOG-surfactant solution increased more pronouncedly for iPP (%152) in contrast to aPP (%31) and was also compared with the greater surface roughness of the polymers. The size variation of the spherical cap on the immersed polymer surfaces were measured between 17 µm and 85 µm using image processing techniques while the data was analyzed by the Young-Laplace equation. The corresponding technical surface roughness of the polymers, the surface tension of the liquids and their air/water contact angle on the flat polymer surfaces were also measured. The results of this study indicated that surface air pockets influence the adsorption capacity of MPs and thus their buoyancy and contamination potential.

Characterizing the anthropogenic-induced trace elements in an urban aquatic environment: A source apportionment and risk assessment with uncertainty consideration.

The spatial distribution of water quality status, especially in water bodies near intensively urbanized areas, is tightly associated with patterns of human activities. For establishing a robust assessment of the sediment quality in an urban aquatic environment, the source apportionment and risk assessment of Cr, Mn, Ni, Cu, Zn, As, Cd, Hg, and Pb in sediments from an anthropogenic-influenced lake were carried out with considering uncertainties from the analysis methods, random errors in the sample population and the spatial sediment heterogeneity. The distribution analysis of the trace metals with inverse distance weighting-determined method showed that the pollutants were concentrated in the middle and southern areas of the lake. According to the self-organizing map and constrained positive matrix factorization receptor model, agricultural sources (24.8%), industrial and vehicular sources (42.5%), and geogenic natural sources (32.7%) were the primary contributors to the given metals. The geogenic natural had the largest random errors, but the overall result was reliable according to the uncertainty analysis. Furthermore, the stochastic contamination and ecological risk models identified a moderate/considerable contamination level and a moderate ecological risk to the urban aquatic ecosystem. With consideration of uncertainties from the spatial heterogeneity, the contamination level of Hg, and the ecological risk of Cd in had a 20-30% probability of the increase.

A comparative analysis of artificial neural networks and wavelet hybrid approaches to long-term toxic heavy metal prediction.

The occurrence of toxic metals in the aquatic environment is as caused by a variety of contaminations which makes difficulty in the concentration prediction. In this study, conventional methods of back-propagation neural network (BPNN) and nonlinear autoregressive network with exogenous inputs (NARX) were applied as benchmark models. Explanatory variables of Fe, pH, electrical conductivity, water temperature, river flow, nitrate nitrogen, and dissolved oxygen were used as different input combinations to forecast the long-term concentrations of As, Pb, and Zn. The wavelet transformation was applied to decompose the time series data, and then was integrated with conventional methods (as WNN and WNARX). The modelling performances of the hybrid models of WNN and WNARX were compared with the conventional models. All the given models were trained, validated, and tested by an 18-year data set and demonstrated based on the simulation results of a 2-year data set. Results revealed that the given models showed general good performances for the long-term prediction of the toxic metals of As, Pb, and Zn. The wavelet transform could enhance the long-term concentration predictions. However, it is not necessarily useful for each metal prediction. Therefore, different models with different inputs should be used for different metals predictions to achieve the best predictions.

Is There a Role for Environmental and Metabolic Factors Predisposing to Severe COVID-19?

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic affects people around the world. However, there have been striking differences in the number of infected individuals and deaths in different countries. Particularly, within Central Europe in countries that are similar in ethnicity, age, and medical standards and have performed similar steps of containment, such differences in mortality rates remain inexplicable. We suggest to consider and explore environmental factors to explain these intriguing variations. Countries like Northern Italy, France, Spain, and UK have suffered from 5 times more deaths from the corona virus infection than neighboring countries like Germany, Switzerland, Austria, and Denmark related to the size of their respective populations. There is a striking correlation between the level of environmental pollutants including pesticides, dioxins, and air pollution such as NO2 known to affect immune function and healthy metabolism with the rate of mortality in COVID-19 pandemic in these European countries. There is also a correlation with the use of chlorination of drinking water in these regions. In addition to the improvement of environmental protective programs, there are possibilities to lower the blood levels of these pollutants by therapeutic apheresis. Furthermore, therapeutic apheresis might be an effective method to improve metabolic inflammation, altered vascular perfusion, and neurodegeneration observed as long-term complications of COVID-19 disease.

Effect of anthropogenic activities on the occurrence of polycyclic aromatic hydrocarbons in aquatic suspended particulate matter: Evidence from Rhine and Elbe Rivers.

As carcinogenic and pervasive pollutants, polycyclic aromatic hydrocarbons (PAHs) in surface water are crucial to environmental policies, and the understanding of their trends and influencing factors is critical for achieving a good chemical and ecological status of water bodies. Based on long-term monitoring data from 1998 to 2017, this study systematically evaluated the spatiotemporal distribution, multimedia transport, fate, and source apportionment of PAHs adsorbed on suspended particulate matter (SPM) in Rhine and Elbe Rivers. The results of the Mann-Kendall test indicated that pollution levels of PAHs decreased from 2.81×105µg⋅s-1 to 9.80×104µg⋅s-1 on average in the Rhine and from 1.60×105 µg⋅s-1 to 5.21×104 µg⋅s-1 in the Elbe in the last 20 years. Spatially, SPM near urban areas had higher PAH mass fluxes (Rhine:3.07×105µg⋅s-1, Elbe: 1.73×105µg⋅s-1) and greater rates of decrease (slopes for Rhine and Elbe: -409, -323) than those near rural areas (Rhine:1.41×105 µg⋅s-1, Elbe: 9.35×104µg⋅s-1; slopes for Rhine and Elbe: -128, -89), indicating the significant influence of anthropogenic activities. Wavelet analysis showed that the pollution level of PAH had significant periodic oscillations for the Rhine and Elbe, and revealed several abrupt change points for the two rivers. A multimedia fugacity model demonstrated that impervious surfaces had the highest concentration (Rhine: 1.84g⋅m-3, Elbe: 0.15g⋅m-3), while soil (Rhine: 8.33×107g, Elbe: 2.53×106g) and sediments (Rhine: 4.85×106g, Elbe: 1.31×106g) had higher masses of PAHs. Furthermore, source apportionment computed using a self-organizing map and positive matrix factorization model suggested that the major sources of PAHs were vehicular emissions and coal combustion, which accounted for 51.86% of the total mass in the Rhine and 62.92% in the Elbe. The data revealed that the long-term trends of PAH variation were associated with changes in energy consumption and the implementation of vehicular emission standards. Therefore, the substitution of coal and petroleum with renewable energies could assist strategies of PAH mitigation in the environment and gradual reduction of pollution levels.