Wastewater Discharge Transports Riverine Microplastics over Long Distances.

Wastewater discharge from wastewater treatment plants continuously pumps microplastics into rivers, yet their transport distances within these waterways remain unknown. Herein, we developed a conceptual framework by synthesizing the microplastic data from the Yangtze River Basin to evaluate its transport distances, quantifying a significant spatial dependence between large-scale wastewater discharge and riverine microplastics (p < 0.05). The presence of microplastics at a specific sampling site could be attributed to wastewater discharge within a large-scale range spanning >1000 km upstream, encompassing a substantial portion equivalent to one-third of the Yangtze River Basin. The dominance analysis indicated that the contribution of wastewater discharge in rivers with higher discharge (>100 m3/s) to riverine microplastic pollution exceeded 65% within the Yangtze River Basin. The spatial dependence framework of riverine microplastics on wastewater discharge advances our prior understanding of the prevention and control of riverine microplastics by demonstrating that such pollution is not limited to nearby environmental factors.

Development and application of a multi-centre cloud platform architecture for water environment management.

To promote the intelligent and accurate management of river basins, especially large basins which involve many catchments, it is highly required to develop a useful platform to effectively coordinate arithmetic resources and data, and simultaneously help to make decisions based on the real-time calculation. In this study, a multi-centre cloud platform architecture called 3L4C was constructed, which includes a Cloud-edge-terminal Layer (3L), data centre, model centre, control centre, and customer-service centre (4C). Data fusion technology and an air-land-water coupled model were constructed. Based on HTML5, JavaScript, and Java, an integrated water environment management platform was created and applied to the Three Gorges Reservoir Basin, China. The platform was tested and successfully used for automatic water quality prediction, water environment pollution analysis and control, early warning of abnormal water quality, and emergency water pollution incident evaluation. This platform quickly and accurately forecasts and perfectly displays past, present and future state of the water environment, and offers beneficial support for management decisions in various water environment departments.

How does anthropogenic activity influence the spatial distribution of dissolved organic matter in rivers of a typical basin located in the Loess Plateau, China.

River ecosystems interact strongly with adjacent terrestrial environments and receive dissolved organic matter (DOM) from a variety of sources, all of which are vulnerable to human activities and natural processes. However, it is unclear how and to what extent human and natural factors drive DOM quantity and quality changes in river ecosystems. Here, three fluorescence components were identified via optical techniques, including two humic-like substances and one protein-like component. The protein-like DOM was mainly accumulated in anthropogenically impacted regions, while humic-like components exhibit the opposite trend. Furthermore, the driving mechanisms of both natural and anthropogenic factors on the variations in DOM composition were investigated using partial least squares structural equation modelling (PLS-SEM). Human activities, especially agriculture, positively influence the protein-like DOM directly by enhancing anthropogenic discharge with protein signals and also indirectly by affecting water quality. Water quality directly influences the DOM composition by stimulating in-situ production through a high nutrient load from anthropogenic discharge and inhibiting the microbial humification processes of DOM due to higher salinity levels. The microbial humification processes can also be restricted directly by a shorter water residence time during the DOM transport processes. Furthermore, protein-like DOM was more sensitive to direct anthropogenic discharge than indirect in-situ production (0.34 vs. 0.25), especially from non-point source input (39.1%), implying that agricultural industry optimization may be an efficient way to improve water quality and reduce protein-like DOM accumulation.

Methodology for a preliminary assessment of water use sustainability in industries at sub-basin level.

The sustainability of industrial production, especially for highly water-demanding processes, is strictly related to water resource availability and to the dynamic interactions between natural and anthropogenic requirements over the spatial and temporal scales. The increase in industrial water demand raises the need to assess the related environmental sustainability, facing the occurrence of global and local water stress issues. The identification of reliable methodologies, based on simple indices and able to consider the impact on local water basins, may play a basilar role in water sustainability diagnosis and decision-making processes for water management and land use planning. The present work focalized on the definition of a methodology based on the calculation of indicators and indices in the view of providing a synthetic, simple, and site-specific assessment tool for industrial water cycle sustainability. The methodology was built starting from geo-referenced data on water availability and sectorial uses derived for Italian sub-basins. According to the data monthly time scale, the proposed indices allowed for an industrial water-related impacts assessment, able to take into account the seasonal variability of local resources. Three industrial factories, located in northern (SB1, SB2) and central (SB3) Italian sub-basins, were selected as case studies (CS1, CS2, CS3) to validate the methodology. The companies were directly involved and asked to provide some input data. The methodology is based on the calculation of three synthetic indexes: the Withdrawal and Consumption water Stress Index (WCSI) allowed for deriving a synthetic water stress level assessment at the sub-basin scale, also considering the spatial and temporal variations; the industrial water use sustainability assessment was achieved by calculating the Overall Factory-to-Basin Impact (OFBI) and the Internal Water Reuse (IWR) indices, which allowed a preliminary evaluation of the factories' impacts on the sub-basin water status, considering the related water uses and the overall pressures on the reference territorial context. The WCSI values highlighted significant differences between the northern sub-basins, characterised by limited water stress (WCSISB1 = 0.221; WCSISB2 = 0.047), and the central ones, more subjected to high stress (WCSISB3 = 0.413). The case studies CS1 and CS3 showed to exert a more significant impact on the local water resource (OFBICS1 = 0.18%; OFBICS2 = 0.192%) with respect to CS2 (OFBI = 0.002%), whereas the IWR index revealed the different company's attitude in implementing water reuse practices (IWRCS1 = 40%; IWRCS1 = 27%; IWRCS1 = 99%). The proposed methodology and the indices may also contribute to assessing the effectiveness of river basin management actions to pursue sustainable development goals.

The architecture and application of an automatic operational model system for basin scale water environment management and design making supporting.

An advanced framework for automatic water quality forecasting and water quality management design supporting was put forward. The system is designed as a flexible and extensible service-oriented architecture with data center, system control center, model center and client center. Two operational running modes, one for water environment automatic assessment and forecast and the other for situational analysis, were set to satisfy water quality management requirements. With loosely-coupled air-land-water numerical models, the weather, pollutants sources, hydrodynamic and water quality are automatically forecasted. According to philosophy of the framework, a one-stop platform with four different subsystems for the Three Gorges Reservoir Basin (TGRB) was developed and has been in operational running for more than two years. The system can accurately assessed, forecasted and perfectly displayed the current status and future character of TGRB in air, land and water environment.

Land use impact on the water quality of large tropical river: Mun River Basin, Thailand.

Globally, rivers and streams are experiencing declining water quality. Anthropogenic activities largely contribute to surface water pollution. Understanding human-induced influence on river water quality remains a challenge owing to spatiotemporal variations. In this study, we assessed the influence of various land uses (LU) on 16 water quality parameters of the Mun River, a tributary of the Mekong River, at different scales. Water quality was statistically analyzed both spatially and temporally (1995-2010). Seasonal and annual effect of LU on water quality was evaluated at buffer zone scale and sub-basin scale (i.e., catchment scale) using multiple regression analysis. The result showed that urban LU extensively adds to the nutrient concentration [i.e., total phosphorus (TP), ammonia nitrogen (NH3-N)] followed by agriculture LU at the sub-basin scale. Site-specific variability of TP is explained by urban LU and biological oxygen demand (BOD) by agriculture LU at the 5-km buffer in Upper and Middle Mun whereas at Lower Mun, the 20-km buffer explains the variability of suspended solids (SS) and total suspended solids (TSS), suggesting a more localized effect on the parameters upstream. The high concentration of parameters was noted in the dry season whereas the opposite was true for fecal coliform bacteria (FCB), SS, and TP. The maximum parameter concentration of NH3-N, FCB, and total coliform bacteria exceeds the permissible surface water quality standards of the Pollution Control Department (PCD) of Thailand in all three sub-basins. The study suggests the need for multi-scale interventions and effective pollution control measures focusing on nutrient, pathogenic bacteria, and solids pollution to improve the river water quality of large river basin.

Basin scale sources of siltation in a contaminated hydropower reservoir.

Siltation and the loss of hydropower reservoir capacity is a global challenge with a predicted 26 % loss of storage at the global scale by 2050. Like in many other Latin American contexts, soil erosion constitutes one of the most significant water pollution problems in Chile with serious siltation consequences downstream. Identifying the sources and drivers affecting hydropower siltation and water pollution is a critical need to inform adaptation and mitigation strategies especially in the context of changing climate regimes e.g. rainfall patterns. We investigated, at basin scale, the main sources of sediments delivered to one of the largest hydropower reservoirs in South America using a spatio-temporal geochemical fingerprinting approach. Mining activities contributed equivalent to 9 % of total recent sediment deposited in the hydropower lake with notable concentrations of sediment-associated pollutants e.g. Cu and Mo in bed sediment between the mine tributary and the reservoir sediment column. Agricultural sources represented ca. 60 % of sediment input wherein livestock production and agriculture promoted the input of phosphorus to the lake. Evaluation of the lake sediment column against the tributary network showed that the tributary associated with both dominant anthropogenic activities (mining and agriculture) contributed substantially more sediment, but sources varied through time: mining activities have reduced in proportional contribution since dam construction and proportional inputs from agriculture have increased in recent years, mainly promoted by recent conversion of steep lands from native vegetation to agriculture. Siltation of major hydropower basins presents a global challenge exemplified by the Rapel basin. The specific challenges faced here highlight the urgent need for co-design of evidence-led, context-specific solutions that address the interplay of drivers both within and without the basin and its communities, enhancing the social acceptability of sediment management strategies to support the sustainability of clean, hydropower energy production.

Development of a basin-scale total nitrogen prediction model by integrating clustering and regression methods.

Nutrient runoff into rivers caused by human activity has led to global eutrophication issues. The Nakdong River in South Korea is currently facing significant challenges related to eutrophication and harmful algal blooms, underscoring the critical importance of managing total nitrogen (T-N) levels. However, traditional methods of indoor analysis, which depend on sampling, are labor-intensive and face limitations in collecting high-frequency data. Despite advancements in sensor allowing for the measurement of various parameters, sensors still cannot directly measure T-N, necessitating surrogate regression methods. Therefore, we conducted T-N predictions using a water quality dataset collected from 2018 to 2022 at 157 observatories within the Nakdong River basin. To account for the water quality characteristics of each location, we employed a clustering technique to divide the basin and compared a Gaussian mixture model with K-means clustering. Moreover, optimal regressor for each cluster was selected by comparing multiple linear regression (MLR), random forest, and XGBoost. The results showed that forming four clusters via K-means clustering was the most suitable approach and MLR was reasonably accurate for all clusters. Subsequently, recursive feature elimination cross-validation was used to identify suitable parameters for T-N prediction, thus leading to the construction of high-accuracy T-N prediction models. Clustering was useful not only for improving the regressors but also for spatially analyzing the water quality characteristics of the Nakdong River. The MLR model can reveal causal relationships and thus is useful for decision-making. The results of this study revealed that the combination of a simple linear regression model and clustering method can be applied to a wide watershed. The clustering-based regression model showed potential for accurately predicting T-N at the basin level and is expected to contribute to nationwide water quality management through future applications in various fields.

Basin-scale study of CO2 storage in stacked sequence of geological formations.

Commercial scale decarbonization through carbon capture and storage may likely involve many CO2 storage projects located in close proximity. The close proximity could raise concerns over caprock integrity associated with reservoir pressure buildup and interference among adjacent projects. Commercial-scale injection will also require large prospective CO2 storage resource and high injectivity in the targeted storage formations. To accommodate the need for both large resource and high injectivity, project operators could consider injecting CO2 into a stacked sequence of formations. This analysis investigates the benefits of injecting CO2 into a vertically stacked sequence of saline formations, over injecting the same amount of CO2 into a single saline formation, in addressing these challenges. Our analysis shows that injecting into the stacked sequence mitigates the extent of pressure buildup among the stacked formations, while still achieving the same or greater target CO2 storage volumes. Among cases modeled, the resulting pressure buildup front is most reduced when each storage site distributes injection volumes over several wells, each of which injects a portion of the total CO2 mass across the stacked sequence. This favorable case not only results in the smallest CO2 aerial footprint, but also shows the largest reduction in the pressure buildup at the top of perforation at the injection wells (upwards of approximately 46% compared to the single-formation storage), the result of which is crucial to maintain caprock integrity. This analysis provides insights into required decision-making when considering multi-project deployment in a shared basin.

Abundance and distribution of microplastics in surface waters of the Kattegat/ Skagerrak (Denmark).

Microplastics (MPs) are ubiquitous pollutants in the ocean, and there is a general concern about their persistence and potential effects on marine ecosystems. We still know little about the smaller size-fraction of marine MPs (MPs <300 µm), which are not collected with standard nets for MPs monitoring (e.g., Manta net). This study aims to determine the concentration, composition, and size distribution of MPs down to 10 µm in the Kattegat/Skagerrak area. Surface water samples were collected at fourteen stations using a plastic-free pump-filter device (UFO sampler) in October 2020. The samples were treated with an enzymatic-oxidative method and analyzed using FPA-µFTIR imaging. MPs concentrations ranged between 11 and 87 MP m-3, with 88% of the MPs being smaller than 300 µm. The most abundant shape of MPs were fragments (56%), and polyester, polypropylene, and polyethylene were the dominant synthetic polymer types. The concentration of MPs shows a significant positive correlation to the seawater density. Furthermore, there was a tendency towards higher MPs concentrations in the Northern and the Southern parts of the study area. The concentration of MPs collected with the UFO sampler was several orders of magnitude higher than those commonly found in samples collected with the Manta net due to the dominance of MP smaller size fractions. Despite the multiple potential sources of MPs in the study area, the level of MPs pollution in the surface waters was low compared (<100 MP m-3) to other regions. The concentrations of MPs found in the studied surface waters were six orders of magnitude lower than those causing negative effects on pelagic organisms based on laboratory exposure studies, thus is not expected to cause any impact on the pelagic food web.

Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models.

Pollutant source apportionment is of great significance for water environmental protection. However, it is still challenging to accurately quantify pollutant loads at basin-scale. Refined analytical methods combined the pollution discharge coefficient method (PDCM), field observation, and numerical model (Soil & Water Assessment Tool, SWAT) to make quantitative source appointment in the Tuojiang River, a key tributary of the upper Yangtze River. The chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (N-NH4+) were analyzed. Results showed that the urban sewage treatment plant point source has the largest contribution to COD, TN, and N-NH4+, while TP is mostly from the agricultural sources throughout the year. The total inflowing loads of pollution sources are significantly affected by rainfall. The overall pollution characteristics showed that pollutant loads present in different seasons are as follows: wet season > normal season > dry season. The month with the highest levels of pollutants is July in the wet season. Among the nine cities, the city that contributes the most COD, TN and N-NH4+, is Neijiang, accounting for about 25%, and the city that contributes the most TP is Deyang, accounting for 23%. Among the sub-basins, the Fuxi River subbasin and Qiuxihe River subbasin contribute the most pollutant loads. The technical framework adopted in this paper can be used to accurately identify the types, administrative regions and sub-basins of the main pollution sources in the watershed, which is conducive to management and governance of the environment.

Attempt of basin-scale sediment quality standard establishment for heavy metals in coastal rivers.

Heavy metal sediment quality standards (SQSs) derived from sediment quality guidelines (SQGs) are crucial in risk evaluation and environmental management. However, the establishment of SQSs is quite complex, especially for heavy metals. This study attempted to establish basin-scale SQSs for Cd, Cu, Pb and Zn based on SQGs combined with water quality standards in two coastal rivers in North China, named Jiaolai River (JL) and Jiahe River (JR), respectively. The spatial distribution, fraction, partition coefficients and environmental risk of heavy metals in sediments-porewater were investigated. The results showed that most heavy metals in sediments in JH were higher than those in JL, however, in the porewater, it exhibited an opposite trend. The geochemical fraction showed that most heavy metals in sediments were dominated by residual fraction. The partition of heavy metals between sediment and porewater were mainly affected by both sediment and porewater properties, and exogenous input of heavy metals. Contamination factors showed that Cd in sediment posed high pollution degree; the interstitial water criteria toxicity units and Nemerow Indexes suggested that heavy metal toxicities in porewater were low. The basin-scale heavy metal SQGs were calculated based on porewater quality derived from surface water quality standards using the modified equilibrium partitioning approach. The basin-scale heavy metal SQGs was classified with different grades to deduce the SQSs. Evaluated results of heavy metals in sediments based on SQSs showed lower potential bio-toxic effects in two rivers. In total, basin-scale SQGs for heavy metals were feasible for basin-scale SQSs establishment in coastal rivers.

Involving citizens in hydrodynamic research: A combined local knowledge - numerical experiment on Lake Garda, Italy.

Local knowledge on surface currents and transport patterns in Lake Garda is acquired through interviews among wind-surfers, sailors, fishermen, ferry boat drivers, firefighters nautical rescue team, and officers from the environmental protection agency. Data are collected by means of individual interviews and focus groups, analyzed for internal consistency and summarized in qualitative maps. Three-dimensional numerical simulations are performed using a one-way coupled atmospheric-hydrodynamic model and the results are compared with the observations of the interviewees. Through this combined effort, currents that were not evident to the scientific community, but are well-known to sailors and surfers, can now be recognized and physically understood, like the 'Corif' that flows along the eastern shore in summertime between late morning and afternoon, when wind blows from the south. The transport patterns are also identified, like the predominant east-to-west surface transport experienced by fishermen under storm events and floods, that is confirmed for northerly wind, and the west-to-east transport for southerly wind. Moreover, the trajectory of a drifting capsized boat is reproduced by the model and the dynamics of the accident (location and timing) are reconstructed in collaboration with the firefighters nautical rescue team of Trento and based on information from local newspapers and witnesses. This exercise demonstrates that the joint effort of the scientific community and local experts can produce advances in the understanding of large-scale hydrodynamic processes in lakes.

Impact of phosphate mining and separation of mined materials on the hydrology and water environment of the Huangbai River basin, China.

The objective of this study was to investigate the influence of large-scale phosphate mining (PM) on hydrology and water quality in the Huangbai River basin, China. Rainfall and runoff data were used to analyze hydrological changes of the basin before (from 1978 to 2002) and during (from 2003 to 2014) the PM period. From 2009 to 2014, flow rate and concentrations of ammonia nitrogen (NH4(+)), nitrate (NO3(-)), fluoride (F(-)), suspended solids (SS), total nitrogen (TN), soluble phosphorus (SP), and total phosphorus (TP) were measured at the outfalls of PM as well as at outlets of sub-basins with and without PM practices. Results showed that the PM activities generally reduced runoff (i.e., the runoff coefficient and runoff peak). The sequential Mann Kendall test revealed a decrease trend of runoff during wet seasons after 2008 in the PM regions. For a mining scale of one unit of PM productivity (i.e., 10(8)kg phosphate ore per year or 2.74×10(5) kg d(-1)), TN, SS, and TP of 0.633, 1.46 to 5.22, and 0.218 to 0.554 kg d(-1) were generated, respectively. The NH4(+) and TN loads in the sub-basins with PM were significantly higher than these in the sub-basins without PM; however, the NH4(+) and TN loads that discharged into rivers from the background non-point sources discharged were less in the sub-basins with PM than those without PM. The result was attributed to the reduction of runoff volume by PM. The annual mean concentrations of TN in reservoir water increased with the scales of PM, whereas the mean concentrations of SP were low. Nevertheless, the SP concentrations in the reservoirs greatly increased after 2012, mainly related to the dissolution of apatite in the sediment. The information from this study should improve the understanding of changes in hydrology and water quality in regions with large-scale PM.

How environmentally significant is water consumption during wastewater treatment? Application of recent developments in LCA to WWT technologies used at 3 contrasted geographical locations.

Environmental impact assessment models are readily available for the assessment of pollution-related impacts in life cycle assessment (LCA). These models have led to an increased focus on water pollution issues resulting in numerous LCA studies. Recently, there have been significant developments in methods assessing freshwater use. These improvements widen the scope for the assessment of wastewater treatment (WWT) technologies, now allowing us to apprehend, for the first time, a combination of operational (energy and chemicals use), qualitative (environmental pollution) and quantitative (water deprivation) issues in wastewater treatment. This enables us to address the following question: Is water consumption during wastewater treatment environmentally significant compared to other impacts? To answer this question, a standard life cycle inventory (LCI) was performed with a focus on consumptive water uses at plant level, where several WWT technologies were operating, in different climatic conditions. The impacts of water consumption were assessed by integrating regionalized characterization factors for water deprivation within an existing life cycle impact assessment (LCIA) method. Results at the midpoint level, show that water deprivation impacts are highly variable in relation to the chosen WWT technology (water volume used) and of WWTP location (local water scarcity). At the endpoint level, water deprivation impacts on ecosystem quality and on the resource damage categories are significant for WWT technologies with great water uses in water-scarce areas. Therefore, our study shows the consideration of water consumption-related impacts is essential and underlines the need for a greater understanding of the water consumption impacts caused by WWT systems. This knowledge will help water managers better mitigate local water deprivation impacts, especially in selecting WWT technologies suitable for arid and semi-arid areas.