Assessment of the water self-purification capacity on a river affected by organic pollution: application of chemometrics in spatial and temporal variations

Attenuation of water contamination in the Paraopeba River after the collapse of B1 tailings dam: Natural wash-off and dredging contributions

Following the B1 dam collapse at Córrego do Feijão Mine, actions were taken to address environmental damage and enhance the quality of water in the Paraopeba River. Natural processes in the river involve gradual reduction of contamination through dispersion and downstream transportation of tailings-a slow, nature-driven process. Dredging, a human intervention, aimed to expedite recovery. Hence, this study aimed to explore dredging's role in reducing contamination in the impacted Paraopeba River zone. Analysis revealed a direct link between dredging and post-collapse turbidity, though recent trends suggest a lessening impact on pre-collapse conditions. Distinct seasonal variations were observed in iron and manganese concentrations, peaking during wet seasons and displaying notable upstream-downstream disparities. An analysis of ratios (downstream/upstream) was conducted to understand and even predict the return to pre-collapse conditions. Wet season averages for iron and manganese decreased by around 90 % over time, with standard deviations reducing by about 48 % and 58 %, respectively. In the dry season, the averages decreased by over 100 %, indicating water quality improvements surpassing pre-collapse levels. Standard deviations also decreased significantly, by approximately 67 % and 79 %, respectively. Employing an exponential decay model revealed that the contribution of dredging in the dry period is negligible, but in the wet period the contribution can be estimated at 28.6 % in the case of iron and 25 % in the case of manganese. While the models performed well based on extensive data, some limitations occur in estimating dredging contribution rates. The model's sensitivity might overlook influential factors, underscoring the importance of considering sediment nature and dredged area extent in understanding water quality dynamics. Despite these potential limitations, this investigation provides crucial insights into the intricate relationship between dredging and water quality in the Paraopeba River. These findings pave the way for future studies aimed at deeper exploration and more accurate assessments of this association.

Heavy metal contamination assessment and potential human health risk of water quality of lakes situated in the protected area of Tisa, Romania

Protected areas are significant due to the high value of natural resources they shelter. This study's primary objective is to assess the quality status of the water resources (13 lakes and Tisa River) localized in the protected area of Tisa River on the territory of Romania. A number of 13 lakes and surface water (Tisa River) situated in the protected area through the Natura 2000 ecological network are studied. The chemistry and potential pollution status were analyzed by measuring and analyzing a set of twenty elements and sixteen physico-chemical parameters. The potential impact of anthropogenic activities was settled through the applied analysis and obtained results. A potential human health risk was noticed. Results indicated that waters are rich in Ni and Fe probably due to interaction with groundwater rich in Fe and Ni. Waters are characterized by potential contamination, which if directly or through the food chain consumed could negatively influence the human health. Piper and Gibbs plots indicated that the studied waters are divided into three categories based on water-rock interactions: mixed Ca2+-Na+-HCO3-, CaCO3-, and Na+-HCO3-. Likewise, the applied pollution indices (Heavy metal Pollution Index, HPI and Heavy metal Evaluation Index, HEI) indicated three pollution categories correlated to the As, Ni and Fe amounts. The findings of this research imply that the chemistry of the studied lakes and surface waters is influenced by the geogenic origin and emergence of anthropogenic activities. The significance of this research is related to understanding of mechanisms that influence the water quality, improving and conserving the natural water resources, and correspondingly understanding if any potential human health risks could be identified.

Evaluation and monitoring of the water quality of an Argentinian urban river applying multivariate statistics

In this work, we present the water quality assessment of an urban river, the San Luis River, located in San Luis Province, Argentina. The San Luis River flows through two developing cities; hence, urban anthropic activities affect its water quality. The river was sampled spatially and temporally, evaluating ten physicochemical variables on each water sample. These data were used to calculate a Simplified Index of Water Quality in order to estimate river water quality and infer possible contamination sources. Data were statistically analyzed with the opensource software R, 4.1.0 version. Principal component analysis, cluster analysis, correlation matrices, and heatmap analysis were performed. Results indicated that water quality decreases in areas where anthropogenic activities take place. Robust inferential statistical analysis was performed, employing an alternative of multivariate analysis of variance (MANOVA), MANOVA.wide function. The most statistically relevant physicochemical variables associated with water quality decrease were used to develop a multiple linear regression model to estimate organic matter, reducing the variables necessary for continuous monitoring of the river and, hence, reducing costs. Given the limited information available in the region about the characteristics and recovery of this specific river category, the model developed is of vital importance since it can quickly detect anthropic alterations and contribute to the environmental management of the rivers. This model was also used to estimate organic matter at sites located in other similar rivers, obtaining satisfactory results.

Production of Mineral-Carbon Composites and Activated Carbons as a Method of Used Gear Oil, Ashes, and Low-Quality Brown Coals Management

The main objective of this study was to assess the usefulness of the low-quality brown coal, ash obtained as a result of its combustion, as well as used gear oil for the production of mineral-carbon adsorbents. The adsorbents were characterized in terms of textural parameters, acidic-basic character of the surface, mineral matter contribution to the structure, as well as their suitability for drinking water purification. Adsorption tests were carried out against two synthetic dyes-methylene blue and methyl orange. In order to understand the nature of the organic pollutants adsorption, the effect of the initial dye concentration, temperature, and pH of the system as well as the phase contact time were investigated. The obtained mineral-carbon composite and activated carbons significantly differed not only in terms of the elemental composition and chemical character of the surface (from slightly acidic to strongly alkaline), but also showed a very diverse degree of specific surface development (from 21 to 656 m2/g) and the type of porous structure generated (from micro/mesoporous to typically mesoporous). Adsorption tests showed that the efficiency of organic dye removal from aqueous solutions primarily depends on the type of the adsorbent and adsorbate applied, and, to a lesser extent, on the temperature and pH of the system. In turn, kinetic studies have shown that the sorption of dyes on such materials is consistent with a pseudo-second-order kinetics model, regardless of the type of adsorbed dye.

Water quality management by enhancing assimilation capacity with flow augmentation: a case study for the Yamuna River, Delhi

This paper aims to assess the requirement of load reductions and flow augmentation to enhance the assimilation yield of the Yamuna River, Delhi. The framework QUAL2kw was used to predict river quality. The model was calibrated and confirmed in critical flow conditions of pre-monsoon periods. Three strategies were established for varying pollutant loads. The DO concentration was predicted with changing BOD and COD loads. The 16 outfalling drains were considered pollutant sources between the 22 km stretch of the river. Four cases with 41 scenarios were studied with varying flow augmentation upstream and varying load. It has been observed that with 80 cumecs of upstream flow, the reach can assimilate 31.33 tonnes per day of BOD and 142.85 tonnes per day of COD load, maintaining the desired level of DO (≥4 mg/L) and BOD (≤3 mg/L) throughout the reach.

Water quality assessment of Remeți watercourse, Maramureș, Romania, located in a NATURA 2000 protected area subjected to anthropic pressure

The study assessed the evolution of water indicators of Remeți water body that is located in the Remeți locality in the Upper Tisa, a Natura 2000 protected area. Thus, electric conductivity, dissolved oxygen, oxygen saturation, temperature, pH, turbidity, ammonium concentration (NH₄⁺), nitrates (NO₃^-), nitrites (NO₂^-), orthophosphate (PO₄^3-), dissolved Fe, Mn, water hardness, alkalinity (A) and chloride were measured over the January (I)-October (X) 2021 period. This water course was subjected to anthropic pressure, being polluted with nutrients such as ammonium and orthophosphate ions, iron and manganese. The concentrations of other metals were either low (Al, Ba, Li, Ga, Rb, Ni, Sr, Zn, Cu, Ti) or below the detection limit (Pb, Cd). The study was performed over a period of 8 months, namely January 2021-October 2021, covering the 4 seasons, in order to establish their influence on the level of water quality indicators. Exceeded turbidity values and high concentrations of ammonium, orthophosphate and dissolved iron were found, these being generally higher in the summer-autumn months. Dissolved oxygen concentrations were low in the summer-autumn months. Based on the values of the physico-chemical indicators, two types of water quality indices WA-WQI (weighted arithmetic water quality indices) and CCME-WQI (Canadian Council of Ministers of the Environment water quality indices) were calculated to evaluate the global water quality and its evolution over the seasons with a single value. WA-WQI values varied in the range of 78.56-761.63, with a tendency to increase in autumn, showing an intensified tendency of global water quality deterioration due to an increase in ammonium, turbidity, iron and orthophosphates in autumn months while CCME-WQI values were between 39.6 and 68.9, being fair in winter-spring months and marginal / bad in summer and autumn months. The results of this study are advantageous in identifying the level of pollution of Remeți water course, being a signal for local authorities in taking the necessary measures to reduce the pollution around it, for a better human health and conservation of the ecosystems hosted in the protected area.

Spatial and temporal analysis and quantification of pollution sources of the surface water quality in a coastal province in Vietnam

The surface water quality in coastal areas may be highly vulnerable to degradation due to various pollution sources such as seawater intrusion and anthropogenic activities. The current study sought to spatially and temporally analyze and quantify pollution sources of the surface water system in the coastal province of Tra Vinh, Vietnam. A total of 600 surface water samples were taken from 30 monitoring sites distributed over 4 spatial zones. Water samples were collected in four campaigns each year during the dry and rainy seasons from 2016 to 2020 and analyzed for 10 physiochemical and biological parameters. The analyzed data were calculated for the water quality index (WQI). Two-way analysis of variance, principal component analysis/factor analysis (PCA/FA), and multivariable regression analysis (MRA) were conducted over the whole dataset. The results showed that the WQI decreased from the inland zone to the coastal area, was greater in the river zone than in the canal zone, and was higher in the dry season than in the rainy season. The PCA/FA revealed that surface water quality was affected by at least 4 main pollution sources, including agricultural production, seawater intrusion, residential activities, and mixed sources. MRA revealed that these pollution sources explained 68.3%, 12.8%, 7.0%, and 2.7% of the total variance of the WQI, respectively. In summary, the surface water quality in the study area significantly changed spatially and temporally, depending on four pollution sources, which need to be managed properly for a better environment and sustainable development.

Assessment of a Multifunctional River Using Fuzzy Comprehensive Evaluation Model in Xiaoqing River, Eastern China

Rivers are beneficial to humans due to their multiple functions. However, human meddling substantially degrades the functions of rivers and constitutes a threat to river health. Therefore, it is vital to assess and maintain river function. This study used the Xiaoqing River in Shandong Province, China, as a case study and established a multilayered multifunctional river evaluation indicator system consisting of environmental function, ecological function, social function, and economic function. The weights of indicators were calculated using the analytic hierarchy process (AHP) and the entropy method. Furthermore, a fuzzy comprehensive evaluation model based on the Cauchy distribution function was developed to assess the operation status of each function in each river segment. The results of the indicator and criterion layers in different river sections varied. The multifunctionality of the river decreased from upstream to downstream. The Jinan section was the most multifunctional, followed by the Binzhou, Zibo, and Dongying sections, and finally the Weifang section. Through additional analysis, this study determined the constraint indicators and functions of each river section. Overall, the results reveal that the idea of a "multifunctional river" can advance the theoretical understanding of a river's function, and the fuzzy comprehensive evaluation model is demonstrated to provide fresh perspectives for evaluating river function.

Hidden challenges behind ecosystem services improvement claims

Substantial evidence indicates that China’s afforestation statistically contributed to the ecosystem services (ES) improvement. However, we found the potential challenges behind this improvement, especially in water-limited areas. We propose an attribution analysis method, which can assess the specific contribution of natural, human and cognition degree drivers to ES dynamics. The results found that the ratio of natural and human drivers in the area north of China’s 400 mm precipitation isopleth is 2:7. This means local vegetation capacity has already exceeded water limitation, implying a conflict between nature and humans. However, the natural contribution in the area between 400 and 800 mm precipitation isopleth is negative, whereas the human contribution is 91%. This means this area has fragile natural conditions and needs more flexible policies. The ratio of natural and human drivers in the region south of 800 mm precipitation isopleth is 6:3, suggesting the ecological policies here can be maintained.

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PDE is used to assess the contribution of natural and human drivers to ES changes

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Land use management dominantly contributed (55%) to China’s ES improvement

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Re-vegetation in the area north of 400 mm precipitation isohyet exceeded NPP threshold

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The area between 400 and 800 mm isoprecipitation line is the key area with ES decrease

Small stream catchments in a developing city context: The importance of land cover changes on the ecological status of streams and the possibilities for providing ecosystem services

Urban expansion and the transformation of rural areas into suburban areas along with increasing human pressure can cause major changes in the environment. Typical effects of urbanization include degradation of aquatic ecosystems. However, urban expansion is often accompanied by an effort to provide residents with some contact with nature in the city. Natural waterbodies are the elements of the environment predestined to ensure appropriate conditions for recreation and other ecosystem services key to human well-being. In this study, the changes in the forms of development of a submontane stream catchment area (Carpathians, Poland) against the background of the gradual extension of city boundaries were analysed. In addition, the impact of urbanization on the ecological conditions of the urban stream, and therefore the potential ecosystem to provide ecosystem services, was assessed. Although the extension of the city entailed the development of settlements, it was accompanied by the expansion of the municipal sewage infrastructure, thus improving sewage management. The disappearance of arable lands from the stream catchment due to the decline in agricultural activities initiated the spontaneous process of buffer restoration along the stream. All the biotic indices such as Shannon diversity index, Margalef species richness index and BMWP-PL index, based on macroinvertebrate communities increased, and the fish were more numerous in the late stage of city development compared with the early (rural) stage. Surprisingly, the system has rehabilitated well with no revitalisation actions. It is necessary, however, to improve morphological in-stream conditions, and to make further efforts to improve water quality for the system to develop a semi-natural state. Only reaching full ecological potential can lead to an increase in the ecosystem capacity to provide ecosystem services. The studied ecosystem may provide many different services simultaneously, but their availability depends on the protection of the ecosystem's functioning as a whole.

Evaluation of spatio-temporal variation of water quality and source identification of conducive parameters in Damodar River, India

The lower course of the Damodar River in West Bengal is one of the most polluted stretches in the Ganga River basin. There is a lack of research along the whole course of the Damodar, and parameter level analysis receives little attention. Eleven monitoring sites were chosen based on the potential sources of pollution for 6 years (2014-2019). Multivariate statistical techniques (factor analysis (FA), cluster analysis (CA), and discriminate analysis (DA)) evaluate the spatial and temporal variation of Damodar River water quality by considering 24 parameters. Factor analysis extracts the most influential seasonal parameters, and stepwise DA extracts ammonia, DO, potassium, temperature, total coliform, TFS, and turbidity, which are the most responsible parameters for seasonal variation of the water quality. CA classify sampling stations into three groups helping to identify the spatial variation of water quality. Ammonia, BOD, calcium, chloride, conductivity, DO, sodium, sulfate, temperature, Alkalinity, TDS, hardness, TSS, and turbidity are the most influential variables for spatial variation extracted through stepwise DA. Monsoon season shows a higher pollution level due to the contribution from both point and non-point sources. Due to high-density urban areas and large-scale industries, the middle course is more polluted. The Canadian Council of Ministers of the Environment (CCME) water quality index (WQI) accesses the water quality in temporal and spatial scales. The resultant water quality pattern is matched with the derived result from multivariate analysis. Poor water quality is regular at all sample sites in all seasons.

Aquatic macroinvertebrate assemblages in rivers influenced by mining activities

Mining is one of the major pollution sources worldwide, causing huge disturbances to the environment. Industrial and artisanal mining activities are widespread in Mexico, a major global producer of various metals. This study aimed to assess the ecological impairments resulting from mining activities using aquatic macroinvertebrates assemblages (MA). A multiple co-inertia analysis was applied to determine the relationships between environmental factors, habitat quality, heavy metals, and aquatic macroinvertebrates in 15 study sites in two different seasons (dry and wet) along two rivers running across the Central Plateau of Mexico. The results revealed three contrasting environmental conditions associated with different MAs. High concentrations of heavy metals, nutrients, and salinity limit the presence of several families of seemingly sensitive macroinvertebrates. These factors were found to influence structural changes in MAs, showing that not only mining activities, but also agriculture and presence of villages in the basin, exert adverse effects on macroinvertebrate assemblages. Diversity indices showed that the lowest diversity matched both the most polluted and the most saline rivers. The rivers studied displayed high alkalinity and hardness levels, which can reduce the availability of metals and cause adverse effects on periphyton by inhibiting photosynthesis and damaging MAs. Aquatic biomonitoring in rivers, impacted by mining and other human activities, is critical for detecting the effect of metals and other pollutants to improve management and conservation strategies. This study supports the design of cost-effective and accurate water quality biomonitoring protocols in developing countries.

Source identification of surface water pollution using multivariate statistics combined with physicochemical and socioeconomic parameters

Accurate identification of potential contamination sources of river water is a basis for effective pollution control and sustainable water management. Pollution source identification based on physicochemical-parameters-only method may lead to uncertainty and subjectivity. In this study along with hydrochemistry parameters (HPs), socioeconomic parameters (SPs) were considered as an auxiliary in multivariate statistics to achieve a comprehensive assessment on pollution sources with accurate estimates of source identification and apportionment. Fifteen physicochemical parameters were combined with twelve socioeconomic parameters in multivariate statistics to quantitatively assess potential pollution sources and their contributions to river water pollution. Multivariate statistics in the study included regression analysis, principal component analysis (PCA), and absolute principal component score-multiple linear regression (APCS-MLR). Regression analysis between hydro-chemical parameters and socioeconomic parameters indicated that industrial and population growths were the main factors related to ammonium nitrogen (NH₄⁺-N), total nitrogen (TN) contamination, while total phosphorus (TP) was more correlated with domestic discharge and poultry breeding. Based on the results of PCA, four latent factors were extracted for hydrochemistry parameters (HPs) and socioeconomics parameters (SPs), accounting for 68.59% and 82.40% of the total variance, respectively. With integrating the PCA results of the two parameter groups, pollution sources were ranked as industrial effluents > rural wastewater > municipal sewage > phytoplankton growth and agricultural cultivation. Source apportionment in APCS-MLR revealed that industrial wastewater and rural wastewater averagely contributed 35.68% and 25.08% of pollution, respectively, followed by municipal sewage (18.73%) and phytoplankton pollution (15.13%) with relatively small percentage of unrecognized source. It is concluded that socioeconomic parameters assisting hydrochemistry parameters in multivariate statistics can improve the accuracy and certainty of pollution source identification, supporting decision makers to formulate strategies on protection of river water quality.

Investigation of long-term hazards of chemical weapon agents in the environment of Sardasht area, Iran

The present study aimed to investigate the persistence and existence of chemical warfare agents (CWAs) and related dissipation products in the environment of Sardasht area, Iran. Three types of environmental samples including water, soil, and native local plant materials were collected and analyzed. Gas chromatography-mass spectrometry in the electron impact ionization mode has been developed for the separation, screening, identification, and qualification of chemicals after the sample preparation methods. The initial results revealed that no trace of related compounds or CWAs was detected in the soil and water samples. However, trace amounts of some degradation products of blistering agents like mustard gas (HD) and lewisite were found in a tree wood from a house subjected to chemical attack as well as in barley samples (a mixture of leaves and root) collected from an agricultural field in the area indicating chronic low exposure to the environment and people. In order to validate the applied extraction procedures, ethylene glycol was spiked to some of the samples including groundwater, surface soil, grape, and alfalfa plants. All the recoveries were in the range of 83.6-107.4% with the relative standard deviations varying from 4.9% to 12.4% (n = 3) successfully.

Solar-driven, self-sustainable electrolysis for treating eutrophic river water: Intensified nutrient removal and reshaped microbial communities

River ecosystems are the most important resource of surface freshwater, but they have frequently been contaminated by excessive nutrient input of nitrogen (N) and phosphorus (P) in particular. An efficient and economic river water treatment technology that possesses the capacity of simultaneous N and P removal is urgently required. In this study, a solar-driven, self-sustainable electrolytic treatment was conducted in situ to intensify N and P removal from eutrophic river water. Solar panel was applied to provide the electrolysis setups with energy (voltage 10 ± 0.5 V), and the current density was controlled to be 0.06 ± 0.02 mA cm^-2. Results indicated that the average removal efficiencies of total N (TN) and total P (TP) under electrolysis conditions reached 72.4 ± 11.7 and 13.8 ± 5.3 mg m^-2 d^-1, which were 3.7- and 4.7-fold higher compared to untreated conditions. Enhanced TN removal mainly reflected the abatement of nitrate N (NO₃^--N) (80.6 ± 4.1%). The formation of ferric ions through the electro-dissolution of the sacrificial iron anode improved TP removal by coprecipitation with SPS. Combined high-throughput sequencing and statistical analyses revealed that electrolysis significantly reshaped the microbial communities in both the sediment-water interface and suspended sediment (SPS), and hydrogenotrophic denitrifiers (e.g., Hydrogenophaga) were highly enriched under electrolysis conditions. These findings indicated that in situ electrolysis is a feasible and effective technology for intensified nutrient removal from river water.

Quality Assessment of Groundwater Resources in the City of Al-Marj, Libya

This study aimed to assess and compare the quality of groundwater in the city of Al-Marj in Libya with the international standard guidelines for drinking water recommended by the World Health Organisation. An evaluation of the groundwater wells in the study area was conducted. Standard techniques, such as Minitab (v. 16) and ArcGIS (v.10.2), were used for the analytics of the physicochemical and biological parameters of the groundwater samples. An assessment of the calculation of groundwater quality was conducted on the basis of temperature, pH, turbidity, electrical conductivity, total dissolved solids, chloride, sulphate, bicarbonate, total hardness, calcium, potassium, magnesium, ammonia, ammoniacal nitrogen, nitrate, sodium, copper, iron, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, total suspended solids, Escherichia coli and total coliform bacteria. Results indicated that most groundwater wells in the study area display a higher concentration of several parameters compared with the permissible limits of drinking water; thus, the water in these wells is chemically and biologically unsafe for drinking purposes. On the basis of the above results, routine water quality monitoring should be performed and additional water filtration plants should be installed by the local government to obtain safe drinking water.

Aerobic Metabolism Impairment in Tambaqui (Colossoma macropomum) Juveniles Exposed to Urban Wastewater in Manaus, Amazon

The main purpose of the present study was to investigate the potential use of metabolic parameters as non-specific biomarkers of pollution. The Igarapé do Quarenta is a small urban river crossing an industrial area in the city of Manaus, Amazon, and receives the city wastewater without treatment. The fish tambaqui (Colossoma macropomum) were exposed to water collected from two different sites of that stretch for 96 h. After exposure, routine metabolic rate (RMR) was measured, and fish were euthanized for measurements of electron transport system (ETS) activity, Copper (Cu) and Cadmium (Cd) bioaccumulation and biliary PAHs. Water in the sampling points presented low oxygen and high pH, conductivity, dissolved ions, Cu, Cd and ammonia. Bile concentrations of PAHs were high suggesting industrial pollution. The tambaqui exposed to water from Igarapé do Quarenta showed increased RMR and decreased ETS/RMR suggesting impairment of metabolic fish performance and the potential use of these parameters as biomarkers.

An integrated approach for assessing surface water quality: Case of Beni Haroun dam (Northeast Algeria)

In this paper, we use an integrated approach to carry out a comprehensive evaluation of water quality in the Beni Haroun (BH) dam, the largest surface water resource in Algeria. Several techniques have been employed under the same framework, including the Canadian Council Ministers Environment Water Quality Index (CCME-WQI), principal component analysis and factor analysis (PCA/FA), the K-means clustering, and the ordinary least square (OLS) analysis. A data set of 22 physicochemical parameters has been collected, over a period of 11 years, from three sampling stations: Ain Smara (ST1) and Menia (ST2), both located upstream of "Wadi Rhumel," and BH dam station (ST3), located at the dam site. The PCA/FA enables the identification of seven key factors that influence significantly BH dam water quality. The average values of CCME indices at the BH dam were 17, 40, 42, and 32 for drinking, irrigation, industry, and aquatic life purposes, respectively, which indicate poor water quality, according to the CCME categorization scheme. Besides, the K-means algorithm has been proven to be a very useful machine learning tool to detect that the major source of BH dam pollution is "Wadi Rhumel." Finally, OLS analysis, along with the Mann-Kendall test, highlighted the positive trend of BH dam's water quality.

Spatiotemporal Dynamics of Nitrogen Transport in the Qiandao Lake Basin, a Large Hilly Monsoon Basin of Southeastern China

The Qiandao Lake Basin (QLB), which occupies low hilly terrain in the monsoon region of southeastern China, is facing serious environmental challenges due to human activities and climate change. Here, we investigated source attribution, transport processes, and the spatiotemporal dynamics of nitrogen (N) movement in the QLB using the Soil and Water Assessment Tool (SWAT), a physical-based model. The goal was to generate key localized vegetative parameters and agronomic variables to serve as credible information on N sources and as a reference for basin management. The simulation indicated that the basin’s annual average total nitrogen (TN) load between 2007 and 2016 was 11,474 tons. Steep slopes with low vegetation coverage significantly influenced the spatiotemporal distribution of N and its transport process. Monthly average TN loads peaked in June due to intensive fertilization of tea plantations and other agricultural areas and then dropped rapidly in July. Subsurface flow is the key transport pathway, with approximately 70% of N loads originating within Anhui Province, which occupies just 58% of the basin area. The TN yields of sub-basins vary considerably and have strong spatial effects on incremental loads entering the basin’ major stream, the Xin’anjiang River. The largest contributor to N loads was domestic sewage (21.8%), followed by livestock production (20.8%), cropland (18.6%), tea land (15.5%), forest land (10.9%), atmospheric deposition (5.6%), orchards (4.6%), industry (1.4%), and other land (0.8%). Our simulation underscores the urgency of increasing the efficiency of the wastewater treatment, conserving slope land, and optimizing agricultural management as components of a comprehensive policy to control N pollution in the basin.

Assessing the Self-Purification Capacity of Surface Waters in Lake Baikal Watershed

The removal of trace metals (TM), dissolved organic carbon (DOC), mineral nitrogen (Nmin.), and polycyclic aromatic hydrocarbons (PAHs) from the water of Lake Baikal and its tributaries was evaluated. The contaminant removal rate (CRR) and the contaminant removal capacity (CRC) were used as water self-purification parameters. The CRR was calculated as the difference between contaminant mass flow rates at downstream and upstream gauging stations. The CRC was calculated as the quotient of the CRR and the change in water discharge between downstream and upstream gauging stations. Whether the CRR and CRC have positive or negative values depends on whether contaminant release or removal occurs in the water body. The CRR depends on the size of the water body. The lowest and the highest CRRs observed for Baikal were equal to −15 mg/s (PAHs) to −7327 g/s (DOC), whereas the highest PAH and DOC removal rates observed for Selenga River (the major Baikal tributary) in summer were equal to −9 mg/s and −3190 g/s correspondingly. The highest PAH and DOC removal rates observed for small tributaries were equal to 0.0004 mg/s and −0.7 g/s respectively. The amplitude of annual CRR oscillations depends on contaminant abundance. The highest amplitude was typical for most abundant contaminants such as Nmin. and DOC. In unpolluted sections of the Selenga River the highest rates of N and C removal (−85 g/s and −3190 g/s, respectively) were observed in summer and the lowest rates (4 g/s and 3869 g/s, respectively) were observed in the spring. The lowest amplitude was typical for PAHs and some low-abundance TM such as V and Ni. The highest summer rates of V and Ni removal were equal to −378 mg/s and −155 mg/s respectively, whereas lowest spring rates are equal to 296 mg/s and 220 mg/s. The intermediate CRR amplitudes were typical for most abundant TM such as Sr, Al, and Fe. The spatial CRR variability depends on water chemistry and the presence of pollution sources. The lowest (up to 38 g/s) rates of Nmin. removal was observed for polluted lower Selenga sections characterized by low water mineralization and high DOC concentrations. The highest rates (−85 g/s) were observed for unpolluted upper sections. Seepage loss from the river to groundwater was also recognized as an important means of contaminant removal. The CRC values depend mostly on water residence time. The DOC removing capacity value of Baikal (−26 g/m3) were lower than those of Selenga in summer (−35 g/m3) but higher than the CRCs of all tributaries during the other seasons (from 30 mg/m3 to −10 g/m3).

River health assessment of the Yellow River source region, Qinghai-Tibetan Plateau, China, based on tolerance values of macroinvertebrates

For decades, the river health of the Yellow River source region (YRSR) on the Qinghai-Tibetan Plateau has been a focal issue owing to its unique geographic location and ecological functions. This study investigated the ecological status of the headwater streams, the main stem, and the tributaries of the Yellow River in the YRSR using the tolerance values of macroinvertebrates and those related to biotic indices. The macroinvertebrate assemblages of the headwater streams were characterized by lower biodiversity than the tributaries downstream, based on comparisons of taxonomical composition, functional feeding group composition, and the pollution-tolerant capacity of taxa. The headwater streams had a lower ratio (16%) of pollution-sensitive macroinvertebrate taxa than that of the tributaries downstream (30%). The biotic indices (family- and genus-level biotic indices) indicated that the ecological health of the headwater streams was comparably poorer than that of the downstream tributaries. The combined effect of vulnerable natural conditions and increasing human disturbance is likely the main cause of eco-environmental degradation in the Yellow River headwater streams.

Modeling the oxygen-depleting potential and spatially differentiated effect of sewage organics in life cycle assessment for wastewater management

Excessive organic emissions measured as chemical oxygen demand (COD) have caused serious regional water pollution i.e. the widespread malodorous black rivers in China. Assessing the optimum treatment strategies is generally a complicated work involving sophisticated trade-offs across regional improvement and global sustainability. Life cycle assessment (LCA) is a promising tool to support such trade-offs, but it appears difficult to comprehensively reflect the direct impact of high-COD wastewater. This is because, the current LCA framework only highlights the effect of nutrients as a representative eutrophication indicator. To address this issue, this study extends the LCA framework by defining a new COD category to characterize the oxygen-depleting processes associated with development of characterization factors and models. By combining water quality model, the modeling scheme is shown capable of converting dynamic effects of COD on the receiving water into the spatially differentiated impact-assessment results. Upon a descriptive case, we also illustrate that the modeling scheme can construct different environmental situations by varying the embedded variables. This enables the refined investigations of the paradigm shift in wastewater treatment, which contributes to the avoidance of "one-size-fits-all" solution identified without considerations of environmental sustainability. Last, we discuss the ways to further refining the modeling scheme to make it applicable in more cases of water pollution.

HIT.WATER scheme: An integrated LCA-based decision-support platform for evaluation of wastewater discharge limits

Determination of appropriate effluent quality limits (EQL) for wastewater treatment plants in China is a complicated process involving multiple factors that need joint consideration. Based on advantages of compiling the energy and material flows as well as the emissions into air, water and soil, life cycle assessment (LCA) presents a standardized approach for evaluation of EQL alternatives. However, challenges arise when incorporating more factors is indispensable, especially for the elements concerning downstream receiving water body, official watershed planning and stakeholder's participation. To this end, an integrated LCA-based decision-support platform named HIT.WATER scheme is proposed, linking the currently available LCA system with Water Quality Model (WQM), Plackett-Burman (PB) design and Conjoint Analysis (CA). A demonstrative case study was conducted to illustrate the processing procedures. Results obtained in the current study show that the officially defined river functions and the downstream cross-section distances resulted in more significant effects on the assessment outcome than other factors such as self-purification coefficients and weighting factors. Nevertheless, the comparisons among EQL alternatives were carried out and the differences were observed, which were dynamic, varying with the changed conditions of either natural factors (e.g. downstream distances) or human factors (e.g. officially defined river functions). Quantitatively presenting the dynamic comparisons to indicate the differences among the alternatives was a principal function of the HIT.WATER scheme. In particular, the approach allows the environmental impacts of EQL examined from various perspectives, which is conducive to the preclusion of "one-size-fits-all" determination with sustainability consideration. Stakeholder's participation was achieved through a transparent decision-making process, and their selection and judgment criterion could be explicitly presented using quantitative metrics. We conclude that the HIT.WATER scheme can be applied to broader scales where the evaluation of paradigm shifts (technological advancement or effluent standard changes) in sewage systems is necessary.

Toxicity of aromatic pollutants and photooxidative intermediates in water: A QSAR study

Extensive commercial use of aromatic hydrocarbons results with significant amounts of these chemicals and related by-products in waters, causing a severe ecological and health threat, thus requiring an increased attention. This study was aimed at developing models for prediction of the initial toxicity of the aromatic water-pollutants (expressed as EC₅₀ and TU₀) as well as the toxicity of their intermediates at half-life of the parent pollutant (TU_1/2). For that purpose, toxicity toward Vibrio fischery was determined for 36 single-benzene ring compounds (S-BRCs), diversified by the type, number and position of substituents. Quantitative structure-activity relationship (QSAR) methodology paired with genetic algorithm optimization tool and multiple linear regression was applied to obtain the models predicting the targeted toxicity, which are based on pure structural characteristics of the tested pollutants, avoiding thus additional experimentation. Upon derivation of the models and extensive analysis on training and test sets, 4-, 4- and 5-variable models (for EC₅₀ and TU₀, TU_1/2, respectively) were selected as the most predictive possessing 0.839<R²< 0.901 and 0.789<Q²< 0.859. The analysis of the selected descriptors indicated three major structural characteristics influencing the toxicity: electronegativity, geometry and electrotopological states of the molecule. Degradation kinetics determining as well the pathways of intermediates formation, reflected over ionization potential, was found to be an important parameter determining the toxicity in half-life.

Pollutant source analysis and tempo-spatial analysis of pollutant discharge intensity in a transboundary river basin

From the perspective of river basin refined management and pollution control of water bodies, a transboundary river basin and its regional pollutant sources are identified and the typical status of discharging processes of different pollutant sources are screened. Then organic connection which can comprehensively reflect and dynamically characterize the discharge of transboundary water pollutants is constructed. In addition, the integrated prediction (IP) model of the transboundary river basin and its regional water pollutants discharge is established. Finally, the dynamic simulation of typical status characteristics of the transboundary river basin and its regional pollutant sources discharge as well as the tempo-spatial changing pattern of pollutant discharge intensity is conducted in this paper. This paper selected the Songhua River basin as an example where planting, industry, household (urban living and rural living), and livestock and poultry are the main pollutant sources. The dynamic simulation of water pollution discharge in Songhua River basin during the 13th Five-year Plan and its tempo-spatial changing trend analysis are conducted by employing the established IP model of transboundary river basin water pollution discharge. The results show that during the 13th Five-year Plan, through comprehensive management and control of pollutant sources in Songhua River basin, the discharge amounts of different pollutant sources (planting, industry, household, livestock, and poultry) present an overall decreasing trend and the main pollutants discharge intensity decreases significantly year by year. It is demonstrated that pollution discharge in Songhua River basin is controlled effectively.

Characterizing Water Pollution Potential in Life Cycle Impact Assessment Based on Bacterial Growth and Water Quality Models

For the life cycle assessment (LCA) of wastewater management, eutrophication is considered the most relevant factor. However, eutrophication is not the only pathway through which wastewater influences the environment, and merely characterizing eutrophication potential is not sufficient for the LCA framework to reflect the influence of wastewater. This study defines the Bacterial Depletion of Oxygen (BDO)—a new impact category that represents the oxygen depleting potential caused by the growth of microorganisms—and characterization models and characterization factors are developed for the application of BDO. Water quality models (both one- and two-dimensional) are incorporated into the BDO characterization models so that the LCA framework includes some spatially differentiated factors, and can be used to estimate the direct impact of wastewater on receiving environment (IBDO value). Based on three case studies, this study demonstrates how the BDO category can be applied for the evaluation of wastewater management. Results show that increases in the downstream distance and self-purification coefficients reduce the IBDO value, whereas the increase in water velocity raises the IBDO value. Future integration of the BDO category with water quality models must link the dilution effect of water bodies, the environmental carrying capacity of receiving water, and the distribution of water pollutants in eutrophication and bacterial oxygen depletion.

Impact of Changes of Land Use on Water Quality, from Tropical Forest to Anthropogenic Occupation: A Multivariate Approach

Worldwide, it is acknowledged that changes of land use influence water quality; however, in tropical forests, the relationship between land use and water quality is still poorly understood. This study assessed spatial and seasonal variations in water quality, and the relationship between water quality and changes of land use in the Bobos-Nautla River, whose upper course runs across a patch of a tropical cloud forest. Spatial and seasonal variations in water quality and land use were assessed with multivariate tools. A cluster analysis, as well as a Principal Component Analysis (PCA-3D), identified three groups of sites: (1) an upper portion, which showed the best water quality and the broadest natural vegetation coverage; (2) a middle course, with high nitrogen and phosphorus concentrations associated with extensive agricultural uses; and (3) a lower course, characterized by the highest levels of total and fecal coliforms, as well as ammonia nitrogen, associated with the highest percentage of urbanization and human settlements. Our findings demonstrate the impact of changes of land use on water quality of rivers running through cloud forests in tropical zones, which are currently endangered ecosystems.

Assessment of surface water quality using a growing hierarchical self-organizing map: a case study of the Songhua River Basin, northeastern China, from 2011 to 2015

The analysis of a large number of multidimensional surface water monitoring data for extracting potential information plays an important role in water quality management. In this study, growing hierarchical self-organizing map (GHSOM) was applied to a water quality assessment of the Songhua River Basin in China using 22 water quality parameters monitored monthly from 13 monitoring sites from 2011 to 2015 (14,782 observations). The spatial and temporal features and correlation between the water quality parameters were explored, and the major contaminants were identified. The results showed that the downstream of the Second Songhua River had the worst water quality of the Songhua River Basin. The upstream and midstream of Nenjiang River and the Second Songhua River had the best. The major contaminants of the Songhua River were chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), total phosphorus (TP), and fecal coliform (FC). In the Songhua River, the water pollution at downstream has been gradually eased in years. However, FC and biochemical oxygen demand (BOD₅) showed growth over time. The component planes showed that three sets of parameters had positive correlations with each other. GHSOM was found to have advantages over self-organizing maps and hierarchical clustering analysis as follows: (1) automatically generating the necessary neurons, (2) intuitively exhibiting the hierarchical inheritance relationship between the original data, and (3) depicting the boundaries of the classification much more clearly. Therefore, the application of GHSOM in water quality assessments, especially with large amounts of monitoring data, enables the extraction of more information and provides strong support for water quality management.

An integrated optimization method for river water quality management and risk analysis in a rural system

In this study, an interval-stochastic-based risk analysis (RSRA) method is developed for supporting river water quality management in a rural system under uncertainty (i.e., uncertainties exist in a number of system components as well as their interrelationships). The RSRA method is effective in risk management and policy analysis, particularly when the inputs (such as allowable pollutant discharge and pollutant discharge rate) are expressed as probability distributions and interval values. Moreover, decision-makers' attitudes towards system risk can be reflected using a restricted resource measure by controlling the variability of the recourse cost. The RSRA method is then applied to a real case of water quality management in the Heshui River Basin (a rural area of China), where chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and soil loss are selected as major indicators to identify the water pollution control strategies. Results reveal that uncertainties and risk attitudes have significant effects on both pollutant discharge and system benefit. A high risk measure level can lead to a reduced system benefit; however, this reduction also corresponds to raised system reliability. Results also disclose that (a) agriculture is the dominant contributor to soil loss, TN, and TP loads, and abatement actions should be mainly carried out for paddy and dry farms; (b) livestock husbandry is the main COD discharger, and abatement measures should be mainly conducted for poultry farm; (c) fishery accounts for a high percentage of TN, TP, and COD discharges but a has low percentage of overall net benefit, and it may be beneficial to cease fishery activities in the basin. The findings can facilitate the local authority in identifying desired pollution control strategies with the tradeoff between socioeconomic development and environmental sustainability.

Migration and transformation characteristics of DOM in fine sand and marl rock

This paper mainly studied migration and transformation characteristics of dissolved organic matter (DOM) in underground aquifers. To achieve the research purpose, we carried out the dynamic column experiments of the DOM at different conditions indoors. In the experiment, the water of Wujiang River from Pingdingshan Coal-field is used as water sample, meanwhile, fine sand and marl rock are used as testing rock sample. A comparative study on migration and transformation characteristics of the DOM in different rock samples is done. The results show that, in the fine sand, the main effects are convection and dispersion, while the adsorption and biological effects are very weak. However, in the marl rock, besides existing convection and dispersion, the adsorption and biological effect are quite significant. And in the marl rock, convection and dispersion plays a major role in the early experiment, while adsorption is the main effect in the medium term, then the biodegradation dominates the final stage. With the increasing of temperature and seepage velocity in the fine sand, the impact of the convection effect becomes gradually weak, the dispersion effect gradually enhances, and, however, convection effect is still playing a dominant role. With the temperature rising in the marl rock, the adsorption effect becomes weak, but biodegradation is enhanced. As the seepage velocity increases in the marl rock, the adsorption and biodegradation both decrease.