Water Environment Research最新文献

Oil sands process-affected water (OSPW) is a by-product of bitumen extraction from oil sands surface mining in Alberta, Canada. A major group of organics in OSPW known as naphthenic acid fraction compounds (NAFCs) are of concern due to their persistence and toxicity. Constructed wetland treatment systems have emerged as potential biological treatment approaches for reducing NAFC concentrations within OSPW. In this study, greenhouse-scale mesocosms simulating a constructed wetland consisting of coarse sand tailings (CST) and OSPW were used to evaluate the ability of Scirpus microcarpus, Triglochin maritima, and unplanted controls to attenuate NAFCs under spring/fall and summer temperatures (10°C/5°C and 20°C/10°C day/night). Overall, in this mesocosm system, NAFC attenuation was similar regardless of different design parameters such as plant type, plant presence, and temperature. By the end of the study, NAFCs attenuation was 30% to 50% lower than the initial OSPW depending on plant species, plant presence, and temperature. The relative abundance of the acutely toxic O₂-NAFCs decreased over time, with an increase in the less toxic O₃, O₄, and SO₃ classes. Various hydrocarbon-degrading microbial families such as Comamonadaceae and Xanthobacteraceae were found to be dominant in OSPW, while cyanobacteria (Trichormus) were enriched in the CST. Principal component analysis indicated that only time led to distinct clusters for NAFC composition, while plant type, temperature, and time influenced the microbial communities. Shifts in microbial communities over time corresponded to shifts in NAFCs, possibly due to a decrease in toxicity with increased oxidation of NAFCs and/or an increase in available nutrients from a decrease in plant fitness in the planted mesocosms. PRACTITIONER POINTS: Constructed wetland mesocosms for NAFC attenuation from OSPW comparing three planted/unplanted conditions under two temperatures. Mesocosms had 30%-50% removal of total NAFCs, with a decrease in O₂-NAFCs and increase in O₃, O₄, and SO₃ classes. NAFC composition only shifted with time, while microbial communities were influenced by plant type, temperature, and time. Lack of difference in NAFC attenuation between treatments could indicate a high level of functional redundancy between the microbial communities.

Water is a crucial raw material in economic production activities. Research indicates that water scarcity can lead to significant economic output losses (water scarcity risk, WSR), affecting not only the local area (referred to as local water scarcity risk, LWSR) but also causing economic losses to other regions through trade networks (referred to as virtual water scarcity risk, VWSR). With climate change exacerbating this challenge, understanding the water scarcity risk under changing climatic conditions is essential. However, few studies have addressed this issue comprehensively. To fill this gap, we developed a comprehensive model incorporating environmental flow requirements, water withdrawal, supply, economic output, and trade networks to assess LWSR and VWSR among China's provinces under climate change. Our analysis reveals a growth in China's WSR from $4.6 trillion in 2020 to $5 trillion in 2030. Specifically, both local water scarcity risk (LWSR) and virtual water scarcity risk (VWSR) amounted to $0.9 trillion and $3.7 trillion, respectively, in 2020, increasing to $1.0 trillion and $4.0 trillion by 2030. We also identified hot-spot provinces and sectors with high WSR and proposed relevant policy implications. Our findings contribute to China's climate change mitigation efforts, particularly in formulating strategies to address water scarcity risk. PRACTITIONER POINTS: Spatial heterogeneity-based environmental flow requirement is considered. The water scarcity risk of the Chinese agricultural sector in 2017 amounted to $1.1 trillion. LWSR and VWSR are 0.3 and 0.8 $trillion, respectively. Hotspot Chinese provinces and sectors are identified.

Membrane-aerated biofilm reactors (MABRs) are being increasingly being implemented at full-scale for domestic wastewater treatment and effective biofilm control is critical to their performance. This study investigated the impact of three biofilm scouring strategies on nitrogen removal performance of a pilot-scale MABR operated in Houston, TX: (1) regular air scouring, (2) high intensity air scouring, and (3) high liquid flow scouring. Normal and high intensity air scouring regimes and a high liquid flow scour (10× baseline flow) were each tested sequentially. High NH₄ ⁺-N removal efficiency of 52% in flow-through mode was observed post-high liquid flow scouring, which was comparable to the performance during the intense scouring regime. The absolute abundance of amoA gene for ammonia oxidizing bacteria (AOB) increased significantly by over 200%, between pre- and post-high liquid flow scouring. The energy consumption was 43% lower for the combination of high liquid flow scouring with regular air scouring as compared to the intense air scouring. This study showed that high liquid flows may be utilized as an energy-efficient biofilm control strategy in nitrifying MABR systems. PRACTITIONER POINTS: Pilot-scale MABR reactors were operated with different scouring settings: regular aeration, intense aeration, and high liquid flow. High liquid flow scouring improved nitrification efficiency, comparable to intense scouring. High liquid flow scouring selected for nitrifiers as seen by an increase in AOB quantified as amoA gene abundance. Using high liquid flow with regular aeration scouring reduces electrical energy consumption by 43% as compared to intense aeration scouring. High liquid flows may be used as an energy-efficient biofilm control strategy to improve nitrification performance in MABR systems.

The progress in reducing process footprints for primary treatment or sludge thickening has been limited compared to efforts in intensifying secondary treatment. The current focus on primary treatment is on improving settling rates or using advanced primary filters, which have reduced the footprint for solids separation but produce thinner and more variable sludges. Sludge thickening processes, particularly for primary sludge (PS), have received relatively little attention regarding footprint minimization but play a large role in the ability to intensify primary treatment. To minimize process footprints and maximize performance, the present study examined, for the first time, the suitability of a suspended air flotation (SAF) technology for both thin PS and a blend of PS and waste-activated sludge (WAS). A 4-week pilot test was conducted using a trailer-mounted pilot-scale SAF system fed with either thin PS, or a blend of PS and WAS. Solids capture performance was monitored, along with solids (solids loading rate [SLR]) and hydraulic loading rates (HLR), froth, surfactant, and polymer dosage. The pilot validated the SAF technology for thickening of both primary and blended sludges at significantly higher loading rates (and subsequently smaller footprints) than competing thickening technologies. The study also demonstrated that SAF of thin PS can maintain a >90% solids capture rate at roughly twice the SLR (186 kg m^-2 h^-1) and HLR (690 m³ m^-2 day^-1) of blended sludge (90 kg m^-2 h^-1 and 293 m³ m^-2 day^-1, respectively), validating the design values for a pending SAF installation. Results were also used to establish recommended polymer and froth dosing rates for the full-scale installation. Overall, this study demonstrates that SAF represents a viable, footprint-efficient solution for footprint-optimized management of thin primary and blended solids. Further testing of SAF with real primary filter backwash is recommended to accelerate the adoption of primary filtration for more intensified, carbon-efficient, and resilient wastewater treatment. PRACTITIONER POINTS: Pilot study confirms SAF tech effectively thickens primary and blended sludge, with more consistent performance for primary sludge processing. Primary sludge can be processed at 2× higher hydraulic and solids loading rates than blended sludge with over 90% solids capture performance. The study validates proposed SAF design values and demonstrates the importance of maintaining adequate froth and polymer dosage. SAF is an alternative footprint-efficient solution for thickening high-volume waste flows such as backwash from advanced primary treatment processes. Testing and optimizing SAF with primary and blended sludges could inform thickener selection and design at other wastewater treatment plants.

In this study, a titanium-based coagulant, (i.e., PTFS), with a three-dimensional spatial mesh structure was prepared for the coagulation removal of polystyrene (PS) and titanium dioxide (TiO₂) nanoparticles in water. The results of scanning electron microscopy, TGA-DSC, Fourier infrared spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy characterization showed that the PTFS was not a simple mixture of raw materials and a chemical reaction occurred, thereby generating new chemically connected bonds. The optimum removal of PS could reach 92.5% at the dosage of 0.6 mg/L, initial concentration of 70 mg/L, pH of 7, stirring intensity of 350 rpm, settling time of 60 min, and kaolin concentration of 70 mg/L. The best removal rate of TiO₂ could reach 95.3% when the dosage was 0.8 mg/L, the initial concentration was 70 mg/L, the pH was 7, the stirring intensity was 350 rpm, the settling time was 60 min, and the kaolin concentration was 50 mg/L. The flocs produced by PTFS were large and dense. In the early stage of coagulation, the flocculation mechanism was dominated by electroneutralization, and in the middle and late stages of coagulation, adsorption, bridging, and netting were dominated. This study aims to provide a reference for the removal of nanopollutants by coagulation in the actual water treatment process. PRACTITIONER POINTS: A titanium-based coagulant PTFS with a three-dimensional spatial mesh structure was prepared. PTFS effectively removes nano-PS and nano-TiO₂ from water. The flocs produced by PTFS were large and dense flocs. Removal of PS and TiO₂ by PFTS has been a combination of multiple coagulation mechanisms.

Lamproglena clariae, a gill parasite of Clarias gariepinus has previously been identified as a valuable indicator of effect for organic and metal pollution. The current study evaluates it as a bioindicator of metal accumulation by recording the concentration (mg/kg) of Mn, Fe, Zn, Se, and Sr in adult females and eggs collected at six sites along the Vaal River, South Africa. The data are compared to the metal concentrations recorded in water and sediment, and with infection variables calculated for L. clariae collected from C. gariepinus in March 2017 and October 2018. Metal concentrations in parasite samples were measured utilizing total reflection X-ray fluorescence spectroscopy. This was the first time this method was used to measure metal concentration in L. clariae. Manganese, Fe, Cu, Se, and Sr concentrations differed between adult females and egg specimens and between the six sampling sites, following the difference in the metal concentrations in the water and sediment samples. More polluted sites had low prevalence and low abundance of L. clariae. In adult females, Mn, Fe, Cu, Zn, Se, and Sr had higher concentrations than the water at the more polluted sites. Metal concentration (Mn, Zn, Cu, and Se) was higher in adult females compared to eggs. However, the Fe concentrations were higher in eggs than in adult females. Metal concentrations in L. clariae females were generally higher than levels recorded in water and sediment samples, indicating biomagnification, and supporting the viability of L. clariae as an accumulation indicator. High concentrations of Fe in eggs suggest that Fe elimination may occur via vitellin maternal transfer to larvae. PRACTITIONER POINTS: Fish ectoparasites have not received sufficient evaluation as indicators of pollution. Lamproglena clariae bioaccumulates metals in polluted environments. Lamproglena clariae eggs accumulate Fe to higher concentrations than the females that produce them.

Groundwater, a pivotal water resource in numerous regions worldwide, confronts formidable challenges posed by severe nitrate pollution. Traditional research methodologies aimed at addressing groundwater nitrate contamination frequently struggle to accurately depict the intricate conditions of the groundwater environment, particularly when dealing with high variability and nonlinear data. However, the advent of machine learning (ML) has heralded an innovative approach to simulating groundwater dynamics. In this study, six ML algorithms were deployed to model the concentrations of shallow groundwater nitrates in the Shaying River Basin. The efficacy of each model was assessed through comprehensive metrics including the coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE), gauging the alignment between observed and predicted groundwater nitrate levels. Subsequently, to discern the principal environmental factors influencing NO₃-N concentrations, the most proficient model was selected. Among the array of models, the XGB algorithm, renowned for its capacity to handle extreme values, demonstrated superior performance (R² = 0.773, MAE = 7.625, RMSE = 11.92). Through an in-depth analysis of groundwater NO₃-N across major urban centers, Fuyang city was identified as the most heavily contaminated locale, attributing the phenomenon to potential sources such as domestic sewage and agricultural activities (feature importance of Cl^- = 78.64%). Conversely, Zhengzhou city emerged as the least polluted city, with notable influences from K⁺ and NO₂ ^- (feature importance = 52.06% and 18.41%), indicative of a prevailing reducing environment compared to other cities. In summation, this study explores a methodology for amalgamating diverse environmental variables in the investigation of groundwater contamination. Such insights hold profound implications for the effective management and mitigation of nitrate contamination in the Shaying River Basin, offering a demonstration for similar endeavors in analogous regions. PRACTITIONER POINTS: Six machine learning models were utilized to simulate the nitrate contamination. XGB model for groundwater nitrate pollution prediction outperformed other models. Relative importance of environmental variables was identified using the XGB model. Impact of main environmental variables on groundwater nitrate was discussed.

This study focuses on the synthesis of composite materials using Zeolitic imidazolate frameworks (ZIF-67) nanoparticles as an effective adsorbent, along with different concentrations (2-10%) of thermally expanded vermiculite (EV) as a low-cost and natural adsorbent substrate. The pristine materials and their composites were fully characterized using XRD, FTIR, BET, SEM, zeta potential, and EDS techniques. The pseudo-second-order kinetic model described both organic dyes' adsorption on synthesized adsorbents. Accordingly, the calculated adsorption capacities of Congo Red (CR) and Malachite Green (MG) dyes over the synthesized adsorbents were found to be about 22.72 and 49.02 mg/g for pure EV, 100 and 100 mg/g for pure ZIF-67, 90.91 and 100 mg/g for ZIF-67/EV-2, 100 and 100 mg/g for ZIF-67/EV-5, 95.24 and 99.01 mg/g for ZIF-67/EV-7, and 92.59 and 97.09 mg/g for ZIF-67/EV-10, respectively. The Langmuir isotherm model fits experimental isotherm data best in the studied temperature range (298-313 K). Among the synthesized adsorbent materials, the ZIF-67/EV-5 composite (containing 5% EV flakes) showed the highest maximum adsorption capacities of 1428.6 and 1114.2 mg/g for MG and CR dyes at pH 7 and 298 K. Moreover, it showed the highest removal efficiency (up to 99.5%) toward both cationic MG and anionic CR dyes in the binary mixture of both dyes. Finally, the regeneration and recyclability of this composite showed a 12% decrease in dye removal after five adsorption cycles. The synthesized ZIF-67/EV composites may therefore be used as efficient and inexpensive adsorbent materials for the simultaneous removal of cationic and anionic dyes from contaminated water. PRACTITIONER POINTS: ZIF-67/expanded vermiculite composites were synthesized and used to simultaneously remove cationic and anionic dyes from wastewater. Kinetics, isotherms, and thermodynamics of adsorption were studied showing good removal of both dyes. The ZIF-67/EV-5 composite achieved maximum adsorption capacities of 1428.6 and 1114.2 mg/g for cationic Malachite Green and anionic Congo Red dyes, respectively. Various interactions like π-π stacking and coordination are proposed as mechanisms of adsorption. The composite showed good selectivity in separating dyes and maintained high removal efficiency even after 5 reuse cycles.

The study investigated the water quality of the Chambal River from 2010 to 2022 throughout the year. The measured parameters like pH, EC (Electrical Conductivity), TDS (Total Dissolved Solids), and Total Hardness (TH) fluctuate between 7.70 and 8.35 (with an average of 8), 289 and 484 μS/cm (with an average of 347 μS/cm), 185 and 315 mg/l (with an average of 224 mg/l), and 68 and 120 mg/l (with an average of 93 mg/l), respectively, on the yearly basis. While the turbidity, nitrate levels, ammonia nitrogen, fluoride, and boron dissolved) fluctuate between 0.79 and 8 NTU (with an average of 2 NTU), 0.38 and 2 mg/l (with an average of 0.92 mg/l), 0.06 and 0.61 mg/l (with an average of 0.22 mg/l), 0.24 and 0.94 mg/l (with an average of 0.67 mg/l), and 0.04 and 0.33 mg/l (with an average of 0.16 mg/l), respectively, on the yearly basis. The water Quality Index (WQI) ranges between 10 to 149 with an average of 73 on a yearly basis. However, WQI ranges between 27 to 95 (with an average of 56) in summer, 6 to 294 (with an average of 116) in rainy, 4 to 123 (with an average of 156) in autumn, and 1 to 82 (with an average of 52) in winter. These results indicate a poor overall Water Quality Index (WQI), rendering the Chambal River's water unsuitable for drinking purposes. Furthermore, the principal component analysis and dendrogram analysis were used in this study. The findings highlight the urgent need for stricter pollution control measures to safeguard the river's health. PRACTITIONER POINTS: The present study is based on Seasonal Variations and Correlation Analysis of Water Quality Parameters via multiparametric approaches from 2010 to 2022 throughout the year in the Chambal River, Rajasthan, India. Two types of statistics (Principal Component Analysis and Dendrogram analysis) have been applied here to know the variation and distribution of WQI. pH fluctuated within the IS standard, with a slight summer alkalinity increase. EC remained stable, higher in summer due to evaporation. Turbidity peaked in the monsoon and reduced in dry periods. Poor overall Water Quality Index (WQI) was found in the sampling site hence the reader of the discussed journal may take an interest in it. Urgent need to control the river's health from the different pollutants. Pearson correlation analysis reveals strong positive correlations between WQI, turbidity, pH, TDS, TH, and EC while negative correlations are observed between these clusters and boron concentration.