Five-day Biochemical Oxygen Demand Research Articles

Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model

Effective evaluation of water quality and accurate quantification of pollution sources are essential for the sustainable use of water resources. Although water quality index (WQI) and positive matrix factorization (PMF) models have been proven to be applicable for surface water quality assessments and pollution source apportionments, these models still have potential for further development in today's data-driven, rapidly evolving technological era. This study coupled a machine learning technique, the random forest model, with WQI and PMF models to enhance their ability to analyze water pollution issues. Monitoring data of 12 water quality indicators from six sites along the Minjiang River from 2015 to 2020 were used to build a WQI model for determining the spatiotemporal water quality characteristics. Then, coupled with the random forest model, the importance of 12 indicators relative to the WQI was assessed. The total phosphorus (TP), total nitrogen (TN), chemical oxygen demand (CODCr), dissolved oxygen (DO), and five-day biochemical oxygen demand (BOD5) were identified as the top five significant parameters influencing water quality in the region. The improved WQI model constructed based on key parameters enabled high-precision (R2 = 0.9696) water quality prediction. Furthermore, the feature importance of the indicators was used as weights to adjust the results of the PMF model, allowing for a more reasonable pollutant source apportionment and revealing potential driving factors of variations in water quality. The final contributions of pollution sources in descending order were agricultural activities (30.26%), domestic sewage (29.07%), industrial wastewater (26.25%), seasonal factors (6.45%), soil erosion (6.19%), and unidentified sources (1.78%). This study provides a new perspective for a comprehensive understanding of the water pollution characteristics of rivers, and offers valuable references for the development of targeted strategies for water quality improvement.

Temporal and Spatial Trends in Livestock Manure Discharge and Water Pollution Risk in Chaohu Lake Basin

Assessments of the spatiotemporal distribution of livestock manure and its risk to the watershed are important to prevent water pollution. In this work, the spatiotemporal livestock manure distribution and its risk for the Chaohu lake basin were evaluated based on the excretion coefficient method and ArcGIS technology. In detail, the amounts of livestock manure and its associated pollutants, including chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD5), ammonia (NH4+-N), total nitrogen (TN), and total phosphorus (TP), were calculated from 2009 to 2019. Then, the diffusion concentrations of COD, BOD5, NH4+-N, TN, and TP and the water pollution risk index from livestock manure were estimated and predicted for the Chaohu lake basin. The results indicated that the mean amount of livestock manure had reached 1.04 × 107 t in the Chaohu lake basin in the studied decade. The COD, BOD5, NH4+-N, TN, and TP from livestock manure in Feixi and Feidong contributed 54.26% and 54.40% of the total in the whole basin. These results demonstrate the potential pollution risk of livestock manure for the Chaohu lake basin. Moreover, the diffusion concentrations of COD, BOD5, NH4+-N, TN, and TP for the lake basin were from highest to lowest as follows: Feixi > Feidong > Chaohu > Lujiang > Wuwei > Shucheng > Hefei. The water pollution risk index was more than 20 in Feixi and Feidong, indicating that these areas were heavily affected by local livestock manure. The water pollution risk index will be approximately 18 for the Chaohu lake basin in 2030, implying that the Chaohu lake watershed will suffer moderate pollution from animal manure. These results provide scientific support for policymakers to enhance manure utilization efficiency and control livestock manure loss, causing water eutrophication in Chaohu lake basin or other similar watersheds.

The effectiveness of using coconut husk powder as an adsorbent to enhance the wastewater quality of the cepuk textile industry in Nusa Penida, Bali, Indonesia

Introduction: Tenun Cepuk (traditional woven) from Nusa Penida holds great potential as a traditional textile art form, cherished for its intricate patterns and cultural significance. However, the textile industry's wastewater, with its dye-related pollution, presents a significant environmental challenge that needs sustainable solutions. Coconut husk powder exhibits promising potential as an adsorbent for treating dye wastewater from the textile industry. Investigating the interplay between varying thicknesses and contact durations is crucial to maximizing coconut husk powder's adsorption capacity and efficiency for dye wastewater treatment. Method: This study, following an Experimental research design with a Posttest Only Control Group Design, aims to assess the impact of an intervention on the experimental group compared to the control group. Coconut fibers, sourced from Nusa Penida agriculture, serve as the adsorbent. Coconut powder is added to these tanks at thicknesses of 5 cm, 10 cm, and 15 cm. Subsequently, wastewater samples from the Cepuk weaving process are introduced into each experimental tank, along with a control group. The process is left for 24 and 72 hours as varying contact times. The adsorption results are subjected to analysis for parameters, including total suspended solids (TSS), total dissolved solids (TDS), five-day biochemical oxygen demand (BOD5), and chemical oxygen demand (COD) at the Panureksa Denpasar Laboratory. Results: The use of coconut husk powder as an adsorbent effectively lowers TDS, TSS, BOD5, and COD in Cepuk textile dye wastewater. The reduction depends on adsorbent thickness and contact time. Thicker adsorbents notably reduce TDS, TSS, BOD5, and COD, enhancing wastewater quality and environmental safety. A 15 cm-thick adsorbent effectively reduces TDS to permissible levels. Prolonged contact times also significantly lower levels. Conclusion: Coconut husk powder can be utilized to decrease TDS, TSS, BOD5, and COD levels in textile dye wastewater. Thickness and contact time significantly impact the enhancement of wastewater quality.

Microfluidic chip-based microbial metabolism-indexed BOD sensor for rapid determination of biochemical oxygen demand

Reliance on five-day biochemical oxygen demand (BOD5) as an indicator of water quality has inhibited the development of efficient process control due to the associated uncertainty and lag time. In the work, we proposed a novel strategy for rapid on-site BOD5 determination by a microfluidic chip-based microbial metabolism-indexed BOD sensor (MCB-MMI BOD sensor). The rapid on-site BOD5 detection was achieved by quantifying the equilibrium concentration of tryptophan involved in aerobic biodegradation for alternating the traditional 5-day monitoring of dissolved oxygen variation. The regulated metabolized tryptophan was identified by fluorescence spectrum and converted into BOD5 value. The prominent performance for MCB-MMI BOD sensor BOD5 determination was accessible in the field application, such as decreasing detection time from 5 days to 10 min, lowering sample volume from 250 mL to 2.5 mL, diminishing the working area, extending the detection range (without dilution) from 6 mg/L to 27 mg/L, featured with 83% accuracy, and free-labor automation, which exhibited the infinite potential for MCB-MMI BOD sensor on rapid on-site BOD5 monitoring. We believe the MCB-MMI BOD sensor would broaden its practical applications in BOD5-contained multiple-parameters water quality sensing, and would favorably supply a new tool for sewage-treatment process control, environmental monitoring, and aquaculture.

Effect of Hydraulic Loading Rate on Treatment Performance of a Pilot Wetland Roof Treating Greywater from a Household

To solve the upcoming environmental problems, sponge city concepts as well as new technologies are being developed these days. One of the future challenges is to reduce drinking water demand by using decentralized water recycling systems. This study aimed to investigate the performance of a specially designed pilot wetland roof (PWR) treating domestic greywater (GW) at ground level under outdoor conditions and to evaluate the effects of different hydraulic loading rates (HLRs) for a period of two years. The results showed highly efficient removal of typical greywater pollutants from the system, e.g., five-day biochemical oxygen demand (BOD5) > 96%, chemical oxygen demand (COD) > 93%, total suspended solids (TSS) >94%, anionic surfactants (AS) > 94%, ammonium-nitrogen (NH4-N) > 84%, total nitrogen (TN) > 71%, total phosphorous (TP) > 87%, and E. coli (1.86 ± 1.54 log-removal). The mean concentrations of the targeted parameters at the outflow were in compliance with the requirements for discharge to the environment and met reclaimed water quality standards for agricultural irrigation, except for E. coli. Statistically significant (p < 0.05) results of pollutant mass removal rate across different HLRs indicated the potential effect of HLR on treatment performance, and HLR in a range of 67–80 L m–2 d–1 contributed to a higher removal efficiency without compromising the limit values. A comparatively low HLR of 45 L m–2 d–1 should be applicable if pathogen removal is the most important requirement. Plant species showed good plant vitality and adapted well to the water storage mat. The higher the mean ambient air temperature, the greater runoff reduction (>50%) was observed due to high evapotranspiration. The results showed the system is a promising green technology for GW recycling and can be scaled up for application to urban buildings.

Assessing water quality in the Pearl River for the last decade based on clustering: Characteristic, evolution and policy implications

The Pearl River (PR) is China's second-largest river, playing a crucial role in regulating and supplying water in the southeast. However, for the last decade, the PR has been experiencing water quality deterioration due to population growth, rapid economic development, and diverse human activities, particularly in its delta areas. This study analyzed the characteristics and evolution of eight water quality variables, including pH values (pH), water temperature (WT), dissolved oxygen (DO), five-day biochemical oxygen demand (BOD5), permanganate index (PI), total phosphorus (TP), ammonia nitrogen (NH3N), and fluoride (F−), which were monitored monthly at 16 water quality monitoring stations from January 2009 to August 2019. Overall, annual average BOD5 and F− concentrations met Class I water quality standards, while TP and NH3N conformed to lower standards. The cluster results showed noticeable differences for parameter grouping (DO-organic parameters-nutrient and solutes), seasonal variation (wet and dry), and water quality status (contaminated-remediating-fine). The Water Quality Index (WQI) ranged from 8.3 ("very poor") to 91.7 ("excellent") in the entire basin from 2009 to 2019, and NH3N-DO based WQImins were identified using the All-Subsets Linear Regression method. The fitting results of the Generalized Additive Models displayed that the deviance explained by natural factors ranged from 37.2% to 61.3%, while the socioeconomic explanation exceeded 70%. The WQImin component evolution (2003–2019) of Shenzhen River estuary, the most important part of the PR estuary, agreed with key parameter variations in heterogeneous clusters in the entire basin. Moreover, Shenzhen's water quality remediation applications indicated that reasonable-efficient-powerful efforts and support from governments could accelerate recovery. For the management departments, consistent measures should be strictly enforced, and elaborate regionalized management based on clusters could be attempted to maintain excellent water quality.

Agricultural Wastewater Treatment Using Oil Palm Waste Activated Hydrochar for Reuse in Plant Irrigation: Synthesis, Characterization, and Process Optimization

The best possible use of natural resources and the large amounts of trash produced by industrial and human activity is necessary for sustainable development. Due to the threat of global climate change and other environmental challenges, waste management systems are changing, leading to more instances of water resource management. The waste generated must be controlled from a sustainability point of view. Typically, the conventional disposal of Agricultural Wastewater (AW) and biomass can be achieved by recycling, reusing, and converting them into a variety of green products. To improve the AW quality for the purposes of environmental sustainability, Sustainable Development Goals (SDGs) 6 and 14, dealing with clean water, sanitation, and life below water, are very important goals. Therefore, the present investigation evaluates the effectiveness of a Bench-scale Activated Sludge Reactor (BASR) system for AW treatment. The BASR was designed to focus on getting the maximum possible utilization out of a biosorbent derived from oil palm waste activated hydrochar (OPAH). This is in accordance with SDG 9, which targets inorganic and organic waste utilization for added value. An experiment was developed using the Response Surface Methodology (RSM). A Hydraulic Retention Time (HRT) of 1–3 days was used in the bioreactor’s setup and operation, and Mixed Liquor Suspended Solids (MLSS) concentrations of 4000–6000 mg/L were used. BASR was fed with AW with initial mean concentrations of 4486 ± 5.63 mg/L and 6649 ± 3.48 for the five-day Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) experiments, respectively. The results obtained showed that maximum reductions of 84.66% and 72.07% were recorded for BOD5 and COD, respectively. Through RSM optimization, the greatest reductions in the amounts of organic materials were achieved with a 2-day HRT and an MLSS dosage of 5000 mg/L. Substrate elimination thresholds were assessed using the first-order, the Grau second-order, and the modified Stover–Kincannon models. The reported observations were found to be perfectly fit by the modified Stover–Kincannon model, with high R2 values of 0.9908 and 0.9931 for BOD5 and COD, respectively. As a result, the model may be used to design the BASR system and forecast how the reactor would behave. The findings from this study suggest that the developed OPAH has promising potential to be applied as eco-friendly material for the removal of BOD5 and COD from AW. Consequently, the study findings additionally possess the ability to address SDGs 6, 9, and 14, in order to fulfil the United Nations (UN) goals through 2030.

Sewage treatment decreased organic carbon resources in Hong Kong waters during 1986–2020

Riverine organic carbon (OC) transport plays a role in regulating terrestrial and marine carbon pools and deteriorating coastal water quality. However, long-term OC transport in Asian rivers and its diffusion in marginal seas have remained unreported. This study reported the spatiotemporal variations in OC resources for Hong Kong waters, China, based on monthly monitoring data collected at 82 river stations and 94 ocean sites during 1986–2020. The station-based riverine OC varied spatially and was generally high, with a mean value of 1.4–52.0 mg/L. Moreover, along with improving water quality, OC at 97.6% of the river stations decreased during 1986–2020; overall, sewage treatment accounted for 83.4% of the exponential decrease in riverine OC (R2 = 0.68, p < 0.01). However, the reduction in riverine OC accounted for only 10.4% of the reduction in the marine five-day biochemical oxygen demand (BOD5), which occurred at 70.2% of the ocean sites, especially those closest to the shore. The linear reduction in the marine BOD5 (R2 = 0.24, p < 0.01) was mainly attributed to reduced OC input from the adjacent Pearl River (61.9%) and decreases in phytoplankton growth (19.0%). These results indicated that sewage treatment improved water quality and decreased OC resources in Hong Kong waters, which can serve as a sustainable development model for other coastal cities. This study has important implications for mitigating organic pollution in the context of human efforts to manage the water environment.

In situ and self-adaptive BOD bioreaction sensing system based on environmentally domesticated microbial populations

Biochemical oxygen demand (BOD) is a water quality parameter of vital importance. Rapid BOD analysis methods have emerged to simplify the five-day BOD (BOD5) measurement protocol. However, their universal implementations are restricted by the tricky environmental matrix (including environmental microbes, contaminants, ionic compositions, etc.). Here, an in situ and self-adaptive BOD bioreaction sensing system consisting of a “gut-like” microfluidic coil bioreactor with self-renewed biofilm was proposed for the establishment of a rapid, resilient and reliable BOD determination method. With the spontaneous surface adhesion of environmental microbial populations, the biofilm was colonized in situ on the inner surface of the microfluidic coil bioreactor. Exploiting the environmental domestication during every real sample measurement, the biofilm was capable of self-renewal to adapt to the environmental changes and exhibited representative biodegradation behaviors. The aggregated abundant, adequate and adapted microbial populations in the BOD bioreactor rendered a total organic carbon (TOC) removal rate of 67.7% within a short hydraulic retention time of 99 s. As validated by an online BOD prototype, exceptional analytical performance was achieved in terms of reproducibility (relative standard deviation of 3.7%), survivability (inhibition by pH and metal ion interference of <20%) and accuracy (relative error of −5.9% to 9.7%). This work rediscovered the interactive effects of the environmental matrix on BOD assays and demonstrated an instructive attempt by making use of the environment to develop practical online BOD monitoring devices for water quality assessments.

An integrated risk assessment framework using information theory-based coupling methods for basin-scale water quality management: A case study in the Danjiangkou Reservoir Basin, China

As the second largest reservoir in China, the Danjiangkou Reservoir (DJKR) serves as the water source of the Middle Route of the South-to-North Water Diversion Project of China (MRSNWDPC), i.e., the currently longest (1273 km) inter-basin water diversion project in the world, for more than eight years. The water quality status of the DJKR basin has been receiving worldwide attention because it is related to the health and safety of >100 million people and the integrity of an ecosystem covering >92,500 km2. In this study, basin-scale water quality sampling campaigns were conducted monthly at 47 monitoring sites in river systems of the DJKRB from the year 2020 to 2022, covering nine water quality indicators, i.e., water temperature (WT), pH, dissolved oxygen (DO), permanganate index (CODMn), five-day biochemical oxygen demand (BOD5), ammonia nitrogen (NH3−N), total phosphorus (TP), total nitrogen (TN), and fluoride (F−). The water quality index (WQI) and multivariate statistical techniques were introduced to comprehensively evaluate water quality status and understand the corresponding driving factors of water quality variations. An integrated risk assessment framework simultaneously considered intra and inter-regional factors using information theory-based and the SPA (Set-Pair Analysis) methods were proposed for basin-scale water quality management. The results showed that the water quality of the DJKR and its tributaries stably maintained a “good” status, with all the average WQIs >60 of river systems during the monitoring period. The spatial variations of all WQIs in the basin showed significantly different (Kruskal-Wallis tests, P < 0.01), while no seasonal differences were found. The increase in built-up land use and agricultural water consumption revealed the highest contributions (Mantel's r > 0.5, P < 0.05) to the rise of nutrient loadings of all river systems, showing the intensive anthropogenic activities can eclipse the power of natural processes on water quality variations to some extent. The risks of specific sub-basins that may cause water quality degradation on the MRSNWDPC were effectively quantified and identified into five classifications based on transfer entropy and the SPA methods. This study provides an informative risk assessment framework that was relatively easy to be applied by professionals and non-experts for basin-scale water quality management, thus providing a valuable and reliable reference for the administrative department to conduct effective pollution control in the future.

Study of the characteristics of pollutants in rural domestic sewage and the optimal sewage treatment process: a Chengdu Plain case study.

Domestic sewage is an important source of surface water pollution in the rural areas of developing countries, especially in the rural areas of China. In recent years, with the strategy of rural revitalization, China has paid increasing attention to the treatment of rural domestic sewage. Therefore, 16 villages in the Chengdu Plain were selected for the study, and seven indicators were analyzed and evaluated, including pH, five-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total phosphorus (TP), suspended solids (SS) and total nitrogen (TN), in the water samples at the inlet and outlet of the wastewater treatment plant. The concentration of each pollutant in the rural scattered domestic sewage of the Chengdu Plain in Southwest China was obtained, and the concentration of each pollutant in domestic sewage was higher than that in summer. In addition, the preferred process for removing each pollutant was obtained by studying the effects of the treatment process, season and hydraulic retention time on the removal efficiency of each pollutant. The research results provide valuable references for the planning and process selection of rural domestic sewage treatment.

Sanitary landfill leachate treatment by aerated electrochemical Fenton process

The aerated electrochemical Fenton procedure was investigated as a viable treatment approach for electrolytic degradation and decolourization of sanitary landfill leachate. The optimization effects of initial pH, applied voltage, H2O2 concentration and combination of iron electrodes on detoxification were demonstrated by COD and colour removal from stabilized leachate, respectively. The study illustrates that, under the optimum experimental parameters voltage of 4.5 V, electrolysis time of 90 min, H2O2 dosage of 5 g/L, pH 3, 99% of chemical oxygen demand (COD) and 100% colour are removed from stabilized leachate, and the biodegradability ratio of the five-day biochemical oxygen demand (BOD5) to COD increases from 0.1 to 0.72. In addition, the pure catalytic metallic iron anode and cathode electrode used in the electrochemical Fenton process was first electro-oxidized to Fe2+ for use during the Fenton reaction, then with Fe3+ that was reverted back to Fe2+ under the applied electrochemical-magnetic field, resulting in the iron dissolution and regeneration circuit (Fe2+/Fe3+/Fe2+). Additionally, Fe2+/Fe3+ served as bridges for agglomerates to coalesce into big, closely packed particles for better filterability and sedimentation action. As a preparatory step for the biochemical treatment, this technology has been effectively used to treat stabilized landfill leachate containing toxic refractory recalcitrant organics on a large scale. Additionally, by estimating the scientific experiment with a regression model approach for the outcomes, RSM software was employed in order to standardize the ECF treatment process, significantly reducing the number of test cases and trials.

Characterization of Dissolved Organic Matter from Agricultural and Livestock Effluents: Implications for Water Quality Monitoring.

There is growing concern about the impact of agricultural practices on water quality. The loss of nutrients such as nitrogen and phosphorous through agricultural runoff poses a potential risk of water quality degradation. However, it is unclear how dissolved organic matter (DOM) composition is associated with pollution levels in water bodies. To address this, we conducted a cross-year investigation to reveal the nature of DOM and its relationship to water quality in agricultural effluents (AEs) and livestock effluents (LEs). We discovered that DOM fluorescence components of AEs were mainly from autochthonous and terrestrial sources, while in LEs it was primarily from autochthonous sources. LEs showed a higher β:α and biological index (BIX) than AEs, indicating that LEs had higher biological activity. Compared to the LEs, DOM in AEs exhibited a higher humification index (HIX), illustrating that DOM was more humic and aromatic. Overall, our results suggest that the BIX and fluorescence index (FI) were best suited for the characterization of water bodies impacted by LEs and AEs. Excitation-emission matrix spectroscopy and parallel factor (EEMs-PARAFAC) analysis showed that DOM in AEs was mainly a humic-like material (~64%) and in LEs was mainly protein-like (~68%). Tryptophan-like compounds (C1) were made more abundant in AEs because of the breakdown of aquatic vegetation. The microbial activity enhanced protein-like substances (C1 and C2) in LEs. Our study revealed a positive correlation between five-day biochemical oxygen demand (BOD5) concentrations and tyrosine-like substance components, suggesting that fluorescence peak B may be a good predictor of water quality affected by anthropogenic activities. For both LEs and AEs, our results suggest that peak D may be a reliable water quality surrogate for total phosphorus (TP).

Temperature sensitivity of oxygen demand varies as a function of organic matter source

Dissolved oxygen (DO) impairment within coastal waters is widespread and rising temperatures may exacerbate low DO levels by enhancing organic matter (OM) degradation. Here, the temperature sensitivity of OM degradation was investigated as DO decay rates determined during standard five-day biochemical oxygen demand (BOD) measurements conducted under different incubation temperatures. Sampling was conducted in the Waccamaw River watershed, South Carolina, a blackwater river with extensive forested wetland that also receives drainage from stormwater detention ponds associated with coastal development, thus providing different sources of contrasting OM composition. Temperature sensitivities were measured as Q10 temperature coefficients, which define how DO decay rates change with 10 degrees of warming. The average Q10 value for the wetland sites (2.14 ± 0.41) was significantly greater (p &amp;lt; 0.05) than those measured in either the River (1.49 ± 0.36) or stormwater ponds (1.41 ± 0.21). Furthermore, using Intergovernmental Panel on Climate Change intermediate-to-very high temperature estimates for 2100 of +2.7 – 4.4°C, average predicted increases in DO decay rates for wetlands (~22-39%) are more than double the River (~11-18%) and stormwater pond rates (~9-16%). Our findings for inland, coastal waters agree with previous results for soils, suggesting that temperature sensitivities are variable across sites and increase with more complex, lower quality OM. Future modeling scenarios of DO utilization must therefore consider the influence of OM heterogeneity and the temperature sensitivity response of OM degradation across sources and region to better predict how climate change may impact oxygen impairment in aquatic ecosystems.

Study on water quality simulation and dynamic water environment capacity of Helan County section of the third drainage ditch in Ningxia

The Helan section of the third drainage ditch in Ningxia is selected as the research object, and its water environmental capacity is analyzed; The Daily discharge and water level are calculated according to the measured data; Then the daily concentration values of the main water quality indexes are simulated by one-dimensional hydrodynamic water quality mathematical model; Finally, the dynamic water environment capacity is calculated. The results show that from May to October 2020, the main water quality indicators exceeding the standard in Helan section of the third drainage ditch were total nitrogen and five-day biochemical oxygen demand. Their water environmental capacity was −11.8744 t and −67.1173 t, respectively. Chemical oxygen demand and total phosphorus exceeded the standard severely in some months. There are problems of eutrophication and high organic content in drainage ditches. The primary pollution sources are aquaculture wastewater form fishery, farmland drainage, seasonal flood, and domestic sewage. It is suggested to take preventive measures such as source control, process blocking, and end treatment.

Small Hydropower Plants’ Impacts on the Ecological Status Indicators of Urban Rivers

Water is the basis of life for living creatures and is used for various purposes, especially in agriculture, industry, municipal services, and energy production. Assessing water quality in terms of its various uses is not without significance. This study investigates the water quality within two small hydropower plants (SHPs) in central European urban areas from an environmental perspective. Wrocław I and Wrocław II SHPs on the Odra River in Poland were selected as case studies. This study presents the results of four-year observations (2017–2020) conducted in different locations located upstream and downstream of the barriers. The following aspects were assessed: physicochemical status, trophic status, assessment of fish living conditions, and water quality indices. The results show that SHPs improved the average physicochemical status of the five-day biochemical oxygen demand (i.e., BOD5; by 6.19% comparing the results downstream and upstream of the SHPs), dissolved oxygen (3.85%), PO4-P (3.31%), and electrical conductivity (0.52%); however, they worsened in the case of the pH (by 2.63%) and NO3-N (by 1.83%). Water near the study cases is classified as mesotrophic or eutrophic. The conditions for salmonids and cyprinids were not met due to the increased concentrations of NO2 and BOD5 values; in the case of salmonids, also due to the temperature and dissolved oxygen concentration. The water quality indices differed and indicated the quality from poor to good, depending on the classification. This study provides important insights for policymakers regarding the awareness of the impacts of SHPs on water quality in urban areas and the immediate measure needed to be considered to improve aquatic habitat conditions.

Performance evaluation of the combined process of ozonation, biological activated carbon reinforced by bacterial consortium, and ultrafiltration in greywater treatment

Background: Background: Because of the growing population and increasing freshwater consumption, treatment and reuse of greywater have been widely considered. The application of a new and environmentally friendly treatment method for synthetic and real greywater (RGW) is of utmost importance. This study aimed to evaluate the efficiency of the combination of ozonation, biological activated carbon, and ultrafiltration (O3 /BAC/UF) in the removal of chemical oxygen demand (COD), turbidity, five-day biochemical oxygen demand (BOD5 ), and linear alkylbenzene sulfonates (LAS) from synthetic greywater and RGW. Methods: Bacillus Subtilis, Acinetobacter radioresistens, Pseudomonas aeruginosa, and Ochrobactrum oryzae were selected from nine pure bacterial species and transferred to granular activated carbon (GAC), then, mineral culture medium was added to the reactor for the growth and establishment of bacterial consortium. The SEM method was employed to ensure the formation of a microbial layer on GAC. Then, the continuous flow of synthetic greywater (for six months) at a low: 6.1, medium: 12.2, and high: 18.3 gCOD/L.d organic loading rates as well as RGW (for two weeks) entered the treatment system. Results: The percentages of COD removal in low, medium, and high organic loads of synthetic greywater and RGW were 85.12%, 79.05%, 85.3%, and 98.65%, respectively. Moreover, the percentages of BOD5 removal were 87%, 82%, 51%, and 92%, respectively. Furthermore, the percentages of turbidity removal were 93.5%, 97%, 96.69%, 73.33%, and the percentages of LAS removal were 91.4%, 88.1%, 84.8%, and 93.7%, respectively. Conclusion: The treatment system has a remarkable ability to remove pollutants from greywater and can be used as a new method of greywater treatment in Iran.

Evaluating optically and non-optically active water quality and its response relationship to hydro-meteorology using multi-source data in Poyang Lake, China

Lakes potentially provide sensitive indicators of global climate change, but water pollution seriously affects the lake ecosystem. Therefore, mapping and monitoring water quality of lake has attracted extensive attention from scholars. However, estimating optically active (OAPs) and non-optically water quality parameters (NOAPs) and clarifying their response relationship with hydro-meteorology still face great challenges. To resolve these issues, this paper presents an approach for assessing OAPs (Chlorophyll a (Chla), Total suspended matter (TSM)) and NOAPs (total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH4-N), five-day biochemical oxygen demand (BOD5)) in Poyang Lake, the largest freshwater lake in China, by using ensemble learning (SEL), combing leave-one-out validation and machine learning (LOOCV-ML) algorithms with multi-source remote sensing images. We further quantitatively evaluated retrieval accuracy differences between OAPs and NOAPs using multispectral and hyperspectral images. Meanwhile, a novel automatic extraction method was proposed in this paper for mapping water bodies. We systematically explored the response relationship between water quality (OAP and NOAP) and hydro-meteorology. We found that NOAPs achieved higher estimation accuracy than OAPs. The LOOCV-XGBoost and LOOCV-GradientBoost provided higher inversion accuracy of OAP and NOAP than SEL, demonstrating the great potential of combining OHS-2A hyperspectral images with LOOCV-ML to estimate the water quality in inland lakes. We revealed that the estimation accuracy (MRE) of TN and TP was 1.09 %-18.03 % higher than NH4-N and BOD5. Finally, we clarified that water temperature had a significantly negative effect on NH4-N and BOD5 (Projected importance of variables (VIP) > 1, Coefficient < -1), and sunshine hours produced a great positive effect on Chla, NH4-N and BOD5 (VIP > 1, Coefficient > 1), further revealing that water temperature, water body area, wind speed, rainfall, mean relative humidity and sunshine hours were important divers of OAPs and NOAPs changes. These results provide a scientific basis for restoration and protection of water quality in lake ecosystems.

Synthesis of a Doped α-Fe2O3/g-C3N4 Catalyst for High-Efficiency Degradation of Diazinon Contaminant from Liquid Wastes

In this work, a hematite/porous graphite carbon-nitride (α-Fe2O3/g-C3N4) catalyst was synthesized through the doping of hematite loaded onto porous graphite carbon-nitride using a heat treatment process. Then, the ability of catalyst was evaluated to degrade diazinon (DZN) for the first time, mainly via the sonophotocatalytic process. Among the samples, the greatest DZN degradation was observed in the sonophotocatalytic system, which separated 100% of DZN from the aqueous solution after 50 min, while the removal percentages for the sonocatalytic, photocatalytic, and adsorption systems were 72.9, 89.1, and 58.1%, respectively. The results of scavengers showed that both sulfate and hydroxyl radicals (•OH) participated in removing DZN, although positive holes and negative •OH played a major role. Moreover, the removal efficiencies of the target pollutant using the sonophotocatalytic process were higher than those using the photocatalytic, sonocatalytic, and adsorption processes. The reaction profile followed pseudo-first-order kinetics, and the reaction rate coefficient for the sonophotocatalytic system was 2.2 times higher than that of the photocatalytic system and 2.64 times higher than that of the sonocatalytic system. The energy consumption of the sonophotocatalytic system after 60 min was 11.6 kWh/m3, while it was 31.1 kWh/m3 for the photocatalytic system. A DZN removal percentage of 100% was obtained after 50 min under the following conditions: UV intensity of 36 watts, ultrasound frequency of 36 kHz, DZN concentration of 50 mg/L at pH 5, and α-Fe2O3/g-C3N4 dosage of 0.4 g/L. The catalyst reusability was examined with only a 9.9% reduction in efficiency after eight consecutive cycles. The chemical oxygen demand (COD) and total organic compound (TOC) removal percentages were 95.6% and 88.6%, respectively, and the five-day biochemical oxygen demand (BOD5)/COD ratio was 0.16 at the beginning of the degradation process and 0.69 at the end of the process. In addition, toxicological experiments showed that degradation of DZN by the sonophotocatalytic process exhibited low toxicity. All results confirmed that the sonophotocatalytic process using α-Fe2O3/g-C3N4 was a highly efficient process for DZN pollutant removal from liquid wastes.

A holistic assessment of spatiotemporal variation, driving factors, and risks influencing river water quality in the northeastern Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau (QTP) is the source for many of the most important rivers in Asia. It is also an essential ecological barrier in China and has the characteristic of regional water conservation. Given this importance, we analyzed the spatiotemporal distribution patterns and trends of 10 water quality parameters. These measurements were taken monthly from 67 monitoring stations in the northeastern QTP from 2015 to 2019. To evaluate water quality trends, major factors influencing water quality, and water quality risks, we used a series of analytical approaches including Mann-Kendall test, Boruta algorithm, and interval fuzzy number-based set-pair analysis (IFN-SPA). The results revealed that almost all water monitoring stations in the northeastern QTP were alkaline. From 2015 to 2019, the water temperature and dissolved oxygen of most monitoring stations were significantly reduced. Chemical oxygen demand, permanganate index, five-day biochemical oxygen demand, total phosphorus, and fluoride all showed a downward trend across this same time frame. The annual average total nitrogen (TN) concentration fluctuation did not significantly decrease across the measured time frame. Water quality index (WQI-DET) indicated bad or poor water quality in the study area; however, water quality index without TN (WQI-DET′) reversed the water quality value. The difference between the two indexes suggested that TN was a significant parameter affecting river water quality in the northeastern QTP. Both Spearman correlation and Boruta algorithm show that elevation, urban land, cropland, temperature, and precipitation influence the overall water quality status in the northeastern QTP. The results showed that between 2015 and 2019, most rivers monitored had a relatively low risk of degradation in water quality. This study provides a new perspective on river water quality management, pollutant control, and risk assessment in an area like the QTP that has sensitive and fragile ecology.