Dissolved Oxygen Concentration Research Articles

Explainable machine learning models for estimating daily dissolved oxygen concentration of the Tualatin River

ABSTRACT Monitoring the quality of river water is of fundamental importance and needs to be taken into consideration when it comes to the research into the hydrological field. In this context, the concentration of the dissolved oxygen (DO) is one of the most significant indicators of the quality of river water. The current study aimed to estimate the minimum, maximum, and mean DO concentrations (DO min, DO max, DO mean) at a gauging station located on Tualatin River, United States. To that end, four machine learning models, such as support vector regression (SVR), multi-layer perceptron (MLP), random forest (RF), and gradient boosting (GB) were established. Root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (R), and Nash-Sutcliffe efficiency (NSE) metrics were employed to better assess the accuracies of these models. The modeling results demonstrated that the SVR and MLP surpassed the RF and GB models. Despite this, the SVR was concluded to be the best-performing method when used to estimate the DO min, DO max, and DO mean. The best error statistics in the testing phase were related to the SVR model with full (four) inputs to estimate DO mean concentration (RMSE = 0.663 mg/l, MAE = 0.508 mg/l, R = 0.945, NSE = 0.875). Finally, the explainability of the superior models (i.e. SVR models) was conducted using SHapley Additive exPlanations (SHAP) for the first time to estimate DO concentration. In fact, evaluating the explainability of machine learning models can provide useful information about the impact of each of the input estimators used in the procedure of models development. It was concluded that the specific conductance (SC) and followed by water temperature (WT) could provide the most contributions for estimating the DO min, DO max, and DO mean concentrations.

Zooplankton of Pronskoye reservoir in August 2023

The aim of this study was to investigate the zooplankton of Pronskoye Reservoir during the summer period of 2023. Sampling and processing of hydrobiological zooplankton samples were carried out using standard methods in August 2023 at six monitoring stations in Pronskoye Reservoir. A total of 15 zooplankton taxa were identified in the samples: 6 taxa of rotifers, 5 taxa of cladocerans, and 4 taxa of copepods. On average, the abundance and biomass of zooplankton (mean values across stations) in Pronskoye Reservoir in August 2023 were 928.1 thousand individuals/m3 and 3.4 g/m3, respectively. Rotifers dominated in terms of abundance (63,5%), while cladocerans dominated in terms of biomass (40,3%). Pronskoye Reservoir exhibited above-average productivity in terms of zooplankton, which is favorable from a fisheries perspective. The abundance and biomass of zooplankton for all major groups (rotifers, cladocerans, and copepods) were higher in the lower part of the reservoir, separated from the middle and upper parts by a narrow neck. The increase in the abundance of the rotifer species Brachionus angularis was particularly noticeable in the lower part of the reservoir. The lower part of the water body is classified as highly productive, while the middle and upper parts has above-average productivity. The lower part of the reservoir is characterized by lower temperatures and lower dissolved oxygen concentrations in the water. The lower part of Pronskoye Reservoir exhibits a more diverse species composition compared to the middle and upper parts. It is evident that abiotic factors, in one way or another, determine the differences in the abundance, biomass, and species composition of zooplankton between the lower and upper parts of Pronskoye Reservoir.

Enhanced Removal of Dissolved Effluent Organic Matter in Wastewater Using Lignin-Based Biochar Supported Fe–Cu Bimetallic Oxide Catalyst

The effluent discharged from wastewater treatment facilities frequently enters the ocean, posing a considerable threat to the health of marine life and humans. In this paper, an alkali lignin-based biochar-loaded modified Fe–Cu catalyst (FeCu@BC) was prepared to remove soluble microbial products (SMP) from secondary effluent as disinfection by-products precursors at ambient temperature and pressure. The humic acid (HA) was taken as the representative substance of SMP. The results showed that the maximum removal efficiency of HA reached 93.2% when the FeCu@BC dosage, pH, initial HA concentration, and dissolved oxygen concentration were 5.0 g/L, 7, 100 mg/L, and 1.75 mg/L, respectively. After three cycles, the removal efficiency of HA could be maintained at more than 70%. The quenching experiments and electron spin resonance (EPR) results showed that •OH and 1O2 were involved in the degradation of HA in the FeCu@BC catalyst reaction system, with 1O2 playing a dominant role. Theoretical calculations confirmed that •OH and 1O2 were more prone to attack the C=O bond of the side chain of HA. After processing by the FeCu@BC catalyst, the yield of chlorinated disinfection by-products from secondary effluent had decreased in an obvious manner. This study provides a new solution to efficiently solve the problem of chlorinated disinfection by-products from HA.

Polyvinyl Chloride Microplastics Facilitate Nitrous Oxide Production in Partial Nitritation Systems.

Partial nitritation (PN) is an important partner with anammox in the sidestream line treating high-strength wastewater and primarily contributes to nitrous oxide (N2O) emissions in such a hybrid system, which also suffers from ubiquitous microplastics because of the growing usage and disposal levels of plastics. In this study, the influences of polyvinyl chloride microplastics (PVC-MPs) on N2O-contributing pathways were experimentally revealed to fill the knowledge gap on N2O emission from the PN system under microplastics stress. The long-term results showed that the overall PN performance was hardly affected by the low-dose PVC-MPs (0.5 mg/L) while obviously deteriorated by the high dose (5 mg/L). According to the batch tests, PVC-MPs reduced biomass-specific ammonia oxidation rates (AORs) by 5.78-21.94% and stimulated aerobic N2O production by 9.22-88.36%. Further, upon increasing dissolved oxygen concentrations from 0.3 to 0.9 mg O2/L, the degree of AOR inhibition increased but that of N2O stimulation was lightened. Site preference analysis in combination with metabolic inhibitors demonstrated that the contributions of hydroxylamine oxidation and heterotrophic denitrification to N2O production at 0.3 mg O2/L were enhanced by 18.84 and 10.34%, respectively, accompanied by a corresponding decreased contribution of nitrifier denitrification. Finally, the underlying mechanisms proposed for negative influences of PVC-MPs were bisphenol A leaching and reactive oxygen species production, which led to more cell death, altered sludge properties, and reshaped microbial communities, further resulting in enhanced N2O emission. Overall, this work implied that the ubiquitous microplastics are a hidden danger that cannot be ignored in the PN system.

Sea level rise from climate change is expected to increase the release of arsenic into Bangladesh's drinking well water by reduction and by the salt effect.

Over 165,000,000 people live in Bangladesh; approximately 97% of Bangladeshis drink well water. Approximately 49% of Bangladesh's area has drinking well water with arsenic (As) concentrations that exceed the 10 micrograms per liter (μg/L) World Health Organization (WHO) guideline. This exposure to a potent carcinogen is a significant threat to public health. About 21% of Bangladesh is flooded each year during a typical monsoon season. As climate change progresses, sea levels will continue to rise, and the area and duration of these annual floods will increase. We hypothesize that these consequences of climate change can increase the release of arsenic from sediments into Bangladesh's drinking well water. Drinking well water samples were collected during a national-scale survey in Bangladesh. The dissolved oxygen concentration, oxidation-reduction potential, specific conductance, pH, and temperature were measured at sampling with calibrated portable electronic sensors. The arsenic concentration was measured by the silver diethyldithiocarbamate method. As the concentration of dissolved oxygen decreases, the concentration of arsenic increases (p-value = 0.0028). Relatedly, as the oxidation-reduction potential decreases, the concentration of arsenic increases (p-value = 1.3×10-5). This suggests that arsenic is released from sediments into Bangladesh's drinking well drinking water by reduction. As the specific conductance increases, the concentration of arsenic increases (p-value = 0.023). This suggests that arsenic is also released from sediments into water by the salt effect. Rising sea levels can cause a decrease in the dissolved oxygen concentration and oxidation-reduction potential of the underlying aquifer; this should increase the dissolution of insoluble arsenate (H3-xAs(V)O4x-) in sediments by reduction. This, in turn, should release soluble arsenite (H3-xAs(III)O3x-) into the drinking well water. Rising sea levels can cause an increase in the salt concentration of the underlying aquifer; this should increase the release of arsenic from sediments into the drinking well water by the salt effect.

Comprehensive Evaluation of Tomato Growth Status under Aerated Drip Irrigation Based on Critical Nitrogen Concentration and Nitrogen Nutrient Diagnosis.

In order to provide a theoretical basis for the rational application of nitrogen fertilizer for tomatoes under aerated drip irrigation, a model of the critical nitrogen dilution curve was established in this study, and the feasibility of the nitrogen nutrition index (NNI) for the real-time diagnosis and evaluation of the nitrogen nutrient status was explored. The tomato variety "FENOUYA" was used as the test crop, and aerated drip irrigation was adopted by setting three levels of aeration rates, namely, A1 (dissolved oxygen concentration of irrigation water is 5 mg L-1), A2 (dissolved oxygen concentration of irrigation water is 15 mg L-1), and A3 (dissolved oxygen concentration of irrigation water is 40 mg L-1), and three levels of nitrogen rates, namely, N1 (120 kg ha-1), N2 (180 kg ha-1) and N3 (240 kg ha-1). The model of the critical nitrogen concentration dilution of tomatoes under different aerated treatments was established. The results showed that (1) the dry matter accumulation of tomatoes increased with the increase in the nitrogen application rate in a certain range and it showed a trend of first increase and then decrease with the increase in aeration rate. (2) As the reproductive period progressed, the nitrogen concentration in tomato plants showed a decreasing trend. (3) There was a power exponential relationship between the critical nitrogen concentration of tomato plant growth and above-ground biomass under different levels of aeration and nitrogen application rate, but the power exponential curves were characterized by A1 (Nc = 15.674DM-0.658), A2 (Nc = 101.116DM-0.455), A3 (Nc = 119.527DM-0.535), N1 (Nc = 33.819DM-0.153), N2 (Nc = 127.759DM-0.555) and N3 (Nc = 209.696DM-0.683). The standardized root mean square error (n-RMSE) values were 0.08%, 3.68%, 3.79% 0.50%, 1.08%, and 0.55%, which were less than 10%, and the model has good stability. (4) The effect of an increased nitrogen application rate on the critical nitrogen concentration dilution curve was more significant than that of the increase in aeration rate. (5) A nitrogen nutrition index model was built based on the critical nitrogen concentration model to evaluate the nitrogen nutritional status of tomatoes, whereby 180 kg ha-1 was the optimal nitrogen application rate, and 15 mg L-1 dissolved oxygen of irrigation water was the optimal aeration rate for tomatoes.

Towards a generic model evaluation metric for non-normally distributed measurements in water quality and ecosystem models

Model evaluation is a crucial process in model development and quantified model evaluation metrics play a pivotal role in model calibration and validation. However, in current water quality and ecosystem models, conventional model evaluation metrics are derived from hydrological models and often overlook the non-normal distribution of water quality and ecological state variables. In this study, we proposed a series of metrics that consider non-normal distributions by modifying components of the Kling-Gupta efficiency. Subsequently, we tested the existing metrics and newly proposed metrics using four different synthetic datasets and the actual simulation case of total phosphorus, chlorophyll a, and dissolved oxygen concentrations. The results demonstrate that the newly proposed metric, Fu-Zhang efficiency, which replaces the ratio of standard deviations with the ratio of interquartile ranges to measure dispersion similarity, is more suitable for evaluating simulation results with lots of outliers in the measurements. Our study reveals the hidden perils in conventional integrated model evaluation metrics of water quality and ecosystem models and calls for the development of comprehensive and feasible quantitative evaluation frameworks to drive the next paradigm shift.

First screening of bacteria assemblages associated with the marine polychaete Melinna palmata Grube, 1870 and adjacent sediments

Bacteria associated with marine invertebrate play a fundamental role in the biology, ecology, development and evolution of their hosts. Although many studies have been focused on the microbial populations of benthic and pelagic habitats, little is known about bacteria colonizing tube-dwelling polychaete. In this context, the current study provided the first characterization of the Melinna palmata Grube, 1870 microbiome based on Illumina sequencing of 16S rRNA gene of the polychaete tissue and proximate sediments collected from the Black Sea, Romania, along a 24.2 m – 45.4 m depth-gradient. The diversity, taxonomic composition and deduced functional profile of the tissue and sediments associated bacterial communities were compared and analyzed in relation with the environmental parameters. This polychaete harbored a distinct bacterial assemblage as compared to their sediments and independent on the depth of their habitat, including 8 phyla in tissues dominated by Proteobacteria, and 12 phyla in sediments majorly represented by Actinobacteriota, respectively. At order level, Synechococcales, Rhodobacterales and Actinomarinales were highly represented in the M. palmata microbiome, while Microtrichales, Anaerolineales and Caldilineales were mostly found in sediments. A significant correlation was observed between Cyanobacteria taxa and the dissolved oxygen concentrations in shallow waters impacted by the Danube inputs. Meanwhile, this phylum showed a positive correlation with Planctomycetota colonizing the invertebrate tissues, and a negative one with Actinobacteriota and Chloroflexi found in sediments. The deduced functional profile of these bacterial assemblages suggested the prevalence of the amino acid and carbohydrate metabolism for both analyzed matrices. This pioneering report on the M. palmata microbiome highlighted the environment contribution to bacterial species enrichment of the polychaete, and provided a glimpse on the putative role of microbial communities associated with this marine organism.

A Reconstructing Model Based on Time–Space–Depth Partitioning for Global Ocean Dissolved Oxygen Concentration

Dissolved oxygen (DO) is essential for assessing and monitoring the health of marine ecosystems. The phenomenon of ocean deoxygenation is widely recognized. Nevertheless, the limited availability of observations poses a challenge in achieving a comprehensive understanding of global ocean DO dynamics and trends. The study addresses the challenge of unevenly distributed Argo DO data by developing time–space–depth machine learning (TSD-ML), a novel machine learning-based model designed to enhance reconstruction accuracy in data-sparse regions. TSD-ML partitions Argo data into segments based on time, depth, and spatial dimensions, and conducts model training for each segment. This research contrasts the effectiveness of partitioned and non-partitioned modeling approaches using three distinct ML regression methods. The results reveal that TSD-ML significantly enhances reconstruction accuracy in areas with uneven DO data distribution, achieving a 30% reduction in root mean square error (RMSE) and a 20% decrease in mean absolute error (MAE). In addition, a comparison with WOA18 and GLODAPv2 ship survey data confirms the high accuracy of the reconstructions. Analysis of the reconstructed global ocean DO trends over the past two decades indicates an alarming expansion of anoxic zones.

The formation and adsorption mechanism studies of 3D hydrangea-like ZnFe-LDHs/FeOOH for the highly efficient removal of phosphate

Phosphate in water can cause a series of problems such as overgrowth of algae and other aquatic organisms, foul-smelling, turbid water and lower dissolved oxygen concentrations, thereby posing a serious threat to human health and environment. To efficiently remove phosphate from water, three-dimensional hydrangea-like ZnFe-layered double hydroxides/FeOOH composites (3D hydrangea-like ZnFe-LDHs/FeOOH) were designed and prepared by a facile urea hydrothermal method. The maximum adsorption capacity of phosphate by 3D hydrangea-like ZnFe-LDHs/FeOOH reached about 200 mg·g−1, much higher than that of ZnFe-LDHs prepared by co-precipitation method (53 mg·g−1) and other reported adsorbents, which confirmed that 3D morphology contributed to the improvement of adsorption capacity. Time-dependent experiments were designed to explore the formation mechanism of 3D hydrangea-like structure and the results indicated directional aggregation and epitaxial growth were two main processes. Batch experiments were conducted to investigate adsorption behavior of phosphate. The adsorption kinetics and isotherms showed that the adsorption process followed the quasi-first-order kinetics and Langmuir model. Besides, 3D hydrangea-like ZnFe-LDHs/FeOOH could be regenerated effectively and recycled at least three times. 3D hydrangea-like ZnFe-LDHs/FeOOH possessed fascinating performance in phosphate removal from real river samples and laundry detergent samples, with the removal rates of 66–100 % and 80–100 %, respectively. Furthermore, 3D hydrangea-like ZnFe-LDHs showed good adsorption performance towards other anionic dyes, including Congo Red and Orange Yellow II, with the maximum adsorption capacity of 867 mg·g−1 and 225 mg·g−1, indicating its widespread applicability. The adsorption mechanism of phosphate by 3D hydrangea-like ZnFe-LDHs was furtherly investigated, mainly containing metal coordination, anion exchange between layers and electrostatic interactions.

Metals and biogenic substances’ migration ability in the «bottom sediments – water» system under natural and experimental conditions


 
 
 The paper considers the results of long-term studies on some chemical elements’ migration (Al, Fe, Ti, Mn, Cu, Zn, Pb, N, P, Si) in the «bottom sediments – water» system of surface water bodies under the effect of different aquatic environment factors. The greatest effect is made by water bodies’ oxygen regime, pH, and presence of dissolved organic substances, in particular humic substances. The migration of manganese, iron, inorganic nitrogen and phosphorus from bottom sediments is controlled mostly by oxygen regime. Migration of these chemical elements significantly increases, when there is oxygen deficiency and anaerobic conditions are formed in the bottom water layer. It has been observed in both natural and experimental conditions. Man- ganese concentration increases in bottom water in 25–50 times, iron – in 1.3–13, inorganic nitrogen – in 5.3–19.3, and inorganic phosphorus – in 2.8–23 times. The dissolved oxygen concentration hardly has any effect on the migration of aluminium, titanium, copper, zinc, lead, and silicon from bottom sediments into the water. The chemical elements’ migration is significantly affected by a decrease in pH of water contacting with bottom sediments and the presence of humic substances in it. High humic substances concentrations promote a reduction in water pH and oxygen content, which is consumed for their oxidation. A case study of several water bodies illustrates the cumulative effect of water pH lowering, anaerobic conditions at the solid and liquid phases’ interface, as well as complexation with humic substances on chemical elements’ migration from bottom sediments. Experimental modeling has shown that the metal migration from bottom sediments occurs both due to their labile fractions and complex compounds with dissolved organic matter, especially with humic substances of low molecular weight (≤2.0 kDa). The share of the metal labile fraction gets higher, when water pH decreases. Under recent climate change, the probability of water’s secondary pollution with different chemicals increases significantly in summer. This is mainly caused by oxygen deficiency, water pH lowering, and reducing conditions at the «bottom sediments – water» interface with hydrogen sulphide being formed. This is especially true for highly eutrophic water bodies subject to human impact. The aquatic environment toxicity can get considerably higher due to the migration of chemicals with strong toxic properties from bottom sediments, as well as labile metal fractions, marked by higher bioavailability for hydrobionts.
 
 

Continuing long-term expansion of low-oxygen conditions in the Eastern Gulf of Finland

To develop an oxygen indicator for the eastern part of the Gulf of Finland (EGOF), a dataset covering 1900–2021 was compiled. The analysis revealed a long-term declining trend in dissolved oxygen concentrations in the EGOF deep layer of 0.022 mg L–1 a–1 and multi-decadal variations associated with the observed changes in hydrographic conditions. About 27% of the decline in oxygen concentrations for 1900–2021 and 40% for 1990–2021 can be explained by the decrease in solubility due to the temperature increase and changes in hydrographic conditions. The water volume and bottom area under low oxygen conditions in 2016–2021, characterized by dissolved oxygen concentrations <= 6 mg L–1, have increased, compared to the selected reference period with almost no human impact in the 1920s–1950s, from 9.8 km3 to 78.0 km3 (from 2.6% to 20.9% of the EGOF total volume) and from 1190 km2 to 4950 km2 (from 13.4% to 56.0% of the EGOF total area), respectively. The environmental status of the EGOF was assessed as not good based on the introduced oxygen indicator. We conclude that, in the long-term, low oxygen conditions have expanded mostly due to the excess load and accumulation of nutrients in the system and temperature-related changes in biogeochemical processes and fluxes. However, on a decadal scale, changes in hydrographic conditions, i.e. stratification and mixing, can significantly impact the sub-surface oxygen conditions in the EGOF and similar estuarine basins.

Assessment of the status of selected heavy metals in water, sediments and a fish species (Oreochromis niloticus) of commercial value in Lake Nakuru with a focus on human health risks

AbstractThe present study presents selected water quality parameters and the levels of heavy metals in water, sediments and Nile tilapia (Oreochromis niloticus) of Lake Nakuru. Nine sediments and nine water samples, as well as 30 specimens of Nile tilapia, were collected from the northern part of the lake. Physical parameters were measured in situ using multiple probes and metres. Heavy metals were analysed using an atomic absorption spectrophotometer (AAS). The pH, dissolved oxygen concentration, temperature, salinity and electrical conductivity ranged from 9.52 to 9.72, 4.58 to 8.62 mg/L, 23.40°C to 25.7°C, 2.39‰ to 2.81‰ and 4470–5226 μs/cm, respectively. Heavy metal levels (mean ± SD) were generally low in the water samples. Chromium values ranged between 7.16 and 9.19 mg/kg dw in sediment samples, and between 3.7 and 13.06 mg/kg dw in fish samples. Lead values ranged between 12.5 and 31.04 mg/kg dw in sediment samples and 4.06 and 9.95 mg/kg dw in fish samples. Arsenic values ranged between 9.5 and 21.7 mg/kg dw in sediments and below detectable limit to 2.11 mg/kg dw in fish samples. Mercury values ranged between .14 and .31 mg/kg dw in sediment samples and .12 and .35 mg/kg dw in fish samples. Cadmium was the only heavy metal concentration that was below the detection limit in the three matrices. Significant differences were observed for some heavy metal concentrations in water, sediments and fish across sites (p &lt; .05). The levels of lead and chromium in fish were above the East African Standard, World Health Organization and European Union limits. The results of the present study recommend a possible reclassification of the lake, an immediate ban on fish harvesting and consumption from Lake Nakuru and a policy intervention on the fishery and pollution management.

Cycling Rates of Particulate Organic Carbon Along the GEOTRACES Pacific Meridional Transect GP15

AbstractUnderstanding particle cycling processes in the ocean is critical for predicting the response of the biological carbon pump to external perturbations. Here, measurements of particulate organic carbon (POC) concentration in two size fractions (1–51 and &gt;51 μm) from GEOTRACES Pacific meridional transect GP15 are combined with a POC cycling model to estimate rates of POC production, (dis)aggregation, sinking, remineralization, and vertical transport mediated by migrating zooplankton, in the euphotic zone (EZ) and upper mesopelagic zone (UMZ) of distinct environments. We find coherent variations in POC cycling parameters and fluxes throughout the transect. Thus, the settling speed of POC in the &gt;51 μm fraction increased with depth in the UMZ, presumably due to higher particle densities at depth. The settling flux of total POC (&gt;1 μm) out of the EZ was positively correlated with primary production integrated over the EZ; the highest export occurred in the subarctic gyre while the lowest occurred in the subtropical gyres. The ratio of POC settling flux to integrated primary production was low (&lt;5%) along GP15, which suggests an efficient recycling of POC in the EZ in all trophic regimes. Specific rates of POC remineralization did not show clear variations with temperature or dissolved oxygen concentration, that is, POC recycling was apparently controlled by other factors such as microbial colonization and substrate lability. Particle cohesiveness, as approximated by the second‐order rate constant for particle aggregation, was negatively correlated with trophic regime: particles appeared more cohesive in low‐productivity regions than in high‐productivity regions.

Multimetric socio‐ecological assessment of water hyacinth (Eichhornia crassipes (Mart) solms) invasion of an urban Ramsar wetland lake

AbstractWater hyacinth (Eichhornia crassipes (Mart) solms), a widely distributed invasive aquatic plant in Sri Lanka, has invaded the Diyawannawa wetland lake located in Colombo city, which is the first Ramsar wetland city in South Asia. The present study was conducted to assess the water quality parameters that influence the distribution of water hyacinth and to identify the environmental, economic, and social consequences of its invasion of the Diyawannawa wetland. Five sampling sites were selected from the Diyawannawa lake, and the water pH, temperature, conductivity, total dissolved solids (TDS), salinity, dissolved oxygen concentration (DO), nitrate concentration, and total phosphorus concentration were measured at monthly intervals in the rainy and dry seasons of 2020. The abundance of water hyacinth was recorded at each site at each sampling event. Interviews and focus group discussions (FGDs) were conducted with the representatives of the community associated with the wetland to assess the ecological, economic and social effects of water hyacinth invasion. Principal component analysis of the water quality parameters revealed that phosphorus and nitrate concentrations in water significantly influenced the abundance of water hyacinth. Further, the water quality index (WQI) indicated poor water quality in the sites invaded by water hyacinth. The interviews and FGDs revealed that water hyacinth invasion has adversely affected the lake's fisheries and navigation pathways and increased the frequency of flooding, resulting in an increased mosquito population. The results of the present study highlighted the importance of implementing water quality management programmes in the Diyawannawa wetland to control the invasion of water hyacinth. Further, we recommend increasing community participation in water hyacinth control programmes and providing opportunities for the community to engage in self‐employment activities associated with the uses of water hyacinth.

Spiers Memorial Lecture: Lithium air batteries - tracking function and failure.

The lithium-air battery (LAB) is arguably the battery with the highest energy density, but also a battery with significant challenges to be overcome before it can be used commercially in practical devices. Here, we discuss experimental approaches developed by some of the authors to understand the function and failure of lithium-oxygen batteries. For example, experiments in which nuclear magnetic resonance (NMR) spectroscopy was used to quantify dissolved oxygen concentrations and diffusivity are described. 17O magic angle spinning (MAS) NMR spectra of electrodes extracted from batteries at different states of charge (SOC) allowed the electrolyte decomposition products at each stage to be determined. For instance, the formation of Li2CO3 and LiOH in a dimethoxyethane (DME) solvent and their subsequent removal on charging was followed. Redox mediators have been used to chemically reduce oxygen or to chemically oxidise Li2O2 in order to prevent electrode clogging by insulating compounds, which leads to lower capacities and rapid degradation; the studies of these mediators represent an area where NMR and electron paramagnetic resonance (EPR) studies could play a role in unravelling reaction mechanisms. Finally, recently developed coupled in situ NMR and electrochemical impedance spectroscopy (EIS) are used to characterise the charge transport mechanism in lithium symmetric cells and to distinguish between electronic and ionic transport, demonstrating the formation of transient (soft) shorts in common lithium-oxygen electrolytes. More stable solid electrolyte interphases are formed under an oxygen atmosphere, which helps stabilise the lithium anode on cycling.

Effect of Dissolved Oxygen Content on Photocatalytic Performance of Graphene Oxide

Effect of Dissolved Oxygen Content on Photocatalytic Performance of Graphene Oxide

Lake Water Quality Assessment Based on Multispectral Unmanned Aerial Vehicle Images and In-Situ Testing

In recent years, Universiti Tun Hussein Onn Malaysia has experienced several developments in buildings and road construction. A stormwater retention pond was built as a part of the construction plan to prevent the occurrence of floods downstream of the development sites. However, poor monitoring and maintenance of the pond caused water contamination, which had bad effects on the nearby environment and lake ecosystem. Therefore, this study was conducted to assess the current water quality in the pond by using a combination between Multispectral Unmanned Aerial Vehicle images and in-situ sampling. Four water quality parameters were investigated, namely turbidity, dissolved oxygen, temperature, and pH. Aerial images were taken using a multispectral aerial mapping camera attached to UAV. The in-situ testing was performed on the same day of image capturing at 5 different locations. According to the results, it was found that the pH and water temperature were within the normal levels with maximum and minimum values of 7.34 and 6.94 for pH and 28.39oC and 28.04oC for temperature, respectively. Turbidity readings appaired with a significant variation with a maximum value of 30.9 NTU at the lake outlet and a minimum value of 18.8 NTU at the middle of the lake. Dissolved oxygen concentration was noticed to be low, with an average value of 4.3 mg/l. Water quality mapping showed the concentration distribution of each water quality parameter along the lake surface. In each map, the differences in terms of colours were found to be not significant because of the size of the lake, which is relatively small, as well as because of the small differences in terms of water quality ridings at each sampling point.

Artificial Intelligence for Water Quality

Abstract: This study delves into how AI can be applied within water and environmental engineering research, particu- larly emphasizing the utilization of machine learning models to advance the accuracy of water quality predictions in the Delaware River. Through an analysis of time series data spanning from 2020 to 2022 and the utilization of exploratory data analysis methods, this investigation scrutinizes various elements influenc- ing the dynamics of water quality. For water quality time series analysis, identifying changes in long-term trends is important, yet identifying specific change-points is also important[3]. A strong correlation is notably detected between levels of dissolved oxygen and recorded temperatures. Leveraging this correlation, an intricate polynomial regression model is crafted to forecast dissolved oxygen concentrations based on expected temperature values. This predictive model not only clarifies the inherent link between dissolved oxygen and temperature but also offers insights into projecting future dissolved oxygen levels in the Delaware River, considering anticipated temperature fluctuations. These findings hold significant promise, potentially enhancing ecologi- cal evaluations and the development of impactful management strategies, specifically designed for water quality monitoring and conservation efforts within the Delaware River basin. Hence, eval- uation of water quality of groundwater is extremely important to prepare for remedial measures[1].

Synthesis of gold nanoparticles with allicin to modify boron-doped diamond surface for oxygen sensor applications

Modification of surface of boron-doped diamond (BDD) film with gold nanoparticles (AuNPs) was carried out to increase its catalytic activity for an application as an oxygen sensor. Allicin was isolated from garlic by salting out extraction technique, and then used as the capping agent to synthesize AuNPs as it has a double bond structure that could be reacted to attach the BDD surface under UV light radiation. An average size of AuNPs at around 46,00 ± 9,06 nm was obtained, while the modification of the BDD surface by the synthesized AuNPs indicated that the surface of BDD could be covered by gold at around 0.6 % (w/w). Investigation of the AuNPs-modified BDD as a working electrode for the oxygen reduction by using cyclic voltammograms in 0.1 M phosphate buffer solution pH 7 observed a current peak at around -0.45 V (vs. Ag/AgCl). The current of this peak linearly increased proportionally to the dissolved oxygen concentrations (R2=0.9986). Moreover, a limit of detection of the dissolved oxygen of 0.12 ppm and limit of quantity 0.41 ppm could be achieved with excellent stability at 6.86% RSD with 6 repetitions and sensitivity at 19.086 μA/ppm indicated that the modified BDD is promising for applications as an oxygen sensor.