Indicators Of Organic Pollution Research Articles

Exploring the impact of urban pollution on ciliate diversity along the Sapucaí River (Minas Gerais, Brazil) via DNA metabarcoding.

Protists are diverse single-celled eukaryotes found in various habitats. They exhibit a wide range of forms and functions, representing a significant portion of the eukaryotic tree of life, which also includes animals, plants, and fungi. Due to their high sensitivity to environmental changes, these organisms are widely used as biological indicators of organic pollution. We investigated the molecular diversity of ciliate protists at seven strategic points along the Sapucaí River (Itajubá, Minas Gerais State, Brazil), to assess the impact of urban pollution on the richness, abundance, and diversity indexes of these communities. For each sampling point, values of physicochemical parameters were also recorded. DNA sequences were obtained by high-throughput sequencing (HTS) and analyzed using the V4 18S-rRNA molecular marker, employing the DNA metabarcoding method. We recorded 125 ciliate taxonomic units (OTUs), with nearly 80% corresponding to the classes Spirotrichea, Oligohymenophorea, and Litostomatea. At the genus level, 54 OTUs (43.2%) were identified, spanning 28 genera. The composition of ciliates varied significantly along the river's course, from upstream to downstream of Itajubá city. Samples collected from the urban area displayed the lowest richness and diversity, corroborating the influence of the pollution gradient on these communities. The physicochemical parameters showed little variation among the samples and were not linked to the observed changes in ciliate communities, revealing that these organisms are strongly affected by environmental changes and respond more sensitively to these disturbances than physicochemical parameters, emphasizing their potential as bioindicators.

Drinking water safety evaluation in the selected sub-Saharan African countries: A case study of Madagascar, Uganda and Rwanda

In the sub-Saharan region of Africa, access to safe drinking water remains limited in many countries. This study provides an overview of the quality of surface water and groundwater in rural and peri-urban areas of Madagascar, Uganda, and Rwanda. Selected physico-chemical parameters, inorganic species (including inorganic ions), and organic pollution indicators, such as total organic carbon, non-ionic surfactants, cationic surfactants, anionic surfactants, sum of phenolic compounds and formaldehyde, were analysed. Principal component analysis was applied to assess the variability of the water quality and identify regional dependencies. The inorganic ion composition in the majority of the studied samples meets WHO and EU requirements for drinking water intended for human consumption and poses no human health risk. However, an individual non-cancer-causing health index for nitrates and the values of Water Quality Index show a possible threat of ingesting the studied drinking water. The presence of surfactants (0.1–0.65 mgL−1), phenolic compounds (0.025–1.76 mgL−1) and formaldehyde (0.04–0.32 mgL−1) may also pose a risk to human, animal, and aquatic life. Additionally, in-situ measurements for E. coli and Total Coliforms conducted during the last field campaign in Madagascar (2022) revealed that all studied drinking water sources ranged from intermediate risk to unsafe. This result calls for the urgent need to enhance WASH (water, sanitation, and hygiene) services in the studied areas. The presence of both chemical and microbiological pollutants shows the need for the local authorities to develop and implement a catchment management plan to ensure the protection of water resources from potential pollution, and raise community awareness about the impact of human activity on water resources.

Comparative study for the performance of pure artificial intelligence software sensor and self-organizing map assisted software sensor in predicting 5-day biochemical oxygen demand for Kauma Sewage Treatment Plant effluent in Malawi

Introduction: Modeling plays a crucial role in understanding wastewater treatment processes, yet conventional deterministic models face challenges due to complexity and uncertainty. Artificial intelligence offers an alternative, requiring no prior system knowledge. This study tested the reliability of the Adaptive Fuzzy Inference System (ANFIS), an artificial intelligence algorithm that integrates both neural networks and fuzzy logic principles, to predict effluent Biochemical Oxygen Demand. An important indicator of organic pollution in wastewater.Materials and Methods: The ANFIS models were developed and validated with historical wastewater quality data for the Kauma Sewage Treatment Plant located in Lilongwe City, Malawi. A Self Organizing Map (SOM) was applied to extract features of the raw data to enhance the performance of ANFIS. Cost-effective, quicker, and easier-to-measure variables were selected as possible predictors while using their respective correlations with effluent. Influents’ temperature, pH, dissolved oxygen, and effluent chemical oxygen demand were among the model predictors.Results and Discussions: The comparative results demonstrated that for the same model structure, the ANFIS model achieved correlation coefficients (R) of 0.92, 0.90, and 0.81 during training, testing, and validation respectively, whereas the SOM-assisted ANFIS Model achieved R Values of 0.99, 0.87 and 0.94. Overall, despite the slight decrease in R-value during the testing stage, the SOM- assisted ANFIS model outperformed the traditional ANFIS model in terms of predictive capability. A graphic user interface was developed to improve user interaction and friendliness of the developed model. Integration of the developed model with supervisory control and data acquisition system is recommended. The study also recommends widening the application of the developed model, by retraining it with data from other wastewater treatment facilities and rivers in Malawi.

Spatial Trends and Distribution Patterns of Toxic Heavy Metal Contamination in an Urbanized Watershed

Rapid urban growth in developing nations exacerbates pressures on water resources through increased pollution loading if management practices cannot adapt efficiently. This study evaluated industrial effluent impacts on river systems in Nigeria contaminated by discharge from beverage, oil and biscuit manufacturing plants. Physicochemical parameters and heavy metal concentrations were monitored at sites upstream and downstream from waste outfalls during wet and dry seasons. Results demonstrated exceedances of national water quality standards for indicators of organic pollution like biochemical oxygen demand and chemical oxygen demand. Notably, highly toxic heavy metals exceeded World Health Organization limits by over 100 times, posing serious public health concerns through various exposure pathways. Seasonal variations reflected changes in pollution inputs. Spatial trends showed metal levels decreasing with distance, though remaining well above safe levels 100m downstream. A predictive transport model was formulated based on field measurements incorporated into the advection-dispersion equation. Key coefficients for the dispersion rate and velocity/dispersion ratio were quantified, allowing simulation of concentration changes under differing scenarios. Model predictions closely aligned with observed metal distribution patterns. Findings highlight the need for upgraded wastewater treatment and emissions controls to mitigate pollution over-burdening natural assimilative capacity. Continuous monitoring programs should track remediation effectiveness. This study provides insights to help authorities balance rapid industrialization, environmental protection and sustainable development goals through evidence-based regulatory strategies ensuring public health.

Analyzing retraction responses of Tubifex tubifex (Oligochaeta: Naididae) colonies to copper treatments through a digital image analysis approach for developing early biological warning systems.

Biological monitoring and assessments are commonly used for sustainable ecosystem management. Oligochaetes are found in various freshwater ecosystems and have been used as indicators of water quality and for the biological assessment of aquatic ecosystems. Among aquatic oligochaetes, the sludge worm Tubifex tubifex (Oligochaeta, Naididae) is tolerant to organic pollution and has been used as a biomonitoring indicator of toxicity and organic pollution. In this study, we investigated the response of worm colonies to copper (CuSO4) treatments (0.01, 0.05, 0.1, 0.5, and 1.0mg/L) in an observation cage (100mL beaker) for 30min. Using a digital image analysis approach, we measured the changes in the colony image area between pre- and post-copper treatment. After copper treatment, the colony image area tended to decrease, even at low copper concentrations. In addition, the colony areas did not recover to their original levels at high concentrations, although those at low concentrations did. Area decreased proportional to the logarithm of the copper concentration. Finally, our results present the possible use of the retraction responses of Tubifex tubifex colonies to chemical disturbances as early biological warning systems.

Ecological Influence of Organic Pollution on the Distribution of Benthic Macroinvertebrates in Some Control Forest Watercourses in Cameroon

Monitoring of water quality and distribution of some benthic macroinvertebrates was carried out in a few control watercourses in the Mefou watershed, from August 2022 to June 2023 with the aim of identifying some ecological factors that influence the distribution of benthic organisms in forest areas. The evaluation of granulometric and physicochemical quality was carried out following the appropriate methods and the collection of benthic organisms following the multihabitat approach. The analysis of the particle size parameters shows that the coarse fraction dominates all the points explored, although the beginning of siltation was observed in the middle part of the Abouda and Fam rivers. Physico-chemical analyses revealed a relatively stable environment with well-oxygenated water, low values of organic pollution indicator parameters and low and constant temperatures throughout the watersheds. The analysis of the biological structure shows a total of 8483 individuals collected, all belonging to the arthropod phylum and the insect class. From the orders obtained, Hemiptera dominate the benthic fauna with 6 identified families. The organisational structure of the benthic community was analysed through the calculation of diversity and fairness indices and allows us to affirm that the benthic macroinvertebrate community is diverse and well organised.

Spatiotemporal Variation Analyses of Water Quality, Fish Ecological Guilds, and the Longitudinal Connectivity in Musim Stream

The main objectives of this study were to analyze the spatiotemporal variations of water quality, fish ecological guilds and longitudinal connectivity in the weirs of Musim Stream. Fish were collected at 44 sites during spring and fall seasons for the analysis of trophic guilds, tolerance guilds, and the ecological stream health, based on FAI model. Total 33 species were observed in the stream and the dominant species were <i>Zacco platypus</i> and <i>Squalidus qracilis majimae</i>. Mean values of BOD and COD, as an indicator of organic matter pollution, showed high in the drought spring and low in fall (post-monsoon season). Also, TP showed same pattern with the BOD and COD pattern. The hierarchical clustering, based on the fish compositions, classified as three groups (up-stream, mid-stream and the down-stream). Based on the NMDS (Non-metric Multidimensional Scaling) analysis of fish abundance, high similarity was observed between S1-S5 sites, which were consistent with the results of hierarchical cluster analysis. Fish ecological guilds in the upper stream showed a high similarity between the insectivore and sensitive species, while in the middle and lower reaches, high similarity was found between the omnivore and intermediate species. Evaluations of longitudinal connectivity, based on the structural and hydrological characteristics of the weir, indicated all disconnections by the weirs, except for S15, in the spring. Stream ecological health, based on the FAI model, was significantly (<i>p</i> < 0.05, n=37) influenced by the height of overflow (<i>Hu1</i>). Overall, our study suggests that the longitudinal connectivity, based on the weir structures, flow regime and fish swimming capacity, were blocked off by the weirs in the stream. The results provide valuable insights for securing river management strategies and served as the fundamental data for stream restoration in the future.

Investigating the Plankton Diversity and Physicochemical Properties in a Temple Pond in Tamil Nadu, India: Taxonomic Composition, Seasonal Variations, and Ecological Implications

The present study explores the dynamics of phytoplankton and zooplankton in the Swetharanyeswarar temple pond located in the Mayiladuthurai district of Tamil Nadu, India. The study investigates species composition, diversity, and seasonal variations of these microscopic organisms, considering the ecological implications for the local food chain. Phytoplankton (Seven species), dominated by diatoms, cyanobacteria, and various other taxa, plays a fundamental role as primary producers, influencing nutrient cycling and climate patterns. The presence of Microcystis sp., associated with harmful algal blooms, emphasizes the need for monitoring and understanding its ecological implications. Zooplankton (13 species), including Rotifera, Copepods, and Calanoids, showcases a diverse community with distinct taxonomic members. The Rotifer community peaks in January, gradually declining, while Copepods exhibit notable diversity in April. Calanoids, represented by Macrocyclops albidus and Macrocyclops fuscus, display temporal fluctuations in diversity indices, indicating potential ecological changes influenced by environmental factors. The population of each zooplankton group is expressed as an average number of individuals per liter. Water quality parameters, crucial for understanding ecological dynamics, were meticulously measured in triplicates. Statistical analyses were conducted using Microsoft Excel to process and present the data as percentages.
 The study establishes a connection between zooplankton dynamics and physicochemical parameters, highlighting correlations with turbidity, pH, and organic pollution indicators, as per the methods of APHA. Monthly variations in zooplankton populations reveal dynamic ecological patterns influenced by temperature and organic matter. The species richness index reflects a well-balanced distribution within the planktonic community, suggesting a healthy and resilient ecosystem in the Swetharanyeswarar temple pond. Statistical analysis involves expressing the zooplankton population as an average number of individuals per liter and presenting water quality parameters as percentages using Microsoft Excel. These findings underscore the importance of continued monitoring to decipher long-term trends and implement targeted strategies for maintaining water quality and ecosystem health. Overall, this research contributes valuable insights into the intricate relationships between phytoplankton, zooplankton, and environmental factors in a freshwater ecosystem, providing a foundation for informed fisheries management strategies and conservation efforts.

The effect of organic pollution on the seasonal dynamics of water quality in a semi-arid zone: case of the Hammam Boughrara Dam, Tlemcen (Algeria).

The present study aims to assess the impact of human activities on the water quality of the Hammam Boughrara dam. It also highlights the crucial importance of sustainable management of water resources in the face of persistent challenges related to various forms of pollution. The study is based on an exhaustive database covering a period spread over 16 years, with monthly measurements of organic pollution indicator parameters, namely BOD5, COD, [Formula: see text],[Formula: see text], [Formula: see text], [Formula: see text], Organic Matter (OM), TDS, Dissolved Oxygen (DO) and pH. The box plots showed an asymmetric distribution of almost all the parameters, with significant seasonal variations in the interquartile (IQR) range. The IQR ranges for [Formula: see text] extends from 0.575 mg/l (summer) to 4.445 mg/l (spring), and for [Formula: see text] from 1.3075 mg/l (autumn) to 1.8625 mg/l (spring). This led to the use of the Spearman method for the analysis of correlations between different parameters. The seasonal study of the five categories of water quality, according to the Organic Pollution Index (OPI), revealed considerable organic pollution. At the 1% significance level, the seasonal correlation between OPI and [Formula: see text] varies between -0.71 and -0.85, while that with [Formula: see text] fluctuates between -0.69 and -0.86. During the period analyzed, the COD/BOD Ratio (CBR) reveals two dominant categories with seasonal variations, i.e. the Moderately Biodegradable Effluents (MBE), with 96 cases, reaching 29 in autumn and 20 in spring. The Difficult to Biodegrade or Non-Biodegradable Effluents (DBE or NBE) category records 94 cases, with a maximum frequency of 26 in winter and minimum of 21 in autumn. These results therefore show the persistence of organic pollution, which had an impact on water quality over the four seasons and throughout the period studied. The results indicate persistent organic pollution affecting water quality. Therefore, prompt actions and sustainable strategies are deemed necessary to mitigate these harmful impacts and to ensure the sustainability of the water resource.

Effectiveness of Chemical Oxygen Demand as an Indicator of Organic Pollution in Aquatic Environments

The chemical oxygen demand (COD) is an essential indicator of organic pollution that represents the amount of bulk carbon in water. COD is strongly correlated with nutrient cycles and other pollutants in the environment, but it has a limited ability to quantify the amount of organic carbon (OC), of which a large proportion is made up of refractory dissolved organic carbon (RDOC) and is a potential carbon sink. Moreover, the biodegradability of OC in terms of its fate and destination should be explored, as well as how this is reflected by COD. Methods based on particle size, spectroscopy, and isotopic tracing are expected to help with deciphering the bioavailability of COD-responsive OC and explore the processes of biogeochemical cycles. As the pressure on the environment from anthropogenic inputs increases, understanding the bioavailability of OC associated with COD will help with developing more precise scientific indicators for environmental monitoring and identifying how new tools will increase knowledge of the carbon cycle. In this review, we discuss the application, scope, means, and advances of COD measurement. Based on data in the literature, we estimate the global RDOC stock and assess the impact of anthropogenic RDOC on the carbon cycle in offshore bays. This review presents new insights into the behavior of OC in aquatic environments and a potential pathway for ocean negative carbon emissions by expanding the role of RDOC as a carbon sink to offset the effect of anthropogenic carbon emissions.

Levels of Ammonia and Phosphates as Indicators of Organic Pollution of Morna River, Akola District of Maharashtra, India

Levels of Ammonia and Phosphates as Indicators of Organic Pollution of Morna River, Akola District of Maharashtra, India

Correlations between organic pollution indicators in municipal wastewater

The paper presents the results of a study of parameters used for determining the amount of organic pollutants in wastewater flowing into a collective wastewater treatment plant with a population equivalent of about 120 000 PE. The plant constituted part of a sewage system. Assays were performed for biochemical oxygen demand (BOD5), chemical oxygen demand (CODCr), permanganete index (CODMn) and total organic carbon (TOC). In addition, the pH of wastewater and its alkalinity were determined. Sampling of incoming wastewater and measurement of physicochemical parameters were performed once a week, in the spring. A total of 44 samples of wastewater were collected. The correlations between the individual parameters and the correlations between the ratios of these parameters were determined. It was found that it was possible to estimate, with suffi cient accuracy, the values of selected parameters for determining the concentrations of organic compounds in municipal wastewater, knowing the values of other parameters in this group. Moreover, it was shown that, knowing the relationship between the analyzed parameters, one can find multiple regression equations for a given type of wastewater, which allow one to calculate the remaining relationships with a good fit, i.e. a determination factor R2greater than 0.6

Seasonal Dynamics of Microphytobenthos Distribution in Three Ecotopes on a Mussel Farm (Black Sea)

As the production of cultured bivalve mollusks is increasing worldwide, there is a growing need to study the biodiversity and ecology of microalgae in the mariculture zones. This study presents multiannual data (obtained in 2015–2016 and 2018–2020) on the species composition, abundance, biomass, and community structure of microphytobenthos from three mussel farm ecotopes (mussel shells, the epiphyton of twenty macroalgal species, and sediments under collectors). In total, 150 microalgal taxa were found, including 135 diatom species with a predominance of benthic (76%), marine (65%), and cosmopolite (30%) ones. In all habitats, 10 potentially harmful species and 44 indicators of organic pollution were noted. The maximum values on the mussel shells (abundance N = 119 × 103 cells/cm2 and biomass B = 0.0489 mg/cm2) were recorded in winter with the dominance of Tabularia fasciculata; in summer, the epiphyton was on the brown alga Nereia filiformis (N = 1001 × 103 cells/cm2 and B = 2.06 mg/cm2) with the dominance of toxic Pseudo-nitzschia seriata, on the red alga Phyllophora crispa (N = 1118 × 103 cells/cm2 and B = 3.24 mg/cm2) with the dominance of T. fasciculata, and in sediments (N = 104 × 103 cells/cm3 and B = 0.046 mg/cm3) with the dominance of T. fasciculata and Bacillaria paxillifer. Statistically significant effects of the ecotope and sampling season on the diatom composition were noted. The strongest effect of temperature is observed for the mussel shell diatoms, for which the trend of abundance and biomass increase in winter and their decrease in summer is most noticeable. But in sediments, the effect of the season is reflected only in the permanent changes of the microalgae species composition. For the epiphyton, it was shown that it is temperature, rather than substrate macrophyte species, that affects its numerical structure.

Углеводы в поверхностных водах Карелии и их связь с содержанием биогенных и органических веществ

The results of a long-term research of the content of carbohydrates in natural waters of Republic of Karelia (Russia) from 2011 to 2020 are summarized. In total, 34 water bodies (29 lakes and 5 rivers) were studied in different hydrological seasons. The presented sample of water bodies captures almost all types of surface waters in the humid zone in terms of trophicity and humus content. It was found that the carbohydrates concentration varies widely from 0.7 to 53.1 mg/L (average 3.3 mg/L) and its share of total organic matter averages 16%. It was revealed that the content and distribution of carbohydrates in surface waters depends both on natural (the level of trophicity and humus content in the reservoir) and anthropogenic factors (eutrophication, trout farms, industrial wastewater discharge, seepage waters of solid waste landfills, communal wastewater). In addition, all the studied water bodies were categorized into two groups according to the water pollution degree: contaminated and uncontaminated. It was revealed that the concentration of carbohydrates in contaminated water bodies of Karelia is on average 1.4 times higher than in uncontaminated ones. In addition, the content of carbohydrates increases together with such chemical parameters as 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD Cr), permanganate oxygen demand (COD Mn), chlorophyll a, mineral and total phosphorus (Pmin and Р total relatively) and ammonium (N-NH 4+). In particular, these relations are pronounced in contaminated water bodies, where the highest values of the correlation coefficient between the above parameters are noted. The content of carbohydrates in surface waters is a complex indicator of both organic and biogenic water pollution.

Trophic status determination of the Egyptian Eastern Mediterranean Sea based on phytoplankton diversity and their biochemical contents

The present study attempted to test the applicability of using phytoplankton as a bioindicator for assessing water quality along the Eastern Alexandria coast, Egypt. Eight stations were selected to cover the different characteristics of seawater during the summer 2022. Six algal groups were detected in different ratios: Bacillariophyceae, Cyanophyceae, Dinophyceae, Chlorophyceae, Silicoflagellata, and Euglenophyceae. Phytoplankton abundance was found highest at the Port Said (PS) beach, and the lowest abundance was detected at Ras El Bar (RB) beach. According to the evaluation of phytoplankton abundance, all the studied stations are oligotrophic state except PS was eutrophic. Based on Chl a concentration, the selected stations could be described as good-bad from west to east. The Shannon diversity and Pielou evenness indexes classified the studied stations as being moderate pollution except for PS and RB stations. The existence of organic pollution indicators species like Navicula, Synedra, and Euglena is a warning indication of the declining water quality especially in B and M stations. The biochemical compositions of the collected phytoplankton were spatial fluctuated. Protein and carbohydrates were the dominant macromolecules in the phytoplankton community compared with lipids. These macromolecules are used to assess trophic states whereas the ratio between protein and carbohydrate > 1 represents a healthy coast as observed in some stations. Thus, phytoplankton should be considered a bioindicator within Water Framework Directive monitoring programs for the Mediterranean Sea. For the long-term monitoring of the Mediterranean Sea’s ecosystem, it is recommended that the macromolecules of phytoplankton should be determined.

Optimized photodegradation of palm oil agroindustry waste effluent using multivalent manganese-modified black titanium dioxide.

This article presents a methodological approach to use manganese (Mn3+Mn7+)-modified black titanium dioxide (Mn/BTiO2) as a photocatalyst to optimize and improve visible-light-driven photodegradation of treated agro-industrial effluent (TPOME). A modified wet chemical process was used to prepare BTiO2. The BTiO2 was then wet impregnated with Mn and calcined at 300 °C for 1 h to produce Mn/BTiO2. The activity of Mn/BTiO2 was investigated in terms of photo-assisted elimination of chemical oxygen demand (COD), phenolic compounds (PCs), color, and total organic carbon (TOC). Using the design of experiments (DOE), the conditions of the photocatalytic process, including photocatalyst loading, Mn concentration, hydrogen peroxide (H2O2) dose, and irradiation time, were optimized. Under the optimum conditions (0.85 g/L photocatalyst loading, 0.048 mol/L H2O2 dose, 0.301 wt.% Mn concentration, and 204 min irradiation time) COD, PCs, color, and TOC removal efficiencies of 88.87%, 86.04%, 62.8%, and 84.66%, respectively, were obtained. Statistical analysis showed that the response variable's removal from TPOME estimation had high R2and low RMSE, MSE, MAD, MAE, and MAPE values, indicating high reliability. This study demonstrated the significant potential of the developed photocatalytic system for the treatment of waste effluent generated by the palm oil industry and other agro-industries, with the ability to simultaneously reduce a number of organic pollution indicators (OPIs).

A Method of Water COD Retrieval Based on 1D CNN and 2D Gabor Transform for Absorption-Fluorescence Spectra.

Chemical Oxygen Demand (COD) is one of the indicators of organic pollution in water bodies. The rapid and accurate detection of COD is of great significance to environmental protection. To address the problem of COD retrieval errors in the absorption spectrum method for fluorescent organic matter solutions, a rapid synchronous COD retrieval method for the absorption-fluorescence spectrum is proposed. Based on a one-dimensional convolutional neural network and 2D Gabor transform, an absorption-fluorescence spectrum fusion neural network algorithm is developed to improve the accuracy of water COD retrieval. Results show that the RRMSEP of the absorption-fluorescence COD retrieval method is 0.32% in amino acid aqueous solution, which is 84% lower than that of the single absorption spectrum method. The accuracy of COD retrieval is 98%, which is 15.3% higher than that of the single absorption spectrum method. The test results on the actual sampled water spectral dataset demonstrate that the fusion network outperformed the absorption spectrum CNN network in measuring COD accuracy, with the RRMSEP improving from 5.09% to 1.15%.

Study of organic pollution indicators in two stations of the Garmat Ali River, Basra, Iraq

Water is one of the most important natural sources for sustaining life, as human life and various activities depend on it. The current study dealt with knowing the effect of organic pollution on physical and chemical properties in Garmat Ali river, which was represented in two stations, the first station called Al-Mashab, and the second Al-Sindbad. Water and sediment samples were collected monthly during the period from August, 2016 to July, 2017. Numbers of physical and chemical variables were measured during this period (water temperature, light penetration, pH, Salinity, dissolved oxygen, biological demand oxygen, chemical demand oxygen, total nitrogen, total phosphorus and total organic carbon in sediment). The results of the study was showed that water temperature were ranged between 13.2-31.3°C for the first station and 13.4-33.1°C for the second station. The light penetration values were ​​ranged between 20.6-58.5 cm for the first station and 35-65 cm for the second station. The pH values were ​​ranged between 7.5-8.6 for the first station and 7.5-8.5 for the second station. Salinity values were ​​ranged between 1.58-3.16 g/l for the first station and 0.92-2.13 g/l for the second station. Dissolved oxygen values were ​​ranged between 4.66-10.8 mg/l for the first station and 11.85-6.26 mg/l for the second station. The values ​​of BOD5 were ​​ranged between 1.1-4.26 mg/l for the first station and 0.75-4.06 mg/l for the station. The values ​​of the COD were ranged between 8-120 mg/l for the first station and 8-61 mg/l for the second station. Total nitrogen values were ​​ranged between 2.8-29.4 mg/l for the first station and 2.4-33.6 mg/l for the second station. The total phosphorus values were ​​ranged between 1.11-19.6 mg/l for the first station and between 1.24-19.98 mg/l for the second station. Total organic carbon values were ​​ranged between 0.36-2.19% for the first station and 0.32-2.94% for the second station. The two stations were recorded a little increased in organic pollution levels during summer months and first station (Al-Mashab) was most affected.

Spatio-temporal variation in phytoplankton community structure in backwaters of the Ketar River, central Ethiopia

This study assessed the spatio-temporal dynamics of the phytoplankton community in backwaters of the Ketar River, central Ethiopia, in relation to water quality and macrophyte coverage. Phytoplankton samples and physicochemical information were collected at six sites along the river over 1 year (December 2017 to November 2018). Phytoplankton was collected using a 15-μm mesh net. A total of 56 species belonging to three algal phyla were identified; the most diverse phylum was Bacillariophyta (35 species), followed by Chlorophyta (13 species) and Euglenophyta (eight species). Bacillariophyta had the highest abundance and contributed 80.08% of the total phytoplankton abundance. Site 6 in the downstream portion had the highest abundance and greatest diversity of phytoplankton species. The algal phyla present showed significant differences in species diversity and abundance both spatially and temporally. Redundancy analysis results revealed that the spatial distribution of phytoplankton in the river positively correlated with pH, electrical conductivity, dissolved oxygen and nitrate-nitrogen, while water temperature and total suspended solids correlated negatively. Some indicators of organic pollution suggest that the water quality of the river is progressively declining, meriting close monitoring.

Hydrothermal carbonization of sewage sludge: Hydrochar properties and processing water treatment by distillation and wet oxidation

Hydrothermal carbonization is an innovative method of sewage sludge disposal. The solid product hydrochar (c.a.10%), may be converted to a fuel or fertilizer. Gaseous products (less than 10%) are mainly CO2 and nitrogen, but c.a. 80% of post-processing liquid presents as a challenging issue due to its high toxicity. Therefore, the main aim of this study was to determine the potentiality of hydrochars derived from sewage sludge as a fuel, at two temperatures: 200 and 220 °C, and 2 h of residence time, and successfully utilize the filtrates after the implementation of an adequate purification process. The results of hydrochars depicted better energy properties and dewaterability than in the case of raw sewage sludge, including improved chemical composition, a higher fixed carbon content and fuel ratio, and it also gained more effective filtration. The comprehensive analysis of the Thermal Analysis data proved that hydrochar can be combusted, but based on X-ray Fluorescence data a high tendency to slagging and contamination is expected. The highly toxic processing liquids indicated a great need for an appropriate treatment. Accordingly, distillation and the preliminary study of wet oxidation processes were applied. In both methods the chemical oxygen demand, an indicator of organic pollution, was significantly reduced.