Modelling Euphrates river water quality index based on field measured data in Al-Diwaniyah City, Iraq.

Pollution monitoring in surface water using field observational procedure is a challenging matter as it is time consuming, and needs a lot of efforts. This study addresses the challenge of efficiently monitoring and predicting water pollution using a GIS-based artificial neural network (ANN) to detect heavy metal (HM) pollution in surface water and effect of wastewater required discharge on the Euphrates River in Al-Diwaniyah City, Iraq. The study established using 40 water sampling stations and incorporates Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-OES) to assess HM levels.

Data-driven water quality prediction for wastewater treatment plants.

Monitoring and managing wastewater treatment plants (WWTPs) is crucial for environmental protection. The presection of the quality of treated water is essential for energy efficient operation. The current research presents a comprehensive comparison of machine learning models for water quality parameter prediction in WWTPs.

Occurrence of pharmaceuticals in rice (Oryza sativa L.) plant through wastewater irrigation.

The present investigation focuses on the identification of popular PhACs in roots, leaves and rice grains, which are cultivated in soil irrigated with waters and wastewater. The present study reveals the presence of PhACs in rice grains from different brands which are available in the current market, which has thus motivated these experiments. The rice plants were cultivated in garden containers and irrigated with three different water sources.

Removal of pharmaceutical compounds and toxicology study in wastewater using Malaysian fungal Ganoderma lucidum.

Elevated usage of pharmaceutical products leads to the accumulation of emerging contaminants in sewage. In the current work, Ganoderma lucidum (GL) was used to remove pharmaceutical compounds (PCs), proposed as a tertiary method in sewage treatment plants (STPs). The PCs consisted of a group of painkillers (ketoprofen, diclofenac, and dexamethasone), psychiatrists (carbamazepine, venlafaxine, and citalopram), beta-blockers (atenolol, metoprolol, and propranolol), and anti-hypertensives (losartan and valsartan).

Heavy metals prediction in coastal marine sediments using hybridized machine learning models with metaheuristic optimization algorithm.

This study proposes different standalone models viz: Elman neural network (ENN), Boosted Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As (mg/kg)) and zinc (Zn (mg/kg)) in marine sediments owing to anthropogenic activities. A heuristic algorithm based on the potential of RVM and a flower pollination algorithm (RVM-FPA) was developed to improve the prediction performance. Several evaluation indicators and graphical methods coupled with visualized cumulative probability function (CDF) were used to evaluate the accuracy of the models.

Mycoremediation of Industrial Textile Wastewater Using Ganoderma lucidum Pellets and Activated Dolomite in Batch Bioreactor.

In the world of fast fashion, textile industries are blooming rapidly to meet the consumer's demands. However, vast amounts of wastewater have been constantly produced, and it is becoming a serious environmental problem in the waterways. Although the technology for treating textile wastewater has been well reported and established, more sustainable efforts have taken the attention nowadays.

Water Quality Assessment and Decolourisation of Contaminated Ex-Mining Lake Water Using Bioreactor Dye-Eating Fungus (BioDeF) System: A Real Case Study.

The environmental conditions of a lake are influenced by its type and various environmental forces such as water temperature, nutrients content, and longitude and latitude to which it is exposed. Due to population growth and development limits, former mining lakes are being converted to more lucrative land uses like those of recreational zones, agriculture, and livestock. The fungus Ganoderma lucidum has the potential to be utilised as a substitute or to perform synergistic bacteria-coupled functions in efficient contaminated lake water treatment.

Machine learning models development for accurate multi-months ahead drought forecasting: Case study of the Great Lakes, North America.

The Great Lakes are critical freshwater sources, supporting millions of people, agriculture, and ecosystems. However, climate change has worsened droughts, leading to significant economic and social consequences. Accurate multi-month drought forecasting is, therefore, essential for effective water management and mitigating these impacts.

Convolutional neural network-multi-kernel radial basis function neural network-salp swarm algorithm: a new machine learning model for predicting effluent quality parameters.

A wastewater treatment plant (WWTP) is an essential part of the urban water cycle, which reduces concentration of pollutants in the river. For monitoring and control of WWTPs, researchers develop different models and systems. This study introduces a new deep learning model for predicting effluent quality parameters (EQPs) of a WWTP.

Role of ascomycete and basidiomycete fungi in meeting established and emerging sustainability opportunities: a review.

Fungal biomass is the future's feedstock. Non-septate Ascomycetes and septate Basidiomycetes, famously known as mushrooms, are sources of fungal biomass. Fungal biomass, which on averagely comprises about 34% protein and 45% carbohydrate, can be cultivated in bioreactors to produce affordable, safe, nontoxic, and consistent biomass quality.

Determination and risk assessment of pharmaceutical residues in the urban water cycle in Selangor Darul Ehsan, Malaysia.

The environmental fate of non-steroidal anti-inflammatory drugs (NSAIDs) in the urban water cycle is still uncertain and their status is mainly assessed based on specific water components and information on human risk assessments. This study (a) explores the environmental fate of NSAIDs (ibuprofen, IBU; naproxen, NAP; ketoprofen, KET; diazepam, DIA; and diclofenac, DIC) in the urban water cycle, including wastewater, river, and treated water gas chromatography-mass spectrophotometry (GCMS), (b) assesses the efficiency of reducing the targeted NSAIDs in sewage treatment plant (STP) using analysis of variance (ANOVA), and (c) evaluates the ecological risk assessment of these drugs in the urban water cycle teratogenic index (TI) and risk quotient (RQ). The primary receptor of contaminants comes from urban areas, as a high concentration of NSAIDs is detected (ranging from 5.

The occurrence of non-steroidal anti-inflammatory drugs (NSAIDs) in Malaysian urban domestic wastewater.

The water stream has been reported to contain non-steroidal anti-inflammatory drugs (NSAIDs), released from households and premises through discharge from Sewage Treatment Plant (STP). This research identifies commonly consumed NSAIDs namely ibuprofen (IBU), diclofenac (DIC), ketoprofen (KET) and naproxen (NAP) in the influent wastewater from two urban catchments (i.e.

Functionalization of remote sensing and on-site data for simulating surface water dissolved oxygen: Development of hybrid tree-based artificial intelligence models.

Dissolved oxygen (DO) is an important indicator of river health for environmental engineers and ecological scientists to understand the state of river health. This study aims to evaluate the reliability of four feature selector algorithms i.e.

Strength enhancement of concrete using incinerated agricultural waste as supplementary cement materials.

The potassium (K) and sodium (Na) elements in banana are needed for hydration reaction that can enhance the strength properties of concrete. This research aims (a) to determine the material engineering properties of banana skin ash (BSA) and concrete containing BSA, (b) to measure the strength enhancement of concrete due to BSA, and (c) to identify optimal application of BSA as supplementary cement materials (SCM) in concrete. The BSA characterization were assessed through X-ray fluorescence (XRF) and Blaine's air permeability.

Optimization of mycoremediation treatment for the chemical oxygen demand (COD) and ammonia nitrogen (AN) removal from domestic effluent using wild-Serbian Ganoderma lucidum (WSGL).

The fungi-based technology, wild-Serbian Ganoderma lucidum (WSGL) as myco-alternative to existing conventional microbial-based wastewater treatment is introduced in this study as a potential alternative treatment. The mycoremediation is highly persistent for its capability to oxidatively breakdown pollutant substrates and widely researched for its medicinal properties. Utilizing the nonhazardous properties and high degradation performance of WSGL, this research aims to optimize mycoremediation treatment design for chemical oxygen demand (COD) and ammonia nitrogen (AN) removal in domestic wastewater based on proposed Model 1 (temperature and treatment time) and Model 2 (volume of pellet and treatment time) via response surface methodology (RSM).

Dataset of computed N-value and factual N-value traced for Soil Subsurface Profiling.

Soil requires load bearing impact assessment for stability. Therefore, this study aims to utilize the multi-channel analysis surface wave (MASW) for soil subsurface investigation and profiling around Peninsular Malaysia. The standard penetration test (SPT) was conducted for comparison between factual and computed from shear wave velocity ( ) obtained from MASW using the Imai and Tonouchi equation.

Dataset on leaching properties of coal ashes from Malaysian coal power plant.

Coal combustion by-products (CCPs) (i.e. fly (FA) and bottom (BA) ashes) generated by power plants contain heavy metals.

Dataset on specific UV absorbances (SUVA) at stretch components of Perak River basin.

Perak River basin is in Perak state of Peninsular Malaysia. In this research, the river stretch serves as water intake for domestic, agricultural and industrial purposes in Perak Tengah, Hilir Perak and Manjung regions. It is located in mixed use area whilst exposing the river to anthropogenic elements.

Forecasting shear stress parameters in rectangular channels using new soft computing methods.

Shear stress comprises basic information for predicting the average depth velocity and discharge in channels. With knowledge of the percentage of shear force carried by walls (%SFw) it is possible to more accurately estimate shear stress values. The %SFw, non-dimension wall shear stress ([Formula: see text]) and non-dimension bed shear stress ([Formula: see text]) in smooth rectangular channels were predicted by a three methods, the Bayesian Regularized Neural Network (BRNN), the Radial Basis Function (RBF), and the Modified Structure-Radial Basis Function (MS-RBF).

Performance of wild-Serbian Ganoderma lucidum mycelium in treating synthetic sewage loading using batch bioreactor.

The fluctuation of domestic wastewater characteristic inhibits the current conventional microbial-based treatment. The bioremediation fungi has received attention and reported to be an effective alternative to treat industrial wastewater. Similar efficient performance is envisaged for domestic wastewater whereby assessed performance of fungi for varying carbon-to-nitrogen ratios in domestic wastewater is crucial.

Step by step procedures: Degradation of polycyclic aromatic hydrocarbons in potable water using photo-Fenton oxidation process.

Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic compounds, composed of two or more fused benzene rings and abundantly found in mixed-use areas. Mixed-use areas consist of dense population, urbanization, industrial and agricultural activities. River pollution are common in mixed-use areas and 98% of Malaysia's fresh water supply originates from surface water.

Spatial and temporal risk quotient based river assessment for water resources management.

Malaysia depends heavily on rivers as a source for water supply, irrigation, and sustaining the livelihood of local communities. The evolution of land use in urban areas due to rapid development and the continuous problem of illegal discharge have had a serious adverse impact on the health of the country's waterways. Klang River requires extensive rehabilitation and remediation before its water could be utilised for a variety of purposes.