River water quality assessment using environmentric techniques: case study of Jakara River Basin

Jakara River Basin has been extensively studied to assess the overall water quality and to identify the major variables responsible for water quality variations in the basin. A total of 27 sampling points were selected in the riverine network of the Upper Jakara River Basin. Water samples were collected in triplicate and analyzed for physicochemical variables. Pearson product-moment correlation analysis was conducted to evaluate the relationship of water quality parameters and revealed a significant relationship between salinity, conductivity with dissolved solids (DS) and 5-day biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), and nitrogen in form of ammonia (NH₄). Partial correlation analysis (r _p) results showed that there is a strong relationship between salinity and turbidity (r _p?=?0.930, p?=?0.001) and BOD₅ and COD (r _p?=?0.839, p?=?0.001) controlling for the linear effects of conductivity and NH₄, respectively. Principal component analysis and or factor analysis was used to investigate the origin of each water quality parameter in the Jakara Basin and identified three major factors explaining 68.11 % of the total variance in water quality. The major variations are related to anthropogenic activities (irrigation agricultural, construction activities, clearing of land, and domestic waste disposal) and natural processes (erosion of river bank and runoff). Discriminant analysis (DA) was applied on the dataset to maximize the similarities between group relative to within-group variance of the parameters. DA provided better results with great discriminatory ability using eight variables (DO, BOD₅, COD, SS, NH₄, conductivity, salinity, and DS) as the most statistically significantly responsible for surface water quality variation in the area. The present study, however, makes several noteworthy contributions to the existing knowledge on the spatial variations of surface water quality and is believed to serve as a baseline data for further studies. Future research should therefore concentrate on the investigation of temporal variations of water quality in the basin.     

Modeling of methane oxidation in landfill cover soil using an artificial neural network

Knowing the fraction of methane (CH₄) oxidized in landfill cover soils is an important step in estimating the total CH₄ emissions from any landfill. Predicting CH₄ oxidation in landfill cover soils is a difficult task because it is controlled by a number of biological and environmental factors. This study proposes an artificial neural network (ANN) approach using feedforward backpropagation to predict CH₄ oxidation in landfill cover soil in relation to air temperature, soil moisture content, oxygen (O₂) concentration at a depth of 10 cm in cover soil, and CH₄ concentration at the bottom of cover soil. The optimum ANN model giving the lowest mean square error (MSE) was configured from three layers, with 12 and 9 neurons at the first and the second hidden layers, respectively, log-sigmoid (logsig) transfer function at the hidden and output layers, and the Levenberg-Marquardt training algorithm. This study revealed that the ANN oxidation model can predict CH₄ oxidation with a MSE of 0.0082, a coefficient of determination (R ²) between the measured and predicted outputs of up to 0.937, and a model efficiency (E) of 0.8978. To conclude, further developments of the proposed ANN model are required to generalize and apply the model to other landfills with different cover soil properties.

Implications:

To date, no attempts have been made to predict the percent of CH₄ oxidation within landfill cover soils using an ANN. This paper presents modeling of CH₄ oxidation in landfill cover soil using ANN based on field measurements data under tropical climate conditions in Malaysia. The proposed ANN oxidation model can be used to predict the percentage of CH₄ oxidation from other landfills with similar climate conditions, cover soil texture, and other properties. The predicted value of CH₄ oxidation can be used in conjunction with the Intergovernmental Panel on Climate Change (IPCC) First Order Decay (FOD) model by landfill operators to accurately estimate total CH₄ emission and how much it contributes to global warming.     

Probabilistic public health risks associated with pesticides and heavy metal exposure through consumption of common dried fish in coastal regions of Bangladesh

Environmental Science and Pollution Research - The chemical contaminants in dried fish are of great food safety concern and an emerging public health issue in Bangladesh. The aim of this study was...     

Anticancer properties of medicinal plants and their bioactive compounds against breast cancer: a review on recent investigations

Environmental Science and Pollution Research - Breast cancer (BC) is one of the most common and recurring diseases and the second leading cause of death in women. Despite prevention, diagnostics,...     

Hydrochemical characteristics and identification of groundwater pollution sources in tropical savanna

Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic processes. In this study, classic chemical and multivariate statistical methods were utilized to assess the groundwater quality and ascertain the potential contamination sources affecting the groundwater quality of Galma sub-watershed in a tropical savanna. For this purpose, the data set of 18 groundwater quality variables covering 57 different sampling boreholes (BH) was used. The groundwater samples essentially contained the cations in the following order of dominance: Ca²⁺ ?>?Na⁺ ?>?Mg²⁺ ?>?K⁺. However, the anions had HCO₃^–?>?Cl^–?>?SO₄^–2?>?NO₃^– respectively. The hydrochemical facies classified the groundwater types of the sub-watershed into mixed Ca–Mg–Cl type of water, which means no cations and anions exceeds 50%. The second dominant water type was Ca–Cl. The Mg–HCO₃ water type was found in BH 9, and Na–Cl water type in BH 29 of the studied area. The weathering of the basement rocks was responsible for the concentrations of these ions in the groundwater chemistry of the sub-watershed. Hierarchical cluster analysis (HCA) grouped the groundwater samples (boreholes) into five clusters that are statistically significant regarding the similarities of groundwater quality characteristics. The principal component analysis (PCA) extracted two major principal components explained around 65% of the variance and suggested the natural and anthropogenic processes especially the agricultural pollutants including synthetic fertilizers, and leaching of agricultural waste as the main factors affecting the groundwater quality. The integrated method proved to be efficient and robust for groundwater quality evaluation, as it guaranteed the precise assessment of groundwater chemistry in the sub-watershed of the tropical savanna. The findings of this investigation could be useful to the policy makers for developing effective groundwater management plans for the groundwater resources and protection of the sub-watershed.

     

A multiobjective model for the green capacitated location-routing problem considering drivers’ satisfaction and time window with uncertain demand

Environmental Science and Pollution Research - Location-routing problem is a combination of facility location problem and vehicle routing problem. Numerous logistics problems have been extended to...     

Recovery potential of aerobic sludge biomass from Co (II) stress in sequencing batch reactors

Heavy metals in higher concentrations are often encountered in domestic sewage of developing and under-developed countries. High metallic concentrations can stress reactor sludge biomass morphology impeding its performance in organics reduction. However, the extent of damage and ability of sludge biomass to recover from the metallic stress is not fully understood. Also, there is no protocol to identify and prevent the sludge biomass from metallic stress in fully functional sewage treatment plants (STPs). This study investigates performance, metabolic activity, morphology, and settling characteristics of the sludge biomass under different Co(II) stress conditions. The extent of recovery in biomass, when the supply of Co(II) metal ion was discontinued in the inlet stream, was explored. The study also proposed a protocol based on simple settling characteristics of sludge biomass to get an early indication of metal infiltration to prevent potential damage to the biomass morphology. Four sequencing batch reactors (SBRs) with Co(II) ion concentrations of 0 (designated as RCo0), 5 (RCo5), 25 (RCo25), and 75 mg/L (RCo75) in the feed were operated with a cycle time of 12 h. Reactors were operated for 35 days with Co(II) in the feed (termed as stressed phase operation) followed by 24 days of operation without Co(II) in the feed (termed as recovery phase operation). Results show that COD removal in reactor RCo75 reduced to 48% on the 10th day of stressed phase operation, showing a lag in COD removal due to metallic stress. The activity of biomass in reactors RCo5, RCo25, and RCo75 was reduced by 39%, 45%, and 49%, respectively, in the stressed phase compared to the biomass in control reactor. Recovery in COD removal efficiency and specific biomass activity were observed in all the reactors after the removal of metallic stress. The settleability of sludge biomass in reactors RCo25 and RCo75 was significantly affected. Transformation in the shape of flocs in reactor RCo25 and RCo75 biomasses revealed the prolonged effect of metallic stress, which was observed to be irreversible even during the recovery phase operation.

     

Propolis efficacy on SARS-COV viruses: a review on antimicrobial activities and molecular simulations

Environmental Science and Pollution Research - This current study review provides a brief review of a natural bee product known as propolis and its relevance toward combating SARS-CoV viruses....     

Hydrogeochemistry and water quality assessment of the Kor–Sivand Basin, Fars province, Iran

In order to assess the quality and suitability of waters in the Kor-Sivand river basin, 60 water samples from the Kor river and 90 water samples from wells in the basin were studied. Assessments were based on Piper's and Gibbs' diagrams for water quality, Food and Agricultural Organization's (FAO) guidelines, and US Salinity Laboratory diagram for water suitability. The results showed that the river water is of Ca-HCO(3) type, while well water is of Ca-Cl and Na-Cl type. Based on Gibbs' diagram, the source of soluble ions in the river water samples is the weathering of stones over which water flows, while evaporation was found to be the dominant process in the ion concentration of the well samples. According to the FAO Guidelines, the salinity of surface water for irrigation did not cause great restrictions; however, many of these waters could create potential permeability problems. In the groundwater samples, a high salt concentration is more important than the infiltration problem. Mg hazard values at some sites limit its use for agricultural purposes. One third of the river water samples and two thirds of well waters had more than 50% magnesium. Saturation indices showed that 94% of the analyzed water samples are supersaturated with calcite, aragonite, and dolomite. Based on the US Salinity Laboratory diagram, river water samples were classified as C(2)S(1) and C(3)S(1), while C(4)S(3), C(4)S(4), C(2)S(1), and C(3)S(1) were the most dominant classes in well samples. Some management practices necessary for sustainable development of water resources in the study area were discussed briefly, including appropriate selection of crops, adequate drainage, leaching, blending and cyclic use of saline water, proper irrigation method, and addition of soil amendment.     

Assessment of elemental concentrations in the urban air (case study: Tehran city)

Tehran is one of the megacities of the world with a population of over eight million. Its air is highly polluted mainly due to the suspended particulate matters, which encompasses a wide spectrum of chemical elements. These elements based on their type, size, and impact on the life cycle have various environmental and heath risks. In this research, the neutron activation method is used to determine the concentration levels of Al, Ba, Fe, Mg, and V in the urban air. Thus, two districts of Tehran with different characteristics are selected. District 21 includes much of the industries located in Tehran metropolitan and is considered as an industrial area. In contrast, district 22 lacks any significant industrial activity. It is a newly established and expanding district adjacent to district 21 with a great deal of constructional activities. For the measurement of the suspended particulate matters in the air, the various sections of the aforesaid districts with industrial, residential, heavily congested traffic, residential/commercial, residential/heavily congested traffic, and residential/industrial classifications were identified. Subsequently, 24 sampling stations were selected. The sampling of the suspended particulate matters was conducted with the aid of a high volume pump containing 125 mm cellulose filters in two different time intervals. After completion of the sampling process, the samples were prepared and sent to the research reactor of the Iran Nuclear Energy Organization for Neutron Activation. During the next steps, the radiations emitted from the samples were registered, the radiation curves were plotted, and the amounts of the trace elements were determined. As a result, the average concentration levels of Al, Ba, Fe, Mg, and V were identified to be 3.301140, 2.273658 × 10, 4.0681696 × 10^???1, 3.5525475 × 10^???1, and 3.04075 × 10^???2 μg/m³, respectively. Moreover, the emission sources of the aforesaid elements into the air were identified. The concentration levels of these elements in the industrial and heavily congested traffic sections were higher. Finally, it was concluded that the statistical analysis of these elements presents a meaningful correlation among them.