Investigation of arsenic removal in batch wise water treatments by means of sequential hydride generation flow injection analysis

Arsenic water pollution is a big issue worldwide. Determination of inorganic arsenic in each oxidation state is important because As(III) is much more toxic than As(V). An automated arsenic measurement system was developed based on complete vaporization of As by a sequential procedure and collection/preconcentration of the vaporized AsH(3), which was subsequently measured by a flow analysis. The automated sensitive method was applied to monitoring As(III) and As(V) concentrations in contaminated water standing overnight. Behaviors of arsenics were investigated in different conditions, and unique time dependence profiles were obtained. For example, in the standing of anaerobic water samples, the As(III) concentration immediately began decreasing whereas dead time was observed in the removal of As(V). In normal groundwater conditions, most arsenic was removed from the water simply by standing overnight. To obtain more effective removal, the addition of oxidants and use of steel wools were investigated. Simple batch wise treatments of arsenic contaminated water were demonstrated, and detail of the transitional changes in As(III) and As(V) were investigated.     

Hydroxychloroquine in COVID-19: therapeutic promises,current status,and environmental implications

Environmental Science and Pollution Research - The outbreak of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected the entire world with its infectious spread and...     

Chemometric application in identifying sources of organic contaminants in Langat river basin

Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.     

Development of statistical models for predicting muscle and mental activities during repetitive precision tasks

This study was conducted to develop muscle and mental activities on repetitive precision tasks. A laboratory experiment was used to address the objectives. Surface electromyography was used to measure muscle activities from eight upper limb muscles, while electroencephalography recorded mental activities from six channels. Fourteen university students participated in the study. The results show that muscle and mental activities increase for all tasks, indicating the occurrence of muscle and mental fatigue. A linear relationship between muscle activity, mental activity and time was found while subjects were performing the task. Thus, models were developed using those variables. The models were found valid after validation using other students’ and workers’ data. Findings from this study can contribute as a reference for future studies investigating muscle and mental activity and can be applied in industry as guidelines to manage muscle and mental fatigue, especially to manage job schedules and rotation.     

Geo-accumulation index and contamination factors of heavy metals (Zn and Pb) in urban river sediment

The aim of the present study was to appraise the levels of heavy metal contamination (Zn and Pb) in sediment of the Langat River (Selangor, Malaysia). Samples were collected randomly from 15 sampling stations located along the Langat River. The parameters measured were pH, redox potential, salinity, electrical conductivity, loss of ignition, cation exchanges capacity (Na, Mg, Ca, K), and metal ions (Zn and Pb). The geo-accumulation index (I _geo) and contamination factor (C _f) were applied to determine and classify the magnitude of heavy metal pollution in this urban river sediment. Results revealed that the I _geo of Pb indicated unpolluted to moderately polluted sediment at most of the sampling stations, whereas Zn was considered to be within background concentration. The I _geo results were refined by the C _f values, which showed Pb with very high C _f at 12 stations. Zinc, on the other hand, had low to moderate C _f values. These findings indicated that the sediment of the Langat River is severely polluted with Pb. The Zn concentration at most sampling points was well below most sediment quality guidelines. However, 40% of the sampling points were found to have a Pb concentration higher than the consensus-based probable effect concentration of 128 mg/kg (concentrations above this value are likely to cause harmful effects). This result not only highlights the severity of Pb pollution in the sediment of the Langat River, but also the potential risk it poses to the environment.     

Agroforestry environment,potentiality and risk in India: a remote sensing and GIS understanding

Environment, Development and Sustainability - The study utilized the tree covers per cent, agroforestry suitability, present and future (2050) climate, agriculture vulnerability (2050), percentage...     

Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.     

Environmental perception during rapid population growth and urbanization: a case study of Dhaka city

Dhaka city in Bangladesh has been passing through a hasty process of urbanization and population growth since the last few decades. Rapid growth of population, unplanned urbanization and industrialization in the periphery has generated pressure to the changes in land use pattern, which has also caused huge urban expansion. This expansion process is engulfing cultivated land, vegetation, wetlands and water bodies without considering their environmental impacts. This study argues that these changes and their scale of environmental impacts or sufferings are not equally distributed among the dwellers in Dhaka city. It seeks to explore variations of environmental qualities on the basis of people’s perceptions. The study finds that the dwellers in the city perceive their neighborhood environment differently, which may affect environmental qualities of the area and their sustainable management as well. Therefore, it is imperative to consider spatial variations and inequalities of environmental opportunities or sufferings in urban planning of Dhaka city.     

Approaches for prevention and environmental management of novel COVID-19

Environmental Science and Pollution Research - The World Health Organization (WHO) recognized a novel coronavirus as the causative agent of a new form of pneumonia. It was subsequently named...     

Watering techniques and zero-valent iron biochar pH effects on As and Cd concentrations in rice rhizosphere soils, tissues and yield

Zero-valent iron amended biochar (ZVIB) has been proposed as a promising material in immobilizing heavy metals in paddy fields. In this study, the impacts of pH of ZVIB (pH 6.3 and pH 9.7) and watering management techniques (watering amount in the order of CON (control, 5/72)>3/72>1–3/72>3/100>1/72, with 5/72, for example, representing irrigation given to 5 cm above soil surface in 72 hr regular interval) on As and Cd bioavailability for rice and its grain yield (Yield_BR) were investigated in a pot experiment. Brown rice As (As_BR) content was irrelative to the watering treatments, while significantly decreased (>50%) with the addition of both ZVIB materials. The diminutions of brown rice Cd (Cd_BR) content as well as the Yield_BR were highly dependent on both the soil amendment materials’ pH and watering amount. Among all the watering treatments, 3/72 treatment (15% less irrigation water than the CON) with ZVIB 6.3 amendment was the optimum fit for simultaneous reduction of As_BR (50%) and Cd_BR contents (19%) as well as for significant increment (12%) of the Yield_BR. Although high pH (9.7) ZVIB application could also efficiently decrease As and Cd contents in brown rice, it might risk grain yield lost if appropriate (e.g. 3/72 in our study) watering management technique was not chosen. Therefore, ZVIB would be an environmentally friendly option as an amendment material with proper selection of watering management technique to utilize As and Cd co-contaminated arable soils safely for paddy cultivation.