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...     

Potential of microalgae Bio-Coke as a sustainable solid fuel alternative to coal coke

Energy and environmental issues have triggered the search for new sources of green energy alternatives in recent years. Biofuel production from renewable sources is widely considered one of the most sustainable alternatives for environmental and economic sustainability. Microalgae are currently being promoted as one of the most promising liquid biofuel feedstocks due to their rapid growth, high lipid production capacity, and carbon–neutral cycle. In this study, whole microalgae cells were utilized as raw material to produce solid biofuel, i.e., Bio-Coke, and this study aimed to investigate the possibility of microalgae Bio-Coke as an alternative to coal coke. The results show that Bio-Coke can be produced from microalgae in the temperature range of 80–100 °C. The apparent density is between 1.253 and 1.261 g/cm³, comparable to the apparent density of lignocellulosic Bio-Coke. Additionally, the calorific value is higher than the calorific value of lignocellulosic Bio-Coke and within the range of the calorific value of subbituminous coal. Therefore, microalgae Bio-Coke can be utilized to replace coal coke usage in the future.

     

Flotation kinetics of aluminum powders derived from waste crystalline silicon solar cells and its comparison between batch,continuous and column flotation practices

Journal of Material Cycles and Waste Management - In this study, floatability rate of aluminum (Al) powders was analyzed for the purpose of separating valuable resources from residual materials in...     

Direct and Indirect Effects of Socioeconomic Factors on Age at First Marriage in Slum Areas,Bangladesh

This article attempts to examine the influence of some selected predictor variables on female age at first marriage in slum areas of Bangladesh. A path and multiple classification analysis （MCA） approach have been adopted. Authors thought that respondent＇s educational level and the mass media such as watching television have a significant direct impact on age at marriage, while the types of family and occupational status have an indirect effect on age at marriage.     

Arsenic and heavy metal concentrations in surface soils and vegetables of Feni district in Bangladesh

An investigation of various heavy metals including the arsenic (As) poisoning in soils and vegetables in five upazillas under Feni district of Bangladesh was performed by neutron activation technique using the neutron irradiation facilities of TRIGA MARK II research reactor at Bangladesh Atomic Energy Research Establishment (BAERE), Savar, Dhaka. A total of 30 samples (15 surface soils and 15 foodstuffs) were studied in five Upazillas namely as, Sonagazi, Dagan Bhuiya, Feni Sadar, Fulgazi and Parsuram of Feni district taking three samples of each kind from each upazilla. Samples of each kind together with the standard reference material (SRM) were irradiated in the same neutron flux and the gamma-rays of nuclides from the irradiated samples were assessed and screened for As, Br, U, Th, Cr, Sc, Fe, Zn and Co in soils and As, Br, Na, K, Cr, Sc, Fe, Zn and Co in vegetables (i.e; eddoe, taro, green papaya, plantain, potato, callaloo, bottle ground and carambola). The measurement of gamma-rays was carried out by means of a calibrated high resolution HPGe detector. The concentration of product nuclides containing in the irradiated samples was determined from the peak count-rates of prominent gamma-lines for the corresponding nuclides. Among all contaminants, only As, Zn and Cr for both samples were focused because of their higher values compared with the local as well as the world typical values. The present results revealed that the mean levels of As in Parsuram, Feni Sadar and Pulgazi upazillas are higher than the world typical value of 2 mg/kg. The mean values of Zn and Cr for all upazillas are higher than the world typical values 32 and 27.9 mg/kg, respectively. For the case of vegetables, the mean concentration of As is found only in Eddoe (5.33 ppm) and Taro (1.46 ppm) collected from Sonagazi and Feni Sadar upazilla; which are higher than the values in Samta (0.1 ppm for eddoe and 0.44 ppm for taro) under Jessore district of Bangladesh. The mean concentrations of Zn and Cr in all kinds of vegetables are higher compared with the existing local values as well as the world typical values. The mean estimated daily dietary intake of As, Zn and Cr from vegetables are found to be 0.105, 12.47 and 3.53 mg respectively, which are higher than the recommended values of some countries. The consumption of toxic metals in vegetables is a risk for public health in the studied area.     

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.     

Deterioration of water quality of Surma river

Surma River is polluted day by day by human activities, poor structured sewerage and drainage system, discharging industrial and household wastes. The charas (natural channels) are responsible for surface runoff conveyance from its urban catchments to the receiving Surma River. Water samples have been collected from a part of Surma River along different points and analyzed for various water quality parameters during dry and monsoon periods. Effects of industrial wastes, municipal sewage, and agricultural runoff on river water quality have been investigated. The study was conducted within the Chattak to Sunamganj portion of Surma River, which is significant due to the presence of two major industries – a paper mill and a cement factory. The other significant feature is the conveyors that travel from India to Chattak. The river was found to be highly turbid in the monsoon season. But BOD and fecal coliform concentration was found higher in the dry season. The water was found slightly acidic. The mean values of parameters were Conductivity 84–805 μs; DO: dry-5.52 mg/l, monsoon-5.72 mg/l; BOD: dry-1mg/l, monsoon-0.878 mg/l; Total Solid: dry-149.4 mg/l, monsoon-145.7 mg/l. In this study, an effort has been taken to investigate the status of concentration of phosphate (PO⁻⁴) and ammonia–nitrogen (NH₄–N) at four entrance points of Malnichara to the city, Guali chara, Gaviar khal and Bolramer khal. Data has been collected from March–April and September–October of 2004. Concentrations have been measured using UV Spectrophotometer. Although the phosphate concentration has been found within the limit set by DOE for fishing, irrigation and recreational purposes, however ammonia–nitrogen has been found to exceed the limit.     

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...     

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.     

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.