Temporal variability of groundwater chemistry in shallow and deep aquifers of Araihazar, Bangladesh

Samples were collected every 2-4 weeks from a set of 37 monitoring wells over a period of 2-3 years in Araihazar, Bangladesh, to evaluate the temporal variability of groundwater composition for As and other constituents. The monitoring wells are grouped in 6 nests and span the 5-91 m depth range. Concentrations of As, Ca, Fe, K, Mg, Mn, Na, P, and S were measured by high-resolution ICPMS with a precision of 5% or better; concentrations of Cl were measured by ion chromatography. In shallow wells <30 m deep, As and P concentrations generally varied by <30%, whereas concentrations of the major ions (Na, K, Mg, Ca and Cl) and the redox-sensitive elements (Fe, Mn, and S) varied over time by up to +/-90%. In wells tapping the deeper aquifers >30 m often below clay layers concentrations of groundwater As were much lower and varied by <10%. The concentrations of major cations also varied by <10% in these deep aquifers. In contrast, the concentration of redox-sensitive constituents Fe, S, and Mn in deep aquifers varied by up to 97% over time. Thus, strong decoupling between variations in As and Fe concentrations is evident in groundwaters from shallow and deep aquifers. Comparison of the time series data with groundwater ages determined by (3)H/(3)He and (14)C dating shows that large seasonal or inter-annual variations in major cation and chloride concentrations are restricted to shallow aquifers and groundwater recharged <5 years ago. There is no corresponding change in As concentrations despite having significant variations of redox sensitive constituents in these very young waters. This is attributed to chemical buffering due to rapid equilibrium between solute and solid As. At two sites where the As content of groundwater in existing shallow wells averages 102 microg/L (range: <5 to 648 microg/L; n=118) and 272 microg/L (range: 10 to 485 microg/L; n=65), respectively, a systematic long-term decline in As concentrations lends support to the notion that flushing may slowly deplete an aquifer of As. Shallow aquifer water with >5 years (3)H/(3)He age show a constant As:P molar ratio of 9.6 over time, suggesting common mechanisms of mobilization.     

Revealing empirical association among ecological footprints,renewable energy consumption,real income,and financial development: a global perspective

Environmental Science and Pollution Research - This study quantifies the effect of real income, financial development, trade openness, and renewable energy consumption on the ecological footprint...     

Nested numerical scheme in a polar coordinate shallow water model for the coast of Bangladesh

This study is concerned with the development of storm surge model to predict water level accurately due to surge associated with a cyclone along the coast of Bangladesh. Considering the funnel shape of the Bay of Bengal, coastal bending and the existence of off-shore islands, a vertically integrated model in cylindrical polar coordinate system is developed using nested numerical scheme. A fine mesh scheme capable of incorporating coastal bending and offshore islands properly in the numerical scheme is nested into a coarse mesh scheme covering up to 15° N latitude of the Bay of Bengal. The developed model is used to estimate water levels at different coastal and island stations associated with a few storms that hit the coast of Bangladesh. The computed surge levels compared well with observed ones and predicted surge levels investigated with different approaches.     

Revitalization of tourism and hospitality sector: preempting pandemics through lessons learned

Environmental Science and Pollution Research - The devastating effects of the COVID-19 pandemic have left many repercussions for the tourism industry to preempt any future catastrophe of this...     

Estimation of bacteriological levels in surface water samples to evaluate their contamination profile

The present work deals with the assessment of bacteriological contamination along with some physico-chemical parameters of water samples from Lahore canal. ANOVA showed that the observed p values of log-transformed viable plate counts, total suspended solids, turbidity, and biological oxygen demand are 0.000, 0.000, 0.000, and 0.000, respectively, which are <0.05, while the p value of total coliforms, total fecal coliforms, and Escherichia coli are 0.728, 0.827, and 0.081, respectively which are >0.05. Significant correlation was observed between log-transformed viable plate counts (CFU), biological oxygen demand, total suspended solids, and turbidity. Further regression analysis revealed that simple line regression model is fit for log-transformed viable plate counts and total suspended solids, log-transformed viable plate counts and turbidity, turbidity and total suspended solids, biological oxygen demand and total suspended solids, biological oxygen demand and log-transformed viable plate counts, and biological oxygen demand and turbidity.     

Distribution and solid-phase speciation of toxic heavy metals of bed sediments of Bharali tributary of Brahmaputra River

Heavy metal (Fe, Mn, Zn, Cu, Ni, Pb, and Cd) concentrations and their chemical speciations were investigated for the first time in bed sediments of Bharali River, a major tributary of the Brahmaputra River of the Eastern Himalayas. Levels of Fe, Mn, Pb, and Cd in the bed sediments were much below the average Indian rivers; however, Cu and Zn exhibit levels on the higher side. Enrichment factors (EF) of all metals was greater than 1 and a higher trend of EF was seen in the abandoned channel for most metals. Pb showed maximum EF of 32 at site near an urban center. The geoaccumulation indices indicate that Bharali river is moderately polluted. The metals speciations, done by a sequential extraction regime, show that Cd, Cu, and Pb exhibit considerable presence in the exchangeable and carbonate fraction, thereby showing higher mobility and bioavailability. On the other hand, Ni, Mn, and Fe exhibit greater presence in the residual fraction and Zn was dominant in the Fe?CMn oxide phase. Inter-species correlations at three sites did not show similar trends for metal pairs indicating potential variations in the contributing sources.     

Financial development,international trade,and environmental degradation: a nonlinear threshold model based on panel smooth transition regression

Environmental Science and Pollution Research - Environmental degradation has severely affected the natural cycle of ecosystem. It’s high time now and humans should execute strategies...     

Municipal solid waste generation in China: influencing factor analysis and multi-model forecasting

Journal of Material Cycles and Waste Management - In the developing countries, the inadequacy of basic waste data is a significant obstacle for municipal solid waste management. To evaluate an...     

Development of Artificial Neural Network Based Metamodels for Inactivation of Anthrax Spores in Ventilated Spaces Using Computational Fluid Dynamics

ABSTRACT

Linear, quadratic, and artificial neural network (ANN)-based metamodels were developed for predicting the extent of anthrax spore inactivation by chlorine dioxide in a ventilated three-dimensional space over time from computational fluid dynamics model (CFD) simulation data. Dimensionless groups were developed to define the design space of the problem scenario. The Hammersley sequence sampling (HSS) method was used to determine the sampling points for the numerical experiments within the design space. A CFD model, comprised of multiple submodels, was applied to conduct the numerical experiments. Large eddy simulation (LES) with the Smagorinsky subgrid-scale model was applied to compute the airflow. Anthrax spores were modeled as a dispersed solid phase using the Lagrangian treatment. The disinfectant transport was calculated by solving a mass transport equation. Kinetic decay constants were included for spontaneous decay of the disinfectant and for the reaction of the disinfectant with the surfaces of the three-dimensional space. To enhance the mixing of the disinfectant with the room air, a momentum source was included in the simulation. An inactivation rate equation accounted for the reaction between the spores and the disinfectant. The ANN-based metamodels were most successful in predicting the number of viable bioaerosols remaining in an arbitrary enclosed space. Sensitivity analysis showed that the mass fraction of the disinfectant, inactivation rate constant, and contact time had the most influence on the inactivation of the spores.

IMPLICATIONS This investigation presents a framework for the development of user-friendly models; metamodels for the prediction of the number of viable spores remaining in an indoor room during disinfection from accurate but time-consuming CFD studies. During any decontamination event, to know when to stop pumping in the disinfectant and to know what level of log reduction of the spores have been achieved before even starting decontamination would provide valuable guidance. The neural network based metamodels can be applied to obtain quick and relatively accurate answers. This would be necessary when immediate information is required during emergencies.