Removal of doxycycline hydrochloride from aqueous solution by rice husk ash using response surface methodology and disposability study

Environmental Science and Pollution Research - The huge demand and consumption of DOX, its incomplete metabolism, and complex behavior in atmosphere are causing a great ecological issue, which...     

Construction of multifunctional NH2-UiO-66 metal organic framework: sensing and photocatalytic degradation of ketorolac tromethamine and tetracycline in aqueous medium

Environmental Science and Pollution Research - Existence of pharmaceutical residues in water has endangered environmental pollution worldwide, which makes it ineludible to develop prospective...     

Heat storage material: a hope in solar thermal

Environmental Science and Pollution Research - Solar energy is a vast renewable energy source, but uncertainty in the demand and supply of energy due to various geographical regions raises a...     

Five-wheel framework for system-based monitoring of heavy metal pollution in rivers

Sectorial approach for monitoring heavy metal pollution in rivers has failed to report realistic pollution status and associated ecological and human health risks. The increasing spread of heavy metals from different sources and emerging risks to human and environmental health call for reexamining heavy metal pollution monitoring frameworks. Also, the sources, spread, and load of heavy metals in the environment have changed significantly over time, requiring consequent modification in the monitoring frameworks. Therefore, studies on heavy metal monitoring in rivers conducted in the last decade were evaluated for experimental designs, research frameworks, and data presentations. Most studies (∼99%) (i) lacked inclusiveness of all environmental compartments; (ii) focused on “one pollutant – one/two compartment” or sometimes “one pollutant – one compartment – one effect” approach; and (iii) remained “data-rich but information poor.” An ecological approach with integrative system thinking is proposed to develop a holistic approach for monitoring river pollution. It is visualized that heavy metal monitoring, risk analyses, and water management must incorporate tracking pollutants in different environmental compartments of a river (water, sediment, and floodplain/bank soil) and consider correlating it with riverbank land use. The systems-based pollution monitoring and assessment studies will reveal the critical factors that drive heavy metals pollutant movement in ecosystems and associated potential risks to the environment, wildlife, and humans. Also, water quality and pollution indexing tools would help better communicate complex pollution data and associated risks among all stakeholders. Therefore, integrating systems approaches in scientific- and policy-based tools would help sustainably manage the health of rivers, wildlife, and humans.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

Identification and characterization of extracted microplastics from agricultural soil near industrial area: FTIR and X-ray diffraction method

Microplastics have been found in large quantities in agricultural soil and now become a major global issue. Different types of microplastic have adverse effects on agricultural soil. The most widely used method for the extraction of microplastics in agricultural soil is the density floatation method by using saturated NaCl solution. This method includes the pre-digestion of soil samples with H₂O₂ to remove all the organic matter present in the soil. Different types of microplastic particles were extracted and identified by using ATR-FTIR viz polypropylene, polybutylene tetrapthalate, polyethylene, polystyrene, and polyethylene tetrapthalate. The crystalline nature of extracted microplastic was checked by employing XRD analytical technique. Floatation with higher density saturated sodium chloride (NaCl) solution recovered approximately 80% MPs from soil. Floatation methods were found to be effective for extracting microplastics from soils.     

Nickel and copper accumulation strategies in Odontarrhena obovata growing on copper smelter-influenced and non-influenced serpentine soils: a comparative field study

The present investigation is the first in situ comparative study for the identification of Ni and Cu accumulation strategies involved in Odontarrhena obovata (syn. Alyssum obovatum (C.A. Mey.) Turcz.) growing in Cu-rich smelter-influenced (CSI) and non-Cu-influenced (NCI) sites. The total and Na₂EDTA (disodium ethylenediaminetetraacetic acid)-extractable metal concentration in soils and plant tissues (roots, stem, leaves and flowers) were determined for CSI and NCI sites. High concentrations of total Ni, Cr, Co and Mg in the soil suggest serpentine nature of both the sites. In spite of high total and extractable Cu concentrations in CSI soil, majority of its accumulation was restricted to O. obovata roots showing its excluder response. Since the translocation and bioconcentration factors of Ni?>?1 and the foliar Ni concentration?>?1000 μg g^?1, it can be assumed that O. obovata has Ni hyperaccumulation potential for both the sites. No significant differences in chlorophyll content in O. obovata leaves were observed between studied sites, suggesting higher tolerance of this species under prolonged heavy metal stress. Furthermore, this species from CSI site demonstrated rather high viability under extreme technogenic conditions due to active formation of antioxidants such as ascorbate, free proline and protein thiols. The presence of Cu in higher concentration in serpentine soil does not exert detrimental effect on O. obovata and its Ni hyperaccumulation ability. Thus, O. obovata could act as a putative plant species for the remediation of Cu-rich/influenced serpentine soils without compromising its Ni content and vitality.

     

Metal characterization of airborne particulate matters in a coastal region

The concentrations of suspended particulate matter in the air of the Orissa Sand Complex had an average value of 128 ± 10 µg m^?3 in residential areas and 170 ± 8 µg m^?3 in mining areas. PM₁₀ levels in residential areas were found to have an average of 35 ± 10 µg m^?3, in mining areas 45 ± 10 µg m^?3. The distribution of some elements is also discussed here. Inhalation doses were observed to be higher in summer than in winter and the rainy season. The highest dose rate was for the age group of 1 year, and health risks were found to be highest for the same. For adults, inhalation dose and health risk are 1.3 times higher in mining than in residential areas.     

Advent of sheet flow in suction affected alluvial channels

The presence of suction (flow of water from channel to ground water) affects the channel hydrodynamics and increases the bed shear stress. At high bed shear stress in alluvial channels made of the non-cohesive material, sediment transport occurs as sheet flow layer of high sediment concentration. The sediment transport in the form of sheet flow has been observed in the present study when suction was applied to the non-transporting channels designed on incipient motion condition. The erosion of the channel banks contributed to the sheet flow because of the increased channel bed shear stress. An empirical relation for the thickness of sheet flow layer has been developed which includes suction as independent parameter along with others.     

Redox processes in water remediation

Groundwater is the main source of drinking water and water for agricultural and industrial usage. Therefore, groundwater contamination is prevented and contaminated groundwater is remediated to protect public health and the environment. Methods to remediate groundwater contamination have been recently developed. The use of redox processes in water remediation technologies has not been properly reviewed. Numerous water remediation technologies, such as ultrasonication, bioremediation, electrokinetics and nanotechnology, are closely related to redox processes. Redox processes control the chemical speciation, bioavailability, toxicity, mobility and adsorption of water pollutants in environment. Here, we review (1) general introduction of redox processes, (2) applicability of redox processes in water remediation, and (3) catalytic enhancement of redox potentials to explore its wide applicability in environmental remediation.