Environmental Science and Pollution Research - Environmental arsenic exposure in adults and children has been associated with a reduction in the expression of club cell secretory protein (CC16) and... 相似文献
Environmental Science and Pollution Research - Glyphosate is the most used herbicide worldwide. Many studies have reported glyphosate risks to aquatic organisms of different trophic levels.... 相似文献
Environmental Science and Pollution Research - A theoretical physicochemical and thermodynamic investigation of the adsorption of heavy metals Zn2+, Cd2+, Ni2+, and Cu2+on carbon-based adsorbents... 相似文献
Surface sediments were collected from 122 sites in the upstream of the Yellow River, China. The concentration of Fe, Mn, Cu, Ni, Zn, Cr, Pb, and Cd in sediments was investigated to explore the spatial distribution based on statistics and interpolation method. The results suggested that the concentrations of heavy metals were lower than potential effect levels (PEL). The samples above threshold effect level (TEL) for Pb and Zn were less than 10%, while almost 50% of samples for Ni exceeded PEL. Pb and Zn in sediments performed little or no adverse effects on the aquatic ecosystems. Higher concentrations of all heavy metals occurred in Qinghai and Gansu sections; the concentrations of Cu, Ni, and Zn were significantly higher than the Inner Mongolia section. Lower concentration of Fe, Mn, Cu, Ni, and Zn appeared in Qinghai section; the concentrations of Fe, Mn, Cr, and Pb manifested relatively steady and similar distributions and approximately decreasing tendency along the upstream of Yellow River.
Environmental Science and Pollution Research - Aerobic denitrifiers have the potential to reduce nitrate in polluted water under aerobic conditions. A salt-tolerant aerobic denitrifier was newly... 相似文献
Environmental Science and Pollution Research - Polycyclic aromatic hydrocarbons (PAHs), as a class of important environmental pollutants, have received considerable concern due to their widespread... 相似文献
Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box–Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand–metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model–genetic algorithm (RSM–GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47 μg/g) is facilitated at 30.22 mg C/L of EtOH with initial As(III) concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM. 相似文献