The arsenic adsorption capacity of a manganese oxide-modified biochar composite (MBC), prepared by pyrolysis of a mixture of potassium permanganate and biochar, was investigated in red soil. Adsorption experiments using batch procedures were used to estimate the arsenic adsorption capacities of the absorbent materials. Adsorption and desorption isotherms, Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS) were used to characterise the prepared adsorbent materials, and a plausible mechanism for arsenic removal by MBC was proposed. Arsenic in red soil-MBC mixtures exhibited lower mobility than that in soils amended with pristine biochar. The improved removal performance of soil-MBC mixtures was attributed to a lower H/C ratio, higher O/C ratio, higher surface hydrophilicity, and higher surface sorption capacity, even though the impregnation of manganese oxide decreased the specific surface area of the biochar. Arsenic retention increased as the biochar content increased, mainly owing to an increase in soil pH. Several oxygenated functional groups, especially O-H, CO, Mn-O, and Si-O, participated in the adsorption process, and manganese oxides played a significant role in the oxidation of arsenic. This study highlights the potential of MBC as an absorbent to immobilise arsenic for use in contaminated land remediation in the red soils region.
There is a continuing need to develop effective materials for the environmental remediation of copper-contaminated sites. Nano-MnO2–biochar composites (NMBCs) were successfully synthesized through the reduction of potassium permanganate by ethanol in a biochar suspension. The physicochemical properties and morphology of NMBCs were examined, and the Cu(II) adsorption properties of this material were determined using various adsorption isotherms and kinetic models. The adsorption capacity of NMBCs for Cu(II), which was enhanced by increasing the pH from 3 to 6, was much larger than that of biochar or nano-MnO2. The maximum adsorption capacity of NMBCs for Cu(II) was 142.02 mg/g, which was considerably greater than the maximum adsorption capacities of biochar (26.88 mg/g) and nano-MnO2 (93.91 mg/g). The sorption process for Cu(II) on NMBCs fitted very well to a pseudo-second-order model (R2 > 0.99). Moreover, this process was endothermic, spontaneous, and hardly influenced by ionic strength. The mechanism of Cu(II) adsorption on NMBCs mainly involves the formation of complexes between Cu(II) and O-containing groups (e.g., COO–Cu and Mn–O–Cu). Thus, NMBCs may serve as effective adsorbents for various environmental applications, such as wastewater treatment or the remediation of copper-contaminated soils.
BackgroundThe transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by population dynamics of its main host, rodents. It is therefore important to better understand rodents’ characteristic in epidemic areas.Methodology/Principal FindingsWe examined the potential impact of food available and climatic variability on HFRS rodent host and developed forecasting models. Monthly rodent density of HFRS host and climate data in Changsha from January 2004 to December 2011 were obtained. Monthly normalized difference vegetation index (NDVI) and temperature vegetation dryness index (TVDI) for rice paddies were extracted from MODIS data. Cross-correlation analysis were carried out to explore correlation between climatic variables and food available with monthly rodent data. We used auto-regressive integrated moving average model with explanatory variables to examine the independent contribution of climatic variables and food supply to rodent density. The results indicated that relative rodent density of HFRS host was significantly correlated with monthly mean temperatures, monthly accumulative precipitation, TVDI and NDVI with lags of 1–6 months.Conclusions/SignificanceFood available plays a significant role in population fluctuations of HFRS host in Changsha. The model developed in this study has implications for HFRS control and prevention.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.