Fenton-like oxidation and mineralization of phenol using synthetic Fe(II)–Fe(III) green rusts

Background, aim, and scope  

In literature, the environmental applications of green rust (GR) have mainly been pointed out through the reduction of inorganic contaminants and the reductive dechlorination of chlorinated organics. However, reactions involving GR for the oxidation and mineralization of organic pollutants remain very scantly described. In this study, the ability of three synthetic Fe(II)–Fe(III) green rusts, GR(CO₃²⁻), GR(SO₄²⁻), and GR(Cl⁻), to promote Fenton-like reaction was examined by employing phenol as a model pollutant. Unlike the traditional Fenton’s reagent (dissolved Fe(II) + H₂O₂), where the pH values have to be lowered to less than 4, the proposed reaction can effectively oxidize the organic molecules at neutral pH and could avoid the initial acidification which may be costly and destructive for the in situ remediation of contaminated groundwater and soils. The green rust reactivity towards the oxidative transformation of phenol was thoroughly evaluated by performing a large kinetic study, chemical analyses, and spectroscopic investigations.     

Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.     

A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

There are several deficiencies in the statistical approaches proposed in the literature for the assessment and redesign of surface water-quality-monitoring locations. These deficiencies vary from one approach to another, but generally include: (i) ignoring the attributes of the basin being monitored; (ii) handling multivariate water quality data sequentially rather than simultaneously; (iii) focusing mainly on locations to be discontinued; and (iv) ignoring the reconstitution of information at discontinued locations. In this paper, a methodology that overcomes these deficiencies is proposed. In the proposed methodology, the basin being monitored is divided into sub-basins, and a hybrid-cluster analysis is employed to identify groups of sub-basins with similar attributes. A stratified optimum sampling strategy is then employed to identify the optimum number of monitoring locations at each of the sub-basin groups. An aggregate information index is employed to identify the optimal combination of locations to be discontinued. The proposed approach is applied for the assessment and redesign of the Nile Delta drainage water quality monitoring locations in Egypt. Results indicate that the proposed methodology allows the identification of (i) the optimal combination of locations to be discontinued, (ii) the locations to be continuously measured and (iii) the sub-basins where monitoring locations should be added. To reconstitute information about the water quality variables at discontinued locations, regression, artificial neural network (ANN) and maintenance of variance extension (MOVE) techniques are employed. The MOVE record extension technique is shown to result in a better performance than regression or ANN for the estimation of information about water quality variables at discontinued locations.     

A novel methodology for household waste characterization during the COVID-19 pandemic: case study results

Journal of Material Cycles and Waste Management - The COVID-19 pandemic has caused a large number of the world’s cities to establish quarantines. Much has been said about the environmental...     

Use of beetroot fibers to clean water contaminated with heavy metals,to soften hard water,and to desalinate seawater

In this article we describe the use of beetroot fibers in treating water contaminated with heavy metals, in softening hard water, and in desalinating seawater. The study was carried out with either beetroot fibers or powdered fibers using a laboratory column with a fixed bed. The effectiveness of the method and the effect of the pH on it were monitored by atomic absorption spectrometry, infrared spectroscopy, conductivity measurements, and a volumetric method. The optimum pH range for all the treatment was found to be between 6.0 and 6.6. The heavy metals included in this study were lead, copper, nickel, and zinc. The amount of heavy metals retained by the fibers or the powder was significant in each case. The retention capacity was the strongest for lead and the weakest for nickel. In the case of hard water and seawater studies, our experiments revealed a dramatic decrease in total dissolved solids (TDS), indicating the potential of the method as an aid or an alternative to conventional methods.     

Meeting the Aichi targets: Pushing for zero extinction conservation

Effective protection of the ~19 000 IUCN-listed threatened species has never been more pressing. Ensuring the survival of the most vulnerable and irreplaceable taxa and places, such as those identified by the Alliance for Zero Extinction (AZE) species and their associated sites (AZEs&s), is an excellent opportunity to achieve the Aichi 2020 Targets T11 (protected areas) and T12 (preventing species extinctions). AZE taxa have small, single-site populations that are especially vulnerable to human-induced extinctions, particularly for the many amphibians. We show that AZEs&s can be protected feasibly and cost-effectively, but action is urgent. We argue that the Alliance, whose initial main aim was to identify AZEs&s, must be followed up by a second-generation initiative that directs and co-ordinates AZE conservation activities on the ground. The prominent role of zoos, conservation NGOs, and governmental institutions provides a combination of all-encompassing knowhow that can, if properly steered, maximize the long-term survival of AZEs&s.     

Determinants of indoor and personal exposure to PM2.5 of indoor and outdoor origin during the RIOPA study

Effects of physical/environmental factors on fine particle (PM_2.5) exposure, outdoor-to-indoor transport and air exchange rate (AER) were examined. The fraction of ambient PM_2.5 found indoors (F_INF) and the fraction to which people are exposed (α) modify personal exposure to ambient PM_2.5. Because F_INF, α, and AER are infrequently measured, some have used air conditioning (AC) as a modifier of ambient PM_2.5 exposure. We found no single variable that was a good predictor of AER. About 50% and 40% of the variation in F_INF and α, respectively, was explained by AER and other activity variables. AER alone explained 36% and 24% of the variations in F_INF and α, respectively. Each other predictor, including Central AC Operation, accounted for less than 4% of the variation. This highlights the importance of AER measurements to predict F_INF and α. Evidence presented suggests that outdoor temperature and home ventilation features affect particle losses as well as AER, and the effects differ.Total personal exposures to PM_2.5 mass/species were reconstructed using personal activity and microenvironmental methods, and compared to direct personal measurement. Outdoor concentration was the dominant predictor of (partial R² = 30–70%) and the largest contributor to (20–90%) indoor and personal exposures for PM_2.5 mass and most species. Several activities had a dramatic impact on personal PM_2.5 mass/species exposures for the few study participants exposed to or engaged in them, including smoking and woodworking. Incorporating personal activities (in addition to outdoor PM_2.5) improved the predictive power of the personal activity model for PM_2.5 mass/species; more detailed information about personal activities and indoor sources is needed for further improvement (especially for Ca, K, OC). Adequate accounting for particle penetration and persistence indoors and for exposure to non-ambient sources could potentially increase the power of epidemiological analyses linking health effects to particulate exposures.     

Atmospheric nitrous oxide: patterns of global change during recent decades and centuries

Data from weekly global measurements of nitrous oxide from 1981 to the end of 1996 are presented. The results show that there is more N2O in the northern hemisphere by about 0.7 +/- 0.04 ppbv, and the Arctic to Antarctic difference is about 1.2 +/- 0.1 ppbv. Concentrations at locations influenced by continental air are higher than at marine sites, showing the existence of large land-based emissions. For the period studied, N2O increased at an average rate of about 0.6 ppbv/year (approximately 0.2%/year) although there were periods when the rates were substantially different. Using ice core data, a record of N2O can be put together that goes back about 1000 years. It shows pre-industrial levels of about 287 +/- 1 ppbv and that concentrations have now risen by about 27 ppbv or 9.4% over the last century. The ice core data show that N2O started increasing only during the 20th century. The data presented here represent a comprehensive view of the present global distribution of N20 and its historical and recent trends.