Simultaneous determination of estrogenic odorant alkylphenols,chlorophenols, and their derivatives in water using online headspace solid phase microextraction coupled with gas chromatography-mass spectrometry

A simple online headspace solid-phase microextraction (HS-SPME) coupled with the gas chromatography-mass spectrometry (GC-MS) method was developed for simultaneous determination of trace amounts of nine estrogenic odorant alkylphenols and chlorophenols and their derivatives in water samples. The extraction conditions of HS-SPME were optimized including fiber selection, extraction temperature, extraction time, and salt concentration. Results showed that divinylbenzene/Carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber was the most appropriate one among the three selected commercial fibers, and the optimal extraction temperature, time, and salt concentration were 70 °C, 30 min, and 0.25 g/mL, respectively. The developed method was validated and showed good linearity (R ²?>?0.989), low limit of detection (LOD, 0.002–0.5 μg/L), and excellent recoveries (76–126 %) with low relative standard deviation (RSD, 0.7–12.9 %). The developed method was finally applied to two surface water samples and some of these target compounds were detected. All these detected compounds were below their odor thresholds, except for 2,4,6-TCAS and 2,4,6-TBAS wherein their concentrations were near their odor thresholds. However, in the two surface water samples, these detected compounds contributed to a certain amount of estrogenicity, which seemed to suggest that more attention should be paid to the issue of estrogenicity rather than to the odor problem.     

Electrospun and functionalized PVDF/PAN nanocatalyst-loaded composite for dechlorination and photodegradation of pesticides in contaminated water

A novel approach for the electrospinning and functionalization of nanocatalyst-loaded polyvinylidene fluoride/polyacrylonitrile (PVDF/PAN) composite grafted with acrylic acid (AA; which form polyacrylic acid (PAA) brush) and decorated with silver (Ag/PAN/PVDF-g-PAA-TiO₂/Fe–Pd) designed for the dechlorination and photodegradation of pesticides was carried out. PAN was used both as a nitrogen dopant as well as a co-polymer. Smooth nanofibers were obtained by electrospinning a solution of 12:2 wt.% PVDF/PAN blend using dimethylformamide (DMF) as solvent. The nanofibers were grafted with AA by free-radical polymerization using 2,2′azobis(2-methylpropionitrile) (AIBN) as initiator. Both bimetallic iron–palladium (Fe–Pd) and titania (TiO₂) nanoparticles (NP) were anchored on the grafted nanofibers via the carboxylate groups by in situ and ex situ synthesis. The Fe–Pd and nitrogen-doped TiO₂ nanoparticles were subsequently used for dechlorination and oxidation of target pollutants (dieldrin, chlorpyrifos, diuron, and fipronil) to benign products. Structural and chemical characterizations of the composites were done using various techniques. These include surface area and porosity analyzer (ASAP) using the technique by Brunner Emmett Teller (BET), Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscope (TEM) analyses were done. After dechlorination, the transformation products (TPs) for dieldrin, chlorpyrifos, diuron, and fipronil were obtained and identified using two-dimensional gas chromatography (time-of-flight) with a mass spectrometer detector (GCxGC-TOFMS). Analysis of total organic carbon (TOC) was carried out and used to extrapolate percentage mineralization. Experimental results showed that dechlorination efficiencies of 96, 93, 96, and 90 % for 1, 2, 2, and 3 h treatment period were respectively achieved for 5 ppm solutions of dieldrin, chlorpyrifos, diuron, and fipronil. The dechlorination of dieldrin, diuron, and fipronil follows first-order kinetics while that of chlorpyrifos followed pseudo-first order. Mineralization performance of 34 to 45 % were recorded when Fe–Pd was used, however upon electrospinning, doping, and grafting (Ag/PAN/PVDF-g-PAA-TiO₂/Fe–Pd composite); it significantly increased to 99.9999 %. This composite reveals great potential for dechlorination and mineralization of pesticides in contaminated water.     

Dry reforming of methane to syngas: a potential alternative process for value added chemicals—a techno-economic perspective

During the past decade, there has been increasing global concern over the rise of anthropogenic CO₂ emission into the Earth’s atmosphere (J Air Waste Manage Assoc 53:645–715, 2003). The utilization of CO₂ to produce any valuable product is need of the hour. The production of syngas from CO₂ and CH₄ seems to be one of the promising alternatives in terms of industrial utilization, as it offers several advantages: (a) mitigation of CO₂, (b) transformation of natural gas and CO₂ into valuable syngas, and (c) producing syngas with H₂/CO ratio 1 which may further be used for the production of valuable petrochemicals (J Air Waste Manage Assoc 53:645–715, 2003). A conceptual design for the production of synthesis gas by dry reforming of methane is presented here. An economic assessment of this process with an integrated methanol production section as a case was conceptualized and compared with the conventional steam methane reforming route to produce methanol. The economic study indicated that dry reforming of natural gas/methane is a competitive process with lower operating and capital costs in comparison with steam reforming assuming negligible cost of CO₂ import.     

Increasing the recovery of heavy metal ions using two microbial fuel cells operating in parallel with no power output

The present study aimed to improve the performance of microbial fuel cells (MFCs) by using an intermittent connection period without power output. Connecting two MFCs in parallel improved the voltage output of both MFCs until the voltage stabilized. Electric energy was accumulated in two MFCs containing heavy metal ions copper, zinc, and cadmium as electron acceptors by connection in parallel for several hours. The system was then switched to discharge mode with single MFCs with a 1000-Ω resistor connected between anode and cathode. This method successfully achieved highly efficient removal of heavy metal ions. Even when the anolyte was run in sequencing batch mode, the insufficient voltage and power needed to recover heavy metals from the cathode of MFCs can be complemented by the developed method. The average removal ratio of heavy metal ions in sequencing batch mode was 67 % after 10 h. When the discharge time was 20 h, the removal ratios of zinc, copper, and cadmium were 91.5, 86.7, and 83.57 %, respectively; the average removal ratio of these ions after 20 h was only 52.1 % for the control group. Therefore, the average removal efficiency of heavy metal ions increased by 1.75 times using the electrons stored from the bacteria under the open-circuit conditions in parallel mode. Electrochemical impedance data showed that the anode had lower solution resistance and polarization resistance in the parallel stage than as a single MFC, and capacitance increased with the length of time in parallel.

     

Efficacy of Si fertilization to modulate the heavy metals absorption by barley (Hordeum vulgare L.) and pea (Pisum sativum L.)

Silicon-based fertilizers and soil amendments can have direct and indirect positive influences on cultivated plants. The solid forms of Si-based substances, the most widespread in use, are efficient only at high application rates due to their low level of solubility. Several types of Si-based substances such as fumed silica, slags from the iron and steel industry, modified slags, and a Si-rich product were tested using barley and pea as silicon accumulative and non-accumulative plants, respectively, at two application rates. The plants were grown under toxic concentrations of heavy metals in a greenhouse. Si-rich materials high in water-soluble Si had a positive effect at both the low and high application rates, and for both plant species. This type of substance can be regarded as Si fertilizer, demonstrating greater efficiency at a low application rate and lessened efficiency at a high application rate for protection of the cultivated plants against accumulation of the heavy metals.

     

Wastewater reuse: modeling chloroform formation

The chloroform is a substance that presents a significant risk to or via the aquatic environment. Thus, the emissions, discharges and losses of this substance need to be controlled during wastewater disinfection for reclamation and reuse purposes. Due to its carcinogenetic potential, multiple studies have been carried out on drinking and surface/natural waters but less consideration has been directed to the wastewater disinfection. The focus of this work studied the formation of chloroform during chlorination in prepared waters or artificial matrices that intended to simulate wastewaters stored in landscape ponds for green areas irrigation. The relation between reaction time, chlorine dose, and chloroform formation and the variation of the dissolved organic carbon (DOC) content during the reaction was assessed. A two-variant model was proposed to simulate breakpoint chlorination practices (when chlorine dose is equal or lower than chlorine demand) and super chlorination techniques (when chlorine dose tends to surpass chlorine demand). The model was validated by the application of actual data from working conditions of six wastewater treatment plants located in Algarve, Portugal, including other data obtained in previous research studies that were not used in the model development, and by comparing the predicted values with real measured ones.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Increasing CACNA1C expression in placenta containing high Cd level: an implication of Cd toxicity

Cadmium (Cd) has known to produce many adverse effects on organs including placenta. Many essential transporters are involved in Cd transport pathways such as DMT-1, ZIP as well as L-VDCC. Fourteen pregnant women participated and were divided into two groups: high and low Cd-exposed (H-Cd, L-Cd) groups on the basis of their residential areas, Cd concentrations in the blood (B-Cd), urine (U-Cd), and placenta (P-Cd). The results showed that the B-Cd and U-Cd were significantly increased in H-Cd group (p < 0.05). Interestingly, the P-Cd in H-Cd group was elevated (p < 0.05) and positively related to their B-Cd and U-Cd values (p < 0.05). However, the mean cord blood Cd (C-Cd) concentration in H-Cd group was not significantly increased about 2.5-fold when comparing to L-Cd group. To determine the Cd accumulation in placental tissues, metallothionein-1A (MT-1A) and metallothionein-2A (MT-2A) expressions were used as biomarkers. The results revealed that mean MT-1A and MT-2A mRNAs and MT-1/2 proteins were up-regulated in H-Cd group (p < 0.05). In addition, the Ca channel alpha 1C (CACNA1C) mRNA and protein expressions were noticeably elevated in H-Cd group (p < 0.05). From these findings, we suggested that CACNA1C might be implicated in Cd transport in human placenta.     

Rapid metal extractability tests from polluted mining soils by ultrasound probe sonication and microwave-assisted extraction systems

Ultrasonic probe sonication (UPS) and microwave-assisted extraction (MAE) were used for rapid single extraction of Cd, Cr, Cu, Ni, Pb, and Zn from soils polluted by former mining activities (Mónica Mine, Bustarviejo, NW Madrid, Spain), using 0.01 mol L^?1 calcium chloride (CaCl₂), 0.43 mol L^?1 acetic acid (CH₃COOH), and 0.05 mol L^?1 ethylenediaminetetraacetic acid (EDTA) at pH 7 as extracting agents. The optimum extraction conditions by UPS consisted of an extraction time of 2 min for both CaCl₂ and EDTA extractions and 15 min for CH₃COOH extraction, at 30% ultrasound (US) amplitude, whereas in the case of MAE, they consisted of 5 min at 50 °C for both CaCl₂ and EDTA extractions and 15 min at 120 °C for CH₃COOH extraction. Extractable concentrations were determined by inductively coupled plasma atomic emission spectrometry (ICP-AES). The proposed methods were compared with a reduced version of the corresponding single extraction procedures proposed by the Standards, Measurements and Testing Programme (SM&T). The results obtained showed a great variability on extraction percentages, depending on the metal, the total concentration level and the soil sample, reaching high values in some areas. However, the correlation analysis showed that total concentration is the most relevant factor for element extractability in these soil samples. From the results obtained, the application of the accelerated extraction procedures, such as MAE and UPS, could be considered a useful approach to evaluate rapidly the extractability of the metals studied.