Assessing inter-laboratory comparability and limits of determination for the analysis of cyclic volatile methyl siloxanes in whole Rainbow Trout (Oncorhynchus mykiss)

Cyclic volatile methyl siloxanes (cVMS) are high volume production chemicals used in a wide range of industrial and consumer products. Three cVMS compounds (D4, D5, and D6) have and are undergoing environmental risk evaluations in several countries and have been proposed for legal regulation in Canada. As interest in monitoring concentrations of these chemicals in the environment increase, there is a need to evaluate the analytical procedures for cVMS in biological matrices in order to assess the quality of data produced. The purpose of this study was to determine laboratory testing performance for measuring residues of D4, D5, and D6 in a standard set of fish homogenate samples and to estimate limits of determination for each substance. The samples sent to each laboratory consisted of homogenized whole body tissues of hatchery raised rainbow trout which were fed food fortified with D4, D5, and D6 (dosed) and trout that were fed standard food rations (control). The participants analyzed each sample using their analytical method of choice using their own standards and procedures for quantification and quality control. With a few exceptions, participating laboratories generated comparable results for D4, D5, and D6 in both the dosed and control samples having z-scores between 2 and −2. Method detection limits for the whole fish matrix were on average 2.4 ng g⁻¹ ww for D4, 2.3 ng g⁻¹ ww for D5, and 1.8 ng g⁻¹ ww for D6.     

Efficient treatment of azo dye containing wastewater in a hybrid acidogenic bioreactor stimulated by biocatalyzed electrolysis

In this study, a novel scaled-up hybrid acidogenic bioreactor(HAB) was designed and adopted to evaluate the performance of azo dye(acid red G, ARG) containing wastewater treatment. Principally, HAB is an acidogenic bioreactor coupled with a biocatalyzed electrolysis module. The effects of hydraulic retention time(HRT) and ARG loading rate on the performance of HAB were investigated. In addition, the influent was switched from synthetic wastewater to domestic wastewater to examine the key parameters for the application of HAB. The results showed that the introduction of the biocatalyzed electrolysis module could enhance anoxic decolorization and COD(chemical oxygen demand) removal. The combined process of HAB-CASS presented superior performance compared to a control system without biocatalyzed electrolysis(AB-CASS). When the influent was switched to domestic wastewater, with an environment having more balanced nutrients and diverse organic matters, the ARG, COD and nitrogen removal efficiencies of HAB-CASS were further improved, reaching 73.3% ± 2.5%, 86.2% ± 3.8% and 93.5% ± 1.6% at HRT of 6 hr, respectively, which were much higher than those of AB-CASS(61.1% ± 4.7%,75.4% ± 5.0% and 82.1% ± 2.1%, respectively). Moreover, larger TCV/TV(total cathode volume/total volume) for HAB led to higher current and ARG removal. The ARG removal efficiency and current at TCV/TV of 0.15 were 39.2% ± 3.7% and 28.30 ± 1.48 m A,respectively. They were significantly increased to 62.1% ± 2.0% and 34.55 ± 0.83 m A at TCV/TV of 0.25. These results show that HAB system could be used to effectively treat real wastewater.     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

微电解-UBF-CASS工艺处理制药废水

针对某制药业废水的特点，采用了“微电解-UBF-CASS”为主体的组合处理工艺。工程运行结果表明：在进水CODCr为10000—12000ms／L，处理后出水CODCr小于200mg/L，平均去除率达到98％以上，系统出水达到《污水综合排放标准》（GB8978—1996）中的二级标准。     

Impact Assessment and Recommendation of Alternative Conjunctive Water Use Strategies for Salt Affected Agricultural Lands through a Field Scale Decision Support System – A Case Study

Conjunctive use of saline/non-saline irrigation waters is generally aimed at minimizing yield losses and enhancing flexibility of cropping, without much alteration in farming operations. Recommendation of location-specific suitable conjunctive water use plans requires assessment of their long-term impacts on soil salinization/sodification and crop yield reductions. This is conventionally achieved through long-term field experiments. However such impact evaluations are site specific, expensive and time consuming. Appropriate decision support systems (DSS) can be time-efficient and cost-effective means for such long-term impact evaluations. This study demonstrates the application of one such (indigenously developed) DSS for recommending best conjunctive water use plans for a, rice-wheat growing, salt affected farmer’s field in Gurgaon district of Haryana (India). Before application, the DSS was extensively validated on several farmers and controlled experimental fields in Gurgaon and Karnal districts of Haryana (India). Validation of DSS showed its potential to give realistic estimates of root zone soil salinity (with R = 0.76–0.94; AMRE = 0.03–0.06; RMSPD = 0.51–0.90); sodicity (with R = 0.99; AMRE = 0.02; RMSPD = 0.84) and relative crop yield reductions (AMRE = 0.24), under existing (local) resource management practices. Long term (10 years) root zone salt build ups and associated rice/wheat crop yield reductions, in a salt affected farmer’s field, under varied conjunctive water use scenarios were evaluated with the validated DSS. It was observed that long-term applications of canal (CW) and tube well (TW) waters in a cycle and in 1:1 mixed mode, during Kharif season, predicted higher average root zone salt reductions (2–9%) and lower rice crop yield reductions (4–5%) than the existing practice of 3-CW, 3-TW, 3-CW. Besides this, long-term application of 75% CW mixed with 25% TW, during Rabi season, predicted about 17% lower average root-zone salt reductions than the cyclic applications of (1-CW, 1-TW, 2-CW) and (2-CW, 1-TW, 1-CW, i.e., existing irrigation strategy). However, average wheat crop yield reductions (16–17%) simulated under all these strategies were almost at par. In general, cyclic-conjunctive water use strategies emerged as better options than the blending modes. These results were in complete confirmation with actual long-term conjunctive water use experiments on similar soils. It was thus observed that such pre-validated tools could be efficient means for designing, local resource and target crop yield-specific, appropriate conjunctive water use plans for irrigated agricultural lands.     

纳米铂微粒电极催化氧化有机污染物的研究

采用电化学阴极还原-阳极氧化方法制备了纳米铂微粒电极.电极表面的微观结构表征表明,铂微粒在三维网状的氧化钛膜孔道中呈均匀、高度分散状态,且粒径细小,铂微粒充分裸露,使得纳米铂微粒电极活性点多,电催化性能高.采用循环伏安法研究了铂微粒电极对有机小分子代表性物质甲醇的电催化氧化行为.结果表明,在酸性、中性和碱性介质中纳米铂微粒电极对甲醇的电催化氧化性能均明显优于光滑铂片电极,甲醇在纳米铂微粒电极上产生的氧化电流密度比光滑铂片电极高100倍以上.2种铂电极催化氧化降解甲醇、苯酚和甲基橙3种有机物时,纳米铂微粒电极的平均氧化电流效率是光滑铂片电极的数倍,这进一步表明纳米铂微粒电极对有机污染物具有良好的催化氧化降解能力.     

One-electron standard reduction potentials of nitroaromatic and cyclic nitramine explosives

Extensive studies have been conducted in the past decades to predict the environmental abiotic and biotic redox fate of nitroaromatic and nitramine explosives. However, surprisingly little information is available on one-electron standard reduction potentials (E^o(R-NO₂/R-NO₂⁻)). The E^o(R-NO₂/R-NO₂⁻) is an essential thermodynamic parameter for predicting the rate and extent of reductive transformation for energetic residues. In this study, experimental (linear free energy relationships) and theoretical (ab initio calculation) approaches were employed to determine E^o(R-NO₂/R-NO₂⁻) for nitroaromatic, (caged) cyclic nitramine, and nitroimino explosives that are found in military installations or are emerging contaminants. The results indicate a close agreement between experimental and theoretical E^o(R-NO₂/R-NO₂⁻) and suggest a key trend: E^o(R-NO₂/R-NO₂⁻) value decreases from di- and tri-nitroaromatic (e.g., 2,4-dinitroanisole) to nitramine (e.g., RDX) to nitroimino compound (e.g., nitroguanidine). The observed trend in E^o(R-NO₂/R-NO₂⁻) agrees with reported rate trends for reductive degradation, suggesting a thermodynamic control on the reduction rate under anoxic/suboxic conditions.     

Treatment of dynamic mixture of hexane and benzene vapors in a Trickle Bed Air Biofilter integrated with cyclic adsorption/desorption beds

One of the main challenges that face successful biofiltration is the erratic loading pattern and long starvation periods. However, such patterns are common in practical applications. In order to provide long-term stable operation of a biofilter under these conditions, a cyclic adsorption/desorption beds system with flow switching was installed prior to a biofilter. Different square waves of a mixture containing n-hexane and benzene at a 2:1 ratio were applied to the cyclic adsorption/desorption beds and then fed to a biofilter. The performance of this integrated system was compared to a biofilter unit receiving the same feed of both VOCs. The cyclic adsorption/desorption beds unit successfully achieved its goal of stabilizing erratic loading even with very sharp peaks at the influent concentration equalizing influent concentrations ranging from 10-470 ppmv for n-hexane to 30-1410 ppmv for benzene. The study included different peak concentrations with durations ranging from 6 to 20 min. The cyclic beds buffered the fluctuating influent load and the followed biofilter had all the time a continuous stable flow. Another advantage achieved by the cyclic adsorption/desorption beds was the uninterrupted feed to the biofilter even during the starvation where there was no influent in the feed. The results of the integrated system with regard to removal efficiency and kinetics are comparable to published results with continuous feed studies at the same loading rates. The removal efficiency for benzene had a minimum of 85% while for n-hexane ranged from 50% to 77% according to the loading rate. The control unit showed very erratic performance highlighting the benefit of the utilization of the cyclic adsorption/desorption beds. The biofilter was more adaptable to concentration changes in benzene than n-hexane.     

Effects of cadmium on the activities of photosystems of Chlorella pyrenoidosa and the protective role of cyclic electron flow

Cadmium (Cd) shows high toxicity to aquatic microalgae. Many studies showed that Cd inhibited activities of photosystem II (PSII) but the effects of heavy metals on photosystem I (PSI) and cyclic electron flow (CEF) were still controversial and unclear. The effects of CdCl₂ on the activities of PSI, PSII and CEF in Chlorella pyrenoidosa was measured simultaneously in the present study. In presence of 200 μM of Cd, ultrastructure of some cells was strongly modified. Cd exposure led to decrease of the activities of photosynthetic oxygen evolution and respiration. PSII was more sensitive to Cd treatment than PSI. Cd treatment showed significant inhibition on the photochemical quantum yield and electron transport rate of PSII. Cd increased the quantum yield of non-light-induced non-photochemical fluorescence quenching, indicating the damage of PSII. The activity of PSI showed tolerance to Cd treatment with concentration less than 100 μM in the experiment. Linear electron flow (LEF) made significant contribution to the photochemical quantum yield of PSI of the untreated cells, but decreased with increasing Cd concentration. The contribution of CEF to the yield of PSI increased with increasing Cd concentration. The activation of CEF after exposure to Cd played an essential role for the protection of PSI.     

Modelling the spatial population dynamics of the green oak leaf roller (Tortrix viridana) using density dependent competitive interactions: Effects of herbivore mortality and varying host-plant quality

Cyclic population dynamics of forest insects with periods of more than two generations have been discussed in relation to a variety of extrinsic and intrinsic forces. In the present study, we employed the selection pressure of density dependent competitive interactions according to Witting's equations (Witting, 2000) as driver for a discrete spatiotemporal model of the green oak leaf roller (Tortrix viridana). The model was successfully parameterised to rebuild the cyclic population dynamics of an empirical data set of a 30-year leaf roller monitoring in Russia. Our analysis focussed on the role of herbivore mortality and host plant food quality, which have a significant effect on T. viridana population dynamics. An additional egg or larvae mortality lowers population density and can lead to selection pressures that favour individuals with higher growth rate. This increased population growth rate can not only compensate the additional mortality, but also can lead to higher average moth abundances in subsequent generations. Furthermore, we analysed the effect of inter- and intraspecific variation in host plant quality on herbivore population dynamics and the spatial distribution of abundance and defoliation patterns. We found significant effects of the qualitative composition of a trees neighbourhood on the herbivore population of the respective tree. Also, the patchy damage patterns observable in reality have been reproduced by the present model. The applicability of the model approach and the putative genetic processes underlying Witting's model are discussed.