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.     

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.

     

Toward better understanding and feasibility of controlling greenhouse gas emissions from treatment of industrial wastewater with activated sludge

Wastewater treatment plants (WWTPs) have been recognized as important sources for anthropogenic greenhouse gas (GHG) emission. The objective of the study was to thoroughly investigate a typical industrial WWTP in southern Taiwan in winter and summer which possesses the emission factors close to those reported values, with the analyses of emission factors, mass fluxes, fugacity, lab-scale in situ experiments, and impact assessment. The activated sludge was the important source in winter and summer, and nitrous oxide (N₂O) was the main contributor (e.g., 57 to 91 % of total GHG emission in a unit of kg carbon dioxide-equivalent/kg chemical oxygen demand). Albeit important for the GHGs in the atmosphere, the fractional contribution of the GHG emission to the carbon or nitrogen removal in wastewater treatment was negligible (e.g., less than 1.5 %). In comparison with the sludge concentration or retention time, adjusting the aeration rate was more effective to diminish the GHG emission in the activated sludge without significantly affecting the treated water quality. When the aeration rate in the activated sludge simulation was reduced by 75 %, the mass flux of N₂O could be diminished by up to 53 % (from 9.6 to 4.5 mg/m²-day). The total emission in the WWTP (including carbon dioxide, methane, and N₂O) would decrease by 46 % (from 0.67 to 0.36 kg CO₂-equiv/kg COD). However, the more important benefit of changing the aeration rate was lowering the energy consumption in operation of the WWTP, as the fractional contribution of pumping to the total emission from the WWTP ranged from 46 to 93 % within the range of the aeration rate tested. Under the circumstance in which reducing the burden of climate change is a global campaign, the findings provide insight regarding the GHG emission from treatment of industrial wastewater and the associated impact on the treatment performance and possible mitigation strategies by operational modifications.

     

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.     

Deodorization of pig manure using lignin peroxidase with different electron acceptors

Odor pollution is a big environmental problem caused by large-scale livestock production in China, and developing a practical way to reduce these odors is pressing. In this study, a combination of 0.2–1.0 U/mL lignin peroxidase (LiP) and one of three peroxides (H₂O₂, CaO₂, 2Na₃CO₃·3H₂O₂) was examined for its efficiency in reducing the release of eight chemicals (propionic acid, isobutyric acid, isocaproic acid, isovaleric acid, phenol, p-cresol, indole, and skatole), NH₃, H₂S, and odor intensity from pig manure. The results showed an approximately 90% reduction in p-cresol, 40–60% reduction in odor intensity, 16.5–40% reduction in indolic compounds, and 25–40% reduction in volatile fatty acids. Being the electron acceptors of LiP, 2Na₃CO₃·3H₂O₂ and CaO₂ performed better than H₂O₂ in reducing the concentration of eight chemicals, NH_3, H₂S, and odor intensity from pig manure. The effect of deodorization can last for up to 72 hr.

Implications: In China, one of the major environmental problems caused by confined feeding is odor pollution, which brings a major threat to the sustainability, profitability, and growth of the livestock industry. To couple the LiP with the electron acceptors, a low–cost, simple, and feasible method for odor removal was established in this study. Based on the study results, a practical treatment method was provided for odor pollution and supply the farm operators a more flexible time to dispose treated manure.     

绵阳市代表性点位土壤多环芳烃剖面分布特征

通过挑选绵阳市有代表性的点位土壤柱,应用GC MS分析土壤柱垂直剖面中多环芳烃的含量水平,得出其垂直剖面分布特征。结果表明：5~20 cm深度中的PAHs含量最高,40 cm以下则含量锐减。由于表层（0～5 cm）土壤与大气之间的土气交换频繁,PAHs含量相对较低,而5~20 cm处土壤受到表层土壤的遮盖,PAHs富集较高,含量达到整个土壤柱最高值。多环芳烃总体垂直剖面分布特征表现出随深度增加含量减少的趋势。PAHs总含量以江油市点位(33024 ng/g)最高,其次是三台县点位(29989 ng/g),最低是游仙区点位(11274 ng/g)。研究区主要污染物为Nap、Phe和Chr/y。其中不同的土质、种植物都能影响PAHs的富集和迁移速率,导致含量在不同深度上产生变化。此外,参照有关环境质量标准,发现PAHs总量上江油市点位与三台县点位属于轻微污染、游仙区点位则属于无污染。     

In situ removal of copper from sediments by a galvanic cell

This study dealt with in situ removal of copper from sediments through an electrokinetic (EK) process driven by a galvanic cell. Iron (Fe) and carbon (C) were placed separately and connected with a conductive wire. Polluted sediments were put between them and water was filled above the sediments. The galvanic cell was thus formed due to the different electrode potentials of Fe and C. The cell could remove the pollutants in the sediments by electromigration and/or electroosmosis. Results showed that a weak voltage less than 1V was formed by the galvanic cell. The voltage decreased with the increase of time. A slight increase of sediment pH from the anode (Fe) to the cathode (C) was observed. The presence of supernatant water inhibited the variation of sediment pH because H(+) and OH(-) could diffuse into the water. The removal of copper was affected by the sediment pH and the distribution of electrolyte in sediment and supernatant water. Lower pH led to higher removal efficiency. More electrolyte in the sediment and/or less electrolyte in the supernatant water favored the removal of copper. The major removal mechanism was proposed on the basis of the desorption of copper from sediment to pore solution and the subsequent electromigration of copper from the anode to the cathode. The diffusion of copper from sediment to supernatant water was negligible.     

针铁矿对Pb~(2+)的吸附特征及影响因素研究

通过恒温振荡平衡法研究了Pb~(2+)在针铁矿上的等温吸附和吸附动力学特征,探讨了吸附的影响因素.结果表明:(1)随Pb~(2+)平衡浓度和pH的增大,针铁矿对Pb~(2+)的吸附量逐渐增大.(2)针铁矿对Pb~(2+)的等温吸附可用Freundlich和Langmuir方程较好地拟合.(3)在相同温度和pH下,随离子强度的提高,针铁矿对Pb~(2+)的吸附量增大.(4)在相同离子强度和pH下,针铁矿对Pb~(2+)的吸附量总体随温度升高而增大.针铁矿对Pb~(2+)的吸附是自发进行的吸热反应.(5)针铁矿吸附Pb~(2+)的过程可分为初始的快吸附和随后的慢吸附2个阶段.pH影响吸附反应快慢,随pH增大吸附速率增大;随着pH的增大,达到平衡吸附的时间缩短.吸附动力学方程用Elovich方程拟合最佳.     

无银催化-分光光度法测定COD的研究

以XS-LP为催化剂,探讨了改进的无银催化HACH法测定污水中COD的系列条件实验。结果表明:在药剂A,B的投配比为1∶2,投加总量为12 g/L的条件下,其准确度、精密度与国标法有较好的可比性,分别小于10%和3%;对实际废水的测量结果与国标回流法的相关系数分别高达0.9951和0.9874,可满足一般环境检测技术规范要求。     

表面活性剂清洗处理重度石油污染土壤

为了优化表面活性剂清洗处理重度石油污染土壤的方法和具体洗脱条件参数,采集山东省东营市胜利油田污染土壤,研究了阴离子-非离子混合表面活性剂对该土壤中石油类污染物的去除效果。应用化学热洗原理,主要考查了表面活性剂配比、投加量、清洗温度及清洗助剂对去除效果的影响。实验得到的清洗处理最佳条件为：使用LAS与TX-100质量比为8∶2的组合表面活性剂,总表面活性剂浓度为3 g/L,助剂硅酸钠浓度为5 g/L,75℃条件下搅拌1 h。清洗后土壤含油量从20%下降到4.6%,去除率达到76.9%。废水回用实验表明,清洗处理的废水对土壤中石油烃类物质仍有一定的去除效果。废水回用比从30%到100%时,对土壤中石油烃的去除率都可达到55%以上。对废水进行二次回用时仍能去除18.8%的污染物。