Reversibly enhanced aqueous solubilization of volatile organic compounds using a redox-reversible surfactant

Surfactant-enhanced remediation (SER) is an effective method for the removal of volatile organic compounds (VOCs) from contaminated soils and groundwater. To reuse the surfactant the VOCs must be separated from the surfactant solutions. The water solubility of VOCs can be enhanced using reversible surfactants with a redox-acive group, (ferrocenylmethyl)dodecyldimethylammonium bromide (Fcl2) and (ferrocenylmethyl)tetradecanedimethylammonium bromide (Fcl4), above and below their critical micelle concentrations (CMC) under reducing (I⁺) and oxidative (I²⁺) conditions. The CMC values of Fcl2 and Fcl4 in I⁺ are 0.94 and 0.56 mmol/L and the solubilization of toluene by Fcl2 and Fcl4 in I⁺ for toluene is higher than the solubilization achieved with sodium dodecyl sulfate, cetyltrimethylammonium bromide and Trition X-114. The solubilization capacity of the ferrocenyl surfactants for each tested VOCs ranked as follows: ethylbenzene > toluene > benzene. The solubilities of VOCs by reversible surfactant in I⁺ were 30% higher than those in I²⁺ at comparable surfactant concentrations. The effects of Fcl4 concentrations on VOCs removal efficiency were as follows: benzene > toluene > ethylbenzene. However, an improved removal efficiency was achieved at low ferrocenyl surfactant concentrations. Furthermore, the reversible surfactant could be recycled through chemical approaches to remove organic pollutants, which could significantly reduce the operating costs of SER technology.     

高温状态下受热时间对膨润土物性指标的影响∗

高温状态下膨润土的物性指标变化是高放核废物深地质处置库设计的重要参数之一。通过高温状态下不同受热时间MX80钠基膨润土的比重、液塑限、自由膨胀率试验,研究了受热时间对膨润土基本物性指标的影响规律;并通过热重分析(TGA)、X衍射(XDR)、电镜扫描(SEM)试验,从微观角度对上述变化规律进行了合理解释。研究结果表明:随着受热时间的增加,膨润土的比重、液塑限、自由膨胀率在受热15～30天内急剧下降,降幅分别为2.5%、3.1%和28.3%,之后各值变化量很小;高温状态下,膨润土的矿物成分转化、结合水脱附、微观形貌改变是膨润土物性指标发生变化的根本原因,三者之间相互作用和彼此影响。     

ECONOMIC RESOURCE MULTIPLIERS FOR REGIONAL IMPACT ANALYSIS1

ABSTRACT: Tradeoffs between regional economic development and resource use is a question often confronting local decisionmakers. A resource-interindustry model can be used to depict the interrelationships between regional economic sectors as to household income and/or employment and resource use. A resource-interindustry model was developed for Humboldt and Lander Counties in Nevada which shows the tradeoffs between regional household income (wages, salaries, profits, and rents) and/or employment and water usage. Water income and water employment multipliers can be ranked, enabling decisionmakers to realize sectors which require greatest regional water usage to regional household income and/or employment.     

Remediating ethylbenzene-contaminated clayey soil by a surfactant-aided electrokinetic (SAEK) process

The objectives of this research are to investigate the remediation efficiency and electrokinetic behavior of ethylbenzene-contaminated clay by a surfactant-aided electrokinetic (SAEK) process under a potential gradient of 2 Vcm(-1). Experimental results indicated that the type of processing fluids played a key role in determining the removal performance of ethylbenzene from clay in the SAEK process. A mixed surfactant system consisted of 0.5% SDS and 2.0% PANNOX 110 showed the best performance of ethylbenzene removed in the SAEK system. The removal efficiency of ethylbenzene was determined to be 63-98% in SAEK system while only 40% was achieved in an electrokinetic system with tap water as processing fluid. It was found that ethylbenzene was accumulated in the vicinity of anode in an electrokinetic system with tap water as processing fluid. However, the concentration front of ethylbenzene was shifted toward cathode in the SAEK system. The electroosmotic permeability and power consumption were 0.17 x 10(-6)-3.01 x 10(-6) cm(2)V(-1)s(-1) and 52-123 kW h m(-3), respectively. The cost, including the expense of energy and surfactants, was estimated to be 5.15-12.65 USD m(-3) for SAEK systems, which was 2.0-4.9 times greater than that in the system of electrokinetic alone (2.6 USD m(-3)). Nevertheless, by taking the remediation efficiency of ethylbenzene and the energy expenditure into account for the overall process performance evaluation, the system SAEK was still a cost-effective alternative treatment method.     

WATER MULTIPLIERS - REGIONAL IMPACT ANALYSIS1

A significant research problem is the assessment of impacts associated with growth and/or decline in a regional economy. A relevant method for analyzing such problems is the Leontief input/output model. Associated with these models are economic multipliers measuring total changes in sales, income, and employment. In this paper, the author contends resource multipliers are equally relevant. The specific form of these multipliers are defined. Water multipliers for a two-county region in central Nevada are presented and their uses described.     

三峡库区巴东县龙船河库岸塌岸预测及稳定性评价

采用卡丘金法、工程地质类比法对三峡库区巴东县龙船河库岸不同成因的土质岸坡、岩土混合质岸坡、软硬相间的岩质岸坡在水库蓄水后的塌岸进行了预测,并采用不平衡推力法对其稳定性进行了计算分析与评价,根据预测评价结果进行的防治方案设计,通过了三峡水库三期蓄水的检验,取得了较好的防治效果.     

预测沉积物-水微宇宙系统中化学品浓度变化的多介质模型

沉积物-水微宇宙系统是经济合作发展组织(Organisation for Economic Co-Operation and Development,OECD)颁布的化学品测试准则中推荐的试验系统之一,可用来测试化学品对底栖生物的慢性毒性。为了在试验前对化学品的浓度变化进行预测,进而确定试验方法,以摇蚊慢性毒性试验系统为例,采用环境多介质模型的建模方法,构建了一种可通过化学品理化性质和试验系统参数,对化学品在沉积物-水试验系统中浓度变化进行预测的模型。结合试验数据和文献资料,给出了模型中试验系统参数的推荐取值,并使用Matlab软件中的Simulink工具对模型进行编程和求解。以此模型为基础,给出了模型在3个方面的应用,即预测蓄积时间、预测平衡时间以及拟合试验数据。对80种已有或假想化学品的蓄积时间和平衡时间进行了计算,得出的范围分别为1~204 d和1~73 d。此外,适当修改模型结构和模型参数,也可将其应用于其他暴露场景中。但使用模型对化学品浓度进行预测时发现,模型仅对沉积物中化学品浓度的预测结果较为准确,而对水中化学品浓度的预测结果与实测值相差1~2个数量级。模型对浓度的预测精度未来仍需进一步提高。上述研究结果完善了沉积物-水微宇宙系统试验方法。     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Pollution levels and characteristics of phthalate esters in indoor air in hospitals

The concentrations of phthalate esters(PAEs) in Chinese hospitals were investigated by simultaneously determining concentrations of gas- and particle-phase PAEs. PAEs were detected in two third-class first-grade hospitals, two second-class first-grade hospitals, and a community health service center. Hospital drugstores had the highest concentration(24.19 μg/m3), which was 1.54 times that of newly decorated houses. The second highest concentration was found in the transfusion rooms, averaging 21.89 μg/m3; this was followed by the concentrations of PAEs in the nurse's workstations, the wards, and the doctor's offices, with mean concentrations of 20.66, 20.0, and 16.92 μg/m3, respectively. The lowest concentrations were found in the hallways(16.30 μg/m3). Of the six different kinds of PAEs found, major pollutants included diethyl phthalates, dibutyl phthalates, butylbenzyl phthalates and di(2-ethylhexyl) phthalates, comprising more than 80% of all PAEs present.Meanwhile, a comparison between different wards showed that PAE concentrations in the maternity wards were 1.63 times higher than in the main wards. Based on known health hazards, our results suggest that the PAEs seriously influence the health of the pregnant women and babies; therefore, it is of great importance to take the phthalate concentrations in hospitals into consideration. In addition, hospital indoor air was more seriously contaminated than the air of newly decorated houses.