Characterization of the monthly variation in (1 → 3)-β-d-glucan concentrations in university laboratories

We characterize the monthly variation in (1 → 3)-β-d-glucan concentration measured over the course of 1 year, and we evaluate the characteristics of size selection using a two-stage cyclone sampler. The (1 → 3)-β-d-glucan concentrations were measured in four bio-related laboratories. A total of 156 samples were collected using a new two-stage cyclone sampler. Analysis of (1 → 3)-β-d-glucan was performed using the kinetic Limulus amebocyte lysate assay. The study showed that airborne (1 → 3)-β-d-glucan concentrations were significantly higher in laboratory D (mean ± SD 1,105?±?1,893 pg/m³) and in the spring (5,458 pg/m³). The highest concentration of (1 → 3)-β-d-glucan occurred in the spring, particularly in May.     

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.     

Antibiotics along an alpine river and in the receiving lake with a catchment dominated by grazing husbandry

The livestock breeding industries face overuse of antibiotics, which has been intensively studied in recent years. However, the occurrence and fate of antibiotics as well as their potential threats to the aquatic environments in alpine and arid regions remain unclear. This study investigated the relationship of the occurrence and concentrations of antibiotics between the Kaidu River and Bosten Lake in a typical alpine basin in China. Hot spots with antibiotic pollution source were explored. The antibiotic concentrations in river water and suspended sediment (SPS) were 2.20-99.4 ng/L and 1.03-176 ng/g. The dominant antibiotics were tetracyclines, sulphacetamide, and ofloxacin in river water and sulfonamides, clarithromycin, roxithromycin, and ofloxacin in SPS. The apparent differences in pollution sources and landscapes in different reaches led to the obvious spatial patterns of antibiotics in the Kaidu River. Higher partition coefficient of antibiotic between SPS and water phases for sulfonamides than tetracyclines was because that tetracyclines strongly responded to clay contents while sulfonamides significantly responded to organic carbon contents in SPS. There were significant differences in detected antibiotic categories between the river and the lake. Fluoroquinolones (especially ciprofloxacin and enrofloxacin) were detected in the lake while sulphacetamide was only detected in the river. Therefore, the surrounding husbandry and aquaculture around the Bosten Lake was an important antibiotic pollution source in addition to inputs from the Kaidu River. This research suggested that alpine lakes could be an important sink of antibiotics in alpine dry regions, and thus impose greater threats to the aquatic ecosystem.     

节能型虹吸式滗水器的设计与应用

详细介绍了虹吸式滗水器的构成、特点及工作原理,结合理论和实践经验给出了虹吸式滗水器的设计、计算方法及关键设计参数,提出了常规使用方法,整套设备的设计全面而简单明了。     

电石渣-石膏湿法烟气脱硫废水处理工艺研究

电石渣-石膏湿法脱硫废水与石灰石-石膏湿法脱硫废水存在差异,主要体现在悬浮物与COD较难去除,采用在中和池添加助凝剂与曝气池添加氧化剂的方法,可在沿用石灰石法脱硫废水处理工艺设计的前提下达到对电石渣法脱硫废水的良好处理效果。     

基于高铁酸钾同步氧化-絮凝技术在污水处理中的研究进展

Fe(Ⅵ)具有较高的氧化还原电位,Fe(OH)3具有良好的絮凝效果,废水处理中高铁酸钾发挥同步氧化和絮凝作用。介绍高铁酸钾处理各种难降解废水的机理,同时分析高铁酸钾投加量、pH、反应温度、反应时间等因素对各种废水去除效果的影响。并提出基于高铁酸钾同步氧化絮凝技术处理污水的局限性和未来的发展方向。