垃圾渗滤液浇灌对红壤原生动物群落的影响

采用“非浸没培养皿法”（non-flooded petri dish method)培养，对李坑垃圾填埋汤垃圾渗液淋灌的土壤中的原生动物群落进行了分析。实验发现4属4种纤毛虫：膨胀肾形虫（Colpoda inflata)、有肋薄咽虫（Leptopharynx costatus)、莫式拟肾形虫（Paracolpoda maupasi)、恼斜板虫（Plagiocampa difficils)。随淋灌中垃圾渗滤液浓度的上升，出现的纤毛虫种类呈递减趋势，从定量实验的结果来看，即使是较低浓度的垃圾渗滤液，也对土壤原生动物群落造成了较大的伤害。25％浓度的垃圾渗滤液淋灌的土样中，原生动物数量仅为CK组的30％；超过50％浓度的渗滤液稀释液淋灌土样，则仅为CK组的10％左右。数据表明污染本身并没有被降解，而是全部（或至少大部分）转移到了受渗滤液影响的土壤中，从而导致土壤中的原生动物群落的结构无论是从数量上还是从种类上均曹到相当大的破坏。表4参15     

Negotiation System of Ecological Compensation of Water Source Areas

In view of no generally accepted ecological compensation standards and methods at present,this paper discusses the introduction of the negotiation system to the process of ecological compensation for water source areas.That is,the government in water source areas and the downstream regions of river basins should confirm their respective rights and obligations and then establish their compensation standards through negotiations according to the different purposes of water use.The amount of compensation should be determined in the comprehensive consideration of the quality,quantity and compensation price of water.Through open and fair negotiations,an institutional arrangement will be set up,which can make the water source areas and the downstream regions of river basins fully express their true preferences and their independent choices on the ecological environment.     

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.     

单甲脒饱和蒸气压的测定和估算

用气体的法测单甲脒在１５，２５，３５和４５℃时的饱和蒸气分别为０．２０２，０．５５４６，１．９５，６．２９Ｐａ；亨利常数计算值分别为６．３０×１０＾－４，１．６７×１０＾－３，５．６８×１０＾０－３和１．７８×１０＆－２，根据Ｃｌａｕｓｉｕｓ Ｃｌａｐｅｙｒｏｎ方程求出单甲脒在常温下气化热为８９．２ｋＪ．ｍｏｌ＾－１。     

南方土壤酸沉降敏感性研究Ⅷ.盐基离子淋溶的多因素分析

在模拟酸雨条件下土壤盐基离子淋溶特性研究的基础上，采用生成分分析及多元回归分析方法研究了土壤盐基淋溶的影响因子．结果表明，通过主成分分析方法可将选取的15个原始变量综合成为2个主成分，为进一步分析盐基释放量与土壤理化性质之间的关系提供了方便．影响盐基释放量的主要因子有土壤原始pH值、可交换性盐基含量、蒙脱石含量、活性氧化物、1.4nm矿物等，它们表现出效应，而高岭石和可交换性铝含量表现出负效应．利用主成分分析的结果进行多元回归分析，可得到土壤累积盐基释放量与2个主成分之间的回归方程．     

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。     

表观遗传学机制与空气污染的健康效应

空气污染是一个全球性的问题,并且具有深远的环境影响。暴露于空气污染会对人体健康产生许多不同的影响,理解空气污染的健康效应又是一个复杂命题,既要考虑不同类型的污染物同时也要考虑相关疾病的复杂性。然而越来越多的研究表明,表观遗传学在空气污染相关疾病的发生、发展中发挥着重要的作用。空气污染物可引起DNA甲基化、组蛋白修饰和miRNA表达等表观遗传学改变,这种改变往往发生在疾病产生的早期,因此相关研究不仅可以了解疾病的发病机制,而且还为疾病早期诊断和预防筛选可能的标志物。本文综述了表观遗传学的几种修饰方式和空气污染物造成不良健康损伤机制的一些研究进展。     

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.