邻苯二甲酸酯类增塑剂的体外细胞毒性评价

邻苯二甲酸酯(Phthalate esters, PAEs)是环境介质中的一类典型的有机污染物。已有研究表明,PAEs具有明显的内分泌干扰毒性,并会对动物和人体的生殖发育与神经系统造成损伤。体外细胞评价模型因具有高通量、测试周期短、成本低和毒性效应易于探明等技术优点,被广泛应用到PAEs毒理学效应的研究中。本文从内分泌干扰毒性、胚胎发育毒性、神经毒性、免疫毒性、遗传毒性以及致癌作用等方面,对PAEs的一些体外细胞毒性评价模型进行了分类和总结,并对其相应的研究进展进行了综述。本文旨在为体外细胞毒性评价模型的有效利用提供借鉴,并对PAEs毒性作用机制的深入研究提供思路和依据。     

环境样品中 PCBs 的测定

通过碱解、酸洗、萃取、净化、浓缩、脱硫等步骤处理实际样品,利用毛细管柱GC/ECD进行PCBs的定性和定量.方法定性准确,定量良好,具有较高的回收率.各同系物的方法检出限,水样为0.01～0.08ng/L;土壤样为0.003～0.03μg/kg,可以应用于土壤、沉积物、水样、油样等环境样品中PCBs的测定     

Sources and seasonal variation of PAHs in the sediments of drinking water reservoirs in Hong Kong and the Dongjiang River (China)

The main objective of this study was to investigate occurrence of polycyclic aromatic hydrocarbons (PAHs) in the sources of the drinking water supply of Hong Kong. The main emphasis was on the Dongjiang River in mainland China which is the major source, supplying 80% of the total consumption in Hong Kong (the remaining 20% is obtained from rain water). Sediments were collected from four sites along the Dongjiang River and four reservoirs in Hong Kong during both the dry and wet weather seasons. The concentrations of total PAHs in the sediments ranged between 36 and 539 microg/kg dry wt. The lower levels were detected at the upstream site on the Dongjiang River and at the reservoirs in Hong Kong (44-85 microg/kg dry wt), while the mid- and downstream sites on the Dongjiang River were more polluted (588-658 microg/kg dry wt). Examination of the PAH profiles revealed that the mid- and downstream sections of the Dongjiang River contained high percentages of 4,5,6-ring PAHs, similar to the amounts of atmospheric particulate matter and road dust collected during the dry weather season from the Pearl River Delta region as reported in the literature. Seasonal changes were revealed in the reservoirs of Hong Kong, with higher PAH levels in the wet weather season than in the dry weather season. For those reservoirs in Hong Kong that store water from the Dongjiang River, a distinct seasonal pattern was also observed, namely, that under dry weather season conditions the PAHs found in the sediments were primarily from petrogenic source, while under wet weather season conditions they were from pyrolytic sources. No such pattern was detected in the reservoirs which stored only rain water.     

The organic composition of diesel particulate matter, diesel fuel and engine oil of a non-road diesel generator

Diesel-powered equipment is known to emit significant quantities of fine particulate matter to the atmosphere. Numerous organic compounds can be adsorbed onto the surfaces of these inhalable particles, among which polycyclic aromatic hydrocarbons (PAHs) are considered potential occupational carcinogens. Guidelines have been established by various agencies regarding diesel emissions and various control technologies are under development. The purpose of this study is to identify, quantify and compare the organic compounds in diesel particulate matter (DPM) with the diesel fuel and engine oil used in a non-road diesel generator. Approximately 90 organic compounds were quantified (with molecular weight ranging from 120 to 350), which include alkanes, PAHs, alkylated PAHs, alkylbenzenes and alkanoic acids. The low sulfur diesel fuel contains 61% alkanes and 7.1% of PAHs. The identifiable portion of the engine oil contains mainly the alkanoic and benzoic acids. The composition of DPM suggests that they may be originated from unburned diesel fuel, engine oil evaporation and combustion generated products. Compared with diesel fuel, DPM contains fewer fractions of alkanes and more PAH compounds, with the shift toward higher molecular weight ones. The enrichment of compounds with higher molecular weight in DPM may be combustion related (pyrogenic).     

氟里昂12(CCl2F2)燃烧分解催化剂性能的研究

本文对贵金属、氧化物和复合氧化物体系催化剂上氟里昂_(12)(F_(12))燃烧分解反应进行了活性评价和稳定性研究.结果表明:TiO_2,ZrO_2/TiO_2催化剂对氟里昂_(12)燃烧分解反应具有良好的低温催化活性和较好的稳定性,ZrO_2/TiO_2催化剂具有一定的臭氧-催化氧化活性     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

广西不同地理区域森林土壤水文物理性质研究

对广西９个不同区域森林土壤（０－１００ｃｍ）水文物理性质进行测定,结果表明,不同林型的土壤容重为０．５４～１５５ｇ／ｃｍ３;总孔隙度３９％一９６．４％;最大持水量４１１．７～７５９．６ｍｍ;通气度３．２％～２７．６％;平均渗透速度０．７９～３８．５ｍｍ／ｍｉｎ。不同土类及林型的土壤容重的大小为;黄壤＜红壤和阔叶林或针阔叶混交林＜针叶林,而总孔隙度、持水量、通气度及渗透速度则相反。     

广西涠洲岛沉凝灰岩土壤粘粒矿物的研究

用X射线衍射分析和电子显微镜分析,对涠洲岛沉凝灰岩母质发育土壤的两个典型剖面八个土样的粘粒矿物进行分析研究。结果表明,离火山口距离不同的两个剖面土壤粘粒矿物组成不同,1号剖面以2:1型粘粒矿物为主,2号剖面则以1:1型粘粒矿物为主;结合其它分析结果,讨论了两个剖面土壤粘粒矿物组成不同的原因、对土壤有关特性的影响及其与土壤形成和分类的关系。     

我国现代煤化工项目废水处理的误区和建议

介绍了我国现代煤化工项目的废水来源及特性,归纳了废水的处理技术路线,从废水"零排放"、废水处理技术与管理、蒸发塘的污染转移、废水处理与固体废物处理及废气处理的关系、污染物源头控制等方面阐述了我国当前煤化工废水处理存在的误区和建议。     

用好氧-厌氧反复耦合固定床生物反应器处理肌苷生产废水

利用由多孔微生物载体构建的好氧-厌氧反复耦合固定床生物反应器进行了高浓度肌苷生产废水处理中试研究。连续84d的运行结果表明，当进水COD为1500-2700mg／L、水力停留时间为22．1h时，出水COD可维持在150mg／L左右，COD去除率达90％～95％。装置运行稳定后，未经沉淀的出水中的固体悬浮物质量浓度小于50mg／L，表明该反应器可避免剩余污泥的产生。中试结果验证了该反应器处理高浓度肌苷废水的可行性和优势，同时为装置放大提供了理论依据。