室内空气和灰尘中全(多)氟烷基化合物的研究进展

全(多)氟烷基化合物(per(poly)fluoroalkyl substances,PFASs)在环境各个介质及人体样品中广泛被检出,近年,在室内空气和灰尘中也普遍发现PFASs.研究表明,室内空气中PFASs的含量普遍高于室外空气,室内空气和灰尘中的PFASs可能是室外空气的污染来源及人体暴露源,因此室内环境中PFASs成为环境领域的又一个研究热点.但目前为止,我国还没有开展室内空气中PFASs的相关研究,室内灰尘中PFASs的研究也相对较少.本文就室内空气和灰尘中PFASs的采样与分析方法、污染现状、来源分析及人体暴露等4个方面进行了综合阐述,以期为我国室内环境中PFASs的研究提供参考.     

Effects of Coastal Lighting on Foraging Behaviorof Beach Mice

Abstract:  Introduction of artificial light into wildlife habitat represents a rapidly expanding form of human encroachment, particularly in coastal systems. Light pollution alters the behavior of sea turtles during nesting; therefore, long-wavelength lights—low-pressure sodium vapor and bug lights—that minimize impacts on turtles are required for beach lighting in Florida (U.S.A.). We investigated the effects of these two kinds of lights on the foraging behavior of Santa Rosa beach mice (  Peromyscus polionotus leucocephalus ). We compared patch use and giving-up densities of mice for experimental food patches established along a gradient of artificial light in the field. Mice exploited fewer food patches near both types of artificial light than in areas with little light and harvested fewer seeds within patches near bug lights. Our results show that artificial light affects the behavior of terrestrial species in coastal areas and that light pollution deserves greater consideration in conservation planning.     

Stability of a Coal Waste Artificial Reef

The feasibility of using U.K. coal-fired power station waste materials for artificial reef production is being examined. in June, 1989, an experimental artificial reef was constructed in Poole Bay, off the central south coast of the U.K., using three different mixtures of pulverised fuel ash (PFA), flue gas desulphurisation (FGD) gypsum and slurry, stabilized with cement and formed into blocks. Fifty tonnes of 40 × 20 × 20 cm blocks were formed into eight conical reef units replicating three different PFA/gypsum mixtures and one concrete control. the reef structure is 10m below chart datum on a flat sandy sea-bed.

Combustion of coal concentrates the heavy metal content in the resultant ash. the purpose of stabilization of the ash as blocks is twofold: to immobilize heavy metals (or other components) and to provide hard substratum for the attachment of organisms. to examine the effectiveness of this stabilization and hence the environmental compatibility of the block materials, heavy metal (Cd, Cr, Cu, Pb, Mn, Ni, Zn) content of the blocks has been monitored routinely over two years, to determine leaching rates. Sectional profiles indicate partial replacement of calcium content by magnesium. Associated with this there has also been some redistribution of heavy metals. Only in the case of cadmium has there been a detectable loss from the surface of blocks. Chromium and manganese concentrations appear to have increased. the metal content of the reef epibiota (including ascidians, Ascidia mentula; hydroids, Halecium spp.; bryozoans, Bugula spp. and red algae) growing on the ash blocks has been compared to that of epibiota attached to the concrete controls and surrounding sea-bed. to date no evidence of excess bioaccumulation of metals has been detected.

The physical integrity of the ash reef blocks has been maintained. There is evidence that the blocks are increasing in compressive strength.

An indication of the fishery enhancement potential of the experimental structure is given by the presence of eight commercially fished species (crustaceans and molluscs) including lobsters (Homarus gammarus).     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。     

人工智能技术对长江流域水污染治理的思考

随着经济的快速发展和城市化进程的不断加速,促使水污染严重的长江流域需从污染物去除过程的建模与优化、污水处理过程的优化控制、水污染监测系统的构建开展水污染治理研究.传统的水污染处理技术存在污染物去除效率预测精度较低、污水优化控制成本较高、水污染监测滞后效应严重的问题.人工智能技术能够有效克服上述问题,因此通过梳理国内外学者利用人工智能技术在污水污染物去除过程的建模与优化、污水处理过程的优化控制及水污染监测系统的构建等方面的研究成果,为全面加强长江流域水污染治理能力提供科学可靠的技术指导.结果表明:①利用人工神经网络技术（径向基神经网络、多层前馈网络-人工神经网络、多层感知器神经网络）对污水污染物去除过程进行建模与优化,为精确预测长江流域重金属（Cr、Cu）、营养盐（TN、TP）、持久性有机污染物〔PBDEs（多溴二苯醚）、HCH（六氯环己烷）〕的去除率提供重要参考价值.②采用污水处理的自动控制技术与人工智能技术（递归神经网络、支持向量机、模糊神经网络等）构建污水智能控制系统,为长江流域实现高效节能的污水优化控制提供重要的技术指导.③利用在线监测仪器和人工智能技术（小波神经网络、多元线性回归-人工神经网络、叠层去噪自动编码器等）建立水污染智能监测系统,为解决长江流域水污染监测响应滞后问题提供有力的技术支持.因此,人工智能技术对长江流域提高污水污染物去除率,降低污水优化控制成本,提升水污染监测时效性具有重要的推广价值.      

基于神经网络的东北地区秸秆焚烧预测

选取农作物秸秆露天燃烧严重的东北地区,采用人工神经网络的方法,结合卫星火点和气象数据,开展秸秆露天燃烧预测研究.结果表明：人工神经网络预测模型成功验证了松嫩平原地区2015年10月25日~11月15日的秸秆露天燃烧情况,其准确度为67.1%,经过多次试验,在神经网络建模与验证数据配比为80：20时,预测准确度最高,可达69.7%,同时该模型的稳定性较好.而对不同区域,不同时间段的预测研究表明,人工神经网络较适用于长时间序列的预测.就影响因素而言,相对湿度是影响秸秆露天燃烧的最重要因素.本研究结果可为空气质量模式提供火点预测数据,提高其预报预警能力,为区域联防联控政策的制定提供科技支持.     

Formulation and Validation of an Empirical Moisture Damage Index

An empirical moisture damage index was developed in order to reduce the subjectivity of the estimation of moisture damage in domestic residences, in relation to occupant health. The database was generated using information gathered from a sample of 164 houses that were examined by civil engineers, and questionnaire data collected from the occupants. The index was formulated to associate with the occupant reported respiratory symptoms by calculating weighted estimates of selected moisture damage attributes using 80% of the sample. The remaining 20% of the sample was used to verify the final index. The index associated strongly with the health symptoms of interest. This index is a tool that may be used as an indicator of moisture damage induced exposure in domestic residences.     

对室内装饰装修材料检测中甲醛分析方法的研究

目前室内装饰装修材料中甲醛含量的检测有六个类别,分析方法不统一,且没有一定的质量控制措施.文章对分析方法进行了改进,并且研究用水中的甲醛标样来对检测过程进行质量控制,结果较好.     

Macroinvertebrate Regionalisation for use in the Management of Aquatic Ecosystems in Victoria, Australia

The development of a broader, more holistic approach to aquaticecosystem management has been called for in recent years. Physical and chemical objectives alone are no longer consideredsufficient for the protection of aquatic ecosystems and shouldbe supplemented with biological objectives. The ubiquitousand sedentary nature of macroinvertebrates, combined with theirmeasurable response to environmental conditions, favour their use as important indicators in environmental policies. To establish biological objectives, there is a need for a regionalframework to limit the variability between ecosystems. Past studies have demonstrated that an a posteriori regionalisationapproach may be more useful than an a priori approach in explaining single component (e.g. macroinvertebrates) patternsacross ecosystems. This is particularly important as aquaticresource management agencies often focus on one or twocomponents of the ecosystem to assess environmental health. This study uses an a posteriori method to delineate and describebiological regions based on edge and riffle macroinvertebrate data. The regionalisation will provide a framework for settingbiological objectives, based on the range of reference conditionsmeasured within each separate region. The objectives will includeregional checklists for taxa and biotic indices. Predictive modelling in the style of RIVPACS or AUSRIVAS will also be usedwithin each region to develop objectives, incorporating local, regional and systematic features as predictor variables.     

Derivation of Nutrient Guidelines for Streams in Victoria, Australia

Human induced increases to nutrientconcentrations in streams have led to many agenciesdeveloping strategies and criteria for nutrientreduction. National or statewide guidelines aregenerally inappropriate, due to the natural variabilityin stream ecosystems within political boundaries. Thisstudy used an extant aquatic macroinvertebrate-basedregionalisation for the state of Victoria, Australia, asthe basis for defining regions of relatively homogeneousenvironmental character. This enabled the selection ofecologically-based regional reference sites andsubsequent characterisation of the nutrient status ofthese sites. Using an extensive biological and nutrientdata base for streams across the State, we calculated50th and 75th percentile concentrations forreference sites within each region. Using thesepercentiles in conjunction with impact and recoverystudies, we defined nutrient guidelines for each region. Although the nutrient data largely supported thebiological regionalisation, patterns in the nutrient datadid require some minor modifications for the nutrientregions. Relatively unimpacted regions with referencesites in very good-to excellent-condition were assignedguidelines largely based on the 75th percentiles. The more impacted regions, where best availablereference sites were of poorer quality, were assignedguidelines based largely on the 50th percentiles. Professional judgement and known extents of impactsacross each region provided important contributions tothe decision-making process. The derived guidelineconcentrations are comparable to several cited in theliterature and are proposed for use in monitoring,assessment and restoration targets.