中国长江三角洲流域百菌清水生生物基准研究

通过生态毒理试验,获得百菌清对长江三角洲流域14种代表性水生生物的毒性数据。分别采用评价因子法、物种敏感度分布法和毒性百分数排序法,推导长江三角洲流域百菌清水生生物基准值。评价因子法、物种敏感度分布法和毒性百分数排序法得出的急性基准值分别是0.066μg·L~(-1)、3.00μg·L~(-1)和0.51μg·L~(-1),慢性基准值分别是0.0089μg·L~(-1)、0.40μg·L~(-1)和0.136μg·L~(-1)。比较了3种方法得出的基准值之间的差异并分析了原因,在此基础上,提出了我国长江三角洲流域百菌清水生生物基准推荐值,并与国外基准值进行了比较。研究结果可为中国农药水质标准制修订及水生生物风险评估提供科学依据。     

化工园区安全风险容量探讨

探讨并提出化工园区安全风险容量的内涵,从量化风险的角度论述区域安全风险容量;以个人风险、社会风险和潜在生命损失值作为化工园区风险容量分析的指标,并给出风险计算的模型和风险标准;对园区内企业生产规模、运输量与安全风险容量的关系进行讨论,认为企业生产规模的扩大可能不增加固定危险源的风险,但直接增加运输风险;给出了化工园区的现状及规划新建项目的安全容量的具体确定程序;以某化工园区为应用实例对安全风险容量进行分析和说明。     

重庆市无公害蔬菜基地环境和产品质量评价标准初探

通过对重庆市环境污染情况的调查分析 ,结合现行的国家相关环境质量标准和食品卫生标准 ,提出了适合重庆市无公害蔬菜基地建设的环境质量和产品质量评价标准体系 ,为建立规范化、标准化绿色蔬菜基地打下了基础     

Metals in biomass

Background, Aim and Scope

Metal ions generally share the ability/tendency of interacting with biological material by forming complexes, except possibly for the heavy alkali metals K, Rb and Cs. This is unrelated to the metals being either essential for sustaining life and its reproduction, apparently insignificant for biology, although perhaps undergoing bioconcentration or even being outright toxic, even at low admission levels. Yet, those different kinds of metal-biomass interactions should in some way depend on properties describing coordination chemistries of these very metals. Nevertheless, both ubiquitously essential metals and others sometimes used in biology should share these properties in numeric terms, since it can be anticipated that they will be distinguished from nonessential and/or toxic ones. These features noted above include bioconcentration, the involvement of metal ions such as Zn, Mg, Cu, Fe, etc. in biocatalysis as crucial components of metalloenzymes and the introduction of a certain set of essential metals common to (almost) all living beings (K, Mg, Mo, Mn, Fe, Cu and Zn), which occurred probably very early in biological evolution by ‘natural selection of the chemical elements’ (more exactly speaking, of the metallomes).

Materials and Methods

The approach is semiempirical and consists of three consecutive steps: 1) derivation of a regression equation which links complex stability data of different complexes containing the same metal ion to electrochemical data pertinent to the (replaced) ligands, thus describing properties of metal ions in complexes, 2) a graphical representation of the properties-two typical numbers c and x for each metal ion-in some map across the c/x-space, which additionally contains information about biological functions of these metal ions, i.e. whether they are essential in general (e.g. Mg, Mn, Zn) or, for a few organisms of various kinds (e.g. Cd, V), not essential (e.g. rare earth element ions) or even generally highly toxic (Hg, U). It is hypothesized that, if coordination properties of metals control their biological ‘feasibility’ in some way, this should show up in the mappings (one each for mono and bidentate-bonding ligands). 3) eventually, the regression equation produced in step 1) is inverted to calculate complex stabilities pertinent to biological systems: 3a) complex stabilities are mapped for ligands delivered to soil (-water) by green plants (e.g. citrate, malate) and fungi and, compared to their unlike selectivities and demands of metal use (photosynthesis taking place or not), 3b) the evolution of the metallome during late chemical evolution is reconstructed.

Results

These maps show some ‘window of essentiality’, a small, contrived range/area of c and x parameters in which essential metal ions gather almost exclusively. c and x thus control the possibility of a metal ion becoming essential by their influencing details of metal-substrate or (in cases of catalytic activities) metal-product interactions. Exceptions are not known to be involved in biocatalysis anyhow.

Discussion

Effects of ligands secreted, e.g. from tree roots or agaric mycelia to the soil on the respective modes (selectivities) of metal bioconcentration can be calculated by the equation giving complex stability constants, with obvious ramifications for a thorough, systematic interpretation of biomonitoring data. Eventually, alterations of C, N and P-compounds during chemical evolution are investigated — which converted CH₄ or CO₂, N₂ and other non-ligands to amino acids, etc., for example, with the latter behaving as efficient chelating ligands: Did they cause metal ions to accumulate in what was going to become biological matter and was there a selectivity, a positive bias in favour of nowessential metals (see above) in this process? Though there was no complete selectivity of this kind, neither a RNA world in which early ribozymes effected most of biocatalysis, nor a paleoatmosphere containing substantial amounts of CO could have paved the way to the present biochemistry and metallomes.

Conclusions

This way of reasoning provides a causal account for abundance distributions described earlier in the Biological System of Elements (BSE; Markert 1994, Fränzle &; Markert 2000, 2002). There is a pronounced change from chemical evolution, where but few transformations depended on metal ion catalysis to biology.

Recommendations and Perspectives

The application of this numerical approach can be used for modified, weighted evaluation of biomonitoring analytical data, likewise for the prediction of bioconcentration hazards due to a manifold of metal ions, including organometallic ones. This is relevant in ecotoxicology and biomonitoring. In combining apoproteins or peptides synthesized from scratch for purposes of catalysing certain transformations, the map and numerical approaches might prove useful for the selection of central ions which are even more efficient than the ‘natural’ ones, like for Co²⁺ in many Zn enzymes.

     

天津滨海新区黑潴河下游沉积物多环芳烃风险评价及环境基准值的比较

对黑潴河下游表层沉积物中16种多环芳烃(PAHs)的污染现状进行了调查研究。结果表明,表层沉积物中PAHs总量变化范围为41.2～129.3ng/g(平均值为83.7ng/g),PAHs的组成以5～6环PAHs组分为主。黑潴河下游沉积物中PAHs主要来源于周边地区化石燃料的高温燃烧。比较了基于不同方法建立的沉积物中PAHs环境基准值的差异,分析产生差异的原因,选择生态效应区间法对黑潴河沉积物中的PAHs进行了生态风险评价。黑潴河下游PAHs生态风险较小,属PAHs低生态风险河道。     

Derivation of predicted no effect concentrations (PNEC) for 2,4,6-trichlorophenol based on Chinese resident species

2,4,6-Trichlorophenol (2,4,6-TCP) is a common chemical intermediate and a by-product of water chlorination and combustion processes, and is a priority pollutant of the aquatic environment in many countries. Although information on the toxicity of 2,4,6-TCP is available, there is a lack of information on the predicted no-effect concentration (PNEC) of 2,4,6-TCP, mainly due to the shortage of chronic and site-specific toxicity data. In the present study, acute and sub-chronic toxicity of 2,4,6-TCP on six different resident Chinese aquatic species were determined. PNEC values were calculated and compared by use of two approaches: assessment factor (AF) and species sensitivity distribution (SSD). Values for acute toxicity ranged from 1.1 mg L⁻¹ (Plagiognathops microlepis) to 42 mg L⁻¹ (Corbicula fluminea) and the sub-chronic no observed effect concentrations (NOECs) ranged from 0.05 mg L⁻¹ (Mylopharyngodon piceus) to 2.0 mg L⁻¹ (C. fluminea). PNECs obtained by the assessment factor approach with acute (AF = 1000, 0.001 mg L⁻¹) or chronic (AF = 10, 0.005 mg L⁻¹) toxicity data were one order of magnitude less than those from SSD methods (0.057 mg L⁻¹). PNEC values calculated using SSD methods with a 50% certainty for 2,4,6-TCP was less than those obtained by use of the USEPA recommend final chronic value (FCV) method (0.097 mg L⁻¹) and the one obtained by use of the USEPA recommend acute-to-chronic (ACR) methods (0.073 mg L⁻¹). PNECs derived using AF methods were more protective and conservative than that derived using SSD methods.     

An analytic network process approach for locating undesirable facilities: an example from Istanbul, Turkey

Locating an undesirable facility is a sophisticated problem, for the evaluation procedures involve several objectives and the solution to the problem calls for some compromises to be made between probable conflicting criteria. This paper addresses the problem of undesirable facility location selection using the analytic network process (ANP), a multi-criteria decision-making technique. The ANP technique enables us to consider both qualitative and quantitative criteria as well as the interdependencies and feedbacks. A number of criteria (benefits, opportunities, costs and risks) and their sub-criteria are considered for siting a new facility with which this study has dealt. The questions of what criteria would be considered and what the interdependencies between these criteria and their weights would be were discussed and determined via interviews with some competent authorities of the Istanbul Municipality and of two environmental organizations. Four representative locations were evaluated and the most convenient one was selected. This was followed by the sensitivity analyses of the results.     

Land Use,Geology, Enrichment,and Stream Biota in the Eastern Ridge and Valley Ecoregion: Implications for Nutrient Criteria Development1

Abstract: The eastern panhandle region of West Virginia is entirely within the Appalachian Ridge and Valley ecoregion. It is underlain by limestone in the eastern part and by shale and sandstone in the western part. Agricultural and urban development has affected the condition of the streams of this region. We examined samples from 165 stations in the Ridge and Valley, collected from 1998 to 2004. Land use, geological characteristics, physical and chemical parameters, and algal and macroinvertebrate assemblages were used to identify potential stressors that affect streams in the region. Our analyses indicated that both human land uses and ecoregional differences led to elevated nutrient concentrations in streams of the study areas. Multiple regression analyses indicated that both agricultural and urban land use in the watershed were associated with high nutrient concentrations (NO₂₊₃, total nitrogen, and total phosphorus) in streams. These elevated nutrient concentrations have led to increased algal biomass, increased trophic state, and degradation of macroinvertebrate community in the streams. Values of the West Virginia Stream Condition Index, as well as several other benthic macroinvertebrate metrics, decreased with increased nutrient concentrations and conductivity, especially in the limestone region. When regional differences were partitioned out in the analysis, nutrient concentrations became the strongest stressor in the limestone region while conductivity exhibited less of an effect on macroinvertebrate metrics. Meanwhile, periphyton diagnostic metrics also responded to increased nutrient concentrations, suggesting nutrients could be a cause of biological degradation in the Eastern Ridge and Valley region. Multiple approaches and multiple lines of evidence (reference approach and stressor‐response approach) were applied to develop nutrient benchmarks for different geological regions in the study watershed.