一个从酸化和金属污染中恢复的湖泊历史悠久的水蚤属(Daphnia)群落的重现

通过综合采用古湖泊学技术和分子遗传技术重现汉纳(Hannah)湖--个从工业酸化、金属污染及动物灭绝中恢复的湖泊--中水蚤属(Daphnia)群落组成的长期型式.像许多浮游动物一样,水蚤属可以产出能生存几十年,甚至一百年以上的滞育卵.然而,过去20年D.mendotae在汉纳湖中的出现可能是从其他附近湖泊扩散的结果,而不是从沉积物卵库移居而来的.我们利用聚合酶连锁反应(PCR),单股构象多形现象(SSCP)以及排序进行的成因测试结果表明,D.mendotae滞育卵在过去250年沉积物记录中没有发现,在该地区金属冶炼作业之前,该生物群落由D.pulicaria控制.在湖泊化学复原之后这一物种的变化与早期湖泊酸性的历史变化一致.在汉纳湖的整个远古历史中,环境波动可能决定了群落组成.将这一分子一古湖泊学方法扩展到其他湖泊应该有助于更准确地阐述生物复原过程.     

对加拿大东南部湖泊从酸沉降效应中恢复的评价

北美洲SO2排放量的减少激起了人们对加拿大东南部的水生态系统能迅速摆脱酸化的状态的期待.但是只有那些明显减少了排放量的冶炼厂附近的湖泊达到了这种期望值.在临近大西洋的省份魁北克和安大略,受远程污染源影响的湖泊的硫酸根离子(SO2- 4)浓度都有一定降低,但pH和碱度则仅有较少量的提高.对于这种延迟的酸度响应,有如下几种因素可以解释:碱基阳离子含量的下降,干旱加速SO2- 4的迁移,水体内部碱性物质生成机制遭到破坏;同时硝酸盐和有机阴离子含量的提高也可能是其中的原因.对加拿大东南部生物恢复的监测资料非常有限,即使有的话,在萨德伯里(Sudbury)和基拉尼(Killarney)地区以外也很难找到恢复的证据.比如,尽管除了酸化作用外其他因素也对上述现象有一定影响,新思科舍河中的大西洋鲑鱼出现率和安大略湖潜鸟的繁殖成功率实际上正在下降.化学和生物学模型预测,只有比目前法规要求严格的多的SO2排放削减额才能促进广泛的化学恢复和其后的生物恢复,而在加拿大东南部的众多湖泊中重建工业化前的化学与生物学条件或许很难实现.     

Binary logistic regression—Instrument for assessing museum indoor air impact on exhibits

This paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The prediction of the impact on the exhibits during certain pollution scenarios (environmental impact) was calculated by a mathematical model based on the binary logistic regression; it allows the identification of those environmental parameters from a multitude of possible parameters with a significant impact on exhibitions and ranks them according to their severity effect. Air quality (NO₂, SO₂, O₃ and PM_2.5) and microclimate parameters (temperature, humidity) monitoring data from a case study conducted within exhibition and storage spaces of the Romanian National Aviation Museum Bucharest have been used for developing and validating the binary logistic regression method and the mathematical model. The logistic regression analysis was used on 794 data combinations (715 to develop of the model and 79 to validate it) by a Statistical Package for Social Sciences (SPSS 20.0). The results from the binary logistic regression analysis demonstrated that from six parameters taken into consideration, four of them present a significant effect upon exhibits in the following order: O₃>PM_2.5>NO₂>humidity followed at a significant distance by the effects of SO₂ and temperature. The mathematical model, developed in this study, correctly predicted 95.1 % of the cumulated effect of the environmental parameters upon the exhibits. Moreover, this model could also be used in the decisional process regarding the preventive preservation measures that should be implemented within the exhibition space.

Implications: The paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The mathematical model developed on the environmental parameters analyzed by the binary logistic regression method could be useful in a decision-making process establishing the best measures for pollution reduction and preventive preservation of exhibits.     

Assessment of dermal exposure to benzene and toluene in shoe manufacturing by activated carbon cloth patches

OBJECTIVES: The aim of this investigation was to use activated carbon cloth (ACC) patches to study the probability and extent of dermal exposure to benzene and toluene in a shoe factory. METHODS: Inhalation and dermal exposure loading were measured simultaneously in 70 subjects on multiple days resulting in 113 observations. Dermal exposure loading was assessed by ACC patches attached to likely exposed skin areas (e.g. the palm of the hand and abdomen). A control patch at the chest and an organic vapor monitor (OVM) were used to adjust the hand and abdomen patches for the contribution from the air through passive absorption of benzene and toluene on the ACC patches. Systemic exposure was assessed by quantification of unmetabolized benzene (UBz) and toluene (UTol) in urine. RESULTS: Mean air concentrations for the study population were 1.5 and 7.5 ppm for benzene and toluene, respectively. Iterative regression analyses between the control patch, OVM and the dermal patches showed that only a small proportion of the ACC patches at the hand had likely benzene (n = 4; mean 133 microg cm(-2) h(-1)) or toluene (n = 5; mean 256 microg cm(-2) h(-1)) contamination. Positive patches were exclusively observed among subjects performing the task of gluing. Significant dermal exposure loading to the abdomen was detected only for toluene (n = 2; mean 235 microg cm(-2) h(-1)). No relation was found between having a positive hand or abdomen ACC patch and UBz or UTol levels. In contrast a strong association was found between air levels of benzene (p = 0.0016) and toluene (p < 0.0001) and their respective urinary levels. CONCLUSIONS: ACC patches are shown to be a useful technique for quantifying the probability of dermal exposure to organic solvents and to provide estimates of the potential contribution of the dermal pathway to systemic exposure. Using ACC patches we show that dermal exposure to benzene and toluene in a shoe manufacturing factory is probably rare, and when it occurred exposures were relatively low and did not significantly contribute to systemic exposure.     

Using Wildlife as Receptor Species: A Landscape Approach to Ecological Risk Assessment

To assist risk assessors at the Department of Energy’s Savannah River Site (SRS), a Geographic Information System (GIS) application was developed to provide relevant information about specific receptor species of resident wildlife that can be used for ecological risk assessment. Information was obtained from an extensive literature review of publications and reports on vertebrate- and contaminant-related research since 1954 and linked to a GIS. Although this GIS is a useful tool for risk assessors because the data quality is high, it does not describe the species’ site-wide spatial distribution or life history, which may be crucial when developing a risk assessment. Specific receptor species on the SRS were modeled to provide an estimate of an overall distribution (probability of being in an area). Each model is a stand-alone tool consisting of algorithms independent of the GIS data layers to which it is applied and therefore is dynamic and will respond to changes such as habitat disturbances and natural succession. This paper describes this modeling process and demonstrates how these resource selection models can then be used to produce spatially explicit exposure estimates. This approach is a template for other large federal facilities to establish a framework for site-specific risk assessments that use wildlife species as endpoints.Current address: Biology Department, University of South Dakota, Vermillion, SD 57069