Toxicity assessing for chlorpyrifos-contaminated soil with three different earthworm test methods

Earthworm toxicity tests are useful tools for terrestrial risk assessment but require a hierarchy of test designs that differ in effect levels (behavior, sublethal, lethal). In this study, the toxicity of chlorpyrifos contaminated soil on earthworms was assessed. In addition to the acute and chronic tests, an avoidance response test was applied. Earthworms were exposed to sublethal and lethal concentration of chlorpyrifos, and evaluated for acute toxicity, growth, fecundity and avoidance response after a certain exposure period. The test methods covered all important ecological relevant endpoints (acute, chronic, behavioral). Concentration of 78.91 mg/kg, chlorpyrifos caused significant toxic effects in all test methods, but at lower test concentrations, only significant chronic toxic effects could be observed. In the present study, chlorpyrifos had adverse effect on growth and fecundity in earthworm exposed to 5 mg/kg chlorpyrifos after eight weeks. The avoidance response test, however, showed significant repellent effects concentration of 40 mg/kg chlorpyrifos. For chlorpyrifos, concentration affecting avoidance response was far greater than growth and fecundity, it seemed likely that earthworms were not able to escape from pesticide-contaminated soil into the clean soil in field and hence were exposed continuously to elevated concentrations of pesticides.     

丹江口水库表层沉积物不同形态氮的赋存特征及其生物有效性

为了揭示丹江口水库沉积物氮空间分布特征及其生物有效性,采用连续分级提取法研究了表层沉积物中可交换态氮(Exchangeable nitrogen,EN)、酸解态氮(Acid hydrolysable nitrogen,HN)及残渣态氮(Residue nitrogen,RN)的赋存特征,同时结合生物可利用态氮的含量,探讨了各形态氮对生物可利用态氮的贡献。结果表明,丹江口水库沉积物中总氮(Total nitrogen,TN)在425~5796 mg/kg之间,平均为1 319.32 mg/kg,其中EN、HN和RN的平均值相对比例为2.15∶1.95∶1,且各形态氮含量的空间分布呈入库河流大于库区开阔区域的特征,尤其在丹江、老灌河以及犟河-堵河入库口的含量较大。潜在矿化氮(Potential mineralized nitrogen,PMN)含量在40.20~1 468.95 mg/kg之间,平均为275.06 mg/kg,其中EN对丹江口水库沉积物PMN的贡献较大,比例在19.85%~90.80%之间,平均为63.47%。各形态氮在不同的水环境条件下发生迁移转化,保持着水-沉积物界面氮的动态平衡。     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

Monitoring Environmental Impact in the Upper Sonoran Lifestyle: A New Tool for Rapid Ecological Assessment

Characterized by expensive housing, high socioeconomic status, and topographic relief, Upper Sonoran Lifestyle communities are found primarily along the Wildland-Urban Interface (WUI) in the Phoenix, Arizona metro area. Communities like these sprawl into the wildlands in the United States Southwest, creating a distinct urban fringe. This article, through locational comparison, introduces and evaluates a new field assessment tool for monitoring anthropogenic impact on soil–vegetation interactions along the well-maintained multi-use recreational trails in Upper Sonoran Lifestyle region. Comparing data from randomly selected transects along other multi-use trails with data from a control site revealed three key indicators of anthropogenic disturbances on soil–vegetation interactions: soil disturbance, vegetation disturbance, and vegetation density. Soil and vegetation disturbance displayed an average distance decay exponent factor of −0.60, while vegetation density displayed a reverse decay average of 0.60. Other important indicators of disturbance included vegetation type, biological soil crusts, and soil bulk density. The predictive ability of this new field tool enhances its applicability, offering a powerful rapid ecological assessment method for monitoring long-term anthropogenic impact in the Upper Sonoran Lifestyle, and other sprawling cities along the WUI.     

可靠性技术的发展与应用

本文介绍了可靠性标准体系与参数体系,可靠性的分析与设计方法,可靠性试验的发展趋势,指出可靠性管理是产品可靠性工作的核心,以及提高电子设备可靠性的发展策略。     

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds1

Abstract: Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient‐reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight‐digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.     

金竹山土朱煤矿开采地表沉降规律与灰色预测模型研究

针对金竹山矿业公司土朱煤矿煤层赋存条件,依据采动理论的裂缝垂直分带模型,分析地表沉降和塌陷的机理;提出在采煤活动阶段应进行地表实际位移观测,经数据处理后得到地面沉降曲线,以确保地面人类活动的安全;在采煤活动后阶段则实施灰色预测地面沉降,即通过采煤活动阶段的地表实际观测数据为历史原始数据序列,建立灰色Logistic模型;并对采煤活动后阶段的地面沉降进行预测。精度检验表明:灰色Logistic模型预测精度高,利用该模型预测地面沉降可减少地面沉降监测经费和实时提供预警信息,以确保开采区域内人们生命财产安全。     

Climate dynamics and extreme precipitation and flood events in Central Europe

Past changes and possible future variations in the nature of extreme precipitation and flood events in Central Europe and the Alpine region are examined from a physical standpoint. An overview is given of the following key contributory physical processes: (1) the variability of the large-scale atmospheric flow and the associated changes of the North-Atlantic storm track; (2) the feedback process between climate warming and the water cycle, and in particular the potential for more frequent heavy precipitation events; and (3) the catchment-scale hydrological processes associated with variations in major river flooding events and that are related to land-use changes, river training measures, and shifts in the proportion of rain to snowfall. In this context an account is provided of the possible future forecasting and warning methodologies based upon high-resolution weather prediction and runoff models. Also consideration is given to the detectability of past (future) changes in observed (modeled) extreme events. It is shown that their rarity and natural fluctuation largely impedes a detection of systematic variations. These effects restrict trend analysis of such events to return periods of below a few months. An illustration using daily precipitation from the Swiss Alps does yield evidence for pronounced trends of intense precipitation events (return period 30 days), while trends of stronger event classes are not detectable (but nevertheless can not be excluded). The small detection probability for extreme events limits possible mitigation of future damage costs through an abatement of climate change alone, and points to the desirability of developing improved early forecasting/warning systems as an additional no-regret strategy. This revised version was published online in July 2006 with corrections to the Cover Date.     

水安全及城市水安全研究进展与趋势

归纳和总结国内外水安全及城市水安全相关研究实践及其所用的评价指标体系,并对几种常用模型与方法的应用情况及其各自的特点进行分析,针对目前水安全及城市水安全研究中存在的主要问题,指出水安全及城市水安全进一步研究的方向:从自然、生态环境、社会经济、人文4个基本方向,以系统性、持续性、动态性和层次性4个特征为基础,分析水安全及城市水安全的概念与内涵;根据研究区域特征及其主要水安全问题建立评价指标体系;以研究者对各个模型的理解程度及驾驭能力为准则选用或改造现有模型与方法;针对加强城市应急水源地建设、突发性水安全事件应急预案、湿润地区水安全等问题开展研究。     

企业安全文化评估与企业安全行为的质化研究

通过总结国内外各种不同的安全文化概念,归纳分析了国内外较为流行的近10种安全文化建立模式。在研讨文献的基础上,通过深入访谈、焦点小组与参与观察,归纳构造了一套共11个维度,总题项为152题的安全文化评估量表。通过对选定企业的实证问卷调查,进行统计分析,采用多元逐步回归分析等方法对安全文化各评核因素及整体安全文化进行预测,并以百分数呈现其整体的安全文化现状水平。通过基于扎根理论的各种质化研究方法,对案例企业的安全文化建设和企业安全行为进行研究,得到了7点关于企业安全行为的研究发现,并提出了相应的改进建议。