北京市城市河流中抗生素的污染特征及多层次生态风险评估

为评估北京市河流中抗生素的污染特征和生态风险,利用固相萃取结合高效液相色谱串联质谱检测了4类共35种常见抗生素的浓度水平,并利用风险商法（RQ）和联合概率曲线法（JPCs）评估了抗生素的生态风险.结果表明,北京市10条河流地表水中共检测出33种抗生素,总浓度范围是N.D.~1573.57 ng·L^-1,磺胺甲噁唑的浓度最高（N.D.~160.04 ng·L^-1）,其次为磺胺嘧啶（0.09~147.90 ng·L^-1）和氧氟沙星（0.28~94.72 ng·L^-1）,其中检出率 > 50.0 %的抗生素有16种;RQ法显示有12种抗生素存在生态风险,四环素、克拉霉素和甲氧苄氨嘧啶的风险最高,其风险商分别为3.99、1.86和1.01,污水处理厂出口的风险高于其所在河流干流的风险.四环素、克拉霉素和甲氧苄氨嘧啶的预测无效应浓度超标率均为2.3 %,基于JPCs发现,克拉霉素的最大风险乘积为1.66 %,对0.3 %~7.0 %的物种具有低等风险,其余抗生素的风险可忽略.抗生素的检出率、浓度分布、最敏感物种和物种敏感性分布对生态风险评估具有重要影响,采用多层次生态风险评估法能有效避免保护不足和过保护现象,有助于在全区域范围内对抗生素进行分级和分区管理.     

正态信息扩散法在确定河冰抗压强度概率分布中的应用

将正态信息扩散法应用于小样本条件下河冰抗压强度概率密度函数的确定,建立了小样本条件下河冰抗压强度概率分布,并结合K-S检验法和河冰抗压强度试验数据,分析了该方法的合理性。结果表明,本文方法可以较好解决小样本情况下河冰抗压强度概率分布的确定问题,正态信息扩散分布更加接近河冰抗压强度的真实分布,并优于经典分布的拟合方法。     

Modeling Summer Month Hydrological Drought Probabilities in the United States Using Antecedent Flow Conditions

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5‐11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best‐performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid‐Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.     

道路交通噪声变化的马尔柯夫过程定量预测

介绍了马尔柯夫过程的理论及方法,并将其预测模型和稳定状态方程应用于道路交通噪声变化的定量预测上,其预测结果与研究市区道路交通噪声变化的实际情况相一致,表明用马尔柯夫过程定量预测道路交通噪声变化是可行的。      

天然气管道不同孔径泄漏失效概率量化方法研究*

为研究不同孔径泄漏下天然气管道失效概率,首先基于EGIG数据库和UKOPA数据库天然气管道历史失效数据,计算由不同失效原因导致3种孔径泄漏所占比例;然后将我国管道各原因基础失效概率按照对应比例分别进行修正,获得较适用于我国天然气管道特点的不同孔径泄漏基础失效概率;最后分别考虑第三方破坏、腐蚀、施工缺陷/材料失效、误操作、自然力破坏5种失效原因,完成对天然气管道不同孔径泄漏基础失效概率的修正计算。研究结果表明:小孔泄漏、中孔泄漏和破裂泄漏的基础失效概率分别为0.173,0.128,0.048次/（103 km·a）;修正因子包括管径、埋深、壁厚、管龄、防腐层类型、管道所处区域,上述因子能够满足不同场景下天然气管道失效概率的修正计算;概率量化方法综合考虑失效原因、泄漏孔径以及管道本体信息,能够定量化预测天然气管道失效概率,为天然气管道定量风险评价提供数据支撑。     

上海地区洪涝致灾因子复合概率及未来变化分析

根据上海地区三阶段(1970-2004年,2020-2054年和2060-2094年)四要素(降水、吴淞口风速、太湖流域面雨量、吴淞口潮位)提取年极值时间序列,采用GEV分布首先开展"雨洪风潮"各致灾因子气候变化分析,结果显示:"雨洪风潮"各致灾因子年极值受气候变化影响均呈增加趋势;进而基于Copula联合函数中的三维...     

基于元胞自动机的城市区域火蔓延概率模型探讨

考虑建筑结构物震后可能发生的次生火灾的不确定性,给出解决问题的基本思路,构建了基于元胞自动机的城市地震次生火灾蔓延概率模型,指出元胞着火的概率与建筑物的特性和灾害条件有关,包括建筑材料、外墙是否有开口、与着火元胞的距离、地震对建筑的破坏程度以及气象条件等因素。模型通过设置没有开口的外墙以及道路和空地来区分单体建筑和建筑之间的火蔓延。该模型量化了影响火蔓延概率的因素,能快速实现城市区域火蔓延过程的动态模拟,特别适宜用于城市宏观角度上的火蔓延模拟。模拟结果再现了火灾过程,这不仅提高了人们对城市区域火蔓延危害的认识,而且为城市规划设计和消防扑救措施提供了有益的理论依据。     

沿海和河口城市防灾设防标准系统分析

本文针对天津、上海、青岛等三种不同类型的沿海、河口城市,运用灰色理论、随机模拟等方法进行了洪水、风暴湖、巨浪等环境因素的计算,并进行了灾害经济损失的风险分析,给出了不同的防灾设防标准。     

Prediction of potential areas of species distributions based on presence-only data

We introduce a methodology to infer zones of high potential for the habitat of a species, useful for management of biodiversity, conservation, biogeography, ecology, or sustainable use. Inference is based on a set of sites where the presence of the species has been reported. Each site is associated with covariate values, measured on discrete scales. We compute the predictive probability that the species is present at each node of a regular grid. Possible spatial bias for sites of presence is accounted for. Since the resulting posterior distribution does not have a closed form, a Markov chain Monte Carlo (MCMC) algorithm is implemented. However, we also describe an approximation to the posterior distribution, which avoids MCMC. Relevant features of the approach are that specific notions of data acquisition such as sampling intensity and detectability are accounted for, and that available a priori information regarding areas of distribution of the species is incorporated in a clear-cut way. These concepts, arising in the presence-only context, are not addressed in alternative methods. We also consider an uncertainty map, which measures the variability for the predictive probability at each node on the grid. A simulation study is carried out to test and compare our approach with other standard methods. Two case studies are also presented.     

基于人的认知可靠性(HCR)模型的人因操作失误研究

以人的认知可靠性(HCR)模型为指导,选择包含技能型、规则型和知识型3种认知类型,结合大连化工集团公司影响运行安全的17个异常事件,对54名操纵员的时间响应状况和允许操作时间进行录像、记录与分析;依据IAEA提供的指标[1],找出操纵员在生产过程中可能出现的操作失误类别及其可能造成的危害;基于3参数威布尔模型推导出操纵员操作响应失误概率模型,并从人机工程学角度提出了具体预防事故的安全对策措施。结果表明,基于HCR模型的大化集团公司操纵员的人因操作失误模型实用、有效,为实现操作者与机器系统相协调的目标、正确评估操作着实时操作的响应时间提供了重要参考依据。