电化学微传感器检测水中痕量铜离子

为改善微电极在阳极溶出伏安法检测重金属离子过程中低电流响应和低电催化能力的缺点,提出了一种在碳纤维微电极表面合成还原氧化石墨烯/纳米金材料制得还原氧化石墨烯纳米金修饰碳纤维微电极（rGO/AuNPs CFMEs）的方法.通过SEM表征,所制备的rGO/AuNPs CFMEs具有比表面积高、吸附能力强和催化活性好的特点,因此改性微电极适合作为方波阳极溶出伏安法（SWASV）测定水中铜离子（Cu²⁺）的工作电极.在构建微传感器测试水中痕量铜离子系统后,对pH值、电导率、富集时间和富集电位等检测条件进行了优化.在pH值为4,电导率为36.1S/m,富集时间为360s,富集电位为-1.2V的最佳条件下,铜的线性范围和检出限分别0~1.0μmol/L和2.4nmol/L.此外,微传感器的可重复性、长期稳定性以及选择性也得到了验证.     

基于形态滤波遗传算法对目标红外图像特征检测

将形态滤波和自适应遗传算法结合起来,提出了一个用于目标检测的形态滤波器参数优化遗传算法。通过设计了形态滤波的遗传算法,寻求最佳结构元,以实现对目标的自适应检测。作为2个特殊环境中的应用检测实例,分别对固体推进器尾喷焰红外图像和复杂背景下的弱小目标进行检测。实验结果表明该方法能够更好地适应环境变化,更大程度地提高目标信号检测的信号噪声（SNR）比,有效地检测出复杂背景下的目标。     

太湖流域水污染对太湖水质的影响分析

从太湖地区(苏州、无锡、常州、杭州、嘉兴和湖州)的污染物排放量、水质监测结果，以及工农业发展、人口变化、人民生活水平的提高、东太湖萎缩，底泥中营养物的变化和湖泊生态系统失衡的特点入手，分析了太湖流域水污染现状。结果表明，工业废水排放量高于城镇生活废水排放量；太湖湖体、环湖河流水质与省、市边界断面主要超标项目分别为：总磷、总氮和氨氮；水体水质演变是由工农业迅速发展、人口过度增加、污染防治措施相对滞后，以及太湖水生态系统失衡等原因造成的。     

空气阴极微生物燃料电池的构型优化及其快速测定BOD的性能评价

设计了一种新型双室空气阴极微生物燃料电池(MFC)并将其作为生物传感器,与传统双室空气阴极MFC进行对比,考察其电化学性能及用于快速检测BOD的性能。结果表明：新型空气阴极MFC可有效提高功率密度并降低内阻,其功率密度最高为897 mW·m⁻²,而内阻最低为92 Ω;该MFC可用于直接快速检测高浓度有机物的BOD,对醋酸钠底物的线性检测限为1 280 mg·L⁻¹,在此底物浓度下MFC的检测时间为31.2~66 h,线性可决系数R²为0.97~0.99;对于GGA底物的线性检测限为1 250 mg·L⁻¹,在此底物浓度下MFC的检测时间为33~67 h,线性可决系数R²为0.98。本研究可为MFC型BOD检测传感器的性能优化提供参考。     

Fault detection and diagnostics of a three-phase separator

A high demand of oil products on daily basis requires oil processing plants to work with maximum efficiency. Oil, water and gas separation in a three-phase separator is one of the first operations that are performed after crude oil is extracted from an oil well. Failure of the components of the separator introduces the potential hazard of flammable materials being released into the environment. This can escalate to a fire or explosion. Such failures can also cause downtime for the oil processing plant since the separation process is essential to oil production. Fault detection and diagnostics techniques used in the oil and gas industry are typically threshold based alarm techniques. Observing the sensor readings solely allows only a late detection of faults on the separator which is a big deficiency of such a technique, since it causes the oil and gas processing plants to shut down.A fault detection and diagnostics methodology for three-phase separators based on Bayesian Belief Networks (BBN) is presented in this paper. The BBN models the propagation of oil, water and gas through the different sections of the separator and the interactions between component failure modes and process variables, such as level or flow monitored by sensors installed on the separator. The paper will report on the results of the study, when the BBNs are used to detect single and multiple failures, using sensor readings from a simulation model. The results indicated that the fault detection and diagnostics model was able to detect inconsistencies in sensor readings and link them to corresponding failure modes when single or multiple failures were present in the separator.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

滇西北高原湖泊剑湖演变过程及其生态环境效应分析

以滇西北高原湖泊剑湖为研究区,1974—2015年间8期遥感影像为数据源,运用遥感和地理信息系统技术,研究剑湖湖泊近40年间的时空演变过程,探析剑湖湖泊的入湖污染物及其生态环境效应变化。结果表明:近40年来剑湖湖泊面积呈现先明显减少再增加后缓慢减少的变化规律,由1974年的504.47 hm~2减至2015年的451.72 hm~2;目前剑湖水体中COD含量较低,符合地表水环境质量Ⅱ类标准;TP含量满足Ⅲ类标准;TN含量仅可满足IV类标准;剑湖入湖的主要污染源是农村生活污染和农业面源污染;随着时间的演变剑湖湖泊TN、TP污染物浓度呈上升趋势,剑湖湖泊生态系统受到极大干扰。     

原子吸收火焰法次灵敏线测定污水和电镀污泥中高含量的锌

对采用原子吸收火焰法次灵敏线测定污水和电镀污泥中高含量的锌进行了研究。试验结果表明：在锌浓度50．0～600．0mg/L之间,溶液锌含量与吸光度呈线性关系。线性回归方程为y＝0．000661x-0．0007,相关系数γ＝0．9998。方法检出限为25．0mg/L,相对标准误差（RSD）＜2．96％,加标回收率为92．5％～105％,与标准法的相对误差＜2．76％。     

pH值对凯氏蒸馏法氨氮检出量的影响分析研究

土壤、肥料中的氨氮测定常用2mol·L^-1KC浸提一蒸馏法一酸滴定的方法进行测定,其中蒸馏是最关键和最重要的一个环节。以污泥堆肥样品为例,利用统计学原理,研究了汽提蒸馏过程中pH对氨氮检出量的影响。结果显示：pH值在6．5—11．0范围内与氨氮的检出系数是显著的正相关关系（相关系数r=0．9891）;回归方程在0．05的水平下是非常显著的,拟合度很好。进一步做残差和预测分析可以得出：pH值在6．5～10．0范围内,预测值和测定值的符合度更好。     

水体中总氮检测的方法研究

使用碱性过硫酸钾氧化紫外分光光度法(GB 11894—1989)测定水中的总氮时,在严格按该方法分析步骤操作的情况下,依然会出现空白值偏高、检测结果不准确等问题。本文对水中总氮检测过程中的影响因素进行了总结、分析,对需要重点注意的环节进行了探讨,找出了问题的原因并提出了解决方法。