Strategies to Make Methods Based on Flow Injection Analysis Greener     

Marcos Almeida Bezerra  Ricardo Erthal Santelli  Valfredo Azevedo Lemos  Juscelia Pereira dos Santos Alves  Bernardo Ferreira Braz  Luana Bastos Santos 《洁净——土壤、空气、水》2020,48(7-8)

The implementation of flow injection analysis (FIA) systems and correlated techniques in the laboratory routine provides an increase of analytical throughput and the reduction of risks of analyte losses and contamination. Naturally, it contributes to the reduction of reagent consumption and minimization of waste generation. This paper presents and discusses an overview of the main strategies adopted to make methods based on FIA systems more environmentally friendly, and offers a review of these methods that covers the period from January 2002 to December 2019. Strategies based on reagent management (adoption of procedures without reagents, replacement of toxic reagents, recycling and reuse of reagents and, use of immobilized reagents), the online waste treatment, and the improvements of FIA systems (flow system configurations that avoid reagent wastage, use of green detectors, automation, and miniaturization) are approached in this perspective.  相似文献   

城市地下变电站非线性地震反应分析     

文波  杨金熹  张路 《地震工程与工程振动》2020,(2):33-42

为研究城市地下变电站结构及其内部电气设备的动力特性及地震反应规律,以西安市快速轨道交通二号线张家堡地下变电站为工程背景,依据黏弹性人工边界理论及有限单元法,建立考虑土体-结构-设备动力相互作用的三维有限元计算模型,首先通过半空间自由场模型验证了地震动输入方法的有效性,继而开展地下变电站系统的模态分析和动力时程分析,得到了该类结构的动力特性及地震响应规律。研究结果表明,结构上覆土体及电气设备在地震作用下产生的惯性力是结构构件应力增长的主要原因,8度罕遇地震作用下地下变电站内电气设备的加速度放大系数明显超出规范要求,需要采取相应保护措施。  相似文献   

大水面日本沼虾(Macrobrachium nipponensis)资源人工增殖   总被引：4，自引：0，他引：4  

何绪刚  龚世园  刘军  张训蒲 《湖泊科学》2002,14(4):377-380

挑选受精卵颜色呈褐色或接近褐色的抱卵虾,放入网箱多点布局孵化,直接放流孵出幼体是大水面日本沼虾资源增殖的有效方法.2001年,采用此法对湖北省阳新县网湖日水沼虾进行增殖,其产量从增殖前(2000年)的10000kg上升至35000kg,取得显著增殖效果,进箱孵化的抱卵数量(N,kg)可用计划生产量(Y,kg),总回捕率(R)及个体平均体重(W,g/ind)计算:N≥Y·(1000·R·W)-1.  相似文献   

COMPARISON OF METHODS FOR DISTINGUISHING DIFFERENT GRADES OF GEOMORPHOLOGIC SURFACES BASED ON SEDIMENT PARTICLE SIZE FEATURES: TAKING THE QINGYIJIANG RIVER BASIN AS AN EXAMPLE          下载免费PDF全文

LIU Rui  JIANG Da-wei  LI An  GUO Chang-hui  ZHANG Shi-min 《地震地质》2019,41(4):837-855

When using river geomorphology to study tectonic deformation, it is often difficult to distinguish the same level geomorphology in areas with severe weathering. In this paper, we take the geomorphologic surfaces of the Qingyijiang river basin as an example and try to distinguish the geomorphic surfaces by the sediment features that make up them. In order to distinguish different geomorphic surfaces, the traditional particle-size analysis method, SOFM network method and system clustering analysis method are taken to classify 29 samples from different geomorphic surfaces. The classification results of the three methods are different to a certain extent. We analyzed and compared the classification results of the three methods in detail. The results show that the traditional particle size analysis method, SOFM network method and cluster analysis method all can distinguish the geomorphic surface of different genesis, besides, they also can distinguish low-level terraces(T₁, T₂)and high-level terraces(T₃, T₄)for different grades of river terraces. Furthermore, the results also show that SOFM network method and cluster analysis method can make a certain distinction for the low-level terraces(T₁, T₂), while the traditional particle size analysis method is difficult to distinguish them. In addition, we analyzed and compared the three methods from the classification results, the results presentation, the operation process, and the error transmission. The results suggest that the advantages and disadvantages of the three methods are obvious. From the perspective of the classification results, the three methods all can distinguish the river terraces and alluvial fans and can make certain discrimination for different levels of river terraces. From the presentation of the results, the result of SOFM network is simple and clear. From the operation process, the traditional particle-size analysis method is relatively cumbersome, and the SOFM network method and the cluster analysis method are relatively simple to operate. From the perspective of error transmission, the traditional particle-size analysis method calculates the partial particle size feature value of the sample, which has a certain loss for the particle size distribution information of the whole sample. The error of the clustering analysis method has cumulative features and the influence exists consistently. The classification results of the SOFM network are independent of each other, which effectively avoids the problem of such error transmission of clustering analysis method. Overall, the classification results of the SOFM network method are simple and clear, the operation is simple, and the error is small. It has stronger adaptability to identifying different levels of different geomorphic surfaces. The results of this study will provide a simple and effective means for distinguishing different levels of geomorphic surfaces.  相似文献   

基于Matlab GUI的全球重力固体潮可视化实现     

闫如玉  万永革  解朝娣  汪园园  刘勇 《地震地磁观测与研究》2019,40(3):160-167

阐明重力固体潮理论值计算原理,利用改进的计算新方法编写Matlab计算程序,采用Matlab中的GUI平台,对全球重力固体潮进行可视化实现,直观观察固体潮在地面的时空变化规律。通过输入时间和经纬度,确定采样间隔(秒采样、分钟采样、时采样),实现以下功能:(1)以图像和Excel形式,输出某一地区的重力固体潮理论值;(2)仿真未来24小时全球重力固体潮。  相似文献   

Modelling long-term groundwater fluctuations by extreme learning machine using hydro-climatic data   总被引：1，自引：1，他引：0  

Meysam Alizamir  Mohammad Zounemat-Kermani 《水文科学杂志》2018,63(1):63-73

The ability of the extreme learning machine (ELM) is investigated in modelling groundwater level (GWL) fluctuations using hydro-climatic data obtained for Hormozgan Province, southern Iran. Monthly precipitation, evaporation and previous GWL data were used as model inputs. Developed ELM models were compared with the artificial neural networks (ANN) and radial basis function (RBF) models. The models were also compared with the autoregressive moving average (ARMA), and evaluated using mean square errors, mean absolute error, Nash-Sutcliffe efficiency and determination coefficient statistics. All the data-driven models had better accuracy than the ARMA, and the ELM model’s performance was superior to that of the ANN and RBF models in modelling 1-, 2- and 3-month-ahead GWL. The RMSE accuracy of the ANN model was increased by 37, 34 and 52% using ELM for the 1-, 2- and 3-month-ahead forecasts, respectively. The accuracy of the ELM models was found to be less sensitive to increasing lead time.  相似文献   

浅水湖泊动力作用下水-土界面底泥起悬驱动力野外观测   总被引：1，自引：1，他引：0  

李一平  王建威  姜龙  唐春燕  杜薇  罗潋葱  戴淑君 《湖泊科学》2017,29(1):43-51

动力扰动引起的水-土界面沉积物悬浮是浅水湖泊蓝藻水华控制的难点,本文基于声学高频流速仪、浊度仪、气象、波浪等观测仪器获取的高时空分辨时间序列参量,以太湖为例对动力扰动下的底泥起悬驱动力进行研究.结果表明风速小于3 m/s时,水-土界面处平均悬浮物浓度为59 mg/L,波流综合切应力小于0.015 N/m~2,底泥未起悬或在底床附近极小范围内发生起悬;风速在3~6 m/s时,水-土界面处平均悬浮物浓度为103 mg/L,波浪产生的底切应力大部分情况远大于湖流产生的切应力,波流综合切应力处于0.015~0.25 N/m~2范围内,底泥中等规模起悬;风速大于6 m/s时,水-土界面处平均悬浮物浓度为174 mg/L,波浪产生的底切应力占据绝对的主导地位,波流综合切应力大于0.25 N/m~2,底泥大规模起悬.梅梁湾底泥起悬的临界切应力在0.015 N/m~2左右,临界风速大约为3 m/s.  相似文献   

Composts Containing Natural and Mg‐Modified Zeolite: The Effect on Nitrate Leaching,Drainage Water,and Yield     

Hajar Taheri‐Soudejani  Manouchehr Heidarpour  Mohammad Shayannejad  Hossein Shariatmadari  Hossein Kazemian  Majid Afyuni 《洁净——土壤、空气、水》2019,47(8)

  相似文献   

小流域水污染治理示范工程——杭州长桥溪的生态修复   总被引：4，自引：0，他引：4  

吴芝瑛  陈鋆 《湖泊科学》2008,20(1):33-38

长桥溪是杭州西湖上游四大溪流之一.长桥溪生态修复工程利用长桥溪流域的微地貌和水动力作用,通过地埋式污水处理系统与人工湿地相结合的方法,将污水处理工艺与景观园林紧密结合,综合运用物理、化学、生物等手段对长桥溪流域内污水进行处理,从而减少该溪向西湖的污染物排放.工程经过两年运行,2006年其入湖湖水的TP、TN、NH4 -N和CODMn浓度分别降至0.067±0.041mg/L、3.54±1.23 mg/L、0.59±0.46mg/L和2.11±0.38mg/L,较2003年依次降低了88.5%、68.8%、89.1%和68.0%.  相似文献   

Long-range forecasting of suspended sediment     

A. O. Pektas 《水文科学杂志》2017,62(14):2415-2425

This study examines the employment of two methods, multiple linear regression (MLR) and an artificial neural network (ANN), for multistep ahead forecasting of suspended sediment. The autoregressive integrated moving average (ARIMA) model is considered for one-step ahead forecasting of sediment series in order to provide a comparison with the MLR and ANN methods. For one- and two-step ahead forecasting, the ANN model performance is superior to that of the MLR model. For longer ranges, MLR models provide better accuracy, but there is an important assumption violation. The Durbin-Watson statistics of the MLR models show a noticeable decrease from 1.3 to 0.5, indicating that the residuals are not dependent over time. The scatterplots of the three methods (MLR, ARIMA and ANN) for one-step ahead forecasting for the validation period illustrate close fits with the regression line, with the ANN configuration having a slightly higher R² value.  相似文献