离子选择性电极测定煤中氟浓度方法及影响因素分析

采用高温碱熔离子选择性电极法测量烟煤及石煤中氟化物浓度,对测量过程中的影响因素进行了分析,并对溶液的ｐＨ值及温度的影响进行了试验研究,结果表明该测量方法准确度较高,误差小,测量方便快速,实用性强,可作为煤及其它矿物质中氟含量测量的一种有效方法     

原子荧光光度法同时测定水中砷、硒的不确定度分析

对原子荧光光度法测定水样中砷、硒浓度的影响因素进行分析,对各因素的不确定度进行计算和评估。结果表明,影响其测量不确定度主要因素是原子荧光强度值带来的不确定度,其它因素是次要的。     

催化分光光度法测定环境样品中微量碘

本文介绍一个简单而灵敏的催化分光光度法,用于测定环境样品中微量碘,本法系基于亚硝酸根存在时微量碘离子催化还原硫氰酸铁络含物,并以分光光度计测量该红色络合物的减弱强度,在一定温度时,该络合物的分解速度正比于磺的含量.在给定的实验条件下,磺离子的浓度在0.001-0.024毫克/升之间服从比尔定律. 本法已成功地应用于天然水、土壤、海底泥和海生物中微量磺的测定,结果良好.     

分光光度法测定大气中的过氧化物

采用液氮冷冻法采集大气中的过氧化物,并用分光光度法测定其浓度.研究中对大气采样条件和样品测定条件进行了探讨,并将测定结果与高压液相色谱法的测定结果进行了对比.在野外大气监测中应用该方法测定了长江三角洲地区大气中过氧化物浓度及日变化规律.结果表明,分光光度法显色稳定,灵敏度高,检测下限为7.92×10-8mol/L,可用于测定大气中的H2O2和有机过氧化物,是一种操作方便,易于推广的方法.     

6项环境监测分析方法标准中钴、铬、钼、钛的不确定度分析及其在达标判定中的应用

研究依据测定不确定度的基本理论和ISO 21748：2017《采用重复性、再现性和正确度评估测量不确定度的导则》，提出了基于中国环境监测分析方法标准多家实验室验证中已获得的数据计算合成标准不确定度的方法，将方法标准中规定的重复性、再现性等指标与合成标准不确定度进行了衔接。分析了近年发布的6项水质监测分析方法标准中钴、铬、钼、钛等4种金属元素的相对合成标准不确定度，结果表明：被测量的浓度是影响方法标准测量不确定度的重要因素。对于火焰原子吸收分光光度法（FAAS）和石墨炉原子吸收分光光度法（GAAS），样品浓度为方法标准测定下限3倍左右时，测定结果的相对标准不确定度可保持在15%以下；对于电感耦合等离子体发射光谱法（ICP-AES），样品浓度为方法标准测定下限3~5倍时，测定结果的相对标准不确定度为12%~17%；对于电感耦合等离子体质谱法（ICP-MS），钛元素浓度为测定下限3倍左右时，相对标准不确定度在15%以下，而钴、铬、钼的浓度在测定下限40~100倍以上时，相对标准不确定度在15%以下。6项方法标准可分别用于《地表水环境质量标准》（GB 3838—2002）以及22项水污染物排放标准钴、铬、钼、钛的达标监测。     

4—氨基安替比林直接光度法测定挥发酚的改进

挥发酚的测定一般采用4一氨基安替比林光度法[1]。酚浓度小于0．1mg／L的采用4—氨基安替比林萃取光度法．大于0．1mg／L的采用4—氨基安替比林直接光度法。在例行监测中，我们事先并不知道水样中酚浓度的高低、仅根据以往的经验判断，这种判断时常有失误。由于直接法和萃取法所取馏出液的体积不同．加试剂的量也不同．当显色后发现浓度不在所用方法的范围之内时．只得重取水样．预蒸馏后用另一种方法显色测定，费时费力。为此．我们对直接法进行了改进，使其与萃取法所取馏出液体积相同，加试剂的量也相同．显色后若颜色较深．即用直接法…     

硼酸-碘分光光度法测量混合印染废水中聚乙烯醇的研究

采用硼酸-碘分先光度法测量聚乙烯醇的浓度,对显色剂用量、最大吸收波长、显色时间、淀粉干扰、样品存放时间等进行研究.结果表明,最佳工作波长为645nm,淀粉的干扰可以通过加酸水解消除.该法标准曲线线性良好,相关系数达0.99915.     

海洋沉积物中多种重金属的X射线荧光分析法

建立了海洋沉积物中包括砷、铜、铅、锌、镍和总铬在内的多种重金属X射线荧光分析法,测量不需要任何消解前处理过程,可在约1h内测量1个样品中的50余种元素,用该方法分析了8个海洋沉积物标准样品,还与原子荧光光谱法或原子吸收分光光度法比对分析了2个实际样品,结果表明,该方法可信度较高,且具有快速、简便、高效等特点,是一种非破坏性分析方法。     

原子荧光光度法测定煤中砷的研究

利用原子荧光光度法测定煤中砷的含量,通过原子荧光条件的优化,建立一种利用原子荧光法测定煤中砷含量的新方法,该方法浓度测定范围大、灵敏度高,用于煤中微量砷的测定,结果令人满意.     

甲基橙分光光度法测定环境中氯气的分析方法研究

绘制甲基橙分光光度法测氯气的标准曲线,研究在同一采样速率下不同浓度气体的采集效率和回收情况,探讨不同反应温度与放置时间对褪色反应的影响,为更好地掌握现场采样条件提供理论依据。应用甲基橙分光光度比色法测定不同浓度氯气,在不同温度下进行实验,并将吸收放置不同时间。本法的检出限为0.2μg/ml;若采样体积为2 L时,可测量浓度范围为0.5-30 mg/m3的氯气。回收率在60%~102%之间。对于环境空气中浓度超出其范围的氯气测定,高浓度需要稀释或减小采样速率,低浓度则需要加大采样速率或延长采样时间,温度对褪色反应影响明显,在温度较低的情况下进行褪色反应可使测得值偏低,反应温度控制在30℃为宜。放置时间长短对褪色反应不大,可隔天测试。但考虑空气中可能含有的臭氧等氧化物质,吸收液最好封口保存。     

硝化污泥低温冲击强化试验

采用完全好氧式膜生物反应器富集耐低温硝化污泥,通过低温冲击强化试验研究硝化污泥的耐低温特性。结果表明,低温对硝化污泥中微生物的群落多样性影响较大,温度越低,微生物多样性越低。低温强化组投加了耐低温高硝化菌含量硝化污泥,使得硝化菌在反应器内生长趋势良好,对低温冲击的恢复更有效果,且低温硝化污泥比中温硝化污泥具有更好的氨氮及亚硝氮去除效果。     

人工神经网络用于铅的化学形态模拟计算

用前馈线性网络法求解水体系中Ｐｂ（２＋）与ＯＨ－之间的反应常数，不同训练算法对求解结果的精度、收敛速度及权值均有影响．结果表明，批处理算法的精度最好，权值不出现负值，但运算时间最长；在线算法的精度虽不如批处理算法，而比数据变换－在线算法好，权值有时会出现负值．运算时间较长；数据变换－在线算法的优点是运算时间短，但相对误差较大，权值出现负值的机会多。采用反馈网络模拟计算铅的各种化学形态的浓度．用物料核算的方法对反馈网络模型进行检验表明，此种模型用于平衡计算是可行的，详细分析了理论模拟和实验曲线的差异的原因，温度的影响最小，在４＜ｐＨ＜９时，ＣＯ有重要的影响．在国代检验时，ｎ值取整所引入的误差的影响亦不可忽视。从本文的结果可以看到，采用前馈网络和反馈网络相结合的方法考察水体中的化学形态是可行的．从而为解决这一类问题提供了一种可能的途径．     

室内装饰装修材料测试舱的研制与应用

介绍了测试舱的研制意义、测试舱构造和温度控制部分,以及空气交换、循环控制,空气净化装置和温度、湿度、流速显示装置等.通过实验,对测试舱的温度控制,空气净化系统检验,空气交换、循环的检验,释放甲醛平衡点的快速判断和测试舱的比对等运行技术指标进行了论证、优化.结果表明,简易的室内装饰装修材料测试舱对主要运行参数可以自动运行与控制,运行情况满足国家标准方法的技术指标要求,与同类商品化测试舱相比,误差在2%左右.     

Geostatistical Uncertainty Modelling for the Environmental Hazard Assessment During Single Erosive Rainstorm Events

This paper presents an environmental hazard assessment to account the impacts of single rainstorm variability on river-torrential landscape identified as potentially vulnerable mainly to erosional soil degradation processes. An algorithm for the characterisation of this impact, called Erosive Hazard Index (EHI), is developed with a less expensive methodology. In EHI modelling, we assume that the river-torrential system has adapted to the natural hydrological regime, and a sudden fluctuation in this regime, especially those exceeding thresholds for an acceptable range of flexibility, may have disastrous consequences for the mountain environment. The hazard analysis links key rainstorm energy variables expressed as a single-storm erosion index (EI_sto), with impact thresholds identified using an intensity pattern model. Afterwards, the conditional probabilities of exceeding these thresholds are spatially assessed using non-parametric geostatistical techinques, known as indicator kriging. The approach was applied to a test site in river-torrential landscape of the Southern Italy (Benevento province) for 13 November 1997 rainstorm event.     

Influence of different digital terrain models (DTMs)on alpine permafrost modeling

The thawing of alpine permafrost due to changes in atmospheric conditions can have a severe impact, e.g., on the stability of rock walls. The energy balance model, PERMEBAL, was developed in order to simulate the changes and distribution of ground surface temperature (GST) in complex high-mountain topography. In such environments, the occurrence of permafrost depends greatly on the topography, and thus, the digital terrain model (DTM) is an important input of PERMEBAL. This study investigates the influence of the DTM on the modeling of the GST. For this purpose, PERMEBAL was run with six different DTMs. Five of the six DTMs are based on the same base data, but were generated using different interpolators. To ensure that only the topographic effect on the GST is calculated, the snow module was turned off and uniform conditions were assumed for the whole test area. The analyses showed that the majority of the deviations between the different model outputs related to a reference DTM had only small differences of up to 1 K, and only a few pixels deviated more than 1 K. However, we also observed that the use of different interpolators for the generation of a DTM can result in large deviations of the model output. These deviations were mainly found at topographically complex locations such as ridges and foot of slopes.     

Thermal impact evaluation for brunner Island steam electric station: Toward a more realistic assessment

A realistic approach to thermal impact assessment is presented which employs a two-dimensional thermal plume model, a large data base for river flow and temperature, and accounts for nonuniform spatial distribution of habitats and seasonal differences in fish behavior. The end result portrays real effects of the thermal impact rather than an artificially constructed worst-case scenario.     

核电站温排水遥感监测方法研究——以田湾核电站为例

以江苏省连云港田湾核电站为主要研究区，通过热红外遥感技术研究温排水热污染现象，综合应用美国Landsat卫星热红外波段数据及地面气象测站资料，定量反演核电站建成前后附近海域水温分布与变化情况。研究结果表明，遥感技术完全能够满足温排水监测要求，对于完善近岸海域生态环境保护工作具有积极意义。     

Water Quality Prediction of Water Sources Based on Meteorological Factors using the CA-NARX Approach

With the increasingly serious problem of surface water environmental safety, it is of great significance to study the changing trend of reservoir water quality, and it is necessary to establish a water quality prediction and early warning system for the management and maintenance of water resources. Aiming at the problem of water quality prediction in reservoirs, a CA-NARX algorithm is designed, which combines the improved dynamic clustering algorithm with the idea of machine learning and the forward dynamic regression neural network. The improved dynamic clustering algorithm is used to classify the eutrophication degree of waterbodies according to the total phosphorus and total nitrogen content. Considering four meteorological factors, air temperature, water temperature, water surface evaporation, and rainfall, synthetically for each water quality condition, the total phosphorus and total nitrogen in the waterbody are forecasted by an improved forward NARX dynamic regression neural network. Based on this, the CA-NARX prediction algorithm can realize short period water quality prediction. Compared with the traditional support vector regression machine model, improved GA-BP neural network, and exponential smoothing method, the CA-NARX model has the least prediction error.

     

Numerical Analyses of Soft Bottom Macroinvertebrates to Diagnose the Pollution in Tropical Coastal Waters

Soft bottom benthic organisms especially polychaetes are known to adapt as r or k selected strategies to different gradients of pollution. This will result in changes of benthic community structure from that of normal structure. There are a number of techniques to assess the impact of pollution on benthic community structure. Hence, to test this hypotheses some of the univariate and multivariate techniques were applied to soft bottom macro-invertebrates data of coastal waters of Mangalore, central west coast of India, a hot-spot area. Univariate techniques such as Pearson Rosenberg Model (PRM), abundance biomass comparison curve (ABC), geometrical class distribution, dominance-diversity curve, benthic community structure indices and multivariate techniques such as cluster classification, multidimensional scaling (MDS) and principal component analysis (PCA) were used to discriminate and diagnose the disturbance among the sites. Effectiveness and applicability of some of the above techniques are highlighted and discussed with the present set of data for environmental impact assessment studies.     

Climate Impact Response Functions for Terrestrial Ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO₂ concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand. This revised version was published online in July 2006 with corrections to the Cover Date.