中俄跨界水体水质联合监测数据可比性研究

中俄跨界水体水质联合监测已经连续开展了11 a,积累了大量的监测数据。笔者针对双方实际监测数据,选用相关性分析和t检验等统计学方法,分析了中俄双方联合监测数据可比性。研究结果表明:p H、溶解氧、高锰酸盐指数和化学需氧量的相对偏差统计容许限基本满足中国标准建议值;氨氮和铁2个指标高于中国标准建议值;锰的数据差异最大。建议中俄双方针对溶解氧使用便携式溶解氧仪进行原位监测;重点对氨氮、铁和锰开展技术交流,设计相关实验,从样品采集、保存、运输、前处理和实验室分析等各环节查找双方差异。     

一种便携式荧光测油仪在海上溢油应急监测中的适用性研究

研究了一种便携式荧光测油仪在海上溢油应急监测中的适用性,并与现行仲裁标准方法进行比较分析。研究表明:该便携式荧光测油仪测定海水中油类样品仅需100 mL水样,平均每个样品所需的前处理时间约340 s,方法检出限为0.003 mg/L,测定下限为0.012 mg/L。测定用标准物质配制的不同浓度海水样品,相对标准偏差为0.08%~0.87%,测定标准样品的相对误差为0.49%~4.50%,实际样品加标回收率为90%~107%。对标准物质配制的海水样品进行检测,与现行仲裁标准方法在0.05水平下无显著性差异。在渤海中部海上监测中,连续6 d测定不同标准样品的相对标准偏差为0.26%~0.83%。研究结果表明,该便携式荧光测油仪适用于现场对油类的定量分析和水质评价。     

Influence of different nitrate–N monitoring strategies on load estimation as a base for model calibration and evaluation

Model-based predictions of the impact of land management practices on nutrient loading require measured nutrient flux data for model calibration and evaluation. Consequently, uncertainties in the monitoring data resulting from sample collection and load estimation methods influence the calibration, and thus, the parameter settings that affect the modeling results. To investigate this influence, we compared three different time-based sampling strategies and four different load estimation methods for model calibration and compared the results. For our study, we used the river basin model Soil and Water Assessment Tool on the intensively managed loess-dominated Parthe watershed (315 km²) in Central Germany. The results show that nitrate–N load estimations differ considerably depending on sampling strategy, load estimation method, and period of interest. Within our study period, the annual nitrate–N load estimation values for the daily composite data set have the lowest ranges (between 9.8% and 15.7% maximum deviations related to the mean value of all applied methods). By contrast, annual estimation results for the submonthly and the monthly data set vary in greater ranges (between 24.9% and 67.7%). To show differences between the sampling strategies, we calculated the percentage deviation of mean load estimations of submonthly and monthly data sets as related to the mean estimation value of the composite data set. For nitrate–N, the maximum deviation is 64.5% for the submonthly data set in the year 2000. We used average monthly nitrate–N loads of the daily composite data set to calibrate the model to achieve satisfactory simulation results [Nash–Sutcliffe efficiency (NSE) 0.52]. Using the same parameter settings with submonthly and monthly data set, the NSE dropped to 0.42 and 0.31, respectively. Considering the different results from the monitoring strategy and the load estimation method, we recommend both the implementation of optimized monitoring programs and the use of multiple load estimation methods to improve water quality characterization and provide appropriate model calibration and evaluation data.     

《地下水管理条例》实施后的金属指标检测样品采集及前处理规范性分析

《地下水管理条例》自2021年12月1日起施行,但是由于《地下水质量标准》(GB/T 14848—2017)未明确其中的金属指标是检测可溶态含量还是总量,导致各检测机构在检测过程中的采样和前处理环节存在较多不确定之处。梳理了国内外地下水监测相关标准和规范,并进行了实验比对,经分析得出以下结论:铜、铅、锌、铁、锰的可溶态含量和总量检测结果存在明显差异,其中,铁和铅检测结果的差异最明显,铁和锰检测结果的差异会影响地下水质量类别判定。《地下水质量标准》中的金属指标应检测可溶态,包括汞、砷和硒。充分洗井后采集的地下水样品存在一定的浑浊度是合理的。完成采集的地下水金属指标检测样品中不应包含沉淀相。测定地下水可溶态汞、砷和硒时,如采用原子荧光法,则需对样品进行消解;如采用电感耦合等离子体质谱法,则无需对样品进行消解。在此基础上,对地下水采样及前处理关键环节和地下水检测管理工作提出了相关建议。     

Strategically designed sample composition for fastest screening of polychlorinated biphenyl congeners in water samples

A new strategy for preparing composite samples of special interest and applicability in environmental screening studies is presented. The use of supersaturated experimental design matrices to conduct the sample composition of water sample specimens in screening studies is demonstrated. In contrast to well known conventional sample composition, this strategic approach provides analytical objects allowing the accurate prediction of analyte concentration levels in the original individual sample specimens while fixing the number of experiments to be carried out down to the very number of sample specimens. This will be of special importance when dealing with analytes that require complicated, labour intensive and expensive analytical processes. To reach this goal, two main conditions must be fulfilled. The first one is the sparsity effect (Pareto principle) which holds for the specimens in the sampling campaign. This means that the number of really anomalous or contaminated specimens, as compared to the total number of specimens to be analysed, is low. In environmental screening studies, frequently this situation can be reasonably assumed. The second condition is to have an effective manner to develop and solve the experimental designs required to build-up the composite samples. The challenging problem of screening PCBs in water samples has been tackled to show the usefulness of this strategic approach by combining chemometrically assisted sample composition and rapid analysis using solid-phase microextraction of the composite samples.     

Bioavailability assessment of phosphorus and metals in soils and sediments: a review of diffusive gradients in thin films (DGT)

This paper provides an overview of the principle and latest development of the diffusive gradients in thin films (DGT) technology and its applications in environmental studies with a focus on bioavailability assessment of phosphorus and metals in sediments and soils. Compared with conventional methods, DGT, as a passive sampling method, has significant advantages: in situ measurement, time averaged concentrations and high spatial resolution. The in situ measurement avoids artificial influences including contamination of samples and sample treatment which may change the forms of chemicals. The time averaged concentration reflects representative measurement over a period of time. The high-resolution information captures the biogeochemical heterogeneity of elements of interest distributed in microenvironments, such as in the rhizosphere and the vicinity of the sediment-water interface. Moreover, DGT is a dynamic technique which simultaneously considers the diffusion of solutes and their kinetic resupply from the solid phases. All the advantages of DGT significantly promote the collection of “true” information of the bioavailable or labile forms of chemicals in the environment. DGT provides potential for applications in agriculture, environmental monitoring and the mining industry. However, the applications are still at the early testing stage. Further studies are needed to properly interpret the DGT-measured results under complex environmental conditions, and standard procedures and guideline values based on DGT are required to pave the way for its routine applications in environmental monitoring.     

影响地表水高锰酸盐指数自动监测数据准确性的因素

地表水高锰酸盐指数自动监测仪器在实际应用中存在质控样测试和实际水样比对测试合格率相对偏低的问题。通过对高锰酸盐指数氧化还原机理的分析,结合目前国控水站对质控样品的测试数据,探讨了如何使用高锰酸盐指数自动监测仪分析测试得到准确可靠的水质监测数据。认为应尽量保持自动分析仪器的反应条件、稀释条件与标准方法一致,即取样量与试剂用量比与标准方法一致,并根据样品浓度变化实现量程自动切换,分量程进行仪器校准和测量,才能够提高自动分析仪器测量的准确性。     

便携式GC-MS测定气体样品中6种典型VOCs的不确定度评定

以便携式GC-MS测定气体样品中6种典型挥发性有机物(VOCs)组分(苯、1,1,2-三氯乙烷、四氯乙烯、乙苯、间二甲苯和1,3,5-三甲基苯)为例,应用不确定度理论,从检测过程和计算方法的角度分析了影响测量不确定度的各种因素:标准气体定值、标准气体稀释、工作曲线的非线性及重复性测定。对各测量不确定度分量进行计算和评定,同时采用稳健统计方法对测定结果进行准确度评价。结果表明:采用便携式GC-MS测定气体样品中VOCs不确定度的主要影响因素是标准气体定值和工作曲线的非线性,其次是重复性测定,标准气体稀释引入的不确定度较小。当VOCs组分含量为200 nmol/mol浓度水平时,测量扩展不确定度为14～17 nmol/mol,测量相对扩展不确定度为7.1%～9.2%(k=2,置信水平为95%),相对误差为1.5%～4.0%。     

Water quality evaluation of two interconnected dam lakes with field-captured and laboratory-acclimated fish, <Emphasis Type="BoldItalic">Cyprinus carpio</Emphasis>

Karakaya and Sultansuyu Dam Lakes, located in the eastern part of Turkey, are important water sources, both for irrigation and fishery. The main goal of the study was to investigate water qualities of dam lakes using a set of biomarkers in the fish Cyprinus carpio. For this aim, field sample and laboratory-acclimated fish were compared to identify changes in selected biomarkers. The activities of ethoxyresorufin-O-deethylase, glutathione S-transferase, glutathione reductase, and carboxylesterase were determined in liver samples. Also, plasma and liver lactate dehydrogenase, aspartate aminotransferase, and alanine aminotransferase activities were assayed. Brain acetylcholinesterase and carboxylesterase activities were also determined. The hepatosomatic index and condition factors were calculated. Plasma vitellogenin assays were evaluated for the presence of xenoestrogen. Physicochemical values of water samples showed the existence of eutrophication risk, and also, some chemicals in both lakes were determined to be over tolerable limits. The comparisons of samples from both dam lake and laboratory-acclimated fish showed that the lakes may be at risk of pollution by some xenobiotics, namely xenoestrogens and acetylcholinesterase-inhibiting agents.     

Estimation of Heavy Metals in Different Berberis Species and Its Market Samples

Popularity of herbal drugs is increasing all over the world because of lesser side effects as compared to synthetic drugs. Besides, it costs less and easily available to poor people particularly in developing countries. But quality assurance of herbal drugs is very necessary prior to its use. Because in today's polluted environment, even herbal drugs are not safe. Berberis spp. is very important medicinal plant, having various medicinal properties. It is also included in Indian and British pharmacopoeias. Its demand is quite high in herbal drug market. So, to check the quality of market samples of this drug, ten different samples were procured from different drug markets of India for heavy metal estimation. Besides, genuine samples of four species of Berberis viz. B. aristata, B. chitria, B. lycium, B. asiatica were also collected from natural habitats to compare heavy metal concentration in both market and genuine samples. It was found that market samples were much more contaminated than genuine samples. Lead (Pb) concentration is far beyond from WHO permissible limit (10 ppm) for herbal drugs, reaching to maximum 49.75 ppm in Amritsar market sample. Likewise, concentration of all other metals like Cd, Cr and Ni were also very high in market samples as compared to genuine samples.     

Field measurement of lead in workplace air and paint chip samples by ultrasonic extraction and portable anodic stripping voltammetry

On-site measurement of lead in workplace air filter samples and paint chip samples by ultrasonic extraction and anodic stripping voltammetry (UE-ASV) was evaluated in the field during renovation and remodeling activities in residences having leaded paint. Aerosol and paint samples were collected using standard techniques, and the samples were analyzed on-site for lead content by portable UE-ASV. Lead in sample extracts was subsequently determined by atomic absorption (AA) spectrometry in a fixed-site laboratory. The remaining sample extracts plus undissolved material (air filters or paint particles) were then subjected to hot plate digestion in concentrated nitric acid-30% hydrogen peroxide prior to AA analysis for lead. Field UE-ASV lead data were thereby compared to UE-AA and hot plate digestion-AA results from fixed-site laboratory lead measurement. Determination of lead in air filter samples by UE-ASV (over the range of 5 microg to approximately 800 microg Pb per sample) was extremely well correlated with lead measurement by UE-AA and hot plate digestion-AA procedures. However, a significant negative bias associated with ASV measurement was observed, and this was attributed to a matrix effect. Lead measurement in paint chip samples by UE-ASV (over the range of approximately 10 to approximately 550 microg Pb g(-1)) was well correlated with lead measurement by UE-AA and hot plate digestion-AA procedures. However, correlation and precision were lower for lead measurement in paint samples as compared to aerosol samples, and a negative bias was also observed. Lead measurements by UE-AA were compared to lead determinations by hot plate digestion-AA; these data were highly correlated and demonstrated no significant bias. Thus it was concluded that the ultrasonic extraction procedure performed equivalently to hot plate digestion. It was reasoned that matrix effects due to the preparation and analysis of paint chip particles resulted in greater imprecision as well as negative bias by ASV measurement. Despite significant negative bias in this sample set, UE-ASV offers promise for on-site measurement of lead in samples of interest in occupational and environmental health.     

影响总氮准确定量的光谱检测因素

对现行的双波长紫外分光光度法在测定水体总氮中由光学检测本身所产生的影响因素进行了探讨,提出了一种基于三波长的光谱检测总氮量的方法。结果表明,由于仪器信号波动或光散射引起的光谱检测基线上移所造成的误差可以用在NO3-没有吸收的340 nm处的吸光度加以判断,从而用三波长的方法扣除由于光谱基线上移对220 nm和275 nm处吸光度检测的干扰。对2个水样进行同样的光谱检测,以不同的计算公式所得的数据比较可以看出,三波长法明显优于双波长法。三波长法检测重现性相对偏差小于0.2%,其总氮含量的结果要比双波长法高7%～16%。这也解决了人们对总氮含量测定结果总是偏低的困惑。     

Estimating means and variances: The comparative efficiency of composite and grab samples

This paper compares the efficiencies of two sampling techniques for estimating a population mean and variance. One procedure, called grab sampling, consists of collecting and analyzing one sample per period. The second procedure, called composite sampling, collectsn samples per period which are then pooled and analyzed as a single sample. We review the well known fact that composite sampling provides a superior estimate of the mean. However, it is somewhat surprising that composite sampling does not always generate a more efficient estimate of the variance. For populations with platykurtic distributions, grab sampling gives a more efficient estimate of the variance, whereas composite sampling is better for leptokurtic distributions. These conditions on kurtosis can be related to peakedness and skewness. For example, a necessary condition for composite sampling to provide a more efficient estimate of the variance is that the population density function evaluated at the mean (i.e.f()) be greater than . If , then a grab sample is more efficient. In spite of this result, however, composite sampling does provide a smaller estimate of standard error than does grab sampling in the context of estimating population means.     

Bias from two analytical laboratories involved in a long-term air monitoring program measuring organic pollutants in the Arctic: a quality assurance/quality control assessment

Initiated in 1992, air monitoring of organic pollutants in the Canadian Arctic provided spatial and temporal trends in support of Canada's participation in the Stockholm Convention of Persistent Organic Pollutants. The specific analytical laboratory charged with this task was changed in 2002 while field sampling protocols remained unchanged. Three rounds of intensive comparison studies were conducted in 2004, 2005, and 2008 to assess data comparability between the two laboratories. Analysis was compared for organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) in standards, blind samples of mixed standards and extracts of real air samples. Good measurement accuracy was achieved for both laboratories when standards were analyzed. Variation of measurement accuracy over time was found for some OCPs and PCBs in standards on a random and non-systematic manner. Relatively low accuracy in analyzing blind samples was likely related to the process of sample purification. Inter-laboratory measurement differences for standards (<30%) and samples (<70%) were generally less than or comparable to those reported in a previous inter-laboratory study with 21 participating laboratories. Regression analysis showed inconsistent data comparability between the two laboratories during the initial stages of the study. These inter-laboratory differences can complicate abilities to discern long-term trends of pollutants in a given sampling site. It is advisable to maintain long-term measurements with minimal changes in sample analysis.     

Methodology for designing air quality monitoring networks: I. Theoretical aspects

An objective methodology is presented for determining the number and disposition of ambient air quality stations in a monitoring network for the primary purpose of compliance with air quality standards. The methodolgy utilizes a data base with real or simulated data from an air quality dispersion model for application with a two-step process for ascertaining the optimal monitoring network. In the first step, the air quality patterns in the data base are collapsed into a single composite pattern through a figure-of-merit (FOM) concept. The most desirable locations are ranked and identified using the resultant FOM fields. In the second step the network configuration is determined on the basis of the concept of spheres of influence (SOI) developed from cutoff values of spatial correlation coefficients between potential monitoring sites and adjacent locations. The minimum number of required stations is then determined by deletion of lower-ranked stations whose SOIs overlap. The criteria can be set to provide coverage of less than some fixed, user-provided percentage of the coverage of tha SOIs of the higher ranked stations and for some desired level of minimum detection capability of concentration fluctuations.The methodology is applied in a companion paper (McElroy et al., 1986) to the Las Vegas, Nevada, metropolitan area for the pollutant carbon monoxide.Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency through Contract No. 68-03-2446 to Systems Applications, Inc., it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Estimation of suspended sediment concentration from turbidity measurements using artificial neural networks

Suspended sediment concentration (SSC) is generally determined from the direct measurement of sediment concentration of river or from sediment transport equations. Direct measurement is very costly and cannot be conducted for all river gauge stations. Therefore, correct estimation of suspended sediment amount carried by a river is very important in terms of water pollution, channel navigability, reservoir filling, fish habitat, river aesthetics and scientific interests. This study investigates the feasibility of using turbidity as a surrogate for SSC as in situ turbidity meters are being increasingly used to generate continuous records of SSC in rivers. For this reason, regression analysis (RA) and artificial neural networks (ANNs) were employed to estimate SSC based on in situ turbidity measurements. The SSC was firstly experimentally determined for the surface water samples collected from the six monitoring stations along the main branch of the stream Harsit, Eastern Black Sea Basin, Turkey. There were 144 data for each variable obtained on a fortnightly basis during March 2009 and February 2010. In the ANN method, the used data for training, testing and validation sets are 108, 24 and 12 of total 144 data, respectively. As the results of analyses, the smallest mean absolute error (MAE) and root mean square error (RMSE) values for validation set were obtained from the ANN method with 11.40 and 17.87, respectively. However these were 19.12 and 25.09 for RA. It was concluded that turbidity could be a surrogate for SSC in the streams, and the ANNs method used for the estimation of SSC provided acceptable results.     

Assessment of vehicular pollution in Kolkata, India, using CALINE 4 model

Michigan water quality standards for public bathing beaches require local health departments to collect and analyze a minimum of three water samples for Escherichia coli during each sampling event. The geometric mean number of E. coli colonies is then compared to the 300 colonies per 100 ml standard to determine compliance. This article compares the results of the currently mandated procedure to a composite sampling method, whereby the three samples are mixed in equal volumes and analyzed once. This effectively replaces the geometric mean of the individual sample results with an arithmetic mean. Although arithmetic means are more affected by outliers, this sensitivity to high concentrations is more health conservative than the geometric mean. During the 2007 sampling season, nine bathing beaches were monitored once each week. Three individual point samples and a composite sample were analyzed for each sampling event. No statistically significant differences in bacteria concentrations were found between composite sample analysis and the arithmetic mean of individual point sample analyses. No violations were detected in the 2007 sampling season, so using historical data, a retrospective analysis was performed on samples gathered at nine bathing beaches in Kalamazoo County, Michigan during the years 2001–2007. The arithmetic mean of the three samples taken at each site served as a surrogate composite sample. The benefits of compositing the three samples were investigated assuming a 2/3 reduction in analytical costs. In the traditional sampling method, three individual samples were obtained and analyzed once in every 3-week period during the summer season, whereas compositing was simulated by taking the arithmetic mean of each week’s results. The results of this retrospective cost analysis indicates that ten to 14 violations would have been missed using the less frequent traditional sampling and analysis methodology. Composite sampling is a cost-saving alternative to traditional sampling techniques that can be more protective of public health, particularly when the savings are applied to increased numbers of samples in time or space.     

Using ‘found’ data to augment a probability sample: Procedure and case study

While probability sampling has the advantage of permitting unbiased population estimates, many past and existing monitoring schemes do not employ probability sampling. We describe and demonstrate a general procedure for augmenting an existing probability sample with data from nonprobability-based surveys (found data). The procedure, first proposed by Overton (1990), uses sampling frame attributes to group the probability and found samples into similar subsets. Subsequently, this similarity is assumed to reflect the representativeness of the found sample for the matching subpopulation. Two methods of establishing similarity and producing estimates are described: pseudo-random and calibration. The pseudo-random method is used when the found sample can contribute additional information on variables already measured for the probability sample, thus increasing the effective sample size. The calibration method is used when the found sample contributes information that is unique to the found observations. For either approach, the found sample data yield observations that are treated as a probability sample, and population estimates are made according to a probability estimation protocol. To demonstrate these approaches, we applied them to found and probability samples of stream discharge data for the southeastern US.     

Amperometric Detection of Pesticides Using Polymer Electrodes

Abstact The real time monitoring of some organophosphorus based pesticides is of great concern to environmentalists because the widespread use of pesticides is causing severe health hazards to all living beings and also hampering our ecological balance. The traditional methods of measurement of pesticide residues are time consuming, need sample pre-treatment, and lack desired specificity and accuracy. We have developed an amperometric biosensor for indirect measurement of the pesticide concentration precisely in ppb level. The method is based on the action of two enzymes namely acetylcholine esterase and choline oxidase which are uniquely immobilized in a polymeric porous network directly on the working electrode of a screen-printed sensor. Polyacrylamide matrix has been prepared by copolymerisation of acrylamide andN,N′-methylenebisacrylamide using Potassium peroxodisulphate (K₂S₂O₈) as initiator. A linear relationship was obtained between the range of 0 to 10 ppb.     

土壤重金属监测过程及其质量控制

重点探讨了土壤中典型重金属含量监测过程中样品制备、含水率、预处理等因素对分析结果的影响。实验结果表明,充分风干土壤的含水率在2%～3%左右,200目土壤颗粒度可满足分析精度的要求。硝酸-氢氟酸-高氯酸的多元混酸消解体系可实现对土壤重金属的充分溶解,对标准土壤样品中各元素的回收率可达84%～98%。批次内平行样品以及批次间质控样品各元素的相对标准偏差大都小于10%,符合《土壤环境监测技术规范》的要求,表明该研究建立的系统土壤重金属检测方法结果准确可靠。