Quality assurance and quality control in monitoring programs

There are three general characteristics of the data to be collected in a monitoring program that should be met in order to maximize the use and value of the data: the data quality should be known, the data type and quality should be consistent and comparable, and the data should be available and accessible. Potential problems with each of these characteristics are addressed effectively by quality assurance and quality control. One of the most important aspects of quality assurance in a monitoring program is the development of a quality assurance plan, which should identify clearly the quality of the data needed and describe in detail the planned actions to provide confidence that the program will meet its stated objectives.Quality control data, which allow for the quality and suitability of the environmental data to be evaluated and ascertained, should be collected and utilized as an integral part of the QA effort associated with a monitoring program.     

Quality control and quality assurance for particle size distribution measurements at an urban monitoring station in Augsburg, Germany

Long-term observations of atmospheric constituents such as aerosol particles are increasingly needed to assess their impact on climate and human health. In contrast to particle mass concentration (MC), there are currently no standardized quality control (QC) and quality assurance (QA) procedures for the measurement of particle size distribution (PSD). This study describes some fundamental QC and QA procedures associated with the collection and evaluation of a 2 year dataset between 2005 and 2006 at an urban background monitoring site in Augsburg, Germany. The considered parametres include ambient PSD between 3 nm and 10 microm (merged from a twin differential mobility and an aerodynamic particle sizer, TDMPS and APS, respectively) as well as total particle number (TNC), length (LC) and MC determined by independent instruments. The hourly 1st and 0th moment of PSD showed good correlations with the independently measured LC (R(2) = 0.86) and TNC (R(2) = 0.79), respectively, the deviation for LC with 4% and for TNC with 22% being rather small. The volume concentration (3rd moment) of hourly measured PSD and the resultant MC (when assuming a realistic apparent density of 1.5 g cm(-3)) correlated well with the independently measured MC of PM(2.5) or PM(10) (R(2) > 0.86) and showed only small deviation from PM(2.5) (1%) or PM(10) (5%), respectively. The study demonstrates that the described QC and QA measures define both a high accuracy of the PSD measurements and their long-term comparability against data obtained in similar measurement programmes.     

城市污水中PCBs的分析及其QA/QC研究

报道了一种城市污水中痕量PCBs的分析方法,并进行了QA/QC研究,采用二氯甲烷萃取剂对城市污水进行液-液萃取,联合运用浓硫酸和硅胶层析柱将PCBs与杂质分离,以毛细管GC-ECD和内标法对PCBs定量.空白加标回收试验得出,PCBs的回收率为58%～125%,标准偏差为0.00173～0.00778μg/L,相对标准偏差为1.58%～12.43%.以实际城市污水作为加标基质,得出加入污水中的19种PCBs的分析方法回收率为57.6%～129.2%,方法的检测限为0.010～0.056μg/L,满足了US EPA对PCBs回收率要求.经过3次平行测定,测得实际城市污水中PCBs含有9种PCBs,PCBs总量的平均值为0.0235μg/L,相对标准偏差为9.63%,该分析方法所需的仪器简便、容易操作.     

城市环境空气质量监测网格实测法优化布点研究质量保证

质量保证体系是网格实测法环境空气质量监测优化布点研究工作的重要组成 ,该体系可确保实测数据准确可靠和研究成果质量 ,具有可操作性并已在实践中应用 ,取得满意效果     

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.     

Characterization and validation of a Portuguese natural reference soil to be used as substrate for ecotoxicological purposes

This study describes the first attempt to validate a Portuguese natural soil (PTRS1) to be used as reference soil for ecotoxicological purposes, aimed to both: (i) obtain ecotoxicological data for the derivation of Soil Screening Values (SSVs) with regional relevance, acting as a substrate to be spiked with ranges of concentrations of the chemicals under evaluation and (ii) act as control and as substrate for the dilution of contaminated soils in ecotoxicological assays performed to evaluate the ecotoxicity of contaminated soils, in tier 2 of risk assessment frameworks, applied to contaminated lands. The PTRS1 is a cambisol from a granitic area integrated in the Central Iberian Zone. After chemical characterization of the soil in terms of pseudo-total metals, PAHs, PCBs and pesticide contents, it was possible to perceive that some metals (Ba, Be, Co, Cr and V) surpass the Dutch Target Values (Dtvs) corrected for the percentage of organic matter and clay of the PTRS1. Nevertheless, these metals displayed total concentrations below the background total concentrations described for Portuguese soils in general. The same was observed for aldrin, endosulfan I, endosulfan II, heptachlor epoxide, and heptachlor; however the Dtvs corrected become negligible. The performance of invertebrate and plant species, commonly used in standard ecotoxicological assays, was not compromised by both soil properties and soil metal contents. The results obtained suggest that the PTRS1 can be used as a natural reference soil in ecotoxicological assays carried out under the scope of ecological risk assessment.     

The role of metadata and strategies to detect and control temporal data bias in environmental monitoring of soil contamination

It is crucial for environmental monitoring to fully control temporal bias, which is the distortion of real data evolution by varying bias through time. Temporal bias cannot be fully controlled by statistics alone but requires appropriate and sufficient metadata, which should be under rigorous and continuous quality assurance and control (QA/QC) to reliably document the degree of consistency of the monitoring system. All presented strategies to detect and control temporal data bias (QA/QC, harmonisation/homogenisation/standardisation, mass balance approach, use of tracers and analogues and control of changing boundary conditions) rely on metadata. The Will Rogers phenomenon, due to subsequent reclassification, is a particular source of temporal data bias introduced to environmental monitoring here. Sources and effects of temporal data bias are illustrated by examples from the Swiss soil monitoring network. The attempt to make a comprehensive compilation and assessment of required metadata for soil contamination monitoring reveals that most metadata are still far from being reliable. This leads to the conclusion that progress in environmental monitoring means further development of the concept of environmental metadata for the sake of temporal data bias control as a prerequisite for reliable interpretations and decisions.     

谈监测仪器的质量控制标准与维护管理

监测仪器是从事环境监测工作必不可少的工具。我国环保事业对监测仪器的需求量越来越大,仪器也越来越复杂。本文就监测仪器的质量控制标准与管理问题进行了探讨,以求最大限度地发挥监测仪器设备的效能,使我国监测科研工作提高到一个新水平。     

Dermal exposure to pesticides in greenhouses workers: discrimination and selection of variables for the design of monitoring programs

Dermal exposure to pesticides is one of the main sanitaryproblems which greenhouses workers face. With the dual aimsof establishing both the body part that receives the greatestexposure and the variable that has greatest influence on this exposure level, 22 pesticide application trials were performed. Trials were carried out in different greenhouse vegetable crops,using different pesticides and different spray diameters from the spray gun. In order to determine dermal exposure, the wholebody method was used. Pieces of the applicator suit were subject to an extraction procedure and their pesticide contentdetermined using GC-NPD analysis. Multivariate analysis were applied to the data obtained. Principal component analysis showed that all trials produced a high exposure level on lowerleft leg and lower right leg. Cluster analysis distinguished between three sample groups. The most and the least affectedparts were clearly distinguished. Discriminant analysis indicated that the thin drop size of the spray gun is responsible for both the differences between groups and the minimum or maximum exposure level measured on the applicatorsuit. Therefore, selecting the variables, lower legs and thindrop size, is considered fundamental in designing programs formonitoring pesticide exposure.     

On the use of multivariate statistical methods for combining in-stream monitoring data and spatial analysis to characterize water quality conditions in the White River Basin,Indiana, USA

Mechanistic hydrologic and water quality models provide useful alternatives for estimating water quality in unmonitored streams. However, developing these elaborate models for large watersheds can be time-consuming and expensive, in addition to challenges that arise during calibration when there is limited spatial and/or temporal monitored in-stream water quality data. The main objective of this research was to investigate different approaches for developing multivariate analysis models as alternative methods for rapidly assessing relationships between spatio-temporal physical attributes of the watershed and water quality conditions in monitored streams, and then using the developed relationships for estimating water quality conditions in unmonitored streams. The study compares the use of various statistical estimates (mean, geometric mean, trimmed mean, and median) of monitored water quality variables to represent annual and seasonal water quality conditions. The relationship between these estimates and the spatial data is then modeled via linear and non-linear multivariate methods. Overall, the non-linear techniques for classification outperformed the linear techniques with an average cross-validation accuracy of 79.7%. Additionally, the geometric mean based models outperformed models based on other statistical indicators with an average cross-validation accuracy of 80.2%. Dividing the data into annual and quarterly datasets also offered important insights into the behavior of certain water quality variables impacted by seasonal variations. The research provides useful guidance on the use and interpretation of the various statistical estimates and statistical models for multivariate water quality analyses.     

New procedures for simultaneous determination of mesotrione and atrazine in water and soil. Comparison of the degradation processes of mesotrione and atrazine

A method for the determination of residues of mesotrione, atrazine and its degradation products: deethylatrazine, hydroxyatrazine, deisopropylatrazine, desethyldesisopropylatrazine in a variety of water and soil matrices has been developed. Mesotrione is a new selective herbicide for use in corn, which has been substituted for atrazine, which has been banned in European Union countries since 2007. Although atrazine has not been used for three vegetative periods, it is still detected in the environment. The analysis was conducted by means of ultra-high-pressure liquid chromatography with ultraviolet detection and liquid chromatography with diode array detection. The procedures for analyte separation from water and soil matrices were also established. The optimal conditions for solid-phase extraction (SPE) were determined. The recoveries were compared with that obtained by means of SPE. Method fortification recoveries from water samples averaged 78–97% and for soil 80–97% depending on the analyte and type of sample. The limits of detection were 0.04–0.61 μg/L for water samples and for soil samples 0.02–0.88 μg/g. The soil samples were collected in spring 2009 from three different fields with water samples being made from effluents from these fields. Samples collection was conducted in the day of mesotrione (Callisto 100SC) application and then done weekly, until the mesotrione concentration was below the limit of quantification. The results enabled the monitoring of mesotrione degradation in soil and its permeability into surface waters; simultaneously, the same studies were conducted for atrazine.     

Many roads may lead to Rome: Selected features of quality control within environmental assessment systems in the US,NL, CA,and UK

As there is no one-and-only concept on how to precisely define and establish quality control (QC) or quality assurance (QA) in the making of environmental assessments (EA), this paper presents selected features of international approaches that address quality in EA systems in the USA, the Netherlands, Canada, and the United Kingdom. Based on explanative case studies, we highlight the embedding of specific quality control features within the EA systems, the objectives and processes, and relevant transparency challenges. Such features of QC/QA approaches can be considered in cases where substantial quality control and assurance efforts are still missing. Yet further research needs to be conducted on the efficacy of these approaches, which remains beyond the scope of this study.     

Application of QUAL2Kw for water quality modeling and dissolved oxygen control in the river Bagmati

A stream water quality model, QUAL2Kw, was calibrated and validated for the river Bagmati of Nepal. The model represented the field data quite well with some exceptions. The influences of various water quality management strategies have on DO concentrations were examined considering: (i) pollution loads modification; (ii) flow augmentation; (iii) local oxygenation. The study showed the local oxygenation is effective in raising DO levels. The combination of wastewater modification, flow augmentation and local oxygenation is necessary to ensure minimum DO concentrations. This reasonable modeling guarantees the use of QUAL2Kw for future river water quality policy options.     

Evaluation of the effect of data pre-treatment procedures on classical pattern recognition and principal components analysis: a case study for the geographical classification of tea

A simple transformation that uses the half-range and central value has been used as a data pre-treatment procedure for principal component analysis (PCA) and pattern recognition techniques. The results obtained have been compared with the results from classical normalisation of data (mean normalisation, maximum normalisation and range normalisation), autoscaling and the minimum-maximum transformation. Three data sets were used in the study. The first was formed by determining 17 elements in 53 tea samples (901 pieces of data). The second and third data sets arose from two long-term drift studies performed to examine instrumental stability at standard and robust conditions. The instruments used were an inductively coupled plasma atomic emission spectrometer and an inductively coupled plasma mass spectrometer. Each drift diagnosis experiment consisted of replicate determinations of a test solution containing 15 analytes at 10 mg l-1 over 8 h without recalibration. Twenty-nine emission lines were determined 99 times, thus, each data set was formed by 2881 pieces of data. Data pre-treatment was applied to the three data sets prior to the use of principal component analysis, cluster analysis, linear discrimination analysis and soft independent modelling of class analogy. The study revealed that the half-range and central value transformation resulted in a better classification of the tea samples than that achieved using the classical normalisation. The loadings in the PCA for the long-term stability study, under both standard and robust conditions, were found to be similar to the drift trends only when the minimum-maximum transformation and the mean or maximum normalizations were used as data pre-treatments.     

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.     

Re-construction of the shut-down PM10 monitoring stations for the reliable assessment of PM10 in Berlin using fuzzy modelling and data transformation

A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It endeavours to find the non-linear relationship between the hourly PM10 concentration of both the still operating and the shut-down PM10 monitoring stations by using a fuzzy modelling technique, called modified active learning method (MALM). In addition, the simulations were performed by using not only raw PM10 databases but also log-transformed PM10 databases for skewness reduction. According to the results of hourly PM10 simulation (root mean square error about 13.0 μg/m³, correlation coefficient 0.88), the shut-down stations have been appropriately simulated and the idea of dense monitoring network development by the re-construction of the shut-down stations was realised. The results of simulations using raw and log-transformed databases showed that data transformation has no significant effect on the performance of MALM in the simulation of shut-down PM10 stations. By the combination of the 11 still operating stations and the 20 re-constructed stations, a dense monitoring network was generated for Berlin and was utilised for the calculation of the reliable monthly and mean annual PM10 concentration for five different PM10 zones in Berlin (the suburban-background, urban-background, urban-traffic, rural-background and suburban-traffic areas). The results showed that the mean annual concentration of PM10 at the five zones increased by about 13.0% in 2014 (26.3 μg/m³) in comparison with 2013 (23.3 μg/m³). Furthermore, the mean annual concentration of PM10 in the traffic lanes of the suburban (2013 25.0 μg/m³, 2014 26.9 μg/m³) and urban (2013 27.7 μg/m³, 2014 31.3 μg/m³) areas is about 14 and 20% higher than the PM10 concentration of suburban-background (2013 21.3 μg/m³, 2014 24.5 μg/m³) and urban-background (2013 23.0 μg/m³, 2014 26.1 μg/m³) areas, respectively.     

Using a neural network approach and time series data from an international monitoring station in the Yellow Sea for modeling marine ecosystems

The international marine ecological safety monitoring demonstration station in the Yellow Sea was developed as a collaborative project between China and Russia. It is a nonprofit technical workstation designed as a facility for marine scientific research for public welfare. By undertaking long-term monitoring of the marine environment and automatic data collection, this station will provide valuable information for marine ecological protection and disaster prevention and reduction. The results of some initial research by scientists at the research station into predictive modeling of marine ecological environments and early warning are described in this paper. Marine ecological processes are influenced by many factors including hydrological and meteorological conditions, biological factors, and human activities. Consequently, it is very difficult to incorporate all these influences and their interactions in a deterministic or analysis model. A prediction model integrating a time series prediction approach with neural network nonlinear modeling is proposed for marine ecological parameters. The model explores the natural fluctuations in marine ecological parameters by learning from the latest observed data automatically, and then predicting future values of the parameter. The model is updated in a “rolling” fashion with new observed data from the monitoring station. Prediction experiments results showed that the neural network prediction model based on time series data is effective for marine ecological prediction and can be used for the development of early warning systems.     

以北运河（北京段）为例模拟评估北京市“水十条”水质改善效果

基于MIKE11构建北运河(北京段)一维水质模型,以氨氮、COD为目标污染物,建立污染源与水质响应关系。以2013年为基准年,考虑不同人口疏解情景预测2020年北运河(北京段)流域人口,并结合北京市"水十条"设置减排情景方案,对2020年水质改善效果进行量化评估。模拟结果表明:北京市"水十条"可实现显著的水质改善效果,到2020年,在中人口疏解方案下,北运河氨氮、COD平均质量浓度相比2013年分别下降40.8%~77.7%、39.3%~59.7%。COD质量浓度可稳定达标,氨氮质量浓度离达标还有一定差距,但日浓度可稳定在8mg/L以下,基本消除了黑臭水体。     

Water quality status and trends in agriculture-dominated headwaters; a national monitoring network for assessing the effectiveness of national and European manure legislation in The Netherlands

Large nutrient losses to groundwater and surface waters are a major drawback of the highly productive agricultural sector in The Netherlands. The resulting high nutrient concentrations in water resources threaten their ecological, industrial, and recreational functions. To mitigate eutrophication problems, legislation on nutrient application in agriculture was enforced in 1986 in The Netherlands. The objective of this study was to evaluate this manure policy by assessing the water quality status and trends in agriculture-dominated headwaters. We used datasets from 5 agricultural test catchments and from 167 existing monitoring locations in agricultural headwaters. Trend analysis for these locations showed a fast reduction of nutrient concentrations after the enforcement of the manure legislation (median slopes of ?0.55 mg/l per decade for total nitrogen (N-tot) and ?0.020 mg/l per decade for total phosphorus (P-tot)). Still, up to 76 % of the selected locations currently do not comply with either the environmental quality standards (EQSs) for nitrogen (N-tot) or phosphorus (P-tot). This indicates that further improvement of agricultural water quality is needed. We observed that weather-related variations in nutrient concentrations strongly influence the compliance testing results, both for individual locations and for the aggregated results at the national scale. Another important finding is that testing compliance for nutrients based on summer average concentrations may underestimate the agricultural impact on ecosystem health. The focus on summer concentrations does not account for the environmental impact of high winter loads from agricultural headwaters towards downstream water bodies.     

Development of a software package for trend detection in temporal series: Application to water and industrial effluent quality data for the St. Lawrence River

Despite the considerable amount of effort and resources involved in monitoring water quality, water quality assessment and environmental follow-up are sometimes carried out with simple statistics, the main reason being the lack of appropriate statistical methods adapted to the nature of sampled water quality data.A survey of the classical methods used for trend detection and of their limitations is first presented, including the most recent non-parametric techniques adapted to the structure of the sampled data and to the possible types of trends occuring. This paper then presents an interactive user-friendly software package developed for microcomputers making use of these latest adapted techniques. Afterwards, some applications of the software are described pertaining to the concentrations measured at long-term stations on the St. Lawrence River and to the mass loadings discharged by regulated industries. Finally, conclusions are drawn about the assumptions, performance and limitations of the package as well as about the research needs to improve the usefulness and applicability of the software.