Inter-relation between environmental monitoring data,human exposure and health effects

To determine whether a population has been affected by a chemical, evidence of exposure must be established. The mere presence of a chemical in the surroundings of a population may not, in all instances, result in actual exposure. Not all such exposures will cause health effects; nor is it always possible to establish that illness has or will result from exposure to chemicals. The inability to establish health effects in humans cannot a priori be translated to mean that a specific chemical is harmless. On the other hand, it must be determined whether health studies would be fruitful. If exposure was so minimal that no health effects are expected, then no health studies should be conducted.     

Statistical models for evaluating suspected artefacts in long-term environmental monitoring data

Long-term water quality monitoring is of high value for environmental management as well as for research. Artificial level shifts in time series due to method improvements, flaws in laboratory practices or changes in laboratory are a common limitation for analysis, which, however, are often ignored. Statistical estimation of such artefacts is complicated by the simultaneous existence of trends, seasonal variation and effects of other influencing factors, such as weather conditions. Here, we investigate the performance of generalised additive mixed models (GAMM) to simultaneously identify one or more artefacts associated with artificial level shifts, longitudinal effects related to temporal trends and seasonal variation, as well as to model the serial correlation structure of the data. In the same model, it is possible to estimate separate residual variances for different periods so as to identify if artefacts not only influence the mean level but also the dispersion of a series. Even with an appropriate statistical methodology, it is difficult to quantify artificial level shifts and make appropriate adjustments to the time series. The underlying temporal structure of the series is especially important. As long as there is no prominent underlying trend in the series, the shift estimates are rather stable and show less variation. If an artificial shift occurs during a slower downward or upward tendency, it is difficult to separate these two effects and shift estimates can be both biased and have large variation. In the case of a change in method or laboratory, we show that conducting the analyses with both methods in parallel strongly improves estimates of artefact effects on the time series, even if certain problems remain. Due to the difficulties of estimating artificial level shifts, posterior adjustment is problematic and can lead to time series that no longer can be used for trend analysis or other analysis based on the longitudinal structure of the series. Before carrying out a change in analytic method or laboratory, it should be considered if this is absolutely necessary. If changes cannot be avoided, the analysis of the two methods considered, or the two laboratories contracted, should be run in parallel for a considerable period of time so as to enable a good assessment of changes introduced to the data series.     

Beyond data management: how ecoinformatics can benefit environmental monitoring programs

We review ways in which the new discipline of ecoinformatics is changing how environmental monitoring data are managed, synthesized, and analyzed. Rapid improvements in information technology and strong interest in biodiversity and sustainable ecosystems are driving a vigorous phase of development in ecological databases. Emerging data standards and protocols enable these data to be shared in ways that have previously been difficult. We use the U.S. Environmental Protection Agency’s National Coastal Assessment (NCA) as an example. The NCA has collected biological, chemical, and physical data from thousands of stations around the U.S. coasts since 1990. NCA data that were collected primarily to assess the ecological condition of the U.S. coasts can be used in innovative ways, such as biogeographical studies to analyze species invasions. NCA application of ecoinformatics tools leads to new possibilities for integrating the hundreds of thousands of NCA species records with other databases to address broad-scale and long-term questions such as environmental impacts, global climate change, and species invasions.     

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.     

An approach to the assessment of the quality of environmental monitoring data

This paper reports an approach to the assessment of the validity of environmental monitoring data--a 'data filter'. The strategy has been developed through the UK National Marine Analytical Quality Control (AQC) Scheme for application to data collected for the UK National Marine Monitoring Plan, although the principles described are applicable more widely. The proposed data filter is divided into three components: Part A, 'QA/QC'--an assessment of the laboratory's practices in Quality Assurance/Quality Control; Part B, 'fitness for purpose'--an evaluation of the standard of accuracy that can be demonstrated by activities in (A), in relation to the intended application of the data; and Part C, the overall assessment on which data will be accepted as usable or rejected as being of suspect quality. A pilot application of the proposed approach is reported. The approach described in this paper is intended to formalise the assessment of environmental monitoring data for fitness for a chosen purpose. The issues important to fitness for purpose are discussed and assigned a relative priority order on which to judge the reliability/usefulness of monitoring data.     

Industrial effluent quality, pollution monitoring and environmental management

Royal Commission Environmental Control Department (RC-ECD) at Yanbu industrial city in Kingdom of Saudi Arabia has established a well-defined monitoring program to control the pollution from industrial effluents. The quality of effluent from each facility is monitored round the clock. Different strategic measures have been taken by the RC-ECD to implement the zero discharge policy of RC. Industries are required to pre-treat the effluent to conform pretreatment standards before discharging to central biological treatment plant. Industries are not allowed to discharge any treated or untreated effluent in open channels. After treatment, reclaimed water must have to comply with direct discharge standards before discharge to the sea. Data of industrial wastewater collected from five major industries and central industrial wastewater treatment plant (IWTP) is summarized in this report. During 5-year period, 3,705 samples were collected and analyzed for 43,436 parameters. There were 1,377 violations from pretreatment standards from all the industries. Overall violation percentage was 3.17%. Maximum violations were recorded from one of the petrochemical plants. The results show no significant pollution due to heavy metals. Almost all heavy metals were within RC pretreatment standards. High COD and TOC indicates that major pollution was due to hydrocarbons. Typical compounds identified by GC-MS were branched alkanes, branched alkenes, aliphatic ketones, substituted thiophenes, substituted phenols, aromatics and aromatic alcohols. Quality of treated water was also in compliance with RC direct discharge standards. In order to achieve the zero discharge goal, further studies and measures are in progress.     

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.     

Electrochemical sensors for environmental monitoring: design, development and applications

The advancement in miniaturization and microfabrication technology has led to the development of sensitive and selective electrochemical devices for field-based and in situ environmental monitoring. Electrochemical sensing devices have a major impact upon the monitoring of priority pollutants by allowing the instrument to be taken to the sample (rather than the traditional way of bringing the sample to the laboratory). Such devices can perform automated chemical analyses in complex matrices and provide rapid, reliable and inexpensive measurements of a variety of inorganic and organic pollutants. Although not exhaustive due to the vast amounts of new and exciting electrochemical research, this review addresses many important advances in electrochemical sensor design and development for environmental monitoring purposes. Critical design factors and development issues including analytical improvements (e.g. detection limits), microfabrication and remote communication are presented. In addition, modern environmental applications will be discussed and future perspectives considered.     

我国环境监测仪器向规范化方向发展刍议

从我国环境监测事业发展和建立社会主义市场经济体制的需要，论述了加速我国环境监测仪器规范化的必要和可行性，并阐述了具体实施意见。     

The use of sensor arrays for environmental monitoring: interests and limitations

Continuous, in situ monitoring of air, water and land quality is fundamental to most environmental applications. Low cost and non-invasive chemical sensor arrays provide a suitable technique for in situ monitoring. Their ability and performance under realistic conditions is discussed in this paper. Published studies report promising results despite a number of limitations that are associated with both the technology itself and its application in ever changing ambient conditions. Early investigations include the analysis of single substances as well as odour and wastewater organic load monitoring. Reported applications typically highlight the sensitivity of the currently available sensors to changes in temperature, humidity and flow rate. Two types of approaches are recommended to deal with these effects: either working under fixed experimental conditions or measuring the external parameters to numerically compensate for their change. The main challenge associated with the use of non-specific sensor arrays lies in establishing a relationship between the measured multivariate signals and the standards metrics that are traditionally used for quality assessment of gas mixtures. For instance, odour monitoring requires calibration against olfactometric measurements while investigations of wastewater samples still need to be correlated with organic pollution parameters such as BOD, COD or TOC. On the other hand, results obtained in the field have demonstrated how sensor arrays can be readily used as simple alarm devices or as early warning systems based on a general air/water quality index.     

Statistical and nonstatistical considerations for environmental monitoring studies

In environmental studies statistics is too often used as a salvage operation, or as an attempt to show significance in the absence of any clear hypothesis. Good design is needed, not fancier statistics. Too often we pursue short-term problems that are in fashion rather than study long-term environmental deterioration that really matters. Since change-often unpredictable change-is an intrinsic part of nature, it is pointless to fight all environmental change. We must choose our level of concern and then influence environmental change where we can. The judgement on whether a given change is bad cannot be left to the statistician or to statistical tests; the politician in consultation with the ecologist are responsible for it. The statistical significance of a hypothesized impact-related change should be tested against year-to-year variation in the unimpacted situation rather than against replicate sampling error. This is another argument for long-term studies. Attributes of good design and appropriate criterion and predictor variables are discussed.Paper presented at a Symposium held on 20–21 April 1982, in Edmonton, Alberta, Canada.     

Comparison of ordinary and lognormal kriging on skewed data of total cadmium in forest soils of Sweden

Spatial statistical analysis of georeferenced data of total cadmium (TCd) in forest soils of Sweden was assumed to providemore advantageous maps than traditional interpolated maps. However, 264 measurements of TCd in O-horizon of forest soils displayed skewed frequency distribution. Since atypicalobservations affect badly the variogram, outliers wereidentified, different data transformations were tested andordinary (OK) and lognormal kriging (LK) scenarios werecompared based on cross-validation. Results were comparedusing overall measures of predictors, e.g. traditionalmean squared prediction error (MSPE), mean of krigingvariances, variance ratio, median of internallystandardised residuals, and assessments of classificationaccuracy, such as percentage of correctly predictedsamples and within-class MSPE.One outlier was identified based on the absolute value of skewness of value differences less or equal to one in data pairs separated at certain lag classes. Mapping categories characterised by percentage of correct classification and within-class MSPE were found to be essential in comparison of kriging results additionally to the overall measures. In comparison of kriging methods, OK predicted high values moreaccurately and LK was more effective to predict low and mediumvalues. Thus, OK was suggested for mapping high concentration of TCd and other pollutants. Percentage of correctly predictedsamples and within-class MSPE were found to be dependent on kriging method, as well as on the number and limits of categories.     

The mini mobile environmental monitoring unit: a novel bio-assessment tool

This paper introduces a new bio-assessment tool, the mini-mobile environmental monitoring unit (MMU). The MMU is a portable, lightweight, energy-efficient, miniaturized laboratory that provides a low-flow system for on-site exposure of aquatic animals to local receiving waters in a protected, controllable environment. Prototypes of the MMU were tested twice in week-long studies conducted during the summers of 2008 and 2009, and in a 12-day study in 2010. In 2008, fathead minnows and polar organic chemical integrative samplers (POCIS) were deployed downstream from the Hastings, Nebraska wastewater treatment plant (WWTP), a waterway known to contain estrogenic contaminants in biologically active concentrations. In 2009, minnows and POCIS were deployed downstream, upstream and within the Grand Island, Nebraska WWTP, a site where the estrogenic contaminants had been detected, but were found at levels below those necessary to directly impact fish. In 2010, an advanced prototype was tested at the Sauk Center, Minnesota WWTP to compare its performance with that of traditional fish exposure methods including caged fish and static-renewal laboratory testing of effluent. Results from the prototype illustrate the capabilities of the MMU and offer an inexpensive monitoring tool to integrate the effects of pollutant sources with temporally varying composition and concentration.     

Development of low-cost ammonia gas sensors and data analysis algorithms to implement a monitoring grid of urban environmental pollutants

The present study is focused on the implementation of a novel, low cost, urban grid of nanostructured chemresistor gas sensors for ammonia concentration ([NH(3)]) monitoring, with NH(3) being one of the main precursors of secondary fine particulate. Low-cost chemresistor gas sensors based on carbon nanotubes have been developed, their response to [NH(3)] in the 0.17-5.0 ppm range has been tested, and the devices have been properly calibrated under different relative humidity conditions in the 33-63% range. In order to improve the chemresistor selectivity towards [NH(3)], an Expert System, based on fuzzy logic and genetic algorithms, has been developed to extract the atmospheric [NH(3)] (with a sensitivity of a few ppb) from the output signal of a model chemresistor gas sensor exposed to an NO(2), NO(X) and O(3) gas mixture. The concentration of these pollutants that are known to be the most significant interfering compounds during ammonia detection with carbon nanotube gas sensors has been tracked by the ARPA monitoring network in the city of Milan and the historical dataset collected over one year has been used to train the Expert System.     

Some international activities in environmental health monitoring and surveillance

Environmental health monitoring and surveillance include activities such as collection of information on the production and use of chemicals; preparation of inventories of waste discharges; measurement of physical, chemical and biological agents in air, water and food, at work place and at home; epidemiological investigations, and collection and analysis of environmental, and health statistical data. There are two main objectives of these activities: estimation of human exposure to potentially harmful environmental factors and timely detection of adverse health effects; and the assessment of environmental conditions in relation to established guidelines and standards. Environmental health monitoring and surveillance projects initiated, organized and implemented by the Specialized Agencies and other bodies of the United Nations system include monitoring of air and water quality and of food and animal feed contamination; pilot projects on air pollution exposure assessment and biological monitoring; and ionizing radiation surveillance. Principles of environmental and health monitoring in occupational environment, and of monitoring and surveillance of environmental health effects are outlined. Two examples are provided of national environmental health surveillance systems.Revised and up-dated text of a paper presented at the World congress on Environmental Health in Development Planning, Mexico City, November 1979.Formerly Manager, Environmental Health Criteria and Standards, and Chief Central Unit, International Programme on Chemical Safety, Division of Environmental Health, World Health Organization, Geneva, Switzerland.     

A cost-precision model for marine environmental monitoring,based on time-integrated averages

Ongoing marine monitoring programs are seldom designed to detect changes in the environment between different years, mainly due to the high number of samples required for a sufficient statistical precision. We here show that pooling over time (time integration) of seasonal measurements provides an efficient method of reducing variability, thereby improving the precision and power in detecting inter-annual differences. Such data from weekly environmental sensor profiles at 21 stations in the northern Bothnian Sea was used in a cost-precision spatio-temporal allocation model. Time-integrated averages for six different variables over 6 months from a rather heterogeneous area showed low variability between stations (coefficient of variation, CV, range of 0.6–12.4%) compared to variability between stations in a single day (CV range 2.4–88.6%), or variability over time for a single station (CV range 0.4–110.7%). Reduced sampling frequency from weekly to approximately monthly sampling did not change the results markedly, whereas lower frequency differed more from results with weekly sampling. With monthly sampling, high precision and power of estimates could therefore be achieved with a low number of stations. With input of cost factors like ship time, labor, and analyses, the model can predict the cost for a given required precision in the time-integrated average of each variable by optimizing sampling allocation. A following power analysis can provide information on minimum sample size to detect differences between years with a required power. Alternatively, the model can predict the precision of annual means for the included variables when the program has a pre-defined budget. Use of time-integrated results from sampling stations with different areal coverage and environmental heterogeneity can thus be an efficient strategy to detect environmental differences between single years, as well as a long-term temporal trend. Use of the presented allocation model will then help to minimize the cost and effort of a monitoring program.     

The use of simple kinetic models to help design environmental monitoring systems

This paper describes the application of simple linear models to help design environmental monitoring systems. This process involves five steps: (1) The derivation of a schematic of the identified pollutant's transport and fate. (2) The derivation of the equation in the schematic. (3) Estimation of input data and numerical solution. (4) Comparison with initial field data. (5) Design of a monitoring system.Two examples of how this system was applied under field conditions are given. Advantages of this approach are: (1) It forces a consideration of the system as a whole rather than a series of distinct environmental components. (2) It forces a consideration of the physical-chemical and biological factors effecting pollutant transport in the system. (3) It sets up an analytical procedure for data analysis at the time the monitoring system is designed. (4) It helps show the functional relationship between pollutant levels in different environmental media. (5) It identifies points where sampling design could be changed to provide for a more efficient monitoring system. (6) It identifies gaps in our knowledge base.     

On applications of remote sensing for environmental monitoring

Modern airborne and satellite remote sensing techniques offer attractive opportunities to coastal monitoring systems. Improvements of the evaluation of larger scales phenomena and processes due to the synopticity of the remote sensing data are of particular interest. However, some uncertainties and limitations about remote sensing must be considered. Microwave, infrared and visible radiation methods and their applications are briefly discussed and some applications are demonstrated. Special attention is paid to the remote sensing of various pollutants in the sea, in particular with respect to oil pollution.Promising developments of the remote sensing methods for coastal monitoring are to be expected from the European remote sensing satellite missions ERS 1 and ERS 2.Combination of these observations with simultaneous in situ measurements from ships (sea truth) appears to be most advantageous for the interpretation of the collected data.     

和田地区环境监测质量管理工作初探

结合和田地区环境监测站环境监测质量管理现状,就提高环境监测质量管理水平,充分发挥其在环境管理中的基础性作用,初步探讨了环境质量管理的必要性和基本思路。