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.     

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.     

Designing Environmental Databases for Statistical Analyses

The Environmental Monitoring and Assessment Program (EMAP) collects data that are used to statistically assess the environmental condition of large geographic regions. These data are then posted on the EMAP web site so that anyone can use them. Databases used for the statistical analyses, "analytical" databases, differ in design from the "general-use" databases used by a secondary audience. Their scope is usually restricted in time, in geographic extent, and in type and content of data, often being limited to a single scientific discipline. Their structure may be more horizontal than vertical, so that statistical programs can import the data easily. Their design is strongly influenced by the nature of the scientific analysis because the goal is to create a good computing environment for that analysis. We illustrate these aspects of design with an analytical database for estuaries in the U.S. mid-Atlantic region.     

Biomonitoring and environmental management

The advantages of biological monitoring of the environment have been long recognised. Direct measurements on biota of importance rather than the use of chemical surrogates, integration over time and the ability to measure the perhaps subtle changes brought about by minor or intermittent pollution have all been propounded as adantages.There appear to be a variety of barriers to the wider adoption of biomonitoring approaches. The perception that biomonitoring takes longer and is more expensive than chemical monitoring. The idea that chemical measurements are an adequate surrogate for direct measurements of biological change. The belief that interpretation of biological data is complex and uncertain in comparison with chemical data. These widely held myths are addressed and some broad principles to guide the development of biomonitoring programs are developed.     

The coastal component of the U.S. integrated ocean observing system

The combined effects of human activities and natural variability present significant challenges to the goals of protecting, restoring, and sustaining coastal ecosystems. Meeting these challenges and resolving conflicts in an informed fashion will require: (1) more timely detection and prediction of environmental changes and their consequences; and (2) more timely access to relevant environmental information. The achievement of these goals depends on the development of a sustained and integrated coastal ocean observing system (ICOOS) that insures timely access to the data and information required to improve: (1) climate predictions and the effects of changes in the weather on coastal populations; (2) efforts to sustain and restore healthy coastal marine ecosystems and living marine resources; and (3) compliance monitoring and evaluations of the efficacy of environmental policies. Although the responsible federal and state agencies all require similar environmental information, many separate programs have evolved for collecting, managing, and analyzing data for various purposes. Consequently, there is too much redundancy; access to diverse data from disparate sources is limited and time consuming; and individual programs are inevitably underfunded and too limited in scope. A system is needed that coordinates and integrates many of the elements of these programs to minimize redundancy, be more comprehensive, provide more timely access to data and information, and satisfy the information needs of a greater number of user groups in a more cost-effective fashion. This is the purpose of the ICOOS.     

涉刑环境监测中有待解决的若干技术问题及对策建议

指出了涉刑环境监测工作中，司法鉴定机构的资质及监测数据认可、环保标准与规范、固体废物监测等方面存在的问题。提出，涉刑监测单位应尽快获取司法鉴定机构资质；国家层面应给出涉刑监测数据认可的指导性意见；加快环境标准制修订工作，增强标准的适用性和可操作性；修订《危险废物鉴别技术规范》（HJ/T 298-2007）和相应系列鉴别标准。     

A comparison of data quality control protocols for atmospheric mercury speciation measurements

Significant advances in the measurement of atmospheric mercury species have been made in the past 10 years yet limited protocols on quality control (QC) and assurance on this data have been published in the literature. Recently, considerable work has been done to develop quality control and assurance programs within North America. Environment Canada and the National Atmospheric Deposition Network (NADP) independently developed programs, RDMQ? and AMQC, respectively, to QC atmospheric mercury speciation data (including gaseous elemental mercury (GEM), reactive gaseous mercury (RGM) and mercury associated to particles (PHg)). These 2 programs were assessed by the criteria on which the data is QCed and comparability of the final data products. Results show that the criteria used to flag data compare well within the 4 tested sites and that the number of flags for each criterion is generally comparable. The QC programs were applied to 2 distinct data sets and the final QCed data was compared. From a mid-latitude site, the final data sets compare very well and showed there to be a 0.3, 8.6 and 15% difference in the mean GEM, RGM and PHg concentrations post QC of each program. It is recommended that either the RDMQ or the AMQC programs be employed for a typical mid-latitude site. When the QC programs were applied to highly variable data, the data do not compare as well for RGM and PHg. Results showed a 2.7, 27 and 33% difference in the mean GEM, RGM and PHg concentrations, respectively, post QC of each program. It is recommended that RDMQ be used for data that is highly variable with high RGM/PHg concentrations as it allows for more manual correction over the QCed data. This investigation of 2 QC programs produced comparable data and that either of these programs can be used as standard methods for the quality control of atmospheric mercury speciation data.     

The need for long-term stream monitoring programs in forest ecosystems of the Pacific Northwest

Concepts, planning and design procedures are examined that are needed in the development of long-term stream monitoring programs in forested regions. A long-term stream monitoring program is viewed as the key component for bringing together management organizations, researchers and decision-makers to improve the management of natural resources. The keystones of such ecosystem monitoring are long-term data records that provide the basis for analysis of environmental assessment objectives, predictions and analysis of outcomes which in-turn can be used to modify and improve future projects. Management organizations that initiate long-term monitoring programs are urged to use monitoring actions and information to facilitate decision-making processes that pertain to conserving and allocating resources for future beneficial uses. Recommendations are provided for careful planning and definition of interactive activities of monitoring programs and that should provide information feedbacks that can be used to evaluate issues pertaining to beneficial uses of resources. Procedural requirements and literature sources are suggested for developing long-term stream monitoring programs. They include reviews of background and historical information to provide precise definitions of long-term objectives, planning considerations and monitoring methods. Examples are given of specific procedures that need to be identified during the planning process. They include the application of management standards to variable conditions encountered within natural ecosystems and the detection of the timing of recovery phases of stream ecosystem development following a disturbance. These procedures are viewed as being essential for improving applications of management standards and perceived thresholds to stream and watershed ecosystems monitoring programs.     

新《大气污染防治法》施行,环境监测数据面临考验

新修订的《中华人民共和国大气污染防治法》确立了超标排污违法的法律地位 ,监测数据将作为实施环境行政处罚的依据。文章从行政处罚、行政复议和行政诉讼三个方面 ,阐述了确保监测数据权威性的重要意义 ;介绍了对废气污染源排放进行监测所存在的问题 ,提出了确保监测数据权威性的建议 ,为环境行政处罚顺利实施提供准确的法律依据。     

Prioritizing organic chemicals for long-term air monitoring by using empirical monitoring data—application to data from the Swedish screening program

This paper illustrates a step-by-step approach for evaluating chemical monitoring data in air and deposition and for prioritizing chemicals to be included in long-term air monitoring programs. The usability of the method is shown by application to data generated within the Swedish screening program. The suggested prioritization approach uses a novel methodology by combining empirical data on occurrence in air and deposition with publicly available quantitative structure activity relationship estimation tools that predict atmospheric persistence and bioaccumulation. A selection tree is presented, which may be used by regulatory bodies to prioritize chemicals for long-term air monitoring. A final ranking list is presented proposing a prioritization order for inclusion in monitoring programs. Based on the suggested strategy, the chemicals identified as most relevant to include in Swedish long-term monitoring programs were short-chain chlorinated paraffins(C10-C13), perfluorooctane sulfonate, octachlorostyrene, hexabromocyclododecane, hexachlorobenzene, pentachloroanisole, decamethylcyclopentasiloxane, octamethylcyclotetrasiloxane, pentachlorobenzene, 1,2,3,4-tetrachlorobenzene, hexachlorobutadiene, dodecamethylcyclohexasiloxane, perfluorodecane sulfonate, 1,2,4,5-tetrachlorobenzene, and pentabromophenol.     

Finding Common Ground in Managing Data Used for Regional Environmental Assessments

Evaluating the overall environmental health of a region invariably involves using databases from multiple organizations. Several approaches to deal with the related technological and sociological issues have been used by various programs. Flexible data systems are required to deal with rapid changes in technology, the social and political climate for sharing and integrating data, and expectations of diverse users. Here we describe how the Environmental Monitoring and Assessment Program and the Chesapeake Bay Program manage their data for regional studies. These programs, which encompass areas of different geographic scales but face similar issues, have adopted some solutions in common, but also have tried some unique solutions suited to their needs. Understanding the tribulations and successes of these programs may help others attempting similar assessments. Both these programs have embraced distributed data systems that are managed by the organizations owning them. Both use common guidelines and policies that assure consistency and quality of data and information. These principles and tools comprise a flexible, sustainable approach that meets modern challenges of data management.     

MOSESS: A New Emission Model for the Compilation of Model-Ready Emission Inventories—Application in a Coal Mining Area in Northern Greece

Over the last years, the capabilities of chemical transport models have been greatly improved and the need for more accurate emission data has increased as well. In the past, a number of emission models have been developed and present different functionalities and applications. The majority of these though cover very specific needs. This paper describes the development of a new emission model namely computer model for the construction of model-ready emission inventories (MOSESS) which is used to compile high-resolution emission inventories or improve existing ones, utilizing complex GIS techniques. The model aims in helping chemical modelers to obtain a better overview of their modeling application by having a comprehensive understanding of the emission input. MOSESS incorporates more than 70 different emission calculation methodologies, and it is capable of handling external emission databases (such as EMEP and EPER) from which emissions can be extracted. The temporal variation (annual/daily and diurnal processing), chemical speciation of NMVOCs and particles, vertical distribution and point source treatment, as well as the spatial disaggregation of emissions (utilizing numerous spatial proxies including high-resolution landuses) can help create model-ready emission inventories which can be used for contemporary modeling applications.     

Neural Network Based Automated Interpretation Algorithm for Combined Geophysical Soundings in Coastal Zones

The fresh water availability in coastal aquifers is an important problem faced by a major part of world’s population dwelling there. For in situ and dynamic characterization of seawater encroachment into coastal aquifers, electrical geophysical methods are better suited. However, the resolving power of such data in distinguishing saline sands from moist clays in the subsurface is very poor. To meet this aspect and also the problem of analyzing voluminous data sets, we propose a feed forward back-propagation neural network (BPNN) based approach for the analysis of combined vertical electrical and induced polarization soundings. Our method is tested on synthetic data computed from available geo-electric sections and prevailing subsurface geological information of coastal aquifers of East Coast of India.The synthetic data are comprised of 18 combined soundings spread over five profiles. 15 out of 18 are used for training the BPNN, while 3 are used for testing. The trained BPNN (one node each in each of the input and output layers and 18 hidden nodes) showed 84.85% accuracy in testing phase for distinguishing clays from saline sands.Our method is also tested on real data concerning a shaly aquifer in Bahia, Brazil yielding an overall accuracy of 84.9%, comparable to that of synthetic case; thereby validating our approach.     

Integrating sentinel watershed-systems into the monitoring and assessment of Minnesota’s (USA) waters quality

Section 303(d) of the Clean Water Act requires States and Tribes to list waters not meeting water quality standards. A total maximum daily load must be prepared for waters identified as impaired with respect to water quality standards. Historically, the management of pollution in Minnesota has been focused on point-source regulation. Regulatory effort in Minnesota has improved water quality over the last three decades. Non-point source pollution has become the largest driver of conventional 303(d) listings in the 21st century. Conventional pollutants, i.e., organic, sediment and nutrient imbalances can be identified with poor land use management practices. However, the cause and effect relationship can be elusive because of natural watershed-system influences that vary with scale. Elucidation is complex because the current water quality standards in Minnesota were designed to work best with water quality permits to control point sources of pollution. This paper presents a sentinel watershed-systems approach (SWSA) to the monitoring and assessment of Minnesota waterbodies. SWSA integrates physical, chemical, and biological data over space and time using advanced technologies at selected small watersheds across Minnesota to potentially improve understanding of natural and anthropogenic watershed processes and the management of point and non-point sources of pollution. Long-term, state-of-the-art monitoring and assessment is needed to advance and improve water quality standards. Advanced water quality or ecologically-based standards that integrate physical, chemical, and biological numeric criteria offer the potential to better understand, manage, protect, and restore Minnesota’s waterbodies.     

The countryside information system: A strategic-level decision support system

The Institute of Terrestrial Ecology (ITE) has monitored ecological change in Great Britain (GB) since 1978. The task has been undertaken using a stratified sampling scheme working with a 1 km square as the sample unit. In more recent years, scientific researchers at ITE have been working closely with the policy-makers of the United Kingdom Department of the Environment. The presentation of information to policy advisors and planners was a component within a large project investigating the ecological consequences of land-use change. A simple PC-based decision support system was developed during the project and subsequently has been expanded to produce a marketable product. The system, called the Countryside Information System (CIS), presents and links information at national, regional and thematic levels along with qualifying data describing accuracy and appropriateness of use (i.e., metadata). An integral part of the CIS is the ITE Land Classification, which divides GB into 32 environmental land classes; all 250 000 squares have been classified. The classification allows sampled data to be presented and, as the co-ordinate system is widely used in GB, it allows census datasets to be linked and compared. CIS has been described as a Geographical Information System, but the classification, data held within the system, and the use of metadata to assist in interpretation of results make the system much more decision-support oriented. Indeed, government departments have been involved in directing the development and are now starting to use the system to answer parliamentary questions and formulate, assess and monitor environmental policy. The CIS is an open system, running on a standard PC in Microsoft Windows. Tools for loading and editing new datasets (both sample and census) are incorporated in the suite of programs. The Windows environment and users comments during development have produced a system with an intuitive feel, removing some of the overhead of acquiring specialised technical skills before being able to operate a system. This paper describes the CIS and presents examples of its applications.     

A rapid approach to rational water pollution control strategies

The formulation of rational wastewater control strategies is becoming increasingly important in many countries where, exploding urbanization, industrialization and/or tourism, often combined with improved standards of living and better awareness of the environmental problems, are resulting in enlarged pollution problems, but also in the availability of expanding financial resources for environmental protection. However, more often than one tends to believe, lack of planning, or planning with limited understanding of the principles involved, has resulted in solutions that are both expensive and incapable of addressing the key problems.As rigorous planning is extremely resource intensive, and for this reason impractical for most study areas, the development of a much simplified analysis procedure, capable of generating rational, near-optimum, strategies and detailed action programs, is required, if proper environmental management is to be widely practiced.In an effort to achieve the above objectives, a systems analysis approach is selected as the most suitable at rationalizing the allocation of available resources and at producing detailed action programs that promote implementation. In the context of this approach, new, easy to use models have been developed, while others, have been selected, adapted and streamlined in their use. The entire problem analysis and strategy synthesis procedures have thus been simplified and defined to a degree appropriate for widespread use, and the resultant procedure is actively promoted by WHO and UNEP.     

The effect of thermodynamic data on computer model predictions of uranium speciation in natural water systems

Computer models have found widespread application in order to help elucidate and predict changes in environmental systems. One such application is the prediction of trace metal speciation in aqueous systems. This is achieved by solving a set of non-linear equations involving equilibrium constants for all the components in the system, within mass and charge balance constraints. In this study a comparison of the predicted uranium speciation from two computer programs, WHAM and PHREEQCI, is used to illustrate the effect variations in thermodynamic data can have on the models produced. Using the original thermodynamic data provided with the models, WHAM predicted the UO2(2+) ion as the major species (84%) while PHREEQCI predicted UO2(HPO4)2(2-) as the major species (86%). Substituting uranium data from the Nuclear Energy Agency Thermochemical Database project (NEA-TDB) into both programs produced similar results from each program, with UO2F+ predicted to dominate (68%) in a groundwater sample. Natural water samples often contain humic substances. The possible interaction of such substances with uranium was also modelled. The WHAM program includes a discreet site electrostatic humic substance model, however in order to use the PHREEQCI program to model humic substance interactions, a 'model fulvic acid' dataset was added to the program. These models predicted 85 to 98% uranium-humic substance species at neutral pH. This indicates that humic substances do need to be taken into account when modelling uranium speciation in natural water samples.