An expert system for water quality modelling

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.     

An environmental stress information system

This paper reports on the development of an environmental stress information system (ESIS) for the purpose of storing, updating and analysing environmental stress data related to noise, heat, improper illumination and air contaminants. The information system (ESIS) consists of a set of programs as well as a set of data base files for the purpose of efficient data processing. The system is user-friendly and, once started, guides the user with the help of menu-driven options. All data related to noise, heat, illumination and air contaminants can be entered, updated, displayed or printed in certain specified formats. Finally, the use of the ESIS in evaluating air contaminants such as total suspended particles, certain specified metals and inorganic gases in the Jeddah Industrial estate is also reported.     

An expert system for assessing safety and security of heterogeneous public water sources

We have implemented a diagnostic system designed to advise on the likely causes of sanitary problems with public water sources. The approach to the problem makes extensive use of rule based expert systems and multi media information (maps, data, text, expert knowledge). The rules were based on actual water survey data, with a weighting scheme designed to highlight causes of health risks approximately in reverse order of importance (where such order may be presumed to exist). Out put is a vailable in one of several languages.     

Expres: An expert system for assessing the fate of pesticides in the subsurface

The expert system described here is designed to aid regulatory personnel in their assessment of the potential for pesticides to contaminate the soil and groundwater environment. The expert system, known as EXPRES (EXpert system for Pesticide Regulatory Evaluation Simulations), consists of existing numerical models which are used to simulate the transport and transformation of pesticides in the unsaturated zone, coupled with a knowledge-based system that guides the user through the choice of all the necessary information for characterizing the physical, meteorological, hydrogeological, pedological and agricultural settings of typical agricultural regions across Canada, as required by the pesticide model. The expert system is designed to be used as a management tool to aid in policy decisions. Thus, its purpose is to provide an assessment of the potential hazards and to identify if further study is warranted.     

A prototype expert system for fishway design

The design of structures for fish passage in rivers and streams provides an opportunity to apply expert system concepts to a design problem. Fishways contribute to the sustainable development of water resources projects by providing a path that allows fish migrations to be maintained. A prototype expert system (FDES) has been developed to recommend the most suitable fishway type for given design conditions. A recommendation is provided on the basis of fishway hydraulics, fish passage performance, and cost requirements. Fishway design demands expertise in various scientific disciplines such as hydrology, hydraulics, and fish biology. Expert system technology may be used to reduce design time requirements and to serve as a teaching aid to inexperienced engineers by organizing and accessing the cumulative knowledge of the most experienced designers. The rule-based expert system development tool, VP-Expert, supplies the backward chaining control structure for accessing the knowledge within the prototype.     

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.     

Benchmarking for best practice environmental management

Benchmarking of environmental performance to demonstrate theachievement of best practice environmental management is acomponent of a new form of licensing of industrialdischarges in Western Australia. The paper describes theapproaches to benchmarking for the critical environmentalissues for an alumina refinery and wastewater treatmentplant. It also describes the lessons learnt from thebenchmarking process on appropriate methods, the benefitsand difficulties in the benchmarking process, and changesthat would assist benchmarking for best practiceenvironmental management.     

环境监测质量管理体系日常维护探讨

通过对当前环境监测质量管理体系日常运行及维护过程进行汇总分析,探讨质量管理体系具体实施过程中易产生疏忽的部分关键环节,对出现的一些共性问题进行归纳,并提出相应预防及纠正措施,为进一步规范环境质量监测活动提供参考和借鉴。     

Permutation/randomization-based inference for environmental data

Quantitative inference from environmental contaminant data is almost exclusively from within the classic Neyman/Pearson (N/P) hypothesis-testing model, by which the mean serves as the fundamental quantitative measure, but which is constrained by random sampling and the assumption of normality in the data. Permutation/randomization-based inference originally forwarded by R. A. Fisher derives probability directly from the proportion of the occurrences of interest and is not dependent upon the distribution of data or random sampling. Foundationally, the underlying logic and the interpretation of the significance of the two models vary, but inference using either model can often be successfully applied. However, data examples from airborne environmental fungi (mold), asbestos in settled dust, and 1,2,3,4-tetrachlorobenzene (TeCB) in soil demonstrate potentially misleading inference using traditional N/P hypothesis testing based upon means/variance compared to permutation/randomization inference using differences in frequency of detection (Δf _d). Bootstrapping and permutation testing, which are extensions of permutation/randomization, confirm calculated p values via Δf _d and should be utilized to verify the appropriateness of a given data analysis by either model.     

Cultured human-cell-based bioassay for environmental risk management

Among bioassays for evaluating various impacts of chemicalson humans and ecosystems, those based on culturedmammalian-cells can best predict acute lethal toxicity to humans. Weexpect them to be employed in the future in environmentalrisk management alongside mutagenicity tests and endocrine-disrupting activity tests. We recently developed adisposable bioassay device that immobilizes humanhepatocarcinoma cells in a small micropipette tip. Thisenables very quick (within 2 h) evaluation of acute lethaltoxicity to humans. For bioassay-based environmentalmanagement, 2 promising approaches have been demonstrated bythe US-EPA: toxicity identification evaluation (TIE) andtoxicity reduction evaluation (TRE). The Japanese Ministryof Environment has been supporting a multi-center validationproject, aimed at assembling a bioassay database. To makefull use of these resources, we present a numerical modelthat describes contribution of individual chemical toobserved toxicity. This will allow the selection of the mosteffective countermeasure to reduce the toxicity. Bioassay-based environmental risk management works retrospectively,whereas impact assessment using substance flow models andtoxicity databases works prospective. We expect that these 2approaches will exchange information, act complementarily,and work effectively in keeping our environment healthy inthe 21st century.     

Value functions for environmental pollutants: A technique for enhancing the assessment of expert judgements

This paper presents a new procedure to assess value functions for environmental pollutants. It has been particularly designed for eliciting expert-based value functions for pollutant substances. The main features of the model are the possibility to integrate direct and indirect assessment techniques, the possibility to make explicit assessment uncertainties and to avoid forcing quantitative judgements. The main aim of the procedure is to improve the reliability of the assessment but also to make the expert's task easier by using qualitative judgements more frequently. The procedure has been developed especially for soil pollutants, for which an application is described.     

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.     

The development of an ecological classification data management and analysis system for British Columbia

Since 1975, the British Columbia Ministry of Forests has been systematically developing an ecosystem classification of the province, an area covering 94 million hectares. This Biogeoclimatic Ecosystem Classification (BEC) system provides a framework for resource conservation and management. To date, approximately 250 person-years have been invested in the collection, analysis and synthesis of over 8000 ecological (vegetation and environmental data) plots, and in the production of ecological field guides.The development of a database and analysis system on the micro-computer platform to support a classification system of this magnitude was a complex procedure that required judicious planning and coordination. We have developed data-processing software that permits a user to select raw data from broad provincial or regional coverage to plot- and species-level summaries, and to export the data to a variety of output formats.This paper addresses key issues for handling ecological field data on the desktop computer with emphasis on standards, operator ease-of-use, and data access.     

Taraxacum species as environmental indicators for grassland management

A classification of the microspecies of the genus Taraxacum was made in a range from low to highly dynamic habitats based on qualitative inventories of grasslands under different management conditions. After several years of constant management, a characteristic species composition occurs. Under mowing (hayfield) conditions, dandelions disappear over a period of about twenty years in a sequence where the low-dynamic species T. adamii and T. nordstedtii are the last to vanish. Different microspecies in the section Vulgaria in one field can show small differences in response to environmental conditions, even where no other directly visible indication exists. New appearance of highly dynamic species can indicate disturbance of some kind or other within a relatively short period. The classification adopted seems to be correlated with the phosphate content of the soil. Differences in two easily perceptible morphological characteristics, namely position of the outer bracts and colour of the leaf-stem, fit into the established sequence. Small changes in these characteristics indicate conditions in the field that are improving or worsening from a nature-conservation point of view. A system is introduced in which merely these two morphological characters, without further taxonomical knowledge, can be used for an evaluation of grasslands and the impact of management practice.     

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.     

An assessment of cause and effect decision-making model for firm environmental knowledge management capacities in uncertainty

Environmental practices in knowledge management capability (EKMC) is a complex and uncertainty concept that is difficult to determine based on a firm’s real situation because measuring EKMC requires a set of qualitative and quantitative measurement. The objective of this study is to develop a cause and effect model in uncertainty using the fuzzy set theory and Decision Making Trial and Evaluation Laboratory (DEMATEL) method. A framework for evaluating EKMC is proposed. An approach of fuzzy linguistic is proposed to evaluate the firm EKMC. The evaluation results of EKMC obtained through the proposed approach are objective and unbiased due to two reasons. Firstly, the results are generated by a group of experts in the presence of motile attributes. Secondly, the fuzzy linguistic approach has more advantage to reduce distortion and losing of information. Through evaluating the result of EKMC, managers could judge the necessity to improve the EKMC and determine which criteria are the needed directions to improve. The managerial implication and conclusions are discussed.     

Normality transformations for environmental data from compound normal-lognormal distributions

The combination of lognormally distributed quantities of interest with normally distributed random measurement error produces data that follow a compound normal-lognormal (NLN) distribution. When the measurement error is large enough, such data do not approximate normality, even after a logarithmic transformation. This paper reports the results of a search for a transformation method for NLN data that is not only technically appropriate, but easy to implement as well. Three transformation families were found to work relatively well. These families are compared in terms of success in achieving normality and robustness, using simulated NLN data and actual environmental data believed to follow a NLN distribution. The exponential family of transformations was found to give the best overall results. This work was supported by the U.S. Department of Energy, Office of Environmental Restoration and Waste Management, under DOE Idaho Field Office Contract DE-AC07-76ID01570.     

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.     

Evaluating environmental performance using new process capability indices for autocorrelated data

Traditionally, the process capability index is developed by assuming that the process output data are independent and follow normal distribution. However, in most environmental cases, the process data are autocorrelated. The autocorrelated process, if unrecognized as an independent process, can lead to erroneous decision making and unnecessary quality loss. In this paper, three new capability indices with unbiased estimators are proposed to relieve the independence assumption for the-nominal-the-best and the-smaller-the-better cases. Furthermore, we use mean squared error (MSE) and mean absolute percent error (MAPE) to compare the accuracy of our proposed indices to previous autocorrelated indices. The results show that our proposed capability indices outperform the predecessors.