Christina G Siontorou | PubMed Health

PubMed2006

A knowledge-based approach to environmental biomonitoring.

This paper presents the design, development and implementation of an integrated GIS-controlled knowledge-based system for environmental monitoring applications, utilizing indigenous flora for assessing quality. The system gathers and combines geographical, ecological, and physicochemical data of organisms' response to pollution within an intelligent computer program that (a) recognises groups of indigenous species suitable for long-term monitoring of a specific pollutant or a combination of pollutants, (b) estimates the ambient concentration of pollutant(s) from the population of the species comprising the bioindicator group and (c) provides biomonitoring capacity indices at national and international/transboundary levels. Significantly, a novel system in the form of a rational framework at the conceptual design level has been developed, that actually contributes towards achieving a cost-effective long-term biomonitoring program, with the flexibility to counter on-course any (anticipated or not) variations/modifications of the surveillance environment: the scheme assumes a robust dynamic cooperation between instrumental and biomonitoring systems, with a view to minimise uncertainty and monitoring costs and increase reliability of pollution control and abatement, aiming eventually at the shifting, partially or totally, from instrumental to natural monitoring. The proposed approach is presently implemented at pilot-scale for establishing a biomonitoring network at a large industrial area in Greece. The results obtained indicate that a cost-effective program can be only attained and maintained under a suitable financial/organizational scheme at the macro level, whereas the micro level viability strongly depends upon careful management of human resources and fixed assets.

Biodiversity↗

PubMed2006

A novel system for environmental monitoring through a cooperative/synergistic scheme between bioindicators and biosensors.

This paper addresses environmental monitoring through a robust dynamic integration between biomonitor and biosensor systems, a strategy that has not been attempted before. The two systems are conceptually interrelated and methodologically correlated to a cooperative/synergistic scheme (CSS) with a view to minimise uncertainty and monitoring costs and increase reliability of pollution control and abatement. The structures and operations of the biosensor component (in terms of sensitivity, device and method versatility, nature-mimicking physicochemical mechanisms, prospects and technological input) are such that they reinforce or promote the structures and operations of the natural component (in terms of bio-surveillance, impact assessment, environmental quality indexing, stress responses, metabolic pathways, etc.) and vice versa. The bioindicator ontology presented herein, including concepts, relations and controlled vocabulary aiming at establishing an integrated methodology for mapping/assessing negative environmental externalities, provides a useful tool for the design/development/implementation of an environmental network for the monitoring of a variety of pollutants over time and space and the assessment of environmental quality; the collection of the available information and its classification into taxonomic and partonomic relations allows the construction of a database that links pollutants with organisms' response, at a phenomenological and in-depth level, considering ecological parameters, relations and geomorphologic characteristics. As a result, a computer program has been designed/developed as a decision support system and has been successfully tested on a representative population of species indigenous to southern Greece. Significantly, a novel system in the form of a rational framework at the conceptual design level has been developed, that actually contributes towards achieving a cost-effective long-term monitoring program, with the flexibility to counter on-course any (anticipated or not) variations/modifications of the surveillance environment. This novel and pioneering approach will further offer a dynamic system utilised in (a) environmental impact studies and risk assessment (positive/analytic approach), (b) decision-making in the short-run (normative/tactic approach), and (c) policy-making in the long-run (normative/strategic approach). The proposed CSS, based on the integration of multiple data sources, can establish a local area network, incorporated into/expanding to a wide area network, thus offering the potential of better predictive ability and greater lead-time warning at alarm conditions than that provided by separate, stand-alone surveillance modalities.

Biosensing Techniques↗