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Using Real-time Physical/Chemical Sensors and In-situ Biological Indicators to Monitor Water Pollution

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Water Pollution: Modelling, Measuring and Prediction

Abstract

Meaningful water pollution monitoring to assess marine environmental quality should include chemical measurements to document the extent of environmental contamination and biological measurements to estimate the effects of that contamination. The approach described here emphasizes the use of real-time chemical sensors and in-situ biological indicators in a monitoring strategy with the following fundamental elements: 1) Direct, in-situ measurements that avoid extrapolation; 2) Sequential measurements at a frequency commensurate with scales of natural and pollution-related variability; and 3) Integrating measurements from various disciplines to overcome the limitations of separate approaches. Results are presented from studies in San Diego Bay that demonstrate significant seasonal and tidal variability in many natural physical/chemical factors (turbidity, temperature, salinity, dissolved oxygen, pH, chlorophyll-a) and in the concentration of several different contaminants (copper, zinc, tributyltin (TBT), oil) that could affect biological responses. Biological responses were related to temperature and tissue concentrations of TBT, copper, and zinc. Mapping surveys revealed significant spatial variability of contaminants and natural factors, as well as temporal variability across tidal and seasonal cycles. Significant differences among in-situ biological responses were measured over time scales of weeks and months and at locations separated by as little as three meters in depth. Collectively, the data presented here show dramatic fluctuations with potentially significant implications for monitoring water pollution and its effects.

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© 1991 Computational Mechanics Publications

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Salazar, M.H., Chadwick, D.B. (1991). Using Real-time Physical/Chemical Sensors and In-situ Biological Indicators to Monitor Water Pollution. In: Wrobel, L.C., Brebbia, C.A. (eds) Water Pollution: Modelling, Measuring and Prediction. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-3694-5_33

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  • DOI: https://doi.org/10.1007/978-94-011-3694-5_33

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-85166-697-3

  • Online ISBN: 978-94-011-3694-5

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