MANAGEMENT OF RADIOLOGICAL CAPACITY OF SURFACE WATER ECOSYSTEMS, WHICH INCLUDES TECHNOLOGICAL RESERVOIRS OF NPPS

Due to widespread utilization in many industrial spheres and agrochemicals, N-methyl-2-pyrrolidone (NMP) is a potential contaminant of different surface water ecosystems. Hence, investigation was made into its aerobic microbial degradability in samples of water from a river, wetland area and spring. The results showed that the compound was degradable in all water types, and that the fastest NMP removal occurred in 4 days in river water, while in the wetland and spring samples the process was relatively slow, requiring several months to complete. Key bacterial degraders were successfully isolated in all cases, and their identification proved that pseudomonads played a major role in NMP degradation in river water, while the genera Rhodococcus and Patulibacter fulfilled a similar task in the wetland sample. Regarding spring water, degrading members of the Mesorhizobium and Rhizobium genera were found.

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Wastewater‐contaminated groundwater as a source of endogenous hormones and pharmaceuticals to surface water ecosystems

Environmental Toxicology and Chemistry ◽

10.1897/07-604.1 ◽

2008 ◽

Vol 27 (12) ◽

pp. 2457-2468 ◽

Cited By ~ 63

Author(s):

Laurel J. Standley ◽

Ruthann A. Rudel ◽

Christopher H. Swartz ◽

Kathleen R. Attfield ◽

Jeff Christian ◽

...

Keyword(s):

Surface Water ◽

Contaminated Groundwater ◽

Endogenous Hormones ◽

Water Ecosystems

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An integrated model for assessing the risk of TCE groundwater contamination to human receptors and surface water ecosystems

Ecological Engineering ◽

10.1016/j.ecoleng.2010.01.004 ◽

2010 ◽

Vol 36 (9) ◽

pp. 1126-1137 ◽

Cited By ~ 38

Author(s):

Ursula S. McKnight ◽

Simon G. Funder ◽

Jes J. Rasmussen ◽

Michael Finkel ◽

Philip J. Binning ◽

...

Keyword(s):

Surface Water ◽

Groundwater Contamination ◽

Integrated Model ◽

Water Ecosystems

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Cross-Sensor Quality Assurance for Marine Observatories

Remote Sensing ◽

10.3390/rs12213470 ◽

2020 ◽

Vol 12 (21) ◽

pp. 3470

Author(s):

Roee Diamant ◽

Ilan Shachar ◽

Yizhaq Makovsky ◽

Bruno Miguel Ferreira ◽

Nuno Alexandre Cruz

Keyword(s):

Quality Assurance ◽

Surface Water ◽

Eastern Mediterranean ◽

Automatic Identification ◽

Surface Water Temperature ◽

Short Term ◽

Trade Off ◽

Observation Systems ◽

Water Ecosystems

Measuring and forecasting changes in coastal and deep-water ecosystems and climates requires sustained long-term measurements from marine observation systems. One of the key considerations in analyzing data from marine observatories is quality assurance (QA). The data acquired by these infrastructures accumulates into Giga and Terabytes per year, necessitating an accurate automatic identification of false samples. A particular challenge in the QA of oceanographic datasets is the avoidance of disqualification of data samples that, while appearing as outliers, actually represent real short-term phenomena, that are of importance. In this paper, we present a novel cross-sensor QA approach that validates the disqualification decision of a data sample from an examined dataset by comparing it to samples from related datasets. This group of related datasets is chosen so as to reflect upon the same oceanographic phenomena that enable some prediction of the examined dataset. In our approach, a disqualification is validated if the detected anomaly is present only in the examined dataset, but not in its related datasets. Results for a surface water temperature dataset recorded by our Texas A&M—Haifa Eastern Mediterranean Marine Observatory (THEMO)—over a period of 7 months, show an improved trade-off between accurate and false disqualification rates when compared to two standard benchmark schemes.

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