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We have found 268 datasets for the keyword "sediment concentration". You can continue exploring the search results in the list below.
Datasets: 103,466
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268 Datasets, Page 1 of 27
Maritime region grain size data
Fisheries and Oceans Canada (DFO) Maritime Science Branch has collected grain size data from sediment and water column samples using bottle samples, sediment cores, and sediment grabs as part of numerous research projects not only in the Atlantic provinces, but also worldwide. The data collected by DFO focuses on the fine grained (<1mm) particles as these are both a source of food and means of contaminant transport. Grain size data are used to study the fate and distribution of complimentary chemistries like heavy metals, pesticides, hydrocarbons, aquaculture waste as well as a variety of physical processes such as the resuspension and transport of sediment.
Seabed grain size analyses, offshore Canada
Grain size is the most fundamental physical property of sediment, and these data are widely used in a variety of applications in science. Marine expeditions of the Geological Survey of Canada have been collecting grain size information on seabed and sub-seabed samples for over 50 years. Results have been recorded at 5th phi midpoints since the early 1990's in contrast to the earlier full, half or quarter phi interval end point values. Users of high resolution data must note that the sum of %Silt and %Clay equals the total %Mud makeup and that %Gravel, %Sand, %Silt and %Clay sum to 100%. Summary statistics include percentages of gravel, sand, silt, clay and mud as well as mean, kurtosis, skewness and standard deviation. The quality of these data varies. Results should be used with some caution as they may not be fully representative of seabed grainsize, particularly in areas of sandy and coarser sediment (e.g., sand and mud can leak out of the sampler during recovery). Canada makes no representation or warranty of any kind with respect to the accuracy, usefulness, novelty, validity, scope, completeness or currency of the data and expressly disclaims any implied warranty of merchantability or fitness for a particular purpose of the data. For the purpose of the web mapping service, grain size data are sorted by the expedition id. Coarse and detailed grain size distribution plots are shown when a point is chosen. If the sample contains more that one sub-sample ( e.g., as with a piston core sequence), the grain size plots are stacked in the display window from the top of the core downwards.
Sediment, Oil Sands Region
Monitoring activities have collected bulk suspended sediment samples using continuous flow centrifuges and Phillips Tube samplers in the Lower Athabasca River and tributaries respectively. Further, in the absence of pre-development monitoring for this region, high fidelity dated lake sediment cores were used to assess the natural range in contaminant deposition to this region and to obtain a historical perspective of contaminant loadings. All sediments (suspended river and lake cores) have been analyzed in the laboratory for sediment quality variables as per Appendix B in the Integrated Monitoring Plan (cores were also analyzed for paleo indicators of ecosystem health such as diatoms). In addition, as the Lower Athabasca river bed sediments are known to shift and migrate downstream, bathymetric maps of the bed-channel morphology over time was also completed. This will allow for estimates of bed sediment transport downstream for the period of survey, and be useful in calibration/validation of sediment and contaminant numerical transport models.
Concentrations of suspended particulate matter (SPM) in the St. Lawrence
The layer provides information on suspended particulate matter (SPM) concentrations by area. There is a natural interaction phenomenon between hydrocarbons and SPM, that creates hydrocarbon-SPM aggregates. The SPM in the water column, hence has an effect on hydrocarbon capacity to sink to the bottom in aggregate form (Gong et collab., 2014 ; Fitzpatrick et collab., 2015, cited in Centre d'expertise en analyse environnementale du Québec, 2015). Additional InformationThe suspended particulate matter data for this layer are derived from multiple sources given the need to cover the St. Lawrence portion from Montreal to Anticosti. The layer has been cut into 6 different zones. Denis Lefaivre, a researcher at Maurice-Lamontagne Institute, has provided the coordinates of the points allowing the delimitation of areas. The values in each zone are derived from different studies carried out at different times. The references are cited below for each of the polygons from West to East, as well as for the summary:1- Department of Sustainable Development, Environment and Climate Change and Environment and Climate Change Canada, 2016. Recommendations for Suspended Matter Management (ESM) during dredging activities. Quebec. 64 pages and appendices. http://planstlaurent.qc.ca/fileadmin/publications/diverses/Registre_de_dragage/Recommandations_dragage.pdf2- D'Anglejan, B. 1990. Recent Sediments and Sediment Transport Process in the St. Lawrence Estuary. In Oceanography of a Large-Scale Estuarine System: The St. Lawrence, edited by M. I. El-Sabh and N. Silverberg. New York: Springer-Verlag, 109-153.3- Silverberg, N., and B. Sundby. 1979. Observations in the maximum turbidity of the St. Lawrence estuary. Can. J. Earth Sci. 16: 939-950.4- Michel Lebeuf, 2016.Unpublished personal data.Collected between 2015-2016 for research purposes.5- Sundby, B. 1974. Distribution and Transport of Suspended Particulate Matter in the Gulf of St. Lawrence. Canadian Journal of Earth Sciences11 (11): 1517-1533.6- Gong, Y., X. Zhao, Z. Cai, S. E. O'Reilly, X. Hao and D. Zhao. 2014. A review of oil, dispersedoil and sediment interactions in the aquatic environment: Influence on the fate, transportand remediation of oil spills. Marine Pollution Bulletin, vol. 79: 1-2, p.16-33. 7- Fitzpatrick, F.A., M.C., Boufadel, R., Johnson, K., Lee, T.P., Graan, A.C., Bejarano, Z.,Zhu, D., Waterman, D.M., Capone, E., Hayter, S.K., Hamilton, T., Deffer, M.H.,Garcia, et J.S., Hassan. 2015. Oil-particle interactions and submergence from crudeoil spills in marine and freshwater environments – Review of the science and futurescience needs. U.S. Geological Survey Open-file report 2015-2016, 33 p.8- Centre d'expertise en analyse environnementale du Québec,2015.Hydrocarbures pétroliers : caractéristiques, devenir et criminalistique environnementale –Études GENV222 et GENV23, Évaluation environnementale stratégique globale sur leshydrocarbures. Ministère du Développement durable, de l’Environnement et de la Lutte contreles changements climatiques, 41 p. et annexes.9- CSL – Centre Saint-Laurent, 1997. Le Saint-Laurent : dynamique et contamination des sédiments, Montréal, Environnement Canada – Région du Québec, Conservation de l’environnement, 127 p. (coll. BILAN Saint-Laurent). [Rapport thématique sur l’état du Saint-Laurent].
Historical trace metals concentrations from sediment samples and suspended particulate matter (SPM) samples, 1976 - 1987
This dataset is a compilation of numerous data files recovered as part of a data request in 2024 from a historical archive of DFO research data. Sediment and Suspended Particulate Matter (SPM) samples were collected over more than a decade as part of Dr. Douglas Loring’s research program while working at the Bedford Institute of Oceanography (BIO). Samples were collected as part of individual and collaborative research projects, and links to the relevant primary science publications and reports are included in the data in an effort to provide context to the data, as well as describe the field and laboratory techniques used to generate the attached data.
Radionuclide Releases - Uranium Mines and Mills / Direct Discharge
This dataset contains the total annual releases of radionuclides released directly to the environment through direct discharge (i.e. releases to water) from uranium mines and mills in Canada.Note that there is no stack emissions for the uranium mines and mills.
Characterization of sediment and faunal attributes of Simoom Sound, British Columbia
These datasets provide information pertaining to sediment grain size, porosity, organic content, total carbon and nitrogen concentrations, trace element concentrations, chlorophyll and phaeopigment concentrations, and meiofauna and macrofaunal abundance in Simoom Sound between November, 2000, and February, 2001. Data formatting of files were performed by Meagan Mak.Sutherland et al (2023) covers the benthic component of a broader project investigating potential modification of marine ecosystems by shrimp trawling and trapping on the central coast of British Columbia. Sediment and infaunal samples were collected before and after fishing with commercial fishing gear consisting of otter-trawl, beam-trawl, and trap-lines. Simoom Sound was sampled in November 2000 and February 2001. Tabulated data of sediment characteristics that include sediment grain size, porosity, carbon and nitrogen content, trace-element, and chlorophyll concentrations are presented in this report. In addition, the infaunal data are comprised of both macrofaunal and meiofaunal communities.
Atlantic herring - Concentration areas, spawning sites and breeding areas - FHAMIS
Atlantic herring. Concentration, breeding areas and larval retention areas of Atlantic Herring in the St. Lawrence Estuary.Data extracted from the Fish Habitat Management Information System (FHAMIS).Concentration areas, spawning sites and breeding areas of Atlantic herring according to a literature review of documents produced between 1977 and 1998.
Sediment Chemistry (Great Lakes Nearshore Areas)
Data is collected each year, according to the lake-by-lake cycle. Information includes: * sediment chemistry * approximately 80 index and reference stations throughout the Great Lakes basin
Global Deterministic Wave Prediction System
The Global Deterministic Wave Prediction System (GDWPS) produces wave forecasts out to 120 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds and the ice concentration from the Global Deterministic Prediction System (GDPS). The ice concentration is used by the model to attenuate wave growth in areas covered by 25% to 75% ice and to suppress it for concentration above 75%. Forecast elements include significant wave height, peak period and primary swell height, direction and period.
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