Utilization of bathymetry data to examine lead sediment contamination distributions in Lake Ontario

K. Wayne Forsythe; Chris H. Marvin; Danielle E. Mitchell; Joseph M. Aversa; Stephen J. Swales; Debbie A. Burniston; James P. Watt; Daniel J. Jakubek; Meghan H. McHenry; Richard R. Shaker; K. Wayne Forsythe; Chris H. Marvin; Danielle E. Mitchell; Joseph M. Aversa; Stephen J. Swales; Debbie A. Burniston; James P. Watt; Daniel J. Jakubek; Meghan H. McHenry; Richard R. Shaker

doi:10.3934/environsci.2016.3.347

AIMS Environmental Science

2016, Volume 3, Issue 3: 347-361. doi: 10.3934/environsci.2016.3.347

Previous Article Next Article

Research article Special Issues

Utilization of bathymetry data to examine lead sediment contamination distributions in Lake Ontario

1.
Department of Geography and Environmental Studies, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada
2.
Aquatic Contaminants Research Division, Water Science and Technology Directorate, Environment and Climate Change Canada, 867 Lakeshore Road, Burlington, ON L7S 1A1, Canada
3.
Water Quality Monitoring and Surveillance Division, Science and Technology Branch, Environment and Climate Change Canada, 867 Lakeshore Road, Burlington, ON L7S 1A1, Canada
4.
CH2M Hill, 815 8th Avenue SW, Suite 1100, Calgary, AB T2P 3P2, Canada
5.
Geospatial Map and Data Centre, Ryerson University Library, 350 Victoria Street, Toronto, ON M5B 2K3, Canada

Received: 15 April 2016 Accepted: 20 June 2016 Published: 21 June 2016

Bathymetry data offer interesting opportunities for the analysis of contaminant distribution patterns. This research utilized lead surficial sediment sample data from Lake Ontario that were collected by the Canada Centre for Inland Waters in 1968 and 1998. Traditionally, two-dimensional analyses such as dot maps or proportional circle representation have been utilized to examine pollutant levels. Generating area estimates allows for expanded spatial analysis of contaminant distribution patterns. Lake-wide surfaces were derived using the ordinary kriging technique. These were then layered on bathymetry data to examine three-dimensional relationships between observed pollution patterns and lake-bottom features. Spatial variability was observed in both the 1968 and 1998 datasets. Contamination levels in 1998 dropped substantially, especially in areas that were previously the most heavily polluted and above the Probable Effect Level (4660.23 km2 or 26.72% of the common analysis area lake-bottom in 1998 versus 6189.07 km2 or 62.00% in 1968). Conversely, areas below the Threshold Effect Level increased from 922.09 km2 (5.29%) in 1968 to 3484.22 km2 (19.98%) in 1998. In both years, shallow and sill/ridge areas tended to have lower levels of contamination than deeper lake basins or contaminant inflow areas. The 1968 dataset likely provides a more detailed estimation surface as there were more points available for interpolation procedures. The kriging surfaces when combined with bathymetry, sedimentology information, and knowledge of physical processes provide a comprehensive illustration of the contaminant distributions whether they are high (1968) or when loadings are significantly reduced (1998). The results have implications for future sediment assessment programs and survey design on a lake-wide basis. The bathymetry data allowed for enhanced interpretation and an improved understanding of observed lead pollution patterns.
- lead,
- contamination,
- bathymetry,
- sediment,
- kriging,
- geovisualization,
- log-normalization,
- Lake Ontario
Citation: K. Wayne Forsythe, Chris H. Marvin, Danielle E. Mitchell, Joseph M. Aversa, Stephen J. Swales, Debbie A. Burniston, James P. Watt, Daniel J. Jakubek, Meghan H. McHenry, Richard R. Shaker. Utilization of bathymetry data to examine lead sediment contamination distributions in Lake Ontario[J]. AIMS Environmental Science, 2016, 3(3): 347-361. doi: 10.3934/environsci.2016.3.347

Related Papers:

Abstract

Bathymetry data offer interesting opportunities for the analysis of contaminant distribution patterns. This research utilized lead surficial sediment sample data from Lake Ontario that were collected by the Canada Centre for Inland Waters in 1968 and 1998. Traditionally, two-dimensional analyses such as dot maps or proportional circle representation have been utilized to examine pollutant levels. Generating area estimates allows for expanded spatial analysis of contaminant distribution patterns. Lake-wide surfaces were derived using the ordinary kriging technique. These were then layered on bathymetry data to examine three-dimensional relationships between observed pollution patterns and lake-bottom features. Spatial variability was observed in both the 1968 and 1998 datasets. Contamination levels in 1998 dropped substantially, especially in areas that were previously the most heavily polluted and above the Probable Effect Level (4660.23 km2 or 26.72% of the common analysis area lake-bottom in 1998 versus 6189.07 km2 or 62.00% in 1968). Conversely, areas below the Threshold Effect Level increased from 922.09 km2 (5.29%) in 1968 to 3484.22 km2 (19.98%) in 1998. In both years, shallow and sill/ridge areas tended to have lower levels of contamination than deeper lake basins or contaminant inflow areas. The 1968 dataset likely provides a more detailed estimation surface as there were more points available for interpolation procedures. The kriging surfaces when combined with bathymetry, sedimentology information, and knowledge of physical processes provide a comprehensive illustration of the contaminant distributions whether they are high (1968) or when loadings are significantly reduced (1998). The results have implications for future sediment assessment programs and survey design on a lake-wide basis. The bathymetry data allowed for enhanced interpretation and an improved understanding of observed lead pollution patterns.

References

[1]	U.S. Environmental Protection Agency and Government of Canada (USEPAGC), (1995) The Great Lakes—An Environmental Atlas and Resource Book (3rd Edition), Chicago: Great Lakes National Program Office.
[2]	Great Lakes Information Network (GLIN), 2004. Great Lakes Facts and Figures. Great Lakes Information Network. Available from: http://www.great-lakes.net/lakes/ref/lakefact.html
[3]	Crane J, MacDonald DD (2003) Applications of Numerical Sediment Quality Targets for Assessing Sediment Quality Conditions in a US Great Lakes Area of Concern. Environ Manage 32: 128-140.
[4]	Canadian Council of Ministers of the Environment (CCME), 1999. Canadian Environmental Quality Guidelines. Winnipeg, MB: Canadian Council of Ministers of the Environment.
[5]	Forsythe KW, Marvin CH, Valancius CJ, et al. (2016) Using Geovisualization to Assess Lead Sediment Contamination in Lake St. Clair. The Canadian Geographer/Le Géographe canadien 60: 149-158.
[6]	Newell RG, Rogers K, The U.S. Experience with the phasedown of lead in gasoline, 2003. Available from: http://web.mit.edu/ckolstad/www/Newell.pdf
[7]	Currie E (1994) Contaminated Sediment Removal Program Environment Canada—Great Lakes Cleanup Fund.
[8]	Forsythe KW, Watt JP (2006) Using Geovisualization to Assess Sediment Contamination in the “Sixth” Great Lake. In: Strobl J, Blaschke T, Griesebner G (Eds), Proceedings of the 18th Symposium for Applied Geographic Information Processing, AGIT XVIII, Salzburg, Austria, July 5-7, 2006, Herbert Wichmann Verlag, Hüthig GmbH & Co. KG: Heidelberg, Germany, 161-170.
[9]	Forsythe KW, Marvin CH, Valancius CJ, et al. (2016) Geovisualization of Mercury Contamination in Lake St. Clair Sediments. J Mar Sci Eng 4: 19.
[10]	Forsythe KW, Dennis M, Marvin CH (2004) Comparison of Mercury and Lead Sediment Concentrations in Lake Ontario (1968–1998) and Lake Erie (1971-1997/98) using a GIS-based Kriging Approach. Water Qual Res J Can 39: 190-206.
[11]	Jakubek DJ, Forsythe KW (2004) A GIS-based kriging approach for assessing Lake Ontario sediment contamination. Great Lakes Geographer 11: 1-14.
[12]	Forsythe KW, Marvin CH (2005) Analyzing the Spatial Distribution of Sediment Contamination in the Lower Great Lakes. Water Qual Res J Can 40: 389-401.
[13]	Gewurtz SB, Helm PA, Waltho J, et al. (2007) Spatial distributions and temporal trends in sediment contamination in Lake St. Clair. J Great Lakes Res 33: 668-685.
[14]	Gewurtz SB, Shen L, Helm PA, et al. (2008) Spatial distribution of legacy contaminants in sediments of Lakes Huron and Superior. J Great Lakes Res 34: 153-168.
[15]	Forsythe KW, Marvin CH (2009) Assessing Historical versus Contemporary Mercury and Lead Contamination in Lake Huron Sediments. Aquat Ecosyst Health 12: 101-109.
[16]	Forsythe KW, Paudel K, Marvin CH (2010) Geospatial analysis of zinc contamination in Lake Ontario sediments. J Environ Inform 16: 1-10. doi: 10.3808/jei.201000172
[17]	Gawedzki A, Forsythe KW (2012) Assessing anthracene and arsenic contamination within Buffalo River sediments. Int J Ecol 2012: Article ID 496740.
[18]	Forsythe KW, Irvine KN, Atkinson DM, et al. (2015) Assessing lead contamination in Buffalo River sediments. J Environ Inform 26: 106-111.
[19]	Johnston K, Ver Hoef J, Krivoruchko K, et al. (2001) Using ArcGIS geostatistical analyst. Redlands, CA: Environmental Systems Research Institute.
[20]	Isaaks EH, Srivastava MR (1989) An Introduction to Applied Geostatistics. New York, NY: Oxford University Press.
[21]	National Oceanographic and Atmospheric Administration (NOAA), Great Lakes bathymetry. 2014. Available from: http://www.ngdc.noaa.gov/mgg/greatlakes/greatlakes.html.
[22]	Great Lakes Information Network (GLIN), 2004. Lake Ontario Facts and Figures. Great Lakes Information Network. Available from: http://www.great-lakes.net/lakes/ref/ontfact.html
[23]	Marvin CH, Charlton MN, Reiner EJ, et al. (2002) Surficial sediment contamination in Lakes Erie and Ontario: A comparative analysis. J Great Lakes Res 28: 437-450. doi: 10.1016/S0380-1330(02)70596-0
[24]	Marvin CH, Painter S, Rossmann R (2004) Spatial and temporal patterns in mercury contamination in sediments of the Laurentian Great Lakes. Environ Res 95: 351-362.
[25]	Marvin CH, Painter S, Charlton MN, et al. (2004) Trends in spatial and temporal levels of persistent organic pollutants in Lake Erie sediments. Chemosphere 54: 33-40. doi: 10.1016/S0045-6535(03)00660-X
[26]	Dunn RJK, Zigic S, Burling M, et al. (2015) Hydrodynamic and Sediment Modelling within a Macro Tidal Estuary: Port Curtis Estuary, Australia. J Mar Sci Eng 3: 720-744. doi: 10.3390/jmse3030720
[27]	Hessl A, Miller J, Kernan J, et al. (2007) Mapping Paleo-Fire Boundaries from Binary Point Data: comparing Interpolation Methods. The Professional Geographer 59: 87-104. doi: 10.1111/j.1467-9272.2007.00593.x
[28]	Niu Y, Jiao W, Yu H, et al. (2015) Spatial Evaluation of Heavy Metals Concentrations in the Surface Sediment of Taihu Lake. Int J Environ Res Public Health 12: 15028-15039. doi: 10.3390/ijerph121214966
[29]	Ouyang Y, Higman J, Campbell D, et al. (2003) Three-Dimensional Kriging Analysis of Sediment Mercury Distribution: A Case Study. J Am Water Resour Assoc 39: 689-702. doi: 10.1111/j.1752-1688.2003.tb03685.x
[30]	Marvin CH, Charlton MN, Stern GA, et al. (2003) Spatial and temporal trends in sediment contamination in Lake Ontario. J Great Lakes Res 29: 317-331. doi: 10.1016/S0380-1330(03)70437-7
[31]	Beletsky D, Saylor JH, Schwab DJ (1999). Mean circulation in the Great Lakes. J Great Lakes Res 25: 78-93. doi: 10.1016/S0380-1330(99)70718-5
[32]	Environment Canada, Environment Canada’s gasoline regulations, 2009. Available from: http://www.ec.gc.ca/lcpe-cepa/default.asp?lang¼En&n¼54FE5535-1&wsdoc¼8E3C2E9B-38A8-461A-8EC3-C3AA3B1FD585.
[33]	Marvin CH, Charlton MN, Stern GA, et al. (2003) Spatial and temporal trends in sediment contamination in Lake Ontario. J Great Lakes Res 29: 317-331. doi: 10.1016/S0380-1330(03)70437-7

Reader Comments

your name:*

Email:*
© 2016 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)