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Creator:: Paulik, L. Blair, Smith, Brian W., Bergmann, Alan J., Sower, Greg J., Forsberg, Norman D., Teeguarden, Justin G., and Anderson, Kim A.
Abstract:: Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict...

Creator:: Paulik, L. Blair, Smith, Brian W., Bergmann, Alan J., Sower, Greg J., Forsberg, Norman D., Teeguarden, Justin G., and Anderson, Kim A.
Abstract:: Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict...

Creator:: Bergmann, Alan J.
Abstract:: Assessing the risk from exposure to a chemical mixture in the environment can seem prohibitively challenging. Most components of the mixture are not readily identifiable, chemicals may interact to cause other-than-additive toxicity, and the number of potential combinations of environmental contaminants is enormous. These challenges can make it seem impossible...
Resource Type:: Dissertation

Creator:: Paulik, L. Blair, Smith, Brian W., Bergmann, Alan J., Sower, Greg J., Forsberg, Norman D., Teeguarden, Justin G., and Anderson, Kim A.
Abstract:: Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict...
Resource Type:: Article

ScholarsArchive@OSU