The objective of this doctoral dissertation is to develop a model to predict the phototoxicity of petroleum and petroleum components to aquatic organisms. Petroleum contains polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs and heterocyclic PAHs some of which absorb light in the ultraviolet light (UV) and visible (VIS) regions. The result is increased photo-enhanced toxicity, by a factor of two to greater than 1000 in the presence of light.
The PAHs in petroleum differ in their properties, such as octanol-water partitioning coefficients and molar absorption spectra, and each may exhibit phototoxicity. It is inefficient and impractical to conduct toxicity tests on all the chemicals and all the organisms of concern. Even if the testing was undertaken, it is not clear how to interpret the results and use them for phototoxic risk assessments where light conditions and time of exposure vary. Accordingly, there has been a considerable effort expended to develop models to predict the phototoxicity of PAHs to the aquatic organisms. In each of the previous modeling frameworks various combination of the underlying factors in phototoxicity were incorporated to varying degrees. However, no model included all elements in a unified modeling framework such that the model can be applicable to all PAHs, PAH mixtures, organisms, and light exposure conditions.
In this dissertation, a phototoxic target lipid model (PTLM) is developed to predict phototoxicity of single PAHs measured either as median lethal concentration (LC50) at a fixed duration of exposure or median lethal time (LT50) at a fixed concentration. The model accounts for differences in the physical and chemical properties of PAHs and test species sensitivities, as well as variations in light characteristics, such as length of exposure, and the light source irradiance spectrum and intensity. The PTLM is based on the narcotic target lipid model (NTLM) of PAHs. Both models rely on the assumption that mortality occurs when the toxicant concentration in the target lipid of the organism reaches a threshold concentration. The model is calibrated using 333 observations of LC50s and LT50s for 20 individual PAHs, 15 test species, and various UV light exposure conditions and times ranging from 1 hour to 100 hours. The LC50 concentrations range from less than 0.1 to greater that 104 μg/L. The model has two fitting parameters that are shown to be constant across PAHs and organisms. The compound specific parameters incorporated in the PTLM are the octanol-water partition coefficient and molar absorption coefficient. The critical target lipid body burden is the only organism specific parameter. The root mean square error (RMSE) of prediction for log(LC50) and log(LT50) are 0.473 and 0.382, respectively. Other phototoxic components of petroleum include alkylated PAHs (APAHs) and benzothiophenes. The PTLM is validated by predicting the observed phototoxic LT50 and LC50 of those chemicals exposed to four different species under different light conditions with RMSE = 0.478. The results support the PTLM capability to predict the phototoxicity of single PAHs for organisms with a wide range of sensitivity and for various light exposure conditions.
Modeling the phototoxicity of mixtures is accomplished by using the toxic unit (TU) approach and TU additivity. The model is validated by predicting the phototoxicity of the binary and ternary mixtures of three PAHs, pyrene, anthracene, and fluoranthene exposed to Americamysis bahia and Menidia beryllina. The comparison between the observed and predicted phototoxicity for the mixtures results in RMSE = 0.274.
The PTLM is applied to predict petroleum phototoxicity of the water accommodated fraction for three field collected oil samples, MASS (neat oil), CTC (moderately weathered oil), and Juniper (heavily weathered oil) exposed to four aquatic species indigenous to the Gulf of Mexico, M. beryllina, A. bahia, Cyprinodon variegatus, and Fundulus grandis using natural or simulated solar radiation. For cases in which no phototoxicity was observed, the PTLM predictions are correct in over 70% of the cases (10 out of 14 predictions). When toxicity was observed the RMSE = 0.321.
|Advisor:||Di Toro, Dominic M.|
|Commitee:||Allen, Herbert E., Neal, Sharon L., Stubblefield, William A.|
|School:||University of Delaware|
|Department:||Department of Civil and Environmental Engineering|
|School Location:||United States -- Delaware|
|Source:||DAI-B 78/04(E), Dissertation Abstracts International|
|Keywords:||Deep water horizon oil spill, Oil spill phototoxicity risk, PAHs phototoxicity modeling, Petroleum phototoxicity modeling, Phototoxic target lipid model, Polycyclic aromatic hydrocarbons|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be