Geology topics

James P. Hickey

Publications and source records attributed to James P. Hickey.

14 recordsLinked to original sources

USGS2009

An expert system for prediction of aquatic toxicity of contaminants

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

Book chapter↗

USGS2007

Trends of brominated diphenyl ethers in fresh and archived Great Lakes fish (1979-2005)

While few environmental measurements of brominated diphenyl ethers (BDEs) were completed prior to the mid-1990s, analysis of appropriately archived samples might enable the determination of contaminant trends back to the introduction of these chemicals. In this paper, we first investigate the stability of BDEs in archived frozen and extracted fish samples, and then characterize trends of these chemicals in rainbow smelt ( Osmerus mordax ) and lake trout ( Salvelinus namaycush ) in each of the Great Lakes between 1979 and 2005. We focus on the four most common congeners (BDE-47, 100, 99 and 153) and use a change-point analysis to detect shifts in trends. Analyses of archived fish samples yielded precise BDE concentration measurements with only small losses (0.8% per year in frozen fish tissues, 2.2% per year in refrigerated extracts). Trends in fish from all Great Lakes showed large increases in BDE concentrations that started in the early to mid-1980s with fairly consistent doubling times (generally 2–4 years except in Lake Erie smelt where levels increased very slowly), though concentrations and trends show differences by congener, fish species and lake. The most recent data show that accumulation rates are slowing, and concentrations of penta- and hexa-congeners in trout from Lakes Ontario and Michigan and smelt from Lake Ontario started to decrease in the mid-1990s. Trends in smelt and trout are evolving somewhat differently, and trout concentrations in the five lakes are now ranked as Michigan > Superior = Ontario > Huron = Erie, and smelt concentrations as Michigan > Ontario > Huron > Superior > Erie. The analysis of properly archived samples permits the reconstruction of historical trends, congener distributions, biomagnification and other information that can aid the understanding and management of these contaminants.

Chemosphere↗

USGS2005

Estimation of inorganic species aquatic toxicity

The acute aquatic toxicities (narcoses) for a range of organism types may be estimated with LSER for a large number of inorganic and organometal species, many with an accuracy at or within an order of magnitude. Optimum estimations make use of a bioavailable metal fraction and a more accurate structure(s) for the toxic solution species. The estimated toxicities for a number of salts were quite different from the observed values, likely due to a dominant specific toxicity mechanism other than baseline narcosis. The tool still requires fine-tuning.

Book chapter↗

USGS2003

Assessment of lake sturgeon ( Acipenser fulvescens ) spawning efforts in the lower St. Clair River, Michigan

One of the most threatened remaining populations of lake sturgeon in the Great Lakes is found in the connecting channels between Lake Huron and Lake Erie. Only two spawning grounds are presently known to be active in this region, and both are in the St. Clair River. The spawning reef in the St. Clair River delta has been recently colonized by round gobies ( Neogobius melanostomus ) in densities up to 25/m 2 , raising concerns regarding predation on the benthic-oriented eggs and larvae of the sturgeon. Investigations in 1998–1999 showed that while round goby predation does occur, a number of other factors may be equally affecting sturgeon spawning success, including few spawning adults (< 60), suspected poaching pressure, low retention rate of eggs on the reef, low hatch rate (~0.5%), the presence of organic contaminants, and predation from native and exotic invertebrates and fish. Overall, we estimate that less than 1% of the eggs deposited during a spawning run survive to hatch. We were able to increase the egg hatch rate to 16% by placing eggs in predator-exclusion chambers on the reef. The fate of the larvae is uncertain. Two weeks after hatching, no larvae were found on the reef. We were unable to find them anywhere else in the river, nor was predation on larvae noted in either year. There were factors other than predation affecting larval survival in 1999. There was a higher silt load on the reef than in 1998 and large numbers of dead larvae were found. Recruitment success from this site could be improved by utilizing techniques to increase the number of eggs on the reef, such as reducing the illegal take of adult fish and by placing eggs in predator-exclusion chambers to increase hatch rate.

Michigan↗

USGS2002

Linear solvation energy relationships: "rule of thumb" for estimation of variable values

For the linear solvation energy relationship (LSER), values are listed for each of the variables (V i /100, π*, &beta m , α m ) for fundamental organic structures and functional groups. We give the guidelines to estimate LSER variable values quickly for a vast array of possible organic compounds such as those found in the environment. The difficulty in generating these variables has greatly discouraged the application of this quantitative structure-activity relationship (QSAR) method. This paper present the first compilation of molecular functional group values together with a utilitarian set of the LSER variable estimation rules. The availability of these variable values and rules should facilitate widespread application of LSER for hazard evaluation of environmental contaminants.

Environmental Science & Technology↗

USGS2000

Natural remediation in the Great Lakes

Overall, the existence of stricter environmental laws during the last 30 years and a reduction in the manufacturing base in the Great Lakes has resulted in improvement in conditions in harbors, rivers, and nearshore waters. Problems remain, such as the inability to dredge certain harbors and remove sediments because of lack of disposal facilities for contaminated sediments. Because of the wide extent of of contaminated sediments in the Great Lakes, much work remains to be done to document the condition of contaminated areas and the degree to which remediation of these areas is occurring from biotic and abiotic natural processes.

Book chapter↗

USGS1999

Hazard evaluation of ten organophosphorous insecticides against the midge, Chironomus riparius via QSAR

Toxicities of ten organophosphorus (OP) insecticides were measured against midge larvae (Chironomus riparius) under varying temperature (11, 18, and 25°C) and pH (6, 7, and 8) conditions and with and without sediment. Toxicity usually increased with increasing temperature and was greater in the absence of sediment. No trend was found with varying pH. A series of unidimensional parameters and multidimensional models were used to describe the changes in toxicity. Log K ow was able to explain about 40–60% of the variability in response data for aqueous exposures while molecular volume and aqueous solubility were less predictive. Likewise, the linear solvation energy relationship (LSER) model only explained 40–70% of the response variability, suggesting that factors other than solubility were most important for producing the observed response. Molecular connectivity was the most useful for describing the variability in the response. In the absence of sediment, 1 χ v and 3 κ were best able to describe the variation in response among all compounds at each pH (70–90%). In the presence of sediment, even molecular connectivity could not describe the variability until the partitioning potential to sediment was accounted for by assuming equilibrium partitioning. After correcting for partitioning, the same molecular connectivity terms as in the aqueous exposures described most of the variability, 61–87%, except for the 11°C data where correlations were not significant. Molecular connectivity was a better tool than LSER or the unidimensional variables to explain the steric fitness of OP insecticides which was crucial to the toxicity.

SAR and QSAR in Environmental Research↗

USGS1999

Estimation of environmental properties for inorganic compounds using LSER

The Great Lakes Science Center has devised values for inorganic species for use in the environmental property- predictive quantitative structure-activity relationships (QSAR) Linear Solvation Energy Relationship (LSER). Property estimation has been difficult for inorganic species. In this presentation aqueous solubility, bioconcentration and acute aquatic toxicity are estimated for inorganic compounds using existing LSER equations. The best estimations arise from the most accurate description of predominant solution species, many within an order of magnitude. The toxicities also depend on an estimation of the bioactive amount and configuration. A number of anion/cation combinations (salts) still resist accurate property estimation, and the reasons currently are not understood. These new variable values will greatly extend the application and utility of LSER for the estimation of environmental properties.

Conference Paper↗

USGS1998

Estimation of octanol/water partition coefficients using LSER parameters

The logarithms of octanol/water partition coefficients, log Kow , were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for log Kow was 0.49. The regression equation was then used to estimate log Kow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

Advances in Environmental Research↗

USGS1997

Evaluation of estimation methods for organic carbon normalized sorption coefficients

A critically evaluated set of 94 soil water partition coefficients normalized to soil organic carbon content ( K oc ) is presented for 11 classes of organic chemicals. This data set is used to develop and evaluate K oc estimation methods using three different descriptors. The three types of descriptors used in predicting K oc were octanol/water partition coefficient ( K ow ), molecular connectivity ( m X t ) and linear solvation energy relationships (LSERs). The best results were obtained estimating K oc from K ow , though a slight improvement in the correlation coefficient was obtained by using a two-parameter regression with K ow and the third order difference term from m X t . Molecular connectivity correlations seemed to be best suited for use with specific chemical classes. The LSER provided a better fit than m X t but not as good as the correlation with K oc . The correlation to predict K oc from K ow was developed for 72 chemicals; log K oc = 0.903* log K ow + 0.094. This correlation accounts for 91% of the variability in the data for chemicals with log K ow ranging from 1.7 to 7.0. The expression to determine the 95% confidence interval on the estimated K oc is provided along with an example for two chemicals of different hydrophobicity showing the confidence interval of the retardation factor determined from the estimated K oc . The data showed that K oc is not likely to be applicable for chemicals with log K ow < 1.7. Finally, the K oc correlation developed using K ow as a descriptor was compared with three nonclass-specific correlations and two 'commonly used' class-specific correlations to determine which method(s) are most suitable.

Water Environment Research↗

USGS1996

Linear solvation energy relationships (LSER): 'rules of thumb' for V i /100, π * , Β m , and α m estimation and use in aquatic toxicology

This chapter provides a listing of the increasing variety of organic moieties and heteroatom group for which Linear Solvation Energy Relationship (LSER) values are available, and the LSER variable estimation rules. The listings include values for typical nitrogen-, sulfur- and phosphorus-containing moieties, and general organosilicon and organotin groups. The contributions by an ion pair situation to the LSER values are also offered in Table 1, allowing estimation of parameters for salts and zwitterions. The guidelines permit quick estimation of values for the four primary LSER variables V i /100, π * , Β m , and α m by summing the contribtuions from its components. The use of guidelines and Table 1 significantly simplifies computation of values for the LSER variables for most possible organic comppounds in the environment, including the larger compounds of environmental and biological interest.

Book chapter↗

USGS1995

Linear solvation energy relationship of the limiting partition coefficient of organic solutes between water and activated carbon

A linear solvation energy relationship has been found for 353 values of the limiting adsorption coefficients of diverse chemicals: log K = −0.37 + 0.0341 V i − 1.07β + D + 0.65 P with R = 0.951, s = 0.51, n = 353, and F = 818.0, where V i is the intrinsic molar volume; β is a measure of the hydrogen bond acceptor strength of the solute; D is an index parameter for the research group which includes the effects of the different types of carbon used, the temperature, and the length of time allowed for the adsorption equilibrium to be established; and P is an index parameter for the flatness of the molecule. P is defined to be unity if there is an aromatic system in the molecule or if there is a double bond or series of conjugated double bonds with no more that one non-hydrogen atom beyond the double bond and zero otherwise. A slightly better fit is obtained if the two-thirds power of V i is used as a measure of the surface area in place of the volume term: log K = −1.75 + 0.227 V 2/3 − 1.10β + D + 0.60 P with R = 0.954, s = 0.49, n = 353, and F = 895.39. This is the first quantitative measure of the effect of the shape of the molecule on its tendency to be adsorbed on activated carbon.

Environmental Science & Technology↗

USGS1995

Baseline risk assessment for aquatic life for the Buffalo River, New York, Area of Concern

The Great Lakes National Program Office of the U.S. Environmental Protection Agency initiated the Assessment and Remediation of Contaminated Sediments (ARCS) program to address concerns of environmental degradation at 43 Areas of Concern in the Great Lakes. In our first report (Passino-Reader et al. 1992), we developed a generic approach for baseline hazard evaluation of aquatic life in the Great Lakes Areas of Concern. In this report, we demonstrate the application of the generic approach to the Buffalo River (New York) Area of Concern. Using available historical data on residues in sediments, water, and biota, we evaluated exposure for 41 contaminants from the Buffalo River for eight taxa of fish and invertebrates representing the major trophic levels in the Buffalo River. By comparing exposure concentrations with reference toxicities, we calculated risk to the eight receptor organisms for typical and worst cases of exposure to the 41 contaminants. For mixtures of the contaminants present at the Buffalo River, primarily metals and polyaromatic hydrocarbons, we compared sediment concentrations with effects range-low (EL-R) values as reference values for toxicity of mixtures to estimate risk to aquatic biota.

Report↗

USGS1988

Linear solvation energy relationships for toxicity of selected organic chemicals to Daphnia pulex and Daphnia magna

In the Laurentian Great Lakes, more than 300 contaminants have been identified in fish, other biota, water, and sediment. Current hazard assessment of these chemicals by the National Fisheries Research Center-Great Lakes is based on their toxicity, occurrence in the environment, and source. Although scientists at the Center have tested over 70 chemicals with the crustacean Daphnia pulex , the number of experimental data needed to screen the huge array of chemicals in the Great Lakes exceeds the practical capabilities of conducting bioassays. This limitation can be partly circumvented, however, by using mathematical models based on quantitative structure-activity relationships (QSAR) to provide rapid, inexpensive estimates of toxicity. Many properties of chemicals, including toxicity, bioaccumulation and water solubility are well correlated and can be predicted by equations of the generalized linear solvation energy relationships (LSER). The equation we used to model solute toxicity is Toxicity = constant + m VI/100 + s (π* + dδ) + b βm + a αm where VI = intrinsic (Van der Waals) molar volume; π* = molecular dipolarity/polarizability; δ = polarizability 'correction term'; βm = solute hydrogen bond acceptor basicity; and αm = solute hydrogen bond donor acidity. The subscript m designates solute monomer values for α and β. We applied the LSER model to 48-h acute toxicity data (measured as immobilization) for six classes of chemicals detected in Great Lakes fish. The following regression was obtained for Daphnia pulex (concentration = μM): log EC50 = 4.86 - 4.35 VI/100; N = 38, r2 = 0.867, sd = 0.403 We also used the LSER modeling approach to analyze to a large published data set of 24-h acute toxicity for Daphnia magna ; the following regression resulted, for eight classes of compounds (concentration = mM): log EC50 = 3.88 - 4.52 VI/100 - 1.62 π* + 1.66 βm - 0.916 αm; N = 62, r2 = 0.859, sd = 0.375 In addition we developed computer software that identifies chemical structures, estimates the LSER parameters, and predicts toxicity. The LSER models promise to be effective in differentiating between reactive and nonreactive toxicity behavior where other models have failed. Contaminants with reactive behavior are generally the most toxic and rank highest in hazard assessment of environmental chemicals.

Proceedings of the QSAR↗