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Prediction of ecotoxicity of hydrocarbon‐contaminated soils using physicochemical parameters
Author(s) -
Wong Diana C. L.,
Chai Eric Y.,
Chu Karin K.,
Dorn Philip B.
Publication year - 1999
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.5620181131
Subject(s) - eisenia fetida , earthworm , germination , environmental chemistry , ecotoxicity , total petroleum hydrocarbon , ecotoxicology , chemistry , soil contamination , soil water , toxicity , biology , botany , agronomy , ecology , organic chemistry
The physicochemical properties of eight hydrocarbon‐contaminated soils were used to predict toxicity to earthworms (Eisenia fetida) and plants. The toxicity of these preremediated soils was assessed using earthworm avoidance, survival, and reproduction and seed germination and root growth in four plant species. No‐observed‐effect and 25% inhibitory concentrations were determined from the earthworm and plant assays. Physical property measurements and metals analyses of the soils were conducted. Hydrocarbon contamination was characterized by total petroleum hydrocarbons, oil and grease, and GC boiling‐point distribution. Univariate and multivariate statistical methods were used to examine relationships between physical and chemical properties and biological endpoints. Soil groupings based on physicochemical properties and toxicity from cluster and principal component analyses were generally similar. Correlation analysis identified a number of significant relationships between soil parameters and toxicity that were used in univariate model development. Total petroleum hydrocarbons by gas chromatography and polars were identified as predictors of earthworm avoidance and survival and seed germination, explaining 65 to 75% of the variation in the data. Asphaltenes also explained 83% of the variation in seed germination. Gravimetric total petroleum hydrocarbons explained 40% of the variation in earthworm reproduction, whereas 43% of the variation in plant root growth was explained by asphaltenes. Multivariate one‐component partial least squares models, which identified predictors similar to those identified by the univariate models, were also developed for worm avoidance and survival and seed germination and had predictive powers of 42 and 29%, respectively.