Predicting water quality criteria for protecting aquatic life from physicochemical properties of metals or metalloids.

Metals are widely distributed pollutants in water and can have detrimental effects on some aquatic life and humans. Over the past few decades, the United States Environmental Protection Agency (U.S. EPA) has published a series of criteria guidelines, which contain specific criteria maximum concentrations (CMCs) for 10 metals. However, CMCs for other metals are still lacking because of financial, practical, or ethical restrictions on toxicity testing. Herein, a quantitative structure activity relationship (QSAR) method was used to develop a set of predictive relationships, based on physical and chemical characteristics of metals, and predict acute toxicities of each species for five phyla and eight families of organisms for 25 metals or metalloids. In addition, species sensitivity distributions (SSDs) were developed as independent methods for determining predictive CMCs. The quantitative ion character-activity relationships (QICAR) analysis showed that the softness index (σp), maximum complex stability constants (log -β(n)), electrochemical potential (ΔE(0)), and covalent index (X(m)(2)r) were the minimum set of structure parameters required to predict toxicity of metals to eight families of representative organisms. Predicted CMCs for 10 metals are in reasonable agreement with those recommended previously by U.S. EPA within a difference of 1.5 orders of magnitude. CMCs were significantly related to σp (r(2) = 0.76, P = 7.02 × 10(-9)) and log -β(n) (r(2) = 0.73, P = 3.88 × 10(-8)). The novel QICAR-SSD model reported here is a rapid, cost-effective, and reasonably accurate method, which can provide a beneficial supplement to existing methodologies for developing preliminarily screen level toxicities or criteria for metals, for which little or no relevant information on the toxicity to particular classes of aquatic organisms exists.