Obtaining a complex picture of how pollutants synergistically influence toxicity of a system requires statistical correlation of chemical and ecotoxicological data. In this study, we determined concentrations of eight potentially toxic metals (PTMs) and four groups of organic pollutants in 15 sewage sludge and 12 river sediment samples, then linked measured contaminant concentrations to the toxicity of each matrix through constrained correspondence analysis (CCA). In sludge samples, Fig, As, hexachlorohexane (HCH), polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecane (HBCD) influenced the toxicity profiles, with the first four having significant effects and HBCD being marginally significant. In sediment samples, Hg, As, PBDEs, hexachlorobenzene (HCB), dichlorodiphenyltrichloroethane (DDT), HBCD, HCH and polycyclic aromatic hydrocarbons (PAHs) were found to explain toxicity profiles with Hg, As, PBDEs, HCB, DDT, HBCD, and HCH having significant effects and PAHs being marginally significant. Interestingly, HCH was present in small amounts yet proved to have a significant impact on toxicity. To the contrary, PAHs were often present in high amounts, yet proved to be only marginally significant for sediment toxicity. These results indicate that statistical correlation of chemical and ecotoxicological data can provide more detailed understanding of the role played by specific pollutants in shaping toxicity of sludge and sediments. (C) 2016 Elsevier B.V. All rights reserved.