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Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites
Published on: November 28, 2014
Toxicity and risk assessment of landfill leachate on the earthworm, Eisenia fetida
Krishna Gautam1, Namrata Pandey2, Anshul Tiwari3
1Ecotoxicology Laboratory, REACT Division, C.R. Krishnamurti (CRK) Campus, CSIR-Indian Institute of Toxicology Research, Lucknow 226008, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
Abstract:
Landfill leachates have complex cocktails of metals, pesticides and polycyclic aromatic hydrocarbons (PAHs), posing significant yet often overlooked ecological risks through mixture toxicity. This study unveils how seasonal monsoon dynamics amplify leachate contaminant levels from the Dubagga landfill site, Lucknow (India), triggering cascading physiological and molecular disruptions in the earthworm, Eisenia fetida, upon acute and chronic exposures. Post-monsoon leachate contained 1841 μg L-1 PAHs, 196 μg L-1 pesticides and 10,710 μg L-1 metal - a 150-fold increase in chemical diversity compared to pre-monsoon samples. While acute exposure caused no mortality, chronic exposure (56 days) reduced cocoon production by 67 % and hatchling viability by 89 % at 100 % concentration, unmasking latent reproductive toxicity. Oxidative stress increased markedly, evidenced by a 3.8-fold surge in reactive oxygen species and dysregulation of antioxidant enzymes. Concurrently, neurotoxicity was demonstrated by a 4.7-fold elevation in acetylcholinesterase activity. Transcriptomics revealed differentially expressed genes, dominated by oxidative phosphorylation suppression (FDR < 0.01) and mRNA surveillance pathway activation, a novel biomarker signature of mixture stress. Paradoxically, conventional risk quotients (RQ < 1) underestimated hazards, as metal-PAH complexes demonstrated combined neurotoxic effects exceeding individual contaminant predictions by 2.4-fold. These findings challenge traditional, single-contaminant risk models, advocating for mixture toxicity indices in landfill management. By bridging chemical analysis, multi-omics and ecotoxicology, this work provides a blueprint for detecting hidden interaction effects in complex environmental matrices, a critical step toward safeguarding soil ecosystems in an era of escalating waste generation and climate volatility.

