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Ecotoxicity assessment of ashes from calcium-rich fuel combustion: contrasting results and regulatory implications.

Mari-Liis UmmikOliver JärvikJanek ReinikAlar Konist
Published in: Environmental science and pollution research international (2024)
The European Union's (EU) regulation for the waste classification based on their ecotoxicological hazard (hazardous property HP14) came into force on 5 July 2018. The regulation advocates the utilisation of computational formulae for the hazard classification of waste associated with hazardous property HP14. Concurrently, ecotoxicological testing remains an alternative. To date, the absence of a consensus regarding test organisms and methodologies has vested EU member states with autonomy in determining the approach for conducting ecotoxicity assessments. The discussions on waste classification are also ongoing globally, namely the discussions under the Basel Convention. This paper endeavours to elucidate whether the widely employed test organisms, Daphnia magna and Aliivibrio fischeri, may serve as suitable indicators for the evaluation of the ecotoxicity of waste. The research is grounded in the examination of ashes derived from a combustion process of calcium-rich fuel. Ecotoxicity testing was conducted on 14 ash samples with a liquid-to-solid ratio of 10:1. The results of the Aliivibrio fischeri testing indicated that all 14 ash samples were non-hazardous in terms of their ecotoxicity. However, the results of the Daphnia magna testing showed the opposite, suggesting that the ash samples may have the potential to be ecotoxic. This study offers valuable insights into ecotoxicity assessment and waste classification, emphasising the need for scientific rigour and comprehensive understanding before making regulatory decisions. It also situates its findings within the broader global context of waste management discussions, particularly those related to international agreements like the Basel Convention.
Keyphrases
  • municipal solid waste
  • sewage sludge
  • machine learning
  • deep learning
  • anaerobic digestion
  • heavy metals
  • transcription factor
  • risk assessment
  • clinical practice
  • particulate matter
  • air pollution