Development of a conceptual framework for risk assessment of elevated internal temperatures in landfills

Academic Article

Abstract

  • Subsurface elevated temperatures (SETs) often occur in landfills and pose great threats to their structural and environmental integrity. Current landfill gas monitoring practices only recommend maintaining certain soil gases percentages, with no integrated strategy for predicting subsurface temperature. As a solution, this paper proposes a comprehensive risk assessment framework specific to SET mitigation. The risk model (RSET) was constructed by incorporating independent gas variables (methane, carbon dioxide, oxygen, residual nitrogen, and temperature) identified in the existing literature as SET indicators, and analyzing gas-well data from the Bridgeton Landfill. Upon identifying these gas indictors and their safety thresholds, we found a significant association (p-value < 0.05) between safe–unsafe ranges of gas variables and subsurface temperature. Temperatures above 80 °C were found to be associated with 100%, 92.3%, and only 4% of the unsafe ranges of methane, residual nitrogen, and oxygen, respectively. As the correlation between gases and temperature seemed to vary for different gas combinations, we developed the RSET by incorporating into these correlation coefficients event intensities specific to certain gas combinations, and then normalizing the RSET scale over a 0–10 range. Over the study period, we identified 22.29% of cases as medium risk at the Bridgeton Landfill and 17.7% as high risk. SETs are governed by different combinations of safe–unsafe ranges of parameters rather than any individual parameters alone. Subsequently, we used a decision tree algorithm to assess the risk types associated with RSET values. The proposed RSET can serve as a monitoring and decision-making tool for landfill authorities for managing and preventing SET incidents.
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    Digital Object Identifier (doi)

    Author List

  • Sabrin S; Nazari R; Karimi M; Fahad MGR; Everett J; Peters R
  • Volume

  • 782