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Evaluating the use of electrical resistivity imaging technique for improving CH4 and CO2 emission rate estimations in landfills

Georgaki, I; Soupios, P; Sakkas, N; Ververidis, F; Trantas, E; Vallianatos, F; Manios, T; (2008) Evaluating the use of electrical resistivity imaging technique for improving CH4 and CO2 emission rate estimations in landfills. SCI TOTAL ENVIRON , 389 (2-3) 522 - 531. 10.1016/j.scitotenv.2007.08.033.

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Abstract

In order to improve the estimation of surface gas emissions in landfill, we evaluated a combination of geophysical and greenhouse gas measurement methodologies. Based on fifteen 2D electrical resistivity tomographies (ERTs), longitudinal cross section images of the buried waste layers were developed, identifying place and cross section size of organic waste (OW), organic waste saturated in leachates (SOW), low organic and non-organic waste. CH4 and CO2 emission measurements were then conducted using the static chamber technique at 5 surface points along two tomographies: (a) across a high-emitting area, ERT#2, where different amounts of relatively fresh OW and SOW were detected, and (b) across the oldest (at least eight years) cell in the landfill, ERT#6, with significant amounts of OW. Where the highest emission rates were recorded, they were strongly affected by the thickness of the OW and SOW fraction underneath each gas sampling point. The main reason for lower than expected values was the age of the layered buried waste. Lower than predicted emissions were also attributed to soil condition, which was the case at sampling points with surface ponding, i.e. surface accumulation of leachate (or precipitated water). (C) 2007 Elsevier B.V. All rights reserved.

Type:Article
Title:Evaluating the use of electrical resistivity imaging technique for improving CH4 and CO2 emission rate estimations in landfills
DOI:10.1016/j.scitotenv.2007.08.033
Keywords:greenhouse gases, landfill, solid wastes, geophysical, leachate, static chamber, GAS EMISSIONS, METHANE, FLUXES, SITES
UCL classification:UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Institute for Risk and Disaster Reduction

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