Abstract
Large amount of greenhouse gases (CO2 and CH4) are generated through the disposal of municipal solid waste in landfill. Methane is an increasing concern of greenhouse gas. Complex processes taking place within the landfill leads to formation of gas which has to be managed. In order to manage this landfill gas (LFG), it is necessary to estimate it on daily basis. Conventional hard computing techniques as well as modern soft computing techniques have been used to model LFG estimation. The present study uses soft computing method of linear genetic programming (LGP), to estimate the landfill gas emission for Pune city (India). Data from the simulated laboratory-scale landfill have been used, and the temporal models are developed. Landfill gas is estimated using previous values of the gas recorded. The performance of the models has been analyzed using correlation coefficient (r) and root mean square error (RMSE). It is found that the model results are in good agreement with the actual values.
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Tikhe, K.S., Balapgol, B.S., Mali, S.T. (2019). Estimation of Landfill Gas Using Genetic Programming. In: Kalamdhad, A., Singh, J., Dhamodharan, K. (eds) Advances in Waste Management . Springer, Singapore. https://doi.org/10.1007/978-981-13-0215-2_12
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DOI: https://doi.org/10.1007/978-981-13-0215-2_12
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