ISSN: 2636-8498
Which kinetic model best fits the methane production on pig farms with covered lagoon digesters?
1Department of Agricultural Engineering, Federal University of Viçosa, Viçosa, MG, Brazil;
2Universidade Federal de Minas Gerais, Instito de Clencias Agrarias, Montes Claros, Brazil
3Universidade Estadual do Maranhão, São Luís, Brazil
Environmental Research & Technology 2021; 4(4): 308-316 DOI: 10.35208/ert.916002
Full Text PDF

Abstract

The volumetric production of biogas can be estimated through kinetic models, although many of them have not been validated adequately in full-scale systems with specific operational conditions in tropical countries. This study aimed to evaluate the applicability of these ki-netic models to estimate methane production in pig farming operated with covered lagoon digesters (CLD, to inform: Chen-Hashimoto, First-order, Cone, Modified Gompertz, Modified Stover-Kincannon and Deng. The input data were obtained through the monitoring of two CLD in pig farming located in Minas Gerais-Brazil. The analyzed parameters were methane composition, the temperature of the substrate, chemical oxygen demand (COD), and volatile solids. The real production of methane (Pactual) was determined in relation to the electric power production at the internal combustion engine. The results obtained for Pactual and the models were compared through regression analysis (t-test, α=1%). All of the evaluated models overestimate the methane production in comparison with Pactual (405.0 m³CH4 d-1). The smallest difference between the CH4 production and the measurement on the pig farm was ob-tained with Chen model, overestimating approximately 16.3%, while the highest estimate was 38.5% obtained with the Modified Stover-Kincannon model. The results showed the absence of statistical differences among the real data (monitored system) and the simulated data (p-value>0.01). The mathematical kinetic models are considered a reliable tool to evaluate the en-ergetic potential of biogas in pig farming with CLD from operational simplicity and low cost.