Effect of Temperature on First-Order Decay Models and Uncertainty Analysis for the Prediction of Methane Emissions in a Landfill Located in the Urban Area of Oaxaca City, Mexico

Landfill disposal continues to be the most economically viable municipal solid waste (MSW) management practice in many countries, including Mexico. Landfills are the third-largest source of methane emissions from human activity, a fact that has significant implications for the environment and human health. Due to the difficulty in experimentally quantifying methane emissions, mathematical models have been employed to predict gas emissions. In this work, three first-order decay models were implemented to estimate methane emissions in a landfill located in the metropolitan area of Oaxaca City, Mexico. Each model incorporated a Van’t Hoff–Arrhenius-type approach for calculating the reaction rate constant. Additionally, an uncertainty analysis of the models was presented, applying Monte Carlo simulations with triangular and log-normal distributions. The results show that the simple model exhibited the best predictive performance. For 2020, the simple model estimated 3,488,392.1 m3 of methane at a temperature of 46 °C, 3,509,625.1 m3 of methane at 47 °C, and 3,530,850.2 m3 of methane at 48 °C. The Monte Carlo simulation with a log-normal distribution exhibited more robust and natural process behavior. For the simple model, the mean was 3,486,946.03, the median was 3,487,154.73, and the standard deviation was 212,095.95. The LandGEM model exhibited more linear methane generation behavior, and the uncertainty analysis confirmed that this model had the lowest predictive capability of the three proposed models.