A Monte Carlo Method for Quantifying Uncertainties in the Official Greenhouse Gas Emission Factors Database of Costa Rica

Abstract

With the publication of the latest version of ISO 14064-1, the National Carbon Neutrality Program of Costa Rica included measurement uncertainty as a mandatory requirement for the reporting of greenhouse gas (GHG) inventories as an essential parameter to have precise and reliable results. However, technical gaps remain for an optimal implementation of this requirement, including a lack of information regarding uncertainties in the official database of Costa Rican emission factors. The present article sought to fill the gap of uncertainty information for 22 emission factors from this database, providing uncertainty values through the collection of input information, use of expert criteria, fitting of probability distributions, and the application of the Monte Carlo simulation method. Emission factors were classified into three groups according to their estimation methods and their information sources. Five probability distributions were chosen and fitted to the input data based on their previous application in the field. Standard uncertainties and 95% confidence intervals were estimated for each emission factor as the standard deviations and differences between the 2.5% and 97.5% percentiles of their simulated data. As expected, most of the standard uncertainties were estimated between 15% and 50% of the value of the emission factor, and confidence intervals tended to asymmetry as the standard uncertainties or the number of input data for the emission factor estimation increased. High consistency was found between these results and values reported in other studies. These results are critical to complement the official database of Costa Rican emission factors and for national users to estimate the uncertainties of their greenhouse gas inventories, easing to comply with national environmental policies by adapting to international requirements in the fight against climate change. Additionally, improvement opportunities were identified to update the emission factors from livestock enteric fermentation, manure management, waste treatments, and non-energy use of lubricants, whose estimations are based on outdated references and methodologies. An opportunity to improve and reduce the remarkably high uncertainties for emission factors associated with the biological treatment of solid waste through studies adapted to the specific characteristics of tropical countries like Costa Rica was also pointed out.

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