Equations to Predict Carbon Monoxide Emissions from Amazon Rainforest Fires

Authors

Sarah M. Gallup, Colorado State University
Bonne Ford, Colorado State University
Stijn Naus, National Institute of Water and Atmospheric Research
John L. Gallup, Portland State UniversityFollow
Jeffrey R. Pierce, Colorado State University

Sponsor

We acknowledge funding from NSF grant AGS1950327 and National Aeronautics and Space Administration (NASA) Health and Air Quality Applied Sciences Team grant 80NSSC21K0429.

Published In

Fire

Document Type

Article

Publication Date

12-27-2024

Subjects

Emission inventories, Rain forests, Carbon monoxide, Carbon emissions

Abstract

Earth systems models (ESMs), which can simulate the complex feedbacks between climate and fires, struggle to predict fires well for tropical rainforests. This study provides equations that predict historic carbon monoxide emissions from Amazon rainforest fires for 2003–2018, which could be implemented within ESMs’ current structures. We also include equations to convert the predicted emissions to burned area. Regressions of varying mathematical forms are fitted to one or both of two fire CO emission inventories. Equation accuracy is scored on r², bias of the mean prediction, and ratio of explained variances. We find that one equation is best for studying smoke consequences that scale approximately linearly with emissions, or for a fully coupled ESM with online meteorology. Compared to the deforestation fire equation in the Community Land Model ver. 4.5, this equation’s linear-scale accuracies are higher for both emissions and burned area. A second equation, more accurate when evaluated on a log scale, may better support studies of certain health or cloud process consequences of fires. The most accurate recommended equation requires that meteorology be known before emissions are calculated. For all three equations, both deforestation rates and meteorological variables are key groups of predictors. Predictions nevertheless fail to reproduce most of the variation in emissions. The highest linear r²s for monthly and annual predictions are 0.30 and 0.41, respectively. The impossibility of simultaneously matching both emission inventories limits achievable fit. One key cause of the remaining unexplained variability appears to be noise inherent to pan-tropical data, especially meteorology.

Rights

: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/)

Locate the Document

https://doi.org/10.3390/fire7120477

DOI

10.3390/fire7120477

Persistent Identifier

https://archives.pdx.edu/ds/psu/43131

Citation Details

Gallup, S. M., Ford, B., Naus, S., Gallup, J. L., & Pierce, J. R. (2024). Equations to Predict Carbon Monoxide Emissions from Amazon Rainforest Fires. Fire, 7(12), 477.