Optimizing the Temperature Sensitivity of the Isoprene Emission Model MEGAN in Different Ecosystems Using a Metropolis-Hastings Markov Chain Monte Carlo Method
(2025) In Journal of Geophysical Research: Biogeosciences 130(5).- Abstract
Isoprene is a reactive hydrocarbon emitted to the atmosphere in large quantities by terrestrial vegetation. Annual total isoprene emissions exceed 300 Tg a−1, but emission rates vary widely among plant species and are sensitive to meteorological and environmental conditions including temperature, sunlight, and soil moisture. Due to its high reactivity, isoprene has a large impact on air quality and climate pollutants such as ozone and aerosols. It is also an important sink for the hydroxyl radical which impacts the lifetime of the important greenhouse gas methane along with many other trace gas species. Modeling the impacts of isoprene emissions on atmospheric chemistry and climate requires accurate isoprene emission... (More)
Isoprene is a reactive hydrocarbon emitted to the atmosphere in large quantities by terrestrial vegetation. Annual total isoprene emissions exceed 300 Tg a−1, but emission rates vary widely among plant species and are sensitive to meteorological and environmental conditions including temperature, sunlight, and soil moisture. Due to its high reactivity, isoprene has a large impact on air quality and climate pollutants such as ozone and aerosols. It is also an important sink for the hydroxyl radical which impacts the lifetime of the important greenhouse gas methane along with many other trace gas species. Modeling the impacts of isoprene emissions on atmospheric chemistry and climate requires accurate isoprene emission estimates. These can be obtained using the empirical Model of Emissions of Gases and Aerosols from Nature (MEGAN), but the parameterization of this model is uncertain due in part to limited field observations. In this study, we use ground-based measurements of isoprene concentrations and fluxes from 11 field sites to assess the variability of the isoprene emission temperature response across ecosystems. We then use these observations in a Metropolis-Hastings Markov Chain Monte Carlo (MHMCMC) data assimilation framework to optimize the MEGAN temperature response function. We find that the performance of MEGAN can be significantly improved at several high-latitude field sites by increasing the modeled sensitivity of isoprene emissions to past temperatures. At some sites, the optimized model was nearly four times more sensitive to temperature than the unoptimized model. This has implications for air quality modeling in a warming climate.
(Less)
- author
- organization
- publishing date
- 2025-05
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ecosystem, isoprene, model, Monte Carlo, observations, optimization
- in
- Journal of Geophysical Research: Biogeosciences
- volume
- 130
- issue
- 5
- article number
- e2025JG008806
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- scopus:105005221416
- ISSN
- 2169-8953
- DOI
- 10.1029/2025JG008806
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025. The Author(s).
- id
- 1eef8e9a-7986-45a2-a57d-c946d41a2aa9
- date added to LUP
- 2025-05-30 10:27:15
- date last changed
- 2025-06-02 16:26:23
@article{1eef8e9a-7986-45a2-a57d-c946d41a2aa9,
abstract = {{<p>Isoprene is a reactive hydrocarbon emitted to the atmosphere in large quantities by terrestrial vegetation. Annual total isoprene emissions exceed 300 Tg a<sup>−1</sup>, but emission rates vary widely among plant species and are sensitive to meteorological and environmental conditions including temperature, sunlight, and soil moisture. Due to its high reactivity, isoprene has a large impact on air quality and climate pollutants such as ozone and aerosols. It is also an important sink for the hydroxyl radical which impacts the lifetime of the important greenhouse gas methane along with many other trace gas species. Modeling the impacts of isoprene emissions on atmospheric chemistry and climate requires accurate isoprene emission estimates. These can be obtained using the empirical Model of Emissions of Gases and Aerosols from Nature (MEGAN), but the parameterization of this model is uncertain due in part to limited field observations. In this study, we use ground-based measurements of isoprene concentrations and fluxes from 11 field sites to assess the variability of the isoprene emission temperature response across ecosystems. We then use these observations in a Metropolis-Hastings Markov Chain Monte Carlo (MHMCMC) data assimilation framework to optimize the MEGAN temperature response function. We find that the performance of MEGAN can be significantly improved at several high-latitude field sites by increasing the modeled sensitivity of isoprene emissions to past temperatures. At some sites, the optimized model was nearly four times more sensitive to temperature than the unoptimized model. This has implications for air quality modeling in a warming climate.</p>}},
author = {{DiMaria, C. A. and Jones, D. B.A. and Ferracci, V. and Bloom, A. A. and Worden, H. M. and Seco, R. and Vettikkat, L. and Yáñez-Serrano, A. M. and Guenther, A. B. and Araujo, A. and Goldstein, Allen H. and Langford, B. and Cash, J. and Harris, N. R.P. and Brown, L. and Rinnan, R. and Schobesberger, Siegfried and Holst, T. and Mak, J. E.}},
issn = {{2169-8953}},
keywords = {{ecosystem; isoprene; model; Monte Carlo; observations; optimization}},
language = {{eng}},
number = {{5}},
publisher = {{John Wiley & Sons Inc.}},
series = {{Journal of Geophysical Research: Biogeosciences}},
title = {{Optimizing the Temperature Sensitivity of the Isoprene Emission Model MEGAN in Different Ecosystems Using a Metropolis-Hastings Markov Chain Monte Carlo Method}},
url = {{http://dx.doi.org/10.1029/2025JG008806}},
doi = {{10.1029/2025JG008806}},
volume = {{130}},
year = {{2025}},
}