Improved modelling of biogenic emissions in human-disturbed forest edges and urban areas

Yanli Zhang, Haofan Ran, Alex Guenther (), Qiang Zhang (), Christian George, Wahid Mellouki, Guoying Sheng, Ping’an Peng and Xinming Wang ()
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Yanli Zhang: Chinese Academy of Sciences
Haofan Ran: Chinese Academy of Sciences
Alex Guenther: University of California
Qiang Zhang: Tsinghua University
Christian George: Univ Lyon, Université Claude Bernard Lyon 1, CNRS, IRCELYON
Wahid Mellouki: Aérothermique, Réactivité Environnement (ICARE), CNRS
Guoying Sheng: Chinese Academy of Sciences
Ping’an Peng: Chinese Academy of Sciences
Xinming Wang: Chinese Academy of Sciences

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract Biogenic volatile organic compounds (BVOCs) are critical to biosphere-atmosphere interactions, profoundly influencing atmospheric chemistry, air quality and climate, yet accurately estimating their emissions across diverse ecosystems remains challenging. Here we introduce GEE-MEGAN, a cloud-native extension of the widely used MEGAN2.1 model, integrating dynamic satellite-derived land cover and vegetation within Google Earth Engine to produce near-real-time BVOC emissions at 10-30 m resolution, enabling fine-scale tracking of emissions in rapidly changing environments. GEE-MEGAN reduces BVOC emission estimates by 31% and decreases root mean square errors by up to 48.6% relative to MEGAN2.1 in human-disturbed forest edges, and reveals summertime BVOC emissions up to 25‑fold higher than previous estimates in urban areas such as London, Los Angeles, Paris, and Beijing. By capturing fine-scale landscape heterogeneity and human-driven dynamics, GEE-MEGAN significantly improves BVOC emission estimates, providing crucial insights to the complex interactions among BVOCs, climate, and air quality across both natural and human-modified environments.

Date: 2025
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DOI: 10.1038/s41467-025-63437-8

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