Preprints
https://doi.org/10.5194/egusphere-2026-5116
https://doi.org/10.5194/egusphere-2026-5116
14 Oct 2026
 | 14 Oct 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

High-resolution land-cover dynamics reveal strong regional contrasts in China’s biogenic isoprene emissions, 2000–2025

Haofan Ran, Yuting Lu, Yanli Zhang, and Xinming Wang

Abstract. Isoprene is a reactive biogenic volatile organic compound whose atmospheric impacts depend strongly on spatio-temporal emission patterns. Because Chinese inventories often rely on coarse or static land-cover information, we quantified how annual land-cover dynamics altered isoprene emissions across China during 2000–2025. Using a Google Earth Engine implementation of the Model of Emissions of Gases and Aerosols from Nature (MEGAN), driven by Landsat and Sentinel-2 land cover, satellite leaf area index, and 0.1° ERA5-Land meteorology, emissions were calculated on native 10–30 m grids. These were aggregated to an hourly 100 m output and compared with a 0.25° coarse simulation. National emissions averaged 9.87 ± 1.53 Tg yr-1, increasing from 8.49 in 2000 to 12.35 Tg yr-1 in 2025. Following a non-significant trend (2000–2012), emissions increased by 0.23 Tg yr-1 during 2013–2025 (p < 0.05), driven by temperature (40.4 %) and land-cover change (39.6 %). Crucially, fine land-cover data yielded a national mean only 6.2 % lower than the coarse simulation, yet exposed massive regional contrasts: +101.2 % in Beijing–Tianjin–Hebei and −20.2 % in the Pearl River Delta. Regional seasonality also varied, with summer contributing 49.4 % of emissions in Southwest China versus 78.8 % in the Northeast. Therefore, national-level agreement between inventories can mask substantial regional redistributions, with major implications for biogenic volatile organic compound inputs to atmospheric chemistry models. Estimates remain sensitive to satellite product transitions, default MEGAN emission factors, land-cover-to-plant-functional-type conversion, and meteorological forcing.

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Haofan Ran, Yuting Lu, Yanli Zhang, and Xinming Wang

Status: open (until 25 Nov 2026)

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Haofan Ran, Yuting Lu, Yanli Zhang, and Xinming Wang
Haofan Ran, Yuting Lu, Yanli Zhang, and Xinming Wang
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Short summary
Plants release natural gases that affect air quality, but current pollution models use imprecise map data. Using high-resolution satellite imagery from 2000 to 2025, we tracked these emissions in China. We found that warming and landscape changes caused massive, previously hidden regional shifts, including doubled emissions near Beijing. This proves that detailed satellite data is essential to accurately forecast urban air pollution and guide effective tree-planting policies.
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