Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions
Wetlands are the single largest natural source of atmospheric methane (CH _4 ), contributing approximately 30% of total surface CH _4 emissions, and they have been identified as the largest source of uncertainty in the global CH _4 budget based on the most recent Global Carbon Project CH _4 report....
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/adad02 |
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| Summary: | Wetlands are the single largest natural source of atmospheric methane (CH _4 ), contributing approximately 30% of total surface CH _4 emissions, and they have been identified as the largest source of uncertainty in the global CH _4 budget based on the most recent Global Carbon Project CH _4 report. High uncertainties in the bottom–up estimates of wetland CH _4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH _4 emissions from space. In fact, there are large disagreements between bottom–up estimates versus top–down estimates inferred from inversion of atmospheric CH _4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom–up estimates of global wetland CH _4 emissions, as well as how they are used in top–down inversions. These bottom–up estimates, using (1) empirical biogeochemical modeling (e.g. WetCHARTs: 125–208 TgCH _4 yr ^−1 ); (2) process-based biogeochemical modeling (e.g. WETCHIMP: 190 ± 39 TgCH _4 yr ^−1 ); and (3) data-driven machine learning approach (e.g. UpCH4: 146 ± 43 TgCH _4 yr ^−1 ). Bottom–up estimates are subject to significant uncertainties (∼80 Tg CH _4 yr ^−1 ), and the ranges of different estimates do not overlap, further amplifying the overall uncertainty when combining multiple data products. These substantial uncertainties highlight gaps in our understanding of wetland CH _4 biogeochemistry and wetland inundation dynamics. Major tropical and arctic wetland complexes are regional hotspots of CH _4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top–down inversions to improve bottom–up estimates. Recent advances in surface measurements of CH _4 fluxes (e.g. FLUXNET-CH _4 ) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom–up estimates of wetland CH _4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH _4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH _4 observations directed at wetlands. |
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| ISSN: | 1748-9326 |