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Underestimated Dry Season Methane Emissions from Wetlands in the Pantanal.
Li, Mengze; Kort, Eric A; Bloom, A Anthony; Wu, Dien; Plant, Genevieve; Gerlein-Safdi, Cynthia; Pu, Tianjiao.
Afiliación
  • Li M; Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States.
  • Kort EA; Department of Earth System Science, Stanford University, Stanford, California 94305, United States.
  • Bloom AA; Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States.
  • Wu D; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States.
  • Plant G; Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California 91125, United States.
  • Gerlein-Safdi C; Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States.
  • Pu T; Department of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United States.
Environ Sci Technol ; 2024 Feb 07.
Article en En | MEDLINE | ID: mdl-38325813
ABSTRACT
Tropical wetlands contribute ∼30% of the global methane (CH4) budget. Limited observational constraints on tropical wetland CH4 emissions lead to large uncertainties and disparities in representing emissions. In this work, we combine remote sensing observations with atmospheric and wetland models to investigate dry season wetland CH4 emissions from the Pantanal region of South America. We incorporate inundation maps generated from the Cyclone Global Navigation Satellite System (CYGNSS) satellite constellation together with traditional inundation maps to generate an ensemble of wetland CH4 emission realizations. We challenge these realizations with daily satellite observations for May-July when wetland CH4 emission predictions diverge. We find that the CYGNSS inundation products predict larger emissions in May, in better agreement with observations. We use the model ensemble to generate an empirical observational constraint on CH4 emissions independent of choice of inundation map, finding large dry season wetland CH4 emissions (31.7 ± 13.6 and 32.0 ± 20.2 mg CH4/m2/day in May and June/July during 2018/2019, respectively). These May/June/July emissions are 2-3 times higher than current models, suggesting that annual wetland emissions may be higher than traditionally simulated. Observed trends in the early dry season indicate that dynamics during this period are of importance in representing tropical wetland CH4 behaviors.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos