Methane concentration variability in Pantanal region in the Mato Grosso State using data from AQUA satellite

  • Tonny Jader de Moraes Universidade Federal de Mato Grosso (UFMT). Instituto de Física (IF), Cuiabá, MT, Brasil. Programa de Pós-Graduação em Física Ambiental
  • Fernando da Silva Sallo Universidade Federal de Mato Grosso (UFMT). Instituto de Física (IF), Cuiabá, MT, Brasil. Programa de Pós-Graduação em Física Ambiental
  • Carlo Ralph de Musis Universidade Federal de Mato Grosso (UFMT). Instituto de Física (IF), Cuiabá, MT, Brasil. Programa de Pós-Graduação em Física Ambiental
  • Luciana Sanches Universidade Federal de Mato Grosso (UFMT). Instituto de Física (IF), Cuiabá, MT, Brasil. Programa de Pós-Graduação em Física Ambiental
  • Iramaia Jorge Cabral de Paulo Universidade Federal de Mato Grosso (UFMT). Instituto de Física (IF), Cuiabá, MT, Brasil. Programa de Pós-Graduação em Física Ambiental
  • Rafael da Silva Palácios Universidade Federal de Mato Grosso (UFMT). Instituto de Física (IF), Cuiabá, MT, Brasil. Programa de Pós-Graduação em Física Ambiental
Keywords: cross-correlation, rainfall, wavelet.

Abstract

Methane emission is an important factor in the management of wet areas such as the Pantanal region. The temporal variability of CH4 concentrations on the Pantanal was therefore studied using remote sensing data from 2003 to 2013 from an AIRS sensor on board of AQUA satellite. Wetlands worldwide contribute to the overall CH4 cycle, emitting around one‑third of the overall CH4. However, the dynamics of CH4 remain poorly understood in the Pantanal. This work studied the variability of CH4 in the atmosphere over the Pantanal of Mato Grosso, based on the time series of CH4 concentration (2002-2013). The methodology used was based on descriptive statistics that included weekly averages, variance anomalies, cross‑correlation between precipitation and concentration of CH4, and the transformed wavelet technique. The results showed a seasonal average concentration and the variability of CH4 abnormality in a negative cross-correlation with precipitation.  Sub-annual variations of CH4 were inversely related to precipitation, and seemed to be influenced by the concentration of hydroxyl [OH-] during the rainy season, which reduces the balance of CH4 emissions. The wavelet analysis found an annual and inter-annual cycle of CH4 concentration between 2009‑2013.


Published
02/05/2017
Section
Papers