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Temporal variability of methane concentrations in the northeast region of Amazonia, and association with land use

Grant number: 22/03535-1
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): June 01, 2022
Effective date (End): May 31, 2023
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Meteorology
Principal Investigator:Luciana Varanda Rizzo
Grantee:Laura de Almeida Viana
Host Institution: Instituto de Ciências Ambientais, Químicas e Farmacêuticas (ICAQF). Universidade Federal de São Paulo (UNIFESP). Campus Diadema. Diadema , SP, Brazil
Host Company:Universidade de São Paulo (USP). Escola Politécnica (EP)
Associated research grant:20/15230-5 - Research Centre for Greenhouse Gas Innovation - RCG2I, AP.PCPE


Methane (CH4) is one of the main Green House Gases (GHG), with a significant contribution to global warming. The Amazon region emits about 8% of global CH4, as a result of wetland, biomass burning, and agricultural emissions. The Amazon region is going through intense land-use changes, as a result of agricultural frontier advances, deforestation, urbanization and infrastructure construction of roads and hydroelectric plants. Moreover, changes in temperature and precipitation patterns affect the biogeochemical processes related to CH4 emission, in a complex way. Previous studies have shown that the northeast of Amazonia has CH4 emissions greater than other areas, and the reasons behind that are unclear. This undergrad research project aims to characterize the temporal variability of CH4 concentrations in the northeast of Amazonia between 2003 and 2021, investigating associations with land use change and environmental factors. For that, CH4 mixing ratio data from the AIRS sensor, aboard the Aqua satellite, will be used. The Mapbiomas collection of land use maps will be used to assess changes in the study area, related to the expansion of agricultural lands, the Transamazonica highway and the construction of the Belo Monte hydroelectric plant. Temperature and precipitation data from ERA5/ECMWF reanalysis and biomass burning fire spots from MODIS/Aqua will complete the dataset. The Google Earth Engine data analysis platform will be used to process the geospatial dataset, producing area-averaged time series in the study area. The R software for scientific programming will be used for statistical and multiple regression analysis. With that, we hope to improve the understanding of CH4 dynamics in the northeast of Amazonia, assessing the relative importance of natural and anthropogenic processes. This undergrad research project will be part of the Research Center for Gas Innovation (RCGI2) project entitled "Greenhouse Gas Emissions in Amazon and Data Analytics and Service System" (FAPESP 2020/15230-5). (AU)

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