| Grant number: | 19/25812-4 |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| Start date: | March 01, 2020 |
| End date: | December 21, 2023 |
| Field of knowledge: | Agronomical Sciences - Agronomy - Agricultural Meteorology |
| Principal Investigator: | Newton La Scala Júnior |
| Grantee: | Luis Miguel da Costa |
| Host Institution: | Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil |
| Associated scholarship(s): | 21/06477-0 - Evaluation of different approaches for the retrieval of sun-induced fluorescence, BE.EP.IC |
Abstract Climate change is a challenge for the global community and one of the causes is the increase of greenhouse gases (GHG) in the atmosphere, especially carbon dioxide (CO2). The main source of emission of this gas into the atmosphere comes from the burning of fossil fuels and the burning of biomass, on the other hand, the main source of absorption comes from biochemical processes such as photosynthesis. Thus, CO2 observation is a key point to understand the sources and sinks, in this context, the Orbiting Carbon Observatory 2 (OCO-2) and 3 (OCO-3), are dedicated NASA missions to monitor the average atmospheric carbon dioxide (Xco2) concentration on a global scale. In this work we will combine the OCO-2 and OCO-3 observations to study the relationship of Xco2 anomalies with the occurrence of fires in the Brazilian biomes during 2020 and 2021, considering two different seasons, Dry and Wet. Fire occurrence will be obtained from the Fire Information System for Resource Management (FIRMS). Complementarily we will use soil carbon stock data in pastures, obtained from the pasture atlas maintained by LAPIG and from Sun Induced Chlorophyll Fluorescence (SIF). In view of this, we aim with this project, (I) to characterize the spatial and temporal variability of atmospheric CO2 anomalies (II) to relate CO2 emissions through climate anomaly models with fire focus areas. For the studied area, the data will be grouped into averages for the dry and wet periods, then the analysis of the variables obtained will be carried out through descriptive statistics (mean, standard deviation of the mean), and maps will be generated for spatial variability of anomalies and fire outbreaks, then regression will be performed between the data of anomalies of Xco2 and fire outbreaks. At the end of the study, it is intended to elucidate some questions about the effect of fire on CO2 emissions. (AU) | |
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