Spatiotemporal variability of atmospheric CO2 in the Brazilian southeast: a perspective with remote sensing

Abstract

The southeast of Brazil has an area of approximately 925 thousand km2 with a population density of approximately 87 inhabitants per km2, the high population density causes anthropogenic CO2 emissions to increase, in addition, this state also has a high agricultural base, which in turn has a strong influence on the dynamics of atmospheric CO2, due to the capture of large amounts of CO2 by incorporating carbon in its phytomass and management and land use, these processes can act as a source or sink of this gas. The remote sensing techniques have been widely used to identify and characterize, for example, the impact of land use change on greenhouse gas (GHG) emissions, allowing us to understand their processes and distributions accurately, in addition to enabling the study of their anomalies. Given this, we aim with this project, (I) to characterize the spatial and temporal variability of atmospheric CO2 associating climate and vegetation variables in the southeastern region; (II) to relate CO2 emissions through climate anomaly models between agricultural and urban areas for the entire state of São Paulo using remote sensing techniques. A time series from 2015 to 2019 will be analyzed for Xco2 and SIF data from the Orbiting Carbon Observatory-2 (OCO-2), climate indices obtained by NASA-POWER such as: relative humidity (RH), incident insolation (Qg) and average temperature at 2 meters (T2m), and vegetation indices such as: leaf area index (LAI (MCD15A2H.006 V6)) and Penman-Monteith evapotranspiration (ET (MOD16A2.006 V6)) by MODIS sensor. For the area studied, the data will be grouped into monthly averages, then the analysis of the variables obtained will be performed through descriptive statics (mean, standard deviation of the mean, standard error of the mean), in addition will be generated experimental variogram model of spatialization as a function of the distances between two locations, the anomalies will be calculated from the difference between the observed value and the annual median. At the end of the study, it is intended to elucidate some questions about the effect of photosynthesis on atmospheric CO2 concentrations and the interactions of vegetation cover on the dynamics of CO2, and how the climate can affect these dynamics. (AU)