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Spatiotemporal variability of atmospheric CO2 in the state of São Paulo, Brazil: a perspective with remote sensing

Grant number: 19/25812-4
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): March 01, 2020
Effective date (End): February 28, 2022
Field of knowledge:Agronomical Sciences - Agronomy - Agricultural Meteorology
Principal researcher:Newton La Scala Júnior
Grantee:Luis Miguel da Costa
Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil

Abstract

The state of São Paulo has an extension of 249 thousand km2 with a population density of approximately 170 inhabitants per km2, the high population density causes the anthropic CO2 emissions to increase, moreover, this state also has a high agricultural basis, which in turn has a strong influence on the dynamics of atmospheric CO2, due to the capture of large quantities of CO2 incorporating carbon in its phytomass and the management and use of land, such processes may act as a source or sink of this gas. The techniques of remote sensing, have been widely used to identify and characterize, for example, the impact of land-use change in the emission of greenhouse gases (GHG), allowing us to understand their processes and distributions accurately, and enable the study of their anomalies. Given this, we aim with this project, (I) to characterize the spatial and temporal variability of atmospheric CO2 by associating climatic and vegetative variables in the state of São Paulo; (II) to relate CO2 emissions through models of climatic anomalies between agricultural and urban areas for the whole state of São Paulo using remote sensing techniques. It will be analyzed a time series from 2015 to 2018 for the data of XCO2 and SIF of the Observatory of Carbon in Orbit-2 (OCO-2), climate indexes obtained by NASA-POWER as relative humidity (RH), incident insolation (Qg), and the average temperature at 2 meters (T2m) and so on, and vegetative indexes as leaf area index (LAI (MCD15A2H.006 V6)) and evapotranspiration by Penman-Monteith (ET (MOD16A2.006 V6)), etc. by the MODIS sensor. For the studied area, the data will be divided into the rainy season (WET) and dry season (DRY), later the analysis of the obtained variables will be carried out through descriptive static (mean, standard deviation of the mean, standard error of the mean, etc.), both for the temporal variability and the spatial variability of the atmospheric CO2, besides the model of the experimental variogram of the spatialization will be in function of the distances between two locations, the anomalies will be calculated from the difference between the value of the observation and the annual median. At the end of the study, it is intended to clarify some questions regarding the effect of photosynthesis on atmospheric CO2 concentrations and the interactions of vegetation cover on CO2 dynamics, and how climate can affect these dynamics. (AU)