4.6 Article

Spatiotemporal variability of atmospheric CO2 concentration and controlling factors over sugarcane cultivation areas in southern Brazil

期刊

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
卷 24, 期 4, 页码 5694-5717

出版社

SPRINGER
DOI: 10.1007/s10668-021-01677-6

关键词

Remote sensing; OCO-2; Carbon cycle; Climate-carbon feedbacks; Climate change

资金

  1. Fundacao de Amparo do Estado de Sao Paulo (FAPESP) [2019/25812-4]
  2. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES, Brazil) [001]
  3. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [304075/2018-3]

向作者/读者索取更多资源

This study characterized the spatial-temporal variability and main factors controlling atmospheric CO2 column in the macroregion of Ribeirao Preto, Sao Paulo, Brazil using remote sensing data. Negative correlations were found between Xco(2) and factors such as photosynthesis, relative humidity, and global radiation. Hotspots and coldspots of Xco(2) varied over the years.
With the advancement of remote sensing, it is now possible to identify and characterize greenhouse gas emissions under deferment land uses. Given the above, this study aimed to characterize the spatial-temporal variability and the main factors controlling the average atmospheric CO2 column (Xco(2)) in the macroregion of Ribeirao Preto (MRP), Sao Paulo, a significant sugarcane producer in Brazil. We obtained remote sensing data from January 2015 to December 2018. The variables used were Xco(2) and sun-induced fluorescence of chlorophyll (SIF) by NASA's Orbiting Carbon Observatory-2 satellite (OCO-2), relative humidity (RH), global radiation (Qg), and the average temperature at 2 m (T2m) by the NASA-POWER platform, and leaf area index (LAI) and evapotranspiration by Penman-Monteith (ET) by MODIS sensor. We evaluated the data in trimester's averages, where descriptive statistics, Pearson correlation and linear regression have been applied. The spatial distribution was made by the inverse distance weighted (IDW). The minimum (390.40 +/- 0.41 ppm) and maximum (394.75 +/- 0.34 ppm) mean of Xco(2) was observed in the first quarter of 2015 and third quarter of 2017. The Xco2 obtained negative correlations with the SIF (-0.81), LAI (-0.81), RH (-0.74), ET (-0.84), and Qg (-0.51). Hotspots and coldspots of Xco(2) tend to vary over the years. We conclude that the temporal variation of Xco(2) above sugarcane areas in southern Brazil is well represented by a periodic function. Our results indicate photosynthesis and soil exposure after harvest are factors that could act as source and sink of CO2.

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