International Economic Integration entails collaborative efforts among nations to overcome barriers and achieve shared benefits. The development of analytical models is crucial for comprehending the interaction of countries as a collective entity. In South America, MERCOSUR stands out, comprising Argentina, Brazil, Paraguay, and Uruguay. In this study, Economic Complexity metrics were applied to analyze productive capacities within MERCOSUR. The results underscore integration's significance by forming economic blocs, capabilities are expanded, enriching diversity and the scope of production. Economic complexity serves as a pivotal tool for assessing interdependence and enhancing countries' global positioning. In summary, this work highlights how economic integration, exemplified by MERCOSUR, enhances productive capacity, propelling development, and competitiveness in an interconnected world. Leveraging a novel computational mathematical model, this study offers insights into the complex dynamics of international economic integration, shedding light on strategies to foster growth and collaboration in a rapidly evolving global landscape.

In this presentation, we present a new smoke modeling system High Resolution Rapid Refresh (HRRR-Smoke) to simulate biomass burning (BB) emissions, plume rise and smoke transport in real time. The HRRR model (without smoke) is run as an operational numerical weather prediction system at the National Weather Service. HRRR is NOAA Earth System Research Laboratory's version of the Weather Research and Forecasting (WRF) model. Here we make use of WRF-Chem (the WRF model coupled with chemistry) and simulate fine particulate matter (smoke) emissions emitted by BB as well as anthropogenic sources. The model includes an aerosol aware double moment Thompson microphysics scheme [1], which allows to simulate smoke feedback on microphysics in a computationally efficient manner.

Burned areas map is essential in many applications and the orbital sensors have been used to monitor fires for many years, providing a better understanding of processes at different scales and being the only practical technique to estimate fires in large areas. However, remote sensing methods have limitations that could cause errors in the final products. Therefore, the objective of this work is to evaluate the MCD45A1 burned area product derived from MODIS sensor in Amazon tropical forest by comparing this dataset with the reference data derived from the mapping of burned areas in Acre State/Brazil acquired by TM sensor aboard of Landsat 5 and with a fieldwork that took place in November 2011. The results showed that de MCD45A1 product presented 93% of omission errors in 2010 and 96% in 2011 year in relation to reference data, presenting a low confidence in identifying the burned areas in Amazon region.

Wildfires plays a fundamental intervention in global biogeochemical cycle, by the chemical reaction occurring in the combustion process, and the organic compounds present in vegetation returns to the atmosphere and soil in a cyclical behavior. Therefore, the main objective of this work is to develop a method to estimate the instantaneous fire size in Brazil using Thematic Mapper (TM) aboard of Landsat 5 and Enhanced Thematic Mapper Plus (ETM+) aboard of Landsat 7. The results indicate that active fire to pastures/grasslands is approximately 38% higher than that found for forest areas, 31% higher than the same coefficient used to estimate the fire size in areas of herbaceous and shrub vegetation and 11% higher than the coefficient used in agricultural areas.

Remote sensing is based on the interaction of electromagnetic radiation with the portion of the electromagnetic radiation that interacts with Earth surface targets. Studies to analyze the spectrum of reflectance of surface targets by sensor systems could be done by terrestrial (laboratory and field), aerial and orbital acquisitions. Consequently, for vegetation studies through remote sensing observations is necessary to know the physiology of the plant studied and the reflectance spectrum, considering that the solar radiation reaches the earth's surface and results in three fractions: one part is absorbed, another is reflected and a third part is transmitted. The leaves are the principal absorber of electromagnetic radiation in a canopy and represents the element that more contribute to the signal detected by orbital sensors. The present work has as its main goal the analysis of the spectral signature responses of common species of several forest functional types in a tropical forest area in the Amazon.