Desafios e reflexões da COP 28

Fernanda Macedo; Elaine Cristina Araújo; Izabel da Silva Andrade; Thaís Correa; Vagner dos Santos Macedo

Authors

Fernanda Macedo Fatec Praia Grande https://orcid.org/0000-0001-6778-3976
Elaine Cristina Araújo Instituto de Pesquisas Energéticas e Nucleares - IPEN https://orcid.org/0000-0001-6572-8041
Izabel da Silva Andrade Instituto de Pesquisas Energéticas e Nucleares - IPEN https://orcid.org/0000-0003-0732-3630
Thaís Correa Fatec Praia Grande https://orcid.org/0000-0003-0923-1860
Vagner dos Santos Macedo Fatec Praia Grande https://orcid.org/0000-0003-0773-6443

Keywords:

GEE, CH4, CO2, data driven, atmosphere

Abstract

COP 28, Conference of the Parties on Climate Change, stands out as a crucial event to discuss and address challenges related to greenhouse gases (GHG) in a world increasingly impacted by climate change. GHGs, such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), are the main drivers of global warming and represent the central concern at COP 28. The need to reduce emissions of these gases is indisputable, and data-driven strategies emerge as fundamental tools for understanding and addressing this complex challenge. Using data-driven analytics enables a more accurate understanding of the sources of GHG emissions, identifying critical areas for action and facilitating the implementation of effective mitigation measures. This study surveys data from COP 28, combining discussions on GHG and data driven approaches, which play a crucial role in formulating policies and making decisions aimed at tackling climate change in an effective and sustainable way.

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Author Biographies

Elaine Cristina Araújo, Instituto de Pesquisas Energéticas e Nucleares - IPEN

Technologist in Chemical Processes by the Faculty of Technology of Praia Grande, I did a voluntary internship at the Chemistry Laboratory of FATEC Praia Grande and Scientific Initiation in the area of Environmental Laser Applications by the Institute of Energy and Nuclear Research (IPEN/CNEN-SP) of the University of São Paulo. Master’s degree from the Institute of Energy and Nuclear Research (IPEN/CNEN-SP), 2019, from the University of São Paulo, in the area of Laser Applications in Environment.

Izabel da Silva Andrade, Instituto de Pesquisas Energéticas e Nucleares - IPEN

PhD student in Remote Sensing of the Atmosphere, by the Institute of Energy and Nuclear Research (IPEN/USP). He holds a degree in Technology in Chemical Processes from the Faculty of Technology of Praia Grande (2015) and a master’s degree in remote sensing of the atmosphere from the Institute of Energy and Nuclear Research (2019).

Thaís Correa, Fatec Praia Grande

Graduated in Chemical Process Technology at the Faculty of Technology of the State of São Paulo (FATEC - Praia Grande). Degree in Chemistry (Faculdade de Educação Paulistana). Master in nuclear technology application, in Remote Sensing of the Atmosphere, by the University of São Paulo (IPEN/USP). Currently PhD in Remote Atmosphere Sensing, with lasers, by the Institute of Energy and Nuclear Research (IPEN/ USP). Professor at the Paula Souza Center teaching classes in the disciplines General Chemistry, Organic Chemistry, Analytical Chemistry, Environmental Chemistry , Oil and Gas Technology and Environmental Sciences. Participating in research centers on climate change and detection of greenhouse gases. (LEAL-Environmental Applications Laboratory de Micrometeorologia e METROCLIMA/IAG-USP)

Vagner dos Santos Macedo, Fatec Praia Grande

Master in Nuclear Technology from IPEN / USP. Latu-Sensu specialization in Database Administration by FIAP and in Computer Systems by the Federal University of Uberlândia-MG. He holds a bachelor’s degree in Computer Science from Santa Cecilia University. He is currently a graduate professor at FIAP in the MBAs Big-Data and Business Intelligence. In graduation working in the disciplines of Operating Systems, Programming Languages and Database at FATEC (Faculty of Technology of Praia Grande). He has experience in the area of Computer Science, with an emphasis on data science, acting as a scientist / data engineer in the development of ingestion projects and data science and applications for machine learning.

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