Impact of aerosols on the solar energy potential in Brazil

• Grant number: 24/18374-9
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: November 01, 2024
• End date: February 28, 2025
• Field of knowledge: Interdisciplinary Subjects
• Agreement: CNPq - INCTs
• Principal Investigator: Fernando Ramos Martins
• Grantee: Eduardo Weide Luiz
• Host Institution: Instituto do Mar (IMar). Universidade Federal de São Paulo (UNIFESP). Campus Baixada Santista. Santos , SP, Brazil
• Associated research grant: 14/50848-9 - INCT 2014: INCT for Climate Change, AP.PFPMCG.TEM

Abstract

Solar energy, and in particular, technologies that use concentrated solar power, present a significant growth potential in Brazil in climate change mitigation scenarios. Accurate mapping of solar irradiation and, specifically, direct normal irradiance (DNI) is critical for planning, decision-making, and future operation of solar power installations. Reducing uncertainties in the estimation of global and direct solar irradiation is within the scope of the research conducted by the Energy Security subcomponent of the INCT Climate Change (Process 2019/05361-8). To this end, the research aims to improve the parameterizations implemented in the Brasil-SR model to quantify the contribution of aerosol emissions from fires in attenuating the incident solar resource on the surface. These improvements will help reduce deviations in DNI and integrated and spectral GHI estimates under clear sky conditions and/or high aerosol loads, assuming the availability of local aerosol optical depth (AOD) and Angstrom exponent (EA) data from AERONET or MFRSR. Aiming at this objective, AOD and Angstrom exponent data obtained by satellite and reanalysis will be compared to those obtained by AERONET in Brazil, focusing on the Amazon and Cerrado regions. The presence of spatial correlation patterns will also be investigated. It is expected that the most suitable input data for Brazil will be defined, as well as a proposed strategy for 'calibrating' the regional input data for better performance in radiation modeling results. These tasks are considered essential to achieve accurate mapping of surface solar irradiance across the entire national territory, requiring not only a well-performing model but also accurate input data.