Impact of aerosols on the Brazilian solar energy resource potential

• Grant number: 19/05361-8
• Support type: Scholarships in Brazil - Post-Doctorate
• Effective date (Start): August 01, 2019
• Effective date (End): July 31, 2021
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Fernando Ramos Martins
• Grantee: Madeleine Sánchez Gácita Casagrande
• Home Institution: Instituto de Saúde e Sociedade (ISS). 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, concentrating solar technologies have shown a noteworthy growth potential in Brazil in scenarios of climate change mitigation. The accurate assessment of the surface solar irradiation and, in particular, of the direct normal irradiation (DNI) is critical to support the planning, decision making and future operation of solar energy facilities. On the other hand, atmospheric aerosols are the most important factor for solar radiation extinction under clear sky conditions, posing more influence to the DNI than to the global horizontal irradiation (GHI). In Brazil, biomass burning activities emit large quantities of aerosols that frequently suffer long-range transport. This proposal aims at contributing to the expansion of the solar energy market in Brazil by providing a more accurate knowledge of the impact of aerosols on DNI and GHI. To that end, an aerosol parameterization based on aerosol optical depth (AOD) data will be included in the radiative transfer model BRASIL-SR, while maintaining the spectral and vertical structure of the model. The AOD data could be provided either by mesoscale reanalysis or by GOES-R specific products. The spectral representation of the aerosol optical properties in the model grid will be derived from AERONET data and interpolation techniques. The model will also be tuned to use GOES-R visible data to evaluate the effective cloud cover index. Satellite parallax and clouds location errors will be corrected following geometrical considerations. The new version of model BRASIL-SR will be useful to generate historical series, current estimates or even surface irradiation forecasts. It is expected to reduce uncertainties in DNI and GHI estimates for all atmospheric conditions, and to a greater extent for conditions with a cloudless sky and/or high aerosol load.