Characterization of the Optical Properties of Biomass-Burning Aerosols in Two High Andean Cities, Huancayo and La Paz, and Their Effect on Radiative Forcing

Atmospheric aerosols are known to alter the Earth’s radiative balance and influence climate. However, accurately quantifying the magnitude of aerosol-induced radiative forcing remains challenging. We characterize optical properties of biomass-burning (BB) and non-biomass-burning (NB) aerosols and quantify BB aerosol radiative forcing at two AERONET (AErosol RObotic NETwork) sites in Huancayo (Peru) and La Paz (Bolivia) during 2015–2021. From AERONET data, we derive aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), and asymmetry parameter (ASY). We then employ the SBDART model to calculate aerosol radiative forcing (ARF) on monthly and multiannual timescales. BB aerosols peak in September (AOD: 0.230 at Huancayo; 0.235 at La Paz), while NB aerosols reach maxima in September at Huancayo (0.109) and November at La Paz (0.104). AE values exceeding unity for BB aerosols indicate fine-mode dominance. Huancayo exhibited the highest BB ARF in November: +16.4 W m−2 at the top of the atmosphere (TOA), –18.6 W m−2 at the surface (BOA), and +35.1 W m−2 within the atmospheric column (ATM). This was driven by elevated AOD and high scattering efficiency. At La Paz, where SSA data was only available for September, BBARF values were also significant (+15.16 at TOA, –17.52 at BOA, and +32.73 W m−2 within the ATM). This result underscores the importance of quantifying the ARF, particularly over South America where data is scarce.

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Journal
Atmosphere
Published
2025-10-28
DOI
https://doi.org/10.3390/atmos16111240
Primary Topic
Atmospheric aerosols and clouds
Type
article
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article

Characterization of the Optical Properties of Biomass-Burning Aerosols in Two High Andean Cities, Huancayo and La Paz, and Their Effect on Radiative Forcing

René Estevan, Cesar Victoria-Barros
Atmosphere
Atmospheric aerosols and clouds
article

Characterization of the Optical Properties of Biomass-Burning Aerosols in Two High Andean Cities, Huancayo and La Paz, and Their Effect on Radiative Forcing

René Estevan, Cesar Victoria-Barros
article en

Abstract

Atmospheric aerosols are known to alter the Earth’s radiative balance and influence climate. However, accurately quantifying the magnitude of aerosol-induced radiative forcing remains challenging. We characterize optical properties of biomass-burning (BB) and non-biomass-burning (NB) aerosols and quantify BB aerosol radiative forcing at two AERONET (AErosol RObotic NETwork) sites in Huancayo (Peru) and La Paz (Bolivia) during 2015–2021. From AERONET data, we derive aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), and asymmetry parameter (ASY). We then employ the SBDART model to calculate aerosol radiative forcing (ARF) on monthly and multiannual timescales. BB aerosols peak in September (AOD: 0.230 at Huancayo; 0.235 at La Paz), while NB aerosols reach maxima in September at Huancayo (0.109) and November at La Paz (0.104). AE values exceeding unity for BB aerosols indicate fine-mode dominance. Huancayo exhibited the highest BB ARF in November: +16.4 W m−2 at the top of the atmosphere (TOA), –18.6 W m−2 at the surface (BOA), and +35.1 W m−2 within the atmospheric column (ATM). This was driven by elevated AOD and high scattering efficiency. At La Paz, where SSA data was only available for September, BBARF values were also significant (+15.16 at TOA, –17.52 at BOA, and +32.73 W m−2 within the ATM). This result underscores the importance of quantifying the ARF, particularly over South America where data is scarce.

AtmosphereVol. 16(11)
National University of San Marcos (PE), Instituto Geofísico del Perú (PE)
Openalex Percentile: Top 71%
Atmospheric aerosols and clouds
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Characterization of the Optical Properties of Biomass-Burning Aerosols in Two High Andean Cities, Huancayo and La Paz, and Their Effect on Radiative Forcing — René Estevan, Cesar Victoria-Barros · Atmosphere (2025) | TGRS Research Map | TGRS