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Effect of sub-particle structure on the optical properties of BC-dust-microplastic aerosols
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Tiny particles floating in our air—like black carbon from pollution, dust, and microplastics—scatter light differently depending on how they're arranged and sized, which affects how much they heat or cool our planet. Scientists found that ignoring these small structural details can lead to huge errors (up to 60%) in measuring particles with satellites, making it harder to accurately predict climate change. Understanding these particles matters because they influence both global warming and air quality, both of which directly affect human health.
Abstract Atmospheric aerosol radiative forcing remains highly uncertain in climate assessments, in part due to the inadequate representation of the optical effects arising from complex particle mixing states and internal structures. In this work, the Generalized multiparticle Mie method is used to quantify the optical properties of aerosol clusters composed of black carbon (BC), sand&dust(SD), and microplastics (MPs) in both triangular and fractal configurations. The calculations show that sub-particle composition, spatial arrangement, and size polydispersity all significantly influence cluster optical properties across the 300–1100 nm spectral range. For equal-sized (20 μm) sub-particles, MP-dominated clusters yield the largest scattering cross sections, whereas BC-containing clusters give the smallest. Notably, while the extinction cross section varies by less than 0.6% with sub-particle arrangement, the backscattering cross section changes by as much as 60%—a striking contrast that warns against neglecting internal morphology in lidar-based retrievals. Size polydispersity introduces even larger uncertainty: for a fixed triangular cluster, varying sub-particle radius leads to extinction fluctuations of 10%–20% and scattering changes up to 25%. When the clusters are extended to more realistic 20-particle fractal aggregates, compositional variation (different BC:MPs:SD ratios) alters the extinction cross section by up to a factor of 2.8, the scattering cross section by approximately 60%, and the asymmetry factor by 55%. Ensemble averaging shows that at least 18 random realizations are required for statistically stable optical properties; under polydisperse conditions, the scattering cross section converges more clearly than the extinction cross section. Collectively, these quantitative findings demonstrate that fine-scale sub-particle structure—especially size polydispersity and compositional heterogeneity—cannot be ignored in optical models of complex aerosols. This work provides directly applicable constraints for reducing uncertainties in radiative forcing and for advancing scattering-based aerosol retrieval frameworks.
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Deciphering the Sub-Particle Structural Control on Optical Properties of Complex Aerosols Containing Microplastics via the GMM Method
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Researchers applied the generalized Mie method to model the optical properties of atmospheric aerosol clusters containing black carbon, dust, and microplastics in triangular and fractal configurations, finding that sub-particle arrangement and size distribution are critical drivers of optical variability. Fractal clusters of 20 sub-particles showed up to 2.8-fold variation in extinction cross-section across the 300-1100 nm range, with implications for climate model accuracy.
Deciphering the Sub-Particle Structural Control on Optical Properties of Complex Aerosols Containing Microplastics via the GMM Method
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Researchers applied the generalized Mie method to quantify the optical properties of atmospheric aerosol clusters containing black carbon, dust, and microplastics, demonstrating that sub-particle structural arrangement and compositional heterogeneity govern optical variability across fractal and triangular configurations. The findings suggest that oversimplified aerosol representations in climate models underestimate the radiative forcing contributions of microplastic-containing aerosols.
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