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The influence of biomass burning (BB)-derived organic aerosol (OA) emissions on solar radiationviaabsorption and scattering is related to their physicochemical properties and can change upon atmospheric aging. 

Abstract Air pollution in Africa is a significant public health issue responsible for 1.1 million premature deaths annually. Sub-Saharan Africa has the highest rate of population growth and urbanization of any region in the world, with substantial potential for future emission growth and worsening air quality. Accurate and extensive observations of meteorology and atmospheric composition have underpinned successful air pollution mitigation strategies in the Global North, yet Africa in general and East Africa in particular remain among the most sparsely observed regions in the world. This paper is based on the discussion of these issues during two international workshops, one held virtually in the United States in July 2021 and one in Kigali, Rwanda, in January 2023. The workshops were designed to develop a measurement, capacity building, and collaboration strategy to improve air quality-relevant measurements, modeling, and data availability in East Africa. This paper frames the relevant scientific needs and describes the requirements for training and infrastructure development for an integrated observing and modeling strategy that includes partnerships between East African scientists and organizations and their counterparts in the developed world. 

Abstract. Secondary inorganic aerosols (sulfate, nitrate, and ammonium, SNA) are major contributors to fine particulate matter. Predicting concentrations of these species is complicated by the cascade of processes that control their abundance, including emissions, chemistry, thermodynamic partitioning, and removal. In this study, we use 11 flight campaigns to evaluate the GEOS-Chem model performance for SNA. Across all the campaigns, the model performance is best for sulfate (R2 = 0.51; normalized mean bias (NMB) = 0.11) and worst for nitrate (R2=0.22; NMB = 1.76), indicating substantive model deficiencies in the nitrate simulation. Thermodynamic partitioning reproduces the total particulate nitrate well (R2=0.79; NMB = 0.09), but actual partitioning (i.e., ε(NO3-)= NO3- / TNO3) is challenging to assess given the limited sets of full gas- and particle-phase observations needed for ISORROPIA II. In particular, ammonia observations are not often included in aircraft campaigns, and more routine measurements would help constrain sources of SNA model bias. Model performance is sensitive to changes in emissions and dry and wet deposition, with modest improvements associated with the inclusion of different chemical loss and production pathways (i.e., acid uptake on dust, N2O5 uptake, and NO3- photolysis). However, these sensitivity tests show only modest reduction in the nitrate bias, with no improvement to the model skill (i.e., R2), implying that more work is needed to improve the description of loss and production of nitrate and SNA as a whole. 

The fractal dimension is a key parameter in quantifying the morphology of aerosol aggregates, which is necessary to understand their radiative impact. Here we used Transmission Electron Microscopy (TEM) images to determine 2D fractal dimensions using the nested square and box-grid method and used two different empirical equations to obtain the 3D fractal dimensions. The values ranged from 1.70 ± 0.05 for pine to 1.82 ± 0.07 for Eucalyptus, with both methods giving nearly identical results using one of the empirical equations and the other overestimated the 3D values significantly when compared to other values in the literature. The values we obtained are comparable to the fractal dimensions of fresh aerosols in the literature and were dependent on fuel type and combustion condition. Although these methods accurately calculated the fractal dimension, they have shortcomings if the images are not of the highest quality. While there are many ways of determining the fractal dimension of linear features, we conclude that the application of every method requires careful consideration of a range of methodological concerns.