Marc N. Fiddler’s research while affiliated with North Carolina Agricultural and Technical State University and other places

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 influence of biomass burning (BB)-derived organic aerosol (OA) emissions on solar radiation via absorption and scattering is related to their physicochemical properties and can change upon atmospheric aging. We systematically examined the compositionally-resolved mass concentration and production of primary and secondary organic aerosol (POA and SOA, respectively) in the NC A&T University smog chamber facility. Mass spectral profiles of OA measured by the Aerosol Chemical Speciation Monitor (ACSM) revealed the influence of dark- and photo-aging, fuel type, and relative humidity. Unit mass resolution (UMR) mapping, the ratio of the fraction of the OA mass spectrum signal at m/z 55 and 57 (f55/f57) vs. the same fraction at m/z 60 (f60) was used to identify source-specific emission profiles. Furthermore, Positive Matrix Factorization (PMF) analysis was conducted using OA mass spectra, identifying four distinct factors: low-volatility oxygenated OA (LV-OOA), primary biomass-burning OA (BBOA), BB secondary OA (BBSOA), and semi-volatile oxygenated OA (SV-OOA). Data supports a robust four-factor solution, providing insights into the chemical transformations under different experimental conditions, including dark- and photo-aged, humidified, and dark oxidation with NO3 radicals. This work presents the first such laboratory study of African-derived BBOA particles, addressing a gap in global atmospheric chemistry research.

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, 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 and NMB = 0.09), but actual partitioning (i.e., εNO3= NO3-/TNO3) is challenging to assess given limited ammonia observations. 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.

Sub-Saharan Africa is a hotspot for biomass burning (BB)-derived carbonaceous aerosols, including light-absorbing organic (brown) carbon (BrC). However, the chemically complex nature of BrC in BB aerosols from this region is not fully understood. We generated smoke in a chamber through smoldering combustion of common sub-Saharan African biomass fuels (hardwoods, cow dung, savanna grass, and leaves). We quantified aethalometer-based, real-time light-absorption properties of BrC-containing organic-rich BB aerosols, accounting for variations in wavelength, fuel type, relative humidity, and photochemical aging conditions. In filter samples collected from the chamber and Botswana in the winter, we identified 182 BrC species, classified into lignin pyrolysis products, nitroaromatics, coumarins, stilbenes, and flavonoids. Using an extensive set of standards, we determined species-specific mass and emission factors. Our analysis revealed a linear relationship between the combined BrC species contribution to chamber-measured BB aerosol mass (0.4–14%) and the mass-absorption cross-section at 370 nm (0.2–2.2 m2 g–1). Hierarchical clustering resolved key molecular-level components from the BrC matrix, with photochemically aged emissions from leaf and cow-dung burning showing BrC fingerprints similar to those found in Botswana aerosols. These quantitative findings could potentially help refine climate model predictions, aid in source apportionment, and inform effective air quality management policies for human health and the global climate.

Emission factors (EFs) are crucial in understanding the effects of wildfire emissions on air quality. We examined the variability of EFs of three wildfires (Nethker, Castle, and 204 Cow) during the 2019 Western US wildfire season using the Aerodyne Mobile Laboratory (AML) and compared them to previous studies. The AML sampling captured the high degree of variability present in wildfires, and we report results for a range of combustion conditions that is more extensive than previous field and laboratory studies. For instance, we captured emissions from freshly started flaming fuels and we report rare EF measurements at very high modified combustion efficiencies (MCEs); MCEs >0.9. Differences in emissions between AML‐observed wildfires were attributed to burning state/MCE rather than fuel type. A comparison of EFs versus MCE was made and linear fits were compared to previous observations to reveal important differences that incorporate these high MCEs. For some species, there remains an EF dependence on MCE at these high values, while others reach a minimum value and exhibit either no or a weak dependence above it. EF differences were found for many of the studied compounds when comparing ground‐based and airborne observations, with generally greater airborne EFs possibly due to photochemical oxidation. The largest differences were from monoterpenes and acetaldehyde. Comparisons were made between AML‐observed wildfires, aircraft observations, and the values in literature for EFs and emission ratios, with mixed agreement due to the high degree of variability caused by differences in MCE. Differences in MCE drove the diurnal EF differences.

Aerosols hygroscopic growth is of current interest due to its effect on atmospheric light scattering and extinction. Knowledge of hygroscopic properties is essential for predicting the effect of aerosol on cloud formation, regional visibility, climate impact, and lung deposition. Previous studies have used surrogate components of complex aerosol; and the application to complex multi-component aerosol like biomass burning aerosol is limited. We report aerosol hygroscopicity parameter of biomass burning aerosol derived from Eucalyptus and cow dung in a humidified smog chamber using two techniques: (1) measuring extinction hygroscopic enhancement factor f(RH) of aerosol using a cavity ring down spectrometer and deriving the hygroscopicity parameter using empirical equations and (2) directly using a Cloud Condensation Nuclei Counter (CCNC). Based on repeated measurements of the same fuel under different burning conditions, quantified by the modified combustion efficiency (MCE), we found that aerosol hygroscopicity depends on both fuel types and to some extent on burning conditions. For similar MCE, cow dung has a consistently larger value of hygroscopicity compared to Eucalyptus. Hygroscopicity measurements ranged from 0.024 to 0.577 for MCE measurements that ranged from 0.73 to 0.99. Specifically, sub-saturated hygroscopicity parameter values for cow dung are 0.024–0.131 and Eucalyptus are 0.012–0.300, while supersaturated hygroscopicity parameter values for cow dung are 0.071–0.577 and Eucalyptus are 0.021–0.494. There is a clear increase in hygroscopicity with increasing MCE for supersaturated cow dung measurements using CCNC but the dependence of kappa on MCE is generally inconclusive.

Long-term exposure to ambient fine particulate matter (PM2.5) is the second leading risk factor of premature death in Sub-Saharan Africa. We use GEOS-Chem to quantify the effects of (a) trash burning, (b) residential solid-fuel burning, and (c) open biomass burning (BB) (i.e., landscape fires) on ambient PM2.5 and PM2.5-attributable mortality in Africa. Using a series of sensitivity simulations, we excluded each of the three combustion sources in each of five African regions. We estimate that in 2017 emissions from these three combustion sources within Africa increased global ambient PM2.5 by 2%, leading to 203,000 (95% confidence interval: 133,000-259,000) premature mortalities yr-1 globally and 167,000 premature mortalities yr-1 in Africa. BB contributes more ambient PM2.5-related premature mortalities per year (63%) than residential solid-fuel burning (29%) and trash burning (8%). Open BB in Central Africa leads to the largest number of PM2.5-attributed mortalities inside the region, while trash burning in North Africa and residential solid-fuel burning in West Africa contribute the most regional mortalities for each source. Overall, Africa has a unique ambient air pollution profile because natural sources, such as windblown dust and BB, contribute strongly to ambient PM2.5 levels and PM2.5-related mortality. Air pollution policies may need to focus on taking preventative measures to avoid exposure to ambient PM2.5 from these less-controllable sources.

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.