Aerosol Dynamics Research Articles

Effect of charge on the concentration decay and size growth of PAO aerosol in a closed chamber in different charged conditions

Studies on the charged aerosol dynamics are essential for addressing the radioactive aerosol behavior suspended in fast reactor containment during severe accident conditions. Towards this, lab-scale experiments are conducted to measure the effect of charge on aerosol dynamics. Polyalphaolefin (PAO) aerosol studied here is spherical, nonporous and chargeless during generation. Aerosol is externally charged to different charge conditions and charge levels by controlling the ion exposure using Electrostatic Aerosol Neutralizer (EAN), before suspending inside the test chamber. Electrical Low-Pressure Impactor (ELPI) is used to measure the evolution of aerosols’ charge, concentration decay, and size growth in the chamber. The concentration decay is enhanced for both unipolar and bipolar charged aerosols compared to baseline condition without additional charge. The decay is proportional to the average charge irrespective of the polarity. There is no observable change in size growth for bipolar-charged aerosols compared to baseline with the tested ion asymmetry ratios and average charge levels, and so the enhanced concentration decay is due to increase in deposition. Unipolar charging reduces the size growth due to electrostatic dispersion against the coagulation and increases the deposition. This methodology can be extended to analyze the morphology effect on aerosol charging and dynamics in actual scenarios.

Assessing the impact of device parameters on electronic cigarette aerosol dynamics: Comprehensive analysis of emission profiles and toxic chemical constituents.

The toxicity of electronic cigarette (EC) aerosol is influenced not only by the type of e-liquid but also by various operational parameters of the device used to vaporize it. In this study, we utilized a flask and heating mantle system, instead of a conventional EC device, to systematically evaluate the effects of EC device operational parameters, including vaporization temperature, airflow rate, and the materials of coils and wicks, on the generated mass of EC aerosol and the production of toxic carbonyl compounds. The results demonstrated that these parameters significantly impact aerosol mass and toxicant composition. Specifically, increasing vaporization temperature and airflow rate drastically affect aerosol mass, showing exponential and logarithmic increases. Using the ISO 20768 method, aerosol mass (from 20μL e-liquid) escalated over threefold from 3100μg at 200°C to 10,300μg at 400°C, illustrating temperature's pivotal role. Formaldehyde levels rose from 0.21μg to 60.2μg with temperature increases from 200°C to 400°C. At a realistic vaporization temperature of 300°C, the formaldehyde mass was 2.21μg (3.28ppm), exceeding the lowest-observed-adverse-effect level for acute respiratory toxicity in humans. While cotton wicks modestly affected aerosol mass, they significantly raised formaldehyde and acetaldehyde levels by 36.2%. In contrast, silica, kanthal, and nichrome materials increased aerosol mass and chemicals like propylene glycol, vegetable glycerin, nicotine, formaldehyde, and acetaldehyde by 22.7% to 63.2%. Our findings underscore the urgent need for regulations encompassing e-liquids and EC devices to mitigate health risks associated with EC use, providing a scientific basis for safety-focused regulatory measures.

Carcinogenic and non-carcinogenic risk estimation of indoor TVOCs, RSPM, FPM and SFPM on young women dwellers: a case study from the capital city of Uttar Pradesh, India

Total volatile organic compounds (TVOCs), respiratory suspended particulate matter (RSPM-PM10), fine particulate matter (FPM-PM2.5) and sub-fine particulate matter (SFPM-PM1) have been found to exert negative impact on the women health. This study was conducted to see the effect of indoor RSPM, FPM, SFPM and TVOCs on women health predominantly on young women dwellers (specifically categorized into pre-teenagers i.e., 8–12 years, teenagers i.e., 13–19 years and post-teenagers i.e., 20–21 years). Indoor monitoring was conducted from November 2022 to February 2023 in six different urban households of Lucknow, capital city of Uttar Pradesh state of India. Envirotech APM 550 for RSPM and FPM, APM 577 for SFPM and portable sensor-based instrument (BR-SMART) were used to measure TVOCs. The highest average indoor concentrations was found to be 250.1 ± 14.11 µg/m3 (PM10) at Rajajipuram, 140.62 ± 19.71 µg/m3 (PM2.5) at Indranagar, 27.60 ± 1.87 µg/m3 (PM1) and 934 ± 70.41 µg/m3 (TVOCs) at Kaiserbagh.Health risk assessment was also determined using average daily dose (ADD), excess lifetime cancer risk (ELCR) and hazard quotient (HQ) for carcinogenic and non-carcinogenic risk. ELCR values for PM1 and PM2.5 surpassed the permissible limit in every house and HQ values also exceeded the minimum allowable value for 20–21 year age group at all of the locations, indicating substantial health risk from exposure. International Committee of Radiological Protection Model (ICRP) and Multiple Path Particle Dosimetry (MPPD) model were used to see the regional deposition of PMs on the young women dwellers. To elucidate the spatial dynamics of these pollutants, the Inverse Distance Weighting (IDW) interpolation technique was employed. Additionally, site-specific analysis of PM mass ratios (PM2.5/PM10, PM1/PM2.5 and PM1/PM10) elucidated the particle size distribution and their sources, significantly enhancing the scientific understanding of aerosol dynamics in these urban settings.

Analysis of Brownian coagulation in the spatial mixing layer with average kernel method and iterative direct numerical simulation

This study investigates the evolution of nanoparticle populations undergoing Brownian coagulation in a spatial mixing layer. The dynamics of particle size distribution and number concentration are analyzed using a coupled Eulerian approach that combines fluid dynamics with aerosol dynamics. The mixing layer serves as a fundamental flow configuration to understand particle–vortex interactions and their effect on coagulation rates. Results demonstrate that the shear-induced spatial mixing significantly influences the spatial distribution of nanoparticles and their subsequent coagulation behavior. The enhanced mixing in the shear layer leads to locally increased particle collision frequencies, accelerating the coagulation process compared to laminar conditions. The study reveals that the evolution of the particle size distribution is strongly dependent on both the local vorticity intensity and the initial particle concentration gradients across the mixing layer.

Aerosol dynamics in dental clinics: Effects of ventilation mode on the mitigation of airborne diseases transmission.

Dental operations inherently involve a high risk of airborne cross-infection among medical staff and patients due to the exposure of respiratory secretions, which contain pathogenic microorganisms and typically spread in the form of aerosols. In order to contribute to the understanding of aerosol dynamics during dental operation and efficiently mitigate their dispersion and deposition through appropriate ventilation, 3D numerical simulations and full-scale experimental measurements were performed in this study. The indoor airflow distribution and dynamic aerosol behaviors observed under three optimized ventilation schemes (Scenario I-III) were compared with those observed under the current ventilation system. Qualitative analysis was performed together with quantitative examination using the air age, air change efficiency, contaminant removal effectiveness, and deposition ratio. It is demonstrated that the ventilation currently in use is unable to effectively discharge aerosols, resulting in most of them depositing on surfaces routinely accessed by dental workers. The pronounced air mixing effect induced by the design of Scenario I facilitates the rapid dispersion of aerosols throughout the clinic, impeding the efficient removal via the outlet. Moreover, the effective elimination of indoor aerosols is only attainable by implementing high ventilation rates in Scenario II. The Scenario III exhibits better overall performance, as evidenced by the successful discharge of approximately 69.8% of injected aerosols with limited deposition on indoor surfaces under ACH=6h-1, and further enhanced performance is observed at higher ACHs for contaminant removal. The prevailing ventilation design in dental clinics, which primarily focuses on maintaining a desirable temperature and relative humidity, often overlooks the necessity of proper ventilation for reducing the exposure risk of occupants. This study provides solid evidence for the upgrading or reconstruction of ventilation systems in dental clinics, aiming to promote a safe and healthy treatment environment.

Analytical solution of the 1-D population balance equation using Laplace transformation and Adomian Decomposition Method

The population balance equation (PBE) is a fundamental tool in chemical engineering for modeling particulate processes where particle size distribution significantly impacts product quality and process performance. It finds extensive applications in crystallization, polymerization, granulation, L-L extraction and aerosol dynamics. In this study, we present an analytical technique for solving the one-dimensional population balance equation (PBE). This technique combines Laplace transformation with the Adomian Decomposition Method (LADM), where the Laplace transformation is applied with respect to time, and the Adomian Decomposition Method (ADM) is used to address the resulting equation along the spatial coordinate. We examine specific cases involving pure convection, pure growth, pure breakage, and the combined processes of growth and breakage. This methodology provides analytical solutions involving the transport and particle-particle interaction phenomena of the dispersed phase.

Experimental Full-volume Airway Approximation for Assessing Breath-dependent Regional Aerosol Deposition.

Modeling aerosol dynamics in the airways is challenging, and most modern personalized in vitro tools consider only a single inhalation maneuver through less than 10% of the total lung volume. Here, we present an in vitro modeling pipeline to produce a device that preserves patient-specific upper airways while approximating deeper airways, capable of achieving total lung volumes over 7 liters. The modular system, called TIDAL, includes tunable inhalation and exhalation breathing capabilities with resting flow rates up to 30 liters per minute. We show that the TIDAL system is easily coupled with industrially and clinically relevant devices for aerosol therapeutics. Using a vibrating mesh nebulizer, we report central-to-peripheral (C:P) aerosol deposition measurements aligned with both in vivo and in silico benchmarks. These findings underscore the effectiveness of the TIDAL model in predicting airway deposition dynamics for inhalable therapeutics.

A Ventilated Three-Dimensional Artificial Lung System for Human Inhalation Exposure Studies.

Traditional in vitro and in vivo models for inhalation toxicology studies often fail to replicate the anatomical and physiological conditions of the human lung. This limitation hinders our understanding of intrapulmonary exposures and their related health effects. To address this gap, we developed a ventilated artificial lung system that replicates human inhalation exposures in four key aspects: (1) facilitating continuous breathing with adjustable respiratory parameters; (2) distributing inhaled aerosols through transitional airflow fields in 3D-printed airway structures, which enables size-dependent particle deposition; (3) duplicating the warm and humid lung environment to promote inhaled aerosol dynamics, such as hygroscopic growth; and (4) supporting the cultivation of human airway epithelium for aerosol exposure and toxicological analyses. As a proof-of-concept application, we exposed human bronchial epithelial cells to electronic cigarette aerosols in the system. Our results show that electronic cigarette particles undergo significant hygroscopic growth within the artificial lung, leading to a 19% greater deposition dose compared to data collected at room temperature and relative humidity. Additionally, short-term exposure altered epithelial production of the chemokine Fractalkine in a nicotine-dependent manner, but no acute toxic effects were observed. This artificial lung system provides a more physiologically relevant in vitro model for studying inhalation exposures.

Effects of nasal cavity and exhalation dynamics on aerosol spread in simulated respiratory events

Coughing and sneezing are critical mechanisms for the transmission of airborne respiratory diseases, dispersing pathogen-laden aerosols into the environment. Previous human volunteer studies provided valuable insight into aerosol dynamics but lacked reproducibility due to individual variations. This paper presents a novel, replicable experimental setup using three dimensional models of the upper respiratory tract and nasal cavity to simulate isothermal human-like coughs and sneezes. Results indicate that nasal cavity involvement decreases horizontal aerosol cloud spread while enhancing vertical dispersion. Incorporating this experimental data with theoretical models improves predictive accuracy of aerosol cloud evolution, particularly for indoor environments. Finally, a single novel analytical expression for the evolution of the particle cloud tip is derived that accurately predicts the cases studied.

Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula

Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. Developed and validated over South Korea from 1 January to 31 December 2019, the model effectively improved data coverage from 6% to 100%. The approach demonstrated high performance in blind tests, achieving a root mean square error (RMSE) of 0.064 and a correlation coefficient (CC) of 0.966. Meteorological analysis indicated optimal model performance under cold, dry conditions (RMSE: 0.047, CC: 0.956), compared to humid conditions (RMSE: 0.105, CC: 0.921). Validation against Aerosol Robotic Network (AERONET) ground observations showed that, while the original Himawari-8 data exhibited higher accuracy (RMSE: 0.189, CC: 0.815, n = 346), the gap-filled dataset maintained reasonable precision (RMSE: 0.208, CC: 0.711) and significantly increased the number of valid data points (n = 4149). Furthermore, the gap-filled dataset successfully captured seasonal AOD patterns, with values ranging from 0.245–0.300 in winter to 0.381–0.391 in summer, providing a comprehensive view of aerosol dynamics across South Korea.

Optimization of Placement of Continuous Air Monitors in a Radiological Facility

AbstractThe airborne concentration of radioactive materials in radiological facilities is primarily influenced by the ventilation system, air purification system, and emission sources. Continuous Air Monitors (CAMs) are installed in these facilities to monitor the activity concentration of radioactive aerosols during both routine operations and any malfunctioning conditions. Typically, CAM placement is determined by the direction of maximum airflow. However, aerosols do not always adhere to the behaviour of airstreams, raising concerns about the suitability of CAM placement. To address this issue, this study employs software that integrates aerosol dynamics with computational fluid dynamics to calculate the CAM Placement Parameter. This parameter is derived from the peak aerosol concentration and the lag time to reach the specified CAM location, indicating the relative merit of positioning CAMs in a radiological facility under varying ventilation rates. The findings suggest that the coupled aerosol-fluid dynamics model accurately predicts the optimal placement of CAMs in workplace environments, thereby minimizing occupational exposure.

Real-time measurement of metals in submicron aerosols with particle-into-liquid sampler combined with micro-discharge optical emission spectroscopy

The paper presents a novel technique for quantifying trace metals in aerosol samples in real time. Airborne metals were continuously collected for one week near the Baltic Sea in Finland using a particle-into-liquid sampler (PILS). The collected liquid samples were analyzed for metals using micro-discharge optical emission spectroscopy (µDOES). The micro-discharge analyzer is designed to perform real-time, on-site measurements of metal concentrations in aqueous solutions. Currently, µDOES can provide online measurements of 30 metals, with typical detection limits from 0.01 µg/m3 to 0.06 µg/m3 with a long-term repeatability less than 5%. The novelty of this analyzer lies in its compact design, rapid detection capabilities, and ease of operation and maintenance. Several metals, including potassium (K), calcium (Ca), sodium (Na), aluminum (Al), magnesium (Mg), and copper (Cu), were measured in the aerosol samples collected using PILS. The results indicate that this approach has significant potential for future automated online monitoring of airborne metal concentrations, facilitating investigations into their sources and daily variations. The development of real-time technologies for rapid, online, and accurate atmospheric aerosol measurements is essential for advancing climate change research. Such advancements allowing for continuous real-time data enhance our understanding of aerosol dynamics, improve source identification, and inform public health and environmental policies, ultimately contributing to more effective climate change monitoring and mitigation.

Shape-dependent aerosol dynamics in indoor environments: Penetration, deposition, and dispersion

Particle shape exerts a significant influence on their dynamic behavior, and it is imperative to elucidate these effects given the potential for severe environmental toxicity associated with shaped particles. Despite extensive research on the dynamical processes of spherical particles, the behaviors of non-spherical particles have been insufficiently investigated. In this study, we have developed a suite of computation-based models that account for particle shape and have reported on the typical dynamical behaviors of non-spherical particles within indoor environments. We have explored three typical scenarios, i.e., particle penetration into indoor spaces through building cracks, indoor particle deposition, and indoor particle dispersion. The shape-induced deviations are associated with dynamical processes, showing a decrease trend among penetration, deposition, and dispersion of the non-spherical particles. The maximum discrepancy due to particle shape during the penetration process exceeds 1000 %, observed with particles of approximately 0.02 μm in diameter interacting with straight cracks 4.5 cm in length and 0.25 mm in height. Moreover, there is a discrepancy of more than 70 % in the deposition of particles with a diameter of approximately 10 μm on side walls when using side air supply ventilation. Similarly, a discrepancy of nearly 11 % is noted for particles around 0.02 μm in diameter during dispersion under displacement ventilation within indoor settings. The interaction between shape-related particle dynamics, particularly their diffusion characteristics, and the properties of the flow field leads to these shape-dependent dynamical discrepancies. These findings offer a comprehensive understanding of how the shape of particles affects their indoor dynamic behavior, thereby supporting the control of hazardous particles in indoor environments.

Dynamics of Microbial Ecology, Particulate Matter, and Bacterial Aerosols in Agriculture: Implications for Health and Sustainability

Dynamics of Microbial Ecology, Particulate Matter, and Bacterial Aerosols in Agriculture: Implications for Health and Sustainability

Intercomparison of WRF-chem aerosol schemes during a dry Saharan dust outbreak in Southern Iberian Peninsula

The Iberian Peninsula (IP), where this study is conducted, has experienced an increase of the frequency and intensity of Saharan aerosol dust outbreaks over the latest decades, which may have an impact on its regional climate. The Weather Research and Forecasting model coupled with chemistry (WRF-chem) has been used worldwide to simulate dust outbreaks and can support the analysis of such potential impacts. However, it includes multiple alternative aerosol parameterization choices that have not been conveniently evaluated in the study region yet. Here, three of the most popular WRF-chem aerosol parameterization schemes, namely, the Goddard Chemistry Aerosol Radiation and Transport (GOCART), the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) and the Modal Aerosol Dynamics Model for Europe (MADE) schemes, are inter-compared during a strong and dry dust outbreak on July 2021 in southern IP. The results show that the three schemes predict qualitatively similar dust intrusion patterns that are consistent with ground observations and have inter-model dust loading differences smaller than 4%. However, their average dust size distributions differ notably. While GOCART is reasonably consistent with observations, MOSAIC underpredicts the amount of dust particles with sub-micron diameters and overpredicts that of large particles and MADE does the opposite. This is found to have a strong detrimental impact on the prediction performance of dust optical properties in MOSAIC and MADE, which is related, at least partially, with issues in the required inter-sectional redistribution of dust parameters during the dust emission and calculation of optical properties. Overall, GOCART generally appears a better choice for strong and dry dust outbreak events in southern IP. It remains to be evaluated during wet dust outbreaks, which is a work underway.

Unveiling soil coherence patterns along Etihad Rail using Sentinel-1 and Sentinel-2 data and machine learning in arid region

This research applies machine learning to predict soil coherence for Etihad Rail, marking the first comprehensive study in the United Arab Emirates (UAE)'s arid regions. By integrating Sentinel-1 SAR and Sentinel-2 data with MODIS Aerosol Optical Depth (AOD) observations, the study develops detailed models that depict complex soil coherence patterns crucial for urban planning and risk assessment. Findings show variations in soil coherence between operational and under-construction phases, influenced by seasonal changes in aerosol dynamics and sand dust levels. Higher soil coherence is linked with lower annual sand dust deposition and AOD measurements, emphasizing the importance of this data for informed decision-making. The study employs a unique combination of data sources and machine learning algorithms to predict soil coherence, including Support Vector Machine (SVM), Extreme Gradient Boosting (XGBOOST), Gaussian Process Regression (GPR), Random Forest (RF), and 1D Convolutional Neural Network (CNN), with the Random Forest model achieving the lowest root mean squared error (RMSE) of 0.0826. These contributions enhance our understanding and provide a valuable framework for infrastructure development in similar environments.

Improvement and validation of discrete-sectional method based code for fast reactor aerosol dynamics

The study of the dynamics of aerosols produced during a severe accident is vital to the safety analysis of a Sodium-cooled Fast Reactor (SFR). Sodium leakage into the containment following a severe accident may result in the production of sodium aerosols along with fission product aerosols. The in-containment radioactive source term depends upon the settling behaviour of fission product aerosols, which co-agglomerate with sodium fire aerosols. Hence, an in-depth understanding of the dynamics and deposition of aerosols within the containment is essential for the safety assessment of an SFR. The current work uses an open-source code based on the Discrete-Sectional (DS) method to solve the simplified form of General Dynamics Equation (GDE) for aerosols relevant to fast reactors. Aerosols of SrO2, CeO2 and sodium are considered in the present work. The DS code has been modified and further improved by including gravitational coagulation, turbulent coagulation, Brownian deposition, gravitational deposition and thermophoretic deposition so that the code can handle the different processes leading to the deposition of aerosols following a sodium fire. The code is also enhanced to account for the effect of relative humidity through the modified Cooper's equation. The improved code is then validated with different experiments conducted in the Aerosol Test Facility (ATF), India; Mini Sodium Fire Facility (MINA), India; and AHMED (Aerosol and Heat Transfer Measurement Device), Finland. Validation from different facilities confirms the applicability of the code to various scenarios. It is found that the modified DS code could predict the decay of suspended mass concentration of aerosols in different enclosures with reasonable accuracy.

Measurement report: The Fifth International Workshop on Ice Nucleation phase 1 (FIN-01): intercomparison of single-particle mass spectrometers

Abstract. Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different single-particle mass spectrometers (SPMSs). An intercomparison of SPMSs was conducted at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber at the Karlsruhe Institute of Technology (KIT) in November 2014, as part of the first phase of the Fifth International Workshop on Ice Nucleation (FIN-01). In this paper we compare size distributions and mass spectra of atmospherically relevant particle types measured by five SPMSs. These include different minerals, desert and soil dusts, soot, bioaerosol (Snomax; protein granule), secondary organic aerosol (SOA), and SOA-coated mineral particles. Most SPMSs reported similar vacuum aerodynamic diameter (dva) within typical instrumental ranges from ∼100–200 nm (lower limit) to ∼2–3 µm (upper limit). In general, all SPMSs exhibited a wide dynamic range (up to ∼103) and high signal-to-noise ratio (up to ∼104) in mass spectra. Common spectral features with small diversities in mass spectra were found with high average Pearson's correlation coefficients, i.e., for average positive spectra ravg-pos=0.74 ± 0.12 and average negative spectra ravg-neg=0.67 ± 0.22. We found that instrument-specific detection efficiency (DE) was more dependent on particle size than particle type, and particle identification favored the use of bipolar, rather than monopolar, instruments. Particle classification from “blind experiments” showed that all instruments differentiated SOA, soot, and soil dust and detected subtle changes in the particle internal mixing but had difficulties differentiating among specific mineral types and dusts. This study helps to further understand the capabilities and limitations of the single-particle mass spectrometry technique in general and the specific performance of the instrument in characterizing atmospheric aerosol particles.

Numerical Evaluation of Aerosol Propagation in Wind Instruments Using Computational Fluid Dynamics

This paper examines aerosol propagation in wind instruments through numerical analysis, focusing on particle trajectories within five types of wind instruments: saxophone, clarinet, flute, oboe, and trumpet. Using a computational fluid dynamics approach, it is found that larger particles are deposited within the instruments, while smaller micron-sized particles predominantly exit through the bell. The impact of the instrument’s geometry on aerosol dynamics is quantified; cylindrical instruments (clarinet, flute) show an increased rate of small droplet deposition or escape through tone holes compared to conical instruments (saxophone, oboe). Instruments with steep turnings, such as the trumpet, exhibited significant particle deposition. The study suggests that deposited particles are likely to move towards re-emission points, driven by gravity and airflow, especially in straight-shaped instruments. Integrating computational fluid dynamics (CFD) as a complementary approach to traditional experimental methods provides insights into aerosol transmission mechanisms in musical settings. This methodology not only aids in understanding aerosol behavior but also supports the development of safer musical and educational environments, contributing to the field.

Projected global sulfur deposition with climate intervention

Even with immediate implementation of global policies to mitigate carbon dioxide emissions, the impacts of climate change will continue to worsen over the next decades. One potential response is stratospheric aerosol injection (SAI), where sulfur dioxide is released into the stratosphere to block incoming solar radiation. SAI does not reduce the level of carbon dioxide in the atmosphere, but it can slow warming and act as a stopgap measure to give the world more time to pursue effective carbon reduction strategies. While SAI is controversial, it remains a technically feasible proposition. It ought to be thoroughly modeled both to characterize global risks better and to further the scientific community’s understanding of stratospheric aerosol dynamics. SAI relies on sulfate aerosols which have a lifetime of several years in the stratosphere but will eventually be deposited back onto Earth’s surface. While sulfate is an important nutrient for many ecosystems, high concentrations can cause acidification, eutrophication, and biodiversity loss. We use model outputs from the Geoengineering Model Intercomparison Project (GeoMIP) to track the impacts of sulfur deposition from SAI to various ecoregions through comparison with historical climate and future Shared Socioeconomic Pathway (SSP) scenarios. Our results demonstrate that dry sulfur deposition will continue to decline worldwide, regardless of scenario, from a high of 41 Tg S/yr in 1981 to under 20 Tg S/yr by 2100. Wet sulfur deposition, however, is much more uncertain and further work needs to be done in this area to harmonize model estimates. Under SAI, many ecoregions will experience notably different sulfur deposition regimes by the end of the century compared to historical trends. In some places, this will not be substantially different than the impacts of climate change under SSP2–4.5 or SSP5–8.5. However, in some ecoregions the model projections disagree dramatically on the magnitude of future trends in both emissions and deposition, with, for example, UKESM1–0-LL projecting that SO42- deposition in deciduous needleleaf forests under G6 Sulfur will reach 394 % of SSP2–4.5 deposition by the 2080 s while CESM2-WACCM projects that SO42- deposition will remain at 170 % of SSP2–4.5 deposition during that same time period. Our work emphasizes the lack of agreement between models and the importance of improving our understanding of SAI impacts for future climate decision-making.