Poster Session 2

Poster Session 2 — 1:30–3:00 PM

Poster #	Topic	Title	Authors	Abstract
P2.1	Climate, Extreme Weather, and Dust	Volcanic Ash-Induced Glaciation of Clouds in the Mixed-Phase Regime: Implications for Arctic Climate Intervention	Katie Chan, Nina Iren Kristiansen, Flor Vanessa Maciel, Jasper Kok	Mineral dust is the most abundant ice-nucleating particle (INP) in the atmosphere, and its ability to glaciate supercooled liquid droplets underpins a proposed Arctic geoengineering strategy known as mixed-phase cloud thinning (MCT). MCT aims to seed Arctic mixed-phase clouds with efficient INPs to reduce the liquid water content that contributes to their warming effect at the surface. However, assessing the feasibility of MCT requires observational evidence of how effectively elevated concentrations of mineral-derived INPs can promote cloud glaciation. Here, we investigate the 2010 Eyjafjallajökull eruption, which emitted approximately 40 Tg of volcanic ash into the troposphere, providing a large-scale natural perturbation of mineral-derived INPs relevant to MCT. Given that mineral dust and Eyjafjallajökull ash exhibit comparable immersion-freezing properties, this eruption provides an opportunity to quantify dust-driven cloud glaciation. We combine CALIOP tropospheric aerosol-subtype classifications, CloudSat cloud-top phase retrievals, and three-dimensional ash transport simulations to compare glaciation metrics derived from cloud phase partitioning between clouds within or adjacent to ash layers versus unaffected clouds across the mixed-phase temperature regime (0 to -38 ℃). This framework evaluates whether mineral-derived INP perturbations drive statistically significant increases in primary ice formation, offering insights into the viability of MCT as an Arctic climate intervention strategy.
P2.2	Climate, Extreme Weather, and Dust	Climate Change Impacts of Saharan Dust Emissions and Transport	Rohit Raghuraman Rajagopalan, Shu-Hua Chen, Terry Nathan	Dust aerosols have several impacts on the Earth system, including their influence on climate through their interactions with clouds and radiation. Equally important, climate change is expected to influence dust emissions and transport, modifying future storm activity. This study will explore how climate change will modify Saharan dust emissions and transport and how dust, in turn, affects climate change over the tropical Atlantic Ocean. The WRF-Dust model will be used to dynamically downscale bias-corrected CMIP5 CESM data for the warm season (July to September) for the current (1995 to 2024) and future (2055-2084) climate. How climate change influences Saharan dust emissions and long-range transport, such as reaching the Greater Caribbean Region and Amazon forest, how future Saharan dust modulates cloud activity over North Africa and the eastern Atlantic Ocean, and the climate variability, will be presented.
P2.3	Climate, Extreme Weather, and Dust	Characterizing Dust and Surface PM10 During Compound and Cascading Extreme-Event Regimes	Farhana Meheru, Farnaz Hosseinpour	Atmospheric dust contributes to PM10 and responds to coupled meteorological and land-surface conditions. Understanding of how surface PM10 and aerosol conditions differ among individual hazards, concurrent multihazard events, and time-ordered cascading sequences involving drought, heat, high winds, and wildfire smoke remains limited across California and Nevada. This study develops an event-regime framework using long-term ground-based PM10 observations, aerosol reanalysis, satellite observations, and meteorological and land-surface data. Objective thresholds will identify baseline conditions, individual hazards, and concurrent compound events; event chronology and lagged evolution will characterize cascading sequences. Copula-based analysis will quantify joint and conditional dependence, including tail co-occurrence, among drought, heat, wind, fire-related indicators, and PM10/aerosol conditions. Physical-process diagnostics of surface winds, atmospheric mixing, soil moisture, land-surface state, and synoptic circulation will provide context for observed dependence patterns. The analysis will test whether PM10 magnitude, transport, and persistence differ systematically across event regimes and identify the physical environments associated with those differences. Integrating surface observations with dependence and sequence analyses, the study will advance a process-based characterization of dust-related PM10 under complex extremes.
P2.4	Climate, Extreme Weather, and Dust	Spatiotemporal Deep Learning for PM10 Bias Correction Under Extreme Conditions	Ricky Cavaliero, Farnaz Hosseinpour	Atmospheric dust can produce substantial spatiotemporal variability in surface PM10 that is difficult for coarse-resolution aerosol products to resolve, particularly under extreme conditions. This study develops a process-informed spatiotemporal deep-learning framework to improve MERRA-2 PM10 estimates using EPA observations across California and Nevada. The deep-learning system couples convolutional neural networks (CNNs), which encode spatial structure in gridded aerosol, meteorological, and land-surface fields, with long short-term memory networks (LSTMs) that capture evolving atmospheric states through gap-aware consecutive time windows. Tree-based ensemble models serve as interpretable reference benchmarks. Consistent predictor information and identical data partitions enable a fair assessment of the added value of spatiotemporal deep learning. Training, validation, and an independent future test period are separated chronologically to prevent information from later dates entering model development. Time-aware cross-validation and hyperparameter tuning occur only within the training period. Performance and systematic bias are evaluated overall and during drought, heatwave, high-wind, dust-favorable, and compound-event conditions. Feature-attribution analyses identify environmental features associated with model correction skill. The framework is designed to improve MERRA-2 surface PM10 estimates, reduce systematic bias, and identify conditions under which deep-learning corrections provide the greatest value for dust-relevant air-quality applications.
P2.5	Dust Observations, Forecasting, and Physical Processes	Geometric source apportionment of long transport aerosols collected at Greenland Summit Station	Bora Jin, Nicholas J. Spada, Jessie Creamean, Matthew Shupe, Abhirup Datta	Over the last four decades, the Arctic has warmed four times faster than the rest of the planet, with anthropogenic aerosols among the major forcings driving this change. Summit Station is a high latitude, high elevation research station on the Greenland ice cap. It has operated continuously since 1989, with size-resolved particulate matter (PM) measurements collected year-round beginning in 2003. While a great deal of scientific literature has been produced from gas phase measurements, the PM results have largely been underutilized. A previous assessment of 2005-2006 data identified seven major sources including desert dusts of African and Asian origin, volcanic aerosols, industrial and marine combustion, and the well-mixed Arctic Haze background. We re-analyze an extended record (2003 – 2016) using geometric non-negative matrix factorization for source apportionment and interpretation. This approach recovers sources through geometric operations, avoiding the subjectivity of user-manipulated weighting factors and the ambiguity of regularization choices. It targets a scale-invariant, identifiable source attribution matrix, replaces hard the separability assumption with a soft probabilistic relaxation, and yields consistent estimates without parametric distributional assumptions while accommodating spatio-temporal dependence in the data. Combined with HYSPLIT trajectory analysis, we characterize the long-range transport of anthropogenic and natural species into the Arctic environment.
P2.6	Dust Observations, Forecasting, and Physical Processes	Long-term Consistency of IMPROVE PM2.5 Soil Element Measurements: 1988-2025	Nicole Hyslop, Jiayuan Wang, Xiaolu Zhang, Warren White	The Interagency Monitoring of Protected Visual Environments (IMPROVE) network has monitored the chemical composition of fine particulate matter (PM2.5) in rural U.S. areas since 1988. Concentrations of 24 elements (Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Br, Rb, Sr, Zr, and Pb) have been measured since the network’s inception. Over the years, changes in analytical instruments, reporting conventions, and methods have introduced measurement discontinuities that can complicate long-term trend analyses, particularly for elements with concentrations near detection limits. To evaluate measurement consistency, we analyzed elemental data from 67 IMPROVE sites operating before 2000 with more than 75% sample completeness. Harmonized detection limits were estimated for 21 elements (Mg, Al, Si, P, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Br, Rb, Sr, Zr, and Pb) to provide consistency across instrumental eras. Measurement continuity was assessed using annual empirical cumulative distributions, monthly percentile time series, year-to-year shift, and concurrent-measurement comparisons (elements versus ions and element versus element). The harmonized detection limits agreed closely with the reported method detection limits (MDL) for most elements, supporting the validity of the historical MDL. Based on detectability and continuity, elements were classified into four categories reflecting their suitability for long-term trend analyses. Si, S, K, Ca, Fe, and Br were well detected and exhibited consistent behavior across percentiles and instrumental eras. Al, Ti, Mn, Zn, Sr, Pb, and Na were categorized as “robustly detected”, with detection rate of 50-80% and consistent trends for higher loading samples (above 50~75th percentile). Mg, P, Cl, V, Cr, Ni, Cu, Se, As, Rb were classified as “serviceable”, exhibiting greater inconsistencies across instrumental eras; analyses of these elements are best restricted to appropriate instrumental eras and sites with detection rates exceeding 80%. By harmonizing detection limits and systematically evaluating measurement consistency over more than three decades, this study provides practical guidance for IMPROVE data users to minimize potential pitfalls and improve the reliability of long-term trend analyses.
P2.7	Dust Observations, Forecasting, and Physical Processes	Observations of Dust Emissions and Boundary Layer Dynamics in a Chihuahuan Desert Shrubland	Samuel Jurado, Nicholas Webb, Christopher Hocut, Brandon Edwards, Matthew Mavko	Wind erosion threatens over 60 million hectares of U.S. rangelands, imposing substantial economic costs and accelerating desertification through processes that facilitate woody shrub encroachment. Current dust emission models underestimate summertime atmospheric dust because convective processes, including thunderstorm outflows and boundary-layer turbulence, remain poorly represented in coarse-resolution simulations. These intermittent events may account for a substantial fraction of summertime dust emissions yet remain difficult to resolve, limiting understanding of dust dynamics in arid rangelands. This research investigates convective dust emissions and their diurnal variability over a Chihuahuan Desert shrubland during a 13-week campaign (June - August 2026) in southern New Mexico. We collected eddy covariance measurements of surface dust fluxes alongside ceilometer and sun radiometer observations of aerosol and atmospheric profiles. These synergistic observations are integrated to characterize the timing, magnitude, and atmospheric structure of convective dust events. Direct surface fluxes will be evaluated alongside landscape-scale net dust fluxes estimated using a boundary-layer budget approach based on mixed-layer slab theory, allowing assessment of how local emissions contribute to changes in atmospheric dust burden across the landscape. By linking surface exchange with boundary-layer dynamics, this work will improve understanding of the physical mechanisms governing episodic dust emissions and their diurnal variability in desert shrublands, providing a basis for improved representation of convective dust processes.
P2.8	Dust Observations, Forecasting, and Physical Processes	Source Apportionment of PM2.5 in El Paso, Texas: A Long-Term Study from 2000 to 2025	Jeewan Poudel, Gannet Hallar, Elisabeth Andrews, Rebecca J. Sheesley	El Paso lies within the Chihuahuan Desert, a major mineral-dust source region in the Western US and Northern Mexico. Dust emissions in this region primarily originate from dry lake beds, agricultural lands, unpaved roads, and other exposed soil surfaces. These emissions are influenced by wind speed, drought conditions, vegetation cover, soil crusting, land use, and sediment availability. Dust events in El Paso are commonly associated with synoptic-scale disturbances during the dry season (October to May) and mesoscale convective systems during the warm season (June to September). These dust events have been linked to elevated PM2.5 concentrations that reduce visibility and affect air quality. Exposure to elevated PM2.5 can significantly affect public health and has been associated with increased hospitalizations for respiratory and cardiovascular conditions. Therefore, it is necessary to identify and quantify the major sources contributing to PM2.5, particularly mineral dust. In El Paso, PM2.5 represents a mixture of mineral dust and other natural and anthropogenic sources, but their relative contributions over long time periods are not well characterized. This study will use the US EPA Positive Matrix Factorization (PMF) version 5.0 to perform long-term source apportionment of 24-hour PM2.5 speciated data collected at the Texas Commission on Environmental Quality (TCEQ) sites in El Paso Chamizal and the University of Texas at El Paso (UTEP) from 2000 to 2025. PMF-resolved factor profiles will be interpreted based on their chemical profiles and source-specific tracers.
P2.9	Dust Observations, Forecasting, and Physical Processes	Wind erosion dynamics following the Smokehouse Creek Fire in the Texas Panhandle	Abinash Bhattachan, Branimir Segvic, Riley Young, Scott Van Pelt, John Stout	Fire in drylands trigger high rates of aeolian erosion immediately after the fire. However, the relative contributions of fire-induced mineralogical degradation of soils, seasonal wind forcing and surface armoring to post-fire wind erosion remain poorly constrained. In this study, we examined these controls following the largest wildfire on record in Texas’ history. Time-resolved measurements of horizontal sediment flux were collected at several burned sites. These data were combined with mineralogical analyses of surface (burned) and subsurface (unburned) soils, as well as XRD characterization of eroded sediment collected during the peak post-fire erosion interval. Wind erosion rates were highest immediately after the fire and declined over time. Two burned sites with relatively low pre-fire clay mineral content showed erosion fluxes comparable to the control site suggesting post-fire surface armoring. Surface soils at erosive sites exhibited extensive thermal degradation and depletion of illite-smectite relative to underlying horizons, with losses of smectite up to 96%. XRD modal mineralogy of eroded sediments shows dominance of quartz and absence of clay minerals, contrasting with smectite bearing assemblages at the control site. Thus, post-fire erosion is governed by the pre-fire clay content with wind seasonality and surface armoring controlling the temporal trajectory of aeolian fluxes.
P2.10	Dust Observations, Forecasting, and Physical Processes	Dust Observations with Low-Cost Sensors in the Imperial Valley, California: Lessons Learned.	Maarten Schreuder, José Landeros, Sergio Valenzuela, Paul Schafer	Monitoring networks of low-cost sensors (LCS) are increasingly used to inform communities on the local air quality. These devices can provide more spatially resolved data but can be limited in terms of performance and accuracy compared to traditional regulatory monitors. This presentation will discuss the findings of several LCS monitoring networks for PM2.5 and PM10, using different types of sensors, in the Imperial Valley, California, over a period of up to two years, 2024-2026. These studies were conducted on behalf of the Imperial County Air Quality Control District, as well as local community organizations. Topics will include operational challenges with the instrumentation in a high temperature desert environment and a comparison of co-located results with regulatory monitors. While LCS instruments can be limited in terms of accuracy, it can be shown that they are able to 1) provide a general spatial and temporal indication of the air quality and, 2) register episodic high wind and dust events in the community.
P2.11	Dust Observations, Forecasting, and Physical Processes	Positive Matrix Factorization of XRF PM2.5 Filter Data Collected at Targeted International Border Ports of Entry in El Paso del Norte Region	Josdell Maria Guerra Ruiz, Victor Ajisafe, Gabriel Ibarra-Mejia	Management of fine particulate matter (PM2.5) poses a challenge as it exhibits source-dependent chemical composition. This study identifies and quantifies sources influencing PM2.5 speciation using Positive Matrix Factorization (PMF) receptor modeling on samples collected at targeted international border ports of entry (IBPEs) at The El Paso del Norte (PdN) Region. PdN is characterized by a binational airshed with significant transboundary air pollution challenges, holding non-attainment status for particulate matter as it frequently exceeds U.S. federal air quality standards, further influenced by its geomorphology and other natural and anthropogenic pollutants’ interactions. These include PdN’s characteristic heavy, slow-moving vehicle traffic with frequent braking, industrial manufacturing, and prevalent wind-driven resuspension of unconsolidated surficial sediments. PM2.5 was collected, from February to June 2025, on filters using MiniVol samplers at selected IBPEs, characterized fifty-two filters elementally by XRF, and modeled them using Positive Matrix Factorization (PMF). The analysis reflected routine and episodic dust storm events in the area, and identified six preliminary distinct pollution sources, where crustal dust, regional dust, and traffic non-exhaust were dominant at all sites. Among the modeled components apportioned to background were dust, local soil, brake pad and tire wear, vehicle fume combustion, and anthropogenic-related activity, rare for the region.
P2.12	Dust Impacts on Air Quality, Safety, and Health	Characterizing Arsenic in Playa Dust: Reducing Uncertainty in Health Outcomes Through Arsenic Speciation and Particle Size Distribution	Lindy Miller, Gregory T. Carling, Ruth Kerry, Ryan Tappero, Joshua J. LeMonte	Over 90 million Americans live in regions where year-round particle pollution levels exceed EPA air quality standards (American Lung Association, 2024). Compared with other pathways of contaminant transportation, dust has the highest capacity for transporting nonvolatile contaminants at regional and global scales (Csavina et al., 2012). Playas, especially terminal lake playas, are natural areas of contaminant accumulation, showing increased concentrations of salts and heavy metals. Arsenic is of particular concern because of its widespread occurrence and its toxicity at low levels (Csavina et al., 2012). The toxicity of arsenic depends largely on speciation. This research characterizes arsenic speciation in playa dust sampled at the Great Salt Lake and at two nearby cities in northern Utah using synchrotron-based X-ray absorption near-edge spectroscopy (XANES), and links speciation to particulate size distribution. Preliminary µXANES speciation findings show heterogeneous As speciation – reduced and oxidized forms – across and within sites. Arsenic concentrations are higher in finer fractions. This has important implications for public health, since the mobility and bioaccessibility of As depend on its oxidation state, and finer particles can penetrate deeper into the respiratory system. As playas continue to expand globally, understanding the composition, transport, and health impacts of playa-derived dust is increasingly critical.
P2.13	Dust Impacts on Air Quality, Safety, and Health	Assessing the Toxicity of Lubbock Dust Events Using an Analysis of Individual Human Lung Cells	Lauryn Fox, Karin Ardon-Dryer	Dust is a prevalent concern in the Lubbock area as particles from dust storms have the potential to be toxic to human health. Respiratory health in particular is especially vulnerable to changes in air quality conditions, with dust exposure being known to cause inflammation, trigger asthma, and lead to spikes in hospitalizations. This study aims to investigate the effects of different dust events that occur in Lubbock on human health using in vitro experiments with human epithelial lung cells (A549). Particle samples were collected from the AEROS station at Texas Tech University during dust events on May 17, 2022, and March 24, 2024. These events each had unique particle concentrations, size distributions and originated from different locations. By tracking individual A549 cells over 48 hours of exposure, the frequency and rate of cell division, as well as death, can be observed across different particle concentrations. A chemical analysis of these particles will help identify the primary compounds present in each dust event. This analysis may improve the understanding of the impact dust events have on human health - potentially contributing toward better hospital preparation and eventual prediction of health outcomes related to dust forecasts.
P2.14	Dust Impacts on Air Quality, Safety, and Health	Expert Assesment of Public Health Impacts from Drying Saline Lake Dust	Tyler Stephens, Ben Abbott, Greg Carling, Rachel Wood	Terminal saline lakes worldwide are experiencing unprecedented desiccation, exposing vast playas that generate wind-blown dust laden with a range of inorganic and organic contaminants. As the playas expand, populations in their vicinity face increasing concentrations of PM2.5 and PM10, degrading regional air quality. Despite the growing concern, epidemiological evidence linking saline lake-sourced particulate matter to specific health outcomes remains limited, creating a gap in public health decision-making. This study uses structured expert assessment to characterize health risks associated with lake dust exposure. A panel of experts from public health, atmospheric science, saline lakes, and other disciplines provided assesments of likely health outcomes, areas of highest concern, effectiveness of potential mitigation techniques, and quantitative health burdens. Findings characterize the range of expert opinions across multiple terminal saline lakes and provide a foundation for informed policy responses, including dust monitoring, public health surveillance, and saline lake management.
P2.15	Dust Impacts on Air Quality, Safety, and Health	Characterizing the Aerobiome of California’s San Joaquin Valley	Jesica Calderon, Adeola Fagbayibo, Estrella Herrera, Katrina Hoyer, Asa Bradman	The atmosphere hosts a collection of microorganisms known as the aerobiome and dust can transport these microbes. Changes in the aerobiome can impact respiratory health and introduce pathogens threatening crops. Little is known about the broader aerobiome composition of California’s San Joaquin Valley (SJV). This study was conducted to characterize the aerobiome in a dust prone environment such as the SJV furthering our understanding of fungal exposure risk, community composition, and serve as a foundation for future studies. Samples were collected across 12 sites in the SJV using active and passive air filtration methods. Extracted DNA from collected filters was analyzed using amplicon sequencing. Sequencing was performed on the Illumina MiSeq platform and processed in R using the DADA2 pipeline. Diversity metrics and relative abundance were used to evaluate community structure. Diversity metrics revealed distinct patterns across sampling approaches. Both sampling approaches captured similar amounts of diversity; however, passive samples contained a large fraction of unclassified sequences. Sample collection is complete, with bioinformatic analysis ongoing. This study establishes baseline characterization of the aerobiome in a dust prone region such as the SJV. By profiling microbial community structure, this study supports future surveillance efforts and aerobiome work in the region.
P2.16	Dust Impacts on Air Quality, Safety, and Health	Agricultural land fallowing amplifies local heat extremes and heat exposure during heatwave events across California’s Central Valley.	Md. Minhazul Kibria, Adeyemi A. Adebiyi	Heatwaves are intensifying under global climate change and pose increasing risks to human health worldwide. Farmworkers are particularly vulnerable because of prolonged outdoor exposure during extreme heat events. Beyond large-scale climate drivers, local land-surface conditions can modify heat extremes. In California, agricultural lands are frequently left fallow, altering surface energy balance and potentially enhancing near-surface warming. We assess the influence of fallowed lands on heatwave intensity across California using 4-km fallow fractions from the U.S. Department of Agriculture Cropland Data Layer and daily maximum and dew point temperatures from the PRISM dataset for 2015–2022. Heatwave characteristics are analyzed for the May–September season. Our results show that heatwave intensity over fallowed lands exceeds that over croplands in every year of the study period, with the difference reaching approximately 1.3 °C in May and remaining positive throughout the warm season (May–September). Our findings indicate that agricultural fallowing can intensify local heat extremes, increasing heat exposure risks for farmworkers and nearby rural communities and underscoring the need for targeted adaptation strategies.
P2.17	Dust Impacts on Air Quality, Safety, and Health	The Mountain/Sea Meteorology and Climate Change of California’s Salton Sea Air Basin and Their Impacts on Extreme Levels of Coarse Particulate Matter (PM10)	Ian Faloona, Dominic Ebert	The Salton Sea Air Basin (SSAB) is comprised of the Coachella and Imperial Valleys, running 200 km from Palm Springs to Calexico. The SSAB is categorized as serious 'non-attainment' for PM10 (particles with diameter < 10 m, coarse + fine modes) which is typically associated with dust, soot, and salts/toxic metals from the receding shores of the Salton Sea. Peak values of PM10 appear to be on an upward trajectory this century so understanding the principal causes is crucial. We present decades of meteorology and surface air quality data across the complex terrain of the air basin to illustrate the regional differences in seasonal peaks and proximate causes in order to give a better understanding of the conditions that promote PM10 extremes. Late afternoon wind peaks in spring and/or summer tend to be responsible for the majority of elevated PM10 occurrences. The synoptic setting that gives rise to these afternoon wind and PM10 events are associated with strong heating and intensification of the Southwestern US thermal low. In response to the recent acceleration of climate warming and drying in the US West (+0.7 C/decade, -0.5 %RH/decade) the conditions promoting high PM10 events are likely to increase in the coming decades.
P2.18	Dust and Agriculture, and Others	Mineralogical susceptibility of salt crusts to eolian weathering and atmospheric suspension: A case study of the Salton Sea, CA	Zachary Brown, Cassie Collins, Amato Evan, Rayna Goodman, Jocelyn Hillhouse, Xuan Liu, Maddie Morris, Kylee Nielsen, Lorrain Lucas-Scott, Rebecca Lybrand	The water levels in the Salton Sea continue to rapidly decline, which has exposed playa salt crusts and sediments as sources of dust to the region. The presence of salts can accelerate dust emissions, especially salt crusts and saline sediments experiencing wind erosion, wet-dry cycles, or those comprised of salt crystals that exhibit acicular (i.e. needle-like) and prismatic (i.e. column-like) tendencies. Our overarching goal was to analyze the chemical and mineralogical properties of the surface crusts, soils, and subsurface sediments around and adjacent to the Salt Sea to better understand the pedogenic processes that may influence dust emissions. We analyzed a total of 65 samples that were collected from 11 locations. We collected the following number of samples from the following field areas: Torrez Martinez(TM) (n=23), San Felipe Fan(SFF) (n=3), Naval Test Base(NTB) (n=1), Lupin Wash(LW) (n=2), Desert Shores(DS) (n=4), New River(NR) (n=4), Near the Geothermal Plant(NGP) (n=9), Alamo River(AR) (n=11), Salt Creek(SC) (n=3), Bombay Beach(BB) (n=4), and Glamis (n=1). Our team employed a combination of sampling techniques that involved the collection of contrasting surface crusts, establishing transects along an exposed shoreline gradient, and collecting surface crusts and subsurface sediments as a function of depth near river inflows to the Salton Sea. A combination of lab analysis techniques are currently being employed for each sample including soil pH, electrical conductivity (EC), mineralogical analysis, and particle size analysis (PSA) via the sieve and pipette method. This project also specifically developed a pretreatment method for PSA to remove the salts in order to determine the proportion of sand, silt, and clay present in each sample. Our ongoing work is comparing the resulting soil pH, EC, and PSA data sets across sites and as a function of depth within each field site location. Preliminary analysis show no clear trend in EC throughout subsamples whereas pH tends to stay within ± 0.5 from the surface crust to the lowest sampled depth for each analyzed site. The Salton Sea continues to recede due to climate change and water management changes, and understanding the impact of the exposed salt crusts and sediments on dust generation is critical for mitigating harmful atmospheric particulate matter.
P2.19	Dust and Agriculture, and Others	Quantifying Agricultural Dust Emissions in Southern California	Tobia Rinaldo, Amato Evan, Paolo D'Odorico, Rebecca Lybrand, Alex Kuwano, Greg Okin, Xuan Liu, William Porter, Jasper Kok, Adeyemi Adebiyi, Shu-Hua Chen	Air pollution remains a major problem in many parts of California, significantly impacting public health and regional climate. Dust storms are pervasive throughout California's Imperial and Coachella Valleys, driven by both episodic wind events and persistent fugitive dust sources active year-round. These storms carry wide-ranging costs, affecting agriculture, water resources, solar energy production, and highway visibility. Yet despite these impacts, the contribution of anthropogenic dust from agricultural sources, among the major pollutants in California's semi-arid regions, remains largely unclear. Fallowed land is a well-documented major anthropogenic dust source elsewhere in the state, but comparable data are lacking for the Coachella and Imperial Valleys, leaving agricultural dust sources in Southern California poorly quantified. To address this gap and better understand the mechanisms, characteristics, and controlling factors of dust emission from this common but understudied land type, we conducted a field campaign using a portable dust instrument (PI-SWERL) to measure emissions from typical Southern California land use types. This approach allowed us to map surface dust emissivity while assessing the influence of local factors such as soil texture and soil moisture on emission rates.