During the “Godzilla” dust storm of June 2020, unusually high fluxes of mineral dust traveled across the Atlantic from the Sahara Desert, reaching the Caribbean Basin, Gulf Coast, and southeastern United States. Additionally, an eruption of the La Soufrière volcano on St. Vincent in April 2021 generated substantial ashfall in the southeastern Caribbean. While many studies have analyzed mineral dust’s ability to relieve nutrient limitation of phosphorus (P) in the P-stressed North Atlantic, less is known about the impact of extreme events and other natural aerosols on fluxes of P into seawater and from seawater into marine microbial cells. We quantified P and iron (Fe) content in mineral dust from the Godzilla dust storm and volcanic ash from the La Soufrière eruption collected at Ragged Point, Barbados. We also performed seawater incubations to assess the marine microbial response to aerosol deposition. Using environmentally-relevant concentrations of atmospheric particles for within the ocean’s mixed layer allowed us to draw realistic conclusions about how these deposition events impacted P cycling in situ. Volcanic ash has lower P content than mineral dust, and P in volcanic ash is far less soluble (~1%) than assumed in current atmospheric deposition models. Adding mineral dust and the volcanic ash leachate in concentrations representing different deposition scenarios increased soluble reactive phosphorus (SRP) concentrations in coastal seawater by ~7-32 nM. Phosphate uptake rate was stimulated in coastal seawater after either mineral dust or volcanic ash deposition at aerosol concentrations relevant to the Godzilla dust event, with ash eliciting the fastest uptake rate. Furthermore, high concentrations of both the mineral dust and volcanic ash led to slightly elevated alkaline phosphatase activity (APA) compared to the relevant controls, indicating higher potential for use of dissolved organic phosphorus (DOP) as a P source. Quantifying these aerosols’ impacts on P cycling is a significant step towards achieving a better understanding of their potential roles in relieving nutrient limitation and fueling the biological carbon pump.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data and Scripts associated with “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling.”

This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.

54 ENVIRONMENTAL SCIENCES↗