Environmental Science Division (EVS)a Division of Argonne National Laboratory
 

Bio-Available Iron from Atmospheric Dust

EVS is using X-ray techniques and climate models to investigate the key mechanisms that control the solubility and bioavailability of iron in atmospheric dust, a major iron source for the marine ecosystem.

EVS atmospheric scientist Yan Feng is working in collaboration with EVS chief scientist Rao Kotamarthi and two scientists – Barry Lai and Stefan Vogt – of Argonne's Advanced Photon Source (APS) facility to unravel the chemical transformation mechanisms of iron in atmospheric dust. The three-year research project, entitled “Probing the Chemistry of Atmospheric Dust Particles using X-ray Spectromicroscopy: Implications for Climate Science” and funded by the Laboratory Director's Competitive Grant (2014-2016), strives to address the variations in composition of iron compounds and the dissolution mechanisms involved in the atmospheric transport of dust particles. It combines the synchrotron-based X-ray techniques developed at APS with modeling studies using the high-performance computing capabilities at the Argonne Leadership Computing Facility (ALCF).

Iron is an essential micronutrient for marine ecosystems. In many ocean regions, it controls the primary production (as organic compounds produced by photosynthetic organisms) and sequestration of carbon dioxide from the atmosphere. Iron in atmospheric dust is a major source of iron (about 95%) for marine ecosystems; therefore, it is critical to understand the factors controlling its solubility and associated bioavailability. Although many hypotheses have been proposed, the chemistry surrounding the dissolution of atmospheric (aerosol) iron is still not well understood. Earth System models conventionally assume a constant rate of iron solubility in dust, which could lead scientists to miscalculate carbon dioxide sequestration, especially in iron-limited oligotrophic waters. Our study addresses the uncertainties in modeled global soluble iron inputs to the ocean ecosystems. Its results will improve the effectiveness of Earth System models, making them more effective tools in understanding ocean biogeochemical cycles and their impact on climate change.

Modern microscopy and microanalysis techniques, such as the X-ray fluorescence (XRF) microspectroscopy developed and advanced at APS, provide scientists the unique capability of probing the mineral composition of individual dust particles. These synchrotron-based techniques have been used mostly in studying interplanetary stardust and have only recently been applied to the study of atmospheric particles. Elements such as iron, silicon, calcium, and aluminum in micron-sized atmospheric dust particles (10-7 to 10-5 meters) can easily be measured using hard X-ray microscopy at the APS beamlines in X-ray fluorescence mode for quantities down to the trace level in the real atmosphere. Using the APS microspectropy beamlines (e.g., 2-ID-D), we can further determine the oxidization states of iron (iron (II) or iron (III)) in dust particles, which is linked to the solubility and bioavailability of iron.

Over the first phase of the project, EVS and collaborators have performed beamline tests on more than a hundred dust samples provided by university collaborators from Rutgers, Georgia Tech, Amity University, University of Hawaii, and University of Paris. These samples were collected from seven locations: the Southern Ocean, the Mediterranean, the Atlantic Ocean, Hawaii, Bermuda, Patagonia, and India. They represent a wide range of dust aerosol characteristics from different source regions and remote oceans. To date, we have analyzed the chemical information for a few hundred individual dust particles.

The focus of our current data analysis is the Saharan dust dataset, which includes aerosol samples collected at sites located in the Mediterranean, the Atlantic Ocean, and Bermuda. This dataset characterizes aerosol iron at different stages of atmospheric dust aerosol transport, as reflected in the wide range of observed iron solubility (from 0.41% to 8.9%) across the Atlantic Ocean. Iron solubility is also found to be higher in “aged” dust particles collected from the Atlantic Ocean and Bermuda, but with lower concentrations than the Mediterranean dust collected near Sahara. Nearly half of the aerosol iron in the Bermuda samples is made of iron sulfates, a minor component in original Sahara dust, and the formation of these iron sulfates has been shown to significantly enrich iron solubility. More importantly, strong evidence of reductive iron transformation is found in these samples, as well as indicators of the proton-induced reactions that are typically considered in atmospheric models. Because iron reduction reactions occur in different environments from acid processing, our study highlights the importance of modeling the reductive mechanism to capture variations in dust iron dissolution. A manuscript on the main findings of this study has been prepared for submission to the journal Geophysical Research Letters in 2015.

The next phase of the project is to investigate the role of various iron dissolution schemes using model sensitivity studies. We have set up the latest Community Atmosphere Model version 5 (CAM5), which is the atmospheric component of the Community Earth System Model, on the ALCF Blue Gene/Q test and development platform, Vesta. Eight different dust minerals (illite, kaolinite, montmorillonite, hematite, quartz, calcite, feldspar, and gypsum), each with a unique set of physical and chemical properties, have been added to the CAM5 model and will be compared with the chemical information derived from the previous observational data analysis. In addition, we have upgraded the model with a new dust emission scheme. Currently, we are test-running this new development version of CAM5, implemented with the added multiple dust mineral tracers.

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photo of Yan Feng
Atmospheric and Climate Scientist
Capabilities: Global and regional modeling of atmospheric aerosols and impacts on climate; development and evaluation of aerosol schemes for Earth System Models; multi-scale modeling of cloud processes; air quality modeling; satellite data analyses; boundary layer meteorology for wind energy forecasting.