Mapping the drivers of uncertainty in atmospheric selenium deposition with global sensitivity analysis

Abstract

<p><strong>Abstract.</strong> An estimated 0.5–1 billion people globally have inadequate intakes of selenium (Se), due to a lack of bioavailable Se in agricultural soils. Deposition from the atmosphere, especially through precipitation, is an important source of Se to soils. However, very little is known about the atmospheric cycling of Se. It has therefore been difficult to predict how far Se travels in the atmosphere and where it deposits. To answer these questions, we have built the first global atmospheric Se model by implementing Se chemistry into an aerosol–chemistry–climate model, SOCOL-AER. In the model, we include information from the literature about the emissions, speciation, and chemical transformation of atmospheric Se. Natural processes and anthropogenic activities emit volatile Se compounds, which oxidize quickly and partition to the particulate phase. Our model tracks the transport and deposition of Se in 7 gas-phase species and 41 aerosol tracers. However, there are large uncertainties associated with many of the model's input parameters. In order to identify which model uncertainties are the most important for understanding the atmospheric Se cycle, we conducted a global sensitivity analysis with 34 input parameters related to Se chemistry, Se emissions, and the interaction of Se with aerosols. In the first bottom-up estimate of its kind, we have calculated a median global atmospheric lifetime of 4.4 d (days), ranging from 2.9–6.4 d (2<sup>nd</sup>–98<sup>th</sup> percentile) given the uncertainties of the input parameters. The uncertainty in the Se lifetime is mainly driven by the uncertainty in the carbonyl selenide (OCSe) oxidation rate and the lack of tropospheric aerosol species other than sulfate aerosols in SOCOL-AER. In contrast to uncertainties in Se lifetime, the uncertainty in deposition flux maps are governed by Se emission factors, with all four Se sources (volcanic, marine biosphere, terrestrial biosphere, and anthropogenic emissions) contributing equally to the uncertainty in deposition over agricultural areas. We evaluated the simulated Se wet deposition fluxes from SOCOL-AER with a compiled database of rainwater Se measurements, since wet deposition contributes around 80 % of total Se deposition. Despite difficulties in comparing a global, coarse resolution model with local measurements from a range of time periods, past Se wet deposition measurements are within the range of the model's 2<sup>nd</sup>–98<sup>th</sup> percentile at 79 % of background sites. This agreement validates the application of the SOCOL-AER model to identifying regions which are at risk of low atmospheric Se inputs. In order to constrain the uncertainty in Se deposition fluxes over agricultural soils we should prioritize field campaigns measuring Se emissions, rather than laboratory measurements of Se rate constants.</p>

Selenium concentration in herring from the Baltic Sea tracks decadal and spatial trends in external sources

“…We obtain Se deposition estimates from the aerosol-chemistryclimate model SOCOL-AERv2 33 that tracks Se emissions, atmospheric transport, and gaseous and particulate chemistry. 34 A detailed model description can be found in Feinberg et al 34,35 In the model, emitted volatile Se species are oxidized into low volatility compounds that partition to the aerosol phase. The SOCOL-AER model tracks the sulfate particle size distribution in 40 size bins between 0.39 nm and 3.2 mm, and the Se content of each sulfate aerosol bin.…”

“…Model simulations are nudged towards ERA-Interim 39 surface pressure, temperature, vorticity, and divergence elds to increase the similarity between modelled and observed meteorology. The model is run with Se emission inventories developed in Feinberg et al 34,35 for four source categories: anthropogenic activities, marine biosphere, terrestrial biosphere, and volcanos. The Se emission inventories are scaled from the spatial distribution of existing sulfur emission inventories, [40][41][42][43] with global scaling factors for each source type based on the median estimates from a Bayesian inversion.…”

Sulfur Amino Acid Status Controls Selenium Methylation in Pseudomonas tolaasii: Identification of a Novel Metabolite from Promiscuous Enzyme Reactions

“…"Bottom up" and "top down" approaches have shown considerable differences (~factor 2 in Se fluxes) in global atmospheric emissions (49). Uncertainty in Se deposition maps in "top down" approaches mainly arose from uncertainties in global emission fluxes because of the high variability of past flux measurements (55). Furthermore, the spatial distribution of terrestrial Se emissions is largely unknown (49).…”

Radioactive selenium: origin and environmental dispersion scenarios

“…Given the long half-life of the expected Se radioactive releases, 79 Se may eventually reach the ocean and, further, cycle several times within the biogeochemical cycle of Se in accordance with its nutrient-like behaviour (Cutter & Cutter, 1995). Radioactive Se may also transfer to the atmosphere when methylation processes are favoured within estuaries or in the ocean (e.g., Amouroux & Donard, 1997;Feinberg et al, 2020).…”

“…Microorganisms can also produce nano-elemental Se from Se(IV) under relatively oxic conditions (Bajaj et al, 2012). Potential biomethylation processes in soils due to microbial communities would also favour a transfer of radioactive, methylated Se species to the atmosphere (Feinberg et al, 2020), with the consequent dispersion of the corresponding radioactivity (expected to be very low, Section 2.4.2.3).…”