Search

Atmospheric deposition is a source of potentially bioavailable iron (Fe) and thus can partially control biological productivity in large parts of the ocean. However, the explanation of observed high aerosol Fe solubility compared to that in soil particles is still controversial, as several hypotheses have been proposed to explain this observation. Here, a statistical analysis of aerosol Fe solubility estimated from four models and observations compiled from multiple field campaigns suggests that pyrogenic aerosols are the main sources of aerosols with high Fe solubility at low concentration. Additionally, we find that field data over the Southern Ocean display a much wider range in aerosol Fe solubility compared to the models, which indicate an underestimation of labile Fe concentrations by a factor of 15. These findings suggest that pyrogenic Fe-containing aerosols are important sources of atmospheric bioavailable Fe to the open ocean and crucial for predicting anthropogenic perturbations to marine productivity.

Abstract. This work reports on the current status of the global modeling of iron (Fe)deposition fluxes and atmospheric concentrations and the analyses of thedifferences between models, as well as between models and observations. Atotal of four global 3-D chemistry transport (CTMs) and general circulation(GCMs) models participated in this intercomparison, in the framework ofthe United Nations Joint Group of Experts on the Scientific Aspects of MarineEnvironmental Protection (GESAMP) Working Group 38, “The Atmospheric Inputof Chemicals to the Ocean”. The global total Fe (TFe) emission strength inthe models is equal to ∼72 Tg Fe yr−1 (38–134 Tg Fe yr−1)from mineral dust sources and around 2.1 Tg Fe yr−1 (1.8–2.7 Tg Fe yr−1)from combustion processes (the sum of anthropogeniccombustion/biomass burning and wildfires). The mean global labile Fe (LFe)source strength in the models, considering both the primary emissions and theatmospheric processing, is calculated to be 0.7 (±0.3) Tg Fe yr−1,accounting for both mineral dust and combustion aerosols. Themean global deposition fluxes into the global ocean are estimated to be in the rangeof 10–30 and 0.2–0.4 Tg Fe yr−1 for TFe and LFe, respectively,which roughly corresponds to a respective 15 and 0.3 Tg Fe yr−1 for the multi-model ensemble model mean. The model intercomparison analysis indicates that the representation of theatmospheric Fe cycle varies among models, in terms of both the magnitude ofnatural and combustion Fe emissions as well as the complexity of atmosphericprocessing parameterizations of Fe-containing aerosols. The model comparisonwith aerosol Fe observations over oceanic regions indicates that most modelsoverestimate surface level TFe mass concentrations near dust sourceregions and tend to underestimate the low concentrations observed in remoteocean regions. All models are able to simulate the tendency of higher Feconcentrations near and downwind from the dust source regions, with the meannormalized bias for the Northern Hemisphere (∼14), largerthan that of the Southern Hemisphere (∼2.4) for the ensemble modelmean. This model intercomparison and model–observation comparison studyreveals two critical issues in LFe simulations that require furtherexploration: (1) the Fe-containing aerosol size distribution and (2) therelative contribution of dust and combustion sources of Fe to labile Fe inatmospheric aerosols over the remote oceanic regions.

Assessing aerosol mixing states, which primarily depend on aerosol chemical compositions, is indispensable to estimate direct and indirect effects of aerosols. The limitations of the direct measurements of aerosol chemical composition and mixing states necessitate modeling approaches to infer the aerosol mixing states. The Optical Properties of Aerosols and Clouds (OPAC) model has been extensively utilized to construct optically equivalent aerosol chemical compositions from measured aerosol optical properties using Mie inversion. However, the representation of real atmospheric aerosol mixing scenarios in OPAC has perennially been challenged by the exclusive assumption of external mixing. A Python successor to the aerosol module of the OPAC model is developed, named AeroMix, with novel capabilities to (1) model externally and core–shell mixed aerosols, (2) simulate optical properties of aerosol mixtures constituted by any number of aerosol components, and (3) define aerosol composition and relative humidity in up to six vertical layers. Designed as a versatile open-source aerosol optical model framework, AeroMix is tailored for sophisticated inversion algorithms aimed at modeling aerosol mixing states and also their physical and chemical properties. AeroMix's performance is demonstrated by modeling the probable aerosol mixing states over Kanpur (urban) and the Bay of Bengal (marine) in south Asia. The modeled mixing states are consistent with independent measurements using a single-particle soot photometer (SP2) and transmission electron microscopy (TEM), substantiating the potential capability of AeroMix to model complex aerosol mixing scenarios involving multiple internally mixed components in diverse environments. This work contributes a valuable tool for modeling aerosol mixing states to assess their impact on cloud-nucleating properties and radiation budget. [ABSTRACT FROM AUTHOR]

Assessing aerosol mixing states, which mainly depend on aerosol chemical compositions is indispensable to estimate aerosol direct and indirect effects. While the limitations in the measurements of aerosol chemical composition and mixing states persist globally, the Optical Properties of Aerosols and Clouds (OPAC) model has been widely used to construct optically equivalent aerosol chemical compositions from measured aerosol optical properties using Mie inversion. However, the representation of real atmospheric aerosol mixing scenarios in OPAC has perennially been challenged by the exclusive assumption of external mixing. A Python successor to the aerosol module of the OPAC model is developed, named 'AeroMix,' with novel capabilities to 1) model externally and core-shell mixed aerosols, 2) simulate optical properties of aerosol mixtures constituted by any number of aerosol components, 3) and define aerosol composition and relative humidity in up to 6 vertical layers. Designed as a versatile open-source aerosol optical model framework, AeroMix is tailored for sophisticated inversion algorithms aimed at modeling aerosol mixing states and also their physical and chemical properties. AeroMix's performance is demonstrated by modeling the probable aerosol mixing states over Kanpur (urban), India, and the Bay of Bengal (marine). The modeled mixing states are consistent with independent measurements using single-particle soot photometer (SP2) and transmission electron microscopy (TEM), substantiating the potential capability of AeroMix to model complex aerosol mixing scenarios involving multiple internally mixed components in diverse environments. This work contributes a valuable tool for modeling aerosol mixing states to assess their impact on cloud nucleating properties and radiation budget. [ABSTRACT FROM AUTHOR]

The continental outflow from the Indo-Gangetic Plain and Southeast Asia, during the late NE monsoon (January–March), dominates the transport of chemical constituents to the marine atmospheric boundary layer (MABL) of the Bay of Bengal (BoB). During the rest of the year, prevailing wind regimes and meteorological conditions do not favour the atmospheric transport of continental products. Here we report on the spatio-temporal variability of inorganic phosphorous (PInorg=PO3−4) in the MABL and its dry-deposition flux to the surface BoB. On the basis of the abundance of PInorg in PM2.5 (0.1–0.8 nmol m−3) and PM10 (0.3–2.8 nmol m−3), we document its dominant occurrence in the coarse mode (Da≥2.5 µm). The analytical data also provide evidence for the chemical processing of mineral dust by acidic species and mobilisation of PInorg during the long-range atmospheric transport. However, significantly high PInorg/non-sea-salt Ca2+ ratios over the BoB suggest dominant contribution from anthropogenic sources (fertilisers and biomass burning emissions). PInorg concentration over the Arabian Sea is about 4 to 5 times lower and is primarily associated with the mineral dust from desert regions. The dry-deposition flux of PInorg to the BoB varies by one order of magnitude (0.5–5.0 µmol P m−2 d−1; Av: 0.02 Tg P yr−1). These results have implications to the air-sea deposition of phosphorous over oceanic regions downwind of the pollution sources and impact on the biogeochemistry of surface waters.

The first field measurements of light absorbing water-soluble organic carbon (WSOC), referred as brown carbon (BrC), have been made in the marine atmospheric boundary layer (MABL) during the continental outflow to the Bay of Bengal (BoB) and the Arabian Sea (ARS). The absorption signal measured at 365 nm in aqueous extracts of aerosols shows a systematic linear increase with WSOC concentration, suggesting a significant contribution from BrC to the absorption properties of organic aerosols. The mass absorption coefficient ( b _abs ) of BrC shows an inverse hyperbolic relation with wavelength (from ∼300 to 700 nm), providing an estimate of the Angstrom exponent (α _P , range: 3–19; Av: 9 ± 3). The mass absorption efficiency of brown carbon (σ _abs−BrC ) in the MABL varies from 0.17 to 0.72 m ^2 g ^−1 (Av: 0.45 ± 0.14 m ^2 g ^−1 ). The α _P and σ _abs−BrC over the BoB are quite similar to that studied from a sampling site in the Indo-Gangetic Plain (IGP), suggesting the dominant impact of organic aerosols associated with the continental outflow. A comparison of the mass absorption efficiency of BrC and elemental carbon (EC) brings to focus the significant role of light absorbing organic aerosols (from biomass burning emissions) in atmospheric radiative forcing over oceanic regions located downwind of the pollution sources.