70 research outputs found

    Microbiology and atmospheric processes: chemical interactions of primary biological aerosols

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    This paper discusses the influence of primary biological aerosols (PBA) on atmospheric chemistry and vice versa through microbiological and chemical properties and processes. Several studies have shown that PBA represent a significant fraction of air particulate matter and hence affect the microstructure and water uptake of aerosol particles. Moreover, airborne micro-organisms, namely fungal spores and bacteria, can transform chemical constituents of the atmosphere by metabolic activity. Recent studies have emphasized the viability of bacteria and metabolic degradation of organic substances in cloud water. On the other hand, the viability and metabolic activity of airborne micro-organisms depend strongly on physical and chemical atmospheric parameters such as temperature, pressure, radiation, pH value and nutrient concentrations. In spite of recent advances, however, our knowledge of the microbiological and chemical interactions of PBA in the atmosphere is rather limited. Further targeted investigations combining laboratory experiments, field measurements, and modelling studies will be required to characterize the chemical feedbacks, microbiological activities at the air/snow/water interface supplied to the atmosphere

    Atmospheric processing outside clouds increases soluble iron in mineral dust

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    Iron (Fe) is a key micronutrient regulating primary productivity in many parts of the global ocean. Dust deposition is an important source of Fe to the surface ocean, but most of this Fe is biologically unavailable. Atmospheric processing and reworking of Fe in dust aerosol can increase the bioavailable Fe inputs to the ocean, yet the processes are not well understood. Here, we experimentally simulate and model the cycling of Fe-bearing dust between wet aerosol and cloud droplets. Our results show that insoluble Fe in dust particles readily dissolves under acidic conditions relevant to wet aerosols. By contrast, under the higher pH conditions generally relevant to clouds, Fe dissolution tends to stop, and dissolved Fe precipitates as poorly crystalline nanoparticles. If the dust-bearing cloud droplets evaporated again (returning to the wet aerosol stage with low pH), those neo-formed Fe nanoparticles quickly redissolve, while the refractory Fe-bearing phases continue to dissolve gradually. Overall, the duration of the acidic, wet aerosol stage ultimately increases the amount of potentially bioavailable Fe delivered to oceans, while conditions in clouds favor the formation of Fe-rich nanoparticles in the atmosphere

    Bayesian Monte Carlo analysis applied to regional-scale inverse emission modeling for reactive trace gases

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    International audience[1] The purpose of this article is inverse modeling of emissions at regional scale for photochemical applications. The study is performed for the Ile-de-France region over a two summers (1998 and 1999) period. This area represents an ideal framework since concentrated anthropogenic emissions in the Paris region frequently lead to the formation of urban plumes. The inversion method is based on Bayesian Monte Carlo analysis applied to a regional-scale chemistry transport model, CHIMERE. This method consists in performing a large number of successive simulations with the same model but with a distinct set of model input parameters at each time. Then a posteriori weights are attributed to individual Monte Carlo simulations by comparing them with observations from the AIRPARIF network: urban NO and O 3 concentrations and rural O 3 concentrations around the Paris area. For both NO and O 3 measurements, observations used for constraining Monte Carlo simulations are additionally averaged over the time period considered for analysis. The observational constraints strongly reduce the a priori uncertainties in anthropogenic NOx and volatile organic compounds (VOC) emissions: (1) The a posteriori probability density function (pdf) for NOx emissions is not modified in its average, but the standard deviation is decreased to around 20% (40% for the a priori one). (2) VOC emissions are enhanced (+16%) in the a posteriori pdf's with a standard deviation around 30% (40% for the a priori one). Uncertainties in the simulated urban NO, urban O 3 , and O 3 production within the plume are reduced by a factor of 3.2, 2.4, and 1.7, respectively. Citation: Deguillaume, L., M. Beekmann, and L. Menut (2007), Bayesian Monte Carlo analysis applied to regional-scale inverse emission modeling for reactive trace gases

    Evaluation of Cloud Chemistry Mechanism Towards Laboratory Experiments

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    Metagenomic and metatranscriptomic analysis for the study of clouds and aerosols.

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    H<sub>2</sub>O<sub>2</sub> modulates the energetic metabolism of the cloud microbiome

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    Chemical reactions in clouds lead to oxidation processes driven by radicals (mainly HO⚫, NO3⚫, or HO2⚫) or strong oxidants such as H2O2, O3, nitrate, and nitrite. Among those species, hydrogen peroxide plays a central role in the cloud chemistry by driving its oxidant capacity. In cloud droplets, H2O2 is transformed by microorganisms which are metabolically active. Biological activity can therefore impact the cloud oxidant capacity. The present article aims at highlighting the interactions between H2O2 and microorganisms within the cloud system. First, experiments were performed with selected strains studied as a reference isolated from clouds in microcosms designed to mimic the cloud chemical composition, including the presence of light and iron. Biotic and abiotic degradation rates of H2O2 were measured and results showed that biodegradation was the most efficient process together with the photo-Fenton process. H2O2 strongly impacted the microbial energetic state as shown by adenosine triphosphate (ATP) measurements in the presence and absence of H2O2. This ATP depletion was not due to the loss of cell viability. Secondly, correlation studies were performed based on real cloud measurements from 37 cloud samples collected at the PUY station (1465 m a.s.l., France). The results support a strong correlation between ATP and H2O2 concentrations and confirm that H2O2 modulates the energetic metabolism of the cloud microbiome. The modulation of microbial metabolism by H2O2 concentration could thus impact cloud chemistry, in particular the biotransformation rates of carbon compounds, and consequently can perturb the way the cloud system is modifying the global atmospheric chemistry

    Clouds as atmospheric oases for microorganisms.

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