140 research outputs found

    How much soil dust aerosol is man-made?

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    Field observations of the variability of dust emission, its size-spectrum and mineralogy

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    Atmospheric mineral dust consists of tiny mineral particles that are produced by the wind erosion of arid and semi-arid surfaces of the Earth, and it is one of the most important aerosols in terms of mass in the global atmosphere [1]. The physical and chemical properties of dust, that is, its particle size distribution (PSD), mineralogical composition, shape and mixing state determine its impact on the Earth’s system. Dust mineralogy in particular has been identified by the Intergovernmental Panel on Climate Change (IPCC) as a key uncertainty in the overall contribution of aerosols to radiative forcing [2] and many studies over recent years have shown its potential importance [3,4]. Despite this, Earth System models typically assume dust aerosols to have a globally uniform composition, neglecting the known local and regional variations in the mineralogical composition of the sources [5,6] and therefore, preventing further understanding of the role of dust in the Earth system. However, this simplification is justified by the current incomplete understanding of the physical processes at emission, the lack of coincident measurements of individual mineral PSDs for emitted dust and the parent soil, the fundamental disagreements among existing dust emission schemes on multiple aspects, the limited global knowledge of soil mineral content and the insufficient knowledge of the mixing state of the minerals. The ERC Consolidator Grant called FRAGMENT (FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe) aims to address these limitations and to better understand and constrain the global mineralogical composition of dust along with its effects upon climate. This ambitious and multidisciplinary project combines theory, field measurements, laboratory analyses, remote spectroscopy and modelling

    Foreign and domestic contributions to surface ozone in Spain

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    Tropospheric ozone (O3) exerts strong adverse impacts on human health, climate, vegetation, biodiversity, agricultural crop yields and thus food security. O3 is formed in the atmosphere through non-linear photochemical reactions involving volatile organic compounds (VOCs) and nitrogen oxides (NOx) precursors [1]. Furthermore, meteorological stagnation, high solar radiation, high temperatures and low precipitation favor the formation of tropospheric O3 at surface levels exceeding target regulatory values [2]. Due to the complex and poorly constrained physico-chemical O3 formation and removal pathways, no straightforward strategies currently exist for reducing O3. Currently, there are no observational methods that differentiate the origin of O3. Despite their inherent uncertainties, chemical transport models (CTMs) allow for the apportionment of the contribution of any source to O3 concentrations. The mass-transfer source apportionment method is an optimal approach to study the contribution of different sources to ozone levels [2]. In this study, we provide a quantitative estimation of the foreign and domestic contributions to surface ozone on Spain, relative to European countries and the contribution of hemispheric background ozone. For that, we use the CMAQISAM within the CALIOPE air quality modelling system to simulate the O3 dynamics over Europe quantify national contributions for the ozone season from May to October in 2015. We tag both O3 and its precursors, NOx and VOCs, from the different European countries, all the way through their lifetime, from emission to deposition

    The atmospheric iron cycle in EC-earth

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    The ocean is known to act as an atmospheric carbon dioxide (CO2) sink. About a quarter of the CO2 emitted to the atmosphere since the industrial revolution, has been captured by the ocean [1]. The capacity of the ocean to capture CO2 highly depends on ocean productivity which relies upon bioavailable iron (Fe) for photosynthesis, respiration and nitrogen fixation [2]. Fe is in fact considered to be the limiting nutrient in some remote regions of the ocean known as high-nutrient low-chlorophyll (HNLC) [3]. Understanding and constraining the bio-available iron supply to the ocean is thus fundamental to be able to project future climate. Fe supply reaches the oceans mainly from rivers as suspended sediment. However, fluvial and glacial particulate Fe is restricted to near-coastal areas. Therefore, the dominant input of iron to open ocean surface is the deposition of atmospheric mineral dust emitted from arid and semiarid areas of the world. Another contributor to atmospheric Fe supply that is not always accounted for in models, is combustion, which main sources are anthropogenic combustion and biomass burning. Just a fraction of the deposited Fe over ocean can be used by marine biota as nutrient (bio-available). The assumption that soluble Fe can be considered as bio-available will be used here [4]. Freshly emitted Fe-dust is known to be mainly insoluble. Observations, modelling and laboratory studies suggest that the solubility of Fe-dust increases downwind of the sources due to different processes [5] [6]. On the other hand, although the total burden of emitted combustion Fe is known to be smaller than Fe-dust, combustion Fe at emission may be more soluble [7]

    HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 1: global and regional module

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    Abstract Back to top We present the High-Elective Resolution Modelling Emission System version 3 (HERMESv3), an open source, parallel and stand-alone multi-scale atmospheric emission modelling framework that computes gaseous and aerosol emissions for use in atmospheric chemistry models. HERMESv3 is coded in Python and consists of a global_regional module and a bottom_up module that can be either combined or executed separately. In this contribution (Part 1) we describe the global_regional module, a customizable emission processing system that calculates emissions from different sources, regions and pollutants on a user-specified global or regional grid. The user can flexibly define combinations of existing up-to-date global and regional emission inventories and apply country-specific scaling factors and masks. Each emission inventory is individually processed using user-defined vertical, temporal and speciation profiles that allow obtaining emission outputs compatible with multiple chemical mechanisms (e.g. Carbon-Bond 05). The selection and combination of emission inventories and databases is done through detailed configuration files providing the user with a widely applicable framework for designing, choosing and adjusting the emission modelling experiment without modifying the HERMESv3 source code. The generated emission fields have been successfully tested in different atmospheric chemistry models (i.e. CMAQ, WRF-Chem and NMMB-MONARCH) at multiple spatial and temporal resolutions. In a companion article (Part 2; Guevara et al., 2019) we describe the bottom_up module, which estimates emissions at the source level (e.g. road link) combining state-of-the-art bottom–up methods with local activity and emission factors.The research leading to these results has received funding from the Ministerio de EconomĂ­a y Competitividad (MINECO) as part of the PAISA project CGL2016-75725-R and the NUTRIENT project CGL2017-88911-R. The authors acknowledge PRACE for awarding access to Marenostrum4 based in Spain at the Barcelona Supercomputing Center through the Tier-0 HHRNTCP and Tier-0 EEDMC projects. Carlos PĂ©rez GarcĂ­a-Pando acknowledges long-term support from the AXA Research Fund, as well as the support received through the RamĂłn y Cajal programme (grant RYC-2015-18690) of the Spanish Ministry of Economy and Competitiveness. The authors would also like to thank the two anonymous referees for their thorough comments, which helped improve the quality of the paper.Peer ReviewedPostprint (published version

    HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – part 2: the bottom–up module

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    We describe the bottom–up module of the High-Elective Resolution Modelling Emission System version 3 (HERMESv3), a Python-based and multi-scale modelling tool intended for the processing and computation of atmospheric emissions for air quality modelling. HERMESv3 is composed of two separate modules: the global_regional module and the bottom_up module. In a companion paper (Part 1, Guevara et al., 2019a) we presented the global_regional module. The bottom_up module described in this contribution is an emission model that estimates anthropogenic emissions at high spatial- (e.g. road link level,) and temporal- (hourly) resolution using state-of-the-art calculation methods that combine local activity and emission factors along with meteorological data. The model computes bottom–up emissions from point sources, road transport, residential and commercial combustion, other mobile sources, and agricultural activities. The computed pollutants include the main criteria pollutants (i.e. NOx, CO, NMVOCs (non-methane volatile organic compounds), SOx, NH3, PM10 and PM2.5) and greenhouse gases (i.e. CO2 and CH4, only related to combustion processes). Specific emission estimation methodologies are provided for each source and are mostly based on (but not limited to) the calculation methodologies reported by the European EMEP/EEA air pollutant emission inventory guidebook. Meteorologically dependent functions are also included to take into account the dynamical component of the emission processes. The model also provides several functionalities for automatically manipulating and performing spatial operations on georeferenced objects (shapefiles and raster files). The model is designed so that it can be applicable to any European country or region where the required input data are available. As in the case of the global_regional module, emissions can be estimated on several user-defined grids, mapped to multiple chemical mechanisms and adapted to the input requirements of different atmospheric chemistry models (CMAQ, WRF-Chem and MONARCH) as well as a street-level dispersion model (R-LINE). Specific emission outputs generated by the model are presented and discussed to illustrate its capabilities.This research has been supported by the Ministerio de Ciencia, Innovación y Universidades (grant no. CGL2016-75725-R), the Ministerio de Ciencia, Innovación y Universidades (grant no. RTI2018-099894-B-I00), the Ministerio de Ciencia, Innovación y Universidades (grant no. RYC-2015-18690), and the AXA Research Fund (grant no. AXA Research Fund).Peer ReviewedPostprint (published version

    Multi-sectoral impact assessment of an extreme African dust episode in the Eastern Mediterranean in March 2018

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    In late March 2018, a large part of the Eastern Mediterranean experienced an extraordinary episode of African dust, one of the most intense in recent years, here referred to as the “Minoan Red” event. The episode mainly affected the Greek island of Crete, where the highest aerosol concentrations over the past 15 yeas were recorded, although impacts were also felt well beyond this core area. Our study fills a gap in dust research by assessing the multi-sectoral impacts of sand and dust storms and their socioeconomic implications. Specifically, we provide a multi-sectoral impact assessment of Crete during the occurrence of this exceptional African dust event. During the day of the occurrence of the maximum dust concentration in Crete, i.e. March 22nd, 2018, we identified impacts on meteorological conditions, agriculture, transport, energy, society (including closing of schools and cancellation of social events), and emergency response systems. As a result, the event led to a 3-fold increase in daily emergency responses compare to previous days associated with urban emergencies and wildfires, a 3.5-fold increase in hospital visits and admissions for Chronic Obstructive Pulmonary Disease (COPD) exacerbations and dyspnoea, a reduction of visibility causing aircraft traffic disruptions (eleven cancellations and seven delays), and a reduction of solar energy production. We estimate the cost of direct and indirect effects of the dust episode, considering the most affected socio-economic sectors (e.g. civil protection, aviation, health and solar energy production), to be between 3.4 and 3.8 million EUR for Crete. Since such desert dust transport episodes are natural, meteorology-driven and thus to a large extent unavoidable, we argue that the efficiency of actions to mitigate dust impacts depends on the accuracy of operational dust forecasting and the implementation of relevant early warning systems for social awareness.The authors gratefully acknowledge the COST Association for funding the COST Action inDust (CA16202) as well as the WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) and the ERA4CS DustClim and the AXA Research Fund for funding the AXA Chair on Sand and Dust Storms (hosted by the Barcelona Supercomputing Center). We thank the scientific team of the PROTEAS CSP facility for the feedback provided and T. Bojic and R. Burbidge for facilitating the access to the EUROCONTROL archive. We thank the scientific team of the PROTEAS CSP facility for providing DNI data for this case study. Thanks are due to FCT/MCTES for the financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020) through national funds, and also to the Icelandic Research Fund for the grant no. 207057-051. Authors S. Kazadzis and P. Kosmopoulos would like to acknowledge the European Commission project EuroGEO e-shape (grant agreement No 820852). Also, International Cooperative for Aerosol Prediction (ICAP) and NASA mission researchers are gratefully for providing aerosol data for this study. Aurelio Tobias was supported by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). S. Kutuzov acknowledges the Megagrant project (agreement No. 075-15-2021-599, 8.06.2021).Peer Reviewed"Article signat per 34 autors/es: Alexandra Monteiro, Sara Basart, Stelios Kazadzis, Athanasios Votzis, Antonis Gkikas, Sophie Vandenbussche, Aurelio Tobias, Carla Gama, Carlos PĂ©rez GarcĂ­a Pando, Enric Terradellas, George Notas, Nick Middleton, Jonilda Kushta, Vassilis Amiridis, Kostas Lagouvardos, Panagiotis Kosmopoulos, Vasiliki Kotroni, Maria Kanakidou, Nikos Mihalopoulos, Nikos Kalivitis, Pavla Dagsson-WaldhauserovĂĄ, Hesham El-Askary, Klaus Sievers, T. Giannaros, Lucia Mona, Marcus Hirt, Paul Skomorowski, Timo H.Virtanen, Theodoros Christoudias,, Biagio Di Mauro, Serena Trippetta, Stanislav Kutuzov, Outi Meinander, Slobodan Nickovic"Postprint (author's final draft

    Aerosol characterization in Northern Africa, Northeastern Atlantic, Mediterranean Basin and Middle East from direct-sun AERONET observations

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    We proviede an atmospheric aerosol characterization for North Africa, Northeastern Atlantic, Mediterranean and Middle East based on the analysis of quality-assured direct-sun observations of 39 stations of the AErosol RObotic NETwork (AERONET) which include at least an annual cycle within the 1994–2007 period. We extensively test and apply the recently introduced graphical method of Gobbi and co-authors to track and discriminate different aerosol types and quantify the contribution of mineral dust. The method relies on the combined analysis of the Ångström exponent (α) and its spectral curvature Ύα. Plotting data in these coordinates allows to infer aerosol fine mode radius (Rf) and fractional contribution (η) to total Aerosol Optical Depth (AOD) and separate AOD growth due to fine-mode aerosol humidification and/or coagulation from AOD growth due to the increase in coarse particles or cloud contamination. Our results confirm the robustness of this graphical method. Large mineral dust is found to be the most important constituent in Northern Africa and Middle East. Under specific meteorological conditions, its transport to Southern Europe is observed from spring to autumn and decreasing with latitude. We observe "pure Saharan dust" conditions to show AOD>0.7 (ranging up to 5), α1.5 and Ύα~−0.2 corresponding to η>70% and Rf~0.13 ÎŒm. Here, dust mixed with fine pollution aerosols shifts the observations to the region α<0.75, in which the fine mode contribution is less than 40%.Peer ReviewedPostprint (published version

    Monitoring the impact of desert dust outbreaks for air quality for health studies

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    We review the major features of desert dust outbreaks that are relevant to the assessment of dust impacts upon human health. Our ultimate goal is to provide scientific guidance for the acquisition of relevant population exposure information for epidemiological studies tackling the short and long term health effects of desert dust. We first describe the source regions and the typical levels of dust particles in regions close and far away from the source areas, along with their size, composition, and bio-aerosol load. We then describe the processes by which dust may become mixed with anthropogenic particulate matter (PM) and/or alter its load in receptor areas. Short term health effects are found during desert dust episodes in different regions of the world, but in a number of cases the results differ when it comes to associate the effects to the bulk PM, the desert dust-PM, or non-desert dust-PM. These differences are likely due to the different monitoring strategies applied in the epidemiological studies, and to the differences on atmospheric and emission (natural and anthropogenic) patterns of desert dust around the world. We finally propose methods to allow the discrimination of health effects by PM fraction during dust outbreaks, and a strategy to implement desert dust alert and monitoring systems for health studies and air quality management.The systematic review was funded by WHO with as part of a Grant Agreement with Ministry of Foreign Affairs, Norway. Thanks are also given to the Spanish Ministry for the Ecological Transition for long term support in the last 2 decades to our projects on African dust effects on air quality over Spain; to the Spanish Ministry of Science, Innovation and Universities and FEDER Funds for the HOUSE project (CGL2016-78594-R), and to the Generalitat de Catalunya (AGAUR 2017 SGR41). Carlos PĂ©rez GarcĂ­a-Pando acknowledges long-term support from the AXA Research Fund, as well as the support received through the RamĂłn y Cajal program (grant RYC-2015-18690) of the Spanish Ministry of Science, Innovation and Universities.Peer ReviewedPostprint (published version
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