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    Application of TXRF in monitoring trace metals in particulate matter and cloud water
    (Katlenburg-Lindau : Copernicus, 2020) Fomba, Khanneh Wadinga; Deabji, Nabil; Barcha, Sayf El Islam; Ouchen, Ibrahim; Elbaramoussi, El Mehdi; El Moursli, Rajaa Cherkaoui; Harnafi, Mimoun; El Hajjaji, Souad; Mellouki, Abdelwahid; Herrmann, Hartmut
    Trace metals in ambient particulate matter and cloud are considered key elements of atmospheric processes as they affect air quality, environmental ecosystems, and cloud formation. However, they are often available at trace concentrations in these media such that their analysis requires high-precision and sensitive techniques. In this study, different analytical methods were applied to quantify trace metals in particulate matter (PM) samples collected on quartz and polycarbonate filters as well as cloud water, using the Total reflection X-Ray Fluorescence (TXRF) technique. These methods considered the measurement of filter samples directly without and with chemical pretreatment. Direct measurements involved the analysis of PM samples collected on polycarbonate filters and cloud water samples after they are brought onto TXRF carrier substrates. The chemical treatment method involved the assessment of different acid digestion procedures on PM sampled on quartz filters. The solutions applied were reverse aqua regia, nitric acid, and a combination of nitric acid and hydrogen peroxide. The effect of cold-plasma treatment of samples on polycarbonate filters before TXRF measurements was also investigated. Digestion with the reverse aqua regia solution provided lower blanks and higher recovery in comparison to other tested procedures. The detection limits of the elements ranged from 0.3 to 44 ng cm−2. Ca, K, Zn, and Fe showed the highest detection limits of 44, 35, 6, and 1 ng cm−2, while As and Se had the lowest of 0.3 and 0.8 ng cm−2, respectively. The method showed higher recovery for most trace metals when applied to commercially available reference materials and field samples. TXRF measurements showed good agreement with results obtained from ion chromatography measurements for elements such as Ca and K. Cold-plasma treatment did not significantly lead to an increase in the detected concentration, and the results were element specific. Baking of the quartz filters prior to sampling showed a reduction of more than 20 % of the filter blanks for elements such as V, Sr, Mn, Zn, and Sb. The methods were applied successfully on ambient particulate matter and cloud water samples collected from the Atlas Mohammed V station in Morocco and the Cape Verde Atmospheric Observatory. The obtained concentrations were within the range reported using different techniques from similar remote and background regions elsewhere, especially for elements of anthropogenic origins such as V, Pb, and Zn with concentrations of up to 10, 19, and 28 ng m−3, respectively. Enrichment factor analysis indicated that crustal matter dominated the abundance of most of the elements, while anthropogenic activities also contributed to the abundance of elements such as Sb, Se, and Pb. The results confirm that TXRF is a useful complementary sensitive technique for trace metal analysis of particulate matter in the microgram range as well as in cloud water droplets.
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    Characterization and source apportionment of organic aerosol using offline aerosol mass spectrometry
    (Katlenburg-Lindau : Copernicus, 2016) Daellenbach, K.R.; Bozzetti, C.; Křepelová, A.; Canonaco, F.; Wolf, R.; Zotter, P.; Fermo, P.; Crippa, M.; Slowik, J.G.; Sosedova, Y.; Zhang, Y.; Huang, R.-J.; Poulain, L.; Szidat, S.; Baltensperger, U.; El Haddad, I.; Prévôt, A.S.H.
    Field deployments of the Aerodyne Aerosol Mass Spectrometer (AMS) have significantly advanced real-time measurements and source apportionment of non-refractory particulate matter. However, the cost and complex maintenance requirements of the AMS make its deployment at sufficient sites to determine regional characteristics impractical. Furthermore, the negligible transmission efficiency of the AMS inlet for supermicron particles significantly limits the characterization of their chemical nature and contributing sources. In this study, we utilize the AMS to characterize the water-soluble organic fingerprint of ambient particles collected onto conventional quartz filters, which are routinely sampled at many air quality sites. The method was applied to 256 particulate matter (PM) filter samples (PM1, PM2.5, and PM10, i.e., PM with aerodynamic diameters smaller than 1, 2.5, and 10 µm, respectively), collected at 16 urban and rural sites during summer and winter. We show that the results obtained by the present technique compare well with those from co-located online measurements, e.g., AMS or Aerosol Chemical Speciation Monitor (ACSM). The bulk recoveries of organic aerosol (60–91 %) achieved using this technique, together with low detection limits (0.8 µg of organic aerosol on the analyzed filter fraction) allow its application to environmental samples. We will discuss the recovery variability of individual hydrocarbon ions, ions containing oxygen, and other ions. The performance of such data in source apportionment is assessed in comparison to ACSM data. Recoveries of organic components related to different sources as traffic, wood burning, and secondary organic aerosol are presented. This technique, while subjected to the limitations inherent to filter-based measurements (e.g., filter artifacts and limited time resolution) may be used to enhance the AMS capabilities in measuring size-fractionated, spatially resolved long-term data sets.
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    The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500
    (Katlenburg-Lindau : Copernicus, 2020) Meinshausen, Malte; Nicholls, Zebedee R. J.; Lewis, Jared; Gidden, Matthew J.; Vogel, Elisabeth; Freund, Mandy; Beyerle, Urs; Gessner, Claudia; Nauels, Alexander; Bauer, Nico; Canadell, Josep G.; Daniel, John S.; John, Andrew; Krummel, Paul B.; Luderer, Gunnar; Meinshausen, Nicolai; Montzka, Stephen A.; Rayner, Peter J.; Reimann, Stefan; Smith, Steven J.; van den Berg, Marten; Velders, Guus J. M.; Vollmer, Martin K.; Wang, Ray H. J.
    Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other.
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    On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions
    (Katlenburg-Lindau : Copernicus, 2022) Weger, Michael; Baars, Holger; Gebauer, Henriette; Merkel, Maik; Wiedensohler, Alfred; Heinold, Bernd
    There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. In this paper, CAIRDIO is applied on the simulation of black carbon and particulate matter dispersion for an entire mid-size city using a uniform horizontal grid spacing of 40gm. For model evaluation, measurements from five operational air monitoring stations representative for the urban background and high-traffic roads are used. The comparison also includes the mesoscale host simulation, which provides the boundary conditions. The measurements show a dominant influence of the mixing layer evolution at background sites, and therefore both the mesoscale and large-eddy simulation (LES) results are in good agreement with the observed air pollution levels. In contrast, at the high-traffic sites the proximity to emissions and the interactions with the building environment lead to a significantly amplified diurnal variability in pollutant concentrations. These urban road conditions can only be reasonably well represented by CAIRDIO while the meosocale simulation indiscriminately reproduces a typical urban-background profile, resulting in a large positive model bias. Remaining model discrepancies are further addressed by a grid-spacing sensitivity study using offline-nested refined domains. The results show that modeled peak concentrations within street canyons can be further improved by decreasing the horizontal grid spacing down to 10gm, but not beyond. Obviously, the default grid spacing of 40gm is too coarse to represent the specific environment within narrow street canyons. The accuracy gains from the grid refinements are still only modest compared to the remaining model error, which to a large extent can be attributed to uncertainties in the emissions. Finally, the study shows that the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. The results, however, also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.