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- ItemCloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China – Part 1: Size-resolved measurements and implications for the modeling of aerosol particle hygroscopicity and CCN activity(München : European Geopyhsical Union, 2010) Rose, D.; Nowak, A.; Achtert, P.; Wiedensohler, A.; Hu, M.; Shao, M.; Zhang, Y.; Andreae, M.O.Atmospheric aerosol particles serving as Cloud Condensation Nuclei (CCN) are key elements of the hydrological cycle and climate. We measured and characterized CCN in polluted air and biomass burning smoke during the PRIDE-PRD2006 campaign from 1–30 July 2006 at a rural site ~60 km northwest of the mega-city Guangzhou in southeastern China. CCN efficiency spectra (activated fraction vs. dry particle diameter; 20–290 nm) were recorded at water vapor supersaturations (S) in the range of 0.068% to 1.27%. The corresponding effective hygroscopicity parameters describing the influence of particle composition on CCN activity were in the range of κ≈0.1–0.5. The campaign average value of κ=0.3 equals the average value of κ for other continental locations. During a strong local biomass burning event, the average value of κ dropped to 0.2, which can be considered as characteristic for freshly emitted smoke from the burning of agricultural waste. At low S (≤0.27%), the maximum activated fraction remained generally well below one, indicating substantial portions of externally mixed CCN-inactive particles with much lower hygroscopicity – most likely soot particles (up to ~60% at ~250 nm). The mean CCN number concentrations (NCCN,S) ranged from 1000 cm−3 at S=0.068% to 16 000 cm−3 at S=1.27%, which is about two orders of magnitude higher than in pristine air. Nevertheless, the ratios between CCN concentration and total aerosol particle concentration (integral CCN efficiencies) were similar to the ratios observed in pristine continental air (~6% to ~85% at S=0.068% to 1.27%). Based on the measurement data, we have tested different model approaches for the approximation/prediction of NCCN,S. Depending on S and on the model approach, the relative deviations between observed and predicted NCCN,S ranged from a few percent to several hundred percent. The largest deviations occurred at low S with a simple power law. With a Köhler model using variable κ values obtained from individual CCN efficiency spectra, the relative deviations were on average less than ~10% and hardly exceeded 20%, confirming the applicability of the κ-Köhler model approach for efficient description of the CCN activity of atmospheric aerosols. Note, however, that different types of κ-parameters must be distinguished for external mixtures of CCN-active and -inactive aerosol particles (κa, κt, κcut). Using a constant average hygroscopicity parameter (κ=0.3) and variable size distributions as measured, the deviations between observed and predicted CCN concentrations were on average less than 20%. In contrast, model calculations using variable hygroscopicity parameters as measured and constant size distributions led to much higher deviations: ~70% for the campaign average size distribution, ~80% for a generic rural size distribution, and ~140% for a generic urban size distribution. These findings confirm earlier studies suggesting that aerosol particle number and size are the major predictors for the variability of the CCN concentration in continental boundary layer air, followed by particle composition and hygroscopicity as relatively minor modulators. Depending on the required and applicable level of detail, the information and parameterizations presented in this study should enable efficient description of the CCN activity of atmospheric aerosols in detailed process models as well as in large-scale atmospheric and climate models.
- ItemCloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China – Part 2: Size-resolved aerosol chemical composition, diurnal cycles, and externally mixed weakly CCN-active soot particles(München : European Geopyhsical Union, 2011) Rose, D.; Gunthe, S.S.; Su, H.; Garland, R.M.; Yang, H.; Berghof, M.; Cheng, Y.F.; Wehner, B.; Achtert, P.; Nowak, A.; Wiedensohler, A.; Takegawa, N.; Kondo, Y.; Hu, M.; Zhang, Y.; Andreae, M.O.; Pöschl, U.Size-resolved chemical composition, mixing state, and cloud condensation nucleus (CCN) activity of aerosol particles in polluted mega-city air and biomass burning smoke were measured during the PRIDE-PRD2006 campaign near Guangzhou, China, using an aerosol mass spectrometer (AMS), a volatility tandem differential mobility analyzer (VTDMA), and a continuous-flow CCN counter (DMT-CCNC). The size-dependence and temporal variations of the effective average hygroscopicity parameter for CCN-active particles (κa) could be parameterized as a function of organic and inorganic mass fractions (forg, finorg) determined by the AMS: κa,p=κorg·forg + κinorg·finorg. The characteristic κ values of organic and inorganic components were similar to those observed in other continental regions of the world: κorg≈0.1 and κinorg≈0.6. The campaign average κa values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while forg decreased with particle size. At ~50 nm, forg was on average 60% and increased to almost 100% during a biomass burning event. The VTDMA results and complementary aerosol optical data suggest that the large fractions of CCN-inactive particles observed at low supersaturations (up to 60% at S≤0.27%) were externally mixed weakly CCN-active soot particles with low volatility (diameter reduction <5% at 300 °C) and effective hygroscopicity parameters around κLV≈0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (κt) could be parameterized as a function of κa,p and the number fraction of low volatility particles determined by VTDMA (φLV): κt,p=κa,p−φLV·(κa,p−κLV). Based on κ values derived from AMS and VTDMA data, the observed CCN number concentrations (NCCN,S≈102–104 cm−3 at S = 0.068–0.47%) could be efficiently predicted from the measured particle number size distribution. The mean relative deviations between observed and predicted CCN concentrations were ~10% when using κt,p, and they increased to ~20% when using only κa,p. The mean relative deviations were not higher (~20%) when using an approximate continental average value of κ≈0.3, although the constant κ value cannot account for the observed temporal variations in particle composition and mixing state (diurnal cycles and biomass burning events). Overall, the results confirm that on a global and climate modeling scale an average value of κ≈0.3 can be used for approximate predictions of CCN number concentrations in continental boundary layer air when aerosol size distribution data are available without information about chemical composition. Bulk or size-resolved data on aerosol chemical composition enable improved CCN predictions resolving regional and temporal variations, but the composition data need to be highly accurate and complemented by information about particle mixing state to achieve high precision (relative deviations <20%).
- ItemModeling the global emission, transport and deposition of trace elements associated with mineral dust(München : European Geopyhsical Union, 2015) Zhang, Y.; Mahowald, N.; Scanza, R.A.; Journet, E.; Desboeufs, K.; Albani, S.; Kok, J.F.; Zhuang, G.; Chen, Y.; Cohen, D.D.; Paytan, A.; Patey, M.D.; Achterberg, E.P.; Engelbrecht, J.P.; Fomba, K.W.Trace element deposition from desert dust has important impacts on ocean primary productivity, the quantification of which could be useful in determining the magnitude and sign of the biogeochemical feedback on radiative forcing. However, the impact of elemental deposition to remote ocean regions is not well understood and is not currently included in global climate models. In this study, emission inventories for eight elements primarily of soil origin, Mg, P, Ca, Mn, Fe, K, Al, and Si are determined based on a global mineral data set and a soil data set. The resulting elemental fractions are used to drive the desert dust model in the Community Earth System Model (CESM) in order to simulate the elemental concentrations of atmospheric dust. Spatial variability of mineral dust elemental fractions is evident on a global scale, particularly for Ca. Simulations of global variations in the Ca / Al ratio, which typically range from around 0.1 to 5.0 in soils, are consistent with observations, suggesting that this ratio is a good signature for dust source regions. The simulated variable fractions of chemical elements are sufficiently different; estimates of deposition should include elemental variations, especially for Ca, Al and Fe. The model results have been evaluated with observations of elemental aerosol concentrations from desert regions and dust events in non-dust regions, providing insights into uncertainties in the modeling approach. The ratios between modeled and observed elemental fractions range from 0.7 to 1.6, except for Mg and Mn (3.4 and 3.5, respectively). Using the soil database improves the correspondence of the spatial heterogeneity in the modeling of several elements (Ca, Al and Fe) compared to observations. Total and soluble dust element fluxes to different ocean basins and ice sheet regions have been estimated, based on the model results. The annual inputs of soluble Mg, P, Ca, Mn, Fe and K associated with dust using the mineral data set are 0.30 Tg, 16.89 Gg, 1.32 Tg, 22.84 Gg, 0.068 Tg, and 0.15 Tg to global oceans and ice sheets.
- ItemCharacterization 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.
- ItemAssessment of the MACC reanalysis and its influence as chemical boundary conditions for regional air quality modeling in AQMEII-2(Amsterdam : Elsevier, 2015) Giordano, L.; Brunner, D.; Flemming, J.; Hogrefe, C.; Im, U.; Bianconi, R.; Badia, A.; Balzarini, A.; Baró, R.; Hirtl, M.; Honzak, L.; Jorba, O.; Knote, C.; Kuenen, J.J.P.; Makar, P.A.; Manders-Groot, A.; Neal, L.; Pérez, J.L.; Pirovano, G.; Pouliot, G.; San José, R.; Savage, N.; Schröder, W.; Sokhi, R.S.; Syrakov, D.; Torian, A.; Tuccella, P.; Werhahn, J.; Wolke, R.; Yahya, K.; Žabkar, R.; Zhang, Y.; Galmarini, S.The Air Quality Model Evaluation International Initiative (AQMEII) has now reached its second phase which is dedicated to the evaluation of online coupled chemistry-meteorology models. Sixteen modeling groups from Europe and five from North America have run regional air quality models to simulate the year 2010 over one European and one North American domain. The MACC re-analysis has been used as chemical initial (IC) and boundary conditions (BC) by all participating regional models in AQMEII-2. The aim of the present work is to evaluate the MACC re-analysis along with the participating regional models against a set of ground-based measurements (O3, CO, NO, NO2, SO2, SO42−) and vertical profiles (O3 and CO). Results indicate different degrees of agreement between the measurements and the MACC re-analysis, with an overall better performance over the North American domain. The influence of BC on regional air quality simulations is analyzed in a qualitative way by contrasting model performance for the MACC re-analysis with that for the regional models. This approach complements more quantitative approaches documented in the literature that often have involved sensitivity simulations but typically were limited to only one or only a few regional scale models. Results suggest an important influence of the BC on ozone for which the underestimation in winter in the MACC re-analysis is mimicked by the regional models. For CO, it is found that background concentrations near the domain boundaries are rather close to observations while those over the interior of the two continents are underpredicted by both MACC and the regional models over Europe but only by MACC over North America. This indicates that emission differences between the MACC re-analysis and the regional models can have a profound impact on model performance and points to the need for harmonization of inputs in future linked global/regional modeling studies.