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- ItemLong-term measurements of aerosol and carbon monoxide at the ZOTTO tall tower to characterize polluted and pristine air in the Siberian taiga(München : European Geopyhsical Union, 2013) Chi, X.; Winderlich, J.; Mayer, J.-C.; Panov, A.V.; Heimann, M.; Birmili, W.; Heintzenberg, J.; Cheng, Y.; Andreae, M.O.Siberia is one of few continental regions in the Northern Hemisphere where the atmosphere may sometimes approach pristine background conditions. We present the time series of aerosol and carbon monoxide (CO) measurements between September 2006 and December 2011 at the Zotino Tall Tower Observatory (ZOTTO) in Central Siberia (61° N; 89° E). We investigate the seasonal, weekly and diurnal variations of aerosol properties (including absorption and scattering coefficients and derived parameters, such as equivalent black carbon (BCe), Ångström exponent, single scattering albedo, and backscattering ratio) and the CO mixing ratios. Criteria were established to distinguish polluted from near-pristine air masses, providing quantitative characteristics for each type. Depending on the season, 23–36% of the sampling time at ZOTTO was found to be representative of a clean atmosphere. The summer pristine data indicate that primary biogenic and secondary organic aerosol formation are quite strong particle sources in the Siberian taiga. The summer seasons 2007–2008 were dominated by an Aitken mode around 80 nm size, whereas the summer 2009 with prevailing easterly winds produced particles in the accumulation mode around 200 nm size. We found these differences to be mainly related to air temperature, through its effect on the production rates of biogenic volatile organic compounds (VOC) precursor gases. In winter, the particle size distribution peaked at 160 nm, and the footprint of clean background air was characteristic for aged particles from anthropogenic sources at great distances from ZOTTO and diluted biofuel burning emissions from domestic heating. The wintertime polluted air originates mainly from large cities south and southwest of the site; these particles have a dominant mode around 100 nm, and the ΔBCe / ΔCO ratio of 7–11 ng m−3 ppb−1 suggests dominant contributions from coal and biofuel burning for heating. During summer, anthropogenic emissions are the dominant contributor to the pollution particles at ZOTTO, while only 12% of the polluted events are classified as biomass-burning-dominated, but then often associated with extremely high CO concentrations and aerosol absorption coefficients. Two biomass-burning case studies revealed different ΔBCe / ΔCO ratios from different fire types, with the agricultural fires in April~2008 yielding a very high ratio of 21 ng m−3 ppb−1. Overall, we find that anthropogenic sources dominate the aerosol population at ZOTTO most of the time, even during nominally clean episodes in winter, and that near-pristine conditions are encountered only in the growing season and then only episodically.
- 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%).