Abstract. Heavy regional particulate matter (PM) pollution in China has resulted in an important and urgent need for joint control actions among cities. It is advisable to improve the understanding of the regional background concentration of PM for the development of efficient and effective joint control policies. With the increase of height the influence of source emission on local air quality decreases with altitude, but the characteristics of regional pollution gradually become obvious. A method to estimate regional background PM concentration is proposed in this paper, based on the vertical characteristics of periodic variation in the atmospheric boundary layer structure and particle mass concentration, as well as the vertical distribution of particle size, chemical composition and pollution source apportionment. According to the method, the averaged regional background PM2.5 concentration in July, August and September 2009, being extracted from the original time series in Tianjin, was 40 ± 20, 64 ± 17 and 53 ± 11 μg m−3, respectively.
An instrumental trifecta now exists for aerosol separation and classification by aerodynamic diameter (D ae), mobility diameter (D m) and mass (m) utilizing an aerodynamic aerosol classifier (AAC), differential mobility analyzer (DMA) and aerosol particle mass analyzer (APM), respectively. In principle, any combination of two measurements yields the third. These quantities also allow for the derivation of the particle effective density (q eff) and dynamic shape factor (v). Measured and/or derived deviations between tandem measurements are dependent upon the configuration but are generally <10%. Notably, nonphysical values of v (<1) and q eff (>bulk) were determined by the AAC-APM. Harmonization of the results requires the use of v in the determination of m and D m from the AAC-DMA and AAC-APM requiring either a priori assumptions or determination from another method. Further errors can arise from assuming instead of measuring physical conditionse.g., temperature and pressure affect the gas viscosity, mean free path and the Cunningham slip correction factor therefore impacting D m and D aebut are expected to have a smaller impact than v. Utilizing this triplet of instrumentation in combination allows for quantitative determination of v and the particle density (q p). If the bulk density is known or assumed, then the packing density can be determined. The v and q p were determined to be 1.10 ± 0.03 and (1.00 ± 0.02) g cm À3 , respectively, for a water stabilized black carbon mimic that resembles aged (collapsed) soot in the atmosphere. Assuming q bulk ¼ 1.8 g cm À3 , a packing density of 0.55 ± 0.02 is obtained.
Organic aerosol is ubiquitous, and partially soluble organic particles can uptake water, form droplets, and act as cloud condensation nuclei (CCN). Cholesterol is a well-known organic aerosol. Cholesterol is insoluble in water (<0.002 g in 100 mL of H2O at 293 K) but readily dissolves in organic solvents. In this study, we examine the ability of cholesterol generated in 7.2%, 10.4%, and 18.9% (by volume) dilutions of three water-soluble organic solvents (ethanol, 2-propanol, and acetone) to act as CCN. The measured apparent particle hygroscopicity, κ, can vary over 2 orders of magnitude, from ∼0.001 to 0.1. We use statistical analysis of variance (ANOVA) to quantify experimental design factors, not explicitly addressed in traditional theory, that modify κ-values. Results show that (i) particle sizes (electrical mobility and aerodynamic diameters) are important for apparent hygroscopicity κ-values and that (ii) atomized aerosol formed in the presence of organic solvents modifies particle size and droplet surface tension at the air–water interface and promotes droplet formation. As the volume of water (dilution) in the atomized solution increases, the organic solvent decreases and κ decreases. Increases in organic solvent concentration decrease droplet surface tension and change aerosol shape. Thus, the apparent κ is corrected with surface tension and shape factor data. The results imply that miscible atmospheric organic solvents that readily adsorb and solvate in water enhance the droplet forming potential of cholesterol and may thus extend to other atmospheric water-insoluble organic particles.
Changes in aerosol chemical mixtures modify cloud condensation nuclei (CCN) activity. Previous studies have developed CCN models and validated changes in external and internal mixing state with ambient field data. Here, we develop an experimental method to test and validate the CCN activation of known aerosol chemical composition with multicomponent mixtures and varying mixing states. CCN activation curves consisting of one or more activation points are presented. Specifically, simplified two-component systems of varying hygroscopicity were generated under internal, external, and transitional mixing conditions. κ-Köhler theory predictions were calculated for different organic and inorganic mixtures and compared to experimentally derived kappa values and respective mixing states. This work employs novel experimental methods to provide information on the shifts in CCN activation data due to external to internal particle mixing from controlled laboratory sources. Results show that activation curves consisting of single and double activation points are consistent with internal and external mixtures, respectively. In addition, the height of the plateau at the activation points is reflective of the externally mixed concentration in the mixture. The presence of a plateau indicates that CCN activation curves consisting of multiple inflection points are externally mixed aerosols of varying water-uptake properties. The plateau disappears when mixing is promoted in the flow tube. At the end of the flow tube experiment, the aerosols are internally mixed and the CCN activated fraction data can be fit with a single-sigmoid curve. The technique to mimic externally to internally mixed aerosol is applied to non-hygroscopic carbonaceous aerosol with organic and inorganic components. To our knowledge, this work is the first to show controlled CCN activation of mixed nonhygroscopic soot with hygroscopic material as the aerosol population transitions from externally to internally mixed states in laboratory conditions. Results confirm that CCN activation analysis methods used here and in ambient data sets are robust and may be used to infer the mixing state of complex aerosol compositions of unknown origin.
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