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.
2017) Understanding particles emitted from spray and wall-guided gasoline direct injection and flex fuel vehicles operating on ethanol and iso-butanol gasoline blends, Aerosol Science and Technology, 51:3, 330-341, ABSTRACT Traffic-related pollutants are an ever-growing concern. However, the composition of particle emissions from new vehicle technologies using relevant current and prospective fuel blends is not known. This study tested four current and up-and-coming vehicle technologies with nine fuel blends with various concentrations of ethanol and iso-butanol. Vehicles were driven on both the federal test procedure (FTP) and the unified cycle (UC). Additional tests were conducted under steady-state speed conditions. The vehicle technologies include spray-guided gasoline direct injection (SG-GDI), wall-guided gasoline direct injection (WG-GDI), port-fuel injection flex fuel vehicle (PFI-FFV), and a wall-guided GDI-FFV. The fuels consisted of 10-83% ethanol and 16-55% iso-butanol in gasoline. The composition of soot, water-insoluble mass (WIM), water-soluble organic mass, and water-insoluble organic mass (WIOM), and OM was measured. The majority of emissions over FTP and UC were water-insoluble (>70%), and WIOM contributes mostly to OM. PFIs have lower soot and particulate matter (PM) emissions in comparison to the WG-GDI technology even while increasing the renewable fuel content. SG-GDI technology, which has not penetrated the market, show promise as soot and PM emissions are comparable to PFI vehicles while preserving the GDI fuel economy benefits. The WIM fraction in GDI-FFV consistently increased with increasing ethanol concentration. Lastly, the impact of the future vehicle emissions and traffic pollutants is discussed. SG-GDI technology is found to be a promising sustainable technology to enhance fuel economy and also reduce PM, soot, and WIM emissions.
Abstract. Particle mixing states modify CCN activity. A method of cloud condensation nuclei (CCN) data analysis for multicomponent mixtures of varying mixing states and its relationship to activation curves consisting of one or more activation points is presented. Simplified two component systems of varying solubility 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 are 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 aerosol are internally mixed and the CCN activated fraction data can be fit with a single sigmoidal curve. The technique to mimic external 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 non-hygroscopic black carbon with hygroscopic material as the aerosol population transitions from external to internally mixed. Results confirm that CCN activation analysis methods are robust and may be used to infer the mixing state of complex aerosol compositions of unknown origin.
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