S-Space College of Natural Sciences (자연과학대학) Dept. of Earth and Environmental Sciences (지구환경과학부) Theses (Ph.D. / Sc.D._지구환경과학부)
Chemical aging of organic aerosol and its climatic implications : 유기 에어로졸의 대기 중 화학적 노화 과정과 기후에 미치는 영향 연구
- 자연과학대학 지구환경과학부
- Issue Date
- 서울대학교 대학원
- Organic aerosol ; Chemical aging ; Brown carbon ; Direct radiative effect ; Single scattering albedo
- 학위논문 (박사)-- 서울대학교 대학원 자연과학대학 지구환경과학부, 2017. 8. 박록진.
- Aerosols can offset the positive radiative effect by various greenhouse gases, but there is a large uncertainty in the estimate of aerosols radiative effect. This large uncertainty is mainly due to the limitation of models reproducing various characteristics of aerosols in the real atmosphere. This dissertation is to reduce the gap between observations and models focusing on three issues of aerosol modeling: (1) mass concentration, (2) speciation, and (3) physical/optical property. I investigate these subjects using a global 3-D chemical transport model (GEOS-Chem) and update the model with the new findings. And finally, I apply the developed model to recent aircraft campaign over South Korea (KORUS-AQ) as a case study in a heavily polluted condition. The first issue is that organic aerosol (OA) constitutes significant mass fractions (20%-90%) of total dry fine aerosols in the atmosphere, but global models of OA have shown large discrepancies when compared to the observed values. I update the GEOS-Chem in order to improve the model simulation capability of OA by implementing the volatility basis set (VBS) approach. The VBS method can efficiently simulate chemical aging of SOA in the atmosphere, which can lead to decreases in organic volatility, resulting in an increase of SOA mass yields. I find that the model results with the chemical aging are in better agreement with observations relative to those without chemical aging, especially for rural regions. Second, most models consider OA as a light-scattering aerosol, but the observations showed that a certain fraction of OA (called as brown carbon
BrC) could be a light-absorbing aerosol. I develop the model to explicitly simulate BrC, which has not been considered in most of the current chemical transport models. I develop a new method for the estimation of BrC emission from biomass burning and biofuel use based on the relationship between modified combustion efficiency and absorption Ångstrom exponent. I calculate that BrC accounts for 21% of the global mean OA concentration, which is typically assumed to be scattering. The inclusion of BrC absorption in the model decreases the direct radiative cooling effect of OA by 16%. In addition, the BrC absorption leads to a general reduction of NO2 photolysis rates and ozone concentration (by up to -13% in spring time in Asia). Third, some previous global modeling studies showed positive single scattering albedo (SSA) bias, which can lead to a significant change in aerosol radiative forcing. However, it is difficult to find the cause of the SSA bias because of diverse physical/optical characteristics of aerosols are combined in the model. Therefore, I carry out multiple sensitivity simulations to examine the effects of individual factors on calculated SSA. I find that large variation of calculated black carbon absorption may result from slight changes of its geometric mean radius, geometric standard deviation, real and imaginary refractive indices, and density. The inclusion of BrC and observationally-constrained dust size distribution also significantly affects SSA, and results in a remarkable improvement for simulated SSA at 440 nm compared with the AERONET observations. Finally, I examine the observed OA characteristics during the KORUS-AQ campaign with the updated model above. The model simulates similar mean OA concentrations against the observed OA (5% bias). The model also successfully reproduces mean vertical profile of OA during KORUS-AQ. However, I find that the model performance is significantly changed if the evaluation is focused on the specific research flight. The model underestimates the observed OA by more than a factor of two when the observation is heavily influenced by biomass burning. Fine-scale biomass burning emissions (< 0.01 km2) are missed in the current emission inventory due to the coarse spatial resolution of satellite, but they contribute about 90% of biomass burning in South Korea. On the other hand, the model overestimates observed OA concentrations from some research flights. I find that photolytic loss, which is revealed in the observation but not considered in the model, could reduce the overestimation and should be considered in future modeling studies.