This thesis investigates the mechanism of denitrification o f the Arctic lower stratosphere and the impact o f denitrification on ozone loss using the SLIMCAT chemical transport model. The development of a new microphysical model for the simulation of growth and sedimentation of large nitric acid trihydrate particles is also described. Model simulations of Arctic denitrification were carried out using thermodynamic equilibrium schemes based on the sedimentation of either nitric acid trihydrate or ice using different meteorological analyses. The severity and extent of denitrification in ice-based model runs was found to be highly sensitive to the meteorological analyses used whereas nitric acid trihydrate denitrification schemes exhibited considerably less sensitivity. The response of thermodynamic equilibrium and microphysical NAT-based denitrification to meteorological conditions has been studied in a series of short idealised simulations. It was found that microphysical denitrification was considerably more sensitive to the relative orientation of the polar vortex flow and the region of cold temperatures. A concentric vortex and cold region are required to promote the long particle growth times required for strong denitrification in the microphysical model. Reduced rates of denitrification were evident in the microphysical model at the highest altitudes. Results from the microphyical denitrification scheme were compared with in-situ and remote observations of denitrification for two recent cold Arctic winters. There was remarkable agreement between model and observations of both the magnitude and location of denitrification despite the simple volume-averaged nucleation rate used in the model. The limited range of observations did not allow further constraints to be placed on the microphysical model. Denitrification was found to enhance Arctic ozone loss by up to 30% during 1999/2000. Sensitivity studies o f the impact of denitrification on Arctic ozone loss were performed using thermodynamic nitric acid trihydrate denitrification schemes. Cumulative ozone depletion was found to increase non-linearly with increasing denitrification. Enhanced recovery of chlorine radicals to hydrogen chloride in strongly denitrified model runs offset reduced recovery to chlorine nitrate, limiting the impact of denitrification to the equivalent of 20 days additional ozone loss.

Knowledge of distributions of aerosols is critical to human health, Earth's radiative budget, and air quality. However, the lack of sufficient direct measurements of aerosol type, number, mass concentrations and current limitations of satellite retrievals make it challenging to accurately model the aerosol variability. Such measurement gaps also hinder evaluation of aerosol source budget from emission inventories, modeling of aerosol chemistry, and sinks. In this context, the first study characterizes the potential of multivariate relationships between Aerosol Optical Depth (AOD), a quantity that represents light extinction by aerosols in the atmospheric column and a suite of surface and atmospheric parameters (e.g., vegetation, precipitation, fire characteristics) in order to assess trends in AOD anomalies for the U.S Southwest. This study covers the area that experiences North American Monsoon (NAM) and examines trends in AOD across different aerosol sources in this region such as dust storms, biomass burning, and anthropogenic emissions. We find that aerosols from anthropogenic processes and biomass burning exhibited a strong declining trend in AOD whereas trends along the NAM alley were obfuscated by the monsoon precipitation (sink) and convective dust storms (sources). In the second study, we develop constraints to improve characterization of anthropogenic apparent Elemental Carbon (ECa) using coemitted combustion products such as Carbon Monoxide (CO) and Nitrogen Oxides (NOx). We compare observational ratios of ECa vs CO and ECa vs NOx against those from emission inventories. We find that the observational ratios have increased at sites in the Urban-West due to increase in ECa from 2000-2007 to 2008-2015. Further, emission ratios do not match with observational ratios. We recommend that rigorous efforts are needed to better quantify and monitor the changes in these species in the Urban-West particularly for non-road and residential combustion sectors. The final study of this dissertation discusses a technique to produce forecasts of AOD by combining satellite retrievals and a chemical transport model in an analog based framework. We use model forecasts of AOD, particulate matter (PM) concentrations, and meteorological parameters from Weather Research and Forecasting model with Chemistry (WRF-Chem) to train the framework for choosing analogs (past forecasts similar to current simulations). MODIS Terra and Aqua satellite retrievals of AOD for analog days are then used in a Kalman Filter (KF) framework to determine the forecast error and referred to as KFAN. The analog based estimates better forecasts of AOD for the Western US compared to the East and the mean bias in AOD forecasts are reduced to the range of 0.001-0.1. The reduction in positive bias in AOD is drastic and the method captures the decrease in AOD from morning to afternoon. We find that higher root mean square error (RMSE) values in the East are due to the inability of KFAN to capture the AOD peaks during biomass burning episodes and AOD lows during days of high precipitation rates. A systematic statistical analysis using step-wise linear regression models also show that in the East, there is a stronger dependence of aerosol loading on meteorological factors such as air temperature, precipitation, and relative humidity. As a consequence, overall quality of the analogs in the East is impacted when uncertainties in the simulated meteorological fields are higher. Overall, this study shows that the correlative information from multi-satellite remote sensing retrievals and models provide additional constraints on aerosols using composition/source identification (e.g., aerosol type, landcover, emission sources, fuel consumption), coemitted gas phase species (e.g., CO and NOx), and meteorological parameters (e.g., wind speed, TPW). The synergy of information from these datasets can be beneficial for design of future remote sensing missions, deployment of ground networks, and studies related to feedbacks between meteorology and aerosols.

Ozone (O3) and particulate matter (PM) existing in the atmosphere have adverse effects to human and environment. Southeast Texas experiences high O3 and PM events due to special meteorological conditions and high emission rates of volatile organic compounds (VOCs) and nitrogen oxides (NOx). Quantitative knowledge of the contributions of different emissions sources to O3 and PM is helpful to better understand their formation mechanisms and develop effective control strategies. Tagged reactive tracer techniques are developed and coupled into two chemical transport models (UCD/CIT model and CMAQ) to conduct source apportionment of O3, primary PM, secondary inorganic PM, and secondary organic aerosol (SOA) and aging distribution of elemental carbon (EC) and organic carbon (OC). Ozone (O3) and particulate matter (PM) existing in the atmosphere have adverse effects to human and environment. Southeast Texas experiences high O3 and PM events due to special meteorological conditions and high emission rates of volatile organic compounds (VOCs) and nitrogen oxides (NOx). Quantitative knowledge of the contributions of different emissions sources to O3 and PM is helpful to better understand their formation mechanisms and develop effective control strategies. Tagged reactive tracer techniques are developed and coupled into two chemical transport models (UCD/CIT model and CMAQ) to conduct source apportionment of O3, primary PM, secondary inorganic PM, and secondary organic aerosol (SOA) and aging distribution of elemental carbon (EC) and organic carbon (OC). Models successfully reproduce the concentrations of gas phase and PM phase species. Vehicles, natural gas, industries, and coal combustion are important O3 sources. Upwind sources have non-negligible influences (20-50%) on daytime O3, indicating that regional NOx emission controls are necessary to reduce O3 in Southeast Texas. EC is mainly from diesel engines while majority of primary OC is from internal combustion engines and industrial sources. Open burning, road dust, internal combustion engines and industries are the major sources of primary PM2.5. Wildfire dominates primary PM near fire locations. Over 80% of sulfate is produced in upwind areas and coal combustion contributes most. Ammonium ion is mainly from agriculture sources. The SOA peak values can be better predicted when the emissions are adjusted by a factor of 2. 20% of the total SOA is due to anthropogenic sources. Solvent and gasoline engines are the major sources. Oligomers from biogenic SOA account for 30-58% of the total SOA, indicating that long range transport is important. PAHs from anthropogenic sources can produce 4% of total anthropogenic SOA. Wild fire, vehicles, solvent and industries are the major sources. EC and OC emitted within 0-3 hours contribute approximately 70-90% in urban Houston and about 20-40% in rural areas. Significant diurnal variations in the relative contributions to EC are predicted. Fresh particles concentrations are high at morning and early evening. The concentrations of EC and OC that spend more than 9 hours in the air are low over land but almost accounts for 100% of the total EC and OC over the ocean.

The objective of this thesis is to evaluate the sources of the differences between the NO2 satellite retrieval products provided by the Royal Dutch Meteorological Institute (KNMI) and the National Aeronautics and Space Administration (NASA). Ground studies have shown that although both products use the same satellite, these products yield different observations for NO2 tropospheric columns concentrations. This study does not validate either retrieval product, but rather indentifies the main sources for the discrepancy. There are several parameters which allow successful retrieval of NO2 vertical columns. For this study, only the difference between the radiative models and the a priori NO2 chemical transport models were considered relevant. All other parameters, such as cloud properties, slant columns, stratospheric serration and their assumptions, were held constant. Here, the models are referred to by their proprietor's acronym: "TOMRAD" refers to the radiative model used by NASA, "DAK" refers to the radiative model used by KNMI, "TM4" refers to the a priori chemical transport model used by KNMI, and "REAM" refers to the a priori chemical transport model maintained by the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. Mixing these parameters creates four retrievals for comparison. Many significant differences were identified after comparing these four retrievals. First, there are viewing geometry biases between the port side and the starboard side of the satellite retrieval for each swath. These viewing geometry biases lead to artificial periodicities in the retrievals of NO2 tropospheric vertical columns over a specific coordinate or site, such as a city. Furthermore, there were significant differences found after using different a priori NO2 chemical transport models. The low horizontal resolution of TM4 and the satellite retrieval/TM4 coupling effect compared to REAM leads to considerable questioning of the near real time application of the KNMI NO2 retrieval product. Though the TM4 model performs poorly, TM4 retrievals do perform nearly as well as REAM retrievals at capturing day-to-day variability and the spatial variability of the cities used as examples here. The retrievals using TOMRAD outperformed the retrievals using DAK when compared to the high resolution, hourly REAM a priori chemical transport model. In sum, these findings should lead to better optimizations of both the KNMI and NASA retrievals, and thus make their publicly available data products more reliable and accurate for general use.

In this thesis, a new aerosol module is developed for the STEM model (the Sulfur Transport and dEposition Model) to better understand the chemical aging of dust during long range transport and assess the impact of heterogeneous reactions on tropospheric chemistry. The new aerosol module is verified and first applied in a box model, and then coupled into the 3-Dimentional STEM model. In the new aerosol model, a non-equilibrium (dynamic or kinetic) approach to treat gas-to-particular conversion is employed to replace the equilibrium method in STEM model. Meanwhile, a new numerical method solving the aerosol dynamics equation is introduced into the dynamic aerosol model for its improved computational efficiency and high accuracy. Compared with the equilibrium method, the new dynamic approach is found to provide better results on predicating the different hygroscopicity and chemical aging patterns as a function of size. The current modeling study also takes advantage of new findings from laboratory experiments about heterogeneous reactions on mineral oxides and dust particles, in order to consider the complexity of surface chemistry (such as surface saturation, coating and relative humidity). Modeling results show that the impacts of mineralogy and relative humidity on heterogeneous reactions are significant and should be considered in atmospheric chemistry modeling with first priority. Finally, the upgraded 3-D STEM model is utilized to explore the observations from the Intercontinental Chemical Transport Experiment - Phase B (INTEX-B). The new dynamic approach for gas-to-particular conversion and RH-dependent heterogeneous uptake of HNO3 improve the model performance in term of aerosol predictions under different conditions. It is shown that these improvements change the modeled nitrate and sulfate concentrations, but also modify their size distributions significantly.

Air quality degradation is emerging to be an issue of major concern in India. Recent investigations have shown that anthropogenic aerosols have significant impact on climate as well as on health. In fourth assessment report of IPCC, it has been mentioned that radiative effects of anthropogenic aerosols constitute one of the major uncertainties in assessing aerosol-induced climate impact. In addition to climate impacts, aerosol causes respiratory and cardiovascular diseases, air quality degradation, acidification of aquatic and terrestrial ecosystems. Characterization of anthropogenic aerosol fraction (defined as the fraction of anthropogenic aerosols to composite aerosols) is an appealing topic of research in current scenario. The first step towards achieving this goal is to separate natural aerosol from composite aerosols, which is a complex task. The main objective of this thesis work is the assessment of air quality and anthropogenic aerosol fraction over India using observations (ground-based as well as satellite-based) and chemistry-transport model. Specifically objectives are (a) assessment of air quality and anthropogenic aerosol fraction over Indian region (b) develop a method to derive natural aerosol properties over land and oceans using multi-satellite data analysis, which is first step towards separating natural aerosol effects from its anthropogenic counter parts and (c) evaluate performance of CHIMERE chemistry-transport model for Indian region and validate its suitability to air quality studies over India. In this thesis, different approaches have been followed such as ground-based observations, multi-satellite data analysis and CHIMERE transport model. We have used multi-year observations of particulate mass (PM) concentration, aerosol black carbon (BC) mass concentration and aerosol optical depth (AOD) from a network of observatories to make an assessment of ambient air quality over India. First, we have developed a method to estimate dust and sea-salt optical depth using multi-satellite data analysis. This enabled the determination of anthropogenic aerosol fraction over land and ocean and we have validated this method by comparing against observations. Surprisingly, even over desert locations in India and Saudi Arabia, the anthropogenic fraction were unexpectedly high (~0.3 to 0.4) and the regionally averaged anthropogenic fraction over India was 0.620.06 (for the year 2004). The CHIMERE chemistry-transport model was used to simulate PM, BC and AOD over India and are compared with measurements. Evaluation of CHIMERE output shows that diurnal and seasonal trends are captured reasonably well by the model. It was found that absolute magnitudes differ substantially during monsoon months. Model simulations are also used to estimate anthropogenic fraction over Indian region and are compared with observations. Implications of the results are discussed. Mineral dust constitutes the single largest contributor of natural aerosols over continents. The first step towards separating natural aerosol radiative impact from its anthropogenic counterparts over continents is to gather information on dust aerosols. The infrared (IR) radiance (10.5–12.5 mm) acquired from the Kalpana satellite (8-km resolution) was used to retrieve regional characteristics of dust aerosols over the Afro-Asian region during the winter of 2004, coinciding with a national aerosol campaign. Here, we used aerosol-induced IR radiance depression as an index of dust load. The regional distribution of dust over various arid and semi-arid regions of India and adjacent continents has been estimated, and these data in conjunction with regional maps of column aerosol optical depth (AOD) are used to infer anthropogenic aerosol fraction. Surprisingly, even over desert locations in India and Saudi Arabia, the anthropogenic fraction were relatively high (0.3 to 0.4) and the regionally averaged anthropogenic fraction over India was 0.62 ±0.06. Sea-salt constitutes the single largest contributor of natural aerosols over oceans. We derive sea-salt aerosol distribution using a method utilizing multi-satellite data analysis. This information was used in conjunction with dust aerosols retrieval to calculate anthropogenic fraction over land and ocean. First, we derived a relation between MODIS AOD and NCEP wind speed at the sea-surface. An exponential increase in AOD as a function of wind speed was observed from mid of southern ocean to northern Arabian Sea. Latitudinal variation of wind independent component of optical depth (τ0) and wind index (b) was used to estimate the sea-salt optical depth over Arabian Sea. The value of τ0 showed an exponential increase as we move towards north from 35°S while b showed linear increase. The derived relations for the τ0 and b have been used to derive the sea-salt AOD distribution over oceanic regions in the domain (Eq-30°N; 30°E-110°E). Then we subtract the natural aerosol contribution from composite AOD data from MISR to obtain anthropogenic aerosol fraction. Over Indian region, high anthropogenic fraction was observed over northern belt specifically Indo-Gangetic Plains (IGP). Annually averaged anthropogenic fraction over Indian domain (4N-29.5N; 67E-88.5E) is ~0.43. Further, we have investigated the impact of sea-surface winds on sea-salt radiative effect in visible and infrared region with the help of SBDART radiative transfer model. The SBDART simulations have shown that at 15 m s-1, sea-salt induced shortwave cooling at the sea-surface was -86 W m-2. Derivation of anthropogenic aerosol fraction over whole Indian domain has demonstrated the importance of anthropogenic aerosols. This observation motivated us to examine the air quality over Bangalore, a fast growing city in India. We have analyzed data from ground based measurements of particulate matter, observations from satellites and also model simulations. Comparison with national threshold indicates that more than 50% of observations were above the residential threshold. To represent the air quality of Bangalore we have calculated the air quality index (AQI) for air pollutants. Coarse spatial and temporal resolution of observational data is one major shortcoming in such analysis. Therefore, satellite observations are alternative to quantify the air quality over large area. We have used MODIS AOD and RSPM to develop an empirical relation between these two parameters. A reasonably good agreement was observed between measured RSPM and RSPM derived using satellite data (by applying empirical relation). The CHIMERE chemistry-transport model was used to simulate PM, BC and AOD over India and are compared with measurements. Evaluation of CHIMERE output shows that diurnal and seasonal trends are captured reasonably well by the model. It was found that absolute magnitudes differ substantially during pre-monsoon and monsoon months. Model simulations are also used to estimate anthropogenic fraction over Indian region and are compared with observations. Implications of the results and future scope are discussed. The validation of model results suggests that CHIMERE model is suitable for simulating air quality over India with reasonable accuracy. This would in turn help us to address the impacts of air pollution on regional climate and help policy makers in order to reduce the air pollution. In summary, we have developed a new method to infer natural aerosol (sea-salt and dust) properties using multi-satellite data analysis. This technique has been applied to derive anthropogenic aerosol fraction over Indian region. Surprisingly, even over desert locations in India and Saudi Arabia, the anthropogenic fraction were relatively high (0.3 to 0.4) and regionally averaged anthropogenic fraction over India was 0.62±0.06 in 2004. This study indicates that multi-satellite observations can provide a powerful tool in monitoring air quality. We have noticed that anthropogenic fraction was 0.62 in 2004 and reduced to 0.43 in 2008. Major anthropogenic aerosol over India is BC and decreasing trend in BC could be one of the reasons for the decrease in anthropogenic fraction from 2004 to 2008. The CHIMERE chemistry-transport model was used to simulate PM, BC and AOD over India and are compared with measurements. Evaluation of CHIMERE output shows that diurnal and seasonal trends are captured reasonably well by the model. It was found that absolute magnitudes differ substantially during pre-monsoon and monsoon months. Presence of elevated aerosol layers during these seasons could be one of the sources for such discrepancy. Model simulations of anthropogenic fraction over Indian region are compared with observations and found good agreement. Results from this thesis moves us one step forward to reduce the uncertainties involved in anthropogenic aerosol fraction, its spatial and temporal distributions and regional distribution of OC/BC ratio, which are most important parameters in order to assess the climate forcing by anthropogenic aerosols.

Halogen-driven ozone and nonmethane hydrocarbon losses in springtime Arctic boundary layer are investigated using a regional chemical transport model (CTM). Surface observation of O3 at Alert and Barrow and aircraft observations of O3 and hydrocarbons during the TOPSE experiment from February to May in 2000 are analyzed. We prescribe halogen radical distributions based on GOME BrO observations and calculated or observed other halogen radical to BrO ratios. GOME BrO shows an apparent anti-correlation with surface temperature over high BrO regions. At its peak, area of simulated near-surface O3 depletions (O3 LT 20ppbv) covers GT 50% of the north high latitudes. Model simulated O3 losses are in agreement with surface and aircraft O3 observations. Simulation of halogen distributions are constrained using aircraft hydrocarbon measurements. We find the currently chemical mechanism overestimate the Cl/BrO ratios. The model can reproduce the observed halogen loss of NMHCs using the empirical Cl/BrO ratios. We find that the hydrocarbon loss is not as sensitive to the prescribed boundary layer height of halogen as that of O3, therefore producing a more robust measure for evaluating satellite column measurement. Tropospheric tracer transport and chemical oxidation processes are examined on the basis of the observations at northern mid-high latitudes and over the tropical Pacific and the corresponding global 3D CTM (GEOS-CHEM) simulations. The correlation between propane and ethane/propane ratio is employed using a finite mixing model to examine the mixing in addition to the OH oxidations. At northern mid-high latitudes the model agrees with the observations before March. The model appears to overestimate the transport from lower to middle latitudes and the horizontal transport and mixing at high latitudes in May. Over the tropical Pacific the model reproduces the observed two-branch slope values reflecting an underestimate of continental convective transport at northern mid-latitudes and an overestimate of latitudinal transport into the tropics. Inverse modeling using the subsets of observed and simulated data is more reliable by reducing (systematic) biases introduced by systematic model transport model transport errors. On the basis of this subset we find the model underestimates the emissions of ethane and propane by 14 5%.