South Korea has experienced a rapid increase in ozone concentrations in surface air together with China for decades. Here we use a 3-D global chemical transport model, GEOS-Chem nested over East Asia (110 E - 140 E, 20 N-50 N) at 0.25° × 0.3125° resolution, to examine locally controllable (domestic anthropogenic) versus uncontrollable (background) contributions to ozone air quality at the national scale for 2016. We conducted model simulations for representative months of each season: January, April, July, and October for winter, spring, summer, and fall and performed extensive model evaluation by comparing simulated ozone with observations from satellite and surface networks. The model appears to reproduce observed spatial and temporal ozone variations, showing correlation coefficients (0.40-0.87) against each observation dataset. Seasonal mean ozone concentrations in the model are the highest in spring (39.3 ± 10.3 ppb), followed by summer (38.3 ± 14.4 ppb), fall (31.2 ± 9.8 ppb), and winter (24.5 ± 7.9 ppb), which is consistent with that of surface observations. Background ozone concentrations obtained from a sensitivity model simulation with no domestic anthropogenic emissions show a different seasonal variation in South Korea, showing the highest value in spring (46.9 ± 3.4 ppb) followed by fall (38.2 ± 3.7 ppb), winter (33.0 ± 1.9 ppb), and summer (32.1 ± 6.7 ppb). Except for summer, when the photochemical formation is dominant, the background ozone concentrations are higher than the seasonal ozone concentrations in the model, indicating that the domestic anthropogenic emissions play a role as ozone loss via NO_x titration throughout the year. Ozone air quality in South Korea is determined mainly by year-round regional background contributions (peak in spring) with summertime domestic ozone formation by increased biogenic VOCs emissions with persistent NO_x emissions throughout the year. The domestic NO_x emissions reduce MDA8 ozone around large cities (Seoul and Busan) and hardly increase MDA8 in other regions in spring, but it increases MDA8 across the country in summer. Therefore, NO_x reduction can be effective in control of MDA8 ozone in summer, but it can have rather countereffect in spring.

It is desired to control excessive reactive nitrogen (Nr) deposition due to its detrimental impact on ecosystems. Using a three-dimensional atmospheric chemical transport model, GEOS-Chem, Nr deposition in the contiguous US and eight selected Class I areas (Voyageurs (VY), Smoky Mountain (SM), Shenandoah (SD), Big Bend (BB), Rocky Mountain (RM), Grand Teton (GT), Joshua Tree (JT), and Sequoia (SQ)) is investigated. First, modeled Nr deposition is compared with National Trends Network (NTN) and Clean Air Status and Trends Network (CASTNET) deposition values. The seasonality of measured species is generally well represented by the model (R² > 0.6), except in JT. While modeled Nr is generally within the range of seasonal observations, large overestimates are present in sites such as SM and SD in the spring and summer (up to 0.6 kg N ha month⁻¹), likely owing to model high-biases in surface HNO₃. The contribution of non-measured species (mostly dry deposition of NH₃) to total modeled Nr deposition ranges from 1 to 55 %. The spatial distribution of the origin of Nr deposited in each Class I area and the contributions of individual emission sectors are estimated using the GEOS-Chem adjoint model. We find the largest role of long-range transport for VY, where 50 % (90 %) of annual Nr deposition originates within 670 (1670) km of the park. In contrast, the Nr emission footprint is most localized for SQ, where 50 % (90 %) of the deposition originates from within 130 (370) km. Emissions from California contribute to the Nr deposition in remote areas in the western US (RM, GT). Mobile NO_x and livestock NH₃ are found to be the major sources of Nr deposition in all sites except BB, where contributions of NO_x from lightning and soils to natural levels of Nr deposition are significant (∼ 40 %). The efficiency in terms of Nr deposition per kg emissions of NH₃-N, NO_x-N, and SO₂-S are also estimated. Unique seasonal features are found in JT (opposing efficiency distributions for winter and summer), RM (large fluctuations in the range of effective regions), and SD (upwind NH₃ emissions hindering Nr deposition). We also evaluate the contributions of emissions to the total area of Class I regions in critical load exceedance, and to the total magnitude of exceedance. We find that while it is effective to control emissions in the western US to reduce the area of regions in CL exceedance, it can be more effective to control emissions in the eastern US to reduce the magnitude of Nr deposition above the CL. Finally, uncertainty in the nitrogen deposition caused by uncertainty in the NH₃ emission inventory is explored by comparing results based on two different NH₃ inventories; noticeable differences in the emission inventories and thus sensitivities of up to a factor of four found in individual locations.