The impact of regional emissions (e.g., domestic and international) on surface particulate matter (PM) concentrations in the Seoul metropolitan area (SMA), South Korea, and its sensitivities to meteorology and emissions inventories are quantitatively estimated for 2014 using regional air quality modeling systems. Located on the downwind side of strong sources of anthropogenic emissions, South Korea bears the full impact of the regional transport of pollutants and their precursors. However, the impact of foreign emissions sources has not yet been fully documented. We utilized two regional air quality simulation systems: (1) a Weather Research and Forecasting and Community Multi-Scale Air Quality (CMAQ) system and (2) a United Kingdom Met Office Unified Model and CMAQ system. The following combinations of emissions inventories are used: the Intercontinental Chemical Transport Experiment-Phase B, the Inter-comparison Study for Asia 2010, and the National Institute of Environment Research Clean Air Policy Support System. Partial contributions of domestic and foreign emissions are estimated using a brute force approach, adjusting South Korean emissions to 50 %. Results show that foreign emissions contributed ∼ 60 % of SMA surface PM concentration in 2014. Estimated contributions display clear seasonal variation, with foreign emissions having a higher impact during the cold season (fall to spring), reaching ∼ 70 % in March, and making lower contributions in the summer, ∼ 45 % in September. We also found that simulated surface PM concentration is sensitive to meteorology, but estimated contributions are mostly consistent. Regional contributions are also found to be sensitive to the choice of emissions inventories.

Recent changes of surface particulate matter (PM) concentration in the Seoul Metropolitan Area (SMA), South Korea, are puzzling. The long-term trend of surface PM concentration in the SMA declined in the 2000s, but since 2012 its concentrations have tended to incline, which is coincident with frequent severe hazes in South Korea. This increase puts the Korean government’s emission reduction efforts in jeopardy. This study reports that interannual variation of surface PM concentration in South Korea is closely linked with the interannual variations of wind speed. A 12-year (2004–2015) regional air quality simulation was conducted over East Asia (27-km) and over South Korea (9-km) to assess the impact of meteorology under constant anthropogenic emissions. Simulated PM concentrations show a strong negative correlation (i.e. R = −0.86) with regional wind speed, implying that reduced regional ventilation is likely associated with more stagnant conditions that cause severe pollutant episodes in South Korea. We conclude that the current PM concentration trend in South Korea is a combination of long-term decline by emission control efforts and short-term fluctuation of regional wind speed interannual variability. When the meteorology-driven variations are removed, PM concentrations in South Korea have declined continuously even after 2012.

To show how remote-sensing products can be used to classify the entire CONUS domain into "geographical regions" and "chemical regimes", we analyzed the results of simulation from the Community Multiscale Air Quality (CMAQ) model version 4.7.1 over the Conterminous United States (CONUS) for August 2009. In addition, we observe how these classifications capture the weekly cycles of ground-level nitrogen oxide (NO_x) and ozone (O₃) at US EPA Air Quality System (AQS) sites. We use the Advanced Very High Resolution Radiometer (AVHRR) land use dominant categories and the Global Ozone Monitoring Experiment-2 (GOME-2) HCHO/NO₂ column density ratios to allocate geographical regions (i.e., "urban", "forest", and "other" regions) and chemical regimes (i.e., "NO_x-saturated", "NO_x-sensitive", and "mixed" regimes). We also show that CMAQ simulations using GOME-2 satellite-adjusted NO_x emissions mitigate the discrepancy between the weekly cycles of NO_x from AQS observations and that from CMAQ simulation results. We found geographical regions and chemical regimes do not show a one-to-one correspondence: the averaged HCHO / NO₂ ratios for AVHRR "urban" and "forest" regions are 2.1 and 4.0, which correspond to GOME-2 "mixed" and "NO_x-sensitive" regimes, respectively. Both AQS-observed and CMAQ-simulated weekly cycles of NO_x show high concentrations on weekdays and low concentrations on weekends, but with one- or two-day shifts of weekly high peaks in the simulated results, which eventually introduces the shifts in simulated weekly-low O₃ concentration. In addition, whereas the high weekend O₃ anomaly is clearly observable at sites over the GOME-2 NO_x-saturated regime in both AQS and CMAQ, the weekend effect is not captured at sites over the AVHRR urban region because of the chemical characteristics of the urban sites (≈GOME-2 mixed regime). In addition, the weekend effect from AQS is more clearly discernible at sites above the GOME-2 NO_x-saturated regime than at other sites above the CMAQ NO_x-saturated regime, suggesting that the GOME-2-based chemical regime classification is more accurate than CMAQ-based chemical classification. Furthermore, the CMAQ simulations using the GOME-2-derived NO_x emissions adjustment (decreasing from 462 Gg N to 426 Gg N over the US for August 2009) show large reductions of simulated NO_x concentrations (particularly over the urban, or NO_x-saturated, regime), and mitigates the large discrepancies between the absolute amount and the weekly pattern of NO_x concentrations of the EPA AQS and those of the baseline CMAQ.

This study identified the key chemical components based on an analysis of the seasonal variations of ground level PM_2.5 concentrations and its major chemical constituents (sulfate, nitrate, ammonium, organic carbon, and elemental carbon) in the Seoul Metropolitan Area (SMA), over a period of five years, ranging from 2012 to 2016. It was found that the mean PM_2.5 concentration in the SMA was 33.7 μg/m³, while inorganic ions accounted for 53% of the total mass concentration. The component ratio of inorganic ions increased by up to 61%–63% as the daily mean PM_2.5 concentration increased. In spring, nitrate was the dominant component of PM_2.5, accounting for 17%–32% of the monthly mean PM_2.5 concentrations. In order to quantify the impact of long-range transport on the SMA PM_2.5, a set of sensitivity simulations with the community multiscale air-quality model was performed. Results show that the annual averaged impact of Chinese emissions on SMA PM_2.5 concentrations ranged from 41% to 44% during the five years. Chinese emissions’ impact on SMA nitrate ranged from 50% (winter) to 67% (spring). This result exhibits that reductions in SO₂ and NO_X emissions are crucial to alleviate the PM_2.5 concentration. It is expected that NO_X emission reduction efforts in China will help decrease PM_2.5 concentrations in the SMA.

The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) modeling system. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. In this work, quality-controlled and -assured Air Quality System (AQS) ozone and nitrogen dioxide (NO₂) observations are used to evaluate the experimental predictions in 2010. It is found that both ozone and NO₂ are overestimated over the contiguous US (CONUS), with annual biases of +5.6 and +5.1 ppbv, respectively. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO₂. For both species the overpredictions are most pronounced in the summer. The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. Comparisons for six predefined US regions show the highest annual biases for ozone predictions in Southeast (+10.5 ppbv) and for NO₂ in the Lower Middle (+8.1 ppbv) and Pacific Coast (+7.1 ppbv) regions. The spatial distributions of the NO₂ biases in August show distinctively high values in the Los Angeles, Houston, and New Orleans areas. In addition to the standard statistics metrics, daily maximum eight-hour ozone categorical statistics are calculated using the current US ambient air quality standard (75 ppbv) and another lower threshold (70 ppbv). Using the 75 ppbv standard, the hit rate and proportion of correct over CONUS for the entire year are 0.64 and 0.96, respectively. Summertime biases show distinctive weekly patterns for ozone and NO₂. Diurnal comparisons show that ozone overestimation is most severe in the morning, from 07:00 to 10:00 local time. For NO₂, the morning predictions agree with the AQS observations reasonably well, but nighttime concentrations are overpredicted by around 100%.