Assessment of air quality in North Korea from satellite observations

North Korean CO emissions reconstruction using DMZ ground observations, TROPOMI space-borne data, and the CMAQ air quality model

Emission uncertainty in North Korea can act as an obstacle when developing air pollution management plans in the country and neighboring countries when the transboundary transport of air pollutants is considered. This study introduces a novel approach for adjusting and reallocating North Korean CO emissions, aiming to complement the limited observational and emissions data on the country's air pollutants. We utilized ground observations from demilitarized zone (DMZ) and vertical column density (VCD) data from a TROPOspheric Monitoring Instrument (TROPOMI), which were combined with the Community Multi-Scale Air Quality (CMAQ) chemistry transport model simulations. The Clean Air Support System (CAPSS) and Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) emissions inventories served as the basis for our initial simulations. A two-step procedure was proposed to adjust both the emission intensity and the spatial distribution of emissions. First, air quality simulations were conducted to explore model sensitivity to changes in North Korean CO emissions with respect to ground concentrations. DMZ observations then constrained these simulations to estimate corresponding emission intensity. Second, the spatial structure of North Korean CO emission sources was reconstructed with the help of TROPOMI CO VCD distributions. Our two-step hybrid method outperformed individual emissions adjustment and spatial reallocation based solely on surface or satellite observations. Validation using ground observations from the Chinese Dandong site near the China-North Korea border revealed significantly improved model simulations when applying the updated CO emissions. The adjusted CO emissions were 10.9 times higher than those derived from the bottom-up emissions used in this study, highlighting the lack of information on North Korean pollutants and emission sources. This approach offers an efficient and practical solution for identifying potential missing emission sources when there is limited on-site information about air quality on emissions.

Development of surface observation-based two-step emissions adjustment and its application on CO, NOx, and SO2 emissions in China and South Korea

It is challenging to estimate local emission conditions of a downwind area solely based on concentrations in the downwind area. This is because air pollutants that have a long residence time in the atmosphere can be transported over long distances and influence air quality in downwind areas. In this study, a Two-step Emissions Adjustment (TEA) approach was developed to adjust downwind emissions of target air pollutants with surface observations, considering their long-range transported emission impacts from upwind areas calculated from air quality simulations. Using the TEA approach, CO, NOx, and SO2 emissions were adjusted in China and South Korea between 2016 and 2021 based on existing bottom-up emissions inventories. Simulations with the adjusted emissions showed that the 6-year average normalized mean biases of the monthly mean concentrations of CO, NOx, and SO2 improved to 0.3 %, -2 %, and 2 %, respectively, in China, and to 5 %, 7 %, and 4 %, respectively, in South Korea. When analyzing the emission trends, it was estimated that the annual emissions of CO, NOx, and SO2 in China decreased at a rate of 7.2 %, 4.5 %, and 10.6 % per year, respectively. The decrease rate of emissions for each of these pollutants was similar to that of ambient concentrations. When considering upwind emission impacts in the emissions adjustment, CO emissions increased by 1.3 %/year in South Korea, despite CO concentrations in the country decreasing during the study period. During the study period, NOx and SO2 emissions in South Korea decreased by 3.9 % and 0.5 %/year, respectively. Moreover, the TEA approach can account for drastic short-term emission changes (e.g., social distancing due to COVID-19). Therefore, the TEA approach can be used to adjust emissions and improve reproducibility of concentrations of air pollutants suitable for health studies for areas where upwind emission impacts are significant.

Comparison of inorganic nitrogen concentrations in airborne particles at inshore and offshore sites in the Yellow Sea (2017-2019): Long-range transport and potential impact on marine productivity

Atmospheric deposition of nitrogen is one of the most important external nutrient sources. We investigated the concentrations of NO3- and NH4+ in airborne particles at both an offshore and an inshore site in the Yellow Sea. At the offshore site, devoid of local sources and located downwind from the highly developed areas of Korea and China, the concentrations of atmospheric particulate NO3- and NH4+ were ∼88 ± 101 nmol m-3 and ∼102 ± 102 nmol m-3, respectively, likely due to the transboundary long-range transport of pollutants. The inshore site showed a concentration ∼2 times higher than the offshore site. Considering not only dry inorganic nitrogen deposition but also wet and organic material deposition, the total atmospheric nitrogen deposition was estimated to contribute roughly 10 % to the new production in the Yellow Sea.

Change in Air Quality during 2014-2021 in Jinan City in China and Its Influencing Factors

Air pollution affects climate change, food production, traffic safety, and human health. In this paper, we analyze the changes in air quality index (AQI) and concentrations of six air pollutants in Jinan during 2014-2021. The results indicate that the annual average concentrations of PM₁₀, PM_2.5, NO₂, SO₂, CO, and O₃ and AQI values all declined year after year during 2014-2021. Compared with 2014, AQI in Jinan City fell by 27.3% in 2021. Air quality in the four seasons of 2021 was obviously better than that in 2014. PM_2.5 concentration was the highest in winter and PM_2.5 concentration was the lowest in summer, while it was the opposite for O₃ concentration. AQI in Jinan during the COVID epoch in 2020 was remarkably lower compared with that during the same epoch in 2021. Nevertheless, air quality during the post-COVID epoch in 2020 conspicuously deteriorated compared with that in 2021. Socioeconomic elements were the main reasons for the changes in air quality. AQI in Jinan was majorly influenced by energy consumption per 10,000-yuan GDP (ECPGDP), SO₂ emissions (SDE), NOx emissions (NOE), particulate emissions (PE), PM_2.5, and PM₁₀. Clean policies in Jinan City played a key role in improving air quality. Unfavorable meteorological conditions led to heavy pollution weather in the winter. These results could provide a scientific reference for the control of air pollution in Jinan City.