Minwook Kim

Agricultural activities emit ammonia (NH₃) and particulate matter (PM), yet Korean air-quality monitoring is concentrated in urban areas. We analyzed daily PM₁₀, PM_2.5, NO₂, SO₂, and NH₃ at four rice-paddy sites (March 2023–June 2025) across five calendar-defined cultivation stages, which are confounded with season. We therefore separated winter from early spring, calculated increments relative to paired urban stations, and compared recorded operation days with other days of the same month. PM₁₀ was highest in the preparation stage (46.08 vs. 23.97 μg/m³ in growth management; η² = 0.092), and the March–April maximum persisted after winter was separated and after meteorological adjustment. However, at the three sites without a persistent local coarse-particle source, the early-spring PM₁₀ increment over urban stations was the lowest of all periods (−7.62 μg/m³), while local PM₁₀ and PM_2.5 increments peaked in July–September. In exploratory contrasts, the PM_2.5 increment was 2.3 μg/m³ higher on tillage/leveling days (p = 0.005; q = 0.063). NH₃ was governed mainly by site (partial η²: site 0.256, site × stage 0.145, stage 0.033; site means 8.6–37.0 ppb). The calendar-stage PM contrast largely reflects the regional seasonal cycle, whereas agricultural influences appear as operation day and warm-season local increments and as site-specific NH₃ levels.

Fine particulate matter (PM_2.5) in agricultural areas forms partly from gaseous precursors (NH₃, NO₂, and SO₂), yet in open fields ambient concentrations are strongly modulated by wind-driven dilution, which can obscure precursor–PM_2.5 relationships. This study compared concentration- and loading-rate-based interpretations of these relationships in Korean agricultural areas, evaluating the loading rate—concentration-scaled by a wind-speed-based air exchange rate—as a complementary indicator of pollutant loading at the monitoring site. Using a 547-day record (January 2024–June 2025) from eight monitoring sites, we examined hourly network-average concentrations and loading rates across four subsets (entire period, summer, non-summer, and high-PM events) with Pearson correlation, principal component analysis, and multiple linear regression. Concentration-based correlations among PM_2.5 and its precursors were weak and inconsistent, whereas loading-rate-based ones were strong and uniform (r ≥ 0.816). The stronger loading-rate correlations may reflect the dominant influence of wind speed. Diurnal patterns reinforced this point: concentrations were bimodal and fell during the windy daytime, while loading rates were unimodal and rose over the same hours, showing that lower concentrations need not imply reduced pollutant loading. NH₃ peaked earlier and higher in summer than the other precursors, suggesting a time-lagged rather than simultaneous link with PM_2.5. Multiple linear regression confirmed strong co-variation (R = 0.977–0.997) but was limited by multicollinearity, so its coefficients reflect relative co-variation rather than source contributions. The loading rate is therefore best used not on its own but as a complementary indicator of pollutant loading alongside concentration.

Air pollution monitoring in Korea has not yet been implemented in agricultural areas. Documenting air quality in purely agricultural areas is inherently valuable. This study compares agricultural air quality with urban air quality during two periods: (1) the entire measurement period and (2) high-PM episodes. To ensure broad spatial coverage, eight monitoring stations were installed in Yeoju, Nonsan, Naju, Gimhae, Hongcheon, Danyang, Muan, and Sangju. Real-time measurements of PM₁₀, PM_2.5, SO₂, and NOx were conducted continuously from March 2023 to December 2024. Over the entire measurement period, PM concentrations were similar in both agricultural and urban areas, but gaseous pollutants were lower in agricultural areas. PM levels were higher in agricultural areas during summer, whereas urban areas showed higher concentrations in other seasons. During high-PM episodes (29 days), all pollutants were significantly higher in urban areas, with PM_2.5 showing a greater difference than PM₁₀. Diurnal variations revealed that PM₁₀, PM_2.5, and NO₂ peaked in the morning and reached their lowest levels around 3 PM, with urban levels consistently higher than those in agricultural areas. SO₂ showed a different pattern, reaching its lowest concentration at 6 AM and peaking at noon in urban areas and at 6 PM in agricultural areas. This pattern closely followed temperature and wind speed variations.

As of 2019, the greenhouse gas emissions from agricultural byproduct incineration amounted to 15.83 thousand tons CO₂eq. Only CH₄ and N₂e O emissions are reported from agricultural byproduct incineration, with CO₂2 not being considered carbon neutral. The emission coefficients used to estimate greenhouse gases in this sector rely on the 1996 IPCC GL (Guidelines for National Greenhouse Gas Inventories) values and incorporate oxidation rates and nitrogen content for specific crops. However, there is a need for improvement as emission coefficients are applied without considering crop-specific characteristics. This study focuses on wheat as the target crop, with samples collected during the harvest season in June. To simulate real open burning sites, experiments were conducted using an experimental chamber constructed based on EPA method 5G (Determination of particulate matter emissions from wood heaters - dilution tunnel sampling location) and EPA-600/R-96-128 (Evaluation of Emission from the Open Burning Of Land-Clearing Debris). Sample gases were collected in Tedlar bags using a lung sampler (EPA Method 18) and analyzed via GC-FID to determine the concentrations of CH₄ and N₂O. The emission coefficients developed in this study for wheat agricultural byproduct incineration can serve as foundational data for estimating greenhouse gas emissions in the agricultural sector, enhancing the reliability of national inventories.

Ammonia is one of the precursor gases in the formation of particulate matter (PM) that reacts with nitrogen oxides and sulfur oxides in the atmosphere. Based on the Clean Air Policy Support System (CAPSS) of Korea, the annual ammonia emissions amounted to 261,207 tons in 2020 and the agricultural source (manure management sector) contributes the highest proportion of the ammonia inventory. However, the methodology for the study of ammonia emissions in Korea has some limitations regarding the representativeness of the sites selected and the reliability of the measurement method. In this study, we aimed to recalculate the ammonia emissions from the livestock industry in Korea using the UK’s estimation method, which uses the life cycle assessment of livestock manure. Three major animal types, i.e., cattle (beef cattle and dairy cows), pigs and chickens, and three major processes based on the manure flow, i.e., housing, manure storage and treatment and land application processes, were considered. The total ammonia emissions were estimated to be approximately 33% higher than the official ammonia emissions stated by the CAPSS. For the manure flow, the ammonia emissions were the highest from land application processes. The ammonia emissions from dairy cow and poultry manure were much higher than those stated by the CAPSS, while the emissions from beef cattle and pig manure showed similar levels. The methodology used in this study can offer an alternative approach to the ammonia emission estimation of the manure management sector in the agriculture industry of Korea. Korean emission factors based on the manure flow should be developed and applied in the future.

This study aimed to identify the characteristics of atmospheric pollutants emitted by agricultural activities and to evaluate factors that may cause harm to human health. For the research, atmospheric pollutants were measured over the course of a year in representative rice farming and field crop farming areas in South Korea. The results confirmed that the characteristics of atmospheric pollutants in agricultural areas are influenced by the nature of agricultural activities. Specifically, when comparing rice paddies and field crop areas, during summer, the correlation between oxidative potential and levoglucosan—a marker for biomass burning—weakens due to less burning activity in the rice-growing season, leading to lower oxidative potential despite different PM_2.5 across areas. The study also finds that methyl sulfonic acid, indicating marine influence, plays a big role in keeping oxidative potential low in summer. This suggests that the main causes of PM_2.5-related health risks in the area are from biomass burning and external sources, with burning being a significant factor in increasing oxidative potential. Based on these results, it is hoped that measures can be taken in the future to reduce atmospheric pollutants in agricultural areas.

Analysis of Air Pollutant Characteristics in Agricultural Areas Using Continuous Monitoring Data-Agricultural air pollution,Air quality monitoring,Gaseous pollutants,Particulate matter (PM-10,PM-2.5),Seasonal variation

89 (90 억원 년 건 재산피해 억원 년 건 재산피해), 2020 88 (548), 2021 78 (억원 년 건 재산피해 억원 으로 총 건이 발 53), 2022 99 (254) 453 생했으며 매년 평균 여건이 발생하고 있다 년간 주요 발 , 90. 5 화 원인으로는 전기적 요인 건 부주의 건 215 (47.5%), 107 미상 건 으로 나타났다 여기서 주목되는 점 (23.6%), 78 (17.2%) .