Relationships Between PM2.5 and Its Precursor Gases in Agricultural Areas of South Korea Using a Loading-Rate-Based Analysis

Fine particulate matter (PM2.5) 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–PM2.5 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 PM2.5 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 PM2.5. 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.