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2026 Vol.68, Issue 4 Preview Page
Loading Rate Based Pollution Characteristics of Fine Particulate Matter and Gaseous Precursors in Agricultural Areas

부하속도 기반 농업지역 초미세먼지 및 가스상전구물질 오염 특성

Jeong-Deok Baeka
,
Sung-hyun Baeb
,
Yun-sik Shinc
,
Min-wook Kimd
,
Jin-ho Kime†
,
Il-hwan Seof
,
Ki-yeon Kimg
,
Hung-soo Jooh†
백 정덕a
,
배 성현b
,
신 윤식c
,
김 민욱d
,
김 진호e†
,
서 일환f
,
김 기연g
,
주 흥수h†
aMS Student, Dept. of Environmental Engineering, Anyang University
bBS Student, Dept. of Environmental and Energy Engineering, Anyang University
cPostdoctoral Researcher, Division of Climate Change, Department of Agricultural Environment, National Institute of Agricultural Science, RDA, Wanju 55365, Korea
dResearcher, Division of Climate Change, Department of Agricultural Environment, National Institute of Agricultural Science, RDA, Wanju 55365, Korea
eSenior Researcher, Division of Climate Change, Department of Agricultural Environment, National Institute of Agricultural Science, RDA, Wanju 55365, Korea
fProfessor, Dept. of Safety Engineering, Seoul National University of Science and Technology
gProfessor, Dept. of agricultural engineering, Jeonbuk National University
hProfessor, Dept. of Environmental and Energy Engineering, Anyang University
† Corresponding author Tel.: +82-63-238-2492 E-mail: water86@korea.kr†† Corresponding author Tel.: +82-31-463-1291 E-mail: jhoo@anyang.ac.kr
2026. pp. 37-49
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Abstract

Fine particulate matter (PM2.5) is a critical air pollutant affecting human health, ecosystems, and agricultural productivity. In agricultural areas, PM2.5 is emitted directly through farming activities and indirectly formed via gas–particle conversion involving sulfur dioxide (SO2), nitrogen dioxide (NO2), and ammonia (NH3). However, concentration-based assessments are strongly influenced by meteorological dilution in open agricultural environments, limiting their ability to represent pollutant transport and exposure. To address this limitation, this study applied a loading-rate approach integrating pollutant concentrations with wind-driven transport. Long-term monitoring was conducted at eight agricultural sites across South Korea from January 2024 to June 2025, with PM2.5, gaseous precursors, and meteorological parameters measured at 5-minute intervals. Loading rates were calculated using pollutant concentrations and air exchange rates, and February and August 2024 were selected for comparative analysis. Statistical analyses included principal component analysis, Pearson correlation, and multiple linear regression. Loading rates exhibited greater variability than concentrations and distinct diurnal patterns, with most pollutants peaking 1–2 hours after meteorological maxima. PM2.5 loading rates consistently clustered with SO2 and NO2, suggesting close statistical associations with secondary inorganic aerosol formation. Regression analysis showed high explanatory power for PM2.5 loading rates (R=0.97, p<0.001), identifying SO2 as the largest positive coefficient, while NO2 showed season-dependent significance and NH3 exhibited earlier peaks and time-lagged behavior. Overall, loading-rate metrics more effectively capture pollutant transport and exposure characteristics in agricultural environments and highlight the possible importance of sulfur-driven secondary formation pathways in PM2.5 management.

Keywords
Agricultural air quality
ammonia volatilization
particulate matter
meteorological parameters
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Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 68
  • No :4
  • Pages :37-49
  • Received Date : 2026-01-13
  • Revised Date : 2026-04-14
  • Accepted Date : 2026-04-14
  • DOI :https://doi.org/10.5389/KSAE.2026.68.4.037
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