Education on fine dust is a challenging field, as it must explain abstract phenomena and accompany the demands for behavioral changes. This research studied whether the adoption of augmented reality (AR) technology can effect change in student perspectives with a view to improving the attitudes of passive students regarding fine dust-related matters. With regard to student awareness, 94.0% of students responded that the issue of fine dust in Korea is severe; the higher the degree of interest they had in fine dust, the more severe they perceived the issue to be. On the perceived severity of fine dust in schools, 47.8% viewed it as severe; again, the level differed by the degree of interest. Students (80%) who received a traditional education on fine dust expressed dissatisfaction. The effect of using AR in experiential learning in fine dust environmental education has shown enhanced results compared to before receiving the education, notably in the group with a low degree of interest in fine dust and the group without prior experience in fine dust environmental education. Likewise, in the satisfaction rate for AR-based education on fine dust, 72.5% of participants responded that they had enjoyed the class, 75.9% showed active participation, and 80.0% felt that the content of the education was useful. Considering that the objective of fine dust environmental education is not based on understanding a theory but on maintaining individual health through practice in real life, the use of AR in fine dust environmental education as applied in this study may be interpreted as having a certain level of effect. Additionally, our results demonstrate that the use of AR in classes is effective in arousing students’ interest and inducing participation for better engagement in learning activities, which is, consequently, effective in enhancing the understanding of learning materials by students.

Agricultural activity greatly contributes to the secondary PM_2.5 concentrations by releasing relatively large amounts of ammonia emissions. Nonetheless, studies and air quality policies have traditionally focused on industrial emissions such as NOx and SOx. To compare them, this study used a three-dimensional modeling system (e.g., WRF/CMAQ) to estimate the effects of emission control policies of agricultural and industrial emissions on PM_2.5 pollution in Chungcheong, an agriculturally active region in Korea. Scenario 1 (S1) was designed to estimate the effect of a 30% reduction in NH₃ emissions from the agro-livestock sector on air pollution. Scenario 2 (S2) was designed to show the air quality under a mitigation policy on NOx, SOx, VOCs, and primary PM_2.5 from industrial sources, such as power plants and factories. The results revealed that monthly mean PM_2.5 in Chungcheong could decrease by 3.6% (1.1 µg/m³) under S1 with agricultural emission control, whereas S2 with industrial emission control may result in only a 0.7~1.1% improvement. These results indicate the importance of identifying trends of multiple precursor emissions and the chemical environment in the target area to enable more efficient air quality management.