Nitrogen oxides (NO_X) in the atmosphere cause oxidation reactions with photochemical radicals and volatile organic compounds, leading to the accumulation of ozone (O₃). NO_X constitutes a significant portion of the NO_y composition, with nitrous acid (HONO) and nitric acid (HNO₃) following. HONO plays a crucial role in the reaction cycle of NO_X and hydrogen oxides. The majority of HNO₃ reduction mechanisms result from aerosolization through heterogeneous reactions, having adverse effects on humans and plants by increasing secondary aerosol concentrations in the atmosphere. The investigation of the formation and conversion mechanisms of HONO and HNO₃ is important; however, research in this area is currently lacking. In this study, we observed HONO, HNO₃, and their precursor gases were observed in the atmosphere using parallel-plate diffusion scrubber-ion chromatography. A 0-D box model simulated the compositional distribution of NO_y in the atmosphere. The formation reactions and conversion mechanisms of HONO and HNO₃ were quantified using reaction equations and reaction coefficients. Among the various mechanisms, dominant mechanisms were identified, suggesting their importance. According to the calculation results, the produce of HONO was predominantly attributed to heterogeneous reactions, excluding an unknown source. The sink processes were mainly governed by photolysis during daytime and reactions with OH radicals during nighttime. HNO₃ showed dominance in its production from N₂O₅, and in its conversion mechanisms primarily involving aerosolization and deposition.

We tried to estimate anthropogenic emission sources, including the contributions of neighboring regions, that affect the fine particle concentration (PM_2.5) in Daejeon using positive matrix factorization (PMF), concentration weight trajectory (CWT), and modified concentration weight trajectory (MCWT) models in a manner that might overcome the limitations of widely applied hybrid receptor models. Fractions of ion, carbonaceous compound and elements in PM_2.5 were 58%, 17%, and 3.6% during January and 49%, 17%, and 14.9% during May to June, respectively. The fraction of ions was higher during winter season, while the fraction of elements was higher during the other season. From the PMF model, seven factors were determined, including dust/soil, sea salt, secondary nitrate/chloride, secondary sulfate, industry, coal combustion, and vehicle sources. Secondary sulfate showed the highest contribution followed by secondary nitrate/chloride and vehicle sources. The MCWT model significantly improved the performance of regional contributions of the CWT model, which had shown a high contribution from the Yellow Sea where there are no emission sources. According to the MCWT results, regional contributions to PM_2.5 in the Daejeon metropolitan region were highest from eastern and southern China, followed by Russia, northeastern China, and Manchuria. We conclude that the MCWT model is more useful than the CWT model to estimate the regional influence of the PM_2.5 concentrations. This approach can be used as a reference tool for studies to further improve on the limitations of hybrid receptor models.

Odor is usually a complex mixture of various compounds. In many countries, odor complaints have been addressed using the air dilution olfactory method (ADOM) to reduce their malodor complaint. In this study, continuous monitoring of ammonia, hydrogen sulfide, and total volatile organic compounds (TVOC) using sensors was conducted in facilities for municipal and livestock wastewater treatment (LWT), and for food waste composting (FWC). Odor intensity was modelled by multivariate linear regression using sensor monitoring data with air dilution measured by the ADOM. In testing the performance of sensors in the lab, all three sensors showed acceptable values for linearity, accuracy, repeatability, lowest detection limit, and response time, so the sensors were acceptable for application in the field. In on-site real-time monitoring, the three sensors functioned well in the three environmental facilities during the testing period. Average ammonia and hydrogen sulfide concentrations were high in the LWT facility, while TVOC showed the highest concentration in the FWC facility. A longer sampling time is necessary for ammonia monitoring. Odor intensity from individual sensor data correlated well to complex odor measured by the ADOM. Finally, we suggest a protocol for field application of sensor monitoring and odor data reproduction.

Recently, precursor gases such as ammonia have sparked a growing interest in the secondary formation of particulate matter (PM). Most studies focus on urban areas and scientific data. Studies on precursor gases and PM emitted from agricultural sources are insufficient; thus, this paper presents a field monitoring study conducted from agricultural sources. To estimate the effect of precursor gases for PM_2.5 from naturally ventilated dairy barns, correlation analyses were conducted using real-time monitoring data on the mass concentrations of PM_2.5, NH₃, SO₂, NO₂, and H₂S and meteorological data. In addition to mass concentration, the emission and loading rates were used to closely analyze pollution status. The mass concentrations of PM_2.5 and gaseous compounds did not correlate well, whereas the mass emission rates for PM_2.5 and gaseous compounds (SO₂, NH₃, and NO₂) correlated well because the unit of the emission rate reflected the ventilation factor. The correlation coefficients between PM_2.5 and precursor gas emission rates ranged from 0.72 to 0.89 (R), with the SO₂ emission rate exhibiting the highest correlation coefficient (R = 0.89). This correlation implies that SO₂ from dairy farms is a dominant species among the gaseous precursors influencing the secondary formation of PM_2.5; alternatively, SO₂ and PM_2.5 are produced from the same sources. The ambient PM_2.5 loading rate and barn PM_2.5 emission rate—estimated by multivariate linear regression using the gaseous independent variables NH₃, SO₂, and NO₂—revealed high-correlation coefficients (0.60 and 0.92, respectively) with the measured data. At present, most studies investigating the precursor gases of PM in agricultural fields have focused on NH₃; however, this study suggests that SO₂ is a key factor in PM_2.5 pollution. To elucidate the secondary formation of PM from precursor gases in agricultural sources, particulate ammonium, sulfate, nitrate, and chloride, which were not measured in this study, as well as oxidants and intermediates, should be considered in future research.

Hybrid receptor models overestimate the contribution of background areas (no specific emission sources), like the Yellow Sea in Korea. This study aimed to improve model performances using Advanced Concentration Emission and Retention Time Weighted Trajectory (ACERWT). ACERWT was combined with a positive matrix factorization (PMF), back trajectory, and Regional Emission Inventory in Asia (REAS). The PMF receptor model used one year of data from Korea’s Central Air Environment Research Center. In the PMF receptor model, eight sources (dust/soil, secondary nitrate, biomass burning, vehicles, secondary sulfate, industry, coal combustion and sea salt) influenced PM_2.5 pollution at the receptor site (Daejeon, Korea). Secondary sulfate was the most dominant source, followed by secondary nitrate and vehicle sources. ACERWT results showed high contributions from China, Japan, and Korean regions, while the contribution from the Yellow Sea was significantly lower. Several regions, such as the eastern and south-eastern areas of China, the southern area of Taiwan, the western area of Tokyo, and the central area of Korea, showed high contributions due to large-scale emission facilities and industrial complexes. In this study, the ACERWT model significantly improved its performance regarding regional contributions to PM_2.5 pollution at the receptor site.

Nitrogen oxide (NOX) in the atmosphere causes oxidation reactions with photochemical radicals and volatile organic compounds, causing ozone (O3) accumulation. In the composition of NOy, NOX accounts for the highest portion, and followed by nitrous acid (HONO) and nitric acid (HNO3). HONO significantly contributes to the reaction cycle of NOX and hydrogen oxide (OH). The generation of OH radicals and nitric oxide by photolysis is the main HONO removal mechanism in the morning. The OH radicals generated at this time trigger O3 accumulation in the atmosphere, affecting photochemical smog in urban areas. HNO3 in the atmosphere is produced by the reaction between NO2 and OH during the day while N2O5 and H2O during night time. Aerosolization by heterogeneous reactions of HNO3 is the major mechanism of HNO3 reduction. Aerosolization (heterogeneous) reactions adversely affect humans and plants by increasing the secondary aerosol concentration in the atmosphere and lowering visibility; therefore understanding the conversion mechanism of HNO3 to aerosols is important. In this study, HONO, HNO3, and their precursor gases in the atmosphere were observed using parallel-plate diffusion scrubber-ion chromatography. And a 0-D box model simulated the compositional distribution of NOy in the atmosphere, and the formation reactions and conversion mechanisms of HONO and HNO3 were analyzed.Acknowledgments:This research was supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute (KEITI) funded by the Ministry of Environment (MOE)