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Article

Distribution and Characteristics of Ammonia Concentration by Region in Korea

by
In-Ho Song
1,2,
Hyun-Woong Kim
2,
Jong-Sung Park
2,
Seung-Myung Park
2,
Jae-Yun Lee
2,
Eun-Jung Nam
2,
Yong-Jae Lim
2,
Jung-Min Park
2,
Myung-Soo Yoo
2,
Seog-Yeon Cho
1 and
Hye-Jung Shin
2,*
1
Department of Environmental Engineering, Inha University, Incheon 22201, Republic of Korea
2
Air Quality Research Division, National Institute of Environmental Research, Incheon 22689, Republic of Korea
*
Author to whom correspondence should be addressed.
Atmosphere 2024, 15(9), 1120; https://doi.org/10.3390/atmos15091120
Submission received: 5 August 2024 / Revised: 31 August 2024 / Accepted: 5 September 2024 / Published: 14 September 2024
(This article belongs to the Section Air Quality)
Browse Figures
Versions Notes

Abstract

:
In this study, the characteristics of ammonia and their effects on secondary particulate matter (PM) formation were analyzed by region in Korea in 2020. The NH3 concentration was high in GJ (11.4 ppb), a neighboring agricultural area, followed by DJ (9.0 ppb) and SE (8.6 ppb), which are located in urban areas. On the other hand, BI (2.6 ppb) and JI (4.5 ppb), which are background regions, demonstrated a lower concentration than other areas. Seasonally, ammonia was high in spring and summer, and it generally increased when human activities are active. Therefore, it is believed that the ammonia in the atmosphere not only changes depending on local emissions, but also based on temperature-dependent phase distribution characteristics. For SE and GJ, regions with relatively high ammonia concentrations, investigations into the effect of ammonia on secondary PM formation were conducted. In both regions, the ammonium-to-sulfate mole ratio tended to increase with increasing ammonia or PM2.5 concentration. It can be assumed that the PM2.5 concentration increases as nitrates are formed under the ammonia-sufficient condition. The adjusted gas ratio is generally greater than 4, indicating that there is a lot of free ammonia. Thus, it is estimated that a reduction in ammonia would not be effective to restrain nitrate formation.

1. Introduction

In Korea, episodes of high particulate matter (PM) frequently occur due to the long-range transport of air pollutants from Northeast Asia, which is located in the upward wind region, and the influence of domestic emissions [1,2,3]. Additionally, public interest and concern about high levels of PM have been increasing. Thus, policies such as measures to improve air quality in the metropolitan area, regional air environment conservation ordinances, and the strengthening of PM2.5 national air quality standards (average annual concentration of 15 µg m−3 or less, 2018) are being promoted. However, the concentration of PM2.5 in Korea (18 µg m−3, as of 2021) is still higher than the air quality standards of the US (13.8 µg m−3), the UK (11 µg m−3), France (12 µg m−3), and the WHO (5 µg m−3) [4]. Therefore, the public is not satisfied with the improvements in air quality resulting from the strengthened policies.
PM2.5 is generated through both a chemical reaction of volatile organic compounds (VOCs), sulfur oxides (SOx), and nitrogen oxides (NOx) in the atmosphere and primary emission from various sources such as mobiles and industrial facilities [5,6,7]. In previous studies [8,9,10,11], it has been reported that secondary formation is the major process of PM2.5. In Korea, it has been reported that secondary PM accounts for about 72% of the total PM emissions [12]. Most of the secondary generated PM can affect malignant asthma, respiratory diseases, chronic bronchitis, pulmonary injury, heart and lung disease, and visibility degradation [13,14,15]. As interest in secondary PM has grown, research on gaseous precursors such as VOCs and NH3 has recently been actively conducted [16,17,18,19,20]. Ammonia, one of the precursors of PM formation, is a basic gaseous substance that is mainly emitted from agricultural substances such as fertilizer, soil, and livestock manure, as well as from exhaust gas and industrial activities [21,22]. The NH3 concentration in the atmosphere is closely related to temperature. Also, NH3 significantly contributes to the formation of secondary inorganic aerosols such as ammonium sulfate and ammonium nitrate by reacting with sulfuric acid and nitric acid [16,23,24]. Ammonium nitrate and ammonium sulfate produced via combination with NH3 have a longer residence time than ammonia in the atmosphere [21,25,26,27,28]. Thus, they can exist in the air for a longer period of time.
According to recent studies, unlike sulfur oxides and nitrogen oxides, ammonia emissions are increasing across the world, including in Korea [29,30,31]. As of 2020, Korea’s annual ammonia emission was 261,207 tons, with the largest amount of ammonia being emitted from the agricultural sector, which includes livestock [32]. Several previous studies [16,23,24] have suggested that atmospheric NH3 is converted into particulate ammonium and affects the concentration of PM. There is a need to manage ammonia emission sources to control the atmospheric PM concentration. Nevertheless, there are not many long-term observations of the atmospheric ammonia in East Asia, for which strong management policies are required due to the high concentrations of PM.
In this study, the characteristics of ammonia in Korea were identified according to region using the continuously measured data from January to December of 2020. Also, the effect of ammonia on the formation of secondary PM was analyzed using the adjusted gas ratio (AdjGR) and the ammonium-to-sulfate mole ratio ([NH4+]/[SO42−], simplified as A/S ratio here) in the atmosphere. Through this, we aimed to evaluate the distribution of ammonia in each region, the emission sources, and the contribution of ammonia to the generation of secondary particulate matter. These results can be used to understand the formation mechanism of high PM and to provide scientific evidence for policy making to reduce PM in Northeast Asia.

2. Materials and Methods

2.1. Sampling Sites and Period

From January to December 2020, ammonia concentrations were constantly measured at six air quality research centers. These centers were established in major regions, including background areas, in Korea to study the characteristics and formation mechanism of PM2.5. The physical and chemical properties such as ions, carbon, metal components, and particle size distribution in PM2.5 were continuously measured in all centers. Also, gaseous pollutants such as nitrogen oxides, sulfur oxides, and ammonia, which are precursors of secondary PM, were measured at the same locations. Figure 1 and Table 1 show the locations and characteristics of the research centers, along with the emission contributions of various ammonia sources [32]. Among those six regions, the Jeju (JI, 33°20′ N, 126°23′ E, 560 m a.s.l.) and Baengnyeong (BI, 37°57′ N, 124°37′ E, 153 m a.s.l.) island centers were established to be in background areas, and were used to understand the background concentrations of air pollutants and to characterize their long-range transport. The centers in Seoul (SE, 37°36′ N, 126°56′ E, 67 m a.s.l.) and Daejeon (DJ, 36°19′ N, 127°24′ E, 88 m a.s.l.) are located in densely populated urban areas, as shown in Table S1. The Gwangju (GJ, 35°13′ N, 126°50′ E, 39 m a.s.l.) center is located in a city surrounded by agricultural areas, so it is possible to identify these agricultural characteristics, while the Ulsan (US, 35°34′ N, 129°19′ E, 142 m a.s.l.) center is adjacent to a large industrial complex, so this site is used to understand the impact of local emission sources.

2.2. Measurement Methods

Considering the possibility of real-time continuous measurement, ease of equipment operation and management, and the reliability of measurement data, ammonia was measured in real time using the cavity ring down spectroscopy (CRDS, G2103, Picarro, Santa Clara, CA, USA) method among various ammonia measurement methods such as indophenol, chemiluminescence, and the electrochemical sensor method. Air was sampled at a flow rate of 1.9~2.1 lpm and injected into the cavity. Ammonia was measured at 1 s intervals, and the 1 h averaged value was used for further analysis. Additional information on equipment performance is provided in Table S2.
A measurement system that can minimize the hindrance to ammonia measurement was considered due to the high reactivity of ammonia and possibility of loss caused by adsorption to the inlet tube wall. According to a report by SilcoTek corporation [33] and von Bobrutzki et al. [34], PTFE (Teflon) was used as the inlet material to minimize adsorption/desorption loss during analysis under heating conditions below 40 °C. In addition, the inlet length was kept shorter than 1.5 m to minimize ammonia loss. Also, to minimize the impact of aerosol particles, a 47 mm Teflon filter was installed at the inlet and replaced weekly. The reliability of the measurement was ensured through monthly inlet cleaning, equipment management, and semi-annual calibration. Calibration was performed by multi-point ammonia gas (0~30 ppb) which was generated by diluting ammonia standard gas (10 ppm) with zero air using a mass flow controller. The purity of zero air gas was 99.999%.
The condition of the equipment was checked through a test before starting the measurement. The blank test result using zero gas was 0.25~1.51 ppb, and the detection limit of this method analyzing 5 ppb ammonia gas for 7 times was 0.32~0.69 ppb (Figure 2a). The R2 of the calibration curve was 0.9963~0.9995 with high linearity and correlation (Figure 2b).
In this study, PM2.5, ion components, and meteorological parameters were monitored along with ammonia. The ionic components were measured with an URG-9000D (Thermo) using an ion chromatography method. PM2.5 was measured using BAM1020 (Met one), which uses the beta ray absorption method. A detailed description of ions and PM2.5 measurement could be referred to many previous studies [35,36]. For GJ, the meteorological data measured on-site were used. Other centers did not have measuring equipment, so they used meteorological data of the nearby (1 to 6 km from each center) Korea Meteorological Administration [37].

3. Results and Discussion

3.1. Spatial Variations in Ammonia

Ammonia concentrations by region are shown in Table 2. The overall average concentration of ammonia was 6.8 ppb with the highest in GJ (11.4 ppb) followed by DJ (9.0 ppb), SE (8.6 ppb), JI (4.5 ppb), US (4.0 ppb), and BI (2.6 ppb) by region. It is presumed to be the highest because the GJ is in an urban area and is also adjacent to an agricultural area, which is a major source of ammonia (Figure 3). The second highest areas were the urban areas of DJ and SE, where there was high population density with high human activities and mobile emissions. In addition, the concentration of NOx mainly emitted from mobile pollutants was also high at 23.3 ppb and 26.0 ppb in SE and DJ, respectively (Table S3). The concentration of BI, the background area, was the lowest because there were no nearby emission sources. The average ammonia concentration in JI, another background area, was higher than BI. It is presumed that this was influenced by human and agricultural activities due to the higher population density than BI, as shown in Table S1 and Figure 1. In the case of US, an industrial area, where a large-scale petrochemical complex is located, the contribution of ammonia emitted from industrial processes was high [38,39], but the ammonia concentration was relatively lower than in other regions. Considering the distribution of ammonia concentrations according to the wind direction, the concentration tends to be high in the southeasterly wind from industrial complexes. However, the average concentration is not highly affected by the emission because the US site is located in the up-wind area of the industrial complex (Figure 3).
Ammonia concentrations were compared with the results of other studies and shown in Table 3. Ammonia concentrations in urban areas (SE, DJ, GJ) were lower than those in Beijing, China. However, they were higher than those in Guangzhou and Shanghai, located in southern China. Also, they were about 3 to 4 times higher than those in Houston, USA. The ammonia concentrations in the background areas (BI, JI) were generally lower than those in suburbs such as Shanghai, China and Ontario, Canada. Overall, ammonia concentrations in Korea are higher than those in North America and Europe. Also, in China, while there were regional differences, the overall ammonia concentrations were lower compared to other regions in Asia, such as Qatar and India. It is important that this study used long-term observations of ammonia with high-resolution measurement equipment for a year to obtain more reliable results.

3.2. Temporal Variations in Ammonia

3.2.1. Seasonal Variations in Ammonia

Table 4 shows the ammonia concentrations by seasons in each region. During the study period, the average ammonia concentrations by seasons in all regions were 7.6 ppb and 7.5 ppb in spring and summer, respectively, which is about 1.2 times higher than those in winter. According to previous studies, it is known that ammonia concentrations increase under high temperatures due to the decomposition of nitrogen fertilizers and ammonia volatilization [42,48,49]. Additionally, it is known that ammonia is affected by an increase in the phase transition of ammonium nitrate due to its low thermodynamic stability [9,14,42]. This study also showed similar results to those of previous studies (Table S4).
By region, BI, SE, GJ, and US showed the highest concentrations in spring with 3.5 ppb, 9.9 ppb, 12.6 ppb, and 4.1 ppb, respectively. It is estimated that this was due to the influence of high concentration cases mainly caused by influx or stagnation in spring rather than the effect of temperature [3,50,51]. In the case of GJ, it is presumed that ammonia emission characteristics according to agricultural activities in nearby areas were also reflected. On the other side, DJ and JI show the highest concentrations of 10.6 ppb and 5.7 ppb, respectively, in summer, which is presumed to reflect the case of volatilization by high temperature. Overall, the ammonia concentrations tended to be low in winter, when the temperature was the lowest in most region. But in the case of BI, the concentrations were also high in the winter season as in spring, it is presumed that the concentrations were influenced by external inflow due to long range transport (Figure S1).

3.2.2. Monthly Variations in Ammonia

The monthly concentrations of each region are shown in Figure 4. In SE, the concentration is high in March (10.5 ppb) and June (11.9 ppb). DJ appeared high in May (10.7 ppb) and June (13.9 ppb), and GJ showed high concentrations in May (14.9 ppb) and June (17.4 ppb). BI showed high concentrations in April (3.7 ppb) and June (3.6 ppb), and JI showed high concentrations in June (6.9 ppb) and July (6.9 ppb). Finally, US showed high concentrations in January (4.8 ppb) and June (4.9 ppb) as shown in Figure 4.
Ernst and Massey [52] reported that ammonia volatilization doubled when temperatures increased from 7.2 to 15.6 °C. Other studies also indicate that ammonia concentrations are affected by temperature [48,53]. As a result of the measurement, in June, when the temperature is generally high, ammonia concentration tends to the highest. It is assumed that the high temperature activates ammonia volatilization by gas phase conversion and decomposition of nitrogen fertilizer. However, in July and August, when temperatures were the highest, ammonia concentrations tended to be lower. It is presumed that there was a wash-out effect due to the overall high rainfall during this period as shown in Figure 4. Low summer concentrations of air pollutants due to rainfall have also been observed in previous studies [3,54]. The impact of humidity was also examined, but no clear trends were observed (Figures S2 and S3).

3.2.3. Diurnal Variations in Ammonia

Figure 5 shows the diurnal variations in ammonia concentrations in each region. In urban areas such as SE and DJ, ammonia tended to increase in the morning and evening. SE and DJ are highly affected by mobile emissions, and according to previous studies, ammonia emissions from mobile sources are reported to be high [55,56,57]. However, the diurnal variations in ammonia and NOx, which is mainly emitted from mobile sources, did not match in these two regions. It implies that ammonia is more affected by other emission sources, so the influence of mobile emissions appears to be relatively low. According to the national emission inventory in Korea [32], the highest contribution to ammonia emissions comes from sources classified as “others”. The others are composed of natural sources, fire, water bodies, and emissions from animals (humans), with the highest emissions from human activities [32]. Therefore, it is assumed that ammonia concentrations are relatively more affected by human activities than mobile emissions due to the high population density in SE and DJ.
In GJ, unlike other regions, it showed a single peak trend with the maximum value in the morning. Several previous studies [42,58,59] have reported an increase in the morning due to the influence of agricultural activities and soil emissions, so it is assumed that ammonia in GJ is also greatly affected by agricultural activities. In the background area, BI, there was not a clear diurnal variations in ammonia. In JI, another background area, ammonia concentrations gradually increased in the morning and decreased in the evening. It is assumed that the trend of ammonia concentrations change according to the diurnal temperature changes. In US, the ammonia concentrations increased from 7 a.m., showed the highest concentration (4.4 ppb) at 12 p.m., and then decreased, which is a pseudo characteristic of the urban area. However, unlike SE and DJ, there was no clear increase in the evening hours. In US, the population density and the concentration of NOx, an indicator of mobile emissions, were lower than those of other urban area. Consequently, it is estimated that US does not have a major emission source of ammonia compared to other regions.

3.3. Contribution to Secondary Aerosol Formation of Ammonia

To understand the state of ammonia excess and the importance of ammonia’s role in secondary PM formation, the ammonia adjusted gas ratio (AdjGR) was evaluated for SE and GJ, which have relatively high ammonia concentrations. Details about the HNO3 data used in this part such as measurement method and data verification are provided in the Supplementary Materials (Figure S4). Particulate nitrate exists in equilibrium with ammonia, ammonium, and gaseous nitric acid. In general, thermodynamic equilibrium in the atmosphere is non-linear, so time-averaged concentrations cannot be applied to the equilibrium equation. However, Pinder et al. [60] established a linear relationship between particulate nitrate, total sulfate (TS), total nitric acid (TN), and total ammonia (TA) in the winter in the eastern United States, and applied this equilibrium equation to the time-averaged concentrations of these components. Therefore, the indicator of the ammonia excess state was defined as follows, using the AdjGR proposed in the previous studies [19,60].
A d j G R = f r e e   a m m o n i a t o t a l   n i t r a t e = N H 3 m o l + [ N O 3 − ] ( m o l ) H N O 3 m o l + [ N O 3 − ] ( m o l )
Pinder et al. [60] reported that ammonia is in excess when AdjGR > 1. When AdjGR is 2, nitrate is reduced by 10% if ammonia is reduced by 20%, and when AdjGR is 4, nitrate is reduced by 5% if ammonia is reduced by 20%. Therefore, as the AdjGR increases, it has been reported that the contribution of ammonia to nitrate formation decreases due to ammonia excess condition [19,60,61,62].
During the entire study period, AdjGR showed 11.0 and 20.4 in SE and GJ, respectively. The monthly AdjGR were 6.0~6.4 for SE and 7.4~10.5 for GJ in winter (January and February), lower than in other seasons and even higher than 4 in all periods (Figure 6). As above, it is estimated that reductions in ammonia would not effectively restrain the nitrate formation in Korea due to ammonia excess condition.
Additionally, the relative ratio of [NO3−]/[SO42−] to [NH4+]/[SO42−] (simplified as A/S ratio here) was analyzed to confirm the preference of the secondary formation of nitrate by ammonia (Figure 7). During the periods with high NH3 concentrations, the analysis was conducted on March, when PM2.5 concentrations were also high for the same areas (SE, GJ) as the AdjGR part above. According to previous studies, ammonia affects the phase distribution of nitric acid to form a particle and contributes to nitrate formation [60]. In addition, it was reported that the state of ammonia excess can be estimated using the A/S ratio [19,63,64].
The average A/S ratios for SE and GJ were 1.94 and 1.58, respectively, higher than 1.5, which is the threshold for diagnosing the ammonia excess. The A/S ratio by ammonia level of SE was 1.75 when ammonia was less than 10 ppb, and it was increased to 2.06 in range of 10~20 ppb. Also, it was increased to 3.13 with over 20 ppb ammonia concentration. A/S of GJ was also 1.44 when ammonia was less than 10 ppb, and it was 1.83 in the range of 10~20 ppb. Also, it was increased to 2.00 with over 20 ppb ammonia concentration. In both SE and GJ, the A/S ratio tended to increase as the ammonia concentration increased. As a result of the A/S ratio for each PM2.5 concentration level, when the PM2.5 concentration was high exceeding 35 µg m−3, the A/S ratios for SE and GJ were high at 2.53 and 2.11, respectively. Therefore, it can be estimated that the PM2.5 concentration increases due to nitrate formation in the ammonia excess condition. Figure 7 shows cases of high-concentration PM2.5 in SE and GJ. In cases of increasing the relative concentration of nitrate to sulfate, PM2.5 concentrations also tend to rise. In such circumstances, ammonia concentrations showed a tendency to be maintained at relatively high levels.

4. Conclusions

The average concentration of NH3 by region in Korea was 6.8 ± 4.9 ppb. GJ, located near an agricultural area, showed the highest concentration at 11.4 ± 6.5 ppb, about 1.7 times higher than the overall average. The concentrations of ammonia in DJ and SE, which are urban area, were also high at 9.0 ± 3.9 ppb and 8.6 ± 3.5 ppb, respectively. In contrast, BI and JI, which are background regions with no major emission sources, had lower average concentrations of 2.6 ± 1.7 ppb and 4.5 ± 2.6 ppb, respectively. US, an industrial area, was expected to be high due to the influence of industrial emissions. However, the average concentration was as low as 4.0 ± 1.6 ppb because it is located upwind area of the industrial complex.
During the study period, the concentration of ammonia by seasons was generally higher in spring and summer than in other seasons. In spring, it is judged to be affected by agricultural activities, long range transport, or local stagnation of air flow by depending on each regional characteristic. In summer, the increase in ammonia emissions from waste and manure and the partitioning rate of ammonia to gas are increased causing high ammonia concentrations. However, ammonia concentrations tended to be low in summers. It is presumed that there was a wash-out effect due to the overall high rainfall during this period. Ammonia concentrations varied over time due to different emission sources such as human activities, traffic volume, agricultural activities, and industrial activities in Korea. Concentrations increased mainly in the morning and evening in urban areas (SE, DJ) due to human activities, and in GJ, which was affected by agricultural activities, the concentrations increased at dawn. BI, the background region, did not show a clear trend. The US in the industrial area showed a low ammonia concentration and diurnal variations due to the up-wind location of an industrial complex.
For SE and GJ, regions with relatively high ammonia concentrations, an analysis of the impact of ammonia on secondary PM2.5 formation was conducted. The A/S ratios in March, when both ammonia and PM2.5 concentrations were high, were 1.94 for SE and 1.58 for GJ. Both regions were in a condition of excessive ammonia, and the A/S ratio tended to increase with higher ammonia or PM2.5 concentrations. It is assumed that additional nitrate is possibly formed due to sufficient ammonia. The average AdjGR was 11.0 for SE and 20.4 for GJ, with the higher value in GJ due to agricultural activities, the main source of ammonia in Korea. Even in winter (January and February), which has the lowest AdjGR values, the ratios were 6.0~6.4 for SE and 7.4~10.5 for GJ, which is greater than 4, so the reduction in ammonia would not be effective to restrain the nitrate formation in Korea.
This study is significant in that it used observation data for all year long, unlike the short-term measurements of previous studies. Through the acquisition and analysis of high-resolution data for a year, the various level of temporal changes by region could be identified. If long-term data are accumulated in the future, highly reliable ammonia characteristic analysis will be possible. In addition, it would be able to contribute to improve the chemical model by providing reference data, which is necessary for the evaluation of a 3D model simulating the local formation and long-range transport of PM2.5. Through this, it will be attributed to establish PM2.5 reduction policies in Northeast Asia based on scientific data.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/atmos15091120/s1 [65,66,67,68,69,70,71,72], Table S1: population density by region in 2020; Table S2: performance of main parameters on selected instrument; Table S3: NOx concentration by region in 2020; Table S4: seasonal average concentrations of PM2.5 and nitrate in each region; Figure S1: location of BI and seasonal polar plot; Figure S2: distribution of NH3 concentration with meteorological data, (a) temperature, (b) humidity; Figure S3: distribution of NH3 concentration with temperature and humidity; Figure S4: comparison of correlations between measurement methods.

Author Contributions

Conceptualization, I.-H.S. and H.-J.S.; methodology, H.-J.S.; software, I.-H.S. and H.-J.S.; validation, I.-H.S.; formal analysis, I.-H.S.; investigation, I.-H.S., H.-W.K., J.-S.P. and S.-M.P.; resources, I.-H.S., H.-W.K., J.-S.P., S.-M.P. and J.-Y.L.; data curation, I.-H.S. and H.-W.K.; writing—original draft preparation, I.-H.S. and H.-W.K.; writing—review and editing, Y.-J.L., J.-M.P., M.-S.Y., S.-Y.C. and H.-J.S.; visualization, I.-H.S., H.-W.K. and E.-J.N.; supervision, H.-J.S. project administration, H.-J.S.; funding acquisition, H.-J.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institute of Environmental Research, funded by the Ministry of Environment of the Republic of Korea (Grant number: NIER-2020-03-01-004).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used in this study are available upon request. Interested parties may contact H.J.S. at [email protected] to inquire about access to the dataset. We are committed to promoting transparency and facilitating collaboration in research. Please provide details regarding the specific data or information you are interested in, and we will make reasonable efforts to share the relevant data, ensuring compliance with ethical and legal considerations.

Acknowledgments

The authors wish to extend their gratitude to all the staff of the National Institute of Environmental Research for supporting these research opportunities.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Locations of air quality research centers and contributions of individual emissions in each region in 2020.
Figure 1. Locations of air quality research centers and contributions of individual emissions in each region in 2020.
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Figure 2. (a) Blank and method detection limit (3σ, 300 s) and (b) calibration curves of NH3 measured at 6 monitoring sites.
Figure 2. (a) Blank and method detection limit (3σ, 300 s) and (b) calibration curves of NH3 measured at 6 monitoring sites.
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Figure 3. Wind rose and polar plots of NH3 in GJ (up) and US (down).
Figure 3. Wind rose and polar plots of NH3 in GJ (up) and US (down).
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Figure 4. The monthly variations in atmospheric NH3 concentrations and meteorological parameter (temp., RH, rainfall) in each site.
Figure 4. The monthly variations in atmospheric NH3 concentrations and meteorological parameter (temp., RH, rainfall) in each site.
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Figure 5. The diurnal variations in atmospheric NH3 and NOx in each site.
Figure 5. The diurnal variations in atmospheric NH3 and NOx in each site.
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Figure 6. Monthly AdjGR of SE and GJ.
Figure 6. Monthly AdjGR of SE and GJ.
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Figure 7. A/S ratio by concentration level of NH3 and PM2.5 in March at SE (up) and GJ (down).
Figure 7. A/S ratio by concentration level of NH3 and PM2.5 in March at SE (up) and GJ (down).
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Table 1. Regional research center information.
Table 1. Regional research center information.
RegionTypeLocation
Seoul, Korea (SE)Urban37°36′ N, 126°56′ E, 67 m a.s.l.
Daejeon, Korea (DJ)Urban36°19′ N, 127°24′ E, 88 m a.s.l.
Gwangju, Korea (GJ)Urban35°13′ N, 126°50′ E, 39 m a.s.l.
Baengnyeong, Korea (BI)Background37°57′ N, 124°37′ E, 153 m a.s.l.
Jeju, Korea (JI)Background33°20′ N, 126°23′ E, 560 m a.s.l.
Ulsan, Korea (US)Industrial35°34′ N, 129°19′ E, 142 m a.s.l.
Table 2. Annual average concentrations of NH3 from 2020 in each region.
Table 2. Annual average concentrations of NH3 from 2020 in each region.
Region NH3 Conc. (ppb)
AverageRange
Entire6.8 ± 4.90.0~50.0
SE8.6 ± 3.51.1~32.3
DJ9.0 ± 3.90.8~28.6
GJ11.4 ± 6.50.4~41.6
BI2.6 ± 1.70.0~13.8
JI4.5 ± 2.60.5~50.0
US4.0 ± 1.60.6~13.3
Table 3. Comparison of atmospheric NH3 concentrations to previous studies.
Table 3. Comparison of atmospheric NH3 concentrations to previous studies.
SiteTypePeriodAverage (ppb)S.D.Reference
KoreaAll′20.1~126.84.9This study
Seoul, KoreaUrban′20.1~128.63.5This study
Daejeon, KoreaUrban′20.1~129.03.9This study
Gwangju, KoreaUrban′20.1~1211.46.5This study
Baengnyeong, KoreaBackground′20.1~122.61.7This study
Jeju, KoreaBackground′20.1~124.52.6This study
Ulsan, KoreaIndustrial′20.1~124.01.6This study
Seoul, KoreaUrban′10.9~′11.810.94.3Phan et al. [40]
Beijing, ChinaUrban′15.9~′16.818.1-Pan et al. [41]
Chengdu, ChinaUrban′15.9~′16.811.1-Pan et al. [41]
Guangzhou, ChinaUrban′15.9~′16.87.6-Pan et al. [41]
Shanghai, ChinaUrban′13.7~′14.96.24.6Wang et al. [42]
Houston, USAUrban′10.2.12~3.12.41.2Gong [43]
Houston, USAUrban′10.8.5~9.253.12.9Gong [43]
Barcelona UB, SpainUrban′11.5.6~9.72.91.3Pandolfi et al. [44]
Barcelona CC, SpainUrban′11.5.13~6.287.42.8Pandolfi et al. [44]
Shanghai, ChinaRural′13.7~12
′14.3~6		12.49.1Wang et al. [42]
Haibei, ChinaRural′15.9~′16.84.7-Pan et al. [41]
Yongxing island, ChinaRural′15.9~′16.83.6-Pan et al. [41]
Ontario, CanadaRural′10.3.30~′11.3.294.7-Zbieranowski and Aherne [45]
Shanghai, ChinaIndustrial′14.1~617.69Wang et al. [42]
Industrial Zone, QatarIndustrial′16.2.29~3.3124.5-Alfoldy et al. [46]
Al Cornish, QatarTraffic′16.2.29~3.3125.0-Alfoldy et al. [46]
Madinat Khalifa, QatarTraffic′16.2.29~3.3117.9-Alfoldy et al. [46]
Delhi, IndiaTraffic′13.1~′15.1219.63.5Sharma et al. [47]
Fengqiu, ChinaFarmland′15.9~′16.822.1-Pan et al. [41]
Weinan, ChinaFarmland′15.9~′16.816.3-Pan et al. [41]
Shenyang, ChinaFarmland′15.9~′16.88.8-Pan et al. [41]
LhasaFarmland′15.9~′16.86.3 Pan et al. [41]
Table 4. Seasonal average concentrations of NH3 in each region.
Table 4. Seasonal average concentrations of NH3 in each region.
SiteSpringSummerFallWinter
Average
(ppb)		Range
(ppb)		Average
(ppb)		Range
(ppb)		Average
(ppb)		Range
(ppb)		Average
(ppb)		Range
(ppb)
Total7.6 ± 5.00.6~37.57.5 ± 5.50.0~50.06.2 ± 4.50.0~40.76.1 ± 4.50.0~36.4
SE9.9 ± 3.31.9~32.38.8 ± 3.51.8~22.58.4 ± 3.63.2~26.87.3 ± 3.11.1~21.5
DJ8.9 ± 3.81.1~25.310.6 ± 4.11.2~28.68.3 ± 3.70.8~26.38.1 ± 3.61.3~25.2
GJ12.6 ± 6.41.3~37.512.5 ± 7.50.8~41.610.4 ± 5.71.8~40.710.3 ± 6.10.4~36.4
BI3.5 ± 1.50.7~8.42.6 ± 1.40.0~12.21.8 ± 1.40.0~6.82.3 ± 1.80.0~13.8
JI5.6 ± 2.12.2~16.25.7 ± 3.60.7~50.04.2 ± 1.50.8~18.42.7 ± 1.30.5~8.9
US4.1 ± 1.60.6~8.73.9 ± 1.80.8~11.74.1 ± 1.51.0~13.34.1 ± 1.60.7~8.7
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Song, I.-H.; Kim, H.-W.; Park, J.-S.; Park, S.-M.; Lee, J.-Y.; Nam, E.-J.; Lim, Y.-J.; Park, J.-M.; Yoo, M.-S.; Cho, S.-Y.; et al. Distribution and Characteristics of Ammonia Concentration by Region in Korea. Atmosphere 2024, 15, 1120. https://doi.org/10.3390/atmos15091120

AMA Style

Song I-H, Kim H-W, Park J-S, Park S-M, Lee J-Y, Nam E-J, Lim Y-J, Park J-M, Yoo M-S, Cho S-Y, et al. Distribution and Characteristics of Ammonia Concentration by Region in Korea. Atmosphere. 2024; 15(9):1120. https://doi.org/10.3390/atmos15091120

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Song, In-Ho, Hyun-Woong Kim, Jong-Sung Park, Seung-Myung Park, Jae-Yun Lee, Eun-Jung Nam, Yong-Jae Lim, Jung-Min Park, Myung-Soo Yoo, Seog-Yeon Cho, and et al. 2024. "Distribution and Characteristics of Ammonia Concentration by Region in Korea" Atmosphere 15, no. 9: 1120. https://doi.org/10.3390/atmos15091120

APA Style

Song, I. -H., Kim, H. -W., Park, J. -S., Park, S. -M., Lee, J. -Y., Nam, E. -J., Lim, Y. -J., Park, J. -M., Yoo, M. -S., Cho, S. -Y., & Shin, H. -J. (2024). Distribution and Characteristics of Ammonia Concentration by Region in Korea. Atmosphere, 15(9), 1120. https://doi.org/10.3390/atmos15091120

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