High PM 2.5 Concentrations in a Small Residential City with Low Anthropogenic Emissions in South Korea

: High particulate matter (PM 2.5 ) concentrations have been considered a serious environmental issue in South Korea. Recent studies have focused mostly on metropolitan and industrial cities; however, high PM 2.5 episodes have also been frequently observed even in small– and middle-sized cities. Thus, in this study, PM 2.5 and its major chemical components were measured in a small residential city with low anthropogenic emissions for 2 years to identify the factors a ﬀ ecting the PM 2.5 concentrations. Overall, the average PM 2.5 concentration was 29.4 µ g m − 3 : about two times higher than the annual ambient air quality standard value. In winter, when the PM 2.5 concentrations were generally higher, relative humidity (RH) was signiﬁcantly correlated with both PM 2.5 mass and the PM 2.5 / PM 10 ratio, suggesting that high RH promoted the formation of secondary PM 2.5 . In addition, SO 42 − and NO 3 − were found to be correlated with both NH 4 + and K + in winter, indicating that biomass burning was an important source in this city. Water-soluble organic carbon (WSOC) was also highly correlated with elemental carbon (EC) and K + in fall and winter, when the burning of agricultural residues actively occurred. During high concentration episodes, NO 3 − exhibited the highest increase; nevertheless, other components (e.g., K + and organic carbon) also signiﬁcantly increased. These results suggest that a combination e ﬀ ect of active photochemical oxidation reactions and stagnant air can lead to high PM 2.5 concentration episodes in Chuncheon even serious NH 4 + surplus condition. However, when the Mann-Kendall trend analysis was used in this study, carbonaceous compounds and cationic components showed a decreasing trend, whereas the remaining constituents and PM 2.5 showed no trend during the sampling period of 22 months. The high RH measured in Chuncheon was statistically related with increases of NO 3 − , SO 42 − , NH 4 + , K + , and OC, episodically resulting in high PM 2.5 concentrations. Under conditions of high RH, we also observed a strong correlation between NO 3 − and K + (Pearson r = 0.74). These results suggest an important contribution of aged biomass burning to the high PM 2.5 concentrations detected in this city. This hypothesis is supported by the strong correlations between WSOC and EC (Pearson r = 0.58), and by those between WSOC and K + (Pearson r = 0.52), especially during fall and winter.


Introduction
Fine particulate matter (PM) is a major concern not only in South Korea, but also worldwide. It has been reported to be associated with increased hospitalization, emergency room visits, and mortality [1][2][3]. For this reason, the International Agency for Research on Cancer (IARC) has classified PM as carcinogenic to human beings. In particular, PM with aerodynamic diameter <2.5 µm (PM 2.5 ) can stay in the atmosphere for several weeks, allowing its long-range transport and effectively reducing visibility [4]. In addition, PM 2.5 is directly involved with respiratory and cardiovascular diseases as it can penetrate deep into small airways [5][6][7]. Notably, PM 2.5 consists of ionic compounds, elemental carbon (EC), primary and secondary organic matter, sea salt, and other trace elements [8]. Secondary inorganic ions (e.g., NO 3 − , SO 4 2− , and NH 4 + ) are the main components of PM 2.5 , generally accounting for >30% of this PM fraction [9]. Organic aerosol (OA) contributes to about 20-50% of PM 2.5 mass, and 40-80% of it is presumed to be water-soluble [10,11].

Chemical Analysis
The Teflon filters were stored under controlled conditions of temperature (20 °C) and RH (50%) for at least 24 h before and after sampling; then, they were weighed at least twice using an analytical balance (Sartorius CP225D, readability = 10 −5 g) after removing static electricity using a static eliminator (StaticMaster 2U500, NRD, USA). PM2.5 mass concentrations were calculated based on the mass increase observed for each filter divided by sampled air volume.
To determine the carbonaceous compounds, a small piece (1.5 cm 2 ) was punched out from each quartz filter and analyzed using the National Institute of Occupational Safety and Health (NIOSH) method 5040 for thermal-optical analysis in which a sample is heated in pure helium (He) and subsequently in 2% oxygen (O2) and He atmosphere [21,22]. The temperature gradually increased up to 870 °C and decreased to 550 °C in the pure He condition, and after which it gradually increased again to 870 °C in the 2% O2 atmosphere (Table 1). Some organic carbonaceous aerosols that were not volatilized in the He stage remained in the filter as a pyrolyzed fraction, which was called pyrolyzed OC (PC). Thus, the total OC was calculated by adding the PC to the amount of carbon measured at the He stage, and the total EC was calculated by subtracting the PC from the carbon measured at the He-O2 stage. Calibration of OC and EC analysis was performed using a sucrose standard (50 μg-C/25 μL), and the recovery rate ranged from 100 to 102%. Average system blank values were 0.04 ± 0.04 μg cm −2 and 0.05 ± 0.04 μg cm −2 for OC and EC, respectively.
The remaining portion of quartz filter was then placed into a conical tube filled with 30 mL of ultrapure water and extracted in a sonicator for 1 h. The extract was then filtered using a 0.2-μm PTFE syringe filter (Pall Life Sciences), and the WSOC was quantified using a total organic carbon (TOC) analyzer (Sievers 5310C Laboratory, Boulder, CO, USA). TOC analyzer is based on the oxidation of Meteorological data, including temperature, wind speed, wind direction, relative humidity (RH), and solar radiation, were also measured every 5 min at the sampling site using a meteorological tower (Vantage Pro2, Davis Instrument, Hayward, CA, USA).

Chemical Analysis
The Teflon filters were stored under controlled conditions of temperature (20 • C) and RH (50%) for at least 24 h before and after sampling; then, they were weighed at least twice using an analytical balance (Sartorius CP225D, readability = 10 −5 g) after removing static electricity using a static eliminator (StaticMaster 2U500, NRD, USA). PM 2.5 mass concentrations were calculated based on the mass increase observed for each filter divided by sampled air volume.
To determine the carbonaceous compounds, a small piece (1.5 cm 2 ) was punched out from each quartz filter and analyzed using the National Institute of Occupational Safety and Health (NIOSH) method 5040 for thermal-optical analysis in which a sample is heated in pure helium (He) and subsequently in 2% oxygen (O 2 ) and He atmosphere [21,22]. The temperature gradually increased up to 870 • C and decreased to 550 • C in the pure He condition, and after which it gradually increased again to 870 • C in the 2% O 2 atmosphere (Table 1). Some organic carbonaceous aerosols that were not volatilized in the He stage remained in the filter as a pyrolyzed fraction, which was called pyrolyzed OC (PC). Thus, the total OC was calculated by adding the PC to the amount of carbon measured at the He stage, and the total EC was calculated by subtracting the PC from the carbon measured at the He-O 2 stage. Calibration of OC and EC analysis was performed using a sucrose standard (50 µg-C/25 µL), and the recovery rate ranged from 100 to 102%. Average system blank values were 0.04 ± 0.04 µg cm −2 and 0.05 ± 0.04 µg cm −2 for OC and EC, respectively. The remaining portion of quartz filter was then placed into a conical tube filled with 30 mL of ultrapure water and extracted in a sonicator for 1 h. The extract was then filtered using a 0.2-µm PTFE syringe filter (Pall Life Sciences), and the WSOC was quantified using a total organic carbon (TOC) analyzer (Sievers 5310C Laboratory, Boulder, CO, USA). TOC analyzer is based on the oxidation of organic compounds to form CO 2 using UV radiation and a chemical oxidizing agent (NH 4 ) 2 S 2 O 8 , and the CO 2 is measured using a selective membrane-based conductivity detection technique. The concentration of the total inorganic carbon (TIC) is first determined, and the total carbon (TC) content is measured after the oxidation of the organic compounds. Then, the concentration of the total organic carbon (TOC) is calculated as the difference between TC and TIC [23].
In this study, we analyzed both anions (i.e., NO 3 − and SO 4 2− ) and cations (i.e., Na + , NH 4 + , K + , Ca 2+ , and Mg 2+ ). The filters were first placed in a conical tube filled with 10 mL of ultrapure water and then extracted using a sonicator during 4 h at 60 • C. Afterward, the extract was filtered using a 0.45-µm PTFE syringe filter (Pall Life Sciences) and was analyzed by ion chromatography (IC) ( Table S1 of the Supplementary Material). Sodium carbonate (Na 2 CO 3 ) and methanesulfonic acid solutions were used as eluents for the anion and cation analysis, respectively. For IC analysis, calibration was performed by injecting five different concentrations of standard solution, and r 2 was higher than 0.9993. All instruments used for the sampling and analyses were previously washed with Alconox and ultrapure water. Field blanks (FB) were collected once every six samples, and the method detection limit (MDL) was calculated as three times the standard deviation of these field blanks. Concentration values lower than the MDL were substituted with 0.5 × MDL. The relative percent differences (RPD) between the triplicate (or duplicate) analyses were also obtained. The QA/QC results are shown in Table 2.

Meteorological Data and Other Pollutants
Meteorological data including temperature, wind speed, wind direction, and relative humidity were measured every 5 min at the sampling site using a meteorological tower (Vintage Pro2, DAVIS Inc., California, CA, USA). The concentrations of PM 10 and NO 2 were obtained from the national air quality monitoring station located about 1.5 km south of the PM 2.5 sampling site. PM 10 and NO 2 Atmosphere 2020, 11, 1159 5 of 19 were measured using beta attenuation and chemiluminescence methods, respectively. More detailed measurement methods can be found in Air Pollution Monitoring Network Installing and Operation Guidelines [24].

Backward Trajectories
Three-day backward trajectories were calculated using the NOAA HYSPLIT with GDAS (Global Data Assimilation System) meteorological data, which consist in 3-h, global 1 • latitude by 1 • longitude data sets of the pressure surface. The back-trajectories were then calculated every 2 h for the 24 h-averaged samples; moreover, arrival height of 500 m was considered to describe the regional transport meteorological pattern.

Statistical Analysis
Most of the statistical analysis including correlation and linear regression analysis was conducted using the SPSS (Statistical Package for the Social Sciences, Ver. 23, IBM, Armonk, NY, USA). However, to evaluate the trend of concentration for each PM 2.5 component, the Mann-Kendall analysis was performed using Excel data analysis (XLSTAT). In the Mann-Kendall test, each data value was compared to all subsequent data values. The Mann-Kendall statistic, S, was initially assumed to be 0, and incremented by 1 if data from a later time period was higher than a data value from an earlier time period, or decremented by 1 if the data from a later time period was lower than a data value sampled earlier [25]. The final S was given by Equation (1). where: A very high positive S and a very high negative S values indicate an increasing and a decreasing trends, respectively. The variance of S, VAR(S), and a normalized test statistic Z were then calculated by Equations (2) and (3), respectively.
where, n is the number of data points, g is the number of tied groups, and t p is the number of data points in the p th group.
Negative and positive Z values indicated the decreasing and increasing trends, respectively. If the p-value was less than the level of a significance, α, the null hypothesis, H 0 indicated that there is no trend in the series is rejected.

General Trends
The average PM 2.5 concentration during the study period was 29.4 (±16.8) µg m −3 (Table 3): about two times higher than the current annual NAAQS of South Korea (note that the annual PM 2.5 NAAQS changed from 25 µg m −3 to 15 µg m −3 in 2018). In addition, approximately 24% of the samples exceeded the current daily standard of 35 µg m −3 . The seasonal averaged PM 2.5 values were the highest in winter, followed by spring, fall, and summer ( Figure 2, Table 3; note that spring, summer, fall, and winter are indicated as March-May, June-August, September-November, and December-February, respectively). The same trend was observed by other researches in South Korea [16,26]. Of the two winters included in the study period, that between 2016 and 2017 showed higher average PM 2.  The Mann-Kendall trend analysis method was used for the mass of PM 2.5 and its chemical constituents. Many constituents including carbonaceous compounds (OC, EC, and WSOC) and cationic components (Na + , NH 4 + , and K + ) showed a decreasing trend during the sampling period, whereas the remaining constituents and PM 2.5 showed no trend at a significance level of 0.05 (Table 4). Carbonaceous compounds were measured from November 2016 to October 2017; therefore, the decreasing trend reflects the seasonal variation-higher concentration in late fall and winter and lower concentration in summer ( Figure 2). The sampling period of about 22 months was not long enough to determine the temporal trend over years, thus, there is a need for long-term monitoring in the future.  During the whole sampling period, there were significant negative correlations between the PM2.5 concentrations and temperature (Pearson r = −0.289, p-value = 0.001) and wind speed (Pearson r = −0.332, p-value < 0.001), and a statistical significant multiple linear regression was identified based on the wind speed and temperature data (Equation (4)): PM2.5 concentrations generally increased in winter when the wind speed was low.
In this study, seven ionic constituents were determined and measured: their total contribution to PM2.5 mass was found to be 28.5%. The average concentrations of NO3 − , SO4 2− , and NH4 + at the KNU site were 2.0 (±2.7) μg m −3 , 2.2 (±1.8) μg m −3 , and 2.9 (±1.7) μg m −3 , respectively ( Table 3). The contribution of NH4 + to PM2.5 mass (12.7% ± 13.2%) was the highest among the seven ionic constituents, followed by SO4 2− (9.2% ± 7.4%) and NO3 − (7.2% ± 7.2%). As anticipated, the proportion of SO4 2− and NO3 − among the ionic compounds was enhanced in summer and in winter, respectively ( Figure 3). Meanwhile, the proportion of NH4 + has generally decreased in winter and increased in spring. K + , which is typically used as a biomass burning marker, then increased in late fall and winter and was not abundant enough to be detected between May and September, along with Mg 2+ and Ca 2+ . There was a positive correlation between Mg 2+ and Ca 2+ (Pearson r = 0.58, p-value< 0.001), indicating that they were affected by the same factors such as crustal dust. The highest average concentrations of Mg 2+ and Ca 2+ were obtained in spring (Table 3), probably because the soils that are frozen during winter are thawed in spring and subsequently suspended from the surface to the atmosphere [17]. During the whole sampling period, there were significant negative correlations between the PM 2.5 concentrations and temperature (Pearson r = −0.289, p-value = 0.001) and wind speed (Pearson r = −0.332, p-value < 0.001), and a statistical significant multiple linear regression was identified based on the wind speed and temperature data (Equation (4)): PM 2.5 concentrations generally increased in winter when the wind speed was low.
In the above equation, T a and WS indicate the atmospheric temperature ( • C) and the wind speed (m s −1 ), respectively. Both of these variables and a constant in Equation (4) were statistically significant (p-value < 0.001).
In this study, seven ionic constituents were determined and measured: their total contribution to PM 2.5 mass was found to be 28.5%. The average concentrations of NO 3 − , SO 4 2− , and NH 4 + at the KNU site were 2.0 (±2.7) µg m −3 , 2.2 (±1.8) µg m −3 , and 2.9 (±1.7) µg m −3 , respectively ( Table 3). The contribution of NH 4 + to PM 2.5 mass (12.7% ± 13.2%) was the highest among the seven ionic constituents, followed by SO 4 2− (9.2% ± 7.4%) and NO 3 − (7.2% ± 7.2%). As anticipated, the proportion of SO 4 2− and NO 3 − among the ionic compounds was enhanced in summer and in winter, respectively ( Figure 3). Meanwhile, the proportion of NH 4 + has generally decreased in winter and increased in spring. K + , which is typically used as a biomass burning marker, then increased in late fall and winter and was not abundant enough to be detected between May and September, along with Mg 2+ and Ca 2+ . There was a positive correlation between Mg 2+ and Ca 2+ (Pearson r = 0.58, p-value< 0.001), indicating that they were affected by the same factors such as crustal dust. The highest average concentrations of Mg 2+ and Ca 2+ were obtained in spring (Table 3), probably because the soils that are frozen during winter are thawed in spring and subsequently suspended from the surface to the atmosphere [17].   [27] identified the possible source of Na + using the Na + /Ca 2+ ratio because the two main sources include marine aerosol and crustal dust. In this study, a higher concentration of Na + than Ca 2+ (Table 3), resulted in an average Na + /Ca 2+ ratio of 10.2 ± 11.8. The Na + /Ca 2+ ratio was high, showing 24.

Sourcing the Measured Species
Correlation coefficients of 7 ionic compounds were identified (Table 5). NO3 − was correlated with all other ionic constituents, and the highest correlation coefficient was observed with K + . SO4 2− showed the strongest correlation with NH4 + which also correlated with NO3 − , indicating the existence  [27] identified the possible source of Na + using the Na + /Ca 2+ ratio because the two main sources include marine aerosol and crustal dust. In this study, a higher concentration of Na + than Ca 2+ (Table 3), resulted in an average Na + /Ca 2+ ratio of 10.2 ± 11.8. The Na + /Ca 2+ ratio was high, showing 24.  [27] identified the possible source of Na + using the Na + /Ca 2+ ratio because the two main sources include marine aerosol and crustal dust. In this study, a higher concentration of Na + than Ca 2+ (Table 3), resulted in an average Na + /Ca 2+ ratio of 10.2 ± 11.8. The Na + /Ca 2+ ratio was high, showing 24.

Sourcing the Measured Species
Correlation coefficients of 7 ionic compounds were identified (Table 5). NO3 − was correlated with all other ionic constituents, and the highest correlation coefficient was observed with K + . SO4 2− showed the strongest correlation with NH4 + which also correlated with NO3 − , indicating the existence

Sourcing the Measured Species
Correlation coefficients of 7 ionic compounds were identified ( of (NH 4 ) 2 SO 4 and NH 4 NO 3 in the PM 2.5 . Na + was rather weakly but statistically correlated with NO 3 − , NH 4 + , K + , and Ca 2+ , suggesting that it was possibly affected by biomass burning and crustal dust. K + was highly correlated with NO 3 − , but it showed a relatively weak correlation with SO 4 2− , Na + , NH 4 + , and Mg 2+ , which indicates that KNO 3 was one of the major constituents of the PM 2.5 . Here, we calculated an NH 4 + availability index: J (Equation (5)) ( Figure S1 of the Supplementary Material) [29]. The value of this index generally exceeded 100%, indicating an NH 4 + surplus and the basicity of SO 4 2− and NO 3 − . In this city, Chuncheon, a large portion of land cover is represented by agricultural areas. From there, significant amounts of NH 3 are emitted due to fertilizer application and cattle farms.  Figure 5). In cities with size and emission characteristics similar to Chuncheon, NH 3 concentrations were reportedly higher in spring and lower in fall and winter [30]. In South Korea, NH 3 has been observed to be lower in summer than in spring due to the occurrence of intensive monsoon-related raining episodes [30]. The poorer correlation observed between the two same variables in spring, summer, and fall ( Figure 5) suggest that NH 3 remained excessive even when combined with H 2 SO 4 and HNO 3 and, hence, it likely existed also in other forms (e.g., NH 4 Cl) [31]. Ammonia can react with hydrochloric acid to form NH 4 Cl [32,33], and according to Du et al. (2010) [31], NH 4 Cl is a common constituent of aerosols in non-sulfate NH 4 + , although NH 4 NO 3 is more favorably formed than NH 4 Cl. Unfortunately, Cl was not measured in this study. Therefore, the possible existence of NH 4  OC concentrations were relatively higher in Chuncheon than in other cities of South Korea, although their ECs were comparable [35,36], resulting in high OC/EC ratios (average = 9.6 ± 4.5). OC corresponded to approximately 40% of PM2.5 mass, ranging from 36.5% in winter to 42.4% in spring. However, OC concentrations were the highest in winter and the lowest in fall (Table 3). Moreover, the OC/EC ratios were about two times higher in summer (16.1 ± 5.0 in average of ratio) compared to the other seasons (8.0 ± 2.6), suggesting a major presence of secondary OC (SOC) in summer [37]. The correlation coefficient between OC and EC was also determined to be lower in summer (Pearson r = 0.68) than in the other seasons (Pearson r = 0.82) ( Figure S2 of the Supplementary Material), likely indicating that a significant portion of the SOC was produced in summer. The high OC/EC ratios observed in all seasons implied the presence of other major sources besides mobile sources. The OC/EC ratios of vehicle exhaust emissions typically range from 1.0 to 4.2, while those of solid fuel combustions (including biomass and coal burning) are in a much higher range [37][38][39][40][41]. Using the EC tracer method (SOC = OCtot − [OC/EC]pri), first suggested by Turpin and Huntzicker (1995) [42], we calculated the average POC and SOC concentrations as 5.3 (±2.4) μg m −3 and 3.9 (±2.5) μg m −3 , respectively. The [OC/EC]pri indicates the OC/EC ratio directly emitted from combustion sources, which has often been estimated from the minimum OC/EC ratio [42]. In this study, the minimum OC/EC ratio for the month was used as the [OC/EC]pri for each month. The POC concentrations were comparable to the SOC concentrations in summer and fall, while they have significantly exceeded SOC values in spring and winter ( Figure S3 of the Supplementary Material). The average WSOC concentration was 4.4 (±2.4) μg m −3 , and the contribution of WSOC to OC ranged from 36.2% in fall to 57.5% in spring (no WSOC data were available for the summer season).

Effect of Humidity
Previous studies have shown that RH affects the gas-particle portioning of semi-volatile species, including NH3, HNO3, HCl, and some organic acids [43][44][45]. A large number of lakes and reservoirs OC concentrations were relatively higher in Chuncheon than in other cities of South Korea, although their ECs were comparable [35,36], resulting in high OC/EC ratios (average = 9.6 ± 4.5). OC corresponded to approximately 40% of PM 2.5 mass, ranging from 36.5% in winter to 42.4% in spring. However, OC concentrations were the highest in winter and the lowest in fall (Table 3). Moreover, the OC/EC ratios were about two times higher in summer (16.1 ± 5.0 in average of ratio) compared to the other seasons (8.0 ± 2.6), suggesting a major presence of secondary OC (SOC) in summer [37]. The correlation coefficient between OC and EC was also determined to be lower in summer (Pearson r = 0.68) than in the other seasons (Pearson r = 0.82) ( Figure S2 of the Supplementary Material), likely indicating that a significant portion of the SOC was produced in summer. The high OC/EC ratios observed in all seasons implied the presence of other major sources besides mobile sources. The OC/EC ratios of vehicle exhaust emissions typically range from 1.0 to 4.2, while those of solid fuel combustions (including biomass and coal burning) are in a much higher range [37][38][39][40][41]. Using the EC tracer method (SOC = OC tot − [OC/EC] pri ), first suggested by Turpin and Huntzicker (1995) [42], we calculated the average POC and SOC concentrations as 5.3 (±2.4) µg m −3 and 3.9 (±2.5) µg m −3 , respectively. The [OC/EC] pri indicates the OC/EC ratio directly emitted from combustion sources, which has often been estimated from the minimum OC/EC ratio [42]. In this study, the minimum OC/EC ratio for the month was used as the [OC/EC] pri for each month. The POC concentrations were comparable to the SOC concentrations in summer and fall, while they have significantly exceeded SOC values in spring and winter ( Figure S3 of the Supplementary Material). The average WSOC concentration was 4.4 (±2.4) µg m −3 , and the contribution of WSOC to OC ranged from 36.2% in fall to 57.5% in spring (no WSOC data were available for the summer season).

Effect of Humidity
Previous studies have shown that RH affects the gas-particle portioning of semi-volatile species, including NH 3 , HNO 3 , HCl, and some organic acids [43][44][45]. A large number of lakes and reservoirs are located within Chuncheon, where the sampling site is located; therefore, fog episodes tend to be frequent and RH tends to be high. As indicated by Equation (1), PM 2.5 was negatively correlated with temperature and wind speed, but it was not correlated with RH during the whole sampling period. However, when considering only the data obtained during winter, the PM 2.5 concentrations and the PM 2.5 /PM 10 ratio showed both a significant positive correlation with RH (Pearson r = 0.69 between PM 2.5 concentrations and RH, Pearson r = 0.79 between PM 2.5 /PM 10 ratio and RH, both p-values < 0.001) ( Figure S4  in spring, summer, fall, and winter, respectively) also suggest the effective conversion of gaseous NO 2 to NO 3 − during winter.
Although the formation of secondary sulfate and secondary organic aerosols in the aqueous phase is significant in summer [49,50], in this study, there was no statistical correlation between RH and PM 2.5 and its chemical constituents in summer. This could be because the number of samples in summer (Table 3) were not enough to show clearly the effect of RH, or it may be difficult to determine the influence of RH on PM 2.5 and/or its constituents because the RH was relatively consistent in summer (the coefficient of variation (standard deviation/average) was 0.13 and 0.21 in summer and winter, respectively). Therefore, there is a need for further research on this.

Effect of Biomass Burning
The outskirts of Chuncheon (where the sampling site is located) consist mainly of forests and agricultural areas. There, the open burning of agricultural residue and household wastes frequently occurs. WSOC served as a proxy for secondary OC in many previous studies [14,51,52], but it is also known to be directly emitted, along with K + , during biomass burning [15,51,53]. In this study, WSOC was significantly correlated with EC (Pearson r = 0.58) and K + (Pearson r = 0.52). This correlation became much stronger during fall and winter (Pearson r = 0.79 with EC and Pearson r = 0.83 with K + , both p-values < 0.001), when the burning of agricultural residue actively occurred. These results suggest that biomass burning was an important source of carbonaceous PM 2.5 in Chuncheon, especially during cold months. Particles derived from the burning of fresh biomass mostly consisted of K + , Cl − , and OC, but can be readily converted to KNO 3 and K 2 SO 4 via heterogeneous reactions during their transport [54,55]. SO 4 2− (Pearson r = 0.63) and NO 3 − (Pearson r = 0.74) were determined to be highly correlated with K + in winter, suggesting the importance of aerosol produced from the burning of aged biomass. In addition, the deliquescence relative humidity (DRH) of KCl is 84.3%, which was lower than that of KNO 3 (97.4%) and K 2 SO 4 (92.5%) [56,57]. Therefore, at RH > ∼84%, chlorine gases can be released to the atmosphere, while KNO 3 and K 2 SO 4 still exist in their solid forms, resulting in a strong correlation of K + with both NO 3 − and SO 4 2− . These results suggest that biomass burning and high RH might have a synergistic effect, enhancing PM 2.5 concentrations in the city.

High Concentration Episode
In this study, a high concentration episode (HCE) was defined for daily PM 2.5 concentrations higher than the 24-h NAARS (35 µg m −3 ). In total, 33 samples were identified as corresponding to a HCE. Of these 13, 12, 6, and 2 samples were obtained in winter, spring, fall, and summer, respectively. The average PM 2.5 concentration was 47.9 (±11.1) µg m −3 during the HCE, ranging from 36.3 to 83.8 µg m −3 . Among them, the samples with the highest PM 2.5 concentrations were those obtained on highest concentrations on January 19, 2017, indicating that the gas-particle partitioning of HNO 3 and heterogeneous reactions in the nitrate and sulfate formation were facilitated by low atmospheric temperatures (−2.4 • C: the lowest temperature observed among HCE) and relatively high RH (77%: the average RH was 63% during winter) [58]. NH 4 + was also high, but its increase was not noticeable China [16,59].
Atmosphere 2020, 11, x FOR PEER REVIEW 12 of 19 concentrations, the components of these samples showed different concentrations. On February 4, 2017, the OC, EC, K + , and NH4 + concentrations all showed an increase ( Figure 2); moreover, the HCE sample collected on this day was characterized by the highest OC/EC ratio (OC/EC = 9.7), possibly indicating biomass burning as a source of PM2.5. On the other hand, NO3 − and SO4 2− reached their highest concentrations on January 19, 2017, indicating that the gas-particle partitioning of HNO3 and heterogeneous reactions in the nitrate and sulfate formation were facilitated by low atmospheric temperatures (−2.4°C: the lowest temperature observed among HCE) and relatively high RH (77%: the average RH was 63% during winter) [58]. NH4 + was also high, but its increase was not noticeable compared to those of NO3 − and SO4 2− , resulting in an NH4 + deficit (NH4 + availability index, J = 69.7%). On January 19, the SO4 2− concentration (9.3 μg m −3 ) was approximately two times higher than on February 4, 2017 (4.4 μg m −3 ), despite the similar PM2.5 concentrations of the corresponding samples. The increase of SO4 2− concentrations was possibly supported by the back-trajectories that originated from northeastern China and Mongolia on January 19, while the back-trajectories were much shorter and stayed for a longer time over the ocean on February 4 ( Figure 6). Previous studies have also highlighted an increase of SO4 2− concentrations in parallel with long-range transport from China [16,59]. All of the PM2.5 components significantly increased during HCEs (by a factor of 1.3 to 2.4, compared to non-HCEs) (Figure 7). NO3 − was determined to be the most important component for the HCE samples, and its concentration increased by approximately 2.4 times; moreover, this component showed the strongest correlation with PM2.5 mass (Pearson r = 0.77) among all components in the HCE samples, suggesting that the source increasing NO3 − should have been crucial for reaching the high PM2.5 concentration observed in Chuncheon. With respect to mass, the highest enhancement was observed for OC: it increased by 4.6 μg m −3 (Figure 7). K + was also significantly higher in the HCE, rather than in the non-HCE samples (by a factor of 1.7), although its contribution to PM2.5 mass was imperceptible.  (Figure 7). K + was also significantly higher in the HCE, rather than in the non-HCE samples (by a factor of 1.7), although its contribution to PM 2.5 mass was imperceptible. In order to identify the characteristics of each HCE, we divided them into four groups: NO3 −driven, OC-driven, crustal element-driven, and summer HCE. Notably, all the 10 components (shown in Table 3) were analyzed only in 14 out of the 33 HCE samples. Six samples were classified as NO3 − -driven HCE. These showed significantly enhanced K + and NO3 − concentrations (Figure 8), as well as the highest six K + concentrations among all the HCE samples. All HCE samples showed a significant increase in K + concentration (Figure 7; nevertheless, the values of this parameter were particularly high in the six NO3 − -driven HCE samples (0.45 ± 0.08 μg m −3 , Figure 8, suggesting the active formation of inorganic aerosol (e.g., NH4NO3 and KNO3) as a result of biomass burning. Of these six samples, the three collected in spring (on March 16, 22, and 28, 2016) have showed PM2.5 concentrations somewhat different from those of the four collected in winter: a distinct increase in Na + and NH4 + occurred under low RH conditions (Figure 8; notably, no carbonaceous compounds were analyzed in these samples). High Na + and NH4 + concentrations might have been possibly derived from the trajectories of air-parcels that had a long residence time over the ocean ( Figure 4) and intense emissions of NH3 in spring [30], respectively.
Two HCE samples collected on 17 December 2016, and 4 January 2017, had very high OC fractions, contributing to 47.3% and 36.3% of the total PM2.5, respectively, and were classified as OCdriven ( Figure 8). The nine PM2.5 constituents analyzed in this study contributed to 83.7% of the total PM2.5 mass of the HCE samples collected on 17 December 2016, indicating that metallic elements directly emitted from primary sources were insignificant, while secondary formation contributed considerably to the high PM2.5 concentrations.
On 29 March 2017, crustal and/or ocean elements (e.g., Na + , Mg 2+ , and Ca 2+ ) clearly increased, showing much higher concentrations (∑3 elements = 2.9 μg m −3 ) and contributed to a higher fraction of the total PM2.5 mass (∑3 elements = 5.4%) compared to the other HCE samples (0.8 μg m −3 and 1.7%) (Figure 8). Two HCE samples collected in summer (on 15 and 30 June 2017) showed an increase in the SO4 2− and OC concentrations (Figure 8). The OC/EC ratios were also very high (13.1 and 9.6 on 15 and 30 June, respectively), and most of the endpoints of the 72-h backward trajectories were stagnant over the Yellow Sea ( Figure 6). These results suggest that a combination effect of active photochemical oxidation reactions and stagnant air can lead to high PM2.5 concentration episodes in Chuncheon even during summer.
Back-trajectories were also calculated for the bottom 10% samples (when PM2.5 < 11 μg m −3 ), and they were relatively long and originated in the north, east, and south ( Figure S5 of the Supplementary Material) whereas the back-trajectories for HCEs were short and originated in the west. In order to identify the characteristics of each HCE, we divided them into four groups: NO 3 − -driven, OC-driven, crustal element-driven, and summer HCE. Notably, all the 10 components (shown in Table 3

Comparison with Other Studies
The characteristics of the chemical constituents of PM2.5 varied in different regions. When the PM2.5 concentration was high, the air masses generally transported from eastern China and Seoul (the capital of South Korea) before arriving at Chuncheon [28,60,61]. Because Baengryeong island, located in the northernmost part of Korea, is the nearest region to China, it is the national background monitoring site in South Korea. Therefore, the PM2.5 characteristics in eastern China, Baengryeong island, Seoul, and Chuncheon were compared. The concentrations of PM2.5 and its ionic components were much higher than those in other sites ( Table 6). One of the notable results is that both the OC concentration and the OC/EC ratio (9.6 as in average of ratio) were significantly high in this study when compared to that in Beijing, China (3.7), Baengryeong island (3.5), and Seoul (2.4) ( Table 6). Considering the low OC/EC ratio generally in the metropolitans, such as Beijing and Seoul due to the large contribution of mobile sources [37][38][39][40][41], the significantly higher OC/EC ratio in Chuncheon than in Baengryeong island indicates the importance of biomass burning and/or large fractions of aged aerosol. Because PM2.5 generally increased with the long-range transport from China to Baengryeong island and Seoul, SO4 2− greatly increased in the haze episode [62]. However, in this study, NO3 − was the most important constituent along with K + and OC especially under the high RH condition, suggesting that the formation of secondary inorganic and organic components and biomass burning were the important processes for the high PM2.5 episode. In a recent study performed in Beijing, China [63], high nitrate to sulfate ratio (2.2) was observed, which increased up to 2.7 during haze events (Table 6). In this study, an average of nitrate to sulfate ratio was 0.9 was obtained, which increased to 1.3 for HCEs, indicating that the increase in NO3 − was greater than that of SO4 2− and other components and that NO3 − was concentrated as the PM2.5 increased. Back-trajectories were also calculated for the bottom 10% samples (when PM 2.5 < 11 µg m −3 ), and they were relatively long and originated in the north, east, and south ( Figure S5 of the Supplementary Material) whereas the back-trajectories for HCEs were short and originated in the west.

Comparison with Other Studies
The characteristics of the chemical constituents of PM 2.5 varied in different regions. When the PM 2.5 concentration was high, the air masses generally transported from eastern China and Seoul (the capital of South Korea) before arriving at Chuncheon [28,60,61]. Because Baengryeong island, located in the northernmost part of Korea, is the nearest region to China, it is the national background monitoring site in South Korea. Therefore, the PM 2.5 characteristics in eastern China, Baengryeong island, Seoul, and Chuncheon were compared. The concentrations of PM 2.5 and its ionic components were much higher than those in other sites ( Table 6). One of the notable results is that both the OC concentration and the OC/EC ratio (9.6 as in average of ratio) were significantly high in this study when compared to that in Beijing, China (3.7), Baengryeong island (3.5), and Seoul (2.4) ( Table 6). Considering the low OC/EC ratio generally in the metropolitans, such as Beijing and Seoul due to the large contribution of mobile sources [37][38][39][40][41], the significantly higher OC/EC ratio in Chuncheon than in Baengryeong island indicates the importance of biomass burning and/or large fractions of aged aerosol. Because PM 2.5 generally increased with the long-range transport from China to Baengryeong island and Seoul, SO 4 2− greatly increased in the haze episode [62]. However, in this study, NO 3 − was the most important constituent along with K + and OC especially under the high RH condition, suggesting that the formation of secondary inorganic and organic components and biomass burning were the important processes for the high PM 2.5 episode. In a recent study performed in Beijing, China [63], high nitrate to sulfate ratio (2.2) was observed, which increased up to 2.7 during haze events (Table 6). In this study, an average of nitrate to sulfate ratio was 0.9 was obtained, which increased to 1.3 for HCEs, indicating that the increase in NO 3 − was greater than that of SO 4 2− and other components and that NO 3 − was concentrated as the PM 2.5 increased.

Conclusions
Different policies should be applied to reduce regional PM 2.5 concentrations by taking into account the unique characteristics of the correspondent PM 2.5 generation mechanisms. Most PM 2.5 studies in South Korea have been conducted in large and industrial cities, and consistent PM 2.5 policies (e.g., reduction of diesel vehicles) are being implemented all over the country. This study was carried out in Chuncheon, a small residential city that has frequently shown high PM 2.5 concentrations despite very low anthropogenic emissions. The average PM 2.5 concentration (29.4 ± 16.8 µg m −3 ) was found to be approximately two times higher than the NAAQS of 15 µg m −3 . By comparing our data with previous ones collected in the same city during 2013 and 2014, we noted that SO 4 2− significantly decreased, while NH 4 + considerably increased, resulting in a serious NH 4 + surplus condition. However, when the Mann-Kendall trend analysis was used in this study, carbonaceous compounds and cationic components showed a decreasing trend, whereas the remaining constituents and PM 2.5 showed no trend during the sampling period of 22 months. The high RH measured in Chuncheon was statistically related with increases of NO 3 − , SO 4 2− , NH 4 + , K + , and OC, episodically resulting in high PM 2.5 concentrations. Under conditions of high RH, we also observed a strong correlation between NO 3 − and K + (Pearson r = 0.74). These results suggest an important contribution of aged biomass burning to the high PM 2.5 concentrations detected in this city. This hypothesis is supported by the strong correlations between WSOC and EC (Pearson r = 0.58), and by those between WSOC and K + (Pearson r = 0.52), especially during fall and winter. Approximately 24% of the samples exceeded the daily standard of 35 µg m −3 ; in particular, NO 3-showed the highest increment in the HCE (high concentration episode) samples, along with K + and OC. Notably, two HCE samples showing significant increases in OC and SO 4 2− were observed during summer, when the residence time of the back-trajectories over the Yellow Sea were relatively long, compared with the back-trajectories for the other HCE sample. Back-trajectories for the bottom 10% samples were relatively long and originated in the north, east, and south, whereas the back-trajectories for HCEs were short and originated in the west. When the PM 2.5 characteristics of this study were compared with those in Beijing, China, Seoul, Korea (the capital of South Korea), and Baengryeong island (the national background monitoring site), both the OC concentration and the OC/EC ratio were significantly high. In general, the results obtained from the HCE samples and comparison with other studies suggest that the formation of secondary inorganic and organic aerosol and biomass burning were the two most important factors contributing to the high PM 2.5 concentrations in Chuncheon.
Funding: This research was funded by a grant from the Ministry of Environment, Republic of Korea, and by a grant from the National Research Foundation of Korea (NRF-2017K1A3A1A12073373 and NRF-2020R1A2C2013445). This work was also supported by 2018 Research Grant (PoINT) from Kangwon National University. We would like to thank the Central Laboratory of Kangwon National University for helping with chemical analysis.