Analysis of PM2.5 inorganic and organic constituents to resolve contributing sources in Seoul, South Korea and Beijing, China and their possible associations with cytokine IL-8.

China and South Korea are the most polluted countries in East Asia due to significant urbanization and extensive industrial activities. As neighboring countries, collaborative management plans to maximize public health in both countries can be helpful in reducing transboundary air pollution. To support such planning, PM2.5 inorganic and organic species were determined in simultaneously collected PM2.5 integrated filters. The resulting data were used as inputs to positive matrix factorization, which identified nine sources at the ambient air monitoring sites in both sites. Secondary nitrate, secondary sulfate/oil combustion, soil, mobile, incinerator, biomass burning, and secondary organic carbon (SOC) were found to be sources at both sampling sites. Industry I and II were only identified in Seoul, whereas combustion and road dust sources were only identified in Beijing. A subset of samples was selected for exposure assessment. The expression levels of IL-8 were significantly higher in Beijing (167.7 pg/mL) than in Seoul (72.7 pg/mL). The associations between the PM2.5 chemical constituents and its contributing sources with PM2.5-induced inflammatory cytokine (interleukin-8, IL-8) levels in human bronchial epithelial cells were investigated. For Seoul, the soil followed by the secondary nitrate and the biomass burning showed increase with IL-8 production. However, for the Beijing, the secondary nitrate exhibited the highest association with IL-8 production and SOC and biomass burning showed modest increase with IL-8. As one of the highest contributing sources in both cities, secondary nitrate showed an association with IL-8 production. The soil source having the strongest association with IL-8 production was found only for Seoul, whereas SOC showed a modest association only for Beijing. This study can provide the scientific basis for identifying the sources to be prioritized for control to provide effective mitigation of particulate air pollution in each city and thereby improve public health.

Source apportionment of PM2.5 using positive matrix factorization (PMF) at a rural site in Korea.

The sources of different pollutants contributing to ambient fine particles (PM2.5) on Daebu Island, Korea, were estimated. Twenty four hour integrated filter samples were collected from May 21-November 1, 2016, and analyzed for organic carbon, elemental carbon, ions, and trace elements. Positive matrix factorization was conducted on the PM2.5 chemical speciation data from the samples to define the pathways and sources of PM2.5 at the sampling site. A total of 80 samples and 24 chemical species were used to run the model and a total of nine sources were identified: secondary sulfate (29.0%), mobile (22.0%), secondary nitrate (13.2%), oil combustion (10.1%), coal combustion (9.4%), aged sea salt (7.9%), soil (5.6%), non-ferrous smelting (1.7%), and industrial activity (1.1%). Conditional probability and potential source contribution functions were then used to determine whether these sources were local or came from pollutants transported over long-range distances. The anthropogenic sources came from local emissions and originated from both industrialized and metropolitan areas, whereas the secondary inorganic aerosols were strongly influenced by the long-range transport of air pollutants from Shandong and Jiangsu provinces in China.

Emission of greenhouse gases from waste incineration in Korea.

Greenhouse gas (GHG) emission factors previously reported from various waste incineration plants have shown significant variations according to country-specific, plant-specific, and operational conditions. The purpose of this study is to estimate GHG emissions and emission factors at nine incineration facilities in Korea by measuring the GHG concentrations in the flue gas samples. The selected incineration plants had different operation systems (i.e., stoker, fluidized bed, moving grate, rotary kiln, and kiln & stoker), and different nitrogen oxide (NOx) removal systems (i.e., selective catalytic reduction (SCR) and selective non-catalytic reduction (SNCR)) to treat municipal solid waste (MSW), commercial solid waste (CSW), and specified waste (SW). The total mean emission factors for A and B facilities for MSW incineration were found to be 134 ± 17 kg CO2 ton-1, 88 ± 36 g CH4 ton-1, and 69 ± 16 g N2O ton-1, while those for CSW incineration were 22.56 g CH4 ton-1 and 259.76 g N2O ton-1, and for SW incineration emission factors were 2959 kg CO2 ton-1, 43.44 g CH4 ton-1 and 401.21 g N2O ton-1, respectively. Total emissions calculated using annual incineration for MSW were 3587 ton CO2-eq yr-1 for A facility and 11,082 ton CO2-eq yr-1 for B facility, while those of IPCC default values were 13,167 ton CO2-eq yr-1 for A facility and 32,916 ton CO2-eq yr-1, indicating that the emissions of IPCC default values were estimated higher than those of the plant-specific emission factors. The emission of CSW for C facility was 1403 ton CO2-eq yr-1, while those of SW for D to I facilities was 28,830 ton CO2-eq yr-1. The sensitivity analysis using a Monte Carlo simulation for GHG emission factors in MSW showed that the GHG concentrations have a greater impact than the incineration amount and flow rate of flue gas. For MSW incineration plants using the same stoker type in operation, the estimated emissions and emission factors of CH4 showed the opposite trend with those of NO2 when the NOx removal system was used, whereas there was no difference in CO2 emissions.

ROS-generating/ARE-activating capacity of metals in roadway particulate matter deposited in urban environment.

In this study we investigated the possible causal role for soluble metal species extracted from roadway traffic emissions in promoting particulate matter (PM)-induced reactive oxygen species (ROS) production and antioxidant response element (ARE) promoter activation. To this end, these responses have been evaluated in alveolar macrophage and epithelial lung cells that have been exposed to 'Unfiltered', 'Filtered' and 'Filtered+Chelexed' water extracts of PM samples collected from the roadway urban environments of Thessaloniki, Milan and London. Except for Thessaloniki, our results demonstrate that filtration resulted in a minor decrease in ROS activity of the fine PM fraction, suggesting that ROS activity is attributed mainly to water-soluble PM species. In contrast to ROS, ARE activity was mediated predominantly by the water-soluble component of PM present in both the fine and coarse extracts. Further removal of metals by Chelex treatment from filtered water extracts showed that soluble metal species are the major factors mediating ROS and ARE activities of the soluble fraction, especially in the London PM extracts. Finally, utilizing step-wise multiple-regression analysis, we show that 87% and 78% of the total variance observed in ROS and ARE assays, respectively, is accounted for by changes in soluble metal concentration. Using a statistical analysis we find that As, Zn and Fe best predict the ROS-generating/ARE-activating capacity of the near roadway particulate matter in the pulmonary cells studied. Collectively, our findings imply that soluble metals present in roadside PM are potential drivers of both pro- and anti-oxidative effects of PM in respiratory tract.

Assessing the role of chemical components in cellular responses to atmospheric particle matter (PM) through chemical fractionation of PM extracts.

In order to further our understanding of the influence of chemical components and ultimately specific sources of atmospheric particulate matter (PM) on pro-inflammatory and other adverse cellular responses, we promulgate and apply a suite of chemical fractionation tools to aqueous aerosol extracts of PM samples for analysis in toxicity assays. We illustrate the approach with a study that used water extracts of quasi-ultrafine PM (PM0.25) collected in the Los Angeles Basin. Filtered PM extracts were fractionated using Chelex, a weak anion exchanger diethylaminoethyl (DEAE), a strong anion exchanger (SAX), and a hydrophobic C18 resin, as well as by desferrioxamine (DFO) complexation that binds iron. The fractionated extracts were then analyzed using high-resolution sector field inductively coupled plasma mass spectrometry (SF-ICPMS) to determine elemental composition. Cellular responses to the fractionated extracts were probed in an in vitro rat alveolar macrophages model with measurement of reactive oxygen species (ROS) production and the cytokine tumor necrosis factor-α (TNF-α). The DFO treatment that chelates iron was very effective at reducing the cellular ROS activity but had only a small impact on the TNF-α production. In contrast, the hydrophobic C18 resin treatment had a small impact on the cellular ROS activity but significantly reduced the TNF-α production. The use of statistical methods to integrate the results across all treatments led to the conclusion that sufficient iron must be present to participate in the chemistry needed for ROS activity, but the amount of ROS activity is not proportional to the iron solution concentration. ROS activity was found to be most related to cationic mono- and divalent metals (i.e., Mn and Ni) and oxyanions (i.e., Mo and V). Although the TNF-α production was not significantly affected by the chelexation of iron, it was greatly impacted by the removal of organics with the C18 resin and all other metal removal methods, suggesting that iron is not a critical pathway leading to TNF-α production, but a wide range of soluble metals and organic compounds in particulate matter play a role. Although the results are specific to the Los Angeles Basin, where the samples used in the study were collected, the method employed in the study can be widely employed to study the role of components of particulate matter in in vitro or in vivo assays.

An in vitro alveolar macrophage assay for the assessment of inflammatory cytokine expression induced by atmospheric particulate matter.

Exposures to air pollution in the form of particulate matter (PM) can result in excess production of reactive oxygen species (ROS) in the respiratory system, potentially causing both localized cellular injury and triggering a systemic inflammatory response. PM-induced inflammation in the lung is modulated in large part by alveolar macrophages and their biochemical signaling, including production of inflammatory cytokines, the primary mechanism via which inflammation is initiated and sustained. We developed a robust, relevant, and flexible method employing a rat alveolar macrophage cell line (NR8383) which can be applied to routine samples of PM from air quality monitoring sites to gain insight into the drivers of PM toxicity that lead to oxidative stress and inflammation. Method performance was characterized using extracts of ambient and vehicular engine exhaust PM samples. Our results indicate that the reproducibility and the sensitivity of the method are satisfactory and comparisons between PM samples can be made with good precision. The average relative percent difference for all genes detected during 10 different exposures was 17.1%. Our analysis demonstrated that 71% of genes had an average signal to noise ratio (SNR) ≥ 3. Our time course study suggests that 4 h may be an optimal in vitro exposure time for observing short-term effects of PM and capturing the initial steps of inflammatory signaling. The 4 h exposure resulted in the detection of 57 genes (out of 84 total), of which 86% had altered expression. Similarities and conserved gene signaling regulation among the PM samples were demonstrated through hierarchical clustering and other analyses. Overlying the core congruent patterns were differentially regulated genes that resulted in distinct sample-specific gene expression "fingerprints." Consistent upregulation of Il1f5 and downregulation of Ccr7 was observed across all samples, while TNFα was upregulated in half of the samples and downregulated in the other half. Overall, this PM-induced cytokine expression assay could be effectively integrated into health studies and air quality monitoring programs to better understand relationships between specific PM components, oxidative stress activity and inflammatory signaling potential.

Fine particle air pollution and mortality: importance of specific sources and chemical species.

BACKGROUND: While exposure to ambient fine particles <2.5 µm in aerodynamic diameter (PM2.5) has well-established health effects, there is limited quantitative evidence that links specific sources of PM2.5 with those effects. This study was designed to examine the risks of exposure to chemical species and source-specific PM2.5 mass on mortality in Seoul, Korea, a highly populated city. METHODS: We compare daily mortality counts with PM2.5 chemical speciation data collected every 3 days, as well as nine sources of PM2.5 mass resolved by a positive matrix factorization receptor model, from March 2003 through November 2007. A Poisson generalized linear model incorporating natural splines was used to evaluate associations of PM2.5 chemical species and sources with mortality. RESULTS: PM2.5 mass and several chemical species were associated with mortality. Organic carbon, elemental carbon, and lead were associated with mortality outcomes when using multipollutant models adjusted for other chemical species levels. Source-apportioned PM2.5 derived from mobile sources (ie, gasoline and diesel emissions) and biomass burning was associated with respiratory mortality and cardiovascular mortality, respectively. There were moderate associations of industry and of roadway emissions with cardiovascular mortality. CONCLUSIONS: Local combustion sources may be particularly important contributors to PM2.5, leading to adverse health effects.

Spatial and temporal variation in fine particulate matter mass and chemical composition: the Middle East Consortium for Aerosol Research Study.

Ambient fine particulate matter (PM2.5) samples were collected from January to December 2007 to investigate the sources and chemical speciation in Palestine, Jordan, and Israel. The 24-h PM2.5 samples were collected on 6-day intervals at eleven urban and rural sites simultaneously. Major chemical components including metals, ions, and organic and elemental carbon were analyzed. The mass concentrations of PM2.5 across the 11 sites varied from 20.6 to 40.3 µg/m(3), with an average of 28.7 µg/m(3). Seasonal variation of PM2.5 concentrations was substantial, with higher average concentrations (37.3 µg/m(3)) in the summer (April-June) months compared to winter (October-December) months (26.0 µg/m(3)) due mainly to high contributions of sulfate and crustal components. PM2.5 concentrations in the spring were greatly impacted by regional dust storms. Carbonaceous mass was the most abundant component, contributing 40% to the total PM2.5 mass averaged across the eleven sites. Crustal components averaged 19.1% of the PM2.5 mass and sulfate, ammonium, and nitrate accounted for 16.2%, 6.4%, and 3.7%, respectively, of the total PM2.5 mass. The results of this study demonstrate the need to better protect the health and welfare of the residents on both sides of the Jordan River in the Middle East.

Understanding the sources and composition of the incremental excess of fine particles across multiple sampling locations in one air shed.

Well-designed health studies and the development of effective regulatory policies need to rely on an understanding of the incremental differences in particulate matter concentrations and their sources. Although only a limited number of studies have been conducted to examine spatial differences in sources to particulate matter within an air shed, routine monitoring data can be used to better understand these differences. Measurements from the US EPA Chemical Speciation Network (CSN) collected between 2002-2008 were analyzed to demonstrate the utility of regulatory data across three sites located within 100 km of each other. Trends in concentrations, source contribution, and incremental excesses across three sites were investigated using the Positive Matrix Factorization model. Similar yearly trends in chemical composition were observed across all sites, however, excesses of organic matter and elemental carbon were observed in the urban center that originated from local emissions of mobile sources and biomass burning. Secondary sulfate and secondary nitrate constituted over half of the PM2.5 with no spatial differences observed across sites. For these components, the excess of emissions from industrial sources could be directly quantified. This study demonstrates that CSN data from multiple sites can be successfully used to derive consistent source profiles and source contributions for regional pollution, and that CSN data can be used to quantify incremental differences in source contributions of across these sites. The analysis strategy can be used in other regions of the world to take advantage of existing ambient particulate matter monitoring data to better the understanding of spatial differences in source contributions within a given air shed.

Is replacing missing values of PM2.5 constituents with estimates using machine learning better for source apportionment than exclusion or median replacement?

East Asian countries have been conducting source apportionment of fine particulate matter (PM2.5) by applying positive matrix factorization (PMF) to hourly constituent concentrations. However, some of the constituent data from the supersites in South Korea was missing due to instrument maintenance and calibration. Conventional preprocessing of missing values, such as exclusion or median replacement, causes biases in the estimated source contributions by changing the PMF input. Machine learning (ML) can estimate the missing values by training on constituent data, meteorological data, and gaseous pollutants. Complete data from the Seoul Supersite in 2018 was taken, and a random 20% was set as missing. PMF was performed by replacing missing values with estimates. Percent errors of the source contributions were calculated compared to those estimated from complete data. Missing values were estimated using a random forest analysis. Estimation accuracy (r2) was as high as 0.874 for missing carbon species and low at 0.631 when ionic species and trace elements were missing. For the seven highest contributing sources, replacing the missing values of carbon species with estimates minimized the percent errors to 2.0% on average. However, replacing the missing values of the other chemical species with estimates increased the percent errors to more than 9.7% on average. Percent errors were maximal at 37% on average when missing values of ionic species and trace elements were replaced with estimates. Missing values, except for carbon species, need to be excluded. This approach reduced the percent errors to 7.4% on average, which was lower than those due to median replacement. Our results show that reducing the biases in source apportionment is possible by replacing the missing values of carbon species with estimates. To improve the biases due to missing values of the other chemical species, the estimation accuracy of the ML needs to be improved.

The impact of size-segregated particle properties on daily mortality in Seoul, Korea.

To investigate the causative component for certain health outcomes, the associations between the properties of ambient particles and cause-specific mortality (all-cause, cardiovascular, and respiratory-related mortality) measured in Seoul, Korea, from January 1, 2013, to December 31, 2016, were evaluated with a quasi-Poisson generalized additive model (GAM). The total mass of PM10 and PM2.5 moderately affected respiratory-related mortality but had almost no impact on all-cause and cardiovascular-related mortality. Among PM2.5 mass compositions, ammonium sulfate, which is in generally 300-500 nm as a secondary species, showed the most statistically significant effect on respiratory-related mortality at lag 4 (p < 0.1) but not for other mortalities. However, from the size-selective investigations, cardiovascular-related mortality was impacted by particle number concentrations (PNCs), particle surface concentrations (PSCs), and particle volume concentrations (PVCs) in the size range from 50 to 200 nm with a statistically significant association, particularly at lag 1, suggesting that mass is not the only way to examine mortality, which is likely because mass and chemical composition concentrations are generally controlled by larger-sized particles. Our study suggests that the size-specific mortality and/or impacts of size-resolved properties on mortalities need to be evaluated since smaller particles get into the body more efficiently, and therefore, more diverse size-dependent causes and effects can occur.

Sources of airborne particulate matter-bound metals and spatial-seasonal variability of health risk potentials in four large cities, South Korea.

Fifteen airborne particulate matter-bound metals were analyzed at 14 sites in four large cities (Seoul, Incheon, Busan, Daegu) in South Korea, between August 2013 and June 2017. Among the seven sources resolved by positive matrix factorization, soil dust and marine aerosol accounted for the largest and second largest portions in the three cities; however, in Seoul, soil dust and traffic occupied the largest and the second largest, respectively. Non-carcinogenic risk assessed by inhalation of eight metals (Cd, Co, Ni, Pb, As, Al, Mn, and V) was greater than the hazard index (HI) of 1 at four sites located at or near the industrial complexes. Cumulative incremental lifetime cancer risk (ILCR) due to exposure to five metals (Cd, Co, Ni, Pb, and As) exceeded the 10-6 cancer benchmark at 14 sites and 10-5 at six sites, which includes four sites with HI greater than 1. The largest contributor to ILCR was coal combustion in Seoul, Incheon, and Daegu, and industry sources in Busan. Moreover, industry sources were the largest contributors to non-carcinogenic risk in Seoul, Busan, and Daegu, and soil dust was in Incheon. Incheon had the highest HI in spring because of the higher contribution of soil dust sources than in other seasons. The higher ILCR in Incheon in spring and winter and higher ILCR and HI in Daegu in autumn were mainly due to the influence of industry or coal combustion sources. Statistically significant differences in the ILCR and HI values among the sampling sites in Busan and Daegu resulted from the higher contribution of industry sources at a certain site in the respective city.

Source apportionment of PM2.5 in Seoul, South Korea and Beijing, China using dispersion normalized PMF.

East Asian countries experience severe air pollution owing to their rapid development and urbanization induced by substantial economic activities. South Korea and China are among the most polluted East Asian countries with high mass concentrations of PM2.5. Although the occurrence of transboundary air pollution among neighboring countries has been recognized for a long time, studies involving simultaneous ground-based PM2.5 monitoring and source apportionment in South Korea and China have not been conducted to date. This study performed simultaneous daily ground-based monitoring of PM2.5 in Seoul and Beijing from January to December 2019. The mass concentrations of PM2.5 and its major chemical components were analyzed simultaneously during 2019. Positive matrix factorization (PMF) as well as dispersion normalized PMF (DN-PMF) were utilized for the source apportionment of ambient PM2.5 at the two sites. 23 h average ventilation coefficients were applied for daily PM2.5 chemical constituents' data. Nine sources were identified at both sites. While secondary nitrate, secondary sulfate, mobile, oil combustion, biomass burning, soil, and aged sea salt were commonly found at both sites, industry/coal combustion and incinerator were identified only at Seoul and incinerator/industry and coal combustion were identified only at Beijing. Reduction of the meteorological influences were found in DN-PMF compare to C-PMF but the effects of DN on mobile source were reduced by averaging over the 23 h sampling period. The DN-PMF results showed that Secondary nitrate (Seoul: 25.5%; Beijing: 31.7%) and secondary sulfate (Seoul: 20.5%; Beijing: 17.6%) were most dominant contributors to PM2.5 at both sites. Decreasing secondary sulfate contributions and increasing secondary nitrate contributions were observed at both sites.

Seasonal characteristics of atmospheric water-soluble organic nitrogen in PM2.5 in Seoul, Korea: Source and atmospheric processes of free amino acids and aliphatic amines.

The seasonal characteristics of atmospheric water-soluble organic nitrogen (WSON) in particulate matter with a diameter of 2.5 µm or smaller (PM2.5) were analyzed focusing on sources and atmospheric processing. Daily collected samples over 23 h (10:00-9:00) from 7 August 2018 to 31 December 2019 on quartz filters with a high-volume sampler at the Korea Institute of Science and Technology (KIST) in Seoul were considered. The most common species in the Seoul atmosphere included Glycine (5.45 ± 9.81 ng/m3) among free amino acids (FAAs) and trimethylamine (TMA) (5.35 ± 3.80 ng/m3) among aliphatic amines (AAs). The top 10 WSON species (93.6% of all WSON species) were categorized into three groups based on correlation analysis considering meteorological data, (e.g., temperature, rainfall, relative humidity (RH), wind speed) gaseous pollutants (e.g., SO2, CO, NO2) and mass concentration of PM10 and PM2.5. Those three groups are G1 (Glycine, Alanine, and Threonine), G2 (Gln Glutamine, Lys Lysine, and Glutamic acid) and G3 (Trimethylamine (TMA), dimethylamine (DMA), and methylamine (MA)), where G1, G2 and G3 accounted for 31.1%, 8.8% and 51.1%, respectively, of the total species. Among these three groups, G1 and G3 are from combustion sources, and G2 shows secondary features generated by photochemical reactions involving ozone. Although both G1 and G3 exhibited features influenced by combustion sources, the AA species (TMA, DMA, and MA) in G3 demonstrated typical features enhanced under high-humidity conditions, suggesting not only primary sources but also secondary formation at the local scale influence to the AA in G3 group. Based on long-term measurements more than a year, our findings suggest that complex and diverse sources of atmospheric WSON are in Seoul, Korea both from primary and secondary, which may affect its environmental, climate and health.

Source attribution of air pollution using a generalized additive model and particle trajectory clusters.

Speciated hourly measurements of fine aerosols were made for more than two years at an urban, an industrial and a port site in Busan, Korea. A Generalized Additive Model (GAM) was designed to deconvolve factors contributing to the pollutant concentrations at multiple scales. The model yields estimates of source contributions to pollution by separately identifying the signals in the time series due to meteorology, vertical mixing, horizontal wind transport and temporal variations such as diurnal, weekly, seasonal and annual trends. The GAM model was expanded to include FLEXPART back trajectory clusters generated using fuzzy c-means clustering. This made it possible to quantify the impact of long-range transport using the Trajectory Cluster Contribution Function (TCCF). TCCF provides a development of methods such as Concentration Field Analysis and Potential Source Contribution Function by providing numerical estimates of concentration changes associated with different air mass transport patterns while accounting for possible confounding factors from meteorology. The GAM simulations identified the importance of local transport for primary pollutants and long-range transport from China for secondary pollutants. Local factors accounted for up to 72% of the variance in concentrations of NO2 and elemental carbon whereas large-scale/seasonal factors accounted for up to 56% of PM2.5 and 80% of inorganic species. The algorithm further identified the importance of the weekend effect and the holiday effect at the different sites in Busan. The residual from the analysis was used to estimate the impact of the COVID-19 pandemic. The signature of the pandemic was different between the pollutants as well as from site to site. The model was able to distinguish small impacts from local pollutants at the residential site; short-lived acute impacts from industrial changes; and longer-term changes due to the early pandemic response in China.

The impact of organic extracts of seasonal PM2.5 on primary human lung epithelial cells and their chemical characterization.

Lung epithelial cells serve as the first line of defense against various inhaled pollutant particles. To investigate the adverse health effects of organic components of fine particulate matter (PM2.5) collected in Seoul, South Korea, we selected 12 PM2.5 samples from May 2016 to January 2017 and evaluated the effects of organic compounds of PM2.5 on inflammation, cellular aging, and macroautophagy in human lung epithelial cells isolated directly from healthy donors. Organic extracts of PM2.5 specifically induced neutrophilic chemokine and interleukin-8 expression via extracellular signal-regulated kinase activation. Moreover, PM2.5 significantly increased the expression of aging markers (p16, p21, and p27) and activated macroautophagy. Average mass concentrations of organic and elemental carbon had no significant correlations with PM2.5 effects. However, polycyclic aromatic hydrocarbons and n-alkanes were the most relevant components of PM2.5 that correlated with neutrophilic inflammation. Vegetative detritus and residential bituminous coal combustion sources strongly correlated with neutrophilic inflammation, aging, and macroautophagy activation. These data suggest that the chemical composition of PM2.5 is important for determining the adverse health effects of PM2.5. Our study provides encouraging evidence to regulate the harmful components of PM2.5 in Seoul.

Apportioning and locating nonmethane hydrocarbon sources to a background site in Korea.

Nonmethane hydrocarbons (NMHCs) measured between April 2004 and March 2005 at a background monitoring site on Sukmo Island, Korea were analyzed to identify and apportion NMHC sources. A total of 7694 samples and 35 NMHC species were analyzed. Positive matrix factorization (PMF), applied to identify and apportion the sources of NMHCs, resolved six sources: two fuel evaporative sources (36.3%), solvent sources (25.4%), mixed sources of vehicle exhaust and combustion (22.8%), petrochemical sources (9.6%), and biogenic sources (5.4%). During the summer, the largest contributors to ozone formation were biogenic sources (48.9% and 79.7% by maximum incremental reactivity and propene-equivalent concentration, respectively), which were situated locally, and secondary sources included solvent sources (22.2% and 7.4%) and fuel evaporative sources (15.6% and 8.2%). For evaporative-1 sources composed of long-lived alkanes, the potential source contribution function (PSCF) technique using 48 h back trajectories revealed oil and gas fields in China as potential source areas of fresh "regional" air masses. In addition, the PSCF results for evaporative-2 sources and a long-lived marker species of vehicle exhaust/combustion sources showed that the NMHC mixing ratio in Sukmo, South Korea was enhanced by long-range transport from the Shandong area in China.

Fifteen-year trends in carbon species and PM2.5 in Seoul, South Korea (2003-2017).

This study focused on particulate matter (PM2.5) and carbon species in Seoul, South Korea, to quantitatively evaluate their long-term trends and assess the main correlating factors. Ambient PM2.5 samples were collected over a 24 h period every third or sixth day from March 2003 to December 2017. The mean concentrations of PM2.5, organic carbon (OC), elemental carbon (EC), primary and secondary OC (POC and SOC) in Seoul over 15 years were 32.2 µg/m3 and 7.28 µg/m3, 1.85 µg/m3, 4.29 µg/m3 and 3.54 µg/m3 respectively. The long-term concentration trends in PM2.5, OC, EC, POC, and SOC decreased significantly at rates of -2.09, -3.13, -6.31, -2.86, and -3.88 per year, respectively from 2003 to 2017 (p < 0.001), whereas the long-term trends in OC/EC significantly increased at a rate of 12.9/year (p < 0.001). These long-term decreases in PM2.5 and carbon species concentrations were most pronounced in 2008 but almost disappeared from 2013 onwards. Considering the decrease in wind speed and variations in the concentration of gaseous air pollutants (carbon monoxide, sulfur dioxide, nitrogen dioxide, and volatile organic compounds) without a tendency to increase or decrease since 2013, secondary aerosol formation by atmospheric stagnation alleviated long-term decreases in PM2.5 and carbon species concentrations. The long-term decreases in EC concentration were the most consistent and rapid, strongly suggesting that atmospheric policies related to mobile in South Korea were effective in reducing EC concentration. Future air quality management should focus on the secondary formation of air pollutants based on regional trends in air pollutant concentrations.

The major chemical constituents of PM2.5 and airborne bacterial community phyla in Beijing, Seoul, and Nagasaki.

Ambient particle (PM2.5) samples were collected in three East Asian cities (Beijing, China; Seoul, South Korea; Nagasaki, Japan) from December 2014 to November 2015 to quantitatively investigate airborne bacteria at the phylum level. Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and Cyanobacteria represented the top five airborne bacterial phyla in all three cities. The most dominant airborne phylum, Proteobacteria, was more prevalent during the winter (at rates of 67.2%, 79.9%, and 87.0% for Beijing, Seoul, and Nagasaki, respectively). Correlations among airborne bacteria and environmental factors including PM2.5, its major chemical constituents, and meteorological factors were calculated. Temperature correlated negatively with Proteobacteria but positively with Firmicutes and Bacteroidetes. The abundance of Cyanobacteria correlated positively with particulate NO3- and SO42- levels in Beijing (R = 0.46 and R = 0.35 for NO3- and SO42-, respectively) but negatively in Seoul (R = -0.14 and R = -0.19 for NO3- and SO42-, respectively) and Nagasaki (R = -0.05 and R = -0.03 for NO3- and SO42-, respectively). Backward trajectory analysis was applied for 72 h and three clusters were classified in each city. Five dominant bacteria and other bacterial groups showed significant differences (p < 0.05) in local clustering, as compared to the long-range transport clusters from Beijing. The proportions of the five bacterial phyla in Seoul were significantly different in each cluster. A local cluster in Nagasaki had higher ratios of all major airborne bacterial phyla, except Proteobacteria.

Long term trends of chemical constituents and source contributions of PM2.5 in Seoul.

PM2.5 was measured and analyzed between 2014 and 2015 in Seoul, and its sources were identified with a positive matrix factorization (PMF) to characterize chemical constituents and sources of the measured PM2.5. To verify policy interventions in reducing PM2.5 levels in Korea, the results were compared with previously published results from 2003 to 2007 at the same study site. A total of 215 PM2.5 samples were collected and analyzed for 24 species, i.e., carbonaceous species (OCEC), ionic species (NO3-, SO42-, and NH4+), and 19 element species in this study. The average PM2.5 mass concentration during the sampling period was 42.6±23.3 µg m-3. The seasonal average mass concentration of PM2.5 was the highest during winter (49.9±20.6 µg m-3), followed by spring (45.2±25.3 µg m-3), fall (34.4±19.3 µg m-3), and summer (28.4±12.5 µg m-3). Nine sources were identified and quantified using the PMF model: secondary nitrate (19.0%), secondary sulfate (20.2%), mobile (23.3%), biomass burning (12.1%), soil (8.3%), roadway emissions (3.1%), aged sea salt (1.0%), coal combustion (4.1%), and oil combustion (9.0%). The PM2.5 levels and chemical constituents during this study were lower than those during the previous study from 2003 to 2007. Particularly, concentrations of mobile related chemicals (OC, EC, and nitrate) and mobile source contributions consistently decreased from 2003 to 2015, indicating that the mobile emission reduction policy is improving PM2.5 levels in the region. The comparison between the two periods allows trends in chemical constituents and the sources of PM2.5 in Seoul to be understood.