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.

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 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.

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.

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.

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.

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.

Personal exposure to fine particulate air pollutants impacts blood pressure and heart rate variability.

Air pollution has increasingly been recognized as a major healthcare concern. Air pollution, particularly fine particulate matter (≤ 2.5 µm in aerodynamic diameter [PM2.5]) has demonstrated an increase in adverse cardiovascular events. This study aimed to assess the cardiovascular response to personal exposure to different levels of PM2.5. This prospective cohort study enrolled healthy volunteers aged ≥ 18 years with no cardiovascular disease. Study subjects carried personal exposure monitor of PM2.5, digital thermo-hygrometer for temperature and humidity, 24-h blood pressure monitor, and continuous electrocardiogram monitor. Measurements were repeated twice with an interval of 6-12 months. Statistical models consisted of generalized estimation equations to various repeated measures of each subject. A total of 22 subjects were enrolled in this study between July 2018 and January 2019. Measurement was performed twice in all participants, and a total of 36 data were collected except for insufficient data collection. The mean age of the study population was 41.6 years, and 95% of the subjects were females. No study subjects had hypertension or other cardiovascular diseases. The average systolic blood pressure increased with higher PM2.5 levels with marginal significance (0.22 mmHg [95% confidential intervals - 0.04 to 0.48 mmHg] per 10 µg/m3 of PM2.5). All parameters for heart rate variability significantly decreased with a higher level of PM2.5. In this study, we measured individual personal exposure to PM2.5 by using a portable device. We found that 24-h exposure to high levels of PM2.5 was associated with a significant decrease in heart rate variability, suggesting impaired autonomous nervous function.

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.

Source apportionment of PM10 and PM2.5 air pollution, and possible impacts of study characteristics in South Korea.

INTRODUCTION: Studies of source apportionment (SA) for particulate matter (PM) air pollution have enhanced understanding of dominant pollution sources and quantification of their contribution. Although there have been many SA studies in South Korea over the last two decades, few studies provided an integrated understanding of PM sources nationwide. The aim of this study was to summarize findings of PM SA studies of South Korea and to explore study characteristics. METHODS: We selected studies that estimated sources of PM10 and PM2.5 performed for 2000-2017 in South Korea using Positive Matrix Factorization and Chemical Mass Balance. We reclassified the original PM sources identified in each study into seven categories: motor vehicle, secondary aerosol, soil dust, biomass/field burning, combustion/industry, natural source, and others. These seven source categories were summarized by using frequency and contribution across four regions, defined by northwest, west, southeast, and southwest regions, by PM10 and PM2.5. We also computed the population-weighted mean contribution of each source category. In addition, we compared study features including sampling design, sampling and lab analysis methods, chemical components, and the inclusion of Asian dust days. RESULTS: In the 21 selected studies, all six PM10 studies identified motor vehicle, soil dust, and combustion/industry, while all 15 PM2.5 studies identified motor vehicle and soil dust. Different from the frequency, secondary aerosol produced a large contribution to both PM10 and PM2.5. Motor vehicle contributed highly to both, whereas the contribution of combustion/industry was high for PM10. The population-weighted mean contribution was the highest for the motor vehicle and secondary aerosol sources for both PM10 and PM2.5. However, these results were based on different subsets of chemical speciation data collected at a single sampling site, commonly in metropolitan areas, with short overlap and measured by different lab analysis methods. CONCLUSION: We found that motor vehicle and secondary aerosol were the most common and influential sources for PM in South Korea. Our study, however, suggested a caution to understand SA findings from heterogeneous study features for study designs and input data.

Reactive oxygen species (ROS) activity of ambient fine particles (PM2.5) measured in Seoul, Korea.

Substantial increase in level of particulate matter has raised concerns in South Korea recently. Ambient particulate matter is classified as Group I carcinogen (IARC, 2013) and multiple epidemiological studies has demonstrated adverse health effects due to exposure of particulate matter. Fine particulate matter (PM2.5) which has a diameter <2.5 µm is likely to penetrate deeply into lung and is known to be eliciting adverse health effects. A number of epidemiological studies have been conducted on adverse health effects of PM-related diseases and mortality rate, yet particulate matter (PM)-induced reactive oxygen species (ROS) activity at the cellular level has not been actively studied in Korea. This study assessed PM-induced oxidative potential by exposure of collected ambient PM2.5 samples to the rat alveolar macrophage cell line. The characteristics of PM2.5 in Korea were further characterized by linking chemical constituents and contributing sources to ROS. PM2.5 mass concentration during the cold season was relatively higher than mass concentration during the warm season and chemical constituents except for Secondary Organic Carbon (SOC) and SO42- which both showed similar trends in both the cold and cold seasons. The concentration of crustal elements was especially high during the cold season which can be an indication of long range transport of Asian dust. Water soluble organic carbon and water soluble transition metals (Cr and Zn) were also shown to be correlated to oxidative potential and metals such as As and V were shown to have a high contribution to ROS activity according to stepwise multiple linear regression. Principal Component Analysis (PCA) results identified six factors that can be interpreted as soil, mobile, industry, secondary inorganic aerosol, secondary organic aerosol and oil combustion. Moreover, through Principal Component Regression (PCR), industry, soil, mobile and SIA were shown to be statistically significant sources in a relation to ROS activity.

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.

Cardiovascular Effects of Long-Term Exposure to Air Pollution: A Population-Based Study With 900 845 Person-Years of Follow-up.

BACKGROUND: Studies have shown that long-term exposure to air pollution such as fine particulate matter (≤2.5 µm in aerodynamic diameter [PM2.5]) increases the risk of all-cause and cardiovascular mortality. To date, however, there are limited data on the impact of air pollution on specific cardiovascular diseases. This study aimed to evaluate cardiovascular effects of long-term exposure to air pollution among residents of Seoul, Korea. METHODS AND RESULTS: Healthy participants with no previous history of cardiovascular disease were evaluated between 2007 and 2013. Exposure to air pollutants was estimated by linking the location of outdoor monitors to the ZIP code of each participant's residence. Crude and adjusted analyses were performed using Cox regression models to evaluate the risk for composite cardiovascular events including cardiovascular mortality, acute myocardial infarction, congestive heart failure, and stroke. A total of 136 094 participants were followed for a median of 7.0 years (900 845 person-years). The risk of major cardiovascular events increased with higher mean concentrations of PM2.5 in a linear relationship, with a hazard ratio of 1.36 (95% confidence interval, 1.29-1.43) per 1 µg/m3 PM2.5. Other pollutants including PM2.5-10 of CO, SO2, and NO2, but not O3, were significantly associated with increased risk of cardiovascular events. The burden from air pollution was comparable to that from hypertension and diabetes mellitus. CONCLUSIONS: This large-scale population-based study demonstrated that long-term exposure to air pollution including PM2.5 increases the risk of major cardiovascular disease and mortality. Air pollution should be considered an important modifiable environmental cardiovascular risk factor.

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.

Source apportionments of ambient fine particulate matter in Israeli, Jordanian, and Palestinian cities.

This manuscript evaluates spatial and temporal variations of source contributions to ambient fine particulate matter (PM2.5) in Israeli, Jordanian, and Palestinian cities. Twenty-four hour integrated PM2.5 samples were collected every six days over a 1-year period (January to December 2007) in four cities in Israel (West Jerusalem, Eilat, Tel Aviv, and Haifa), four cities in Jordan (Amman, Aqaba, Rahma, and Zarka), and three cities in Palestine (Nablus, East Jerusalem, and Hebron). The PM2.5 samples were analyzed for major chemical components, including organic carbon and elemental carbon, ions, and metals, and the results were used in a positive matrix factorization (PMF) model to estimate source contributions to PM2.5 mass. Nine sources, including secondary sulfate, secondary nitrate, mobile, industrial lead sources, dust, construction dust, biomass burning, fuel oil combustion and sea salt, were identified across the sampling sites. Secondary sulfate was the dominant source, contributing 35% of the total PM2.5 mass, and it showed relatively homogeneous temporal trends of daily source contribution in the study area. Mobile sources were found to be the second greatest contributor to PM2.5 mass in the large metropolitan cities, such as Tel Aviv, Hebron, and West and East Jerusalem. Other sources (i.e. industrial lead sources, construction dust, and fuel oil combustion) were closely related to local emissions within individual cities. This study demonstrates how international cooperation can facilitate air pollution studies that address regional air pollution issues and the incremental differences across cities in a common airshed. It also provides a model to study air pollution in regions with limited air quality monitoring capacity that have persistent and emerging air quality problems, such as Africa, South Asia and Central America.

Heat, heat waves, and out-of-hospital cardiac arrest.

OBJECTIVE: Cardiac arrest is one of the common presentations of cardiovascular disorders and a leading cause of death. There are limited data on the relationship between out-of-hospital cardiac arrest (OHCA) and ambient temperatures, specifically extreme heat. This study investigated how heat and heat waves affect the occurrence of OHCA. METHODS: Seven major cities in Korea with more than 1 million residents were included in this study. A heat wave was defined as a daily mean temperature above the 98th percentile of the yearly distribution for at least two consecutive days. RESULTS: A total of 50,318 OHCAs of presumed cardiac origin were identified from the nationwide emergency medical service database between 2006 and 2013. Ambient temperature and OHCA had a J-shaped relationship with a trough at 28°C. Heat waves were shown to be associated with a 14-% increase in the risk of OHCA. Adverse effects were apparent from the beginning of each heat wave period and slightly increased during its continuation. Excess OHCA events during heat waves occurred between 3PM and 5PM. Subgroup analysis showed that those 65years or older were significantly more susceptible to heat waves. CONCLUSIONS: Ambient temperature and OHCA had a J-shaped relationship. The risk of OHCA was significantly increased with heat waves. Excess OHCA events primarily occurred during the afternoon when the temperature was high. We found that the elderly were more susceptible to the deleterious effects of heat waves.