KSOEM
Articles
- Page Path
- HOME > Ann Occup Environ Med > Volume 27; 2015 > Article
- Research Article Public-health impact of outdoor air pollution for 2nd air pollution management policy in Seoul metropolitan area, Korea
- Jong Han Leem, Soon Tae Kim, Hwan Cheol Kim
-
Annals of Occupational and Environmental Medicine 2015;27:7.
DOI: https://doi.org/10.1186/s40557-015-0058-z
Published online: February 27, 2015
Department of Occupational and Environmental Medicine, Inha University Hospital, 27 Inhang road Jung-gu, Incheon, 400-711 South Korea 
Division of Environmental Engineering, Ajou University Woncheon-dong, Yeongtong-gu, Suwon, 443-749 South Korea
• Received: July 26, 2014 • Accepted: February 4, 2015
© Leem et al.; licensee BioMed Central. 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Abstract
-
Objectives Air pollution contributes to mortality and morbidity. We estimated the impact of outdoor air pollution on public health in Seoul metropolitan area, Korea. Attributable cases of morbidity and mortality were estimated.
-
Methods Epidemiology-based exposure-response functions for a 10 μg/m3 increase in particulate matter (PM2.5 and PM10) were used to quantify the effects of air pollution. Cases attributable to air pollution were estimated for mortality (adults ≥ 30 years), respiratory and cardiovascular hospital admissions (all ages), chronic bronchitis (all ages), and acute bronchitis episodes (≤18 years). Environmental exposure (PM2.5 and PM10) was modeled for each 3 km × 3 km.
-
Results In 2010, air pollution caused 15.9% of total mortality or approximately 15,346 attributable cases per year. Particulate air pollution also accounted for: 12,511 hospitalized cases of respiratory disease; 20,490 new cases of chronic bronchitis (adults); 278,346 episodes of acute bronchitis (children). After performing the 2nd Seoul metropolitan air pollution management plan, the reducible death number associated with air pollution is 14,915 cases per year in 2024. We can reduce 57.9% of death associated with air pollution.
-
Conclusion This assessment estimates the public-health impacts of current patterns of air pollution. Although individual health risks of air pollution are relatively small, the public-health consequences are remarkable. Particulate air pollution remains a key target for public-health action in the Seoul metropolitan area. Our results, which have also been used for economic valuation, should guide decisions on the assessment of environmental health-policy options.
Introduction
Urbanization and industrialization are ongoing worldwide. Air pollution accompanied by urbanization and industrialization has already become a major risk factor threatening human health. Fine PM (PM2.5) air pollution and mortality were linked in the Six Cities Study, which reported an association between PM2.5 and all cause, cardiopulmonary, and lung cancer mortality [1,2].
Research conducted during the past 20 years in the US, EU, and Asian countries has confirmed that outdoor air pollution contributes to morbidity and mortality [3-5]. Some effects may be related to short-term exposure [6,7], others have to be considered as contributions of long-term exposure. Although the mechanisms have not been fully explained, epidemiological evidence suggests that outdoor air pollution is a contributing cause of morbidity and mortality [8].
The recent Global Burden of Disease report estimated that 89% of the world’s population lived in areas with PM2.5 ambient levels above the World Health Organization (WHO) Air Quality Guideline of 10 μg/m3, and 32% lived in areas above the WHO Level 1 Interim Target of 35 μg/m3. East Asia was singled out, with an estimated 76% population exposure above the Level 1 Interim Target [9].
In 1998, the average PM10 concentration in Seoul was 78 μg/m3. According to the first metropolitan air pollution management policy, the average PM10 concentration in Seoul was 41 μg/m3 in 2012 [10]. Even with a dramatic decrease of PM10, the current level of PM10 still exerts a significant burden of disease on people in Korea.
The Korean government established the 2nd metropolitan air pollution management plan during 2015–2024. In this plan, the goal of air quality is that PM10 reach 30 μg/m3 and PM2.5 reach 20 μg/m3.
Assessing public health benefit can be possible by risk assessment of air pollution. Up to now, public health assessment are not performed in Korea for monitoring air quality. In this study, we will assess public health benefit by calculating mortality and morbidity cases attributed to air pollution in the Seoul metropolitan area.
Methods
The impact assessment relies on calculating the attributable number of cases [11,12]. Cases of morbidity or mortality attributable to air pollution were derived for the health outcomes listed in Table 1. Outcomes were ignored if quantitative data were not available, if costing was impossible (e.g., valuing decrement in pulmonary function), and to prevent overlapping health measures from causing multiple counting of the same costs (e.g., emergency visits were not considered because they were partly included in the hospital admissions). We selected only PM2.5 or PM10 in order to derive the attributable cases because PM2.5 and PM10 are useful indicators of several sources of outdoor air pollution such as fossil-fuel combustion. Three data components are required for estimation of the number of cases attributed to outdoor air pollution in a given population: the exposure-response function; the frequency of the health outcome (e.g., the incidence or prevalence) and the level of exposure. The association between outdoor air pollution and health-outcome frequency is usually described with an exposure-response function (or effect estimate) that expresses the relative increase in adverse health for a given increment in air pollution.
Table 1
Health outcome definition and source of data
| Health Outcome | Definition | Source of exposure-response function | Source of population frequency |
|---|---|---|---|
| Long-term mortality Adult age ≥ 30 | Death rate, excluding violent death or accidents, >30 years | Dockery DW et al. [1] | National death certificate statistics for 2010 and 2024(prediction) (adults _30 years) |
| Pope CA et al. [2] | |||
| Pope CA et al. [15] | |||
| Respiratory hospital admissions (All age) | ICD9 460–519 | Pope CA et al. [16] | National population statistics for 2010 and 2024(prediction) |
| ICD9 466, 480–487, 493, 490– | Spix C et al. [17] | ||
| 492, 494–496 | Wordley J et al. [18] | ||
| ICD9 480–487, 490–496 | Prescott GJ et al. [19] | ||
| Cadiovascular hospital admissions (All age) | ICD9 410–436 | Wordley J et al. [18] | National population statistics for 2010 and 2024(prediction) |
| ICD9 390–459 | Poloniecki JD et al. [20] | ||
| ICD9 390–459 | Medina S et al. [21] | ||
| ICD9 410–414, 426–429, 434–440 | Prescott GJ et al. [19] | ||
| Lung cancer incidence | ICD9 162 | Raaschou-Nielsen O et al. [26] | |
| Asthma attack (children < 15 years) | Lower respiratory symptoms, age 6–12 years | Roemer W et al. [27] | National population statistics for 2010 and 2024(prediction) |
| Asthma, age 7–15 years | Segala C et al. [28] | ||
| Lower respiratory symptoms, age 7–13 years | Gielen MH et al. [29] | ||
| Asthma attack (adults ≥ 15 years) | Wheeze, age 18–80 years | Dusseldorp A et al. [30] | National population statistics for 2010 and 2024(prediction) |
| Shortness of breath, age 18–55 years | Hiltermann TJN et al. [31] | ||
| Wheeze, age 16–70 years | Neukirch F et al. [32] | ||
| Chronic-bronchitis | Symptoms of cough and/or sputum production on most days, for at least 3 months per year, and for 2 years or more | Abbey D et al. [22] | National population statistics for 2010 and 2024(prediction) |
| Acute bronchitis (age ≤ 18) | Bronchitis in past 12 months, ages less than 18 years. | Dockery DW et al. [23] | National population statistics for 2010 and 2024(prediction) |
Population data for the Seoul metropolitan area from Statistics Korea is classified according to address and registration in the following age groups: 0–4, 5–9, 10–14, 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, and 65+ years. Citizens’ residences in the Seoul metropolitan area were divided into 80 sections according to neighborhoods, forming basic administrative units such as Gu and Gun, used in city planning and management. Eighty sections were formed in order to identify site-specific exposure to air pollution and identify the areas with the greatest risk. 2024 population data were obtained from population prediction data of Statistics Korea. The health outcome definition and source of data are listed in Table 1. The total regional baseline mortality was retrieved from statistics on Korea (International Classification of Diseases–ICD-10, A00-Y98). ICD-9 code in previous studies were translated into ICD10. The morbidity calculations were performed using hospitalization data from the Korean Health Insurance, which covers the entire population and is the sole purchaser of health care services in the country. Hospitalizations due to two main disease groups were included in the calculations: cardiovascular (I00-I99) and respiratory causes (J00-J99). Cardiac admissions (I20-I25) and cerebrovascular admissions (I60-I69) were also used for the exposure-response work on cardiovascular hospitalizations.
CMAQ (Comprehensive Multiscale Air Quality) [13] version 4.7.1 was used to simulate air quality over the Seoul Metropolitan Area (SMA) for a one-month period of each season in 2010and 2024; January, April, July, and October. The Nesting-down domains were composed of 27-km, 9-km, and 3-km horizontally resolved domains. The coarse domain (174x128 arrays) includes northeastern Asia; Korea, Japan, and most of China. The 9-km domain (67x82 arrays) includes all of South Korea and most of North Korea, and the finest domain (58x61 arrays) was set up to focus on the SMA. The SAPRC-99 (Statewide Air Pollution Research Center 99) [14] chemical mechanism for gas-phase chemistry and AERO5 for aerosol module were selected to represent model species over the region.
For meteorological simulation, WRF (Weather Research and Forecast) version 3.4.1 was utilized with NCEP (National Centers for Environmental Prediction) Final (FNL) Operational Global Analysis Model fields for initial and boundary conditions [13]. The WRF was configured to have 35 sigma layers up to 50 hpa, and the lowest layer thickness is around 30 m (sigma = 0.996). The WRF physical options are as follows: WRF Single-Moment 6-class scheme, Rapid Radiative Transfer Model longwave scheme, Goddard shortwave scheme, M-O surface layer scheme, Grell Cumulus scheme, and YSU PBL scheme. Meteorology-Chemistry Interface Program (MCIP) version 3.6 was then used for preparation of CMAQ-ready meteorological inputs. One-way nesting was applied during WRF and CMAQ simulations.
The CAPSS 2010 (Clean Air Protection Supporting System, 2010 base year), anthropogenic emissions inventory, was processed using SMOKE (Sparse Matrix Operation Kernel Emission) version 3.1, and biogenic emissions such as isoprene and terpenes were estimated using MEGAN (Model of Emissions of Gases and Aerosols from Nature) [15] version 2.04. The MICS-Asia emissions inventory was supplementary used for foreign emissions.
To describe the long-term effect of air pollution on mortality, the broadly employed US ACS study relative risk RR = 1.06 (95% CI 1.02–1.11) per 10 μg/m3 increase of PM2.5 was used as the exposure-response relationship [16].
RR = 1.013 (95% CI 1.001–1.025) per 10 μg/m3 increase of PM10 was used for calculations of respiratory hospitalizations due to air pollution [17-20]. For cardiovascular hospitalizations we used a weighted average RR = 1.013 (95% CI 1.007–1.019) per 10 μg/m3 increase of PM10 based on the effect on cardiac and cerebrovascular admissions from a COMEAP meta-analysis [21,22]. For chronic bronchitis incidence, we used RR = 1.098 (95% CI 1.009–1.194) per 10 μg/m3 increase of PM10 based on one study, which reported the effect of PM on the incidence of chronic bronchitis among a population with very low rates of smoking [23].
For bronchitis episodes, we used RR = 1.306 (95% CI 1.135–1.502) per 10 μg/m3 increase of PM10 validated at several studies [24-26]. The meta-analyses showed a statistically significant association between risk of lung cancer and PM10 (hazard ratio [HR] 1 · 22 [95% CI 1 · 03-1 · 45] per 10 μg/m3 [27]. For asthma attacks that occurred in children younger than 15 years old, we used RR = 1.044 (95% CI 1.027–1.062) per 10 μg/m3 increase of PM10 [28-30]. For asthma attacks that occurred in adults older than 15 years old, we used RR = 1.039 (95% CI 1.019–1.059) per 10 μg/m3 increase of PM10 [31-33]. The cases (mortality and morbidity) were calculated in absolute and relative numbers for all sections in the Seoul Metropolitan area. The following equation was used:
[TeX:] \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$ \varDelta \mathrm{Y}=\Big[Y0\left(\mathrm{e}{\hbox{-}}^{\upbeta \kern0.15em \cdot \kern0.15em \varDelta \mathrm{PM}2:5}\cdot \hbox{--} 1\right)\cdot POP $$\end{document}Δ Y = [ Y 0 e ‐ β ⋅ Δ PM 2:5 ⋅ – 1 ⋅ POP
where Y0 is the baseline rate; pop the number of exposed persons; · the exposure-response function and △PM2.5 the estimated excess exposure.For each outcome we selected studies from the peer-reviewed literature in order to derive the exposure-response function and the 95% CI. For inclusion, an adequate study design and published PM10 levels were required. Cross-sectional or cohort studies relying on two or three levels of exposure were omitted, as were ecological studies, given their inherent limitations. The health-outcome frequencies (mortality, prevalence, incidence, or person-days) may differ across countries; thus, national mortality and morbidity data were used (Table 2). For some morbidity data, epidemiological studies were the only source (bronchitis incidence from the Adventist Health and Smog Study [34], which was also used by Ostro and colleagues [35]. Annual mean outdoor PM10 had to be determined on a continuous scale. Although there is no evidence for any threshold, there are also no studies available where participants were exposed to PM10 below 20 μg/m3 (annual mean). This reference level also includes the natural background PM10. Thus, the health impact of air-pollution exposure below 20 μg/m3 was ignored. To derive the population exposure distribution, mean annual concentrations of PM10 were modelled for each area at a spatial resolution of 3 km × 3 km.
Table 2
Effect estimate of health outcome and health outcome frequencies
Using the exposure-response functions, expressed as relative risk (RR) per 10 μg/m3, and the health frequency per 1000 000 inhabitants, for each health outcome we calculated the attributable number of cases (D10) for an increase of 10 μg/m3 PM10, as: D10 = (RR-1)*P0 where P0 is the health frequency, given an baseline exposure E0 and RR is the mean exposure-response function across the studies used (Table 1). The exposure-response functions are usually log-linear. For small risks and across limited ranges of exposure log-linear and linear functions would provide similar results. However, if one may apply the method to populations with very large exposure ranges, the impact may be seriously overestimated on the log-linear scale. Thus, we derived the attributable number of cases on an additive scale. The study protocol was approved by the Institutional Review Boards of the Inha University College of Medicine.
Results
Table 2 summarizes the effect estimates, the specific health-outcome frequencies at E0, and the respective number of cases attributable to a 10 μ/m3 increase in PM10 (D10) for each health outcome. A summary of health outcomes attributed to particulate air pollution in the Seoul metropolitan area is shown in Table 3. The number of cases attributable to air pollution is given for three scenarios; year 2010, year 2024 without regulation regarding air pollution, year 2024, when the goal of air attainment is achieved. PM2.5 concentrations without reducing air emissions in 2024 are shown in Figure 1. PM2.5 concentrations after reducing air emissions in 2024 are shown in Figure 2. We compared the number of cases attributed to air pollution for three scenarios. We drew flow chart of this study (Figure 3).
Table 3
Health outcome attributed to particulate air pollution in Seoul metropolitan area
Air pollution caused 15.9% of total mortality or approximately 15,346 attributable cases per year in 2010. Particulate air pollution also accounted for: 12,511 hospitalized cases of respiratory disease; 20,490 new cases of chronic bronchitis (adults); 278,346 episodes of acute bronchitis (children). After performing the 2nd Seoul metropolitan air pollution management plan, Air pollution caused 6.7% of total mortality or approximately 10,866 attributable cases per year in 2024.
Discussion
The public-health impact depends not only on the relative risk but also on the exposure distribution in the population. Our assessment assigned approximately 15.9% of annual deaths to outdoor air pollution. Our assessment is relatively high compared to 6% of EU’s assessment [12]. Korean people have high chronic disease incidences of cancer and chronic respiratory diseases, such as asthma and COPD [36]. According to OECD Health data [37], in 2009, the hospital admission rate for avoidable asthma in the population age 15 and over was 101.5/100,000 persons, while average OECD was 51.8/100,000 persons. In 2009, the hospital admission rate for COPD in the population age 15 and over was 222/100,000 persons, while average OECD was 198/100,000 persons. The incidence rate for all cancers combined in Korea showed an annual increase of 3.3% from 1999 to 2009 [38]. Considering current air pollution levels and our study’s results, certainly air pollution has important contribution to increases of cancer and chronic respiratory diseases in Seoul metropolitan area. Our study has strong advantages. First, our study attempted to decrease uncertainty inherent in these kinds of public health risk assessment. To account for inherent uncertainty in the impact assessment, an “at least” approach was applied for each step, and the uncertainties in the effect estimates were quantified and the results were given as a range (95% CI of the exposure-response function).
To assess the effects of air pollution—a complex mixture of pollutants—epidemiological studies use several indicators of exposure (e.g., NO2, CO, PM10, total suspended particles, SO2). However, because these pollutants are correlated, epidemiological studies cannot exactly allocate observed effects to each pollutant. A pollutant-by-pollutant assessment would grossly overestimate the impact. Therefore, we selected only one pollutant to derive the attributed cases.
The short-term effects of high pollution levels on mortality were not calculated separately because these are already included in exposure-response function of long-term mortality. We consider it inappropriate to use short-term studies for the impact assessment of annual mortality [39]. Short-term studies capture only part of air-pollution-related cases, namely those where exposure and event (death) are closely connected in time. Our calculation based on cohort studies captures both the short-term effects and the long-term effects. The number of deaths attributed to air pollution would be about 4–5 times smaller if the short-term effect estimates had been applied.
Second, we based our assumption on the consistency of epidemiological results observed across many countries. We derived exposure-response from selected well designed studies used in previous public health assessment. For mortality, we had to rely on two US studies, which were confirmed by a third US study [40], French PAARC study [41], China study [5]. Exposure-response used in our study would be consistent because it was confirmed across many countries.
Third, our study used nationwide frequency data. Health-outcome frequencies may strongly influence the impact assessment. Mortality from national sources may be considered accurate. However, frequency measures of morbidity and data on health-care systems have to be considered estimates with some inherent uncertainties. We selected national health frequency data in order to reduce the impact of these limitations. National health insurance covers almost all people in Korea, so that health-outcome frequencies in our study have fewer inherent uncertainties.
However, our study has some limitations. First, our assessment relies on some limited study for deriving exposure-response functions. For chronic bronchitis, our assessment relies on one study. The advantage of the study is the reporting of effects of PM on the incidence of chronic bronchitis among a population with very low rates of smoking. This measure was particularly useful for the economic valuation and had been used in other studies [42]. Second, our study restricted the effect of air pollution to PM10 and PM2.5, and did not take other pollutants, such as NOx, SO2 and O3 into consideration. It can underestimate independent effects of air pollution not explained by or correlated by PM fractions. Temperature is increasing due to climate change. Ozone, showing higher concentration these days, is expected to have more hazardous effects on mortality in Korea and other countries [43] than before. Our calculation regarding the effect of air pollution may be underestimated, because we consider the effect of PM only.
As we did not quantify the attributed number of deaths below age 30 years, we might have underestimated the real number of deaths attributed to air pollution. We ignored potential effects on newborn babies or infants [44]. Although infant mortality is low in Korea, and thus the number of attributed cases is small, the impact on years of life lost, and therefore the economic valuation, could be considerable.
Third, we did not consider uncertainty in exposure assessment. If we assume another exposure reference value, the impact estimates will be higher. Our study assumed that the health risk showed the least at PM10 exposure level <20 μg/m3. In Korea, we have never experienced PM10 exposure level <20 μg/m3. In other countries such as EU and US, an exposure level of 15 μg/m3 corresponds to the reference value in the public-health impact [45]. Our study can be underestimated because of our assumption about the reference value.
Apart from the variability of epidemiological exposure-response estimates (95% CI), we did not quantify other sources of uncertainty, such as errors in the population exposure distribution, or in the estimation of health outcome frequencies. Simulations of multiple probability distributions may, however, erroneously suggest a level of precision in assessing uncertainty that cannot be achieved. These kinds of public health assessment contained a lot of uncertainty. Our study took an “at least” approach in order to account for inherent uncertainty in the impact assessment. Our study insisted that the risk attributed to air pollution in Korea at least exceeded our assessment.
Recent publication about air pollution study in Korea focused on short-term effects of air pollution [46,47]. Recently some studies report adverse pregnancy outcomes associated with air pollution from birth cohort study [48,49]. There is no report like this study in Korea. We assessed public health benefit by calculating mortality and morbidity cases attributed to air pollution in the Seoul metropolitan area.
Our study showed that air pollution had the significant impact on the health of Korean people. In particular, elderly people and children are the vulnerable population to air pollution. In the valuation of air pollution related death and hospitalization, assumptions about age structure of those affected may be influential [47]. The affected population will increase because of the rapidly ageing population structure. Korea is a rapidly aging society, and the number of elderly people older than 65 years is rapidly increasing. Actually the number of elderly people older than 65 years in 2024 will be 12,635,000 persons and their portion will be 24.4% among all population. Traffic is important contributor to urban air pollution in Korea and Asian countries. But traffic creates costs that are not covered by the polluters. The real related external costs from the Organization for Economic Cooperation and Development (OECD) are quantified [50-53]. The traffic share of the total PM10 exposure depended on the mean concentration, ranging from 28% at an annual mean PM10 of 10–15 μg/m3, and increasing up to 58% in some areas. In Korea, the traffic share of the total PM2.5 exposure will be higher due to rapid urbanization. Traffic air pollution will be great burden to urban air pollution because if increasing car numbers in the near future.
Death attributed to air pollution will increase, if proper countermeasures are not taken. If PM2,5 can be maintained at less than 20 ug/m3 in 2024 in the Seoul metropolitan area, death attributable to air pollution will decrease from 25,781 to 10,866. Korean people have a high disease burden of cancer and chronic respiratory diseases, such as asthma and COPD, attributed to air pollution. Clean air strategies, such as the 2nd air management plan in the Seoul metropolitan area, will decrease the burden of disease in Korean people.
Even after accounting for the overall uncertainty of this estimation, our study emphasizes the need to consider air pollution as a pivotal cause of impaired health. In a century moving toward a sustainable society, closer collaboration of public health and environmental policies will enable us to have preventive capacity. Further development of standardized impact assessment methods is needed in order to more stringently assess the benefits from clean air strategies.
Acknowledgements
This study is supported by the Ministry of Environment, Republic of Korea.
-
Competing interests
The authors have no conflicts of interest with the material presented in this paper.
-
Authors' contributions
LJ formulated the research questions, analyzed the data, and prepared the manuscript. KS performed exposure assessment. KH contributed to Data collection and critically revised the manuscript. All authors read and approved the final manuscript.
NOTES
- 1. Dockery DW, Pope CA, Xu X, Spengler JD, Ware JH, Fay ME, et al. An association between air pollution and mortality in six U.S. cities. N Engl J Med 1993;329:1753–9. 10.1056/NEJM199312093292401. 8179653.ArticlePubMed
- 2. Pope A, Thun M, Namboodiri M, Dockery DW, Evans JS, Speizer FE, et al. Particulate air pollution as a predictor of mortality in a prospective study of US adults. Am J Respir Crit Care Med 1995;151:669–74. 10.1164/ajrccm/151.3_Pt_1.669. 7881654.ArticlePubMed
- 3. Wilson R, Spengler J. Particles in our air: concentrations and health effects. 1996, Boston: Harvard University Press.
- 4. Holgate S, Samet J, Koren H, Maynard R. Air pollution and health. 1999, San Diego/London: Academic Press.
- 5. Zhang LW, Chen X, Xue XD, Sun M, Han B, Li CP, et al. Long-term exposure to high particulate matter pollution and cardiovascular mortality: a 12-year cohort study in four cities in northern China. Environ Int 2014;62:41–7. 10.1016/j.envint.2013.09.012. 24161381.ArticlePubMed
- 6. Katsouyanni K, Touloumi G, Spix C. Short-term effects of ambient sulphur dioxide and particulate matter on mortality in 12 European cities: results from times series data from the APHEA project. BMJ 1997;314:1658–63. 10.1136/bmj.314.7095.1658. 9180068.ArticlePubMedPMC
- 7. Hong YC, Leem JH, Ha EH, Christiani DC. PM(10) exposure, gaseous pollutants, and daily mortality in Inchon. South Korea Environ Health Perspect 1999;107(11):873–8.PubMed
- 8. Bates D. Health indices of the adverse effects of air pollution: the question of coherence. Environ Res 1992;59:336–49. 10.1016/S0013-9351(05)80040-4. 1464287.ArticlePubMed
- 9. Brauer M, Amann M, Burnett RT, Cohen A, Dentener F, Ezzati M, et al. Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution. Environ Sci Technol 2012;46(2):652–60. 10.1021/es2025752. 22148428.ArticlePubMedPMC
- 10. Ministry of Environment. Annual Report of Ambient Air Quality in Korea. 2012.
- 11. Ostro B, Sanchez J, Aranda C, Eskeland G. Air pollution and mortality: results from a study of Santiago, Chile. J Exp Anal Environ Epidemiol 1996;6:97–114.
- 12. Künzli N, Kaiser R, Medina S, Studnicka M, Chanel O, Filliger P, et al. Public-health impact of outdoor and traffic-related air pollution: a European assessment. Lancet 2000;356(9232):795–801. 10.1016/S0140-6736(00)02653-2. 11022926.ArticlePubMed
- 13.
- 14. Carter WPL. Documentation of the SAPRC-99 Chemical Mechanism for VOC Reactivity Assessment, Report to California Air Resources Board, Contracts 92–329 and 95–308. 1999.
- 15. Guenther A, Karl T, Harley P, Wiedinmyer C, Palmer PI, Geron C. Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature). Atmos Chem Phys 2006;6:3181–210. 10.5194/acp-6-3181-2006.Article
- 16. Pope CA III, Burnett RT, Thun MJ, Calle EE, Krewski D, Ito K, et al. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA 2002;287:1132–41. 10.1001/jama.287.9.1132. 11879110.ArticlePubMedPMC
- 17. Pope CA III. Respiratory hospital admissions associated with PM10 pollution in Utah, Salt Lake, and Cache Valleys. Arch Environ Health 1991;46(2):90–7. 10.1080/00039896.1991.9937434. 2006899.ArticlePubMed
- 18. Spix C, Anderson HR, Schwartz J, Vigotti MA, LeTertre A, Vonk JM, et al. Short-term effects of air pollution on hospital admissions of respiratory diseases in Europe: a quantitative summary of APHEA study results. Air Pollution and Health: a European Approach. Arch Environ Health 1998;53(1):54–64. 10.1080/00039899809605689. 9570309.PubMed
- 19. Wordley J, Walters S, Ayres J. Short term variations in hospital admissions and mortality and particulate air pollution. Occup Environ Health 1997;54:108–16.ArticlePubMedPMC
- 20. Prescott GJ, Cohen GR, Elton RA, Fowkes FG, Agium RM. Urban air pollution and cardiopulmonary ill health: a 14.5 year time series study. Occup Environ Med 1998;55:697–704. 10.1136/oem.55.10.697. 9930092.ArticlePubMedPMC
- 21. Poloniecki J, Atkinson R. Ponce de Leon A, Anderson H. Daily time series for cardiovascular hospital admissions and previous day’s air pollution in London, UK. Occup Environ Health 1997;54:535–40.
- 22. Medina S, Le Terte A, Dusseux E. Evaluation des Risques de la Pollution Urbaine sur lar Sante (ERPURS). Analyse des liens a court terme entre pollution atmosherique et sante: resultats 1991–95. 1997, Paris: Conseil Regional d’lle de France.
- 23. Abbey D, Petersen F, Mills P, Beeson W. Long-term ambient concentrations of total suspended particulates, ozone, and sulfur dioxide and respiratory symptoms in a nonsmoking population. Arch Environ Health 1993;48:33–46. 10.1080/00039896.1993.9938391. 8452397.ArticlePubMed
- 24. Dockery D, Speizer F, Stram D, Ware J, Spengler J, Ferris BJ. Effects of inhalable particles on respiratory health of children. Am Rev Respir Dis 1989;139:587–94. 10.1164/ajrccm/139.3.587. 2923355.ArticlePubMed
- 25. Dockery D, Cunningham J, Damokosh A, Neas LM, Spengler JD, Koutrakis P, et al. Health Effects of acid aerosols on north American Children: respiratory symptoms. Env Health Perspect 1996;104:500–5. 10.1289/ehp.96104500. 8743437.ArticlePubMedPMC
- 26. Braun-Fahrlander C, Vuille J, Sennhauser F, Neu U, Künzle T, Grize L, et al. Respiratory health and long-term exposure to air pollutants in Swiss Schoolchildren. Am J Respir Crit Care Med 1997;155:1042–9. 10.1164/ajrccm.155.3.9116984. 9116984.ArticlePubMed
- 27. Raaschou-Nielsen O, Andersen ZJ, Beelen R, Samoli E, Stafoggia M, Weinmayr G, et al. Air pollution and lung cancer incidence in 17 European cohorts: prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE). Lancet Oncol 2013;14(9):813–22. 10.1016/S1470-2045(13)70279-1. 23849838.PubMed
- 28. Roemer W, Hoek G, Brunekreef B. Effect of ambient winter air pollution on respiratory health of children with chronic respiratory symptoms. Am Rev Respir Dis 1993;147:118–24. 10.1164/ajrccm/147.1.118. 8420404.ArticlePubMed
- 29. Segala C, Fauroux B, Just J. Short-term effect of winter air pollution on respiratory health of asthmatic children in Paris. Eur Respir J 1998;11:677–85. 9596121.ArticlePubMed
- 30. Gielen M, van der Zee S, van Wijnen J. Acute effects of summer air pollution on respiratory health of asthmatic children. Am J Respir Crit Care Med 1997;155:2105–8. 10.1164/ajrccm.155.6.9196122. 9196122.ArticlePubMed
- 31. Dusseldorp A, Kruize H, Brunekreef B. Associations of PM10 and airborne iron with respiratory health of adults living near a steel factory. Am J Respir Crit Care Med 1995;152:1032–9. 10.1164/ajrccm.152.6.8520758.Article
- 32. Hiltermann T, Stolk J, van der Zee S. Asthma severity and susceptibility to air pollution. Eur Respir J 1998;11:686–93. 9596122.ArticlePubMed
- 33. Neukirch F, Segala C, Le Moullec Y. Short-term effects of low-level winter pollution on respiratory health of asthmatic adults. Arch Environ Health 1998;53:320–8. 10.1080/00039899809605716. 9766476.ArticlePubMed
- 34. Abbey D, Hwang B, Burchette R. Estimated long-term ambient concentrations of PM10 and development of respiratory symptoms in a nonsmoking population. Arch Environ Health 1995;50:139–52. 10.1080/00039896.1995.9940891. 7786050.ArticlePubMed
- 35. Ostro B, Chesnut L. Assessing the health benefits of reducing particulate matter air pollution in the United States. Environ Res 1998;76:94–106. 10.1006/enrs.1997.3799. 9515064.ArticlePubMed
- 36.
- 37. http://www.oecd.org/els/health-systems/49105858.pdf.
- 38. Jung KW, Park S, Kong HJ, Won YJ, Lee JY, Seo HG, et al. Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2009. Cancer Res Treat 2012;44(1):11–24. 10.4143/crt.2012.44.1.11. 22500156.ArticlePubMedPMC
- 39. McMichael A, Anderson H, Brunekreef B, Cohen A. Inappropriate use of daily mortality analyses to estimate longer-term mortality effects of air pollution. Int J Epidemiol 1998;27:450–3. 10.1093/ije/27.3.450. 9698134.ArticlePubMed
- 40. Abbey D, Nishino N, McDonnel W, Burchette RJ, Knutsen SF, Lawrence Beeson W, et al. Long-term inhalable particles and other air pollutants related to mortality in nonsmokers. Am J Respir Crit Care Med 1999;159:373–82. 10.1164/ajrccm.159.2.9806020. 9927346.ArticlePubMed
- 41. Baldi I, Roussillon C, Filleul L. Effect of air pollution on longterm mortality: description of mortality rates in relation to pollutants levels in the French PAARC Study. Eur Respir J 1999;24(suppl 30):S392.
- 42. Zemp E, Elsasser S, Schindler C, Künzli N, Perruchoud AP, Domenighetti G, et al. Long-term ambient air pollution and chronic respiratory symptoms (SAPALDIA). Am J Respir Crit Care Med 1999;159:1257–66. 10.1164/ajrccm.159.4.9807052. 10194174.ArticlePubMed
- 43. Kim SY, Lee JT, Hong YC, Ahn KJ, Kim H. Determining the threshold effect of ozone on daily mortality: an analysis of ozone and mortality in Seoul, Korea, 1995–1999. Environ Res 2004;94(2):113–9. 10.1016/j.envres.2003.09.006. 14757374.ArticlePubMed
- 44. Brunekreef B. Air pollution kills babies. Epidemiology 1999;10:661–2. 10.1097/00001648-199911000-00001. 10535775.ArticlePubMed
- 45. Council NRD(NRDC). Breath taking: premature mortality due to particulate air pollution in 239 American cities. 1996, San Francisco: NRDC.
- 46. Son JY, Lee JT, Park YH, Bell ML. Short-term effects of air pollution on hospital admissions in Korea. Epidemiology 2013;24(4):545–54. 10.1097/EDE.0b013e3182953244. 23676269.ArticlePubMed
- 47. Park HY, Bae S, Hong YC. PM10 exposure and non-accidental mortality in Asian populations: a meta-analysis of time-series and case-crossover studies. J Prev Med Public Health 2013;46(1):10–8. 10.3961/jpmph.2013.46.1.10. 23407325.ArticlePubMedPMC
- 48. Kim YJ, Lee BE, Park HS, Kang JG, Kim JO, Ha EH. Risk factors for preterm birth in Korea: a multicenter prospective study. Gynecol Obstet Invest 2005;60(4):206–12. 10.1159/000087207. 16088197.ArticlePubMedPDF
- 49. Kim E, Park H, Hong YC, Ha M, Kim Y, Kim BN, et al. Prenatal exposure to PM10 and NO2 and children’s neurodevelopment from birth to 24 months of age: mothers and Children’s Environmental Health (MOCEH) study. Sci Total Environ 2014;481:439–45. 10.1016/j.scitotenv.2014.01.107. 24631606.ArticlePubMed
- 50. Dora C. A different route to health: implications of transport policies. BMJ 1999;318:1686–9. 10.1136/bmj.318.7199.1686. 10373178.ArticlePubMedPMC
- 51. Sommer H, Chanel O, Vergnaud JC, Herry M, Sedlak N, Seethaler R. Monetary valuation of road traffic related air pollution: health costs due to road traffic-related air pollution: an impact assessment project of Austria, France and Switzerland third WHO Ministerial Conference of Environment & Health. 1999, London: WHO.
- 52. Kunzli N, Kaiser R, Medina S, Studnicka M, Oberfeld G, Horak F Jr. Health costs due to road traffic-related air pollution: an impact assessment project of Austria, France and Switzerland. (Air pollution attributable cases. Technical report on epidemiology). 1999, Switzerland: Federal Department for Environment, Energy and Communications Bureau for Transport Studies.
- 53. Filliger P, Puybonnieux-Texier V, Schneider J. PM10 population exposure technical report on air pollution: health costs due to road traffic-related air pollution: an impact assessment project of Austria, France and Switzerland. 1999, London: WHO.
References
Figure & Data
REFERENCES
Citations
Citations to this article as recorded by 
- Economic burden of transport related pollution in Australia
Jiayi Li, Cheng Wang, Shiva Abdoli, Anthony C.Y. Yuen, Sanghoon Kook, Guan H. Yeoh, Qing N. Chan
Journal of Transport & Health.2024; 34: 101747. CrossRef - Indoor and Outdoor Air Quality Correlation in Hospitals of Al-Qadisiyah Governorate, Iraq
Yaqoob Yousif Abid Al-Rudha, Safaa A. Kadhum
IOP Conference Series: Earth and Environmental Science.2023; 1262(2): 022020. CrossRef - Assessing the Spatiotemporal Characteristics, Factor Importance, and Health Impacts of Air Pollution in Seoul by Integrating Machine Learning into Land-Use Regression Modeling at High Spatiotemporal Resolutions
Yue Li, Tageui Hong, Yefu Gu, Zhiyuan Li, Tao Huang, Harry Fung Lee, Yeonsook Heo, Steve H. L. Yim
Environmental Science & Technology.2023; 57(3): 1225. CrossRef - Measurement of fine particle concentrations and estimation of air quality index (AQI) over northeast Douala, Cameroon
Cyrille Adiang Mezoue, Yannick Cedric Ngangmo, Arti Choudhary, David Monkam
Environmental Monitoring and Assessment.2023;[Epub] CrossRef - A Study on the Preliminary Plan for Environmental Health in Seoul, Korea
Jong-Seok Won, Hyomi Kim, Sang-Gyoon Kim
International Journal of Environmental Research and Public Health.2022; 19(24): 16611. CrossRef - Air pollution and risk of respiratory and cardiovascular hospitalizations in a large city of the Mekong Delta Region
Diep Ngoc Le, Ha Ai Phan Nguyen, Dang Tran Ngoc, Thuong Hoai Thi Do, Nghia Tuan Ton, Tuan Van Le, Tinh Huu Ho, Chinh Van Dang, Phong K. Thai, Dung Phung
Environmental Science and Pollution Research.2022; 29(60): 91165. CrossRef - Females with impaired ovarian function could be vulnerable to environmental pollutants: identification via next-generation sequencing of the vaginal microbiome
Seongmin Kim, Se Hee Lee, Kyung Jin Min, Sanghoon Lee, Jin Hwa Hong, Jae Yun Song, Jae Kwan Lee, Nak Woo Lee, Eunil Lee
Journal of Obstetrics and Gynaecology.2022; 42(5): 1482. CrossRef - Nanofiber-Based Face Masks and Respirators as COVID-19 Protection: A Review
Wafa Essa, Suhad Yasin, Ibtisam Saeed, Gomaa Ali
Membranes.2021; 11(4): 250. CrossRef - The Combined Effects of Fine Particulate Matter and Temperature on Preterm Birth in Seoul, 2010–2016
Youngrin Kwag, Min-ho Kim, Shinhee Ye, Jongmin Oh, Gyeyoon Yim, Young Ju Kim, Eunji Kim, Semi Lee, Tai Kyung Koh, Eunhee Ha
International Journal of Environmental Research and Public Health.2021; 18(4): 1463. CrossRef - The impact of PM2.5 on acute otitis media in children (aged 0–3): A time series study
Jongmin Oh, Seulbi Lee, Min-ho Kim, Youngrin Kwag, Hae Soon Kim, Soontae Kim, Shinhee Ye, Eunhee Ha
Environment International.2020; 145: 106133. CrossRef - Evaluations on PM2.5 Concentrations and the Population Exposure Levels for Local Authorities in South Korea during 2015~2017
Kyuwon Son, Eunhye Kim, Minah Bae, Seunghee You, Yoon-Hee Kang, Hyun Cheol Kim, Byeong-Uk Kim, Soontae Kim
Journal of Korean Society for Atmospheric Environment.2020; 36(6): 806. CrossRef - Air quality co-benefits from climate mitigation for human health in South Korea
Satbyul Estella Kim, Yang Xie, Hancheng Dai, Shinichiro Fujimori, Yasuaki Hijioka, Yasushi Honda, Masahiro Hashizume, Toshihiko Masui, Tomoko Hasegawa, Xinghan Xu, Kan Yi, Ho Kim
Environment International.2020; 136: 105507. CrossRef - The Impact of Ambient Fine Particulate Matter on Consumer Expenditures
Hojin Jung
Sustainability.2020; 12(5): 1855. CrossRef - Impact of Urbanization on PM2.5-Related Health and Economic Loss in China 338 Cities
Beidi Diao, Lei Ding, Qiong Zhang, Junli Na, Jinhua Cheng
International Journal of Environmental Research and Public Health.2020; 17(3): 990. CrossRef - Estimating the Shutdown Effect of the Old Coal-fired Power Plants on PM2.5 and its Composition
Minah Bae, Cheol Yoo, Soontae Kim
Journal of Korean Society for Atmospheric Environment.2020; 36(1): 48. CrossRef - Inter-comparisons of Spatially Interpolated Short-term and Long-term PM2.5 Concentrations of Local Authorities in South Korea 2015~2017
Kyuwon Son, Seunghee You, Hyun Cheol Kim, Byeong-Uk Kim, Soontae Kim
Journal of Korean Society for Atmospheric Environment.2020; 36(2): 185. CrossRef - Space-Borne Monitoring of NOx Emissions from Cement Kilns in South Korea
Hyun Cheol Kim, Changhan Bae, Minah Bae, Okgil Kim, Byeong-Uk Kim, Chul Yoo, Jinsoo Park, Jinsoo Choi, Jae-bum Lee, Barry Lefer, Ariel Stein, Soontae Kim
Atmosphere.2020; 11(8): 881. CrossRef - Long-term Effects of Cumulative Average PM2.5 Exposure on the Risk of Hemorrhagic Stroke
Juhwan Noh, Jungwoo Sohn, Minkyung Han, Dae Ryong Kang, Yoon Jung Choi, Hyeon Chang Kim, Il Suh, Changsoo Kim, Dong Chun Shin
Epidemiology.2019; 30(Supplement): S90. CrossRef - Current State of Research on the Risk of Morbidity and Mortality Associated with Air Pollution in Korea
Sanghyuk Bae, Ho-jang Kwon
Yonsei Medical Journal.2019; 60(3): 243. CrossRef - Health risk assessment for occupants as a decision-making tool to quantify the environmental effects of particulate matter in construction projects
Seunghoon Jung, Hyuna Kang, Seulki Sung, Taehoon Hong
Building and Environment.2019; 161: 106267. CrossRef - Effect of air pollutant emission reduction policies on hospital visits for asthma in Seoul, Korea; Quasi-experimental study
Hyomi Kim, Honghyok Kim, Jong-Tae Lee
Environment International.2019; 132: 104954. CrossRef - 미세먼지, 생명권에 대한 책무성
Gilyong Park
Journal of Policy Development.2019; 19(1): 155. CrossRef - Interventions to reduce ambient particulate matter air pollution and their effect on health
Jacob Burns, Hanna Boogaard, Stephanie Polus, Lisa M Pfadenhauer, Anke C Rohwer, Annemoon M van Erp, Ruth Turley, Eva Rehfuess
Cochrane Database of Systematic Reviews.2019;[Epub] CrossRef - The Effects of Transboundary Air Pollution From China on Ambient Air Quality in South Korea
Moon Joon Kim
SSRN Electronic Journal .2019;[Epub] CrossRef - Air pollution and hospital admissions for cardiovascular diseases in Ahvaz, Iran
Maryam Dastoorpoor, Zohreh Sekhavatpour, Kambiz Masoumi, Mohammad Javad Mohammadi, Hamidreza Aghababaeian, Narges Khanjani, Bayram Hashemzadeh, Mostafa Vahedian
Science of The Total Environment.2019; 652: 1318. CrossRef - Electrospun nanofiber filters for highly efficient PM2.5 capture
Changwoo Nam, Sukyoung Lee, Min Ryu, Jaewook Lee, Hyomin Lee
Korean Journal of Chemical Engineering.2019; 36(10): 1565. CrossRef - Premature Deaths Attributable to Long-term Exposure to Ambient Fine Particulate Matter in the Republic of Korea
Jong-Hun Kim, In-Hwan Oh, Jae-Hyun Park, Hae-Kwan Cheong
Journal of Korean Medical Science.2018;[Epub] CrossRef - Spatial and Temporal Trends of Number of Deaths Attributable to Ambient PM2.5in the Korea
Changwoo Han, Soontae Kim, Youn-Hee Lim, Hyun-Joo Bae, Yun-Chul Hong
Journal of Korean Medical Science.2018;[Epub] CrossRef - Review of Shandong Peninsular Emissions Change and South Korean Air Quality
Hyun Cheol Kim, Seulgi Kwon, Byeong-Uk Kim, Soontae Kim
Journal of Korean Society for Atmospheric Environment.2018; 34(2): 356. CrossRef - Impact of air pollution on cause-specific mortality in Korea: Results from Bayesian Model Averaging and Principle Component Regression approaches
Hien Tran, Jeongyeong Kim, Daeun Kim, Minyoung Choi, Minha Choi
Science of The Total Environment.2018; 636: 1020. CrossRef - Environmental Legal & Policy Views on PM-2.5
ByungchunSo
Environmental Law Review.2018; 40(3): 221. CrossRef - Development and Application of the Backward-tracking Model Analyzer to Track Physical and Chemical Processes of Air Parcels during the Transport
Minah Bae, Hyun Cheol Kim, Byeong-Uk Kim, Soontae Kim
Journal of Korean Society for Atmospheric Environment.2017; 33(3): 217. CrossRef - Analysis of the operating parameters of a vortex electrostatic precipitator
Congxiang Lu (陆从相), Chengwu Yi (依成武), Rongjie Yi (依蓉婕), Shiwen Liu (刘诗雯)
Plasma Science and Technology.2017; 19(2): 025504. CrossRef - Influence of fossil-fuel power plant emissions on the surface fine particulate matter in the Seoul Capital Area, South Korea
Byeong-Uk Kim, Okgil Kim, Hyun Cheol Kim, Soontae Kim
Journal of the Air & Waste Management Association.2016; 66(9): 863. CrossRef - Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City
Julio Zúñiga, Musharaf Tarajia, Víctor Herrera, Wilfredo Urriola, Beatriz Gómez, Jorge Motta
Medicine.2016; 95(2): e2464. CrossRef - Investigation on the ambient air quality in a hospital environment
C.O. Ayodele, B.S. Fakinle, L.A. Jimoda, J.A. Sonibare, Peter Christiaan Speldewinde
Cogent Environmental Science.2016; 2(1): 1215281. CrossRef
PubReader
ePub Link
Cite
XML DownloadPublic-health impact of outdoor air pollution for 2nd air pollution management policy in Seoul metropolitan area, Korea
Figure 1
PM2.5 concentration without reducing air emissions at 2024.
Figure 2
PM2.5 concentration after reducing air emissions at 2024.
Figure 3
Flow chart of this study.
Figure 1
Figure 2
Figure 3
Public-health impact of outdoor air pollution for 2nd air pollution management policy in Seoul metropolitan area, Korea
| Health Outcome | Definition | Source of exposure-response function | Source of population frequency |
|---|---|---|---|
| Long-term mortality Adult age ≥ 30 | Death rate, excluding violent death or accidents, >30 years | Dockery DW et al. [1] | National death certificate statistics for 2010 and 2024(prediction) (adults _30 years) |
| Pope CA et al. [2] | |||
| Pope CA et al. [15] | |||
| Respiratory hospital admissions (All age) | ICD9 460–519 | Pope CA et al. [16] | National population statistics for 2010 and 2024(prediction) |
| ICD9 466, 480–487, 493, 490– | Spix C et al. [17] | ||
| 492, 494–496 | Wordley J et al. [18] | ||
| ICD9 480–487, 490–496 | Prescott GJ et al. [19] | ||
| Cadiovascular hospital admissions (All age) | ICD9 410–436 | Wordley J et al. [18] | National population statistics for 2010 and 2024(prediction) |
| ICD9 390–459 | Poloniecki JD et al. [20] | ||
| ICD9 390–459 | Medina S et al. [21] | ||
| ICD9 410–414, 426–429, 434–440 | Prescott GJ et al. [19] | ||
| Lung cancer incidence | ICD9 162 | Raaschou-Nielsen O et al. [26] | |
| Asthma attack (children < 15 years) | Lower respiratory symptoms, age 6–12 years | Roemer W et al. [27] | National population statistics for 2010 and 2024(prediction) |
| Asthma, age 7–15 years | Segala C et al. [28] | ||
| Lower respiratory symptoms, age 7–13 years | Gielen MH et al. [29] | ||
| Asthma attack (adults ≥ 15 years) | Wheeze, age 18–80 years | Dusseldorp A et al. [30] | National population statistics for 2010 and 2024(prediction) |
| Shortness of breath, age 18–55 years | Hiltermann TJN et al. [31] | ||
| Wheeze, age 16–70 years | Neukirch F et al. [32] | ||
| Chronic-bronchitis | Symptoms of cough and/or sputum production on most days, for at least 3 months per year, and for 2 years or more | Abbey D et al. [22] | National population statistics for 2010 and 2024(prediction) |
| Acute bronchitis (age ≤ 18) | Bronchitis in past 12 months, ages less than 18 years. | Dockery DW et al. [23] | National population statistics for 2010 and 2024(prediction) |
| Health Outcome | Effect estimate relative risk (95% CI)per 10 μg/m 3 PM 10 | Health outcome frequency per million inhabitants per year |
|---|---|---|
| Long-term mortality Adult age ≥ 30 | 1 · 06 (1 · 02–1 · 11)* | 5,950 |
| Respiratory hospital admissions (All age) | 1 · 013 (1 · 001–1 · 025) | 15,630 |
| Cadiovascular hospital admissions (All age) | 1 · 013 (1 · 007–1 · 019) | 15,430 |
| Lung cancer incidence | 1 · 22 (1 · 03-1 · 45) | 287 |
| Asthma attack (children < 15 years) | 1 · 044 (1 · 027–1 · 062) | 19,930 |
| Asthma attack (adults ≥ 15 years) | 1 · 039 (1 · 019–1 · 059) | 24,570 |
| Chronic-bronchitis (adults 25 years) | 1 · 098 (1 · 009–1 · 194) | 4,990 |
| Acute bronchitis (age ≤ 18) | 1 · 306 (1 · 135–1 · 502) | 100,720 |
| Health outcome | 2010 | 2024 Without regulation about air pollution | 2024 PM 2.5 20 μg/m 3 PM 10 30 μg/m 3 | 2024, the reducible number and fraction (%) |
|---|---|---|---|---|
| 95% CI | 95% CI | 95% CI | ||
| Premature deaths /persons/year) | 15,346 (4,498 ~ 26,242) | 25,781 (7,555 ~ 44,098) | 10,866 (3,280 ~ 18,081) | 14,915 (57.9%∇) |
| Respiratory hospital admissions (All age) | 12,511 (956 ~ 23,583) | 14,163 (1,114 ~ 26,701) | 7,837 (611 ~ 14,865) | 6,326 (44.7%∇) |
| Cardiovascular hospital admissions (All age) | 12,351 (6,715 ~ 17,868) | 13,982 (7,602 ~ 20,229) | 7,736 (4,193 ~ 11,227) | 6,246 (44.7%∇) |
| Lung cancer incidence | 1,403 (254 ~ 2,170) | 1,590 (287 ~ 2,462) | 962 (159 ~ 1,613) | 628 (45.2%∇) |
| Asthma attack (children < 18 years) | 11,389 (7,180 ~ 15,601) | 9,745 (6,143 ~ 13,350) | 5,563 (3477 ~ 7,688) | 4,182 (42.9%∇) |
| Asthma attack (adults ≥ 18 years) | 44,006 (22,142 ~ 64,488) | 53,300 (26,813 ~ 78,128) | 29,789 (14,835 ~ 44,093) | 23,511 (44.1%∇) |
| Chronic-bronchitis | 20,490 (219 ~ 35,340) | 24,836 (265 ~ 42,884) | 14,276 (145 ~ 25,686) | 10,560 (42.5%∇) |
| Acute bronchitis (age ≤ 18) | 278,346 (153,949 ~ 360,290) | 238,222 (131,744 ~ 313,483) | 151,943 (78,491 ~ 212,851) | 86,279 (36.2%∇) |
Table 1
Health outcome definition and source of data
Table 2
Effect estimate of health outcome and health outcome frequencies
*per 10 μg/m3 PM2.5.
Table 3
Health outcome attributed to particulate air pollution in Seoul metropolitan area
