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Association between air pollution in the 2015 winter in South Korea and population size, car emissions, industrial activity, and fossil-fuel power plants: an ecological study

BACKGROUND: Compared to 10 years ago, the ambient particulate matter 10 (PM(10)) and carbon monoxide (CO) levels in South Korea have decreased. However, compared to many other OECD countries, these levels are still too high. Concentration of air pollutants such as PM(10) is especially higher during...

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Detalles Bibliográficos
Autores principales: Choi, Hyeran, Myong, Jun-Pyo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173887/
https://www.ncbi.nlm.nih.gov/pubmed/30323933
http://dx.doi.org/10.1186/s40557-018-0273-5
Descripción
Sumario:BACKGROUND: Compared to 10 years ago, the ambient particulate matter 10 (PM(10)) and carbon monoxide (CO) levels in South Korea have decreased. However, compared to many other OECD countries, these levels are still too high. Concentration of air pollutants such as PM(10) is especially higher during winter than during summer. The first step to rationally solving the air pollution problem in Korea is to identify the key air pollution sources during each season. This ecological study was performed to assess the association between the number of days the accepted PM(10) and CO thresholds were exceeded and the concentration of potential emission sources in winter season 2015. METHODS: An emission inventory of the PM(10) and CO emissions in the 232 administrative South Korean districts in January, 2015, and February, 2015 and December, 2015, and the population density, number of car registrations, number of car accidents, industrial power usage, and presence of a fossil-fuel power plant in each district was established on the basis of official web-page data from the government. For all emission source variables except power plants, the administrative districts were grouped into quartiles. Districts were also divided according to whether a power plant was present or not. Negative binomial regression was performed to assess the associations between the PM(10) and CO air pollution (defined as ≥100 g/m(3) and ≥ 9 ppm, respectively) and the concentration of each emission source. RESULTS: Compared to the districts with the lowest population density, the districts with the third highest population density associated most strongly with air pollution. This was also observed for industrial power usage. Car accident number and car registration numbers showed a linear relationship with air pollution. Districts with power plants were significantly more likely to have air pollution than districts that lacked a plant. CONCLUSIONS: Greater car numbers, industrial activity, and population density, and the presence of fossil-fuel plants associated with air pollution in the 2015 winter in South Korea. These data highlight the contaminant sources that could be targeted by interventions that aim to reduce air pollution, decrease the incidence of exposure, and limit the impact of pollution on human health. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40557-018-0273-5) contains supplementary material, which is available to authorized users.