National-scale exposure prediction for long-term concentrations of particulate matter and nitrogen dioxide in South Korea

Kim, Sun‐Young; Song, Insang

doi:10.1016/j.envpol.2017.03.056

Cited by 45 publications

(32 citation statements)

References 30 publications

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“…In this approach, it is assumed that air pollution concentrations are composed of geographic predictors and spatial correlation [33]. We estimated a few summary predictors with more than 300 geographic variables using partial least squares (PLS) [34]. For PM 2.5 , because the PLS summary predictors showed an overfitting pattern, we instead applied land use regression, including five geographic variables selected using forward selection [35].…”

Section: Assessment Of Air Pollution Exposurementioning

confidence: 99%

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

Min

Kim

et al. 2020

Environ Health

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Background: Pediatric allergic diseases are a major public health concern, and previous studies have suggested that exposure to traffic-related air pollution (TRAP) exposure is a risk factor. These studies have typically assessed TRAP exposure using traffic measures, such as distance to major roads, or by modeling air pollutant concentrations; however inconsistent associations with pediatric allergic diseases have often been found. Using road proximity and density, we previously found an association between TRAP and atopic eczema among approximately 15,000 children living in Seoul, Korea, heavily populated and highly polluted city in which traffic is a major emission source. We aimed to conduct a parallel analysis using modeled air pollution concentrations and thus examine the consistency of the association. Specifically, we examined the associations of individual-level annual-average concentrations of NO 2 , PM 10 , and PM 2.5 with symptoms and diagnoses of three pediatric allergic diseases including asthma, allergic rhinitis, and atopic eczema. Methods: The study population included 14,614 children from the Seoul Atopy Friendly School Project Survey in Seoul, Korea, in 2010. To assess individual exposures to TRAP among these children, we predicted annualaverage concentrations of NO 2 , PM 10 , and PM 2.5 at the children's home addresses in 2010 using universal kriging and land use regression models along with regulatory air quality monitoring data and geographic characteristics. Then, we estimated odds ratios (ORs) of the three allergic diseases for interquartile increases in air pollution concentrations after adjusting for individual risk factors in mixed effects logistic regression. Results: Symptoms and diagnoses of atopic eczema symptoms showed an association with NO 2 (OR = 1.07, 95% confidence interval = 1.

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Section: Assessment Of Air Pollution Exposurementioning

confidence: 99%

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

Min

Kim

et al. 2020

Environ Health

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“…That is, results may be shown with no impact of air pollution due to using the average concentrations of air pollutants, although it may exist when using the actual values. A specific method of prediction was documented in another published article (31).…”

Section: Prediction For Long-term Concentrations Of Particulate Mattementioning

confidence: 99%

“…Specifically, Kim et al (31) developed the national prediction model by incorporating the annual mean concentration values of log-transformed NO 2 and PM 10 estimated at the 277 air quality monitoring sites between 2010 and 2016 after excluding 11 places that did not meet the inclusion criteria. In the process of developing a prediction model, 322 geographic variables that consist of proximity and buffer in eight categories, including traffic, physical geography, land use, demographic characteristics, etc.…”

Section: Prediction For Long-term Concentrations Of Particulate Mattementioning

confidence: 99%

Gender Difference in the Effects of Outdoor Air Pollution on Cognitive Function Among Elderly in Korea

Kim

Noh

et al. 2019

Front. Public Health

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“…The driving reason behind the interest is the effect of elevated levels of NO 2 in Korea on human health (Kim and Song, 2017 and references therein). Measurements of NO 2 from aircraft have been used to obtain altitude profiles to compare with data obtained from fixed site measurements and to obtain a national scale estimate of pollutant exposure (Lee et al, 2016;Kim and Song, 2017).…”

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confidence: 99%

NO<sub>2</sub> and HCHO measurements in Korea from 2012 to 2016 from Pandora spectrometer instruments compared with OMI retrievals and with aircraft measurements during the KORUS-AQ campaign

et al. 2018

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Abstract. Nine Pandora spectrometer instruments (PSI) were installed at eight sites in South Korea as part of the KORUS-AQ (Korea U.S.-Air Quality) field study integrating information from ground, aircraft, and satellite measurements for validation of remote sensing air-quality studies. The PSI made direct-sun measurements of total vertical column NO 2 , C(NO 2 ), with high precision (0.05 DU, where 1 DU = 2.69 × 10 16 molecules cm −2 ) and accuracy (0.1 DU) that were retrieved using spectral fitting techniques. Retrieval of formaldehyde C(HCHO) total column amounts were also obtained at five sites using the recently improved PSI optics. The C(HCHO) retrievals have high precision, but possibly lower accuracy than for NO 2 because of uncertainty about the optimum spectral window for all ground-based and satellite instruments. PSI direct-sun retrieved values for C(NO 2 ) and C(HCHO) are always significantly larger than OMI (AURA satellite Ozone Monitoring Instrument) retrieved C(NO 2 ) and C(HCHO) for the OMI overpass local times (KST = 13.5 ± 0.5 h). In urban areas, PSI C(NO 2 ) 30-day running averages are at least a factor of two larger than OMI averages. Similar differences are seen for C(HCHO) in Seoul and nearby surrounding areas. Late afternoon values of C(HCHO) measured by PSI are even larger, implying that OMI early afternoon measurements underestimate the effect of poor air quality on human health. The primary cause of OMI underestimates is the large OMI field of view (FOV) that includes regions containing low values of pollutants. In relatively clean areas, PSI and OMI are more closely in agreement. C(HCHO) amounts were obtained for five sites,

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National-scale exposure prediction for long-term concentrations of particulate matter and nitrogen dioxide in South Korea

Cited by 45 publications

References 30 publications

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

Gender Difference in the Effects of Outdoor Air Pollution on Cognitive Function Among Elderly in Korea

NO<sub>2</sub> and HCHO measurements in Korea from 2012 to 2016 from Pandora spectrometer instruments compared with OMI retrievals and with aircraft measurements during the KORUS-AQ campaign

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National-scale exposure prediction for long-term concentrations of particulate matter and nitrogen dioxide in South Korea

Cited by 45 publications

References 30 publications

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

Gender Difference in the Effects of Outdoor Air Pollution on Cognitive Function Among Elderly in Korea

NO&lt;sub&gt;2&lt;/sub&gt; and HCHO measurements in Korea from 2012 to 2016 from Pandora spectrometer instruments compared with OMI retrievals and with aircraft measurements during the KORUS-AQ campaign

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NO<sub>2</sub> and HCHO measurements in Korea from 2012 to 2016 from Pandora spectrometer instruments compared with OMI retrievals and with aircraft measurements during the KORUS-AQ campaign