A study on modeling nitrogen dioxide concentrations using land-use regression and conventionally used exposure assessment methods

Giehae Choi, Michelle L. Bell, Jong-Tae Lee

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The land-use regression (LUR) approach to estimate the levels of ambient air pollutants is becoming popular due to its high validity in predicting small-area variations. However, only a few studies have been conducted in Asian countries, and much less research has been conducted on comparing the performances and applied estimates of different exposure assessments including LUR. The main objectives of the current study were to conduct nitrogen dioxide (NO2) exposure assessment with four methods including LUR in the Republic of Korea, to compare the model performances, and to estimate the empirical NO2 exposures of a cohort. The study population was defined as the year 2010 participants of a government-supported cohort established for bio-monitoring in Ulsan, Republic of Korea. The annual ambient NO2 exposures of the 969 study participants were estimated with LUR, nearest station, inverse distance weighting, and ordinary kriging. Modeling was based on the annual NO2 average, traffic-related data, land-use data, and altitude of the 13 regularly monitored stations. The final LUR model indicated that area of transportation, distance to residential area, and area of wetland were important predictors of NO2. The LUR model explained 85.8% of the variation observed in the 13 monitoring stations of the year 2009. The LUR model outperformed the others based on leave-one out cross-validation comparing the correlations and root-mean square error. All NO2 estimates ranged from 11.3-18.0 ppb, with that of LUR having the widest range. The NO2 exposure levels of the residents differed by demographics. However, the average was below the national annual guidelines of the Republic of Korea (30 ppb). The LUR models showed high performances in an industrial city in the Republic of Korea, despite the small sample size and limited data. Our findings suggest that the LUR method may be useful in similar settings in Asian countries where the target region is small and availability of data is low.

Original languageEnglish
Article number044003
JournalEnvironmental Research Letters
Volume12
Issue number4
DOIs
Publication statusPublished - 2017 Mar 27

Fingerprint

Nitrogen Dioxide
Republic of Korea
nitrogen dioxide
assessment method
Land use
Nitrogen
land use
modeling
Small-Area Analysis
Air Pollutants
Spatial Analysis
Wetlands
Environmental Monitoring
Sample Size
Demography
Guidelines
exposure
Research
Population
Monitoring

Keywords

  • exposure assessment
  • inverse distance weighting
  • kriging
  • land-use regression
  • nitrogen dioxide

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Public Health, Environmental and Occupational Health

Cite this

A study on modeling nitrogen dioxide concentrations using land-use regression and conventionally used exposure assessment methods. / Choi, Giehae; Bell, Michelle L.; Lee, Jong-Tae.

In: Environmental Research Letters, Vol. 12, No. 4, 044003, 27.03.2017.

Research output: Contribution to journalArticle

@article{0257a45811f041749563c5f2fb3cdc30,
title = "A study on modeling nitrogen dioxide concentrations using land-use regression and conventionally used exposure assessment methods",
abstract = "The land-use regression (LUR) approach to estimate the levels of ambient air pollutants is becoming popular due to its high validity in predicting small-area variations. However, only a few studies have been conducted in Asian countries, and much less research has been conducted on comparing the performances and applied estimates of different exposure assessments including LUR. The main objectives of the current study were to conduct nitrogen dioxide (NO2) exposure assessment with four methods including LUR in the Republic of Korea, to compare the model performances, and to estimate the empirical NO2 exposures of a cohort. The study population was defined as the year 2010 participants of a government-supported cohort established for bio-monitoring in Ulsan, Republic of Korea. The annual ambient NO2 exposures of the 969 study participants were estimated with LUR, nearest station, inverse distance weighting, and ordinary kriging. Modeling was based on the annual NO2 average, traffic-related data, land-use data, and altitude of the 13 regularly monitored stations. The final LUR model indicated that area of transportation, distance to residential area, and area of wetland were important predictors of NO2. The LUR model explained 85.8{\%} of the variation observed in the 13 monitoring stations of the year 2009. The LUR model outperformed the others based on leave-one out cross-validation comparing the correlations and root-mean square error. All NO2 estimates ranged from 11.3-18.0 ppb, with that of LUR having the widest range. The NO2 exposure levels of the residents differed by demographics. However, the average was below the national annual guidelines of the Republic of Korea (30 ppb). The LUR models showed high performances in an industrial city in the Republic of Korea, despite the small sample size and limited data. Our findings suggest that the LUR method may be useful in similar settings in Asian countries where the target region is small and availability of data is low.",
keywords = "exposure assessment, inverse distance weighting, kriging, land-use regression, nitrogen dioxide",
author = "Giehae Choi and Bell, {Michelle L.} and Jong-Tae Lee",
year = "2017",
month = "3",
day = "27",
doi = "10.1088/1748-9326/aa6057",
language = "English",
volume = "12",
journal = "Environmental Research Letters",
issn = "1748-9326",
publisher = "IOP Publishing Ltd.",
number = "4",

}

TY - JOUR

T1 - A study on modeling nitrogen dioxide concentrations using land-use regression and conventionally used exposure assessment methods

AU - Choi, Giehae

AU - Bell, Michelle L.

AU - Lee, Jong-Tae

PY - 2017/3/27

Y1 - 2017/3/27

N2 - The land-use regression (LUR) approach to estimate the levels of ambient air pollutants is becoming popular due to its high validity in predicting small-area variations. However, only a few studies have been conducted in Asian countries, and much less research has been conducted on comparing the performances and applied estimates of different exposure assessments including LUR. The main objectives of the current study were to conduct nitrogen dioxide (NO2) exposure assessment with four methods including LUR in the Republic of Korea, to compare the model performances, and to estimate the empirical NO2 exposures of a cohort. The study population was defined as the year 2010 participants of a government-supported cohort established for bio-monitoring in Ulsan, Republic of Korea. The annual ambient NO2 exposures of the 969 study participants were estimated with LUR, nearest station, inverse distance weighting, and ordinary kriging. Modeling was based on the annual NO2 average, traffic-related data, land-use data, and altitude of the 13 regularly monitored stations. The final LUR model indicated that area of transportation, distance to residential area, and area of wetland were important predictors of NO2. The LUR model explained 85.8% of the variation observed in the 13 monitoring stations of the year 2009. The LUR model outperformed the others based on leave-one out cross-validation comparing the correlations and root-mean square error. All NO2 estimates ranged from 11.3-18.0 ppb, with that of LUR having the widest range. The NO2 exposure levels of the residents differed by demographics. However, the average was below the national annual guidelines of the Republic of Korea (30 ppb). The LUR models showed high performances in an industrial city in the Republic of Korea, despite the small sample size and limited data. Our findings suggest that the LUR method may be useful in similar settings in Asian countries where the target region is small and availability of data is low.

AB - The land-use regression (LUR) approach to estimate the levels of ambient air pollutants is becoming popular due to its high validity in predicting small-area variations. However, only a few studies have been conducted in Asian countries, and much less research has been conducted on comparing the performances and applied estimates of different exposure assessments including LUR. The main objectives of the current study were to conduct nitrogen dioxide (NO2) exposure assessment with four methods including LUR in the Republic of Korea, to compare the model performances, and to estimate the empirical NO2 exposures of a cohort. The study population was defined as the year 2010 participants of a government-supported cohort established for bio-monitoring in Ulsan, Republic of Korea. The annual ambient NO2 exposures of the 969 study participants were estimated with LUR, nearest station, inverse distance weighting, and ordinary kriging. Modeling was based on the annual NO2 average, traffic-related data, land-use data, and altitude of the 13 regularly monitored stations. The final LUR model indicated that area of transportation, distance to residential area, and area of wetland were important predictors of NO2. The LUR model explained 85.8% of the variation observed in the 13 monitoring stations of the year 2009. The LUR model outperformed the others based on leave-one out cross-validation comparing the correlations and root-mean square error. All NO2 estimates ranged from 11.3-18.0 ppb, with that of LUR having the widest range. The NO2 exposure levels of the residents differed by demographics. However, the average was below the national annual guidelines of the Republic of Korea (30 ppb). The LUR models showed high performances in an industrial city in the Republic of Korea, despite the small sample size and limited data. Our findings suggest that the LUR method may be useful in similar settings in Asian countries where the target region is small and availability of data is low.

KW - exposure assessment

KW - inverse distance weighting

KW - kriging

KW - land-use regression

KW - nitrogen dioxide

UR - http://www.scopus.com/inward/record.url?scp=85018486529&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85018486529&partnerID=8YFLogxK

U2 - 10.1088/1748-9326/aa6057

DO - 10.1088/1748-9326/aa6057

M3 - Article

AN - SCOPUS:85018486529

VL - 12

JO - Environmental Research Letters

JF - Environmental Research Letters

SN - 1748-9326

IS - 4

M1 - 044003

ER -