Mapping and statistical analysis of NO2 concentration for local government air quality regulation

Jieun Ryu, Chan Park, Seong Woo Jeon

Research output: Contribution to journalArticle

Abstract

With the growing interest in healthy living worldwide, there has been an increasing demand for more accurate measurements of the concentrations of air pollutants such as NO2. In particular, analyzing the characteristics and sources of air pollutants by region could improve the effectiveness of environmental policies applied in accordance with the environmental characteristics of individual regions. In this study, a detailed nationwide NO2 concentration map was generated using the cokriging interpolation technique, which integrates ground observations and satellite image data. The root-mean-square standardized (RMSS) error for this technique was close to 1, which indicates high accuracy. Using spatially interpolated NO2 concentration data, an administrative unit map was generated. When comparing the data for four NO2 data sources (observation data, satellite image data, detailed national data interpolated using cokriging, and NO2 concentrations averaged by an administrative unit based on the interpolated NO2 concentration data), the average concentrations were highest for remote sensing data. Land use regression (LUR) models of urban and non-urban regions were then developed to analyze the characteristics of the NO2 concentration by region using NO2 concentrations for the administrative units.

Original languageEnglish
Article number3809
JournalSustainability (Switzerland)
Volume11
Issue number14
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Air quality
statistical analysis
local government
Statistical methods
air quality
air
Satellites
regulation
Air
Land use
Mean square error
Remote sensing
Interpolation
pollutant
environmental policy
interpolation
land use
remote sensing
regression
demand

Keywords

  • Cokriging
  • County level
  • Interpolation
  • Land use regression model
  • Nitrogen dioxide
  • NO concentration map
  • Satellite image
  • Urban forest

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

Cite this

Mapping and statistical analysis of NO2 concentration for local government air quality regulation. / Ryu, Jieun; Park, Chan; Jeon, Seong Woo.

In: Sustainability (Switzerland), Vol. 11, No. 14, 3809, 01.01.2019.

Research output: Contribution to journalArticle

@article{8df3de3ad4cd4bbea4b0b32a0b901ffe,
title = "Mapping and statistical analysis of NO2 concentration for local government air quality regulation",
abstract = "With the growing interest in healthy living worldwide, there has been an increasing demand for more accurate measurements of the concentrations of air pollutants such as NO2. In particular, analyzing the characteristics and sources of air pollutants by region could improve the effectiveness of environmental policies applied in accordance with the environmental characteristics of individual regions. In this study, a detailed nationwide NO2 concentration map was generated using the cokriging interpolation technique, which integrates ground observations and satellite image data. The root-mean-square standardized (RMSS) error for this technique was close to 1, which indicates high accuracy. Using spatially interpolated NO2 concentration data, an administrative unit map was generated. When comparing the data for four NO2 data sources (observation data, satellite image data, detailed national data interpolated using cokriging, and NO2 concentrations averaged by an administrative unit based on the interpolated NO2 concentration data), the average concentrations were highest for remote sensing data. Land use regression (LUR) models of urban and non-urban regions were then developed to analyze the characteristics of the NO2 concentration by region using NO2 concentrations for the administrative units.",
keywords = "Cokriging, County level, Interpolation, Land use regression model, Nitrogen dioxide, NO concentration map, Satellite image, Urban forest",
author = "Jieun Ryu and Chan Park and Jeon, {Seong Woo}",
year = "2019",
month = "1",
day = "1",
doi = "10.3390/su11143809",
language = "English",
volume = "11",
journal = "Sustainability",
issn = "2071-1050",
publisher = "MDPI AG",
number = "14",

}

TY - JOUR

T1 - Mapping and statistical analysis of NO2 concentration for local government air quality regulation

AU - Ryu, Jieun

AU - Park, Chan

AU - Jeon, Seong Woo

PY - 2019/1/1

Y1 - 2019/1/1

N2 - With the growing interest in healthy living worldwide, there has been an increasing demand for more accurate measurements of the concentrations of air pollutants such as NO2. In particular, analyzing the characteristics and sources of air pollutants by region could improve the effectiveness of environmental policies applied in accordance with the environmental characteristics of individual regions. In this study, a detailed nationwide NO2 concentration map was generated using the cokriging interpolation technique, which integrates ground observations and satellite image data. The root-mean-square standardized (RMSS) error for this technique was close to 1, which indicates high accuracy. Using spatially interpolated NO2 concentration data, an administrative unit map was generated. When comparing the data for four NO2 data sources (observation data, satellite image data, detailed national data interpolated using cokriging, and NO2 concentrations averaged by an administrative unit based on the interpolated NO2 concentration data), the average concentrations were highest for remote sensing data. Land use regression (LUR) models of urban and non-urban regions were then developed to analyze the characteristics of the NO2 concentration by region using NO2 concentrations for the administrative units.

AB - With the growing interest in healthy living worldwide, there has been an increasing demand for more accurate measurements of the concentrations of air pollutants such as NO2. In particular, analyzing the characteristics and sources of air pollutants by region could improve the effectiveness of environmental policies applied in accordance with the environmental characteristics of individual regions. In this study, a detailed nationwide NO2 concentration map was generated using the cokriging interpolation technique, which integrates ground observations and satellite image data. The root-mean-square standardized (RMSS) error for this technique was close to 1, which indicates high accuracy. Using spatially interpolated NO2 concentration data, an administrative unit map was generated. When comparing the data for four NO2 data sources (observation data, satellite image data, detailed national data interpolated using cokriging, and NO2 concentrations averaged by an administrative unit based on the interpolated NO2 concentration data), the average concentrations were highest for remote sensing data. Land use regression (LUR) models of urban and non-urban regions were then developed to analyze the characteristics of the NO2 concentration by region using NO2 concentrations for the administrative units.

KW - Cokriging

KW - County level

KW - Interpolation

KW - Land use regression model

KW - Nitrogen dioxide

KW - NO concentration map

KW - Satellite image

KW - Urban forest

UR - http://www.scopus.com/inward/record.url?scp=85068991949&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85068991949&partnerID=8YFLogxK

U2 - 10.3390/su11143809

DO - 10.3390/su11143809

M3 - Article

AN - SCOPUS:85068991949

VL - 11

JO - Sustainability

JF - Sustainability

SN - 2071-1050

IS - 14

M1 - 3809

ER -