Assessment of air quality in North Korea from satellite observations

Heesung Chong; Seoyoung Lee; Yeseul Cho; Jhoon Kim; Ja Ho Koo; Yong Pyo Kim; Younha Kim; Jung Hun Woo; Dha Hyun Ahn

doi:10.1016/j.envint.2022.107708

Assessment of air quality in North Korea from satellite observations

Heesung Chong, Seoyoung Lee, Yeseul Cho, Jhoon Kim, Ja Ho Koo, Yong Pyo Kim, Younha Kim, Jung Hun Woo, Dha Hyun Ahn

Department of Chemical Engineering & Materials Science

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

North Korea's air quality is poorly understood due to a lack of reliable data. Here, we analyzed urban- to national-scale air quality changes in North Korea using multi-year satellite observations. Pyongyang, Nampo, Pukchang, and Munchon were identified as pollution hotspots. On a national scale, we found that North Korea experienced 6.7, 17.8, and 20.6 times greater amounts of nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO) per unit primary energy supply (PES) than South Korea from 2005 to 2018. Besides, North Korea had a 24.3 times larger aerosol optical depth (AOD) per PES than South Korea from 2011 to 2018. Severe CO and aerosol pollution is aligned with extensive biofuel combustion. High SO₂ pollution corresponds with the strong coal dependence of the industry. The change rates of the national average columns for NO₂, SO₂, and CO were + 3.6, –4.4, and –0.4 % yr⁻¹, respectively. The AOD change rate was –4.8 % yr⁻¹. Overall decreasing trends, except for NO₂, are likely due to a decline in coal-fired PES. Positive NO₂ trends are consistent with increasing industrial activities. Each pollutant showed consistent patterns of linear trends, even after correcting the influence of transboundary pollution. Flue gas control and biofuel consumption reduction seem necessary to improve North Korea's air quality.

Original language	English
Article number	107708
Journal	Environment International
Volume	171
DOIs	https://doi.org/10.1016/j.envint.2022.107708
State	Published - Jan 2023

Bibliographical note

Funding Information:
The authors would like to acknowledge the support by Samsung Advanced Institute of Technology. This work was also supported by the Korea Ministry of Environment (MOE) under the Public Technology Program based on Environmental Policy (2017000160001). Additionally, this work was supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Project for New Climate Regime, funded by Korea Ministry of Environment (MOD) (2022003560007). The authors acknowledge the free use of the OMNO2, OMSO2, MOP02J_8, ERA5, GMTED, and GWPv4 datasets. The authors also acknowledge the free use of PM 2.5 measurements from Airkorea, the China National Urban Air Quality Real-time Publishing Platform, the Ministry of the Environment of Japan, and AEROS. GOCI data were provided by the Korea Institute of Ocean Science and Technology (KIOST). The authors acknowledge the free use of the physical oversampling algorithm developed by Kang Sun (https://github.com/Kang-Sun-CfA/Oversampling_matlab). The authors would like to thank Sara-Eva Mártinez-Alonso and David P. Edwards for their assistance with the MOPITT CO data interpretation. The authors also would like to thank Daniel Jacob and Min Ju Yeo for the fruitful discussion.

Funding Information:
The authors would like to acknowledge the support by Samsung Advanced Institute of Technology. This work was also supported by the Korea Ministry of Environment (MOE) under the Public Technology Program based on Environmental Policy (2017000160001). Additionally, this work was supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Project for New Climate Regime, funded by Korea Ministry of Environment (MOD) (2022003560007). The authors acknowledge the free use of the OMNO2, OMSO2, MOP02J_8, ERA5, GMTED, and GWPv4 datasets. The authors also acknowledge the free use of PM2.5 measurements from Airkorea, the China National Urban Air Quality Real-time Publishing Platform, the Ministry of the Environment of Japan, and AEROS. GOCI data were provided by the Korea Institute of Ocean Science and Technology (KIOST). The authors acknowledge the free use of the physical oversampling algorithm developed by Kang Sun (https://github.com/Kang-Sun-CfA/Oversampling_matlab). The authors would like to thank Sara-Eva Mártinez-Alonso and David P. Edwards for their assistance with the MOPITT CO data interpretation. The authors also would like to thank Daniel Jacob and Min Ju Yeo for the fruitful discussion.

Publisher Copyright:
© 2022

Keywords

Air quality
North Korea
Satellite observations

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.envint.2022.107708

Cite this

@article{299e2d654248444798ba50e026ba7cc1,

title = "Assessment of air quality in North Korea from satellite observations",

abstract = "North Korea's air quality is poorly understood due to a lack of reliable data. Here, we analyzed urban- to national-scale air quality changes in North Korea using multi-year satellite observations. Pyongyang, Nampo, Pukchang, and Munchon were identified as pollution hotspots. On a national scale, we found that North Korea experienced 6.7, 17.8, and 20.6 times greater amounts of nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) per unit primary energy supply (PES) than South Korea from 2005 to 2018. Besides, North Korea had a 24.3 times larger aerosol optical depth (AOD) per PES than South Korea from 2011 to 2018. Severe CO and aerosol pollution is aligned with extensive biofuel combustion. High SO2 pollution corresponds with the strong coal dependence of the industry. The change rates of the national average columns for NO2, SO2, and CO were + 3.6, –4.4, and –0.4 % yr−1, respectively. The AOD change rate was –4.8 % yr−1. Overall decreasing trends, except for NO2, are likely due to a decline in coal-fired PES. Positive NO2 trends are consistent with increasing industrial activities. Each pollutant showed consistent patterns of linear trends, even after correcting the influence of transboundary pollution. Flue gas control and biofuel consumption reduction seem necessary to improve North Korea's air quality.",

keywords = "Air quality, North Korea, Satellite observations",

author = "Heesung Chong and Seoyoung Lee and Yeseul Cho and Jhoon Kim and Koo, {Ja Ho} and {Pyo Kim}, Yong and Younha Kim and Woo, {Jung Hun} and {Hyun Ahn}, Dha",

note = "Funding Information: The authors would like to acknowledge the support by Samsung Advanced Institute of Technology. This work was also supported by the Korea Ministry of Environment (MOE) under the Public Technology Program based on Environmental Policy (2017000160001). Additionally, this work was supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Project for New Climate Regime, funded by Korea Ministry of Environment (MOD) (2022003560007). The authors acknowledge the free use of the OMNO2, OMSO2, MOP02J_8, ERA5, GMTED, and GWPv4 datasets. The authors also acknowledge the free use of PM 2.5 measurements from Airkorea, the China National Urban Air Quality Real-time Publishing Platform, the Ministry of the Environment of Japan, and AEROS. GOCI data were provided by the Korea Institute of Ocean Science and Technology (KIOST). The authors acknowledge the free use of the physical oversampling algorithm developed by Kang Sun (https://github.com/Kang-Sun-CfA/Oversampling_matlab). The authors would like to thank Sara-Eva M{\'a}rtinez-Alonso and David P. Edwards for their assistance with the MOPITT CO data interpretation. The authors also would like to thank Daniel Jacob and Min Ju Yeo for the fruitful discussion. Funding Information: The authors would like to acknowledge the support by Samsung Advanced Institute of Technology. This work was also supported by the Korea Ministry of Environment (MOE) under the Public Technology Program based on Environmental Policy (2017000160001). Additionally, this work was supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Project for New Climate Regime, funded by Korea Ministry of Environment (MOD) (2022003560007). The authors acknowledge the free use of the OMNO2, OMSO2, MOP02J_8, ERA5, GMTED, and GWPv4 datasets. The authors also acknowledge the free use of PM2.5 measurements from Airkorea, the China National Urban Air Quality Real-time Publishing Platform, the Ministry of the Environment of Japan, and AEROS. GOCI data were provided by the Korea Institute of Ocean Science and Technology (KIOST). The authors acknowledge the free use of the physical oversampling algorithm developed by Kang Sun (https://github.com/Kang-Sun-CfA/Oversampling_matlab). The authors would like to thank Sara-Eva M{\'a}rtinez-Alonso and David P. Edwards for their assistance with the MOPITT CO data interpretation. The authors also would like to thank Daniel Jacob and Min Ju Yeo for the fruitful discussion. Publisher Copyright: {\textcopyright} 2022",

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doi = "10.1016/j.envint.2022.107708",

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AU - Chong, Heesung

AU - Lee, Seoyoung

AU - Cho, Yeseul

AU - Kim, Jhoon

AU - Koo, Ja Ho

AU - Pyo Kim, Yong

AU - Kim, Younha

AU - Woo, Jung Hun

AU - Hyun Ahn, Dha

N1 - Funding Information: The authors would like to acknowledge the support by Samsung Advanced Institute of Technology. This work was also supported by the Korea Ministry of Environment (MOE) under the Public Technology Program based on Environmental Policy (2017000160001). Additionally, this work was supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Project for New Climate Regime, funded by Korea Ministry of Environment (MOD) (2022003560007). The authors acknowledge the free use of the OMNO2, OMSO2, MOP02J_8, ERA5, GMTED, and GWPv4 datasets. The authors also acknowledge the free use of PM 2.5 measurements from Airkorea, the China National Urban Air Quality Real-time Publishing Platform, the Ministry of the Environment of Japan, and AEROS. GOCI data were provided by the Korea Institute of Ocean Science and Technology (KIOST). The authors acknowledge the free use of the physical oversampling algorithm developed by Kang Sun (https://github.com/Kang-Sun-CfA/Oversampling_matlab). The authors would like to thank Sara-Eva Mártinez-Alonso and David P. Edwards for their assistance with the MOPITT CO data interpretation. The authors also would like to thank Daniel Jacob and Min Ju Yeo for the fruitful discussion. Funding Information: The authors would like to acknowledge the support by Samsung Advanced Institute of Technology. This work was also supported by the Korea Ministry of Environment (MOE) under the Public Technology Program based on Environmental Policy (2017000160001). Additionally, this work was supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Project for New Climate Regime, funded by Korea Ministry of Environment (MOD) (2022003560007). The authors acknowledge the free use of the OMNO2, OMSO2, MOP02J_8, ERA5, GMTED, and GWPv4 datasets. The authors also acknowledge the free use of PM2.5 measurements from Airkorea, the China National Urban Air Quality Real-time Publishing Platform, the Ministry of the Environment of Japan, and AEROS. GOCI data were provided by the Korea Institute of Ocean Science and Technology (KIOST). The authors acknowledge the free use of the physical oversampling algorithm developed by Kang Sun (https://github.com/Kang-Sun-CfA/Oversampling_matlab). The authors would like to thank Sara-Eva Mártinez-Alonso and David P. Edwards for their assistance with the MOPITT CO data interpretation. The authors also would like to thank Daniel Jacob and Min Ju Yeo for the fruitful discussion. Publisher Copyright: © 2022

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N2 - North Korea's air quality is poorly understood due to a lack of reliable data. Here, we analyzed urban- to national-scale air quality changes in North Korea using multi-year satellite observations. Pyongyang, Nampo, Pukchang, and Munchon were identified as pollution hotspots. On a national scale, we found that North Korea experienced 6.7, 17.8, and 20.6 times greater amounts of nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) per unit primary energy supply (PES) than South Korea from 2005 to 2018. Besides, North Korea had a 24.3 times larger aerosol optical depth (AOD) per PES than South Korea from 2011 to 2018. Severe CO and aerosol pollution is aligned with extensive biofuel combustion. High SO2 pollution corresponds with the strong coal dependence of the industry. The change rates of the national average columns for NO2, SO2, and CO were + 3.6, –4.4, and –0.4 % yr−1, respectively. The AOD change rate was –4.8 % yr−1. Overall decreasing trends, except for NO2, are likely due to a decline in coal-fired PES. Positive NO2 trends are consistent with increasing industrial activities. Each pollutant showed consistent patterns of linear trends, even after correcting the influence of transboundary pollution. Flue gas control and biofuel consumption reduction seem necessary to improve North Korea's air quality.

AB - North Korea's air quality is poorly understood due to a lack of reliable data. Here, we analyzed urban- to national-scale air quality changes in North Korea using multi-year satellite observations. Pyongyang, Nampo, Pukchang, and Munchon were identified as pollution hotspots. On a national scale, we found that North Korea experienced 6.7, 17.8, and 20.6 times greater amounts of nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) per unit primary energy supply (PES) than South Korea from 2005 to 2018. Besides, North Korea had a 24.3 times larger aerosol optical depth (AOD) per PES than South Korea from 2011 to 2018. Severe CO and aerosol pollution is aligned with extensive biofuel combustion. High SO2 pollution corresponds with the strong coal dependence of the industry. The change rates of the national average columns for NO2, SO2, and CO were + 3.6, –4.4, and –0.4 % yr−1, respectively. The AOD change rate was –4.8 % yr−1. Overall decreasing trends, except for NO2, are likely due to a decline in coal-fired PES. Positive NO2 trends are consistent with increasing industrial activities. Each pollutant showed consistent patterns of linear trends, even after correcting the influence of transboundary pollution. Flue gas control and biofuel consumption reduction seem necessary to improve North Korea's air quality.

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Assessment of air quality in North Korea from satellite observations

Abstract

Bibliographical note

Keywords

UN SDGs

Access to Document

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Cite this