North Korean CO emissions reconstruction using DMZ ground observations, TROPOMI space-borne data, and the CMAQ air quality model

Eunhye Kim ¹, Byeong-Uk Kim ², Hyun Cheol Kim ³

¹Department of Environmental & Safety Engineering, Ajou University, Suwon 16499, Republic of Korea; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.
²Georgia Environmental Protection Division, Atlanta, GA 30354, USA.
³Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD 20740, USA; Cooperative Institute for Satellite Earth System Studies, University of Maryland, College Park, MD 20740, USA.
⁴Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.
⁵Department of Environmental & Safety Engineering, Ajou University, Suwon 16499, Republic of Korea.
⁶School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
⁷Department of Chemical Engineering and Materials Science, Ewha Womans University, Seoul 03760, Republic of Korea.
⁸Graduate School of Environmental Studies, Seoul National University, Seoul 08826, Republic of Korea.
⁹Department of Atmospheric Sciences, Yonsei University, Seoul 03722, Republic of Korea.
¹⁰State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
¹¹Emission Inventory Management Team, National Air Emission Inventory and Research Center, Cheongju 28166, Republic of Korea.
¹²Department of Energy, Climate, and Environment, International Institute for Applied Systems Analysis, Laxenburg 2361, Austria.

⁰Department of Environmental & Safety Engineering, Ajou University, Suwon 16499, Republic of Korea; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.

The Science of the Total Environment +

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February 20, 2024

View abstract on PubMed

Summary

This study developed a new method to estimate North Korean carbon monoxide (CO) emissions using satellite data and ground observations. The adjusted emissions were significantly higher, improving air quality models for North Korea and its neighbors.

Area Of Science

Atmospheric Chemistry
Environmental Science
Remote Sensing

Background

Emission uncertainty in North Korea hinders effective air pollution management, especially concerning transboundary pollutant transport.
Limited observational and emissions data for North Korea presents a significant challenge for air quality assessments.

Purpose Of The Study

To introduce a novel hybrid approach for adjusting and reallocating North Korean carbon monoxide (CO) emissions.
To address data scarcity by integrating ground-based and satellite observations with chemical transport models.

Main Methods

Utilized ground observations from the Demilitarized Zone (DMZ) and TROPOMI satellite data (TROPOspheric Monitoring Instrument).
Employed the Community Multi-Scale Air Quality (CMAQ) model, initialized with CAPSS and SIJAQ emissions inventories.
Implemented a two-step procedure: constraining emission intensity with DMZ data and reconstructing spatial distribution using TROPOMI CO Vertical Column Density (VCD).

Main Results

The hybrid method improved air quality simulations compared to methods relying solely on surface or satellite data.
Validation near the China-North Korea border showed significantly enhanced model performance with updated CO emissions.
Adjusted CO emissions were found to be 10.9 times higher than initial bottom-up estimates, revealing substantial data gaps.

Conclusions

The developed hybrid approach offers an efficient solution for estimating emissions in data-scarce regions.
Accurate emission inventories are crucial for effective regional air pollution management and policy development.
This method can identify previously underestimated or unrecorded emission sources, improving transboundary air pollution assessments.

Keywords:

Air quality model Emissions adjustment North Korea Spatial allocation Vertical column density