Quantification of greenhouse gas emissions from a municipal solid waste incinerator using an uncrewed aerial vehicle

The accurate quantification of greenhouse gas emissions from waste treatment facilities is critical for effective climate change mitigation and regulatory compliance. Measurement-based methods are increasingly emphasized as essential for addressing uncertainties in emission estimates, with uncrewed aerial vehicles (UAVs) recognized for their flexibility and ability to capture spatially resolved data. This study evaluated CO<sub>2</sub> emissions at a municipal solid waste incinerator using UAV monitoring with two quantification methods-the mass balance and inverse Gaussian methods. Ground-based wind data introduced significant uncertainty in CO<sub>2</sub> emission quantification. Therefore, this study proposed using a mounted anemometer to capture high-resolution spatially-resolved wind data. The performance of the proposed quantification methods was assessed by comparing UAV-derived fluxes to reference quantification data to calculate errors, which were then compared across methods to evaluate accuracy. The mass balance method, incorporating spatially-resolved wind data, achieved a mean absolute percentage error (MAPE) of 37.34%, which was a marked improvement compared to the 64.32% MAPE using spatially-averaged wind data. Similarly, the inverse Gaussian method showed a lower MAPE of 46.45% using spatially-resolved wind data, compared to 54.97% using spatially averaged wind data. Additionally, the advantages of each method under varying conditions of wind variability were evaluated. This study demonstrates that spatially-resolved wind measurements with a mounted anemometer improve the accuracy of CO<sub>2</sub> emission calculations. This approach highlights the importance of UAV-based monitoring of greenhouse gases emitted by waste management facilities.

Authors

Institutions

Publication Details

Journal
Environment International
Published
2025-03-29
DOI
https://doi.org/10.1016/j.envint.2025.109396
Citations
3
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
2.05
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantification of greenhouse gas emissions from a municipal solid waste incinerator using an uncrewed aerial vehicle

Horim Kim, Keun Taek Kim, Eunhwa Choi, Jae Young Kim et al.
3 citations
Environment International
Vehicle emissions and performance
2.05
article

Quantification of greenhouse gas emissions from a municipal solid waste incinerator using an uncrewed aerial vehicle

Horim Kim, Keun Taek Kim, Eunhwa Choi, Jae Young Kim, Young Su Lee, Sangjae Jeong
article en
3 citations

Abstract

The accurate quantification of greenhouse gas emissions from waste treatment facilities is critical for effective climate change mitigation and regulatory compliance. Measurement-based methods are increasingly emphasized as essential for addressing uncertainties in emission estimates, with uncrewed aerial vehicles (UAVs) recognized for their flexibility and ability to capture spatially resolved data. This study evaluated CO<sub>2</sub> emissions at a municipal solid waste incinerator using UAV monitoring with two quantification methods-the mass balance and inverse Gaussian methods. Ground-based wind data introduced significant uncertainty in CO<sub>2</sub> emission quantification. Therefore, this study proposed using a mounted anemometer to capture high-resolution spatially-resolved wind data. The performance of the proposed quantification methods was assessed by comparing UAV-derived fluxes to reference quantification data to calculate errors, which were then compared across methods to evaluate accuracy. The mass balance method, incorporating spatially-resolved wind data, achieved a mean absolute percentage error (MAPE) of 37.34%, which was a marked improvement compared to the 64.32% MAPE using spatially-averaged wind data. Similarly, the inverse Gaussian method showed a lower MAPE of 46.45% using spatially-resolved wind data, compared to 54.97% using spatially averaged wind data. Additionally, the advantages of each method under varying conditions of wind variability were evaluated. This study demonstrates that spatially-resolved wind measurements with a mounted anemometer improve the accuracy of CO<sub>2</sub> emission calculations. This approach highlights the importance of UAV-based monitoring of greenhouse gases emitted by waste management facilities.

Environment InternationalVol. 198
Seoul National University of Science and Technology (KR), Seoul National University (KR), Hanbat National University (KR), New Generation University College (ET), Sejong University (KR), Research Institute of Industrial Science and Technology (KR), National University College (PR)
Openalex Percentile: Top 14%
Vehicle emissions and performance
2.05
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.