Evaluation of error inducing factors in unmanned aerial vehicle mounted detector to measure fugitive methane from solid waste landfill
| Autor: | Yeong Min Kim, Man Ho Park, Kyeong Ho Lee, Sangjae Jeong, Jae-Young Kim |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
020209 energy
Landfill gas monitoring 02 engineering and technology 010501 environmental sciences Solid Waste 01 natural sciences Methane Automotive engineering chemistry.chemical_compound 0202 electrical engineering electronic engineering information engineering Waste Management and Disposal Reliability (statistics) 0105 earth and related environmental sciences Air Pollutants Measure (data warehouse) System of measurement Detector Reproducibility of Results Bayes Theorem Refuse Disposal Waste Disposal Facilities Landfill gas chemistry Greenhouse gas Environmental science Environmental Monitoring |
| Zdroj: | Waste Management. 124:368-376 |
| ISSN: | 0956-053X |
| DOI: | 10.1016/j.wasman.2021.02.023 |
| Popis: | Many methods have been applied to monitor fugitive methane gas from landfills. Recently, there have been suggestions to use a framework utilizing an unmanned aerial vehicle (UAV) for landfill gas monitoring, and several field campaigns have proved that a rotary UAV-based measurement has advantages of ease of control and high-resolution concentration mapping on the target planes. However, research on the evaluation of error-inducing factors in the suggested system is limited so far. This study prepared a measurement system with a lightweight methane detector and a rotary UAV to support the applicability of rotary UAV in landfill gas monitoring. Then, the validity of the system was tested experimentally and theoretically. In the detector reliability test, the methane detector had sufficient resolution for field application. The critical UAV velocity required was obtained to ensure the credibility of the proposed measurement system. When spatial interpolators were applied to field data from the measurement system, the empirical Bayesian kriging demonstrated the best prediction of methane concentrations at unmeasured points. With the verifications provided in this study, this proposed method may contribute to reducing uncertainty in estimating fugitive landfill gas emission. |
| Databáze: | OpenAIRE |
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