Prof. Dr. Namgoo Kang is currently a Principal Scientist and a Professor at the University of Science and Technology in Daejeon, South Korea. His primary research interest is in the estimation of uncertainties in greenhouse gas emissions in agricultural environments. His teaching courses include Uncertainty Estimation Methods and Experimental Data Analysis Methods. He is a Principal Investigator funded from the Rural Development Agency of South Korea Government in cooperation with National Academy of Agricultural Science.
An accurate determination of the mole fraction of methane is an important task in reliable estimation of methane emission from various sources in developing national greenhouse gas emission inventory. In this study, we experimentally tested four different gas sampling methods to be able to minimize biases of the mole fractions of methane in sample bags from those in calibration gas cylinders when using a gas chromatograph with a flame ionization detector (GC-FID) based on one-point close-match (OPCM) calibration. In order to quantitatively evaluate the magnitudes of such biases we newly developed a measurement uncertainty estimation model based on the OPCM calibration. We found that the measured biases of the mole fractions of methane in the sample bags from those in the calibration cylinders can exceed significantly the expanded uncertainties associated with the mole fractions of methane in the sample bags. We also found that the mole fractions and uncertainties estimated by our model was nearly identical to those estimated by the well-known one-point through-origin (OPTO) calibration under the experimental conditions tested in this study. Information provided in this study would be useful not only to national metrology institutes for the purpose of international comparisons in gas metrology but to environmental scientists for practical field studies. This work was supported by Rural Development Administration, Republic of Korea under Cooperative Research Program for Agriculture Science & Technology Development (No. PJ014853042020).