Uncertainty Analysis of Greenhouse Gas (GHG) Emissions Simulated by the Parametric Monte Carlo Simulation and Nonparametric Bootstrap Method
| Autor: | Jong Seok Lee, Joo Young Lee, Min Hyeok Lee, Kun-Mo Lee |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Nonparametric bootstrap
Control and Optimization nonparametric bootstrap 020209 energy Astrophysics::High Energy Astrophysical Phenomena Monte Carlo method Energy Engineering and Power Technology Probability density function 02 engineering and technology 010501 environmental sciences 01 natural sciences lcsh:Technology parametric Monte Carlo simulation uncertainty analysis GHG emission factor R program 0202 electrical engineering electronic engineering information engineering Econometrics Electrical and Electronic Engineering Engineering (miscellaneous) Uncertainty analysis Astrophysics::Galaxy Astrophysics 0105 earth and related environmental sciences Parametric statistics Renewable Energy Sustainability and the Environment lcsh:T Variance (accounting) Greenhouse gas Environmental science Random variable Energy (miscellaneous) |
| Zdroj: | Energies, Vol 13, Iss 4965, p 4965 (2020) Energies; Volume 13; Issue 18; Pages: 4965 |
| ISSN: | 1996-1073 |
| Popis: | Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method. There was a certain number of observations required of a dataset before GHG emissions reached an asymptotic value. Treating a coefficient (i.e., GHG emission factor) as a random variable did not alter the mean; however, it yielded higher uncertainty of GHG emissions compared to the case when treating a coefficient constant. The non-parametric bootstrap method reduces the variance of GHG. A mathematical model for estimating GHG emissions should treat the GHG emission factor as a random variable. When the estimated probability density function (PDF) of the original dataset is incorrect, the nonparametric bootstrap method, not the parametric MCS method, should be the method of choice for the uncertainty analysis of GHG emissions. |
| Databáze: | OpenAIRE |
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