## 6 Conclusions  
As preliminary research for developing Korea's national DREs in the semiconductor and display industry, the present study aimed to review different determination methods for sample size and data processing. To this end, we examined different sample size calculation methods and selected two methods. For analysis, measurement-based DRE data were obtained for CF4 and CHF3, which are the two gases utilized in the semiconductor and display industry, and were used to calculate the minimum and maximum sample sizes. Some of the previous studies employed the CV method to develop Korea's national GHG emission factors whereas others applied the stratified sampling method. In this study, we employed both methods. The CV method can be considered for many situations; for example, when prior information is unknown, we can apply different ways to handle outliers. In our study, the treatment of outliers was examined in three different ways--using the existing data as they are (Case 1), removing outliers (Case 2), and adjusting outliers to extreme values (Case 3)--because the choice of outlier handling method can influence the results of sample size calculations. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Classification** & **Population** & **Estimated Number of Sample** \\ \hline Burn & 369 & 1 \\ Plasma & 2546 & 4 \\ Catalyst & 2 & 1 \\ Total & 2917 & 6 \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Number of samples per scrubber type for CHF3 DRE development considering the Neumann distribution method. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Classification**} & \multicolumn{3}{c}{**CV Method**} & \multirow{2}{*}{**Neyman Allocation**} \\ \cline{2-4}  & **Case 1** & **Case 2** & **Case 3** & **Method** \\ \hline CF4 & 337 & 17 & 85 & 21 \\ CHF3 & 45 & 3 & 6 & 6 \\ \hline \hline \end{tabular}
\end{table} 
Table 18: Sample size for CHF3 DRE development considering outlier cases and CVs. Depending on the determination method applied, we obtained different optimal sample sizes as follows. For the development of CF4 gas DRE, it turned out that a minimum of 17 and a maximum of 337 data points needed to be collected out of a total of 2968 scrubber data. For CHF3, a minimum of three and a maximum of 45 data points were required out of a total of 2917 scrubber data. The number of samples calculated by the Neumann distribution method, which reflects the scrubber characteristics of the sample, was close to the result of Case 3. In this regard, using a CV and adjusting the outliers (Case 3) can be one of the most feasible ways to reflect the scrubber characteristics when there is no detailed information about the business site. For CF4 and CHF3 gas DREs, plasma-type scrubbers were found to be outliers due to the large variation exhibited by them in the data. As there are limited data that can be removed as outliers on an individual plasma-type basis, eliminating outliers could be challenging in applying a CV to calculate the sample size. When outliers were adjusted to extreme values, the sample size characterizing the scrubber was equal to or slightly higher than the result of outlier removal, indicating that the Case 3 method is likely to be more reliable than removing outliers when they must be handled. It is also regarded that the scrubber type needs to be considered when developing DRE factors for the semiconductor and display industry. This is because the DRE for this industry currently provided by the IPCC is offered only in an overall mean value without consideration of scrubber type. It is important to note the limitations of this study. Due to the lack of prior information, we could consider only the scrubber characteristics in our analysis. Also, it will be important in future work to examine the validation methodology beyond the sample size calculation. We believe these limitations can be addressed in a future study with a larger sample size and more empirical data. Nevertheless, the findings of our study offer important contributions.