## 4 Discussion  
### \(Co_{2}\) Mitigation Potential  
As elaborated in the previous section, in a case where all of Thailand's NDC mitigation measures are fully implemented in the energy sector, the total emissions in Chiang Mai would be lowered by 189,378 tCO\({}_{2}\)e (5.83%). In support of this, a 5.83% GHG reduction \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sustainability Aspects** & **Factors** & **Weight** & **Ranking** \\ \hline Environmental performance & \(\bullet\) Direct contribution to environmental benefits & 0.042 & 6 \\ (0.073) & \(\bullet\) Direct contribution to climate benefits as GHG reduction & 0.030 & 8 \\ \hline \multirow{4}{*}{\
\begin{tabular}{c} Political, technical, and \\ economic feasibility \\ (0.798) \\ \end{tabular} } & \(\bullet\) Costs and benefits of implementing climate & 0.230 & 3 \\ \cline{2-3}  & \(\bullet\) Policy possibility & 0.322 & 1 \\ \cline{2-3}  & \(\bullet\) Technological feasibility of implementing climate & 0.247 & 2 \\ \hline \multirow{4}{*}{
\begin{tabular}{c} Human and social dimensions \\ (0.129) \\ \end{tabular} } & \(\bullet\) Added value creation from energy efficiency measures & 0.036 & 7 \\ \cline{2-3}  & \(\bullet\) Participation in societal decision-making processes & 0.045 & 5 \\ \cline{2-3}  & \(\bullet\) Society’s ability of self-organization & 0.048 & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Overall AHP-weighting of the feasibility of climate policy implementation in the energy sector (CR = 0.070). Figure 6: Results of the multicriteria decision AHP analysis based on (**a**) weightings of sustainability aspects and (**b**) prioritizing multiple sustainability indicators for driving climate change policy in the energy sector of Chiang Mai, Thailand. by 2030 from energy-related CO\({}_{2}\) emissions alone was estimated in the BAU scenario. Previous studies have also primarily focused on energy efficiency improvement and the integration of energy generated with renewable resources. For instance, research conducted by [PERSON] et al. [12] found that the most effective options for reducing carbon emissions in Kolkata, India, were embracing green building standards in all new buildings in commercial areas and implementing the most energy-efficient air conditioners in the residential sector. In Romania, a study carried out by [PERSON] et al. [23] proposed intelligent energy efficiency solutions in hospital buildings, aiming to contribute to the 2050 target of 70% GHG emissions reduction, 70% renewable energy development, and 70% energy efficiency in buildings, under the new \"70-70-70\" efficiency concept. Further, a study performed by [PERSON] et al. [24] reported that energy requirement, energy performance class, and CO\({}_{2}\) emissions were considered to be key considerations in the assessment of sustainable living spaces. In Palembang City, Indonesia, the five most carbon-effective options were replacing diesel with biodiesel in industries, substituting diesel boilers with solar energy water heaters, promoting landfill gas waste to energy (WTE) utilization, promoting WTE, particularly in heat and power projects, and supporting energy efficiency in industries through steam reforming technology. In China, considering an annual GDP growth rate of 6.45%, the total primary energy demand is projected to increase by approximately 63.4%, 48.8%, and 12.2% in the BAU, carbon reduction, and integrated low-carbon economy scenarios, respectively [25]. Total carbon emissions will decrease by approximately 19.6% and 42.9% by 2050 in the carbon reduction and integrated low-carbon economy scenarios, respectively, in the BAU scenario. [PERSON] et al. [25] promote the use of all climate mitigation policies such as long-term low-carbon development strategies, improvement of energy efficiency, and development of economic instruments (i.e., carbon taxation). In Thailand, this is further supported by [PERSON] et al.