## 6 Conclusions  
This study developed an advanced model called the Path Analysis--Generalized Method of Moments based on a Nearest-Neighbor with Observed Variable Model (Path-GMM-Nearest-Neighbor Model). The researcher thoroughly examined all indicators used in the research, finding that all 17 indicators were stationary at the first difference level. Consequently, the indicators were tested for long-term relationships to confirm their suitability for constructing the Path-GMM-Nearest-Neighbor Model. The results indicated that all indicators exhibited complete co-integration based on the criteria. The Path-GMM-Nearest-Neighbor Model was constructed, and its validity and spuriousness were tested. The results showed no issues of heteroskedasticity, multicollinearity, or autocorrelation. Additionally, when the researcher assessed the model's goodness of fit, all values met the specified criteria, demonstrating that each factor exhibited statistically significant relationships in both direct and indirect effects at a 99% confidence interval. Sensitivity analysis was also conducted on all indicators to assess their appropriateness for designing a new scenario policy. The analysis revealed that the most significant factors at a 99% confidence level, both in the short and long term, were green technology and biomass energy. These factors were, thus, designated as the basis for the new scenario policy to forecast long-term outcomes. As for the forecasting results, they indicated that when the government implemented national management policies based on the new scenario, agricultural waste exhibited a continuous decline, with a growth rate reduction of 50.58% (2044/2025). Simultaneously, greenhouse gas emissions steadily decreased, expanding at only 43.68% (2044/2025), remaining below Thailand's carrying capacity limit of 1560 Gg CO\({}_{2}\)e. Therefore, this research approach serves as a critical tool for formulating national management policies. By adopting these strategies, Thailand can effectively achieve the goals of a sustainable green economy in the future. However, this research focuses on reducing greenhouse gas emissions in the agricultural sector by implementing a key strategy, developing a new scenario policy for long-term national planning, specifically through clean technology and biomass energy. The findings indicate that this approach leads to a continuous reduction in greenhouse gas emissions, keeping them below the carrying capacity. A significant factor in this reduction is the decrease in CO\({}_{2}\) emissions, which is the primary contributor to greenhouse gas emissions. This demonstrates that the proposed indicators can be applied to other sectors as well, contributing to a broader reduction in CO\({}_{2}\) emissions. As CO\({}_{2}\) emissions decline, it naturally leads to an overall reduction in greenhouse gas emissions and mitigates climate change. A clear example of sectors where these indicators can be effectively implemented includes the energy and transportation sectors, which are among the highest contributors to CO\({}_{2}\) emissions in Thailand. Conceptualization, [PERSON] ([PERSON]), [PERSON] ([PERSON]), and C.J. ; methodology, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and C.J. ; software, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and C.J. ; validation, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and C.J. ; formal analysis, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and C.J. ; investigation, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and C.J. ; resources, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and [PERSON]; data curation, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and [PERSON];writing--original draft preparation, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and [PERSON]; writing--review and editing, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and [PERSON]; visualization, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and [PERSON]; supervision, [PERSON] and [PERSON]. ([PERSON]); project administration, [PERSON] and [PERSON]. ([PERSON]) All authors have read and agreed to the published version of the manuscript.