## 4 Results
### Results of Performance Evaluation for the Path-GMM-Nearest-Neighbor Model
A comparison was made between the current government management approach and the management scenario defined in this research using the new scenario policy. The objective is to demonstrate how the Path-GMM-Nearest-Neighbor model contributes to achieving the green economy goals under the carrying capacity set by Thailand, as shown in Figures 4 and 5. Figure 4 illustrates the projected agricultural waste volume in Thailand over the next 20 years (2025-2044) under the country's sustainability policy framework. Agricultural waste is categorized into four categories: (1) Crop waste, including rice husks, wheat  
Figure 4: The forecasting results of agricultural waste from 2025 to 2044 in Thailand. Figure 5: The expansion of greenhouse gas emissions over the next 20 years. straw, bagasse; (2) Animal waste, including livestock manure, deceased animals; (3) Processing waste, including packaging materials, fertilizer cans; and (4) Hazardous waste, and pesticides, insecticides. The total agricultural waste volume is projected to increase continuously, with a growth rate of 152.94% (2044/2025), reaching 6450.09 thousand tons by 2044, far exceeding the carrying capacity limit of 3750 thousand tons. Notably, from 2030 onward, agricultural waste is expected to surpass the carrying capacity, reaching 3798 thousand tons in that year alone. Beyond 2030, the volume continues to grow annually at an accelerating rate. This rapid surge poses significant environmental risks, potentially leading to irreversible degradation, as the increasing trend sharply outpaces the carrying capacity. To address this issue, the research proposes a new scenario policy. The results suggest that, under this policy, the agricultural waste volume would grow at a much slower rate of 50.58% (2044/2025), reaching 2580 thousand tons by 2044, which remains within sustainable limits and below the carrying capacity threshold. Therefore, if the expansion of agricultural waste continues to rise, it will have a greater impact on the ecosystem. This increase will also affect the changes in greenhouse gas emissions as follows:  
Figure 5 presents the calculated greenhouse gas (GHG) emissions in the agricultural sector. These emissions are derived from the total release of carbon dioxide (CO\({}_{2}\)), methane (CH\({}_{4}\)), and nitrous oxide (N\({}_{2}\)O), measured in Gg CO\({}_{2}\)e. The key sources of GHG emissions in agriculture are as follows: crop cultivation constituting 71.79%, livestock farming constituting 22.43%, biomass burning from agricultural residues constituting 2.92%, and urea fertilizer application constituting 2.86%. The research findings indicate that GHG emissions are projected to increase by 164.46% (2044/2025) over the study period. However, when the new scenario policy is implemented, the growth rate of greenhouse gas emissions decreases significantly, with a growth rate of only 43.68% (2044/2025), equating to 1306.12 Gg CO\({}_{2}\)e. This rate is still below the carrying capacity limit of 1560 Gg CO\({}_{2}\)e (from 2025 to 2044). The results demonstrate that the new scenario policy proposed in this research can lead to effective management of Thailand's agricultural sector and help achieve the goal of a sustainable green economy in the future.