## 6 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**GDP per Capita, Purchasing Power Parity (PPP*)(USD)**} \\ \cline{2-10}  & **USD 470** & **USD 940** & **USD 1880** & **USD 5635** & **USD 8450** & **USD 11270** & **18780** & **USD 46,950** & **USD 56,715** \\ \hline PM\({}_{2.5}\) & \(-1.112\) & \(-0.951\) & \(-0.790\) & \(-0.536\) & \(-0.441\) & \(-0.375\) & \(-0.256\) & \(-0.044\) & \(0.000\) \\ \hline  & & \multicolumn{6}{c}{PPP*: Purchasing Power Parity 2022 from [11]. Note: The reason for using Purchasing Power Parity (PPP) is to adjust for inflation in order to measure real income growth accurately.} \\ \end{tabular}
\end{table} 
Table 9: The affluence elasticity of impact coefficients (EE\({}_{\text{IA}}\)) for various values of affluence from the Non-spatial Panel Random Effects Regression model. limited impact on PM\({}_{2.5}\) pollution, over time, as Thailand's economy grew and became a long-term source of PM\({}_{2.5}\) pollution, further economic development began to have a severe impact, leading to a significant increase in PM\({}_{2.5}\) levels. This is the reason why the two have a U-shaped EKC relationship. The inflection point analysis based on the Environmental Kuznets Curve (EKC) theory found that, in 2022, the average GPP per capita for each province in Thailand was USD 16,450 (GPP per capita, Purchasing Power Parity (PPP) 2022, USD). This analysis indicates that the inflection point occurs at USD 56,715, which is the threshold where elasticity changes from a negative value to zero. This means that if Thailand's GPP per capita exceeds USD 56,715, further income accumulation per capita will lead to an increase in PM\({}_{2.5}\) concentrations, moving in the same direction as economic growth. The study results provide several policy recommendations for addressing the PM\({}_{2.5}\) pollution problem:  
1. Regional and International Cooperation: Integrated collaboration among various organizations is essential to mitigate the widespread impacts of PM\({}_{2.5}\) pollution, especially in intense manufacturing regions that experience severe PM\({}_{2.5}\) pollution (the BKK&VIC and CE regions). 2. Bottom-Up Policy Formulation: This approach would allow local communities to actively participate in designing PM\({}_{2.5}\) pollution management policies alongside government agencies and central authorities, ensuring more effective and precisely targeted solutions [56]. 3. Transition to Clean Energy: Switching to clean energy sources and maximizing energy efficiency with minimal emissions can significantly reduce PM\({}_{2.5}\) pollution. Strategies include adopting renewable energy sources [57]; transition from diesel engines (which emit high levels of pollutants) to electric or hydrogen-powered engines in the future; and implementing stricter vehicle emission regulations, such as upgrading from Euro 4 to Euro 5-6 exhaust standards, which could substantially reduce vehicle emissions. This study has three limitations. First, the study relies solely on satellite data. By including ground-based air pollution data in future research, we could increase the number of variables and observations, improving the accuracy of the model estimations. Second, this study analyzes data at the provincial level. Future research should conduct more detailed analyses at the district or sub-district level to better understand localized PM\({}_{2.5}\) air pollution problems. Third, the use of only three years of data is a limitation of this study, as the dataset is too small to capture dynamic changes in both the short and long term. In future research, extending the study period would improve the accuracy of the estimations and allow for more insightful policy recommendations. Fourth, provincial-level spatial studies may be affected by confounding variables, such as topography, climate, or economic activities in neighboring countries, which may not be consistent across different regions. Future studies should consider these factors and conduct more detailed area-specific research.