## 7 Conclusions and Policy Implication  
This study utilizes satellite data from MERRA-2, obtained through the Google Earth Engine, to analyze the relationship between PM\({}_{2.5}\) emissions and socio-economic factors in each province of Thailand from 2012 to 2022. Using satellite data to track air pollution issues helps overcome the limitations of ground-based air pollution data, which are unavailable for all provinces in Thailand [56]. By leveraging satellite data from the Google Earth Engine, researchers can compensate for these technological constraints, access low-cost data, and enhance the study of environmental issues, including air pollution in both developed and developing countries worldwide.  
The study results indicate that PM\({}_{2.5}\) pollution in Thailand is spatially clustered, meaning that PM\({}_{2.5}\) spills over into nearby provinces and is not confined to a single area. The factors that positively affect PM\({}_{2.5}\) concentrations include the population density and energy consumption per capita, while industrial density has a negative effect on PM\({}_{2.5}\) levels. Additionally, the Environmental Kuznets Curve (EKC) analysis found that the GPP per capita has a U-shaped relationship with the PM\({}_{2.5}\) concentration. In the initial stage of economic growth, as the GPP per capita increases, the PM\({}_{2.5}\) concentrations gradually decrease. However, once income reaches USD 56,715 and the economy becomes significantly large, further increases in GPP per capita lead to rising PM\({}_{2.5}\) concentrations. In other words, during the early phase of economic development, PM\({}_{2.5}\) pollution does not intensify significantly. However, once Thailand's economy reaches a certain scale, continued economic expansion exacerbates PM\({}_{2.5}\) pollution, leading to greater economic and social consequences.  
Additionally, the development of spatially integrated environmental policies is essential for Thailand, and the enforcement of strict environmental laws will help mitigate the PM\({}_{2.5}\) pollution problem in the long term. This aligns with the findings of [16; 17], which investigated energy consumption issues in Asia. Furthermore, Thailand currently relies on fragmented air pollution management measures without establishing dedicated agencies to take full responsibility for the issue [56]. As a result, if its economic development continues, Thailand will remain at a high risk of experiencing severe air pollution impacts in the future.  
Future studies should consider various other confounding factors and spatial differences to analyze air pollution issues with greater accuracy. Developing forecasting models to predict future air pollution trends as Thailand's economy grows, particularly over the next 30 years, is essential for effective economic and environmental policy planning. This approach will help Thailand achieve sustainable growth while minimizing its environmental impacts.  
T.S.: writing--review, visualization, investigation, sample collection, methodology, conceptualization. K.A.: investigation, supervision, writing--review and editing, methodology, funding acquisition, conceptualization. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.