## 1 Introduction
### Socioeconomic Factors Affecting Energy Consumption  
In addition to the main variables commonly used to explore the EKC theory, several other studies have examined the relationship between energy consumption and environmental impact. For example, [PERSON] et al. [48] tested the EKC hypothesis for Pakistan by analyzing the significance of renewable and non-renewable energy consumption. Their results strongly support the EKC hypothesis in Pakistan, showing that renewable energy plays a dominant role in reducing carbon dioxide emissions. In contrast, non-renewable energy consumption is the primary contributor to increased emissions. [PERSON] et al. [49] analyzed the relationship between economic growth and CO2 emissions in Australia, using annual data from 1965 to 2016, with a focus on fossil fuel (oil and coal) and renewable energy consumption. Their results support the EKC hypothesis, suggesting that Australia is experiencing increased relative decoupling, which indicates that economic growth continues to drive CO2 emissions and environmental degradation. [PERSON] [50] examined the asymmetric environmental effects of different energy sources and tested the EKC hypothesis in the Gulf Cooperation Council (GCC) region from 1975 to 2019. The findings show that CO2 emissions resulting from increased natural gas consumption are less severe than those from oil consumption. As a result, the study recommends that GCC countries shift from oil to natural gas to reduce overall CO2 emissions. [PERSON] and [PERSON] [32] investigated the relationship between economic growth and energy consumption using the hypothesis postulated for the EKC, which assumes an inverted-U shape relationship between income and energy consumption, for 22 Latin American and Caribbean countries for the period 1990-2011. The hypothesis postulated for the EKC is not supported for the region. [PERSON] [43] investigated the EKC hypothesis among the 19 countries in the Asia-Pacific region. The study also tests the EKC hypothesis for low-, middle-, and high-income groups within the region. The test results of both models suggest that the EKC hypothesis holds for the whole Asia-Pacific region. However, the test performed on the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**EKC Patterns** & **Authors** & **Dependent Variables** & **Independent Variables** \\ \hline \multirow{6}{*}{Inverted U-shape} & [PERSON] and [PERSON] [25], & Energy per capita, coal consumption, renewable energy consumption, renewable energy consumption, non-renewable energy consumption, electricity consumption, CO2 emission & Real GDP, manufacturing value added (IVA), industrial value added (IVA), import, export, urbanization, share of secondary industry value \\  & [PERSON] and [PERSON] [25], & Energy per capita, coal consumption, renewable energy consumption, energy  
three different income groups revealed that the hypothesis only holds for the high-income group. The hypothesis was not apparent for the low- and middle-income groups.  
Based on the literature review, this study utilizes variables such as energy consumption per capita, GPP per capita, and population density, which are commonly used to examine the relationship between economic growth and energy consumption. However, unlike previous studies, this research introduces additional control variables, such as road density, and instrumental variables, including nighttime land surface temperature, rainfall, and wind speed, all derived from satellite data at the provincial level in Thailand. Satellite data offer high spatial resolution and low-cost accessibility, making them a valuable alternative for developing countries that lack comprehensive environmental data collection across all provinces.