Enhancing Sustainable Strategic Governance for Energy-Consumption Reduction Towards Carbon Neutrality in the Energy and Transportation Sectors

Pruethsan Sutthichaimethee, Worawat Sa-Ngiamvibool, Buncha Wattana, Jianhui Luo and Supannika Wattana ()
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Pruethsan Sutthichaimethee: Faculty of Engineering, Mahasarakham University, Mahasarakham 44150, Thailand
Worawat Sa-Ngiamvibool: Faculty of Engineering, Mahasarakham University, Mahasarakham 44150, Thailand
Buncha Wattana: Faculty of Engineering, Mahasarakham University, Mahasarakham 44150, Thailand
Jianhui Luo: College of Electrical Engineering, Hunan Mechanical and Electrical Polytechnic, Changsha 410151, China
Supannika Wattana: Faculty of Engineering, Mahasarakham University, Mahasarakham 44150, Thailand

Sustainability, 2025, vol. 17, issue 6, 1-24

Abstract: This research aims to identify appropriate strategies for reducing CO 2 emissions under the carbon neutrality framework within Smart City Thailand. The Path Solow model based on vector moving average–GARCH in mean with environmental pollution (PS–VMA–GARCHM–EnPoll model) has been developed, and it is a highly suitable tool for environmental protection. This model can also be applied to other sectors and stands out from previous models by effectively prioritizing key factors for long-term strategic planning in a concrete and efficient manner. Additionally, the model illustrates the direction of causal relationships, both positive and negative, which is highly beneficial for more concrete policy formulation. This allows the government to determine which factors should be reduced or receive less support and which factors should be promoted for greater growth compared to the past. The findings suggest two strategic approaches to reducing CO 2 emissions: (1) New-scenario policy based on high-sensitivity indicators—By selecting indicators with a sensitivity analysis value above 90%, including clean technology, renewable energy rate, biomass energy, electric vehicles, and green material rate, CO 2 emissions can be reduced by 43.06%, resulting in a total CO 2 gas emission of 398.01 Mt CO 2 Eq. by 2050, which is below Thailand’s carrying capacity threshold of 450.07 Mt CO 2 Eq.; and (2) Expanded-scenario policy using all indicators with sensitivity above 80%—By incorporating additional indicators, such as waste biomass, gasohol use rate, fatty acid methyl ester rate, and solar cell rate, along with those in the first scenario, CO 2 emissions can be reduced by 60.65%, leading to a projected CO 2 gas emission of 275.90 Mt CO 2 Eq. by 2050, which aligns with Thailand’s national strategy goal of reducing CO 2 gas emissions by at least 40% by 2050 and sets the country on the right path toward achieving net-zero greenhouse gas emissions by 2065. Thus, implementing the PS–VMA–GARCHM–EnPoll model can effectively contribute to the long-term national strategy for greenhouse gas reduction, ensuring sustainable environmental management for the future.

Keywords: smart environment; smart energy; smart government; carbon neutrality; net-zero GHG emissions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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