Author
Listed:
- Cheema Soralump
(Graduate School, Kasetsart University, Bangkok 10900, Thailand)
- Polwat Lerskullawat
(Department of Accounting, Faculty of Business Administration, Kasetsart University, Bangkok 10900, Thailand)
Abstract
Background and Objectives: Thailand is currently considering the integration of Small Modular Reactor (SMR) technology into its national energy portfolio under the Power Development Plan (PDP 2025–2037) as part of its transition toward low-carbon energy and climate commitments. As a newcomer nuclear country without upstream fuel-cycle capabilities—such as uranium mining, enrichment, or fuel fabrication—Thailand operates as a back-end nuclear system, where the primary responsibility lies in managing spent fuel and radioactive waste. This creates significant challenges across technical, financial, regulatory, and social dimensions, particularly given the absence of established infrastructure and institutional arrangements for long-term waste management. Against this backdrop, a systematic understanding of risks associated with the SMR back-end cycle is essential to ensure that nuclear adoption is economically viable, environmentally sustainable, and socially acceptable. This study therefore aims to (1) identify key stakeholders across four stages of the SMR back-end cycle—waste generation, interim storage, transportation, and final disposal—and (2) evaluate the associated risk factors using a structured risk-governance framework. Methodology: The study applies a qualitative risk-governance framework grounded in ISO 31000:2018 and IEC/ISO 31010:2019 standards, complemented by relevant International Atomic Energy Agency (IAEA) Safety Standards. The analytical process follows four steps: context establishment, risk identification, risk analysis, and risk evaluation. Risk identification is conducted across the four stages of the SMR back-end cycle, yielding 21 risks classified into four dimensions: technical, financial, policy/regulatory, and social/environmental. A qualitative likelihood–consequence matrix—combining four likelihood levels (L1–L4) and five consequence levels (C1–C5)—is employed to categorize risks into low, medium, high, and extreme levels, thereby enabling a systematic assessment of both probability and impact across the waste management lifecycle. Key Findings: The results show that the overall risk profile of Thailand’s SMR back-end cycle is driven primarily by non-technical factors, despite the presence of advanced engineering safety features. Technical risks are generally assessed as low to medium, reflecting the reliability of passive safety systems and established international standards governing radioactive material management. In contrast, financial, regulatory, and social risks emerge as the principal constraints. Financial risks are assessed as high, particularly those associated with long-term storage, maintenance, and repository development, due to their persistent and intergenerational cost burden in the absence of a dedicated national funding mechanism. Policy and regulatory risks are predominantly medium, reflecting uncertainties in SMR integration into national energy planning, licensing processes, and the absence of a clearly defined long-term disposal strategy, indicating fragmented institutional arrangements. Social risks constitute the most critical challenge, with community opposition identified as the only “extreme” risk, driven by concerns over radiation safety, limited institutional trust, and potential conflicts in stakeholder engagement, all of which affect the social license to operate. Policy Implications: The findings suggest that the successful deployment of SMR technology in Thailand depends more on strengthening governance and institutional capacity than on addressing technical constraints alone. First, establishing a long-term financing mechanism—such as a national radioactive waste management fund—is essential to ensure fiscal sustainability, with a hybrid model combining short-term cost recovery, operator contributions, and long-term statutory funding recommended to address intergenerational liabilities. Second, improving regulatory coherence and institutional coor
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JEL classification:
- Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
- Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
- H87 - Public Economics - - Miscellaneous Issues - - - International Fiscal Issues; International Public Goods
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
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