Modeling Sustainable Energy and Resource Economics in China: Low-Carbon Transition Pathways for Photovoltaic and Mining Sectors

Under China’s “dual-carbon” strategy, which aims for carbon peaking by 2030 and neutrality by 2060, the transition toward low-carbon energy systems has become a national priority. This study integrates Life-Cycle Assessment (LCA) and Multi-Objective Optimization (MOO) models to evaluate the environmental and economic performance of the photovoltaic (PV) and mining sectors. Using real data from the International Energy Agency (IEA, 2023), China Energy Statistical Yearbook (2024), Carbon Emission Accounts and Datasets (CEADS, 2023), and IPCC AR6 (2023), the analysis shows that the life-cycle carbon emission intensity of PV systems averages 45 gCO₂/kWh, representing a 94.5% reduction compared to coal-fired power at 820 gCO₂/kWh. Mining operations emit approximately 520 gCO₂/kWh-equivalent, with 68% arising from the extraction and transport stages. The MOO model indicates that when maximizing returns and minimizing emissions simultaneously, the optimal investment allocation is 0.65 for PV and 0.35 for mining transformation projects. These findings suggest that integrating LCA-based monitoring and carbon-constrained investment models can effectively promote balanced development of clean and resource-based industries.