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 g CO₂/kWh equivalent, with 68% arising from the extraction and transportation 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. 

Keywords: Dual-carbon strategy, Photovoltaic energy, Mining industry, Life-cycle assessment, Multi-objective optimization, Carbon reduction 

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https://tinghuang1.substack.com/p/modeling-sustainable-energy-and-resource

This study develops a dynamic economic assessment framework for rooftop solar photovoltaic (PV) retrofits under uncertain and escalating electricity prices. A commercial educational campus in Maryland, USA, is used as a case study, with two technically feasible system sizes, 205.2 kW and 119.16 kW, derived from professional EnergySage proposals. Unlike conventional evaluations that rely on installer-reported financial outputs, this paper reconstructs all economic indicators using a transparent cash-flow model that explicitly incorporates an annual electricity price escalation rate e.

 For each system, net present value (NPV) is computed over a 30-year lifetime as a function of both e and the discount rate r. A one-dimensional sensitivity analysis (NPV versus e) and a two-dimensional sensitivity matrix (NPV over the (e, r) space) are developed. Results show that under a conservative assumption of zero real electricity price escalation (e=0), the 205.2 kW system yields an NPV of approximately US$195,000, which increases to about US$373,000 at e=2.5% and over US$520,000 at e=4.0%. Similar patterns are observed for the 119.16 kW system, with NPV rising from about US$117,000 (e=0) to approximately US$221,000 (e=2.5%).

 These findings demonstrate that electricity price escalation is a dominant driver of PV investment value and that conventional constant-savings models substantially understate project profitability. The proposed framework provides decision-makers with a more realistic tool for evaluating rooftop PV under uncertain future tariffs and offers a basis for robust, escalation-aware investment decisions.

 Keywords: rooftop solar PV, electricity price escalation, NPV sensitivity, dynamic cash-flow model, economic assessment.

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https://tinghuang1.substack.com/p/economic-and-environmental-assessment-13a

This study presents a comprehensive techno-economic and environmental assessment of two rooftop solar photovoltaic (PV) retrofit options—119.16 kW and 205.2 kW—for an educational facility in Maryland, USA. Using detailed engineering proposals obtained from the EnergySage Solar Marketplace, the analysis evaluates investment cost, projected energy generation, incentive structures, and long-term financial performance over a 30-year lifetime. Key metrics include Net Present Value (NPV), Internal Rate of Return (IRR), Levelized Cost of Energy (LCOE), simple payback period, cumulative savings, and carbon emission reductions. A deterministic optimization model is then applied to determine the system size that maximizes economic and environmental value.

 Results show that both systems are economically feasible, achieving IRRs between 13.7% and 13.9% and payback periods of approximately 6.6–6.7 years. The 205.2 kW system provides substantially higher lifetime savings (US$1.41 million) and carbon reductions (4,270 tCO₂), whereas the 119.16 kW configuration offers slightly superior capital efficiency. The optimization model identifies the 205.2 kW system as the optimal long-term solution. These findings provide actionable insights for institutional facilities seeking cost-effective and sustainable rooftop PV deployment.

 Keywords: Solar photovoltaic, techno-economic analysis, optimal sizing, NPV, IRR, carbon reduction, rooftop solar.

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https://tinghuang1.substack.com/p/economic-and-environmental-assessment