Resource-environment-economics coupled assessment for photovoltaic module recycling

Abstract

The rapid expansion of global photovoltaic (PV) installations has created an emerging challenge of managing end-of-life (EoL) modules. While multiple recycling technologies exist, the trade-offs among material recovery, environmental impact, and economic viability remain inadequately characterized. This study proposes a Resource-Environment-Economics coupled assessment framework that integrates life cycle assessment, and techno-economic analysis through coupling indicators, and applies it to four representative recycling routes under China-specific conditions. Results demonstrate that all recycling routes achieve net carbon benefits, defined as the net avoided emissions per tonne of treated EoL modules, ranging from approximately 715 to 2,791 kg CO2-eq per tonne. The coupling analysis reveals systematic trade-offs. For resource-environment coupling, thermal-chemical avoids the most emissions per unit of process emission, whereas chemical delamination delivers the largest absolute net carbon benefit despite the highest process footprint. For environment-economics coupling, the thermal-chemical and chemical routes generate profit at an order of magnitude lower carbon cost than mechanical processing, as high-value silver and higher-grade silicon recovery decouples earnings from process emissions. For resource-economics coupling, mechanical processing recovers substantial mass but captures limited value, while chemical delamination achieves the highest material value intensity through premium product quality. Circularity assessment indicates that CdTe recycling attains high closed-loop circularity through vertical integration, wherein a single manufacturer produces, collects, recycles, and reincorporates materials into new modules, while crystalline silicon routes remain substantially lower under current conditions. No single technology optimizes all dimensions simultaneously, highlighting the necessity of coupled assessment frameworks for informed technology selection and policy development.