A research team has used machine learning and spatial analysis to show that socioeconomic factors are most strongly associated with PV waste generation, while geographical and climatic conditions are more closely linked to PV lifespan. Their Australia-wide analysis suggests PV recycling policies should be tailored to regional conditions.
A research team of scientists from Australia and Japan has developed correlation and spatial validation models to characterize the relationships between economic, social, geographical, and climatic features and PV decommissioning dynamics, including PV waste generation and PV lifespan.
“Most studies on end-of-life solar panels focus on how much waste will be generated and when it will appear,” said corresponding author Jian Zuo to pv magazine. “Our research goes one step further by asking why these patterns differ across regions. Instead of only projecting future PV waste, we investigated how broader economic, social, geographical, and climatic conditions are associated with PV waste generation and PV lifespan.”
Zuo added that by combining machine learning with spatial analysis, the group provides “a new way to understand the regional context behind PV decommissioning, offering evidence that can support more informed planning for future PV recycling and product stewardship.”
