TY - JOUR
T1 - PV in the circular economy, a dynamic framework analyzing technology evolution and reliability impacts
AU - Ovaitt, Silvana
AU - Mirletz, Heather
AU - Seetharaman, Sridhar
AU - Barnes, Teresa
N1 - Publisher Copyright:
© 2021
PY - 2022/1/21
Y1 - 2022/1/21
N2 - Rapid, terawatt-scale deployment of photovoltaic (PV) modules is required to decarbonize the energy sector. Despite efficiency and manufacturing improvements, material demand will increase, eventually resulting in waste as deployed modules reach end of life. Circular choices for decommissioned modules could reduce waste and offset virgin materials. We present PV ICE, an open-source python framework using modern reliability data, which tracks module material flows throughout PV life cycles. We provide dynamic baselines capturing PV module and material evolution. PV ICE includes multimodal end of life, circular pathways, and manufacturing losses. We present a validation of the framework and a sensitivity analysis. Results show that manufacturing efficiencies strongly affect material demand, representing >20% of the 9 million tons of waste cumulatively expected by 2050. Reliability and circular pathways represent the best opportunities to reduce waste by 56% while maintaining installed capacity. Shorter-lived modules generate 81% more waste and reduce 2050 capacity by 6%.
AB - Rapid, terawatt-scale deployment of photovoltaic (PV) modules is required to decarbonize the energy sector. Despite efficiency and manufacturing improvements, material demand will increase, eventually resulting in waste as deployed modules reach end of life. Circular choices for decommissioned modules could reduce waste and offset virgin materials. We present PV ICE, an open-source python framework using modern reliability data, which tracks module material flows throughout PV life cycles. We provide dynamic baselines capturing PV module and material evolution. PV ICE includes multimodal end of life, circular pathways, and manufacturing losses. We present a validation of the framework and a sensitivity analysis. Results show that manufacturing efficiencies strongly affect material demand, representing >20% of the 9 million tons of waste cumulatively expected by 2050. Reliability and circular pathways represent the best opportunities to reduce waste by 56% while maintaining installed capacity. Shorter-lived modules generate 81% more waste and reduce 2050 capacity by 6%.
KW - Energy policy
KW - Energy systems
KW - Environmental science
UR - http://www.scopus.com/inward/record.url?scp=85121130439&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85121130439&partnerID=8YFLogxK
U2 - 10.1016/j.isci.2021.103488
DO - 10.1016/j.isci.2021.103488
M3 - Article
AN - SCOPUS:85121130439
SN - 2589-0042
VL - 25
JO - iScience
JF - iScience
IS - 1
M1 - 103488
ER -