An open‐source parameterized life cycle model to assess the environmental performance of silicon‐based photovoltaic systems

Abstract

Despite being renewable, photovoltaic energy is not burden‐free, since energy and materials are necessary to manufacture, maintain, dismantle, and recycle photovoltaic systems. Over its life cycle, the assessed carbon footprint of silicon‐based photovoltaic energy published in the literature often ranges from 40 to 110 gCO2eq/kWh. However, most of these estimations rely on life cycle inventory (LCI) data that represent the early‐stage performance of the photovoltaic industry. Indeed, collecting LCI data is time‐consuming and practitioners often reuse existing outdated data, which becomes problematic as the photovoltaic industry has been rapidly and significantly evolving. This analysis relies on the parametrization of existing LCI data to better account for the progress already accomplished by the photovoltaic industry. A Life Cycle Assessment (LCA) model, called PARASOL_LCA, is thus developed. The results of the analysis highlight that the use of outdated LCI data leads to an overestimation of environmental impacts of photovoltaic energy by a factor of 2 or even more for the best current available technologies. The analysis also shows that PARASOL_LCA, with its numerous parameters, can also serve to assess the environmental performance of prospective photovoltaic technologies and to identify impact reduction levers through sensitivity analysis.

Life cycle assessment of prospective trajectories: A parametric approach for tailor‐made inventories and its computational implementation

“…All those elements limit the precision of the LCA of nuclear energy, but not its order of magnitude according to the sensitivity analysis carried out with the parameterized model. 2020) by including additional parameters to account for the latest developments of the PV sector, such as bifacial PV panels (Besseau et al, 2023).…”

A Critical Review of the Environmental Performance of Bifacial Photovoltaic Panels

“…Data quality: A relevant aspect that influences the accuracy of a LCA study is the quality of the data used, which can be directly derived from measurement or by the producers or either gathered from the literature, databases or LCA libraries. In [20], it is shown how using updated data can significantly improve the eco-profile of monofacial and bifacial solar panels. Indeed, the authors compared the data obtained by using only the Ecoinvent database with those obtained by updating process production and available technologies (in terms of cell efficiency, material consumption, auxiliary devices, etc).…”

“…Indeed, the authors compared the data obtained by using only the Ecoinvent database with those obtained by updating process production and available technologies (in terms of cell efficiency, material consumption, auxiliary devices, etc). Analyzing the carbon footprint, the results showed a reduction in emissions from approximately 70 gCO 2eq /kWh for traditional monofacial panels modelled through the Ecoinvent database, to approximately 16 gCO 2eq /kWh and 13 gCO 2eq /kWh, for, respectively, updated monofacial panels and bifacial solar panels mounted on a wooden structure [18][19][20][21]. Finally, although PV systems have reached their maturity level, production companies are still undertaking continuous ongoing research to improve the efficiency and reduce material consumption both in the production of the panels and all the auxiliary devices.…”

“…Common setups are considered between 0.5 and 1.5 m [24]. However, it must be considered that the more material and energy consumption associated with a bigger mounting structure could counterbalance the environmental gain associated with the rise in electricity generation [20]. In open field installations, row distance also has a direct impact on energy production.…”