Prediction of photovoltaic waste generation in Canada using regression-based model

  • Monasib Romel
  • , Golam Kabir*
  • , Kelvin Tsun Wai Ng
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The global surge in photovoltaic (PV) installations and the resulting increase in PV waste are a growing concern. The aims of this study include predicting the volume of photovoltaic waste in Canada. The forecasting of solar waste volume employed linear regression, 2nd order polynomial regression, and power regression models. The study’s results indicate that Canada is on the verge of facing challenges related to the end-of-life treatment of photovoltaic modules in the coming years due to the significant growth in PV capacity over recent decades. According to the analysis, for early loss, the PV waste volume in 2045 could range from 180,000 MT to 270,000 MT, and for regular loss, it could range from 160,000 MT to 180,000 MT. This research is anticipated to assist relevant government agencies in assessing the prospective volume of PV waste to establish a sustainable and resilient PV waste management plan for Canada. These findings may shed light on the feasibility of a circular economy and advocate for the involvement of all stakeholders in a carefully coordinated strategy to mitigate potential environmental impacts and optimize resource utilization efficiency.

Original languageEnglish
Pages (from-to)8650-8665
Number of pages16
JournalEnvironmental Science and Pollution Research
Volume31
Issue number6
DOIs
StatePublished - Feb 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • Forecasting
  • Photovoltaic waste
  • Regression
  • Waste volume

ASJC Scopus subject areas

  • Environmental Chemistry
  • Pollution
  • Health, Toxicology and Mutagenesis

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