Codes for "Towards an equitable future of global photovoltaic waste recycling "
Year: 2025
Type: article
Abstract: README: The files provided are prepared for a manuscript that is currently under peer review. Please use these files with caution, as they may be subject to further modifications prior to final publication. Simulations were conducted using the most recent version of the Global Change Analysis Model (GCAM v7) to estimate solar energy production across 30 regions from 2025 to 2060. GCAM v7 is openly accessible at https://github.com/JGCRI/gcam-core/releases, with documentation available at https://github.com/JGCRI/gcam-core/releases/tag/gcam-v7.1. The installation of the GCAM model typically takes about one hour. Running each scenario generally requires a computation time in the range of 1–4 hours, depending on the selected scenario combination. The installation and execution of the MFA_PV_online script can be completed within one hour. To perform the calculations: Unzip the gcam-v7.1-Windows-Release-Package. Edit the run-gcam.bat file to specify the scenario configuration you intend to run. In this study, we used the configuration_ssp.xml file. Within the configuration_ssp.xml file, locate the line: “ ... ”and input the name of the desired SSP scenario. For example, to run the SSP1 scenario, input batch_SSP_SPA1. In the corresponding batch_SSP_SPA1 file, specify the technology cost assumption (e.g., low cost: solar_adv) and the climate policy pathway. For example, to simulate the RCP6.0 scenario, include the file path:policy_target_6p0_spa1.xml Run the GCAM model to generate regional solar PV generation data for the period 2025–2060. After running GCAM: Place the solar-queries.xml file in the gcam-v7.1-Windows-Release-Package\output directory. Run the MFA_PV_online script to generate PV waste projections from 2025 to 2060. For further information on the input data used in these calculations, please refer to the Data Availability section of the main article.
Author: Wang, Chen
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6911987265
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