Manufacturing-attributed generation carbon intensity of monocrystalline silicon photovoltaic modules in China under production–use spatial coupling
Yaokuan Peng , Siyuan Chen , Yao Tong , Xinyuan Jin , Lipu Zhang
AIMS Environmental Science ›› 2026, Vol. 13 ›› Issue (4) : 774 -796.
Photovoltaic (PV) module manufacturing footprints are typically reported per kWp, yet their interpretation changes when these burdens are allocated over lifetime electricity generation in regions with unequal solar resources. We present a parameterized life-cycle assessment (LCA) model for monocrystalline silicon PV modules linking manufacturing emissions, provincial grid factors, solar resources, technology routes, material-factor scenarios, and Monte Carlo uncertainty. Manufacturing-footprint results are reported in kg CO2e/kWp, while generation-intensity outcomes are described by their relative rankings to avoid mixing different allocation bases. Built on International Energy Agency Photovoltaic Power Systems Programme (IEA PVPS) Task 12 inventories, ecoinvent 3.9.1 Cutoff material factors with the Intergovernmental Panel on Climate Change (IPCC) 2021 100-year global warming potential (GWP100), China’s 2023 provincial electricity factors, and the NASA POWER 2014–2023 irradiation data, the 19.5% crystalline-silicon (c-Si) reference module yields 494.4 kg CO2e/kWp under national-average manufacturing electricity. Route-specific proxies for passivated emitter and rear cell (PERC), tunnel oxide passivated contact (TOPCon), and heterojunction (HJT) modules give 446.2, 392.8, and 367.9 kg CO2e/kWp, respectively, under the ecoinvent 3.9.1 Cutoff factor set. The three factor sets are the ecoinvent 3.9.1 Cutoff, China-adjusted literature, and low-carbon materials-and-power sets; their route-specific ranges are 367.9–446.2, 593.0–719.4, and 73.9–88.7 kg CO2e/kWp, respectively. The production–use matrix distinguishes manufacturing-location effects from use-location solar-resource effects, while the uncertainty analysis shows that factor-set ordering is more stable than technology-route ordering. PV carbon-footprint screening should jointly disclose material factors, electricity factors, solar-resource assumptions, and technology-route parameters.
carbon footprint / life cycle assessment / monocrystalline silicon photovoltaic module / provincial electricity factor / production–use spatial coupling
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