Assessing global carbon mitigation benefits of wind power with spatiotemporal characteristics and production-deployment pathways

Abstract

As wind power capacity continues expanding, its carbon-reduction effectiveness increasingly hinges on the spatiotemporal alignment of production, deployment, and power systems. However, these dimensions are assessed separately, and the role of spatiotemporal interactions in shaping carbon mitigation benefits remains unclear. Here, we develop a spatiotemporal life cycle assessment framework and systematically evaluate the carbon mitigation benefits of global onshore wind power across historical (2014-2023) and future (2025-2060) periods. We show that global wind power achieved cumulative net carbon mitigation benefits of 3,690 Mt CO2e over 2014-2023, while carbon emissions accounted for 8.5% of the direct carbon mitigation benefits from fossil-fuel electricity displacement. Under counterfactual settings, the climate-priority deployment scenario (C3) increases cumulative mitigation to 53,711 ± 935 Mt CO2e by 2060, approximately 2.3 times that of the baseline deployment scenario (C1). The clean-oriented production scenario (M3) yields comparatively modest gains, reducing carbon emissions by approximately 14% relative to the baseline production scenario (M1). The spatially diversified production scenario (M2) achieves the lowest transportation emissions, with cumulative reductions of approximately 6% and approximately 24% relative to M1 and M3. Under the baseline and balanced deployment scenarios (C1/C2), annual net mitigation peaks around 2034 and then declines persistently. In some production-deployment combinations, it turns negative by 2060 due to grid decarbonization. Conversely, scenario C3 remains positive throughout 2025-2060. The work provides scientific evidence for enhancing the carbon mitigation effectiveness of wind power development and boosting climate benefits through international coordinated planning, alongside decision support for optimizing wind power deployment and supply chain configurations.