Achieving net-zero carbon emissions by 2050 necessitates a substantial increase in solar photovoltaic (PV) and other renewable energy production. The global installed capacity of solar PV power has dramatically increased, while its cost has significantly decreased. Solar PV is projected to play a crucial role in the global transition to carbon neutrality, with expectations of it meeting over 30% of power demand by 2050. However, the spatial distribution of PV manufacturing and installation along its industrial chain is uneven and dynamically changing, influenced by national policies and international trade. Europe led in PV installations until 2016, after which the Asia-Pacific region, particularly China, took the lead. Recent trends also suggest a push for diversifying PV manufacturing to increase regional resilience, influencing both emission and mitigation dynamics. Current analyses inadequately account for the spatiotemporal evolution of GHG emissions and mitigation across the PV industrial chain, from manufacturing to installation, potentially leading to missed opportunities for maximizing net GHG mitigation. This study aims to quantify the net GHG mitigation of the global solar PV industrial chain from 2009 to 2060, incorporating the dynamic spatial parameters of manufacturing and installation patterns.

Existing literature utilizes life cycle assessment (LCA) and emission inventories to examine location-specific GHG emissions or mitigation from PV deployment. However, studies often lack sufficient characterization of the spatiotemporal evolution of GHG emission and mitigation intensities along the entire industrial chain. Factors such as technical and energy use efficiency, solar resource availability, and the average emissions of the local power system are crucial but inadequately considered. This study addresses these shortcomings by offering a more comprehensive, spatiotemporal analysis with improved timelines and resolution to guide strategies for maximizing GHG mitigation from solar PV deployment in the context of an increasingly complex global industrial chain.

This analysis quantifies the net GHG mitigation of the global solar PV industrial chain using a spatiotemporal LCA model. The model incorporates dynamic spatial parameters that evolve under multiple industrial chain patterns. The study quantifies annual emissions and mitigation of GHGs at the country level from 2009 to 2019, considering all processes from silicon manufacturing to power generation and disposal/recycling. Net GHG mitigation is calculated as the difference between mitigation and emissions. Nine scenarios combining different manufacturing (M1-M3) and installation (C1-C3) patterns are used to evaluate net GHG mitigation by 2060. Manufacturing scenarios include concentration in China (M1), transfer to other Asia-Pacific countries (M2), and transfer to Europe and North America (M3). Installation scenarios include locking in current patterns (C1), equitable distribution (C2), and targeted deployment in high-emission regions (C3). The model accounts for variations in solar resource availability, emission factors of national power systems, technological advancements, and recycling rates. Three scenarios of emission factor evolution for non-solar power sources (conservative, moderate, optimistic) are also considered. The model includes GHG emissions from all stages of the PV industrial chain, including the transportation of materials and products. The system boundary is clearly defined, and data sources are explicitly stated. The study employs specific equations to calculate GHG emissions, mitigation, and net mitigation, incorporating factors such as activity levels, emission intensities, capacity factor, and power system emission factors. For future projections, a base scenario is defined with 2019 solar capacity, and future mitigation is calculated as avoided emissions relative to the base. The model projects GHG emission factors for non-solar power sources based on three scenarios reflecting different decarbonization rates and carbon neutrality targets of different countries. The model also considers the impact of the installation of solar power on the grid emission factors, especially for the scenario where capacity is prioritized in regions with high emission factors. The model includes the impact of increased recycling on GHG emissions by considering an increasing recycling rate over time. The effects of integrating energy storage systems are analyzed by estimating additional GHG emissions and water consumption and other environmental impacts from the storage systems

The study estimates that from 2009 to 2019, cumulative global net GHG mitigation from solar PV was 1288.5 Mt CO2e. The Asia-Pacific region, particularly China, contributed the largest share. China's net mitigation became positive in 2017, driven by increased domestic installations. Significant spatial and temporal variations in GHG mitigation and emission intensities were observed. Mitigation intensity was highest in the Middle East due to high solar resources and high power grid emissions, while it was lowest in developed regions with decarbonized power systems. Emission intensity decreased significantly globally from 2009 to 2019, particularly in China due to improvements in manufacturing efficiency and decreasing power grid emission factors. Future projections under nine scenarios (three manufacturing and three installation) show substantial differences in net GHG mitigation. The highest mitigation potential (204.7 Gt CO2e) is realized with manufacturing concentrated in Europe and North America and installations targeted to carbon-intensive regions (C3-M3). This represents a 97.5 Gt increase compared to the worst-case scenario (C1-M2). The C3 installation scenario significantly reduces the global average emission factor of the power grid and narrows spatial disparities in emission factors, reducing GHG leakage and potential trade costs associated with carbon border adjustment mechanisms. The carbon payback time (CPT) decreases significantly over time due to declining manufacturing emissions and increasing mitigation intensity. Future CPT is influenced by manufacturing location, with the shortest CPT under the scenario of manufacturing relocation to Europe and North America. Projections include the environmental impacts beyond GHGs (water consumption, energy demand, etc.), revealing that the manufacturing location influences these factors substantially, with M2 (Asia-Pacific) leading to increases in several environmental impacts by 2060 compared to M3 (Europe/North America). Estimates of land use for PV installations are also provided. Analysis of different installation scenarios show that strategic deployment (C3) would increase solar capacity in Africa, Eurasia, the Middle East, and ASEAN compared to maintaining existing patterns (C1), resulting in substantial GHG mitigation and numerous co-benefits such as access to clean energy and reduced air pollution. However, the study also projects additional GHG emissions and other environmental impacts associated with paired energy storage systems, highlighting the need for further efforts to mitigate these.

This study addresses the research question of how to optimize the spatiotemporal deployment of the solar PV industry chain to maximize GHG mitigation. The findings demonstrate that strategic deployment focusing on carbon-intensive regions (C3) significantly increases net GHG mitigation, far exceeding that of maintaining current patterns (C1) or equitable distribution (C2). This emphasizes the importance of considering spatial and temporal variations in mitigation and emission intensities for accurate accounting and policymaking. The results highlight the potential for substantial GHG mitigation by prioritizing PV installations in regions with high power grid emission factors, even considering manufacturing emissions. The results have broad implications for international cooperation, emphasizing the need for financial and technical assistance from developed to developing countries to accelerate PV deployment and capitalize on the co-benefits beyond GHG reduction. The study also reveals the importance of manufacturing location in determining overall environmental impact, advocating for the consideration of environmental impacts beyond just GHGs when planning the global PV industrial chain.

This study provides a comprehensive spatiotemporal analysis of the global solar PV industry's GHG mitigation potential. The findings demonstrate that strategic deployment, prioritizing installations in carbon-intensive regions, significantly enhances GHG mitigation. This calls for international collaboration to support PV development in regions with high mitigation potential. Future research should focus on refining the model by incorporating more detailed grid-level data, exploring the implications of varying capacity factors across regions, and investigating the long-term sustainability and lifecycle environmental impact of different energy storage solutions.

The study uses national-level average data for solar resource availability and power grid emission factors, potentially masking intra-country variations in mitigation potential. The assumption of solar power substituting average grid power simplifies the complex interplay between solar PV output, demand fluctuations, and actual power source substitution. The projections of future decarbonization rates for non-solar power sources rely on several assumptions regarding national climate targets and decarbonization trajectories. Additionally, the lifecycle impacts of different energy storage technologies are approximated and could benefit from further research. While the model incorporates a rising recycling rate, the associated economic costs and technological improvements were not incorporated.