Climate Sustainability through AI-Crypto Synergies and Energy Transition in the Digital Landscape to Cut 0.7 GtCO2e by 2030 DOI
Apoorv Lal, Fengqi You

Environmental Science & Technology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 19, 2025

The rapid expansion of artificial intelligence (AI)-enabled systems and cryptocurrency mining poses significant challenges to climate sustainability due energy-intensive operations relying on fossil-powered grids. This work investigates the strategic coupling AI data centers through shared energy infrastructure including colocated renewable power installations, battery storage, green hydrogen infrastructure, carbon offsetting measures achieve cost-effective climate-neutral operations. Employing a novel modeling framework, it explores synergistic AI-crypto with detailed scenario design along an optimization framework assess decarbonization potential economic implications, enabling transformative shift in digital landscape. results indicate that synergizing while achieving net-zero targets can avoid up 0.7 Gt CO2-equiv 2030. Moreover, reaching these strategies globally requires 90.7 GW solar 119.3 wind capacity. findings advocate for robust policy facilitate credit schemes tailored sector, incentives efficiency improvements, international collaborations bridge disparities. Future research should focus refining interventions across different geopolitical contexts enhance global applicability.

Язык: Английский

Climate Sustainability through AI-Crypto Synergies and Energy Transition in the Digital Landscape to Cut 0.7 GtCO2e by 2030 DOI
Apoorv Lal, Fengqi You

Environmental Science & Technology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 19, 2025

The rapid expansion of artificial intelligence (AI)-enabled systems and cryptocurrency mining poses significant challenges to climate sustainability due energy-intensive operations relying on fossil-powered grids. This work investigates the strategic coupling AI data centers through shared energy infrastructure including colocated renewable power installations, battery storage, green hydrogen infrastructure, carbon offsetting measures achieve cost-effective climate-neutral operations. Employing a novel modeling framework, it explores synergistic AI-crypto with detailed scenario design along an optimization framework assess decarbonization potential economic implications, enabling transformative shift in digital landscape. results indicate that synergizing while achieving net-zero targets can avoid up 0.7 Gt CO2-equiv 2030. Moreover, reaching these strategies globally requires 90.7 GW solar 119.3 wind capacity. findings advocate for robust policy facilitate credit schemes tailored sector, incentives efficiency improvements, international collaborations bridge disparities. Future research should focus refining interventions across different geopolitical contexts enhance global applicability.

Язык: Английский

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