Climate change poses severe threats to the global environment, society, and economy. At COP26, countries committed to combatting global warming, with China targets carbon peak by 2030 and neutrality by 2060. China’s manufacturing industry plays a crucial role in achieving these goals. This white paper addresses China’s current “dual carbon” policy, carbon trading market, carbon footprint accounting methods and standards, manufacturing performance evaluation standards, and research on manufacturing industry segments. It introduces the innovative full life cycle Möbius strip carbon neutral performance evaluation framework, which evaluates carbon neutrality across the organizational and product life cycle, guiding enterprises towards zero-carbon transformation. By incorporating the Möbius strip philosophy, the framework emphasizes the interconnected and continuous nature of low-carbon transformation. This white paper serves as an encyclopedia for the manufacturing industry’s carbon-neutral journey, offering insights for sustainable development across various sectors.
The rapid growth of AI models and data centers has led to significant environmental impacts, including substantial energy consumption, carbon emissions, and water usage. Data centers now account for approximately 1-2% of global electricity consumption. These growing environmental concerns highlight the urgent need for comprehensive assessment and regulation. This paper introduces the AI Green Index, a framework designed to evaluate the environmental impact of AI models and data centers. The index offers a standardized, quantifiable metric to assess both carbon and water footprints across the life cycle of AI technologies. By promoting transparency, sustainable practices, and carbon-efficient innovations, the Green AI Index aims to guide stakeholders in reducing environmental impacts. Additionally, the paper analyzes current policies in major regions, including China, the U.S., and the EU, providing insights into strengths and weaknesses in environmental governance. The white paper seeks to inform researchers, industry leaders, and policymakers, fostering collaboration toward a sustainable AI future.
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