Toward carbon peak in China's manufacturing sector: Robot adoption and capital-embodied technological progress

IF 5.7 3区 环境科学与生态学 Q2 ENGINEERING, ENVIRONMENTAL
Xi Zhang, Xiaoqian Song, Meiting Fan, Beijia Huang, Hongmei Yang, Shuai Shao, Yong Geng
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Abstract

China's manufacturing sector has experienced increasing robot adoption and capital-embodied technological progress, accompanied by massive energy consumption and carbon emissions. The robot adoption brings technological and environmental risks in the manufacturing sector. Based on the data of 28 manufacturing sub-sectors, this study uses the logarithmic mean Divisia index method to investigate the contributions of robot adoption, labor, capital, and energy factors to the changes in carbon emissions in China's manufacturing sector. Furthermore, we conduct the scenario analysis and Monte Carlo simulation to project the future trajectories of carbon emissions in China's manufacturing sector under the different scenarios until 2035. Results show that during 2006–2019, both scale effect and technical effect driven by robots contributed to carbon emission reduction. Robot scale was the dominant contributor to the carbon emission increase, followed by capital automation. On the contrary, the workforce structure and energy-robot structure played dominant roles in carbon emission reduction. Labor productivity, capital deepening, and the carbon intensity of energy exerted marginal effects on carbon emissions. During 2020–2035, carbon emissions will increase consistently from 62.4 million tons (Mt) to 72.6 and 228.2 Mt under the business-as-usual scenario and higher-emission scenario, respectively, while they will have obvious inflection points under other three scenarios. Carbon emissions will peak at 65.3 Mt in 2023 and have the largest mitigation potential in the lower-emission scenario. Finally, several policy suggestions are raised for China to build a manufacturing system with the coordinated development of intelligence and low carbon.

中国制造业走向碳峰值:机器人的采用和资本体现的技术进步
中国制造业经历了越来越多的机器人采用和资本体现的技术进步,伴随着大量的能源消耗和碳排放。机器人的采用给制造业带来了技术和环境风险。本研究基于中国制造业28个子行业的数据,采用对数平均分指数法,考察机器人采用、劳动力、资本和能源等因素对中国制造业碳排放变化的贡献。在此基础上,通过情景分析和蒙特卡洛模拟,预测了2035年前中国制造业碳排放在不同情景下的变化轨迹。结果表明,2006-2019年期间,机器人驱动的规模效应和技术效应对碳减排均有贡献。机器人规模是碳排放增加的主要贡献者,其次是资本自动化。相反,劳动力结构和能源-机器人结构对碳减排起主导作用。劳动生产率、资本深化和能源碳强度对碳排放均有边际效应。在2020-2035年期间,碳排放量将从不变情景和高排放情景下的6240万吨持续增加到7260万吨和2.282万吨,而在其他三种情景下,它们将有明显的拐点。碳排放量将在2023年达到峰值6530万吨,在低排放情景下具有最大的减缓潜力。最后,提出了构建智能与低碳协调发展的中国制造体系的政策建议。
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来源期刊
Journal of Industrial Ecology
Journal of Industrial Ecology 环境科学-环境科学
CiteScore
11.60
自引率
8.50%
发文量
117
审稿时长
12-24 weeks
期刊介绍: The Journal of Industrial Ecology addresses a series of related topics: material and energy flows studies (''industrial metabolism'') technological change dematerialization and decarbonization life cycle planning, design and assessment design for the environment extended producer responsibility (''product stewardship'') eco-industrial parks (''industrial symbiosis'') product-oriented environmental policy eco-efficiency Journal of Industrial Ecology is open to and encourages submissions that are interdisciplinary in approach. In addition to more formal academic papers, the journal seeks to provide a forum for continuing exchange of information and opinions through contributions from scholars, environmental managers, policymakers, advocates and others involved in environmental science, management and policy.
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