{"title":"Toward carbon peak in China's manufacturing sector: Robot adoption and capital-embodied technological progress","authors":"Xi Zhang, Xiaoqian Song, Meiting Fan, Beijia Huang, Hongmei Yang, Shuai Shao, Yong Geng","doi":"10.1111/jiec.70116","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":16050,"journal":{"name":"Journal of Industrial Ecology","volume":"29 6","pages":"2429-2441"},"PeriodicalIF":5.7000,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Industrial Ecology","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jiec.70116","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
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.
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.