除数指数
温室气体
碳纤维
机器人
技术变革
环境经济学
产业组织
能源消耗
劳动力
自然资源经济学
制造业
情景分析
比例(比率)
工业机器人
业务
首都(建筑)
能量强度
索引(排版)
环境科学
高效能源利用
低碳经济
先进制造业
制造工程
资本成本
工程类
碳排放税
经济
计算机科学
碳捕获和储存(时间表)
涡轮机
工业生态学
作者
Xi Zhang,Xiaoqian Song,Mei-Ting Fan,Beijia Huang,Hongmei Yang,Shuai Shao,Yong Geng
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI