Decarbonizing Manufacturing Through Automation: The Role of Industrial Robots in Emission Reduction Strategies

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Authors: Ye Pan, Shenggang Ren, Shuya Rao
Cited by: 1

Abstract

The rapid proliferation of industrial robots is profoundly reshaping production processes and engineering management models in the manufacturing sector. However, existing literature provides limited insight into how the use of industrial robots affects carbon emissions in manufacturing firms. This study leverages a unique firm-level dataset containing granular energy consumption and emissions information to assess the impact of industrial robot adoption on carbon emissions in the manufacturing firms. Our empirical results indicate that a 1% increase in industrial robot exposure is associated with a 0.258% reduction in firm-level carbon emissions, which corresponds to a reduction of approximately 506 tons of carbon emissions per manufacturing firm per year. Calculated at the latest EU carbon price, this reduction yields roughly 48,000 USD in annual carbon cost savings for per firm. This result is robust to a range of checks, including instrumental variable tests, alternative variable specifications, varying clustering levels for standard errors, and different data cleaning procedures. Mechanism analyses suggest that robots improve energy efficiency, lower overall energy consumption, and facilitate a transition from fossil fuels to cleaner electricity sources. Additionally, the emission-reducing effects are more substantial in regions characterized by stable electricity supply, higher degrees of digitalization, and in industries with greater technological intensity. Our findings respond to concerns that industrial robots may trigger a “Jevons Paradox”, emphasizing the potential of industrial automation to promote low-carbon manufacturing and offer policy-relevant insights for advancing sustainable industrial development

Fields of Study & Subjects

Digital Transformation in Industry Energy Environment and Transportation Policies Vehicle emissions and performance

Publication details

Journal / source
IEEE Transactions on Engineering Management
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
73
Pages
3174–3186
Publication date
1 January 2026