A new study published in Nature reveals that industrial robots significantly reduce carbon emissions in global manufacturing by improving labor efficiency and strengthening countries’ positions within global value chains (GVCs).
Study: Industrial robots reduce carbon emissions in manufacturing through global value chains. Image Credit: Gorodenkoff/Shutterstock.com
Background
As climate change accelerates and supply chain disruptions continue to strain global production, the need for low-carbon manufacturing solutions has become more urgent. Industrial robots are already well-known for boosting productivity, but their environmental impact—especially in the context of globally interconnected value chains—has been less clear.
While previous research has explored either the economic impact of automation or its environmental potential in isolated settings, few studies have examined its broader role in reducing emissions through GVCs.
This study addresses that gap by combining global robot adoption data with multi-country input-output tables to assess how industrial automation affects carbon emissions across borders. The findings show that robot use not only cuts emissions locally but also improves value chain positioning, amplifying environmental benefits through trade networks.
What the Study Looked At
The researchers started by investigating how industrial robots are being used to reduce carbon emissions through three key mechanisms:
- Technological innovation – enabling cleaner production techniques
- Labor substitution – replacing emissions-heavy manual tasks
- GVC upgrading – improving a country’s position in global supply chains, allowing more efficient, higher-value production
To test these, the team analyzed panel data from 38 countries and 15 manufacturing sectors between 2000 and 2014. They merged statistics from the International Federation of Robotics (IFR) with the World Input-Output Database (WIOD), measuring robot adoption as units per million labor hours and emissions using fuel consumption coefficients.
The model controlled for variables like energy intensity, trade openness, and foreign direct investment (FDI), and included spatial spillover analysis to capture cross-border effects. To strengthen the findings, the researchers used instrumental variable methods to account for potential endogeneity.
Findings and Analysis
The results were compelling. A 1 % increase in robot adoption was associated with a 0.02 % drop in manufacturing-related carbon emissions. More advanced statistical models suggested this impact may be even greater, with estimates ranging from 0.113 % to 0.178 %, indicating that earlier figures likely understate the true decarbonization potential of automation.
However, not all industries and regions benefited equally. Emissions reductions were most significant in developed economies, capital-intensive sectors, and highly digitalized industries—contexts where automation is easier to integrate and more likely to enhance energy efficiency. In contrast, labor-intensive industries saw little change, largely because robots are still rarely used in low-skilled, manual roles.
The study also confirmed that emissions decline when robots replace inefficient labor processes and help manufacturers move into higher-value segments of the supply chain. A 1 % increase in robot use was found to raise a country’s GVC position by 0.15 %, especially in industries that started from the lower end of the value chain—an effect that helps break the “low-end lock-in” that often traps producers in emissions-heavy, low-margin activities.
One of the study’s most novel contributions was its analysis of spatial effects—how robot adoption in one country can influence emissions in its trade partners. Using spatial econometric models, the researchers found that emissions outcomes tend to cluster geographically, reflecting the structure of global supply chains.
In the short term, adopting robots can lead to increased emissions among partner countries, largely due to carbon leakage as production shifts. However, over time, these indirect effects turn positive. As cleaner technologies and practices spread through trade networks, emissions fall more broadly across the system. While initial adoption creates local gains and regional imbalances, the long-term result is a more efficient and lower-emission manufacturing network.
Conclusion
This study offers compelling evidence that industrial robots help reduce global manufacturing emissions by enhancing labor efficiency, enabling cleaner production, and improving global value chain positions. The strongest benefits are seen in developed economies and capital-intensive, digitally advanced sectors.
While early adoption may lead to short-term emissions increases across supply chains, the long-term effects—fueled by technology diffusion and knowledge transfer—are net reductions in carbon output. The findings reinforce the dual role of industrial automation in promoting economic competitiveness and environmental sustainability.
Policymakers aiming to decarbonize manufacturing should prioritize robot deployment in high-emission sectors and strengthen international collaboration to support technology sharing. This research provides a data-driven framework for aligning Industry 4.0 strategies with global climate targets.
Journal Reference
Zhang, Y., Zhu, J., & Wang, S. Industrial robots reduce carbon emissions in manufacturing through global value chains. Sci Rep 15, 27602 (2025). DOI:10.1038/s41598-025-12958-9. https://www.nature.com/articles/s41598-025-12958-9
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