# The Non-Linear Impact of Industry 4.0 on Carbon Emissions in China's Logistics Sector
## 3 Results
### Regional Variations
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Region** & **Industry 4.0 Index** & **Industry 4.0 Index** & **Carbon Emissions** & **Carbon Emissions** & **\% Change in Emissions** \\  & **(2011)** & **(2019)** & **(2011, Tons)** & **(2019, Tons)** & **(2011–2019)** \\ \hline Eastern China (Jiangsu) & 0.2 & 0.55 & 2,100,000 & 1,850,000 & \(-\)11.90\% \\ \hline Central China (Henan) & 0.15 & 0.35 & 2,500,000 & 2,300,000 & \(-\)8.00\% \\ \hline Western China (Sichuan) & 0.1 & 0.25 & 3,000,000 & 2,900,000 & \(-\)3.30\% \\ \hline Southern China (Guangdong) & 0.3 & 0.6 & 1,800,000 & 1,500,000 & \(-\)16.70\% \\ \hline Northeast China (Liaoning) & 0.18 & 0.4 & 2,200,000 & 2,000,000 & \(-\)9.10\% \\ \hline Northern China (Beijing) & 0.25 & 0.5 & 1,600,000 & 1,300,000 & \(-\)18.80\% \\ \hline Northwestern China (Shaamxi) & 0.12 & 0.32 & 2,800,000 & 2,600,000 & \(-\)7.10\% \\ \hline Eastern China (Shanghai) & 0.28 & 0.58 & 1,700,000 & 1,450,000 & \(-\)14.70\% \\ \hline Central China (Hunan) & 0.14 & 0.36 & 2,400,000 & 2,200,000 & \(-\)8.30\% \\ \hline Western China (Yunnan) & 0.11 & 0.27 & 2,900,000 & 2,800,000 & \(-\)3.40\% \\ \hline Southern China (Fujian) & 0.22 & 0.52 & 1,950,000 & 1,720,000 & \(-\)11.80\% \\ \hline Northern China (Tianjin) & 0.24 & 0.48 & 1,750,000 & 1,480,000 & \(-\)15.40\% \\ \hline Southwestern China (Guizhou) & 0.13 & 0.29 & 3,200,000 & 3,050,000 & \(-\)4.70\% \\ \hline Northeastern China (Jilin) & 0.17 & 0.38 & 2,100,000 & 1,980,000 & \(-\)5.70\% \\ \hline \hline \end{tabular} Explanation: This table compares the adoption of Industry 4.0 and changes in carbon emissions in different regions of China. It illustrates how regional differences influence the effectiveness of Industry 4.0.  
\end{table} 
Table 4: Regional Variations in Industry 4.0 Adoption and Carbon Emission Reductions. Figure 4: Comparison of Carbon Emission Reductions Across Regions (2011 vs. 2019). Explanation: This radar chart presents the results of a dynamic panel regression, showing the long-term impact of Industry 4.0 on carbon emissions. The chart indicates that the influence of Industry 4.0 on reducing carbon emissions increased over time, with the coefficients growing from 2011 to 2019. This suggests that the long-term effects of Industry 4.0 became more significant, contributing increasingly to carbon emission reductions. Future research should explore the potential of integrating Industry 4.0 technologies with emerging Industry 5.0 principles, which emphasize human-centric and collaborative approaches. Longitudinal studies examining the long-term impacts of these technologies on carbon emissions across different sectors will provide valuable insights into their scalability and effectiveness. Interdisciplinary research combining technological innovation, human factors, and policy studies is crucial for developing a comprehensive framework for sustainable technology deployment. * Description--The heatmap illustrates the percentage change in carbon emissions from 2011 to 2019 across regions, along with the final carbon emissions in 2019. Industry 4.0\({}^{\prime}\)s effect on carbon reduction is manifested in green, while the less pronounced effect is in red. * Significance--This gap in carbon reduction from the revolution of Industry 4.0 lies in the spotlight, where the discrepancy in the decrease in carbon emissions by the adoption of advanced technologies is shown. * Future research should focus on cross-sectoral applications of the toolkit, including its integration into manufacturing and smart city infrastructures. Longitudinal studies examining the long-term impact of Industry 4.0 and 5.0 technologies on carbon emissions across different sectors will provide valuable insights into their scalability and effectiveness. Interdisciplinary research combining technological innovation, human factors, and policy studies is crucial for developing a comprehensive framework for sustainable technology deployment.