Title |
Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms |
ID_Doc |
32248 |
Authors |
Shen, Y; Yang, ZH |
Title |
Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms |
Year |
2023 |
Published |
Sustainability, 15, 8 |
DOI |
10.3390/su15086401 |
Abstract |
The coordinated promotion of pollution control and carbon reduction is intended to build a more beautiful China. Intelligent industrial technology plays an important role in the fight against climate change and in improving the ecological environment. Based on panel data from 30 provinces in China from 2006 to 2020, we used a two-way fixed effects model to evaluate the synergistic effects of industrial intelligent transformation on pollution control and carbon reduction and its mechanisms. The results showed that the introduction and installation of industrial robots by enterprises significantly reduced carbon emissions and the concentration of fine particles in the air, as well as having the synergistic effect of reducing pollution and carbon. This conclusion was still robust after using instrumental variable methods to perform endogenous tests. The study also showed that industrial intelligence reduced pollution and carbon through mechanisms that promoted green technological innovation and improved energy efficiency. The conclusions of this study could provide evidence for the use of digital technologies to promote environmental protection and achieve the goal of carbon neutrality, as well as play a significant role in the promotion of economic and societal green transformation. |
Author Keywords |
industrial intelligence; carbon emissions; fine particulate matter; green technological innovation; energy efficiency; econometrics |
Index Keywords |
Index Keywords |
Document Type |
Other |
Open Access |
Open Access |
Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
EID |
WOS:000978267500001 |
WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
PDF |
https://www.mdpi.com/2071-1050/15/8/6401/pdf?version=1680947439
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