TY - JOUR
T1 - Urbanization and low-carbon transformation in China's agriculture
T2 - An empirical investigation
AU - Lei, Xiao
AU - Chen, Xingru
AU - Wang, Nan
AU - Wu, Jiayi
AU - Zhang, Bin
N1 - Publisher Copyright:
© 2025 Elsevier Ltd
PY - 2025/4/1
Y1 - 2025/4/1
N2 - As one of the world's largest carbon emitters, China faces significant challenges in managing agricultural carbon emissions (ACE). Urbanization (UR), propelled by economic development, plays a crucial role in reducing carbon emissions by facilitating agricultural structural adjustments, enhancing production efficiency, and promoting technological advancements. This study employs nighttime light data to model UR, thus overcoming the problems in data acquisition, update and accuracy of traditional methods, comparing it with indicators such as built-up area, population and economy. The results demonstrate that both ACE and UR are spatially spread from east to west, with UR demonstrating a strong capacity to reduce ACE—a conclusion corroborated by robustness analysis. The positive impact of UR on emission reduction remains consistent across different regions and innovation levels. Furthermore, through intermediary mechanisms, UR enhances its emission reduction impact by stimulating technological innovation and high-quality economic transformation, generating positive spatial spillover effects in neighboring regions. This study provides valuable insights for government policy formulation, presents a fresh perspective on UR and agricultural carbon emissions reduction (ACER) strategies, and serves as a reference for local governments seeking to harness UR for technological innovation and economic development.
AB - As one of the world's largest carbon emitters, China faces significant challenges in managing agricultural carbon emissions (ACE). Urbanization (UR), propelled by economic development, plays a crucial role in reducing carbon emissions by facilitating agricultural structural adjustments, enhancing production efficiency, and promoting technological advancements. This study employs nighttime light data to model UR, thus overcoming the problems in data acquisition, update and accuracy of traditional methods, comparing it with indicators such as built-up area, population and economy. The results demonstrate that both ACE and UR are spatially spread from east to west, with UR demonstrating a strong capacity to reduce ACE—a conclusion corroborated by robustness analysis. The positive impact of UR on emission reduction remains consistent across different regions and innovation levels. Furthermore, through intermediary mechanisms, UR enhances its emission reduction impact by stimulating technological innovation and high-quality economic transformation, generating positive spatial spillover effects in neighboring regions. This study provides valuable insights for government policy formulation, presents a fresh perspective on UR and agricultural carbon emissions reduction (ACER) strategies, and serves as a reference for local governments seeking to harness UR for technological innovation and economic development.
KW - Agricultural carbon emissions
KW - Nighttime light data
KW - Spatial spillover
KW - Urbanization
UR - http://www.scopus.com/inward/record.url?scp=85218914361&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2025.135242
DO - 10.1016/j.energy.2025.135242
M3 - Article
AN - SCOPUS:85218914361
SN - 0360-5442
VL - 320
JO - Energy
JF - Energy
M1 - 135242
ER -