 Analyzing Spatiotemporal Variations and Influencing Factors in Low-Carbon Green Agriculture Development: Empirical Evidence from 30 Chinese DistrictsZhiyuan Ma,
Jun Wen (),
Yanqi Huang and
Peifen Zhuang
Agriculture, 2025, vol. 15, issue 17, 1-36 Abstract: Agriculture is fundamental to food security and environmental sustainability. Advancing its holistic ecological transformation can stimulate socioeconomic progress while fostering human–nature harmony. Utilizing provincial data from mainland China (2013–2022), this research establishes a multidimensional evaluation framework across four pillars: agricultural ecology, low-carbon practices, modernization, and productivity enhancement. Through comprehensive assessment, we quantify China’s low-carbon green agriculture (LGA) development trajectory and conduct comparative regional analysis across eastern, central, and western zones. As for methods, this study employs multiple econometric approaches: LGA was quantified using the TOPSIS entropy weight method at the first step. Moreover, multidimensional spatial–temporal patterns were characterized through ArcGIS spatial analysis, Dagum Gini coefficient decomposition, Kernel density estimation, and Markov chain techniques, revealing regional disparities, evolutionary trajectories, and state transition dynamics. Last but not least, Tobit regression modeling identified driving mechanisms, informing improvement strategies derived from empirical evidence. The key findings reveal the following: 1. From 2013 to 2022, LGA in China fluctuated significantly. However, the current growth rate is basically maintained between 0% and 10%. Meanwhile, LGA in the vast majority of provinces exceeds 0.3705, indicating that LGA in China is currently in a stable growth period. 2. After 2016, the growth momentum in the central and western regions continued. The growth rate peaked in 2020, with some provinces having a growth rate exceeding 20%. Then the growth rate slowed down, and the intra-regional differences in all regions remained stable at around 0.11. 3. Inter-regional differences are the main factor causing the differences in national LGA, with contribution rates ranging from 67.14% to 74.86%. 4. LGA has the characteristic of polarization. Some regions have developed rapidly, while others have lagged behind. At the end of our ten-year study period, LGA in Yunnan, Guizhou and Shanxi was still below 0.2430, remaining in the low-level range. 5. In the long term, the possibility of improvement in LGA in various regions of China is relatively high, but there is a possibility of maintaining the status quo or “deteriorating”. Even provinces with a high level of LGA may be downgraded, with possibilities ranging from 1.69% to 4.55%. 6. The analysis of driving factors indicates that the level of economic development has a significant positive impact on the level of urban development, while the influences of urbanization, agricultural scale operation, technological input, and industrialization level on the level of urban development show significant regional heterogeneity. In summary, during the period from 2013 to 2022, although China’s LGA showed polarization and experienced ups and downs, it generally entered a period of stable growth. Among them, the inter-regional differences were the main cause of the unbalanced development across the country, but there was also a risk of stagnation and decline. Economic development was the general driving force, while other driving factors showed significant regional heterogeneity. Finally, suggestions such as differentiated development strategies, regional cooperation and resource sharing, and coordinated policy allocation were put forward for the development of LGA. This research is conducive to providing references for future LGA, offering policy inspirations for LGA in other countries and regions, and also providing new empirical results for the academic community. Keywords: low-carbon and green agriculture; spatial difference; dynamic evolution; influencing factors (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:15:y:2025:i:17:p:1853-:d:1738078 Access Statistics for this article Agriculture is currently edited by Ms. Leda Xuan More articles in Agriculture from MDPI |
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