Abstract:

The LDMI model to decompose the driving and restraining factors of carbon emissions was developed, while using ridge regression to fit an extended STIRPAT model to predict agricultural carbon emissions in Jiangsu province. Five scenarios were established, including baseline, baseline with weak low−carbon development, baseline with strong low−carbon development, low development with strong low−carbon and low development with weak low−carbon. The objective was to clarify the driving mechanisms of agricultural carbon emissions in Jiangsu province, systematically simulated the changing trends of its agricultural carbon emissions from 2021 to 2030, and provided a basis for formulating differentiated emission reduction pathways. The results showed that agricultural production efficiency, agricultural industrial structure and labor force scale played a restraining role in agricultural carbon emissions in Jiangsu from 2006 to 2020. The cumulative contribution of these factors to carbon emissions reached −3259.99×10⁴t, −81.40×10⁴t and −845.73×10⁴t, with agricultural production efficiency being the primary restraining factor. In turn, the level of agricultural economic development and agricultural labor productivity served as driving factors from 2006 to 2020. The cumulative contribution of these factors to carbon emissions reached 1771.62×10⁴t and 1025.74×10⁴t, with agricultural economic development being the main driver. From 2006 to 2020, the restraining effect of labor force size and the promoting effect of agricultural economic development and agricultural labor productivity were both showing a weakening trend in Jiangsu. Under the five scenarios, agricultural carbon emissions in Jiangsu province exhibited a downward trend, among which the scenario of baseline with strong low−carbon development demonstrated the greatest potential for carbon emission reduction, indicating that a robust and green economic development model was the optimal path for Jiangsu province’s future. Therefore, in order to reduce the Jiangsu agricultural carbon emissions, it is necessary to actively develop low−carbon technologies to improve the efficiency of agricultural production, continuously to optimize the industrial and energy structure, to balance economic development and rural population transfer, and to provide quantifiable and actionable practical paths for carbon neutrality of agriculture. 

Key words: Jiangsu, Carbon emissions, LMDI model, STIRPAT model