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Driving factors analysis of agricultural carbon emissions based on extended STIRPAT model of Jiangsu Province, China
Author(s) -
Xiong Chuanhe,
Chen Shuang,
Xu Liting
Publication year - 2020
Publication title -
growth and change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.657
H-Index - 55
eISSN - 1468-2257
pISSN - 0017-4815
DOI - 10.1111/grow.12384
Subject(s) - agriculture , urbanization , agricultural productivity , agricultural machinery , greenhouse gas , driving factors , agricultural economics , population , carbon fibers , environmental science , natural resource economics , china , environmental protection , economics , geography , economic growth , ecology , biology , materials science , demography , sociology , composite number , composite material , archaeology
Abstract STIRPAT (stochastic impact by regression on population, affluence, and technology) model is used to identify the influencing factors of agricultural carbon emissions in Jiangsu province. By referring to Kaya identity and combining with the actual situation of agricultural carbon emissions, four basic influencing factors were obtained: agricultural production efficiency, agricultural structure, agricultural economic development level, and agricultural population size. In addition, urbanization, mechanization, and natural disaster level were listed as influencing factors. The results demonstrated: (a) Urbanization was the first promoting factor of agricultural carbon emissions, indicating a 0.2510% increase in agricultural carbon emissions due to a 1% increase in urbanization. The other three positive factors were, respectively, agricultural mechanization, agricultural structure, and agricultural economic development and their influence indexes were 0.1481, 0.1163, and 0.0845, respectively. (b) Agricultural production efficiency was the most important factor to restrain agricultural carbon emissions. For every 1% increase in agricultural production efficiency, corresponding agricultural carbon emissions would be reduced by 0.3288%. Agricultural population size was also an important factor to reduce agricultural carbon emissions and its influence index was −0.045. Finally, we propose policy recommendations including implementation of orderly urbanization, dependence and development of low carbon technology, establishment of agricultural carbon compensation mechanism, etc.