Carbon footprint of cotton production in China: Composition, spatiotemporal changes and driving factors

文献类型： 外文期刊

第一作者： Huang, Weibin

作者： Huang, Weibin;Wu, Fengqi;Feng, Lu;Li, Yabing;Wang, Zhanbiao;Han, Yingchun;Wang, Guoping;Feng, Lu;Li, Xiaofei;Yang, Beifang;Lei, Yaping;Fan, Zhengyi;Xiong, Shiwu;Xin, Minghua;Li, Yabing;Wang, Zhanbiao;Han, Wanrui;Li, Qinqin;Wang, Zhanbiao

作者机构：

关键词： Cotton; Carbon footprint; Life cycle assessment; Carbon neutral; Carbon peaks

期刊名称：SCIENCE OF THE TOTAL ENVIRONMENT （ 影响因子：10.753； 五年影响因子：10.237 ）

ISSN： 0048-9697

年卷期： 2022 年 821 卷

页码：

收录情况： SCI

摘要： Analyzing the carbon footprint of crop production and proposing low-carbon emission reduction production strategies can help China develop sustainable agriculture under the goal of 'carbon peak and carbon neutrality'. Cotton is an economically important crop in China, but few reports have systematically quantified the carbon footprint of China's cotton production and analyzed its spatiotemporal changes and driving factors. This study used a life cycle approach to analyze the spatiotemporal changes and identify the main components and driving factors of the carbon footprint of cotton production in China between 2004 and 2018 based on statistical data. The results showed that the carbon footprint per unit area of cotton in Northwest China, the Yellow River Basin and the Yangtze River Basin reached 6220.13 kg CO(2)eq.ha(-1), 3528.14 kg CO(2)eq.ha(-1) and 2958.56 kg CO(2)eq.ha(-1), respectively. From 2004 to 2018, the CFa in the Yellow River Basin and Northwest China increased annually, with average increases of 59.87 kg CO(2)eq.ha(-1) and 260.70 kg CO(2)eq.ha(-1), respectively, while the CFa in the Yangtze River Basin decreased by an average of 21.53 kg CO(2)eq.ha(-1) per year. The ridge regression and Logarithmic Mean Divisia Index (LMDI) model showed that fertilizer, irrigation electricity and agricultural film were the main influences on carbon emission growth at the micro level and that the economic factor was the key factor at the macro level. Improving the efficiency of cotton fertilization and electricity use and ensuring the high-quality development of the cotton industry are effective strategies to reduce the carbon footprint of cotton cultivation in the future. This study comprehensively uses statistical data and mathematical modeling to provide theoretical support for accounting and in-depth analysis of cotton carbon emissions. The results are valuable for policy making related to sustainable development and the low-carbon development of the Chinese cotton industry.

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