Literature DB >> 35090924

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

Weibin Huang1, Fengqi Wu1, Wanrui Han2, Qinqin Li2, Yingchun Han3, Guoping Wang3, Lu Feng4, Xiaofei Li3, Beifang Yang3, Yaping Lei3, Zhengyi Fan3, Shiwu Xiong3, Minghua Xin3, Yabing Li4, Zhanbiao Wang5.   

Abstract

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 CO2eq·ha-1, 3528.14 kg CO2eq·ha-1 and 2958.56 kg CO2eq·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 CO2eq·ha-1 and 260.70 kg CO2eq·ha-1, respectively, while the CFa in the Yangtze River Basin decreased by an average of 21.53 kg CO2eq·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.
Copyright © 2022. Published by Elsevier B.V.

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Keywords:  Carbon footprint; Carbon neutral; Carbon peaks; Cotton; Life cycle assessment

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Year:  2022        PMID: 35090924     DOI: 10.1016/j.scitotenv.2022.153407

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Spatial and Temporal Characteristics and Drivers of Agricultural Carbon Emissions in Jiangsu Province, China.

Authors:  Chao Hu; Jin Fan; Jian Chen
Journal:  Int J Environ Res Public Health       Date:  2022-09-30       Impact factor: 4.614

  1 in total

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