|
| Carbon emission accounting and carbon peak prediction for cotton production in China |
| Received:May 10, 2022 |
| View Full Text View/Add Comment Download reader |
| KeyWord:cotton production|carbon emission|carbon emission peak|life cycle assessment|STIRPAT model|carbon neutral |
| Author Name | Affiliation | E-mail | | WU Fengqi | Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China | | | HUANG Weibin | Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China | | | CHEN Jiale | State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China | | | HAN Yingchun | State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China | | | FENG Lu | Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China
State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China | | | WANG Guoping | State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China | | | LI Xiaofei | State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China | | | LI Yabing | Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China
State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China | criliyabing@163.com | | WANG Zhan-biao | Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China
State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China | wangzhanbiao@caas.cn |
|
| Hits: 1113 |
| Download times: 1123 |
| Abstract: |
| Breaking down the constitutive factors and influencing factors of carbon emissions, predicting the peak time and peak value of carbon emissions, and comprehensively analyzing the reduction potential of carbon emissions can provide a theoretical reference for responding to climate change, specific to industry. In this study, a life cycle assessment（LCA）was used to calculate carbon emissions from 2004 to 2018, whilst a Stochastic Impacts by Regression on PAT（STIRPAT）model was also conducted to simulate the production scale, cotton imports, agriculture economy, and urbanization rate, with variables determined by Kaya identity as technical efficiency. Furthermore, a ridge regression was used to determine the coefficient. The carbon emission scenarios from 2019 to 2035 were divided into three categories：high emission reduction scenario（HERS）, medium emission reduction scenario（MERS）, and basic scenario（BS）for variable setting and forecasting. From 2004 to 2018, carbon emissions and their growth rates in China's cotton production showed a gradual upward trend. In 2018, carbon emissions reached their highest values across the 15 years, equivalent to 243.4 thousand tons. Xinjiang had the highest carbon emissions（86.8% of the total in 2018）which also significantly increased. Irrigation electricity, fertilizer, and agricultural film were the main carbon emission factors in the production process. The STIRPAT model used to simulate carbon emissions from national cotton production performed well（R2=0.866, adjusted R2=0.792, P=0.001）, and the independent variables all had significant effects on the dependent variable（P<0.01）. The production scale, urbanization rate, and technical efficiency were the main influencing factors. The results showed that from 2019 to 2035, the carbon peak times of China's cotton production under HERS, MERS, and BS would be 2021, 2025, and 2031, respectively, alongside respective peak values of 248.9 thousand, 261.2 thousand, and 272.5 thousand tons. In the future, whilst China's cotton production is developing in terms of intensification and scale, improving production efficiency and accelerating the research, development, and promotion of low-carbon planting technology and soil carbon sequestration technology remain the main breakthrough points in terms of promoting low-carbon cotton production. |
|
|
|
