Decomposition of agriculture-related non-CO2 greenhouse gas emissions in Chengdu: 1995-2020

被引:2
|
作者
Qiao, Dewen [1 ,2 ]
Luo, Yan [2 ,3 ]
Chu, Yuanyue [1 ]
Zhang, Hao
Zhao, Fei [2 ]
机构
[1] Sichuan Univ, Coll Architecture & Environm, Chengdu 610065, Peoples R China
[2] China Qual Certificat Ctr, Dept ECO Dev, Chengdu 610065, Peoples R China
[3] Sichuan Normal Univ, Coll Engn, Chengdu 610065, Peoples R China
关键词
Non-CO 2 GHG emissions; LMDI model; Monte Carlo simulation; Scenario analysis; CHINA; MITIGATION; DRIVERS;
D O I
10.1016/j.jclepro.2023.140125
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Methane (CH4) and nitrous oxide (N2O) emissions originating from agricultural systems exert a significant in-fluence on climate change. The exploration of potential driving factors and emission trends based on a city is important for policy-makers and land managers, however has been rarely known. We aim to investigate the potential driving factors behind five non-CO2 sources within Chengdu's agricultural sector spanning 1995 to 2020, including rice cultivation (CH4), agricultural land (N2O), manure management (CH4 and N2O), and enteric fermentation (CH4), and project non-carbon dioxide (CO2) greenhouse gas (GHG) emissions in Chengdu's agricultural sector for the period from 2021 to 2035. The logarithmic mean Divisia index (LMDI) decomposition model was adopted to figure out the influencing factors, while Monte Carlo simulation and scenario analysis were applied to predict the agricultural non-CO2 GHG emissions from 2021 to 2035. Results reveal that non-CO2 GHG emissions from Chengdu's agriculture exhibit fluctuations and declines, with N2O emissions from agri-cultural land being the most substantial source. Driving actors such as emission intensity (EI), agricultural in-dustrial structure (IS), and rural population (RP) contribute to carbon emission reductions, resulting in reductions of 8.10, 4.25, and 0.91 million tons (Mt), respectively. Conversely, the regional economic develop-ment level (EDL), and urbanization rate (URB) are the primary drivers behind increased agricultural non-CO2 GHG emissions, leading to emissions of 8.91 and 2.35 Mt, respectively. Ultimately, the predictive analysis demonstrates that, under the technological breakthrough scenario, Chengdu's agricultural non-CO2 GHG emis-sions are projected to peak in 2025, with an expected value of only 2.28 Mt. This study offered practical guidance for mitigating non-CO2 GHG emissions in city-level agriculture.
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页数:9
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