四川省种植业碳排放现状、动态演进及预测  

The situation,dynamic evolution,and prediction of carbon emissions in the planting industry of Sichuan Province

作　　者：熊鹰[1] 但玉玲 王斌[3] 向智敏 刘宗敏[1] XIONG Ying;DAN Yuling;WANG Bin;XIANG Zhimin;LIU Zongmin(Agricultural Information and Rural Economy Institute,Sichuan Academy of Agricultural Sciences,Chengdu 610066,China;Sichuan Academy of Agricultural Machinery Sciences,Chengdu 610066,China;Institute of Environment and Sustainable Development in Agricul-ture,Chinese Academy of Agricultural Sciences,Beijing 100081,China)

机构地区：[1]四川省农业科学院农业信息与农村经济研究所,成都610066 [2]四川省农业机械科学研究院,成都610066 [3]中国农业科学院农业环境与可持续发展研究所,北京100081

出　　处：《中国生态农业学报（中英文）》2024年第7期1136-1147,共12页Chinese Journal of Eco-Agriculture

基　　金：大自然保护协会项目(2022-075);四川省农业科学院科技攻关任务(1+9KJGG009);四川省财政创新能力提升工程专项资金项目(2022ZZCX038)资助。

摘　　要：加强种植业碳排放测算,可为推进种植业绿色低碳转型提供重要依据。本文针对种植业从投入到产出的全过程,基于农地利用碳排放、稻田CH4排放和农地N2O排放3类主要来源,运用碳排放系数法测算2010—2021年四川省种植业碳排放量,从时序特征和地区差异揭示四川省种植业碳排放特征,采用核密度分析法剖析四川省种植业碳排放动态演进趋势,运用灰色预测模型预测2022—2030年四川省种植业碳排放量和碳排放强度。结果表明:1)四川省种植业碳排放量在2010—2016年间呈波动上升趋势,2016年以后呈波动下降趋势,其碳排放强度在2010—2021年间持续降低,四川省种植业碳排放以农地利用和稻田CH_(4)碳排放为主,2021年较2010年农地利用碳排放和稻田CH_(4)排放比重均略有减少,而农地N_(2)O排放比重有所上升。2)四川省各市(自治州)种植业碳排放量和强度差异明显,2021年碳排放量最高的南充市比最低的甘孜高24.69倍,碳排放强度最高的巴中市比最低的甘孜高2.8倍。3)四川省五大区域种植业碳排放动态演进呈差异化特征,成都平原、川南、川东北、攀西和川西北五大区域种植业碳排放强度总体均呈下降趋势,但下降速度和变化幅度各异,总体上五大区域内碳排放强度的差距在逐步缩小。4)四川省种植业碳排放量和碳排放强度预计保持稳步下降态势,估计到2025年和2030年四川省种植业碳排放量将分别减少约68.72万t和137.84万t,碳排放强度将分别减少约0.13 t·万元^(-1)和0.26 t·万元^(-1)。基于此,四川省种植业碳减排应主要关注源于化肥投入和稻田CH4碳排放,因此需因地制宜采取差异化的减排措施,强化农业科技创新和推广,提升四川省种植业绿色低碳整体发展水平。Strengthening the calculation of carbon emissions in the planting industry will provide support for advancing green and low-carbon transformations.Focusing on the entire process of the planting industry,from input to output,this study utilized carbon emission coefficients to estimate the carbon emissions of the planting industry in Sichuan Province from 2010 to 2021.This estima-tion includes carbon emissions from three main sources:agricultural land use,rice field CH_(4) emissions,and agricultural land N_(2)O emissions.This study aims to reveal the temporal characteristics and regional differences in carbon emissions from the planting in-dustry in Sichuan Province.Furthermore,kernel density analysis was employed to analyze the dynamic evolution trend of carbon emissions from the planting industry of Sichuan Province.In addition,a gray prediction model was utilized to predict carbon emis-sions and intensity from the planting industry of Sichuan Province from 2022 to 2030.The results showed that:1)carbon emissions from the planting industry in Sichuan Province showed a fluctuating increasing trend from 2010 to 2016 and a fluctuating decresing trend from 2016 to 2021,while carbon emission intensity continued to decrease from 2010 to 2021.Agricultural land use and rice field CH4 emissions were the primary contributors to carbon emissions from the planting industry.There was a decrease in the propor-tion of carbon emissions from agricultural land use and rice field CH_(4) in 2021 compared to 2010,whereas the proportions of agricul-tural land N_(2)O emissions increased.2)Significant differences exist in carbon emissions and intensity among the cities(prefectures)in Sichuan Province.In 2021,carbon emissions from the city(Nanchong)with the highest value was 24.69 times higher than that from the prefecture(Ganzi)with the lowest value,and carbon emission intensity of the city(Bazhong)with the highest value was 2.8 times higher than that of the prefecture(Ganzi)with the lowest value.3)The dynamic evolution of carbon emissio

关 键 词：种植业 碳排放测算 核密度分析 灰色预测模型 四川省 

分 类 号：F323.2[经济管理—产业经济]