摘要
为明确广东省农业碳排放特征及影响因素,预测2023—2040年农业碳排放趋势,为广东省制定农业碳减排政策提供理论依据,本文基于农业物质投入、农田土壤利用、畜牧业养殖3类主要碳源,利用IPCC(政府间气候变化专门委员会)经典碳排放计算理论,对2000—2020年广东省农业碳排放进行测算,进一步分析其时空特征与动态演变趋势,厘清市际差异;利用LMDI模型开展影响因素分析,并运用灰色预测模型GM(1,1)预测2023—2040年碳排放量。结果表明:1)2000—2020年广东省农业碳排放总量及强度逐年降低,2020年广东省农业碳排放总量为3297.7万t,农业碳排放强度为0.59 t∙(万元)^(−1)。其中农田土壤利用贡献的农业碳排放量占比最高,其次为农业物质投入,最后为畜牧业养殖。农田土壤利用中晚稻种植所导致的碳排放平均占比最高,达41.06%;牛饲养、化肥、早稻种植所引起的碳排放量紧随其后,四者之和占广东省农业碳排放总量的84.53%。2)广东省各市农业碳排放总量及强度呈现地区差异。经济欠发达地区总量及强度以高与次高为主,经济发达地区以次低与低为主,呈现由中心向边缘增加趋势;从2000年到2020年,经济欠发达区与经济发达区农业碳排放强度均呈递减趋势。3)农业生产效率、地区产业结构、劳动力规模因素对农业碳减排发挥一定作用,而农业产业结构、地区经济发展水平及城镇化因素为农业碳排放增加的主要因素。4)预测结果表明广东省农业碳排放量在2023年后持续下降,21个地级市中茂名、湛江的农业碳排放在2023年后仍有上升趋势,其他城市的农业碳排放量呈逐年下降趋势。基于此,本文提出强化科技创新、健全农业政策保障体系、提高绿色技术普及率等相关政策建议,以期为广东省农业碳减排规划提供理论参考。
To clarify the characteristics and influencing factors of agricultural carbon emissions in Guangdong Province,this study forecasted the trend of agricultural carbon emissions from 2023 to 2040 to provide a theoretical basis for formulating agricultural carbon emission reduction policies.Using the classical carbon emission calculation theory of the Intergovernmental Panel on Climate Change(IPCC),this study measured(1)the agricultural carbon emissions in Guangdong Province from 2000 to 2020 based on three main carbon sources:agricultural material input,farmland soil use,and livestock breeding;(2)analyzd its spatial and temporal characteristics and dynamic evolution trends further;(3)clarified inter-municipal differences;(4)used the LMDI model to carry out the analysis of influencing factors;and(5)used the gray prediction model GM(1,1)to forecast carbon emissions from 2023 to 2040.The results showed that:(1)from 2000 to 2020,the total amount and intensity of agricultural carbon emissions in Guangdong Province decreased year by year,and in 2020,the total amount of agricultural carbon emissions in Guangdong Province was 32.977 million tons,and the intensity of agricultural carbon emissions was 0.59 t∙(104¥)^(−1).Among them,agricultural soil use contributed the highest percentage of agricultural carbon emissions,followed by agricultural material inputs and livestock breeding.The average share of carbon emissions caused by late rice cultivation was the highest among agricultural soil use,reaching 41.06%,followed by carbon emissions caused by cattle rearing,chemical fertilizer,and early rice cultivation,and the sum of the four reaches 84.53%of the total agricultural carbon emissions in Guangdong Province.(2)The intensity and total amount of agricultural carbon emissions in Guangdong Province showed regional differences.The total amount and intensity of less economically developed areas were mainly high and second-highest,whereas economically developed areas were mainly second-low and low,showing an increasing trend from the center to the edge.From 2000 to 2020,there was a decreasing trend of agricultural carbon emission intensity in both the less economically developed and economically developed regions.(3)Agricultural production efficiency,regional industrial structure,and labor force size factors played a particular role in agricultural carbon emission reduction.In contrast,agricultural-industrial structure,regional economic development level,and urbanization were the main factors for increased agricultural carbon emissions.(4)The prediction results showed that agricultural carbon emissions in Guangdong Province will continue to decline after 2023.Among the 21 prefecture-level cities,agricultural carbon emissions in Maoming and Zhanjiang still have an increasing trend after 2023,whereas agricultural carbon emissions in other cities show a yearly decreasing trend.Based on these results,we proposed relevant policy recommendations such as strengthening scientific and technological innovation,improving the agricultural policy guarantee system,and increasing the penetration rate of green technology to provide theoretical references for agricultural carbon emission reduction planning in Guangdong Province.
作者
任洪杰
李辉尚
冯祎宇
REN Hongjie;LI Huishang;FENG Yiyu(Institute of Agricultural Information,Chinese Academy of Agricultural Sciences/Key Laboratory of Agricultural Big Data,Ministry of Agriculture and Rural Affairs,Beijing 100081,China;Institute of Agricultural Economics and Development,Chinese Academy of Agricultural Sciences,Beijing 100081,China)
出处
《中国生态农业学报(中英文)》
CAS
CSCD
北大核心
2023年第8期1287-1300,共14页
Chinese Journal of Eco-Agriculture
基金
国家自然科学基金面上项目(72073131)
国家社会科学基金重点项目(22ATJ004)
中国农业科学院创新工程(CAAS-AII-2016)
中央级公益性科研院所基本科研业务费专项(JBYW-AII-2022-10,JBYW-AII-2021-41)资助。
关键词
广东省
农业碳排放
时空演变
碳排放预测
Guangdong Province
Agricultural carbon emission
Spatio-temporal evolution
Carbon emission prediction