张再杰, 杨伟芳. 湖北省农业碳排放及基于K-means聚类算法的县级碳排放研究[J]. 云南农业大学学报(社会科学), 2023, 17(2): 134−140. doi: 10.12371/j.ynau(s).202209104
引用本文: 张再杰, 杨伟芳. 湖北省农业碳排放及基于K-means聚类算法的县级碳排放研究[J]. 云南农业大学学报(社会科学), 2023, 17(2): 134−140. doi: 10.12371/j.ynau(s).202209104
ZHANG Zaijie, YANG Weifang. Agricultural Carbon Emissions in Hubei Province and County-level Carbon Emission Research Based on K-means Clustering Algorithm[J]. Journal of Yunnan Agricultural University (Social Science), 2023, 17(2): 134-140. DOI: 10.12371/j.ynau(s).202209104
Citation: ZHANG Zaijie, YANG Weifang. Agricultural Carbon Emissions in Hubei Province and County-level Carbon Emission Research Based on K-means Clustering Algorithm[J]. Journal of Yunnan Agricultural University (Social Science), 2023, 17(2): 134-140. DOI: 10.12371/j.ynau(s).202209104

湖北省农业碳排放及基于K-means聚类算法的县级碳排放研究

Agricultural Carbon Emissions in Hubei Province and County-level Carbon Emission Research Based on K-means Clustering Algorithm

  • 摘要: 基于2011—2020年湖北省相关农业数据,运用IPCC碳排放系数法,对湖北省农业碳排放进行测度,在此基础上,利用K-means聚类算法,以碳排放量和碳排放强度为指标对湖北省73个县域单元进行“排放—效率”类型划分,结合农林牧副渔总产值对各个聚类碳排放情况进行分析。结果表明:湖北省农业碳排放总量整体呈现下降趋势但伴随着一定的年际波动,根据波动特征可大致归为“持续上升—平稳上升—持续下降”三个阶段,碳排放强度整体呈现下降趋势;基于碳排放构成的差异将73个县域单元划分为8类不同的地区。与低排放区相比,高排放地区对碳排放的贡献更大,碳排放规模与农林牧副渔总产值之间呈正相关;与基期相比,HE−LE(高排放—低效率)地区县域单元个数有所减少;以红安县、安陆市、沙洋县为代表的HE−LE(高排放—低效率)地区是湖北省农业碳排放的重排放区,推行相应的农业碳减排举措有助于减排目标的实现。

     

    Abstract: Based on the relevant agricultural data in Hubei Province from 2011 to 2020, the IPCC carbon emission coefficient method was used to measure the agricultural carbon emission in Hubei Province. The index divided 73 county units in Hubei Province into “emission-efficiency” types, and analyzed the carbon emissions of each cluster in combination with the total output value of agriculture, forestry, animal husbandry, and by-fishing. The research results show that: the total agricultural carbon emission in Hubei Province showed a downward trend as a whole, but it was accompanied by a certain inter-annual fluctuation. According to the characteristics of the fluctuation, it could be roughly classified into three stages: “continuously rising-smoothly rising-continuously decreasing” , and the overall carbon emission intensity presented declining trend; 73 county units were divided into 8 different regions based on differences in carbon emission composition. Compared with low-emission areas, high-emission areas contributed more to carbon emissions, and there was a positive correlation between the scale of carbon emissions and the total output value of agriculture, forestry, animal husbandry and by-fishing; compared with the base period, HE-LE (High Emission-Low Efficiency) counties number of units had decreased; HE-LE (High Emission-Low Efficiency) areas represented by Hong'an County, Anlu City, and Shayang County were the heavy emission areas of agricultural carbon emissions in Hubei Province, and corresponding agricultural carbon emission reductions were implemented. The measures would contribute to the achievement of emission reduction targets.

     

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