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县域尺度下河北省农业碳排放时空演变与影响因素研究

周一凡 李彬 张润清

周一凡, 李彬, 张润清. 县域尺度下河北省农业碳排放时空演变与影响因素研究[J]. 中国生态农业学报 (中英文), 2022, 30(4): 570−581 doi: 10.12357/cjea.20210624
引用本文: 周一凡, 李彬, 张润清. 县域尺度下河北省农业碳排放时空演变与影响因素研究[J]. 中国生态农业学报 (中英文), 2022, 30(4): 570−581 doi: 10.12357/cjea.20210624
ZHOU Y F, LI B, ZHANG R Q. Spatiotemporal evolution and influencing factors of agricultural carbon emissions in Hebei Province at the county scale[J]. Chinese Journal of Eco-Agriculture, 2022, 30(4): 570−581 doi: 10.12357/cjea.20210624
Citation: ZHOU Y F, LI B, ZHANG R Q. Spatiotemporal evolution and influencing factors of agricultural carbon emissions in Hebei Province at the county scale[J]. Chinese Journal of Eco-Agriculture, 2022, 30(4): 570−581 doi: 10.12357/cjea.20210624

县域尺度下河北省农业碳排放时空演变与影响因素研究

doi: 10.12357/cjea.20210624
基金项目: 河北省科技厅软科学课题(21557656D)资助
详细信息
    作者简介:

    周一凡, 主要研究方向为资源环境经济与政策。E-mail: fanzhou0930@163.com

    通讯作者:

    张润清, 主要研究方向为农产品加工业、休闲农业和食用菌产业。E-mail: runqingzhang@163.com

  • 中图分类号: F323.3

Spatiotemporal evolution and influencing factors of agricultural carbon emissions in Hebei Province at the county scale

Funds: This study was supported by the Soft Science Project of Science and Technology Department of Hebei Province (21557656D).
More Information
  • 摘要: 县域是农业碳排放基本单元, 研究县域农业碳排放的时空演变与驱动因素对制定区域差异化农业减排政策有重要意义。本文测算了2009—2019年河北省168个县农业碳排放量, 基于探索性空间统计与空间计量方法, 研究了县域农业碳排放的时空演变与影响因素并讨论了空间溢出的边界。研究表明: 河北省农业碳排放整体呈下降趋势, 农业碳排放中土地管理、畜禽肠道发酵和粪便管理的碳排放分别占33.00%、42.57%和24.33%, 县域尺度农业碳排放呈现高度空间集聚的特点。农业碳排放的热点分布与农业产业结构有密切关系, 土地管理引发的农业碳排放热点在冀东南的深州、武强、饶阳等县, 冀北丰宁、围场、滦平和隆化县为畜牧业排放热点。县域农业碳排放有显著的空间溢出效应, 邻近地区农业碳排放对本地区碳排放有正向作用。农业经济发展是农业碳排放增加的主要驱动力, 农业产业结构、机械化程度、化肥施用强度、农村能源消费和农民收入是驱动农业碳排放增长的重要因素。城镇化率对农业碳排放有反向影响。农业碳排放受空间外溢与边界效应双重影响, 碳排放空间溢出范围大概在6~8个邻近县。本研究为建立区域农业碳减排机制提供了政策依据和定量研究工具。
  • 图  1  县域农业碳排放模型空间权重矩阵W1−W5

    W1: 邻近空间权重矩阵; W2: 固定距离空间权重矩阵; W3: K临近空间权重矩阵; W4: 自然临近空间权重矩阵; W5: 反距离空间权重矩阵。W1: adjacent space weight matrix; W2: fixed distance space weight matrix; W3: K-adjacent space weight matrix; W4: natural-adjacent space weight matri; W5: inverse distance space weight matrix.

    Figure  1.  Spatial weight matrix W1-W5 of the county agricultural carbon emission model

    图  2  2009—2019年河北省农业碳排放结构及变化趋势

    Figure  2.  Structure and trend of agricultural carbon emissions in Hebei Province from 2009 to 2019

    图  3  2009—2019年河北省县域农业土地管理碳排放热点图(Getis-Ord-Gi*指数)

    Figure  3.  Hotspots maps of agricultural land management carbon emissions in counties of Hebei Province (Getis-Ord-Gi* index) from 2009 to 2019

    图  4  2009—2019年河北省县域畜禽肠道发酵碳排放热点图(Getis-Ord-Gi*指数)

    Figure  4.  Hotspot maps of carbon emissions from intestinal fermentation of livestock and poultry in counties of Hebei Province (Getis-Ord-Gi* index) from 2009 to 2019

    图  5  2009—2019年河北省县域畜禽粪便管理碳排放热点图(Getis-Ord-Gi*指数)

    Figure  5.  Hotspot map of carbon emissions from livestock and poultry manure management in counties of Hebei Province (Getis-Ord-Gi* index) from 2009 to 2019

    图  6  动态空间权重矩阵下河北省县域农业碳排放空间溢出的滞后回归系数

    Figure  6.  Lagged regression coefficients of spatial spillover of agricultural carbon emissions in counties of Hebei Province under dynamic spatial weight matrix

    表  1  农业碳源与温室气体排放系数

    Table  1.   Agricultural carbon sources and greenhouse gas emission factors

    碳排放源
    Carbon source
    碳排放系数
    Carbon emission factor
    数据来源
    Data source
    土地管理
    Land management
    化肥 Fertilizer 895.6 kg∙t−1 美国橡树岭国家实验室 Oak Ridge National Laboratory, USA
    农药 Pesticides 4934 kg∙t−1 美国橡树岭国家实验室 Oak Ridge National Laboratory, USA
    农膜 Farm film 5180 kg∙t−1 南京农业大学 Nanjing Agricultural University
    翻耕 Plowing 312.6 kg∙hm−2 中国农业大学 China Agricultural University
    灌溉 Irrigation 266.48 kg∙hm−2 HuaPing Duan
    农业机械
    Agricultural machinery
    0.18 kg∙kW−1 Dubey
    肠道发酵
    Intestinal fermentation
    (CH4)
    牛 Cow 80.46 kg∙head−1∙a−1 中国省级温室气体清单编制指南
    Guidelines for the Preparation of Provincial Greenhouse Gas
    Inventories in China
    猪 Pig 1 kg∙head−1∙a−1
    羊 Sheep 8.23 kg∙head−1∙a−1
    禽畜粪便
    Livestock manure
    (CH4, N2O)
    牛 Cow 5.14 kg∙head−1∙a−1, 中国省级温室气体清单编制指南
    Guidelines for the Preparation of Provincial Greenhouse Gas
    Inventories in China
    1.29 kg∙head−1∙a−1
    猪 Pig 3.12 kg∙head−1∙a−1,
    0.093 kg∙head−1∙a−1
    羊 Sheep 0.16 kg∙head−1∙a−1,
    0.227 kg∙head−1∙a−1
    水稻种植
    Rice cultivation
    华北单季稻
    North China single-season rice
    234 kg∙hm−2 中国省级温室气体清单编制指南
    Guidelines for the Preparation of Provincial Greenhouse Gas
    Inventories in China
      《中国省级温室气体清单编制指南》中猪、羊、牛的碳排放系数不同的饲养规模存在差异, 计算时取其均值。The carbon emission factors of pig, sheep and cattle in the “Guidelines for the Preparation of Provincial Greenhouse Gas Inventories in China” differ for different feeding scales and are calculated by taking their average values.
    下载: 导出CSV

    表  2  县域农业碳排放影响因素变量选取与描述性统计

    Table  2.   Variable selection and descriptive statistics of factors influencing agricultural carbon emissions in counties

    变量
    Variable
    符号
    Symbol
    变量解释
    Explanation
    均值
    Mean
    标准差
    Std. deviation
    人均农业生产总值
    Agricultural GDP per capita (¥)
    AGDP 农业生产总值与农村总人口之比
    Ratio of gross agricultural product to total rural population
    9870 5059
    城镇化率
    Urbanization rate (%)
    Urban 参考河北农村统计年鉴
    Reference to Hebei Rural Statistical Yearbook
    46.7 18.9
    农村居民收入
    Income of rural residents (¥)
    Income 参考河北农村统计年鉴
    Reference to Hebei Rural Statistical Yearbook
    9632 7616
    农业产业结构
    Agricultural industry structure (%)
    Str 种植业产值与农业总产值之比
    Ratio of plantation output to total agricultural output
    0.52 0.15
    农业机械化程度
    Agricultural mechanization level (%)
    Tech 机耕面积与农作物播种面积之比
    Ratio of machine cultivated area to crop sown area
    0.64 0.23
    化肥施用强度
    Fertilizer application intensity (%)
    Fer 化肥使用量与农作物播种面积之比
    Ratio of fertilizer use to crop sown area
    0.39 0.20
    农村用电量
    Energy consumption (×108 kWh)
    Energy 参考河北省农村统计年鉴
    Reference to Hebei Rural Statistical Yearbook
    34 724 62 574
    下载: 导出CSV

    表  3  河北省2009—2019年县域农业碳排放Moran’I指数

    Table  3.   Morans’ I of agricultural carbon emissions in counties of Hebei Province from 2009 to 2019

    年份
    Year
    农业碳
    排放
    Agricultural
    carbon emission
    畜牧业
    碳排放
    Carbon emissions
    from livestock
    farming
    人均碳排
    放强度
    Carbon emission
    intensity per
    capita
    2009 0.287 0.306 0.617
    2010 0.272 0.273 0.599
    2011 0.308 0.225 0.568
    2012 0.308 0.221 0.623
    2013 0.298 0.260 0.638
    2014 0.324 0.251 0.622
    2015 0.304 0.136 0.506
    2016 0.311 0.135 0.412
    2017 0.310 0.289 0.420
    2018 0.344 0.355 0.316
    2019 0.320 0.361 0.326
    下载: 导出CSV

    表  4  河北省县域农业碳排放影响因素回归结果

    Table  4.   Regression results of factors influencing agricultural carbon emissions in counties of Hebei Province counties

     
     
    普通面板
    模型
    Common panel data model
    空间误差模型
    Spatial error model
    空间滞后模型
    Spatial lag model
    空间通用模型
    Spatial general model
    固定效应
    Fixed effect
    随机效应
    Random effect
    固定效应
    Fixed effect
    随机效应
    Random effect
    固定效应
    Fixed effect
    随机效应
    Random effect
    农业人均生产总值 Agricultural GDP per capita 0.96***(0.03) 0.92***(0.03) 0.89***(0.03) 0.88***(0.03) 0.79***(0.03) 0.89***(0.03) 0.81***(0.03)
    城镇化率 Urbanization rate −0.64***(0.12) −0.46***(0.11) −1.31***(0.07) −0.52***(0.11) −1.19***(0.05) −0.50***(0.11) −1.20***(0.05)
    农村居民收入 Income of rural residents 0.05***(0.01) 0.05***(0.01) 0.03*(0.01) 0.05***(0.01) 0.03*(0.01) 0.05***(0.01) 0.03*(0.01)
    农业产业结构 Agricultural industry structure 0.12**(0.04) 0.13***(0.04) 0.10**(0.04) 0.10**(0.03) 0.07*(0.03) 0.11**(0.04) 0.08*(0.03)
    农业机械化率 Agricultural mechanization rate 0.15***(0.03) 0.14***(0.03) 0.14***(0.03) 0.15***(0.03) 0.14***(0.03) 0.15***(0.03) 0.14***(0.03)
    化肥施用强度 Fertilizer application intensity 0.08*(0.03) 0.11***(0.03) 0.12***(0.03) 0.08**(0.03) 0.07*(0.03) 0.09**(0.03) 0.09**(0.03)
    农村能源消耗 Rural energy consumption 0.43***(0.02) 0.42***(0.02) 0.40***(0.02) 0.39***(0.02) 0.37***(0.02) 0.39***(0.02) 0.37***(0.02)
    常数项 Constant 11.45***(0.39) 5.86***(0.32) 6.37***(0.33)
    空间滞后系数 Spatial lag coefficient 0.29***(0.03) 0.34***(0.03) 0.26***(0.04) 0.30***(0.03)
    空间误差系数 Spatial error coefficient 0.29***(0.03) 0.36***(0.04) 0.06(0.05) 0.09*(0.05)
    样本量 Observations 1680 1680 1680 1680 1680 1680 1680
    空间LM检验
    Spatial LM test
    3304***
    空间LM1检验
    Spatial LM1 test
    57***
    空间LM2检验
    Spatial LM2 test
    10***
    空间LM-Lambda
    检验
    Spatial LM-Lambda test
    8***
    空间LM-Mu检验
    Spatial LM-Mu test
    56***
    空间豪斯曼检验
    Hausman test for spatial models
    chisq=36, df=7, P-value=9e−06
      *、**和***分别表示回归系数在P<10%、P<5%和P<1%的显著水平, 括号内为标准差。*, ** and *** denote the significance levels of the regression coefficients of P<10%, P<5%, and P<1%, respectively. Date in parentheses are the corresponding standard deviations.
    下载: 导出CSV

    表  5  稳健性检验结果

    Table  5.   Robustness test results

     W1W4W2
    农业人均生产总值 Agricultural GDP per capita 0.94***(0.03) 0.94***(0.03) 0.90***(0.03)
    城镇化率
    Urbanlization rate
    −0.61***(0.11) −0.60***(0.11) −0.51***(0.11)
    农村居民收入
    Income of rural residents
    0.05***(0.01) 0.05*** (0.01) 0.04***(0.02)
    农业产业结构
    Agricultural industry structure
    0.12**(0.04) 0.10**(0.04) 0.11**(0.04)
    农业机械化水平
    Agricultural mechanization rate
    0.16***(0.03) 0.15***(0.03) 0.15***(0.03)
    化肥施用强度
    Fertilizer application intensity
    0.08**(0.03) 0.08**(0.03) 0.08**(0.03)
    农村能源消费
    Rural energy consumption
    0.41***(0.02) 0.42***(0.02) 0.40***(0.02)
    空间滞后系数
    Spatial lag coefficient
    0.20***(0.03) 0.20***(0.03) 0.14***(0.04)
    空间误差系数
    Spatial error coefficient
    0.03(0.05) −0.003(0.05) 0.07(0.05)
      W1: 邻近空间权重矩阵; W4: 自然临近空间权重矩阵; W2: 固定距离空间权重矩阵。*、**、***分别表示回归系数在P<10%、P<5%、P<1%水平显著, 括号内为标准差。W1: adjacent space weight matrix; W4: natural-adjacent space weight matrix; W2: fixed distance space weight matrix. *, **, *** denote the significance levels of the regression coefficients of P<10%, P<5%, and P<1%, respectively. Date in parentheses are the corresponding standard deviations.
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-09-13
  • 录用日期:  2022-01-05
  • 网络出版日期:  2022-01-20
  • 刊出日期:  2022-04-11

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