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This paper takes the period from 2005 to 2022 as the examination period, and discusses the dynamic evolution law and spatial correlation characteristics of China's animal husbandry on the basis of re-measuring its carbon emissions and analyzing its current characteristics. The results show that the total amount of carbon emissions from China's animal husbandry in the study period has fluctuated, but the overall trend is declining, the carbon emission intensity has been in a continuous downward trend, only the inter-annual rate of decline is different, cattle and hog feeding is the key driver of carbon emissions from the animal husbandry. In 2022, the carbon emissions of the animal husbandry in each province and region were significantly different, and the top 10regions were mainly identified as core livestock production areas or grain production areas. The carbon emissions intensity of the animal husbandry in the interprovincial area was characterized by a distribution pattern of 'high in the northwest and low in the southeast'. The 30 provinces and regions were categorized into four types, such as those driven by cattle feeding and those driven by hog feeding, based on the composition of the carbon emissions of the animal husbandry in each region. During the study period, the carbon emission intensity of the animal husbandry as a whole, as well as that of cattle and sheep rearing, showed an obvious downward trend and the inter-provincial gap narrowed significantly; while the carbon emission intensity of hog rearing also declined, but the inter-provincial gap widened significantly. During the study period, the carbon emission intensity of China's animal husbandry has always had a significant spatial dependence, with low-low agglomeration as the main focus and high-high agglomeration as the secondary focus, and showing the characteristic of “the low is always low and the high is always high”.
, correspAuthors=Yun TIAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Yun TIAN, Rui XIA, Bei LI), CN=ArticleExt(id=1241116645226246184, articleId=1241116641925329919, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=中国畜牧业碳排放再测算：现状特征、动态演进及空间相关性, columnId=1234106419604157142, journalTitle=中国环境科学, columnName=环境影响评价与管理, runingTitle=null, highlight=null, articleAbstract=
以2005~2022年作为考察期，在对中国畜牧业碳排放进行重新测算并分析现状特征的基础上，围绕其动态演进规律及空间关联性特点进行了探讨.结果显示：考察期内中国畜牧业碳排放总量虽存在增减起伏但总体表现出下降趋势，碳排放强度一直处于持续下降态势仅年际降速有所区别，牛和生猪饲养是导致畜牧业碳排放的关键动因;2022年各省区畜牧业碳排放量差异明显，排在前10位的地区主要为核心畜牧业产区或粮食主产区，省际畜牧业碳排放强度总体表现出“西北高、东南低”的分布格局，根据各地区畜牧业碳排放的构成情况可将30个省区划分为牛饲养驱动型、生猪饲养驱动型等4种类型;考察期内畜牧业整体以及牛、羊饲养碳排放强度均表现出了明显下降趋势且省际差距大幅缩小;而生猪饲养碳排放强度虽也出现下降但其省际差距却明显扩大.考察期内中国畜牧业碳排放强度始终存在显著的空间依赖性，且以低-低集聚为主、高-高集聚为辅，同时呈现出“低者恒低、高者恒高”的特征.
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*, address=WTO and Hubei Development Research Center, School of Business Administration, Zhongnan University of Economics and Law, Wuhan 430073, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1241116645712785467, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, authorId=1241116645536624692, language=CN, stringName=田云, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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田云(1986-)，男，湖北长阳人，中南财经政法大学副教授，主要研究方向为碳达峰与碳中和、低碳经济与低碳农业.发表论文100余篇.tianyun1986@163.com.
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田云(1986-)，男，湖北长阳人，中南财经政法大学副教授，主要研究方向为碳达峰与碳中和、低碳经济与低碳农业.发表论文100余篇.tianyun1986@163.com.
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Kernel density distribution of carbon intensity of animal husbandry and cattle, sheep and pig feeding, figureFileSmall=5hdFzzEl6Xbmtxs8D6sRLw==, figureFileBig=hL0nAMV4S2yB1yOThTnibw==, tableContent=null), ArticleFig(id=1241116647637971090, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=CN, label=图1, caption=
畜牧业及牛、羊、生猪饲养碳排放强度核密度分布, figureFileSmall=5hdFzzEl6Xbmtxs8D6sRLw==, figureFileBig=hL0nAMV4S2yB1yOThTnibw==, tableContent=null), ArticleFig(id=1241116649273749673, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=EN, label=Table 1, caption=
Total amount, structure and intensity of animal husbandry carbon emission in China from 2005 to 2022
, figureFileSmall=null, figureFileBig=null, tableContent=
| 年份 | 牛饲养 | 羊饲养 | 生猪饲养 | 其他畜禽饲养 | 能源利用 | 总量(万t) | 强度(t/万元) |
|---|
| 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) |
|---|
| 2005 | 23052.48 | 48.26 | 8002.19 | 16.75 | 10244.71 | 21.45 | 2428.05 | 5.08 | 4043.24 | 8.46 | 47770.67 | 3.60 |
| 2006 | 23011.50 | 47.97 | 8044.23 | 16.77 | 10547.39 | 21.99 | 2408.77 | 5.02 | 3959.80 | 8.25 | 47971.69 | 3.44 |
| 2007 | 20001.30 | 47.42 | 7053.96 | 16.72 | 8758.42 | 20.77 | 2281.01 | 5.41 | 4083.52 | 9.68 | 42178.21 | 2.96 |
| 2008 | 17422.19 | 44.21 | 6055.16 | 15.37 | 9457.48 | 24.00 | 2288.04 | 5.81 | 4185.87 | 10.62 | 39408.74 | 2.59 |
| 2009 | 17725.90 | 44.34 | 6046.15 | 15.13 | 10003.50 | 25.03 | 2294.76 | 5.74 | 3903.04 | 9.76 | 39973.35 | 2.49 |
| 2010 | 17686.32 | 44.00 | 6048.74 | 15.05 | 10336.45 | 25.71 | 2311.97 | 5.75 | 3816.17 | 9.49 | 40199.65 | 2.40 |
| 2011 | 17341.83 | 42.71 | 6334.43 | 15.60 | 10256.21 | 25.26 | 2337.59 | 5.76 | 4337.66 | 10.68 | 40607.72 | 2.39 |
| 2012 | 17112.61 | 41.50 | 6396.45 | 15.51 | 10817.13 | 26.23 | 2389.46 | 5.79 | 4518.26 | 10.96 | 41233.91 | 2.31 |
| 2013 | 17112.91 | 41.87 | 6189.94 | 15.15 | 11091.11 | 27.14 | 2321.65 | 5.68 | 4155.50 | 10.17 | 40871.11 | 2.24 |
| 2014 | 17282.32 | 41.69 | 6403.43 | 15.45 | 11393.96 | 27.48 | 2252.43 | 5.43 | 4124.55 | 9.95 | 41456.69 | 2.21 |
| 2015 | 17546.38 | 42.11 | 6645.10 | 15.95 | 10977.59 | 26.35 | 2265.47 | 5.44 | 4230.67 | 10.15 | 41665.21 | 2.19 |
| 2016 | 17663.18 | 42.53 | 6624.21 | 15.95 | 10617.40 | 25.57 | 2228.66 | 5.37 | 4394.92 | 10.58 | 41528.37 | 2.18 |
| 2017 | 16045.79 | 40.19 | 6569.77 | 16.45 | 10880.88 | 27.25 | 2039.80 | 5.11 | 4391.43 | 11.00 | 39927.67 | 2.05 |
| 2018 | 14450.15 | 39.03 | 6568.77 | 17.74 | 10753.98 | 29.05 | 1839.17 | 4.97 | 3409.29 | 9.21 | 37021.36 | 1.87 |
| 2019 | 14470.70 | 41.30 | 6560.72 | 18.72 | 8434.99 | 24.07 | 2004.47 | 5.72 | 3568.29 | 10.18 | 35039.17 | 1.81 |
| 2020 | 14938.38 | 41.76 | 6678.42 | 18.67 | 8168.80 | 22.83 | 2100.23 | 5.87 | 3888.89 | 10.87 | 35774.72 | 1.81 |
| 2021 | 15431.17 | 40.15 | 6902.16 | 17.96 | 10404.69 | 27.07 | 2096.86 | 5.46 | 3596.82 | 9.36 | 38431.70 | 1.68 |
| 2022 | 15937.92 | 40.34 | 7127.40 | 18.04 | 10848.15 | 27.46 | 2122.50 | 5.37 | 3470.88 | 8.79 | 39506.85 | 1.66 |
| 累计增幅(%) | -30.86 | | -10.93 | | 5.89 | | -12.58 | | -14.16 | | -17.30 | -53.89 |
| 平均增速(%) | -2.15 | | -0.68 | | 0.34 | | -0.79 | | -0.89 | | -1.11 | -4.45 |
), ArticleFig(id=1241116649382801584, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=CN, label=表1, caption=
2005~2022年中国畜牧业碳排放总量、结构及强度
, figureFileSmall=null, figureFileBig=null, tableContent=
| 年份 | 牛饲养 | 羊饲养 | 生猪饲养 | 其他畜禽饲养 | 能源利用 | 总量(万t) | 强度(t/万元) |
|---|
| 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) |
|---|
| 2005 | 23052.48 | 48.26 | 8002.19 | 16.75 | 10244.71 | 21.45 | 2428.05 | 5.08 | 4043.24 | 8.46 | 47770.67 | 3.60 |
| 2006 | 23011.50 | 47.97 | 8044.23 | 16.77 | 10547.39 | 21.99 | 2408.77 | 5.02 | 3959.80 | 8.25 | 47971.69 | 3.44 |
| 2007 | 20001.30 | 47.42 | 7053.96 | 16.72 | 8758.42 | 20.77 | 2281.01 | 5.41 | 4083.52 | 9.68 | 42178.21 | 2.96 |
| 2008 | 17422.19 | 44.21 | 6055.16 | 15.37 | 9457.48 | 24.00 | 2288.04 | 5.81 | 4185.87 | 10.62 | 39408.74 | 2.59 |
| 2009 | 17725.90 | 44.34 | 6046.15 | 15.13 | 10003.50 | 25.03 | 2294.76 | 5.74 | 3903.04 | 9.76 | 39973.35 | 2.49 |
| 2010 | 17686.32 | 44.00 | 6048.74 | 15.05 | 10336.45 | 25.71 | 2311.97 | 5.75 | 3816.17 | 9.49 | 40199.65 | 2.40 |
| 2011 | 17341.83 | 42.71 | 6334.43 | 15.60 | 10256.21 | 25.26 | 2337.59 | 5.76 | 4337.66 | 10.68 | 40607.72 | 2.39 |
| 2012 | 17112.61 | 41.50 | 6396.45 | 15.51 | 10817.13 | 26.23 | 2389.46 | 5.79 | 4518.26 | 10.96 | 41233.91 | 2.31 |
| 2013 | 17112.91 | 41.87 | 6189.94 | 15.15 | 11091.11 | 27.14 | 2321.65 | 5.68 | 4155.50 | 10.17 | 40871.11 | 2.24 |
| 2014 | 17282.32 | 41.69 | 6403.43 | 15.45 | 11393.96 | 27.48 | 2252.43 | 5.43 | 4124.55 | 9.95 | 41456.69 | 2.21 |
| 2015 | 17546.38 | 42.11 | 6645.10 | 15.95 | 10977.59 | 26.35 | 2265.47 | 5.44 | 4230.67 | 10.15 | 41665.21 | 2.19 |
| 2016 | 17663.18 | 42.53 | 6624.21 | 15.95 | 10617.40 | 25.57 | 2228.66 | 5.37 | 4394.92 | 10.58 | 41528.37 | 2.18 |
| 2017 | 16045.79 | 40.19 | 6569.77 | 16.45 | 10880.88 | 27.25 | 2039.80 | 5.11 | 4391.43 | 11.00 | 39927.67 | 2.05 |
| 2018 | 14450.15 | 39.03 | 6568.77 | 17.74 | 10753.98 | 29.05 | 1839.17 | 4.97 | 3409.29 | 9.21 | 37021.36 | 1.87 |
| 2019 | 14470.70 | 41.30 | 6560.72 | 18.72 | 8434.99 | 24.07 | 2004.47 | 5.72 | 3568.29 | 10.18 | 35039.17 | 1.81 |
| 2020 | 14938.38 | 41.76 | 6678.42 | 18.67 | 8168.80 | 22.83 | 2100.23 | 5.87 | 3888.89 | 10.87 | 35774.72 | 1.81 |
| 2021 | 15431.17 | 40.15 | 6902.16 | 17.96 | 10404.69 | 27.07 | 2096.86 | 5.46 | 3596.82 | 9.36 | 38431.70 | 1.68 |
| 2022 | 15937.92 | 40.34 | 7127.40 | 18.04 | 10848.15 | 27.46 | 2122.50 | 5.37 | 3470.88 | 8.79 | 39506.85 | 1.66 |
| 累计增幅(%) | -30.86 | | -10.93 | | 5.89 | | -12.58 | | -14.16 | | -17.30 | -53.89 |
| 平均增速(%) | -2.15 | | -0.68 | | 0.34 | | -0.79 | | -0.89 | | -1.11 | -4.45 |
), ArticleFig(id=1241116649517019321, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=EN, label=Table 2, caption=
Total amount and intensity of animal husbandry carbon emission in 30 provinces of China
, figureFileSmall=null, figureFileBig=null, tableContent=
| 省区市 | 2005年 | 2022年 | 变动率Ⅰ(%) | 变动率Ⅱ(%) |
|---|
| 总量(万t) | 排名 | 强度(t/万元) | 排名 | 总量(万t) | 排名 | 强度(t/万元) | 排名 |
|---|
| 北京 | 241.29 | 28 | 1.78 | 29 | 31.69 | 30 | 0.98 | 26 | -86.87 | -44.62 |
| 天津 | 230.66 | 29 | 2.25 | 26 | 143.61 | 28 | 1.26 | 20 | -37.74 | -43.85 |
| 河北 | 3049.59 | 4 | 2.71 | 22 | 1783.71 | 9 | 0.89 | 29 | -41.51 | -67.34 |
| 山西 | 942.17 | 22 | 6.34 | 7 | 826.68 | 20 | 2.43 | 8 | -12.26 | -61.61 |
| 内蒙古 | 2794.55 | 5 | 6.29 | 8 | 3274.53 | 1 | 3.78 | 5 | 17.18 | -39.83 |
| 辽宁 | 1519.13 | 13 | 2.39 | 23 | 1417.54 | 12 | 1.27 | 19 | -6.69 | -46.92 |
| 吉林 | 1465.58 | 16 | 3.13 | 16 | 1233.09 | 16 | 1.48 | 16 | -15.86 | -52.73 |
| 黑龙江 | 1828.24 | 11 | 3.96 | 10 | 1885.58 | 8 | 1.72 | 11 | 3.14 | -56.56 |
| 上海 | 113.22 | 30 | 2.09 | 27 | 47.88 | 29 | 2.23 | 9 | -57.71 | 6.85 |
| 江苏 | 1038.48 | 20 | 1.73 | 30 | 686.32 | 22 | 0.89 | 29 | -33.91 | -48.68 |
| 浙江 | 558.19 | 25 | 1.95 | 28 | 289.89 | 26 | 1.41 | 17 | -48.07 | -28.00 |
| 安徽 | 1506.85 | 14 | 2.72 | 21 | 996.69 | 19 | 0.91 | 28 | -33.86 | -66.53 |
| 福建 | 637.21 | 24 | 2.30 | 25 | 496.82 | 25 | 1.19 | 23 | -22.03 | -48.57 |
| 江西 | 1141.40 | 18 | 3.13 | 17 | 1061.09 | 17 | 1.51 | 13 | -7.04 | -51.69 |
| 山东 | 3756.31 | 2 | 3.34 | 15 | 1944.27 | 7 | 0.93 | 27 | -48.24 | -72.10 |
| 河南 | 4438.33 | 1 | 3.55 | 13 | 2370.86 | 5 | 0.99 | 25 | -46.58 | -72.07 |
| 湖北 | 1536.20 | 12 | 2.82 | 20 | 1428.97 | 11 | 1.23 | 21 | -6.98 | -56.21 |
| 湖南 | 2507.13 | 6 | 3.00 | 18 | 2212.25 | 6 | 1.49 | 14 | -11.76 | -50.43 |
| 广东 | 1485.29 | 15 | 2.33 | 24 | 1004.54 | 18 | 1.22 | 22 | -32.37 | -47.69 |
| 广西 | 1884.41 | 10 | 3.68 | 12 | 1391.56 | 14 | 1.55 | 12 | -26.15 | -58.04 |
| 海南 | 364.24 | 26 | 3.83 | 11 | 194.45 | 27 | 1.18 | 24 | -46.61 | -69.18 |
| 重庆 | 866.91 | 23 | 3.47 | 14 | 622.69 | 23 | 1.41 | 17 | -28.17 | -59.49 |
| 四川 | 3640.03 | 3 | 2.96 | 19 | 3140.55 | 2 | 1.49 | 14 | -13.72 | -49.63 |
| 贵州 | 1916.69 | 9 | 9.87 | 4 | 1292.10 | 15 | 3.09 | 7 | -32.59 | -68.72 |
| 云南 | 2282.09 | 7 | 6.72 | 6 | 2672.83 | 3 | 3.14 | 6 | 17.12 | -53.21 |
| 陕西 | 944.20 | 21 | 4.74 | 9 | 713.70 | 21 | 1.93 | 10 | -24.41 | -59.23 |
| 甘肃 | 1347.13 | 17 | 10.43 | 3 | 1685.24 | 10 | 4.93 | 3 | 25.10 | -52.72 |
| 青海 | 1134.23 | 19 | 21.94 | 1 | 1404.71 | 13 | 12.80 | 1 | 23.85 | -41.65 |
| 宁夏 | 327.36 | 27 | 7.12 | 5 | 602.06 | 24 | 4.86 | 4 | 83.91 | -31.69 |
| 新疆 | 2273.56 | 8 | 12.39 | 2 | 2650.95 | 4 | 6.55 | 2 | 16.60 | -47.10 |
), ArticleFig(id=1241116649617682622, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=CN, label=表2, caption=
中国30个省区畜牧业碳排放总量及强度
, figureFileSmall=null, figureFileBig=null, tableContent=
| 省区市 | 2005年 | 2022年 | 变动率Ⅰ(%) | 变动率Ⅱ(%) |
|---|
| 总量(万t) | 排名 | 强度(t/万元) | 排名 | 总量(万t) | 排名 | 强度(t/万元) | 排名 |
|---|
| 北京 | 241.29 | 28 | 1.78 | 29 | 31.69 | 30 | 0.98 | 26 | -86.87 | -44.62 |
| 天津 | 230.66 | 29 | 2.25 | 26 | 143.61 | 28 | 1.26 | 20 | -37.74 | -43.85 |
| 河北 | 3049.59 | 4 | 2.71 | 22 | 1783.71 | 9 | 0.89 | 29 | -41.51 | -67.34 |
| 山西 | 942.17 | 22 | 6.34 | 7 | 826.68 | 20 | 2.43 | 8 | -12.26 | -61.61 |
| 内蒙古 | 2794.55 | 5 | 6.29 | 8 | 3274.53 | 1 | 3.78 | 5 | 17.18 | -39.83 |
| 辽宁 | 1519.13 | 13 | 2.39 | 23 | 1417.54 | 12 | 1.27 | 19 | -6.69 | -46.92 |
| 吉林 | 1465.58 | 16 | 3.13 | 16 | 1233.09 | 16 | 1.48 | 16 | -15.86 | -52.73 |
| 黑龙江 | 1828.24 | 11 | 3.96 | 10 | 1885.58 | 8 | 1.72 | 11 | 3.14 | -56.56 |
| 上海 | 113.22 | 30 | 2.09 | 27 | 47.88 | 29 | 2.23 | 9 | -57.71 | 6.85 |
| 江苏 | 1038.48 | 20 | 1.73 | 30 | 686.32 | 22 | 0.89 | 29 | -33.91 | -48.68 |
| 浙江 | 558.19 | 25 | 1.95 | 28 | 289.89 | 26 | 1.41 | 17 | -48.07 | -28.00 |
| 安徽 | 1506.85 | 14 | 2.72 | 21 | 996.69 | 19 | 0.91 | 28 | -33.86 | -66.53 |
| 福建 | 637.21 | 24 | 2.30 | 25 | 496.82 | 25 | 1.19 | 23 | -22.03 | -48.57 |
| 江西 | 1141.40 | 18 | 3.13 | 17 | 1061.09 | 17 | 1.51 | 13 | -7.04 | -51.69 |
| 山东 | 3756.31 | 2 | 3.34 | 15 | 1944.27 | 7 | 0.93 | 27 | -48.24 | -72.10 |
| 河南 | 4438.33 | 1 | 3.55 | 13 | 2370.86 | 5 | 0.99 | 25 | -46.58 | -72.07 |
| 湖北 | 1536.20 | 12 | 2.82 | 20 | 1428.97 | 11 | 1.23 | 21 | -6.98 | -56.21 |
| 湖南 | 2507.13 | 6 | 3.00 | 18 | 2212.25 | 6 | 1.49 | 14 | -11.76 | -50.43 |
| 广东 | 1485.29 | 15 | 2.33 | 24 | 1004.54 | 18 | 1.22 | 22 | -32.37 | -47.69 |
| 广西 | 1884.41 | 10 | 3.68 | 12 | 1391.56 | 14 | 1.55 | 12 | -26.15 | -58.04 |
| 海南 | 364.24 | 26 | 3.83 | 11 | 194.45 | 27 | 1.18 | 24 | -46.61 | -69.18 |
| 重庆 | 866.91 | 23 | 3.47 | 14 | 622.69 | 23 | 1.41 | 17 | -28.17 | -59.49 |
| 四川 | 3640.03 | 3 | 2.96 | 19 | 3140.55 | 2 | 1.49 | 14 | -13.72 | -49.63 |
| 贵州 | 1916.69 | 9 | 9.87 | 4 | 1292.10 | 15 | 3.09 | 7 | -32.59 | -68.72 |
| 云南 | 2282.09 | 7 | 6.72 | 6 | 2672.83 | 3 | 3.14 | 6 | 17.12 | -53.21 |
| 陕西 | 944.20 | 21 | 4.74 | 9 | 713.70 | 21 | 1.93 | 10 | -24.41 | -59.23 |
| 甘肃 | 1347.13 | 17 | 10.43 | 3 | 1685.24 | 10 | 4.93 | 3 | 25.10 | -52.72 |
| 青海 | 1134.23 | 19 | 21.94 | 1 | 1404.71 | 13 | 12.80 | 1 | 23.85 | -41.65 |
| 宁夏 | 327.36 | 27 | 7.12 | 5 | 602.06 | 24 | 4.86 | 4 | 83.91 | -31.69 |
| 新疆 | 2273.56 | 8 | 12.39 | 2 | 2650.95 | 4 | 6.55 | 2 | 16.60 | -47.10 |
), ArticleFig(id=1241116649718345926, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=EN, label=Table 3, caption=
Animal husbandry carbon emission structure in 30 provinces of China in 2022
, figureFileSmall=null, figureFileBig=null, tableContent=
| 类型 | 省区市 | 牛饲养 | 羊饲养 | 生猪饲养 | 其他畜禽饲养 | 能源利用 |
|---|
| 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) |
|---|
| 牛饲养驱动型 | 北京 | 17.12 | 54.02 | 4.25 | 13.41 | 4.99 | 15.75 | 0.87 | 2.75 | 4.46 | 14.07 |
| 吉林 | 597.02 | 48.42 | 151.95 | 12.32 | 285.17 | 23.13 | 54.99 | 4.46 | 143.96 | 11.67 |
| 黑龙江 | 912.72 | 48.41 | 190.56 | 10.11 | 359.26 | 19.05 | 39.32 | 2.09 | 383.72 | 20.35 |
| 贵州 | 784.67 | 60.73 | 84.85 | 6.57 | 307.70 | 23.81 | 30.56 | 2.37 | 84.32 | 6.53 |
| 云南 | 1430.36 | 53.51 | 311.10 | 11.64 | 702.59 | 26.29 | 69.98 | 2.62 | 158.8 | 5.94 |
| 青海 | 1048.34 | 74.63 | 311.14 | 22.15 | 11.92 | 0.85 | 14.15 | 1.01 | 19.16 | 1.36 |
| 宁夏 | 405.74 | 67.39 | 157.61 | 26.18 | 17.18 | 2.85 | 2.10 | 0.35 | 19.43 | 3.23 |
| 生猪饲养驱动型 | 江苏 | 53.82 | 7.84 | 86.87 | 12.66 | 350.18 | 51.02 | 74.88 | 10.91 | 120.57 | 17.57 |
| 浙江 | 28.91 | 9.97 | 35.36 | 12.20 | 131.86 | 45.49 | 20.92 | 7.22 | 72.84 | 25.13 |
| 安徽 | 175.79 | 17.64 | 142.05 | 14.25 | 452.84 | 45.43 | 111.15 | 11.15 | 114.86 | 11.52 |
| 福建 | 57.31 | 11.54 | 24.01 | 4.83 | 250.24 | 50.37 | 108.60 | 21.86 | 56.66 | 11.40 |
| 湖北 | 390.93 | 27.36 | 121.59 | 8.51 | 664.51 | 46.50 | 60.17 | 4.21 | 191.77 | 13.42 |
| 广东 | 187.75 | 18.69 | 19.77 | 1.97 | 542.13 | 53.97 | 130.12 | 12.95 | 124.77 | 12.42 |
| 重庆 | 177.80 | 28.55 | 75.70 | 12.16 | 295.25 | 47.42 | 24.52 | 3.94 | 49.42 | 7.94 |
| 双类别驱动型 | 河北 | 713.87 | 40.02 | 310.70 | 17.42 | 543.57 | 30.47 | 88.13 | 4.94 | 127.44 | 7.14 |
| 内蒙古 | 1353.57 | 41.34 | 1393.09 | 42.54 | 137.50 | 4.20 | 140.30 | 4.28 | 250.07 | 7.64 |
| 辽宁 | 492.20 | 34.72 | 181.74 | 12.82 | 448.72 | 31.65 | 117.79 | 8.31 | 177.09 | 12.49 |
| 江西 | 437.97 | 41.28 | 31.40 | 2.96 | 475.12 | 44.78 | 57.81 | 5.45 | 58.79 | 5.54 |
| 湖南 | 710.69 | 32.13 | 179.40 | 8.11 | 968.69 | 43.79 | 55.25 | 2.50 | 298.22 | 13.48 |
| 广西 | 629.56 | 45.24 | 60.89 | 4.38 | 518.97 | 37.29 | 114.29 | 8.21 | 67.85 | 4.88 |
| 海南 | 77.40 | 39.80 | 13.89 | 7.14 | 63.60 | 32.71 | 17.32 | 8.91 | 22.24 | 11.44 |
| 四川 | 1469.98 | 46.81 | 346.03 | 11.02 | 1015.24 | 32.33 | 145.98 | 4.65 | 163.32 | 5.20 |
| 甘肃 | 865.66 | 51.37 | 571.90 | 33.94 | 138.87 | 8.24 | 50.21 | 2.98 | 58.6 | 3.48 |
| 新疆 | 1142.21 | 43.09 | 1066.95 | 40.25 | 113.90 | 4.30 | 168.35 | 6.35 | 159.54 | 6.02 |
| 三类别驱动型 | 天津 | 54.63 | 38.04 | 11.44 | 7.97 | 31.08 | 21.64 | 6.16 | 4.29 | 40.3 | 28.06 |
| 山西 | 253.78 | 30.70 | 247.61 | 29.95 | 183.86 | 22.24 | 27.09 | 3.28 | 114.34 | 13.83 |
| 上海 | 12.62 | 26.36 | 3.13 | 6.54 | 15.38 | 32.12 | 0.53 | 1.11 | 16.22 | 33.88 |
| 山东 | 511.39 | 26.30 | 332.43 | 17.10 | 702.06 | 36.11 | 267.03 | 13.73 | 131.36 | 6.76 |
| 河南 | 684.11 | 28.85 | 459.86 | 19.40 | 917.62 | 38.70 | 114.58 | 4.83 | 194.69 | 8.21 |
| 陕西 | 260.00 | 36.43 | 200.13 | 28.04 | 198.15 | 27.76 | 9.35 | 1.31 | 46.07 | 6.46 |
), ArticleFig(id=1241116649860952270, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=CN, label=表3, caption=
2022年中国30个省区畜牧业碳排放结构
, figureFileSmall=null, figureFileBig=null, tableContent=
| 类型 | 省区市 | 牛饲养 | 羊饲养 | 生猪饲养 | 其他畜禽饲养 | 能源利用 |
|---|
| 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) | 数量(万t) | 比重(%) |
|---|
| 牛饲养驱动型 | 北京 | 17.12 | 54.02 | 4.25 | 13.41 | 4.99 | 15.75 | 0.87 | 2.75 | 4.46 | 14.07 |
| 吉林 | 597.02 | 48.42 | 151.95 | 12.32 | 285.17 | 23.13 | 54.99 | 4.46 | 143.96 | 11.67 |
| 黑龙江 | 912.72 | 48.41 | 190.56 | 10.11 | 359.26 | 19.05 | 39.32 | 2.09 | 383.72 | 20.35 |
| 贵州 | 784.67 | 60.73 | 84.85 | 6.57 | 307.70 | 23.81 | 30.56 | 2.37 | 84.32 | 6.53 |
| 云南 | 1430.36 | 53.51 | 311.10 | 11.64 | 702.59 | 26.29 | 69.98 | 2.62 | 158.8 | 5.94 |
| 青海 | 1048.34 | 74.63 | 311.14 | 22.15 | 11.92 | 0.85 | 14.15 | 1.01 | 19.16 | 1.36 |
| 宁夏 | 405.74 | 67.39 | 157.61 | 26.18 | 17.18 | 2.85 | 2.10 | 0.35 | 19.43 | 3.23 |
| 生猪饲养驱动型 | 江苏 | 53.82 | 7.84 | 86.87 | 12.66 | 350.18 | 51.02 | 74.88 | 10.91 | 120.57 | 17.57 |
| 浙江 | 28.91 | 9.97 | 35.36 | 12.20 | 131.86 | 45.49 | 20.92 | 7.22 | 72.84 | 25.13 |
| 安徽 | 175.79 | 17.64 | 142.05 | 14.25 | 452.84 | 45.43 | 111.15 | 11.15 | 114.86 | 11.52 |
| 福建 | 57.31 | 11.54 | 24.01 | 4.83 | 250.24 | 50.37 | 108.60 | 21.86 | 56.66 | 11.40 |
| 湖北 | 390.93 | 27.36 | 121.59 | 8.51 | 664.51 | 46.50 | 60.17 | 4.21 | 191.77 | 13.42 |
| 广东 | 187.75 | 18.69 | 19.77 | 1.97 | 542.13 | 53.97 | 130.12 | 12.95 | 124.77 | 12.42 |
| 重庆 | 177.80 | 28.55 | 75.70 | 12.16 | 295.25 | 47.42 | 24.52 | 3.94 | 49.42 | 7.94 |
| 双类别驱动型 | 河北 | 713.87 | 40.02 | 310.70 | 17.42 | 543.57 | 30.47 | 88.13 | 4.94 | 127.44 | 7.14 |
| 内蒙古 | 1353.57 | 41.34 | 1393.09 | 42.54 | 137.50 | 4.20 | 140.30 | 4.28 | 250.07 | 7.64 |
| 辽宁 | 492.20 | 34.72 | 181.74 | 12.82 | 448.72 | 31.65 | 117.79 | 8.31 | 177.09 | 12.49 |
| 江西 | 437.97 | 41.28 | 31.40 | 2.96 | 475.12 | 44.78 | 57.81 | 5.45 | 58.79 | 5.54 |
| 湖南 | 710.69 | 32.13 | 179.40 | 8.11 | 968.69 | 43.79 | 55.25 | 2.50 | 298.22 | 13.48 |
| 广西 | 629.56 | 45.24 | 60.89 | 4.38 | 518.97 | 37.29 | 114.29 | 8.21 | 67.85 | 4.88 |
| 海南 | 77.40 | 39.80 | 13.89 | 7.14 | 63.60 | 32.71 | 17.32 | 8.91 | 22.24 | 11.44 |
| 四川 | 1469.98 | 46.81 | 346.03 | 11.02 | 1015.24 | 32.33 | 145.98 | 4.65 | 163.32 | 5.20 |
| 甘肃 | 865.66 | 51.37 | 571.90 | 33.94 | 138.87 | 8.24 | 50.21 | 2.98 | 58.6 | 3.48 |
| 新疆 | 1142.21 | 43.09 | 1066.95 | 40.25 | 113.90 | 4.30 | 168.35 | 6.35 | 159.54 | 6.02 |
| 三类别驱动型 | 天津 | 54.63 | 38.04 | 11.44 | 7.97 | 31.08 | 21.64 | 6.16 | 4.29 | 40.3 | 28.06 |
| 山西 | 253.78 | 30.70 | 247.61 | 29.95 | 183.86 | 22.24 | 27.09 | 3.28 | 114.34 | 13.83 |
| 上海 | 12.62 | 26.36 | 3.13 | 6.54 | 15.38 | 32.12 | 0.53 | 1.11 | 16.22 | 33.88 |
| 山东 | 511.39 | 26.30 | 332.43 | 17.10 | 702.06 | 36.11 | 267.03 | 13.73 | 131.36 | 6.76 |
| 河南 | 684.11 | 28.85 | 459.86 | 19.40 | 917.62 | 38.70 | 114.58 | 4.83 | 194.69 | 8.21 |
| 陕西 | 260.00 | 36.43 | 200.13 | 28.04 | 198.15 | 27.76 | 9.35 | 1.31 | 46.07 | 6.46 |
), ArticleFig(id=1241116649970004182, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=EN, label=Table 4, caption=
Global Moran Index statistics of animal husbandry carbon emission intensity of China's from 2005 to 2022
, figureFileSmall=null, figureFileBig=null, tableContent=
| 年份 | Moran’s I | Z值 | P值 | 年份 | Moran’s I | Z值 | P值 |
|---|
| 2005 | 0.342 | 4.708 | 0.000 | 2014 | 0.401 | 5.801 | 0.000 |
| 2006 | 0.359 | 4.809 | 0.000 | 2015 | 0.394 | 5.636 | 0.000 |
| 2007 | 0.373 | 5.085 | 0.000 | 2016 | 0.388 | 5.560 | 0.000 |
| 2008 | 0.391 | 5.695 | 0.000 | 2017 | 0.347 | 5.170 | 0.000 |
| 2009 | 0.398 | 5.782 | 0.000 | 2018 | 0.346 | 5.209 | 0.000 |
| 2010 | 0.397 | 5.870 | 0.000 | 2019 | 0.365 | 5.157 | 0.000 |
| 2011 | 0.400 | 5.940 | 0.000 | 2020 | 0.349 | 5.042 | 0.000 |
| 2012 | 0.410 | 5.971 | 0.000 | 2021 | 0.296 | 4.650 | 0.000 |
| 2013 | 0.409 | 5.874 | 0.000 | 2022 | 0.305 | 4.595 | 0.000 |
), ArticleFig(id=1241116650074861789, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=CN, label=表4, caption=
2005~2022年中国畜牧业碳排放强度的全局莫兰指数统计值
, figureFileSmall=null, figureFileBig=null, tableContent=
| 年份 | Moran’s I | Z值 | P值 | 年份 | Moran’s I | Z值 | P值 |
|---|
| 2005 | 0.342 | 4.708 | 0.000 | 2014 | 0.401 | 5.801 | 0.000 |
| 2006 | 0.359 | 4.809 | 0.000 | 2015 | 0.394 | 5.636 | 0.000 |
| 2007 | 0.373 | 5.085 | 0.000 | 2016 | 0.388 | 5.560 | 0.000 |
| 2008 | 0.391 | 5.695 | 0.000 | 2017 | 0.347 | 5.170 | 0.000 |
| 2009 | 0.398 | 5.782 | 0.000 | 2018 | 0.346 | 5.209 | 0.000 |
| 2010 | 0.397 | 5.870 | 0.000 | 2019 | 0.365 | 5.157 | 0.000 |
| 2011 | 0.400 | 5.940 | 0.000 | 2020 | 0.349 | 5.042 | 0.000 |
| 2012 | 0.410 | 5.971 | 0.000 | 2021 | 0.296 | 4.650 | 0.000 |
| 2013 | 0.409 | 5.874 | 0.000 | 2022 | 0.305 | 4.595 | 0.000 |
), ArticleFig(id=1241116650175525091, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=EN, label=Table 5, caption=
Local spatial clustering of animal husbandry carbon emission intensity in 30 provinces in main years
, figureFileSmall=null, figureFileBig=null, tableContent=
| 年份 | 高-高集聚区 | 低-高集聚区 | 低-低集聚区 | 高-低集聚区 |
|---|
| 2005 | 内蒙古、云南、甘肃、青海、宁夏、新疆 | 广西、重庆、四川、陕西 | 北京、天津、河北、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、海南 | 山西、贵州 |
| 2010 | 贵州、云南、甘肃、青海、宁夏、新疆 | 广西、重庆、四川、陕西 | 北京、天津、河北、山西、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、海南 | 内蒙古 |
| 2015 | 云南、甘肃、青海、宁夏、新疆 | 重庆、四川、陕西 | 北京、天津、河北、山西、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、广西、海南 | 内蒙古、贵州 |
| 2022 | 云南、甘肃、青海、宁夏、新疆 | 重庆、四川、陕西 | 北京、天津、河北、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、广西、海南 | 山西、内蒙古、贵州 |
), ArticleFig(id=1241116650280382697, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116641925329919, language=CN, label=表5, caption=
主要年份30省区畜牧业碳排放强度的局部空间聚类情况
, figureFileSmall=null, figureFileBig=null, tableContent=
| 年份 | 高-高集聚区 | 低-高集聚区 | 低-低集聚区 | 高-低集聚区 |
|---|
| 2005 | 内蒙古、云南、甘肃、青海、宁夏、新疆 | 广西、重庆、四川、陕西 | 北京、天津、河北、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、海南 | 山西、贵州 |
| 2010 | 贵州、云南、甘肃、青海、宁夏、新疆 | 广西、重庆、四川、陕西 | 北京、天津、河北、山西、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、海南 | 内蒙古 |
| 2015 | 云南、甘肃、青海、宁夏、新疆 | 重庆、四川、陕西 | 北京、天津、河北、山西、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、广西、海南 | 内蒙古、贵州 |
| 2022 | 云南、甘肃、青海、宁夏、新疆 | 重庆、四川、陕西 | 北京、天津、河北、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、湖南、广东、广西、海南 | 山西、内蒙古、贵州 |
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