夜间灯光数据估算中国省域碳排放与国际碳数据库分配的碳排放比较
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刘贤赵,杨旭
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The Accuracy of Nighttime Light Data to Estimate China's Provincial Carbon Emissions: A Comparison with Carbon Emissions Allocated by International Carbon Database
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Xianzhao Liu,Xu Yang
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表3 基于1997~2014年中国省域建成区提取的TDN值与历史碳排放量建立的碳排放预测模型
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Table 3 Carbon emission prediction model based on TDN values extracted from built-up areas of China's provinces and historical carbon emissions from 1997 to 2014
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| 省份 | 回归结果 | 省份 | 回归结果 |
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| 回归方程 | R2 | F值 | P值 | 回归方程 | R2 | F值 | P值 |
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| 北京 | y=0.0003x+36.67 | 0.855 | 87.03 | 0.000 | 河南 | y=0.0048x-275.57 | 0.894 | 134.36 | 0.000 | | 天津 | y=0.0022x-55.20 | 0.887 | 125.57 | 0.000 | 湖北 | y=0.0037x-135.60 | 0.925 | 196.84 | 0.000 | | 河北 | y=0.0066x-312.23 | 0.954 | 321.23 | 0.000 | 湖南 | y=0.0041x-115.36 | 0.918 | 178.43 | 0.000 | | 山西 | y=0.0217x-927.17 | 0.874 | 111.41 | 0.000 | 广东 | y=0.0011x-65.86 | 0.916 | 173.85 | 0.000 | | 内蒙古 | y=0.0134x-525.89 | 0.903 | 136.72 | 0.000 | 广西 | y=0.0033x-117.72 | 0.884 | 100.08 | 0.000 | | 辽宁 | y=0.0043x-367.74 | 0.964 | 423.64 | 0.000 | 海南 | y=0.0053x-40.70 | 0.832 | 79.10 | 0.000 | | 吉林 | y=0.0038x-107.77 | 0.847 | 85.38 | 0.000 | 重庆 | y=0.0019x+10.57 | 0.865 | 103.00 | 0.000 | | 黑龙江 | y=0.0052x-423.72 | 0.869 | 105.95 | 0.000 | 四川 | y=0.0027x-41.93 | 0.847 | 87.94 | 0.000 | | 上海 | y=0.0012x+11.38 | 0.827 | 78.18 | 0.000 | 贵州 | y=0.0131x-118.83 | 0.864 | 94.49 | 0.000 | | 江苏 | y=0.0024x-56.56 | 0.960 | 371.73 | 0.000 | 云南 | y=0.0038x-28.45 | 0.933 | 221.26 | 0.000 | | 浙江 | y=0.0030x-76.64 | 0.943 | 266.60 | 0.000 | 陕西 | y=0.0083x-327.95 | 0.929 | 210.54 | 0.000 | | 安徽 | y=0.0035x-128.89 | 0.882 | 120.06 | 0.000 | 甘肃 | y=0.0046x-86.37 | 0.895 | 136.98 | 0.000 | | 福建 | y=0.0028x-57.68 | 0.986 | 1140.46 | 0.000 | 青海 | y=0.0150x-75.01 | 0.931 | 216.08 | 0.000 | | 江西 | y=0.0024x-7.81 | 0.952 | 307.82 | 0.000 | 宁夏 | y=0.0084x-86.28 | 0.898 | 141.05 | 0.000 | | 山东 | y=0.0040x-206.05 | 0.936 | 233.76 | 0.000 | 新疆 | y=0.0086x-124.03 | 0.927 | 193.88 | 0.000 |
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