基于灰色关联模型对江苏省PM2.5浓度影响因素的分析
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贺祥, 林振山, 刘会玉, 齐相贞
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Analysis of the driving factors of PM2.5 in Jiangsu province based on grey correlation model
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Xiang HE, Zhenshan LIN, Huiyu LIU, Xiangzhen QI
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表2 江苏省13个省辖市PM2.5浓度影响指标因子的数据 |
Tab. 2 Data of the PM2.5 influencing indices for the 13 provincial cities in Jiangsu province |
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指标层 | 因子 | 南京市 | 无锡市 | 徐州市 | 常州市 | 苏州市 | 南通市 | 连云港市 | 淮安市 | 盐城市 | 扬州市 | 镇江市 | 泰州市 | 宿迁市 | PM2.5 | X0 | 73.82 | 67.27 | 67.28 | 66.48 | 65.92 | 61.51 | 74.78 | 68.65 | 58.30 | 65.93 | 67.28 | 62.83 | 68.81 | 空气 质量 指标 及 气象 要素 | 大气污染物 | X1 | 123.46 | 105.38 | 118.86 | 103.76 | 89.98 | 93.89 | 112.03 | 101.78 | 92.54 | 112.29 | 109.70 | 110.42 | 114.88 | X2 | 23.00 | 28.17 | 37.95 | 35.16 | 22.06 | 26.37 | 29.68 | 27.66 | 19.83 | 33.06 | 24.40 | 30.61 | 27.11 | X3 | 0.90 | 1.10 | 1.22 | 1.10 | 0.93 | 0.74 | 1.01 | 1.07 | 0.77 | 0.83 | 1.18 | 1.21 | 1.20 | X4 | 50.82 | 44.28 | 37.16 | 44.57 | 51.79 | 36.30 | 35.28 | 23.33 | 25.43 | 32.22 | 45.33 | 22.87 | 33.18 | X5 | 99.43 | 101.66 | 91.68 | 102.48 | 95.89 | 105.04 | 98.83 | 111.73 | 101.12 | 86.79 | 90.05 | 75.59 | 92.01 | 气象要素 | X6 | 29.99 | 37.99 | 22.76 | 33.21 | 34.84 | 36.43 | 23.55 | 26.92 | 37.48 | 30.56 | 23.50 | 22.84 | 28.74 | X7 | 25.96 | 22.01 | 17.31 | 20.93 | 20.76 | 28.67 | 20.03 | 21.39 | 22.81 | 18.76 | 28.08 | 22.64 | 17.30 | X8 | 165.09 | 168.78 | 156.64 | 157.37 | 171.46 | 159.49 | 147.39 | 149.43 | 149.53 | 163.13 | 158.22 | 156.89 | 150.55 | X9 | 73.96 | 73.36 | 66.08 | 66.12 | 73.61 | 77.40 | 75.31 | 77.32 | 78.60 | 72.47 | 86.75 | 74.52 | 73.01 | X10 | 51.06 | 47.23 | 60.83 | 48.84 | 44.47 | 50.00 | 53.19 | 47.15 | 60.08 | 56.23 | 58.86 | 57.60 | 54.14 | PM2.5 污染物 来源 | 交通 | X11 | 11131 | 2951 | 3926 | 4276 | 4610 | 3928. 0 | 1529 | 4871 | 2891 | 4203 | 1602 | 3242 | 3228 | X12 | 10493 | 3364 | 10259 | 4673 | 24010 | 6586 | 3133 | 4420 | 4018 | 6035 | 2245 | 3437 | 1374 | X13 | 10912 | 4734 | 7529 | 6932 | 5065 | 4769 | 3053 | 2220 | 2110 | 6155 | 3529 | 1123 | 762 | X14 | 140.41 | 67.63 | 35.80 | 61.01 | 113.22 | 34.56 | 12.13 | 19.30 | 14.91 | 29.02 | 16.15 | 17.97 | 14.45 | 工业生产 | X15 | 286.71 | 194.01 | 158.90 | 215.48 | 418.01 | 96.62 | 28.35 | 63.65 | 24.96 | 69.70 | 84.67 | 53.43 | 51.01 | 工业气体排放 | X16 | 112435 | 83745 | 136060 | 35916 | 165939 | 65145 | 49739 | 47931 | 47125 | 48891 | 66346 | 52501 | 29906 | X17 | 143701 | 148750 | 209055 | 93502 | 248636 | 71126 | 45952 | 70366 | 51645 | 81567 | 82025 | 53889 | 37826 | X18 | 68910 | 47123 | 58398 | 36964 | 70299 | 36439 | 23221 | 23899 | 32914 | 19023 | 24452 | 18243 | 40074 | 建筑 | X19 | 16637 | 4431 | 7703 | 8765 | 10999 | 54420 | 3451 | 8054 | 8943 | 17652 | 1905 | 18977 | 4842 | 城市化 与产业 结构 | 城市与绿化面积 | X20 | 86117 | 18333 | 15269 | 8088 | 21315 | 7271 | 19852 | 6170 | 4040 | 6724 | 7388 | 3585 | 8300 | X21 | 15 | 15 | 16 | 13 | 15 | 14 | 14 | 13 | 12 | 17 | 18 | 9 | 13 | X22 | 44 | 43 | 43 | 43 | 42 | 42 | 40 | 41 | 40 | 43 | 42 | 41 | 42 | X23 | 713 | 325 | 253 | 186 | 441 | 172 | 150 | 140 | 96 | 132 | 128 | 96 | 75 | 人口数量 | X24 | 1243 | 2194 | 1043 | 1813 | 1224 | 1532 | 736 | 846 | 869 | 1048 | 1131 | 1032 | 710 | 产业结构 | X25 | 0.43 | 0.49 | 0.54 | 0.52 | 0.52 | 0.53 | 0.50 | 0.48 | 0.56 | 0.53 | 0.51 | 0.56 | 0.51 | X26 | 98011 | 115985 | 83828 | 99368 | 121230 | 82054 | 54815 | 48405 | 59043 | 90355 | 103675 | 79930 | 41390 | | | X27 | 12563 | 5853 | 5085 | 7874 | 11620 | 3827 | 1384 | 2873 | 2208 | 5426 | 2762 | 3618 | 1019 |
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