地理科学 ›› 2020, Vol. 40 ›› Issue (12): 1949-1957.doi: 10.13249/j.cnki.sgs.2020.12.001
• • 下一篇
收稿日期:
2019-11-04
修回日期:
2020-03-02
出版日期:
2020-12-25
发布日期:
2021-01-09
通讯作者:
姚士谋
E-mail:zguo@niglas.ac.cn;smyao@niglas.ac.cn
作者简介:
郭政(1993−),男,安徽蚌埠人,博士研究生,主要从事城市可持续发展研究。E-mail:
Guo Zheng1,2(), Yao Shimou1,*(
), Wu Changyan3
Received:
2019-11-04
Revised:
2020-03-02
Online:
2020-12-25
Published:
2021-01-09
Contact:
Yao Shimou
E-mail:zguo@niglas.ac.cn;smyao@niglas.ac.cn
摘要:
采用空间分析和空间杜宾模型等方法,研究1999—2017年中国工业烟粉尘排放时空演化特征及其影响因素。结果表明:① 中国工业烟粉尘排放空间分布差异明显,其排放的基尼系数和污染物分布指数均呈现下降态势,空间集中程度有所缓和。② 中国工业烟粉尘排放空间分布呈东北?西南走向,其排放中心不断由东南向西北方向迁移。③ 中国工业烟粉尘排放存在空间相关性和空间溢出效应,其冷热点区空间分布发生显著变化。④ 能源消耗、第二产业比重、人口密度和经济发展水平的提升将会增加工业烟粉尘排放,而外资水平、治理技术水平和环境规制力度的提升则有利于减少工业烟粉尘排放。
中图分类号:
郭政, 姚士谋, 吴常艳. 中国工业烟粉尘排放时空演化及其影响因素[J]. 地理科学, 2020, 40(12): 1949-1957.
Guo Zheng, Yao Shimou, Wu Changyan. Spatial-temporal Pattern of Industrial Soot and Dust Emissions in China and Its Influencing Factors[J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(12): 1949-1957.
Table 1
The subarea and emissions proportion of industrial soot and dust emissions in China from 1999 to 2017 /%"
类型区 | 1999年 | 2005年 | 2011年 | 2017年 | |||||||
排放量比例 | 面积比例 | 排放量比例 | 面积比例 | 排放量比例 | 面积比例 | 排放量比例 | 面积比例 | ||||
低排放区 | 3.465 | 21.721 | 3.081 | 21.721 | 1.576 | 13.505 | 3.218 | 14.362 | |||
较低排放区 | 3.956 | 22.883 | 12.636 | 31.925 | 12.772 | 20.897 | 11.234 | 17.798 | |||
中等排放区 | 13.076 | 25.898 | 31.914 | 17.426 | 21.233 | 15.334 | 27.521 | 23.973 | |||
较高排放区 | 42.108 | 17.558 | 15.427 | 16.384 | 21.257 | 26.433 | 36.946 | 40.310 | |||
高排放区 | 37.396 | 11.940 | 36.943 | 12.544 | 43.163 | 23.831 | 21.081 | 3.557 |
Table 2
The standard deviational elliptic parameter of industrial soot and dust emissions in China from 1999 to 2017"
年份 | 中心坐标 | 长半轴/km | 短半轴/km | 方位角/(°) | 面积/(104 km2) | 扁率 |
1999 | 112.975°E,33.555°N | 1059.360 | 756.080 | 31.060 | 251.614 | 0.286 |
2005 | 112.746°E,33.946°N | 1067.651 | 786.473 | 25.095 | 263.778 | 0.263 |
2011 | 112.593°E,34.628°N | 1083.912 | 974.011 | 26.436 | 331.654 | 0.101 |
2017 | 113.163°E,35.935°N | 1093.657 | 969.848 | 47.121 | 333.206 | 0.113 |
Table 4
Estimation results of SDM model"
变量 | 系数 | T统计量 | 变量 | 滞后项系数 | T统计量 |
注:***、**、*分别表示通过1%,5%和10%水平下的显著性检验;W×LnX表示各因子的空间溢出效应;未含港澳台数据。 | |||||
| 0.343*** | 4.277 | W× | 0.241*** | 2.994 |
| 0.352 | 1.093 | W× | 0.319 | 1.006 |
| ?0.059 | ?1.065 | W× | 0.062 | 1.105 |
| ?0.094* | ?1.927 | W× | ?0.034 | ?0.678 |
| 0.385 | 0.732 | W× | 0.199 | 0.380 |
| 0.515* | 1.740 | W× | ?0.936*** | ?3.120 |
| ?0.017 | ?0.205 | W× | ?0.212*** | ?2.592 |
R2 | 0.498 | ρ | 0.253*** | Log-Likelihood | ?68.238 |
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