地理科学 ›› 2016, Vol. 36 ›› Issue (4): 491-501.doi: 10.13249/j.cnki.sgs.2016.04.002
收稿日期:
2015-02-07
修回日期:
2015-08-20
出版日期:
2016-07-21
发布日期:
2016-07-21
作者简介:
作者简介:杨文越(1988-),男,广东韶关人,博士研究生,研究方向为城市交通地理与土地利用。E-mail:
基金资助:
Wenyue Yang1, Tao Li2, Xiaoshu Cao1,3()
Received:
2015-02-07
Revised:
2015-08-20
Online:
2016-07-21
Published:
2016-07-21
Supported by:
摘要:
通过构建交通CO2排放模型对2000~2012年中国30个省(市)的交通CO2排放时空演变特征进行了分析。并采取“由大到小”逐步回归的建模方式,在传统的固定效应模型(面板数据模型)基础上引入时间固定效应,构建了双向固定效应模型对中国交通CO2排放的社会经济、城市形态、交通发展等方面的影响因素进行研究。结果表明:2000~2012年期间,中国交通CO2排放总量和人均交通CO2排放量分别以9.29%和8.69%的年均增速增长,前者的区域差异呈先增后减趋势,后者的区域差异则首先呈周期性波动,而后一直保持减少趋势。人均GDP和城镇居民家庭人均可支配收入对人均交通CO2排放具有显著的正向效应,表明社会经济发展和居民收入水平提高是交通CO2排放增长的主要驱动因素。城市人口密度对交通CO2排放亦具有显著的正向效应,这意味着未来中国应加强对城市人口密度的规划控制,以避免因人口过度集聚而额外增加产生交通CO2排放。公共交通发展水平对交通CO2排放增长具有显著的负向效应,但小汽车拥有率对交通CO2排放的影响并不显著。
中图分类号:
杨文越, 李涛, 曹小曙. 中国交通CO2排放时空格局演变及其影响因素——基于2000~2012年30个省(市)面板数据的分析[J]. 地理科学, 2016, 36(4): 491-501.
Wenyue Yang, Tao Li, Xiaoshu Cao. The Evolution of Spatial-temporal Characteristics and Influence Factors of CO2 Emissions from Transport in China: A Panel Data Analysis of 30 Provinces in China from 2000 to 2012[J]. SCIENTIA GEOGRAPHICA SINICA, 2016, 36(4): 491-501.
表1
化石燃料燃烧的热值和CO2排放因子"
燃料类型 | 热值(kJ/kg、 kJ/m3) | 单位热值的CO2 排放(kg/TJ) | CO2排放因子 (kg/kg、kg/ m3) | 燃料类型 | 热值(kJ/kg、 kJ/m3) | 单位热值的CO2 排放(kg/TJ) | CO2排放因子 (kg/kg、kg/ m3) |
---|---|---|---|---|---|---|---|
原煤 | 20908 | 96690 | 2.022 | 煤油 | 43070 | 71900 | 3.097 |
洗精煤/其他洗煤 | 26344 | 93170 | 2.454 | 柴油 | 42652 | 74100 | 3.161 |
型煤 | 20700 | 97500 | 2.018 | 燃料油 | 41816 | 77400 | 3.237 |
焦炭 | 28435 | 107000 | 3.043 | 液化石油气 | 50179 | 63100 | 3.166 |
原油 | 41816 | 73300 | 3.065 | 其他石油制品 | 40200 | 73300 | 2.947 |
汽油 | 43070 | 69300 | 2.985 | 天然气 | 38931 | 56100 | 2.184 |
表2
变量描述性统计"
属性 | 变量 | 变量描述 | 平均值 | 标准差 | 最小值 | 最大值 | 观测样本个数 |
---|---|---|---|---|---|---|---|
因变量 | PTC | 人均交通CO2排放(kg) | 417.50 | 338.55 | 62.42 | 2015 | 390 |
社会经济因素 | PGDP | 人均GDP(元) | 17288.95 | 12475.34 | 2742.07 | 69639.91 | 390 |
PIH | 城镇居民家庭人均可支配收入(元) | 12822.63 | 6471.67 | 4724.11 | 40188.30 | 390 | |
TIP | 第三产业占GDP比重(%) | 40.45 | 0.07 | 28.30 | 76.46 | 390 | |
UL | 城市化水平(%) | 35.29 | 0.16 | 14.16 | 89.76 | 390 | |
城市形态因素 | UPD | 城市人口密度(人/km2) | 839.17 | 677.10 | 101.76 | 3306 | 390 |
ACS | 建成区平均规模(km2) | 137.73 | 274.99 | 15.95 | 1349.8 | 390 | |
交通发展水平 | URP | 城市道路比例(%) | 11.17 | 3.28 | 3.64 | 28.97 | 390 |
URD | 城市道路密度(km/ km2) | 6.96 | 2.35 | 2.57 | 18.14 | 390 | |
HWD | 公路密度(km/ km2) | 0.61 | 0.43 | 0.03 | 2.44 | 390 | |
PPT | 城市每万人拥有公共交通车辆数(标台) | 9.83 | 3.88 | 3.00 | 26.4 | 390 | |
PPV | 每万人均拥有私人汽车(辆) | 275.60 | 292.48 | 13.14 | 1960.13 | 390 |
表3
变量的单位根检验"
变量 | 单位根检验 | 变量 | 单位根检验 | ||||||
---|---|---|---|---|---|---|---|---|---|
LLC | ADF-Fisher | LLC | ADF-Fisher | ||||||
校正t统计量 | p值 | 逆卡方值 | p值 | 校正t统计量 | p值 | 逆卡方值 | p值 | ||
LnPTC | -5.30 | 0.0000 | 123.68 | 0.0000 | LnACS | -13.69 | 0.0000 | 140.59 | 0.0000 |
LnPGDP | -4.68 | 0.0000 | 139.97 | 0.0000 | LnURP | -13.45 | 0.0000 | 150.01 | 0.0000 |
LnPIH | -11.12 | 0.0000 | 149.57 | 0.0000 | LnURD | -3.14 | 0.0008 | 199.70 | 0.0000 |
LnTIP | -5.82 | 0.0000 | 123.09 | 0.0000 | LnHWD | -3.35 | 0.0004 | 97.03 | 0.0018 |
LnUL | -10.78 | 0.0000 | 118.39 | 0.0000 | LnPPT | -19.25 | 0.0000 | 146.65 | 0.0000 |
LnUPD | -9.87 | 0.0000 | 227.08 | 0.0000 | LnPPV | -15.31 | 0.0000 | 170.31 | 0.0000 |
表4
双向固定效应模型估计结果"
变量 | 参数估计结果 | ||||
---|---|---|---|---|---|
模型1 | 模型2 | 模型3 | 模型4 | 模型5 | |
lnPGDP | 1.12*** | 1.11*** | 1.13*** | 1.16*** | 1.18*** |
lnPIH | 0.49* | 0.50* | 0.49* | 0.47* | 0.51** |
lnTIP | 0.04 | - | - | - | - |
lnUL | 0.20 | 0.20 | 0.21 | 0.21 | 0.22* |
lnUPD | 0.23*** | 0.23*** | 0.23*** | 0.23*** | 0.22*** |
lnACS | 0.07 | 0.07 | 0.07 | 0.07 | 0.07 |
lnURP | 0.03 | 0.03 | - | - | - |
lnURD | 0.15 | 0.15 | 0.17* | 0.17* | 0.17* |
lnHWD | 0.03 | 0.03 | 0.03 | - | - |
lnPPT | -0.15* | -0.15*** | -0.15*** | -0.14** | -0.15*** |
lnPPV | 0.04 | 0.04 | 0.04 | 0.04 | - |
2001年 | -0.03 | -0.03 | -0.02 | -0.02 | -0.02 |
2002年 | -0.19*** | -0.18*** | -0.18*** | -0.18*** | -0.18*** |
2003年 | -0.20** | -0.19** | -0.19** | -0.19** | -0.19** |
2004年 | -0.30*** | -0.29*** | -0.29*** | -0.29*** | -0.29*** |
2005年 | -0.26** | -0.25** | -0.25** | -0.25** | -0.25** |
2006年 | -0.38** | -0.38** | -0.38** | -0.36** | -0.36** |
2007年 | -0.48*** | -0.47*** | -0.47*** | -0.46*** | -0.46** |
2008年 | -0.57*** | -0.57*** | -0.57*** | -0.55*** | -0.55*** |
2009年 | -0.70*** | -0.69*** | -0.69*** | -0.68*** | -0.67*** |
2010年 | -0.82*** | -0.81*** | -0.82*** | -0.80*** | -0.80*** |
2011年 | -0.92*** | -0.91*** | -0.91*** | -0.90*** | -0.89*** |
2012年 | -1.03*** | -1.02*** | -1.02*** | -1.01*** | -1.01*** |
常数项 | -10.62*** | -10.58*** | -10.80* | -10.87*** | -11.31*** |
R-sq:within | 0.883 | 0.882 | 0.882 | 0.882 | 0.882 |
corr(u_i,Xb) | -0.743 | -0.737 | -0.742 | -0.743 | -0.750 |
F值(回归方程显著性检验) | 109.99*** | 115.31*** | 121.09*** | 127.41*** | 134.22*** |
F值(个体效应显著性检验) | 28.30*** | 31.78*** | 32.01*** | 33.10*** | 35.12*** |
AIC | -287.844 | -289.764 | -291.585 | -293.289 | -294.542 |
BIC | -192.656 | -198.543 | -204.330 | -210.000 | -215.219 |
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