资源科学 ›› 2018, Vol. 40 ›› Issue (2): 262-272.doi: 10.18402/resci.2018.02.04
刘清春1,2(), 张莹莹1, 肖燕3, 袁玉娟2, 夏海斌4,5
收稿日期:
2017-07-10
修回日期:
2017-11-10
出版日期:
2018-02-20
发布日期:
2018-02-11
作者简介:
作者简介:刘清春,女,山东诸城人,博士,副教授,研究领域为城市地理和区域经济。E-mail:
基金资助:
Qingchun LIU1,2(), Yingying ZHANG1, Yan XIAO3, Yujuan YUAN2, Haibin XIA4,5
Received:
2017-07-10
Revised:
2017-11-10
Online:
2018-02-20
Published:
2018-02-11
摘要:
私家车出行方式对城市交通碳排放的影响巨大,如何促使居民出行行为的转变是城市实现绿色交通和低碳发展的关键问题。基于济南市主城区居民日常出行的调查数据,本文分析了私家车日常出行碳排放的基本特征,并应用Heckman两步估计法计量模型,研究了私家车碳排放的影响因素,结果发现:①私家车日常出行年碳排放量的平均值为2.22t,空间分布呈现中心低、外围高的差异化格局,个体分布则符合60/20的量化分布;②与社会经济因素相比,建成环境因素对私家车碳排放的影响更为显著,公共交通可达性水平的提高和职住距离的缩短虽然有助于降低私家车出行概率,但对私家车碳排放的减少并无显著影响,而提高居住地人口密度、完善商服设施供给、促进周边土地利用的多元化则可有效降低长距离的出行需求,减少碳排放量。
刘清春, 张莹莹, 肖燕, 袁玉娟, 夏海斌. 济南市主城区私家车日常出行碳排放特征及影响因素[J]. 资源科学, 2018, 40(2): 262-272.
Qingchun LIU, Yingying ZHANG, Yan XIAO, Yujuan YUAN, Haibin XIA. Characteristics and determinants of carbon emissions from daily private cars travel in central area of Jinan[J]. Resources Science, 2018, 40(2): 262-272.
表1
调查问卷涉及主要变量及统计分析"
变量 | 变量类型 | 描述 | 均值 |
---|---|---|---|
出行特征 | |||
出行方式 | 虚拟变量 | 1=私家车(43.3%);0=其他(56.7%) | |
私家车出行距离/km | 连续变量 | 一周内私家车的日常出行公里数 | 198.000 |
个人及家庭社会经济属性 | |||
年龄/岁 | 等级变量 | 1=20~30岁(15.3%);2=31~40岁(35.6%);3=41~50岁(45.5%);4=51~60岁(3.4%);5=60岁以上(0.2%) | 2.382 |
收入/(元/月) | 等级变量 | 1=2 000元以下(7.4%);2=2 000~3 000元(24.1%);3=3 000~5 000元(34.6%);4=5 000元以上(33.9%) | 2.892 |
受教育水平 | 等级变量 | 1=初中及以下(6.2%);2=高中(11.6%);3=大专(26.5%);4=本科及以上(55.7%) | 3.324 |
家庭规模/人 | 连续变量 | 家庭人口数量 | 3.434 |
私家车拥有量/辆 | 连续变量 | 私家车拥有数量 | 1.880 |
城市建成环境变量 | |||
居住区位/km | 连续变量 | 居住点到泉城广场的距离 | 5.852 |
人口密度/(人/km2) | 连续变量 | 居民居住地所属街道人口除以街道面积 | 13 059.000 |
公交站牌距离/m | 等级变量 | 1=50m以内(19.7%);2=50~100m(28.1%);3=100m以上(52.2%) | 2.321 |
转车次数 | 等级变量 | 1=不需要转车(48.1%);2=转车一次(30.5%);3=转车两次及以上(21.4%) | 1.737 |
商服设施供给/km | 连续变量 | 居住点距其5km范围内最近大型超市的距离 | 1.537 |
土地利用混合度 | 连续变量 | 居住区街道不同土地利用的混合程度 | 0.723 |
停车便利性 | 等级变量 | 1=非常不方便(27.6%);2=不方便(11.5%);3=一般(26.2%);4=方便(14.0%);5=非常方便(20.7%) | 2.882 |
职住距离/km | 连续变量 | 居住点到工作单位的距离 | 8.211 |
表2
基于Pobit模型研究区私家车出行方式影响因素的边际效应估计结果"
变量 | (1) | (2) | (3) | (4) |
---|---|---|---|---|
收入 | 0.035*** | - | 0.046** | 0.048*** |
(0.010) | - | (0.020) | (0.016) | |
年龄 | 0.009 | - | 0.012 | - |
(0.019) | - | (0.031) | - | |
教育水平 | -0.001 | - | -0.004 | - |
(0.017) | - | (0.029) | - | |
家庭规模 | -0.052*** | - | -0.093*** | -0.092*** |
(0.015) | - | (0.022) | (0.024) | |
私家车拥有量 | 0.398*** | - | 0.317*** | 0.323*** |
(0.021) | - | (0.047) | (0.044) | |
居住区位 | - | 0.009 | -0.021 | - |
- | (0.045) | (0.043) | - | |
人口密度 | - | 0.005 | 0.001 | - |
- | (0.019) | (0.018) | - | |
转车次数 | - | -0.018 | -0.003 | - |
- | (0.030) | (0.029) | - | |
公交站牌距离 | - | 0.052* | 0.035 | - |
- | (0.027) | (0.025) | - | |
商服设施供给 | - | 0.020 | 0.052* | 0.060** |
- | (0.031) | (0.030) | (0.028) | |
土地利用混合度 | - | -0.041 | -0.039 | |
- | (0.169) | (0.162) | ||
停车便利性 | - | 0.0030 | 0.000 1 | |
- | (0.014) | (0.014) | ||
职住距离 | - | 0.115*** | 0.097*** | 0.102*** |
- | (0.027) | (0.026) | (0.023) | |
Pseudo R2 | 0.215 | 0.051 | 0.259 | 0.257 |
Log likelihood | -532.232 | -549.713 | -366.660 | -367.782 |
LR | 293.183 | 58.825 | 284.012 | 281.069 |
表3
研究区私家车碳排放影响因素的多元回归结果"
变量 | (1) | (2) | (3) | (4) |
---|---|---|---|---|
收入 | 0.008 | - | -0.041 | - |
(0.036) | - | (0.046) | - | |
年龄 | -0.052 | - | -0.019 | - |
(0.046) | - | (0.066) | - | |
教育水平 | 0.018 | - | 0.004 | - |
(0.052) | - | (0.074) | - | |
家庭规模 | -0.047 | - | 0.007 | - |
(0.038) | - | (0.061) | - | |
私家车拥有量 | 0.145* | - | 0.097 | - |
(0.077) | - | (0.105) | - | |
居住区位 | - | 0.045 | 0.051 | - |
- | (0.086) | (0.088) | - | |
人口密度 | - | -0.067* | -0.062* | -0.075** |
- | (0.035) | (0.037) | (0.035) | |
转车次数 | - | 0.003 | 0.001 | - |
- | (0.056) | (0.057) | - | |
公交站牌距离 | - | 0.036 | 0.026 | - |
- | (0.055) | (0.056) | - | |
商服设施供给 | - | 0.118* | 0.126* | 0.128** |
- | (0.064) | (0.069) | (0.063) | |
土地利用混合度 | - | -0.643* | -0.708** | -0.690** |
- | (0.330) | (0.339) | (0.325) | |
停车便利性 | - | 0.006 | 0.006 | - |
- | (0.029) | (0.030) | - | |
职住距离 | - | 0.008 | 0.011 | - |
- | (0.058) | (0.06) | - | |
常数项 | 7.442*** | 8.642*** | 8.564*** | 8.904*** |
(0.270) | (0.648) | (0.785) | (0.577) | |
R2 | 0.125 | 0.201 | 0.262 | 0.283 |
F | 10.528 | 22.725 | 25.321 | 32.513 |
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