广州市三个圈层社区居民通勤碳排放特征——以都府小区、南雅苑小区和丽江花园为例

doi:10.11821/dlyj201504013

摘要/Abstract

摘要：

低碳城市已成为应对全球气候变化和促进人与自然和谐相处的重要研究领域,但从微观层面探讨城市居民通勤碳排放特征和影响因素的研究较为缺乏。利用对广州市不同圈层社区的问卷调查数据,对其通勤碳排放进行测算,采用分等定级和洛伦兹曲线分析社区间、社区内、个体间的分异,并建立了基于多元回归的社区居民通勤碳排放的影响模型。结果显示：社区居民通勤碳排放较符合“60-20”规律（温室气体排放最多的20%的人排放了总量的60%）。中心区和边缘区的通勤碳排放不均等性更大;不同个人、家庭和通勤属性的通勤者的碳排放量存在较大差异;通勤距离、出行交通方式、每天的通勤往返次数、个人的工作月收入和所在街道的人口密度对家庭通勤碳排放有显著影响。

关键词: 碳排放, 通勤, 多元回归模型, 社区, 广州市

Abstract:

In recent years, as low-carbon city gradually has become a significant research field on studies on global climate change, the scholars at home and abroad have launched a series of research from various angles. However, there is little research discussing about urban commuting carbon emission characteristics and the influencing factors of carbon emissions at disaggregated level. The data used in this study came from a 2011-2012 survey of 291 residents from households in three typical communities from different parts of Guangzhou. The variables used in this study consist of four categories: demographics, auto ownership and use, built environment characteristics, and attitudes. In the survey, respondents were asked to report the number of automobiles in their households and their travel behavior. The survey also contained a list of demographic characteristics, including household size, household income, gender, age, education underground, having a driver's license, and occupation. Consistent with previous studies, we develop a coefficient method for calculating the amount of commuting carbon emissions. In this study, we adopt categorization and Lorenz curve to analyze the differentiation of commuting carbon emissions characteristics between different individuals, inner-community and trans-community. Specifically, we developed a multiple regression analysis method to analyze the impact of selected 16 variables on commuting carbon emissions. The results of commuting carbon emission characteristics analyses show that commuting carbon emission of residents in urban districts is lower than that of their counterparts in county-level cities. Dufu, Nanyayuan and Lijiang Garden communities are consistent with the rule of "60-20" proposed from the UK experience. Multiple regression analysis suggests that commuting distance, travel modes of residents, commuting frequency, income and population density of the sub-district have significant effects on CO₂ emissions. Finally, on the basis of the above findings, the paper puts forward some policy suggestions for reducing commuting carbon emissions.

Key words: CO2 emissions, commute, multiple regression model, community, Guangzhou city

黄晓燕, 刘夏琼, 曹小曙. 广州市三个圈层社区居民通勤碳排放特征——以都府小区、南雅苑小区和丽江花园为例[J]. 地理研究, 2015, 34(4): 751-761.

Xiaoyan HUANG, Xiaqiong LIU, Xiaoshu CAO. Commuting carbon emission characteristics of community residents of three spheres: A case study of three communities in Guangzhou city[J]. GEOGRAPHICAL RESEARCH, 2015, 34(4): 751-761.

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社区名称	城区/街道	区位特点	建立时间	常住人口（人）	特点	问卷样本数
都府小区	越秀区广卫街道	中心区	1993年	6059	以省政府、财政厅宿舍为主	76
南雅苑小区	天河区天河南街道	新城区	1989年	5278	天河建设区较早投入使用的普通住宅区	80
丽江花园	番禺区洛浦街道	边缘区	1992年	9928	以吸引中高收入人群为市场目标	135

交通方式	碳排放系数（g/人·km）	碳排放强度
私人小汽车	135.00	高
单位用车	21.50	中
公交车	16.90	中
电动自行车	10.00	低
地铁	9.10	低
自行车	0.00	零
步行	0.00	零

社区名称	平均值	标准差	上四分位数	中位数	下四分位数
都府小区	1699.49	2691.43	0.00	675.00	2126.25
南雅苑小区	1933.38	2398.54	83.57	658.60	3172.50
丽江花园	3545.77	5733.95	100.00	1755.00	3375.00
样本总体	2620.31	4402.69	66.00	1200.00	3240.00

变量分类	变量	解释变量	变量说明
个人属性	X₁	性别	1. 男;2. 女
	X₂	年龄
	X₃	文化程度	1. 文盲或半文盲;2. 小学;3. 初中;4. 高中;5. 大专、本科;6. 研究生以上
	X₄	职业	1. 国家机关、党群组织、企事业单位管理人员;2. 专业技术与文教科技人员;3. 事务人员;4. 私营业主;5. 商业、服务业人员
	X₅	工作月收入	1. 3000元以下;2. 3000~3999元;3. 4000~5999元;4. 6000~7999元;5. 8000~9999元;6. 1万~1.5万元;7. 1.6万~2万元;8. 2万元以上
家庭属性	X₆	通勤人口	家庭中有通勤需求的人数
	X₇	家庭构成	1. 单身户;2. 一对夫妇;3. 单亲家庭带小孩;4. 一对夫妇一个小孩;5. 一对夫妇两个小孩;6. 一对夫妇多个小孩;7. 三代人家庭;8. 其他
	X₈	家庭人均月收入	同个人属性中的“工作月收入”
	X₉	私人小汽车数量
通勤属性	X₁₀	通勤往返次数
	X₁₁	每周通勤天数
	X₁₂	出行交通方式	1. 步行;2. 公交车;3. 地铁;4. 自行车;5. 私人小汽车;6. 出租车;7. 单位用车;8. 电动自行车
	X₁₃	通勤距离	居住地距工作地的距离
社区属性	X₁₄	社区位置	1. 中心区;2. 新城区;3. 边缘区
	X₁₅	距市中心距离	距广州市政府的距离
	X₁₆	人口密度	六普数据,所在街道的人口密度

	相关系数R	决定系数R²	增加量（ΔR²）	F值	净F值（ΔR²）	B	Beta（β）
截距						2608.804
通勤距离	0.539	0.291	0.291	117.754	117.754	2701.662	0.614
出行交通方式	0.666	0.443	0.152	113.834	78.227	1561.122	0.354
通勤往返次数	0.686	0.470	0.027	84.282	14.462	732.229	0.166
工作月收入	0.703	0.494	0.024	69.450	13.692	919.484	0.209
人口密度	0.717	0.515	0.020	60.054	11.854	726.695	0.165