《水土保持研究》[ISSN:1005-3409/CN:61-1272/P]
卷:
23
期数:
2016年04期
页码:
154-160
栏目:
出版日期:
2016-08-28
- Title:
-
Research on Carbon Footprint of Ecomigration Family and Its Influence Factors in NingXia
- 作者:
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邓慧丽1, 苗红1, 孔云霄1, 马金涛1, 薛晨浩2
-
1. 宁夏大学 资源环境学院, 银川 750021;
2. 西北民族大学 管理学院, 兰州 730000
- Author(s):
-
DENG Huili1, MIAO Hong1, KONG Yunxiao1, MA Jintao1, XUE Chenhao2
-
1. College of Resources and Environment, Ningxia University, Yinchuan 750021, China;
2. College of Management, Northwest University For Nationalities, Lanzhou 730000, China
-
- 关键词:
-
- Keywords:
-
- 分类号:
-
X24
- 摘要:
-
基于生命周期评估方法,以农户调研数据为基础,从能源消耗、房屋建设、家庭洗涤剂使用、交通运输、畜禽肉类饮食消费、衣着服饰6方面对宁夏不同安置方式下生态移民家庭碳足迹进行了测算,采用方差分析和相关分析对移民家庭碳足迹特点及影响因素进行了研究。结果表明:(1)移民迁移前碳足迹总量为190 657.46 kg CO2,迁移后碳足迹总量为153 132.47 kg CO2,不同安置方式下移民搬迁后的碳足迹总量均明显小于移民之前。(2)适度集中就近安置移民人均碳足迹为1.46×103 kg CO2,此类安置方式下的人均碳足迹最大。(3)移民家庭消费碳足迹的主要来源是能源消耗,其次为房屋建设和交通运输,家庭洗涤剂、畜禽肉类饮食消费、衣着服饰类的碳足迹所占比例较小。(4)人口数量、收入水平、消费水平、非农化程度是其重要影响因子。
- Abstract:
-
Based on household survey data, we calculated the carbon footprint of ecological migration family under different resettlement in Ningxia from energy consumption, housing construction, household detergents, transportation, consumption of poultry meat diet, dress and other aspects using the method of life cycle assessment. We analyzed the characteristics and influence factors of carbon footprint of immigrant family by using variance analysis and correlation analysis. Results show that:(1) the migration families’ total carbon footprint is 153 132.47 kg CO2 after migration and now it is 190 657.46 kg CO2, different resettlement modes after the relocation of the total carbon footprint are much less than before immigration; (2) per capita carbon footprint is 1.46×103 kg CO2 of moderately centralized resettlement which is the largest; (3) the main source of the carbon footprint of immigrant families results from energy consumption followed by housing construction and transportation. Family detergents, meat food consumption, and clothing account for the less proportion; (4) the important influence factors are population, income level, consumption level and the degree of nonagriculture.
更新日期/Last Update:
1900-01-01