基于STIRPAT模型的甘肃省交通碳排放测算及影响因素分析

doi:10.7522/j.issn.1000-0240.2015.0092

冰川冻土 ›› 2015, Vol. 37 ›› Issue (3): 826-834.doi: 10.7522/j.issn.1000-0240.2015.0092

• 生态经济与可持续发展 • 上一篇下一篇

基于STIRPAT模型的甘肃省交通碳排放测算及影响因素分析

武翠芳¹, 熊金辉², 吴万才³, 高文齐², 柳雪斌²

1. 兰州财经大学农林经济管理学院, 甘肃兰州 730080;
2. 兰州财经大学经济学院, 甘肃兰州 730080;
3. 甘肃广播电视大学, 甘肃兰州 730030

收稿日期:2015-01-16 修回日期:2015-06-10 出版日期:2015-06-25 发布日期:2015-09-29
通讯作者: 熊金辉, E-mail: huijin0115@sina.com. E-mail:huijin0115@sina.com
作者简介:武翠芳(1975-), 女, 甘肃靖远人, 副教授, 2009年于中国科学院寒区旱区环境与工程研究所获得博士学位, 现主要从事生态经济方面研究. E-mail: wucf@lzcc.edu.cn
基金资助:
国家自然科学基金青年科学基金项目(41401645);国家社科青年基金项目(10CGL050)资助

Calculation and effect factor analysis of transport carbon emission in Gansu Province based on STIRPAT Model

WU Cuifang¹, XIONG Jinhui², WU Wancai³, GAO Wenqi², LIU Xuebin²

1. School of Agriculture & Forestry Economics and Management, Lanzhou University of Finance and Economics, Lanzhou 730080, China;
2. School of Economics, Lanzhou University of Finance and Economics, Lanzhou 730080, China;
3. Gansu Radio & TV University, Lanzhou 730030, China

Received:2015-01-16 Revised:2015-06-10 Online:2015-06-25 Published:2015-09-29

摘要/Abstract

摘要： 依据IPCC清单指南的数据, 采用"自上而下"的碳排放计算方法, 对2000-2013年甘肃省交通碳排放进行测算, 对交通碳排放总量、人均量、交通能源碳排放结构及碳排放强度进行动态分析. 基于STIRPAT模型, 运用岭回归统计方法对甘肃省交通碳排放影响因素进行定量分析. 结果表明: 甘肃省交通碳排放总量和人均碳排放量都呈逐年上升的趋势; 煤炭、汽油、柴油、电力四种能源消费的碳排放量占交通碳排放量的绝大部分; 交通碳排放强度呈下降趋势; 城镇化水平、客运周转量、货运周转量、人均GDP每增长1%, 导致交通碳排放分别增长0.221%、0.137%、0.174%和0.125%. 建设低碳交通体系将成为甘肃省交通部门减碳的有效途径.

关键词: 交通, 碳排放, STIRPAT模型, 甘肃

Abstract: Based on the data of IPCC guideline, in this paper, transport carbon emissions in Gansu Province from 2000 to 2013 were calculated using "from top to bottom" method, and total and per-capita transport carbon emissions, structure and intensity of carbon emissions were analyzed. Factors influencing transport carbon emissions in the province were quantitatively analyzed by using ridge regression method based on the STIRPAT Model. The results indicate that both total and per-capita transport carbon emissions are increasing year by year in Gansu Province. Carbon emissions of coal, gasoline, diesel, electricity consumptions accounted for the majority of transport carbon emission. However, the intensity of transport carbon emission is going down. When the level of urbanization, passenger turnover, freight turnover and per-capita GDP increases by 1%, the transport carbon emission will increase by 0.221%, 0.137%, 0.174%, and 0.125%, respectively. Constructing a low-carbon transportation system would become an effective way to reduce carbon emission in the province.

Key words: transport, carbon emissions, STIRPAT Model, Gansu Province

中图分类号:

F062.2

武翠芳, 熊金辉, 吴万才, 高文齐, 柳雪斌. 基于STIRPAT模型的甘肃省交通碳排放测算及影响因素分析[J]. 冰川冻土, 2015, 37(3): 826-834.

WU Cuifang, XIONG Jinhui, WU Wancai, GAO Wenqi, LIU Xuebin. Calculation and effect factor analysis of transport carbon emission in Gansu Province based on STIRPAT Model[J]. JOURNAL OF GLACIOLOGY AND GEOCRYOLOGY, 2015, 37(3): 826-834.

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基于STIRPAT模型的甘肃省交通碳排放测算及影响因素分析

Calculation and effect factor analysis of transport carbon emission in Gansu Province based on STIRPAT Model

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