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| 中国生态足迹的多尺度变化及驱动因素分析 | |
| 引用本文： | 张学勤,陈成忠,林振山.中国生态足迹的多尺度变化及驱动因素分析[J].资源科学,2010,32(10):2003-2009. |
| 作者姓名： | 张学勤 陈成忠 林振山 |
| 作者单位： | 1. 临沂师范学院商学院,临沂,276000 2. 湖北师范学院地理科学系,黄石,435002 3. 南京师范大学地理科学学院,南京,210046 |
| 基金项目： | 湖北省自然科学基金项目(编号:2009CDB249);临沂市重大科技创新项目(编号:080101003);临沂师范学院博士启动基金资助项目(编号:BS07021)。 |
| 摘 要： | 在基于生态足迹模型计算1953年-2007年中国人均生态足迹(Ecological Footprint,EF)数据基础上,采用经验模态分解(Empirical Mode Decomposition,EMD)方法研究发现,1953年-2007年中国人均EF存在明显的4.3a、10.8a两个波动周期和一个递增趋势。选取与中国人均EF变化高度相关的产业结构、能源消费、发电量、居民消费、城市化水平等7个指标,不同时间尺度下的驱动因素逐步回归分析发现,人均GDP、第二产业产值、重工业、原油消费、发电量、居民消费、城市化率7个因素是驱动其不同周期性变化和持续增长的主要因素。稳定经济增长,优化产业机构,降低原油消费,提高天然气、水电及可再生能源消费比重,提高电力利用效率,适当控制城镇化等是中国减少生态足迹、降低人类环境影响的有效措施。 |
| 关 键 词： | 生态足迹 经验模态分解 逐步回归分析 中国 |
A Study on Driving Forces of Per Capital Ecological Footprint atMultiple Timescales in China during the Period 1953-2007 |
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| ZHANG Xueqin,CHEN Chengzhong and LIN Zhenshan.A Study on Driving Forces of Per Capital Ecological Footprint atMultiple Timescales in China during the Period 1953-2007[J].Resources Science,2010,32(10):2003-2009. | |
| Authors: | ZHANG Xueqin CHEN Chengzhong and LIN Zhenshan |
| Institution: | School of International Business, Linyi Normal University, Linyi 276000, China;Department of Geographical Science, Hubei Normal University, Huangshi 435002, China;School of Geographical Science, Nanjing Normal University, Nanjing 210046, China |
| Abstract: | As an environmental impact assessment method, the ecological footprint (EF) model hasreceived increasingly more attention and positive response in the scientific community. There arevarious EF studies in recent years on long time series of the influence on ecosystem sustainability.The variation in long time EF series is complex as it is determined by a multitude of driving forcessuch as population, consumption, land use, climate, technology, and management. It would,therefore, be greatly helpful to examine the relationship between EF and its driving forces. Theempirical mode decomposition (EMD) method has been applied to nonlinear scientific fieldssuccessfully, such as signal processing, image processing, seismology, atmosphere science, andecological economics. An optimization regress model could be developed with the stepwiseregression method. However, little work has been down on the driving forces of long time EFseries by combining the EMD with stepwise regression methods. In this work, per capital EF inChina during the period 1953-2007 was calculated based on the EF model. Its fluctuant cycles weresubsequently decomposed with the EMD method. In addition, driving factors of per capita EF inChina were explored at multiple timescales based on the stepwise regression method. Resultsshowed that: 1) over the last 55 years, the obvious fluctuation cycles of per capita EF in China were4.3 years, 10.8 years, showing an consistently increasing trend; 2) an around 4.3-year period ofpower generation, per capita GDP, crude oil consumption, secondary industry, heavy industry, etc.were generally consistent with per capita EF in China; 3) an around 10.8-year period ofurbanization, crude oil consumption, heavy industry, etc. were generally consistent with per capitaEF in China; and 4) consistently increasing trends of urbanization, crude oil consumption, etc. weregenerally consistent with per capita EF in China. The changes in these cycles and consistentlyincreasing trend of EF per capita in China may be driven by economic growth, industry structure,energy consumption, and urbanization. These findings suggest that more emphasis be placed onmaintaining proper economic growth, optimizing industrial structure and the composition of totalenergy consumption, properly controlling town construction in policy-making. Correspondingpolicy recommendations are given. This study would provide feasible approaches to mitigatinghuman impacts on the environment, providing reference to sustainable development, and enrichingthe assessment index system of sustainable development based on the EF analysis. In themeantime, it can also provide new means to analyze driving forces of human impacts on theenvironment and environmental impact assessment. |
| Keywords: | Ecological footprint (EF) Empirical mode decomposition (EMD) Stepwise regression analysis China |
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