中文摘要：

能源足迹测度分析是揭示能源消费对区域环境压力及可持续发展的重要方法.基于能源足迹的碳吸收计量模型、能源足迹强度与生态压力分析方法,利用统计年鉴中能源消费数据,对2000—2010年池州能源足迹及生态压力与强度进行了动态测度,运用灰色GM（1,1）预测模型,对2015年、2020年能源足迹进行了预测,并借鉴STIRPAT模型对能源足迹驱动因子进行了分析.结果表明：池州人均能源足迹由2000年的0.1173ghm2（全球公顷,下同）上升至2010年的0.8993ghm2,呈波动上升趋势.2000—2003年,人均能源足迹的供给大于需求,EPIEF〈1,2004年开始人均能源足迹的需求已超过供给,供需状态严重失衡,EPIEF〉1,2010年,EPIEF比值达2.4,能源足迹为森林对能源足迹承载力的2.41倍.煤炭足迹为能源足迹的主要贡献者,平均贡献率达90.21%.能源足迹强度整体呈倒＂U＂型趋势.人口规模、人均GDP、第二产业在经济中所占比例、单位工业增加值能耗与能源足迹呈正相关关系,边际弹性系数分别为0.5698、0.590、1.468、0.144.可为池州市政府动态了解能源消费对环境形成的压力,准确把握可持续发展状况,进而为制定相应的发展策略提供科学依据,也可为微观尺度区域能源足迹研究提供借鉴.

英文摘要：

Ecological footprint （EF） method is a new prevailing approach to evaluate the sustainability of regional development. The time series of ecological footprint （EF） from 2000 to 2010 was calculated by using the statistical data of resource and energy consumption in Chizhou. On this basis, this paper forecasted the EF in the year 2015 and 2020. The driving factors of ecological footprint were analyzed using STIRPAT model. The results showed that EF per capita increased from 0.1173 ghm2 to 0.8993 ghm2 within the past ten years. The ecological pressure intensity of energy footprint （EPIEF） tends to increase, which means pressure of energy consumption on natural ecological system is enhancing. Among the components of EF, the percentage of coal footprint has increased to 90.21%. The EF is positively correlated with population scale, GDP per capita, the secondary industrial proportion and industrial added value of unit energy consumption. Their corresponding coefficients of effect on EF are 0.5698, 0.590, 1.468 and 0.144, respectively. Energy footprint intensity trend exhibits a reverse U-shape pattern. This paper may help Chizhou government to accurately estimate sustainable development capability, and provide a scientific basis which would support the coordinated development between the environment and economy in other areas in similar scales.