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| 基于数据包络分析法的秸秆能源化利用的生态效率评价 |
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郭小青1,2,于晓娜1,2,朱万斌1,2,王洪亮1,2*
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| (1.中国农业大学 农学院, 北京 100193;2.国家能源非粮生物质原料研发中心, 北京 100193) |
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| 摘要: |
| 为定量评价我国主要作物秸秆资源能源化利用对生态环境的影响，本研究借鉴数据包络分析方法构建关于秸秆能源化利用投入产出比的生态效率评价模型，分析2011—2018年我国31个省(市、自治区)的秸秆资源能源化利用的生态效率值。结果表明:江苏省、福建省、海南省、河南省、广西省、四川省、吉林省和黑龙江省8个省生态效率值均为1，即秸秆能源化利用对这8省的生态环境效果相对较好。我国部分地区秸秆能源化利用的生态效率低下的主要原因在于多数投入资源冗余严重和主要产品产量偏低。建议重视区域发展状况，以及提升能源化利用工艺发展水平，在降低资源投入的同时达到提升产量的目的，以提高我国秸秆能源化利用的生态效率。 |
| 关键词: 秸秆 能源化利用 生态效率 数据包络分析 冗余率 |
| DOI：10.11841/j.issn.1007-4333.2021.03.01 |
| 投稿时间：2020-03-26 |
| 基金项目:国家重点研发计划(2018YFB1501500) |
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| Eco-efficiency evaluation of the crop residue energy utilization based on data envelopment analysis |
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GUO Xiaoqing1,2,YU Xiaona1,2,ZHU Wanbin1,2,WANG Hongliang1,2*
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| (1.College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China;2.National Energy R & D Center for Non-Food Biomass, Beijing 100193, China) |
| Abstract: |
| To quantitively evaluate the effect of crop residue energy utilization on the ecological environment, this study analyzes and compares the eco-efficiency of crop residue energy utilization in 31 provinces and cities in China from 2011 to 2018 by using the data envelopment analysis(DEA)method. The results show that the eco-efficiency values of crop residue energy utilization in Jiangsu, Fujian, Hainan, Guangxi, Sichuan, Jilin and Heilongjiang provinces are equal to 1, indicating that the energy utilization of crop residue in these 8 regions has a positive effect on the ecological environment. In addition, reasons for the low ecological efficiency of straw energy utilization in these provinces are identified, which are due to the high redundancy of input indicators and the low product yield. High ecological efficiency of straw energy utilization in China could be achieved by improving both the level of regional development and the level of energy-using processes so as to fulfill the goal of increasing biomass production while reducing resource input. |
| Key words: crop residue energy utilization eco-efficiency DEA analysis redundancy rate |
