基于熵值法的低碳农业发展水平测度及影响因素研究——以甘肃省为例
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摘要
从低碳经济和绿色发展的角度出发,采用熵值法,从社会、经济、减排及生态方面选取20个指标,重新构建低碳农业发展综合评价体系,以甘肃省为研究样本,进行动态评价研究。研究结果显示,2005年—2014年甘肃省低碳农业发展水平总体上呈现不断上升趋势,但是农业经济效应和生态效应提升缓慢。通过对农业总产值与主要投入要素进行岭回归分析,发现农用塑料薄膜、农药施用量、农业机械总动力和农用柴油消耗量等是影响低碳农业发展的主要因素,但是农业化肥施用量已得到有效控制,研究表明所构建的评价指标体系是正确、可行的。在此基础上,提出了推进低碳农业发展的对策建议。
From the perspective of low-carbon economy and green development, this paper uses entropy method to select20 indicators from society, economy, emission reduction and ecology aspects, and reconstructs a comprehensive evaluation system for low-carbon agriculture development, taking Gansu Province as a Dynamic evaluation research sample. The research results show that the development level of low-carbon agriculture in Gansu Province in 2005-2014 is generally on the rise, but the agricultural economic effects and ecological effects are slow to improve. Through the ridge regression analysis of the total agricultural output value and the main input factors, it is found that agricultural plastic film,pesticide application amount, agricultural machinery total power and agricultural diesel consumption are the main factors affecting the development of low-carbon agriculture, but the application amount of agricultural chemical fertilizer has been obtained. Effective control. The research shows that the evaluation index system constructed is correct and feasible.On this basis, the countermeasures and suggestions for promoting the development of low-carbon agriculture were put forward.
From the perspective of low-carbon economy and green development, this paper uses entropy method to select20 indicators from society, economy, emission reduction and ecology aspects, and reconstructs a comprehensive evaluation system for low-carbon agriculture development, taking Gansu Province as a Dynamic evaluation research sample. The research results show that the development level of low-carbon agriculture in Gansu Province in 2005-2014 is generally on the rise, but the agricultural economic effects and ecological effects are slow to improve. Through the ridge regression analysis of the total agricultural output value and the main input factors, it is found that agricultural plastic film,pesticide application amount, agricultural machinery total power and agricultural diesel consumption are the main factors affecting the development of low-carbon agriculture, but the application amount of agricultural chemical fertilizer has been obtained. Effective control. The research shows that the evaluation index system constructed is correct and feasible.On this basis, the countermeasures and suggestions for promoting the development of low-carbon agriculture were put forward.
引文
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[11]黎孔清,马豆豆,李义猛.基于STIR PAT模型的南京市农业碳排放驱动因素分析及趋势预测[J].科技管理研究,2018(08):238-245.
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[13]李波,梅倩.农业生产碳行为方式及其影响因素研究-基于湖北省典型农村的农户调查[J].华中农业大学学报(社会科学版),2017(06):51-58+150.
[2]王娜.河南省低碳农业发展水平及其评价[J].中国农业资源与区划,2018,39(02):123-127.
[3]陈瑾瑜,张文秀.低碳农业发展的综合评价--以四川省为例[J].经济问题,2015(02):101-104.
[4]李练军.基于AHP法的江西现代农业发展水平评价及比较分析[J].安徽农业科学,2015,43(2):334-336.
[5]王亚伟,韩珂.河南省低碳农业系统评价研究[J].天津农业科学,2015,21(3):50-53.
[6]钟婷婷,郑晶,廖福霖,等.省域低碳农业发展水平评价研究[J].福建农林大学学报,2014(014),17(6):43-48.
[7]吴丽娟,于振伟.山东省低碳农业发展评价[J].安徽农业科学,2013,41(36):14169-14170,14172.
[8]孙轶男,梁静溪.基于DEA效率模型的黑龙江省域低碳农业综合评价研究[J].科技与管理,2017,19(06):39-45+72.
[9]刘丽辉,徐军.基于扩展的STIR PAT模型的广东农业碳排放影响因素分析[J].科技管理研究,2016(6):250-255.
[10]高标,房骄,李玉波.基于STIR PAT模型的区域农业碳排放影响因素分析[J].环境科学与技术,2016(10):190-197.
[11]黎孔清,马豆豆,李义猛.基于STIR PAT模型的南京市农业碳排放驱动因素分析及趋势预测[J].科技管理研究,2018(08):238-245.
[12]陈儒,姜志德,姚顺波.低碳农业联合生产的绩效评估及其影响因素分析[J].华中农业大学学报(社会科学版),2018(03):44-55+154-155.
[13]李波,梅倩.农业生产碳行为方式及其影响因素研究-基于湖北省典型农村的农户调查[J].华中农业大学学报(社会科学版),2017(06):51-58+150.