An Empirical Study on the Influence Factors’ Satisfaction of the Crop Rotation and Fallow Governance with the Heavy Metal Contaminated Farmland Based on the Cumulative Logistic Regression Model
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摘要: 研究农村重金属污染耕地轮作休耕治理满意度状况及其影响因素,为当前我国耕地重金属污染治理实施提供参考依据。基于湖南省4区县10个村镇400户调查数据,构建累积logistic回归模型,探究农村重金属污染耕地轮作休耕治理的满意度情况及其影响因素。研究发现受教育程度越高对当前环境治理的效果和收入满意度评价越积极,受教育程度每提高一个层次,满意度提高一个层次的可能性分别增加18%和24%;家庭收入与环境治理满意度及收入满意度呈负向影响,家庭收入每提高一个层次,满意度提高一个层次的可能性分别减少16%和10%;调查对象年龄越大对当前环境治理的效果评价越积极,年龄每增加一个时间段,满意度提高一个层次的可能性增加80%。相反,年龄对收入的满意度评价却呈负向影响,年龄每增加一个时间段,满意度降低一个层次的可能性增加10%;农户拥有耕地受污染程度与环境治理及收入满意度呈正向影响,农户自有耕地受污染程度越高,满意度提高的可能性分别增加23%和16%。加强农村重金属污染耕地治理政策与治理效果的及时宣传,切实提高农户家庭收入的质量和效率,稳步提升农业从业人员的平均受教育水平和环境认知水平、促进农户积极参与耕地保护和环境治理过程中。
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关键词:
- 重金属污染 /
- 轮作休耕 /
- 累积logistic模型 /
- 理性小农
Abstract: The satisfaction degree of heavy metal pollution controlled by the farmland rotation and fallow and its influencing factors in the rural heavy metal pollution farmland were investigated in this study, to provide reference basis for the heavy metal pollution governance. Based on the survey data of 400 households from10 villages and towns in 4 districts and counties of Hunan Province, a cumulative logistic regression model was established to explore the satisfaction degree and its influencing factors of farmland rotation and fallow treatment, these were contaminated by heavy metal. The results showed that the higher level the education, the more positive the assessments on the current environmental governance effect and the income satisfaction. Meanwhile, with the increase of the education by one level, their satisfaction degrees were increased by 18% and 24%, respectively. The family income has a negative influence on the satisfaction degree of environmental governance and the satisfaction degree of income. For every increase of family income, the probability of the satisfaction degree increasing by one level increases by −16% and −10% respectively. Moreover, the older the age, the more positive the assessments on the effect of current environmental governance. For each level of age increased, the probability of increasing satisfaction by one level was increased by 80%. However, the evaluation of satisfaction degree of age to income was negative, showing the probability of satisfaction degree decreased one level was increased by 10% with the increase each level of age. The pollution degree of farmland owned by farmers was positively related to the satisfaction degree of environmental treatment and income. The higher the pollution degree of farmland owned by farmers, the higher the probability of satisfaction increased by 23% and 16% respectively. In general, this study suggested that it was necessary to strengthen the publicity of the policies and effects of the heavy metal polluted farmland in the rural areas, improve the quality and efficiency of the household income, raise the average educational level and the environmental cognitive ability of agricultural employees, and promote farmers to actively participate in the process of cultivated land protection and environmental governance. -
表 1 变量释义、赋值
Table 1. Definition and assignment of variables
变量名称
Variable name变量
Variable变量的含义
Variable Meaning因变量 Y1:环境治理效果满意度评价 非常不满意 = 1,比较不满意 = 2,不满意 = 3,一般满意 = 4,比较满意 = 5,非常满意 = 6 Y2:休耕治理后农户收入的满意度评价 非常不满意 = 1,比较不满意 = 2,不满意 = 3,一般满意 = 4,比较满意 = 5,非常满意 = 6 自变量 X1:调查对象年龄 25 ~ 34岁 = 1,35 ~ 40岁 = 2,41 ~ 50岁 = 3,51 ~ 60岁 = 4,61 ~ 70岁 = 5,70岁以上 = 6 X2:调查对象受教育程度 未上过学 = 1,小学 = 2,初中 = 3,高中或中专 = 4,大专及以上 = 5 X3:调查对象家庭收入(元) 10000元以下 = 1,10000 ~ 20000元 = 2,20001 ~ 30000元 = 3,30001 ~ 50000元 = 4,50001 ~ 80000元 = 5,80000元以上 = 6 X4:调查对象家庭耕地污染程度 较低 = 1,一般 = 2,较高 = 3,非常严重 = 4 X5:调查对象是否关注当地土壤环境治理 不关注 = 1,一般 = 2,比较关注 = 3,非常关注 = 4 表 2 多分类累积logistic回归结果
Table 2. Results of multiple-category cumulative logistic regression
自变量
Independent
variable模型1(因变量:环境治理效果评价)
Model 1 (Dependent variable: assessment of
environmental governance effectiveness)模型2(因变量:治理后农户收入满意度评价)
Model 2 (Dependent variable: assessment of farmers’income
satisfaction after governance)参数系数
Coefficient标准误差
Standard ErrorZ统计量
Z-Statistic概率
Probability参数系数
Coefficient标准误差
Standard ErrorZ统计量
Z-Statistic概率
ProbabilityX1 0.1632 0.0826 1.9756 0.0482 −0.1018 0.0788 −1.6918 0.0964 X2 0.5872 0.1134 5.1782 0.0000 0.2144 0.1086 1.9732 0.0485 X3 −0.1710 0.0785 −2.1769 0.0295 −0.1060 0.0789 −1.5446 0.1188 X4 0.2068 0.1096 1.8868 0.0592 0.1505 0.1042 1.4443 0.1486 X5 0.0266 0.0856 0.5106 0.3561 0.1309 0.0863 1.5167 0.1293 $ {\partial }_{1} $ −1.2696 0.6918 −1.8350 0.0665 −1.7608 0.6319 −2.7862 0.0053 $ {\partial }_{2} $ 1.6466 0.6457 2.5501 0.0108 0.6939 0.6153 1.1276 0.2595 $ {\partial }_{3} $ 3.5517 0.6660 5.3326 0.0000 2.2729 0.6264 3.6283 0.0003 LR 统计量:32.59 LR 统计量:14.07 -
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