Spatial-temporal characteristics and influencing factors of non-point source pollution of chemical fertilizers in China: based on provincial panel data from 1997 to 2020

doi:10.3969/j.issn.1004-1524.20230699

Acta Agriculturae Zhejiangensis ›› 2024, Vol. 36 ›› Issue (5): 1185-1198.DOI: 10.3969/j.issn.1004-1524.20230699

• Agricultural Economy and Development • Previous Articles Next Articles

Spatial-temporal characteristics and influencing factors of non-point source pollution of chemical fertilizers in China: based on provincial panel data from 1997 to 2020

JI Xuanxuan(), JIANG Junsong^*()

Business School, Xiangtan University, Xiangtan 411105, Hunan, China

Received:2023-05-31 Online:2024-05-25 Published:2024-05-29

Abstract

Abstract:

The problem of non-point source pollution of chemical fertilizers is related to the green development of agriculture and the revitalization of rural ecology. Based on the provincial panel data from 1997 to 2020, the emission intensity of non-point source pollution of chemical fertilizers was measured. The Kernel density estimation, Markov chain analysis, Theil index, two-way fixed effect model and other methods were adopted to explore the spatial-temporal characteristics and influencing factors of non-point source pollution of chemical fertilizers in China. The results showed that, the emission intensity of non-point source pollution of chemical fertilizers in China was increasing at first and then decreasing. Taking the year of 2015 as the dividing point, the trend of emission intensity of non-point source pollution of chemical fertilizer shifting to a low level gradually appeared, but it was still stable to maintain the original level, and it was difficult to achieve leapfrog reduction. During the sample period, the emission intensity of non-point source pollution of chemical fertilizers showed a spatial distribution pattern of “high in the east and low in the west, high in the south and low in the north”. The intra-regional difference was the main source of the overall difference. Nine factors, such as the level of financial support for agriculture, the level of agricultural economic growth and rural human capital, affected the emission intensity of non-point source pollution of chemical fertilizers. Therefore, it is necessary not only to formulate differentiated pollution control measures, but also to strengthen cooperation in pollution control among provincial administrative regions. Meanwhile, it is important to expand the path of fertilizer reduction and efficiency increase in order to promote greener agricultural development in all respects.

Key words: non-point source pollution of chemical fertilizer, emission intensity, spatial-temporal characteristic, influencing factor, pollution control

CLC Number:

F329.9

JI Xuanxuan, JIANG Junsong. Spatial-temporal characteristics and influencing factors of non-point source pollution of chemical fertilizers in China: based on provincial panel data from 1997 to 2020[J]. Acta Agriculturae Zhejiangensis, 2024, 36(5): 1185-1198.

Figures/Tables 10

Fig.1 Dynamic of pollutants emission of non-point source pollution of chemical fertilizers from 1997 to 2020

Fig.2 Dynamic of the emission intensity of non-point source pollution of chemical fertilizers from 1997 to 2020 National, The mean value of 31 provincial administrative regions excluding Hongkong, Macao and Taiwan; Eastern region, The mean value of Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan; Central region, The mean value of Heilongjiang, Jilin, Shanxi, Anhui, Jiangxi, Henan, Hubei, Hunan; Western region, The mean value of Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Xizang, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang.

Fig.3 Kernel density estimation of the emission intensity of non-point source pollution of chemical fertilizers

Table 1 Markov transition probability matrix of emission intensity of non-point source pollution of chemical fertilizers

时间段 Period	t年的排放水平 Emission intensity at t year	(t+1)年转换为相应排放水平的概率 Probability of emission intensity transition at (t+1) year
时间段 Period	t年的排放水平 Emission intensity at t year	高High	中高Mid-high	中低Mid-low	低Low
1997—2020	高High	0.961 3	0.038 7	0	0
	中高Mid-high	0.045 7	0.954 3	0	0
	中低Mid-low	0	0.005 6	0.988 8	0.005 6
	低Low	0	0	0.022 3	0.977 7
1997—2015	高High	0.985 5	0.014 5	0	0
	中高Mid-high	0.050 7	0.949 3	0	0
	中低Mid-low	0	0.007 2	0.985 5	0.007 2
	低Low	0	0	0.027 8	0.972 2
2016—2020	高High	0.852 9	0.147 1	0	0
	中高Mid-high	0.033 3	0.966 7	0	0
	中低Mid-low	0	0	1	0
	低Low	0	0	0	1

Fig.4 Spatial distribution of the emission intensity of non-point source pollution of chemical fertilizers a, All the 31 provincial administrative regions in the present study; b, Eastern region, including Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan; c, Central region, including Heilongjiang, Jilin, Shanxi, Anhui, Jiangxi, Henan, Hubei, Hunan; d, Western region, including Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Xizang, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang.

Fig.5 The overall differences and main sources of the emission intensity of non-point source pollution of chemical fertilizers

Fig.6 The intra-regional differences and contribution rates of the emission intensity of non-point source pollution of chemical fertilizers in different regions

Table 2 Influencing factors of the emission intensity of non-point source pollution of chemical fertilizers

类型 Type	变量 Variable	变量符号 Symbol of variable	含义 Denotation	预期影响方向 Anticipated influencing direction
政策支持 Policy support	财政支农水平 Level of financial support for agriculture/ (10⁴ yuan·hm^-2)	X₁	财政农林水事务支出/农作物总播种面积 Financial expenditure on agriculture, forestry and water affairs/total sown area of crops	未定 Uncertain
农业发展 Agricultural development	农业经济增长水平 Level of agricultural economic growth/ (10⁴ yuan)	X₂	农业总产值/农业从业人数 Total agricultural output value/number of agricultural employees	未定 Uncertain
	农作物种植结构 Crop planting structure	X₃	粮食作物种植面积/农作物总播种面积 Planting area of grain crops/total sown area of crops	负向 Negative
	农业复种指数 Agricultural multiple cropping index	X₄	农作物总播种面积/耕地面积 Total sown area of crops/cultivated land area	未定 Uncertain
	规模化经营水平 Scale management level/m²	X₅	耕地面积/农业从业人数 Cultivated land area/number of agricultural employees	未定 Uncertain
	农业机械投入强度 Intensity of agricultural machinery input/ (kW·hm^-2)	X₆	农业机械总动力/农作物总播种面积 Total power of agricultural machinery/total sown area of crops	负向 Negative
外部环境 External environment	农民收入水平 Income level of farmers/(10⁴ yuan)	X₇	农村居民人均可支配收入 Per capita disposable income of rural residents	未定 Uncertain
	农村人力资本 Rural human capital/a	X₈	各学历层次年限与其人员构成比例乘积的加总, 将小学、初中、高中或中专、大专及以上分别设定为6、9、12、15.5 a The sum of the product of the years of each educational level and its personnel composition ratio. In particular, primary school, junior high school, senior high school or technical secondary school, junior college and above are recorded as 6, 9, 12, 15.5 a, respectively	负向 Negative
	城镇化水平 Urbanization level	X₉	城镇人口/年末常住人口 Urban population/resident population at year end	未定 Uncertain

Table 2 Influencing factors of the emission intensity of non-point source pollution of chemical fertilizers

类型 Type	变量 Variable	变量符号 Symbol of variable	含义 Denotation	预期影响方向 Anticipated influencing direction
政策支持 Policy support	财政支农水平 Level of financial support for agriculture/ (10⁴ yuan·hm^-2)	X₁	财政农林水事务支出/农作物总播种面积 Financial expenditure on agriculture, forestry and water affairs/total sown area of crops	未定 Uncertain
农业发展 Agricultural development	农业经济增长水平 Level of agricultural economic growth/ (10⁴ yuan)	X₂	农业总产值/农业从业人数 Total agricultural output value/number of agricultural employees	未定 Uncertain
	农作物种植结构 Crop planting structure	X₃	粮食作物种植面积/农作物总播种面积 Planting area of grain crops/total sown area of crops	负向 Negative
	农业复种指数 Agricultural multiple cropping index	X₄	农作物总播种面积/耕地面积 Total sown area of crops/cultivated land area	未定 Uncertain
	规模化经营水平 Scale management level/m²	X₅	耕地面积/农业从业人数 Cultivated land area/number of agricultural employees	未定 Uncertain
	农业机械投入强度 Intensity of agricultural machinery input/ (kW·hm^-2)	X₆	农业机械总动力/农作物总播种面积 Total power of agricultural machinery/total sown area of crops	负向 Negative
外部环境 External environment	农民收入水平 Income level of farmers/(10⁴ yuan)	X₇	农村居民人均可支配收入 Per capita disposable income of rural residents	未定 Uncertain
	农村人力资本 Rural human capital/a	X₈	各学历层次年限与其人员构成比例乘积的加总, 将小学、初中、高中或中专、大专及以上分别设定为6、9、12、15.5 a The sum of the product of the years of each educational level and its personnel composition ratio. In particular, primary school, junior high school, senior high school or technical secondary school, junior college and above are recorded as 6, 9, 12, 15.5 a, respectively	负向 Negative
	城镇化水平 Urbanization level	X₉	城镇人口/年末常住人口 Urban population/resident population at year end	未定 Uncertain

Table 3 Model regression results

变量Variable	回归1 Regression 1	回归2 Regression 2	回归3 Regression 3
X₁	-0.337^***(0.079)	-0.154^***(0.033)	-0.107^***(0.034)
X₂	0.862(0.527)	2.749^***(0.390)	2.422^***(0.344)
$X_{2}^{2}$	-0.109(0.109)	-0.383^***(0.058)	-0.289^***(0.048)
X₃	-9.477^***(1.298)	-1.556^***(0.576)	-2.754^***(0.641)
X₄	3.623^***(0.352)	-3.358^***(0.243)	-3.540^***(0.275)
X₅	-0.089^***(0.014)	-0.085^***(0.010)	-0.077^***(0.010)
X₆	-0.183^***(0.034)	0.058^***(0.017)	-0.035^**(0.017)
X₇	8.422^***(1.266)	-1.070^**(0.539)	-3.229^***(0.738)
X₈	-0.708^***(0.146)	0.304^***(0.095)	-0.302^***(0.117)
X₉	-1.794(1.182)	-2.048^***(0.701)	-2.638^***(0.647)
时间固定效应 Time fixed effect	未控制Not controlled	未控制Not controlled	控制Controlled
个体固定效应Individual fixed effect	未控制Not controlled	控制Controlled	控制Controlled
常数项Constant	11.023^***(1.280)	9.797^***(0.809)	15.400^***(1.015)
n	744	744	744
R²	0.590	0.976	0.980

Table 3 Model regression results

变量Variable	回归1 Regression 1	回归2 Regression 2	回归3 Regression 3
X₁	-0.337^***(0.079)	-0.154^***(0.033)	-0.107^***(0.034)
X₂	0.862(0.527)	2.749^***(0.390)	2.422^***(0.344)
$X_{2}^{2}$	-0.109(0.109)	-0.383^***(0.058)	-0.289^***(0.048)
X₃	-9.477^***(1.298)	-1.556^***(0.576)	-2.754^***(0.641)
X₄	3.623^***(0.352)	-3.358^***(0.243)	-3.540^***(0.275)
X₅	-0.089^***(0.014)	-0.085^***(0.010)	-0.077^***(0.010)
X₆	-0.183^***(0.034)	0.058^***(0.017)	-0.035^**(0.017)
X₇	8.422^***(1.266)	-1.070^**(0.539)	-3.229^***(0.738)
X₈	-0.708^***(0.146)	0.304^***(0.095)	-0.302^***(0.117)
X₉	-1.794(1.182)	-2.048^***(0.701)	-2.638^***(0.647)
时间固定效应 Time fixed effect	未控制Not controlled	未控制Not controlled	控制Controlled
个体固定效应Individual fixed effect	未控制Not controlled	控制Controlled	控制Controlled
常数项Constant	11.023^***(1.280)	9.797^***(0.809)	15.400^***(1.015)
n	744	744	744
R²	0.590	0.976	0.980

Table 4 Regional heterogeneity analysis

变量Variable	东部Eastern region	中部Central region	西部Western region
X₁	-0.064(0.048)	-2.996^***(0.988)	-0.092(0.111)
X₂	2.925^***(0.577)	-0.905(0.855)	2.230^***(0.708)
$X_{2}^{2}$	-0.320^***(0.084)	0.216(0.187)	-0.365^*(0.198)
X₃	-5.243^***(1.582)	-0.883(0.954)	-5.071^***(0.975)
X₄	-3.477^***(0.457)	-2.419^***(0.525)	-2.490^***(0.508)
X₅	-0.184^***(0.040)	-0.025(0.017)	-0.017(0.013)
X₆	-0.059(0.055)	0.012(0.046)	-0.061^**(0.029)
X₇	-3.808^**(1.617)	-1.842(3.632)	1.842(1.442)
X₈	-0.208(0.264)	0.432^**(0.204)	-0.197(0.152)
X₉	-0.296(2.523)	4.995^***(1.494)	-4.809^***(0.419)
常数项Constant	10.157^***(2.984)	5.932^***(1.655)	13.089^***(1.469)
n	264	192	288
R²	0.981	0.989	0.981

Table 4 Regional heterogeneity analysis

变量Variable	东部Eastern region	中部Central region	西部Western region
X₁	-0.064(0.048)	-2.996^***(0.988)	-0.092(0.111)
X₂	2.925^***(0.577)	-0.905(0.855)	2.230^***(0.708)
$X_{2}^{2}$	-0.320^***(0.084)	0.216(0.187)	-0.365^*(0.198)
X₃	-5.243^***(1.582)	-0.883(0.954)	-5.071^***(0.975)
X₄	-3.477^***(0.457)	-2.419^***(0.525)	-2.490^***(0.508)
X₅	-0.184^***(0.040)	-0.025(0.017)	-0.017(0.013)
X₆	-0.059(0.055)	0.012(0.046)	-0.061^**(0.029)
X₇	-3.808^**(1.617)	-1.842(3.632)	1.842(1.442)
X₈	-0.208(0.264)	0.432^**(0.204)	-0.197(0.152)
X₉	-0.296(2.523)	4.995^***(1.494)	-4.809^***(0.419)
常数项Constant	10.157^***(2.984)	5.932^***(1.655)	13.089^***(1.469)
n	264	192	288
R²	0.981	0.989	0.981

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Spatial-temporal characteristics and influencing factors of non-point source pollution of chemical fertilizers in China: based on provincial panel data from 1997 to 2020

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