Transfer of agricultural implied water pollution and responsibility sharing among regions in China

doi:10.3969/j.issn.1004-9479.2024.04.20220098

Abstract

Abstract:

In order to clarify the environmental governance and emission reduction responsibilities of all parties and realize the emission reduction of agricultural water pollution. Based on the multi regional input-output model of 31 provinces in China, the agricultural COD emissions of various provinces in China based on producer responsibility, consumer responsibility and income responsibility are calculated respectively, the main paths of agricultural water pollution transfer are identified from the regional and provincial levels, the transfer of agricultural implied water pollution in various regions in China is discussed, and the allocation scheme of water pollution responsibility is put forward. The results show that: (1) agricultural COD has obvious regional transfer characteristics. From the perspective of final demand, northeast region, central region and northwest region are the three largest pollution export regions; From the perspective of initial investment, the transfer of agricultural COD mainly occurs between the central region and the northeast and other northern regions. (2) "Heilongjiang → Guangdong", "Hebei → Guangdong" and "Liaoning → Guangdong" are the three largest net transfer paths of agricultural COD on the consumption side, and "Heilongjiang → Jiangsu" and "Heilongjiang → Jilin" are the two largest net transfer paths of agricultural water pollution on the income side. (3) Compared with schemes A and B, scheme C fully considers the pollution responsibility of income earners and consumers, and measures the water pollution responsibility of the region more comprehensively and scientifically from the perspective of the whole production chain. It is suggested to use a scientific pollution responsibility allocation scheme, strengthen the inter regional coordination and pollution control mechanism, and strengthen the governance responsibilities of different types of regions to reduce water pollution.

Key words: agricultural water pollution, Multi Regional Input-Output Model, implied pollution transfer, liability for pollution

摘要：

为厘清各方环境治理减排责任，实现农业水污染减排。基于中国31省份多区域投入产出模型，分别测算中国各省份基于生产者责任、消费者责任和收入者责任下的农业COD排放量，从区域和省份层面识别出农业水污染转移的主要路径，探讨中国各地区农业隐含水污染转移情况并提出水污染责任分配方案。研究表明：（1）农业COD存在明显的区域转移特征，在最终需求视角下，东北区域、中部区域和西北区域是三个最大的污染输出区域；在最初投入视角下，农业COD的转移主要发生在中部区域和东北区域等北方地区之间。（2）“黑龙江→广东”“河北→广东”和“辽宁→广东”是三条最大的消费侧农业COD净转移路径，“黑龙江→江苏”和“黑龙江→吉林”是两条最大的收入侧农业水污染净转移路径。（3）相较于方案A和B，方案C充分考虑作为收入者和消费者的污染责任，从整个生产链的角度更全面和科学地衡量了本地区应承担的水污染责任。建议使用科学的污染责任分配方案，加强区域间协调治理污染机制，强化不同类型地区的治理责任以减少水污染。

关键词: 农业水污染, 多区域投入产出模型, 隐含污染转移, 污染责任

Chuanlong CHEN, Lianhong QIU. Transfer of agricultural implied water pollution and responsibility sharing among regions in China[J]. World Regional Studies, 2024, 33(4): 73-87.

陈传龙, 邱联鸿. 中国区域间农业隐含水污染转移及责任分担[J]. 世界地理研究, 2024, 33(4): 73-87.

Figures/Tables 8

Fig.1 Schematic diagram of inter regional water pollution transfer

Tab.1 Water pollution economic multi-regional input-output table

变量			中间需求			最终需求			出口	总产出
			$C 1$	$⋯$	$C n$	$C 1$ $Y$	$⋯$	$C n$ $Y$
			$S 1$ $⋯$ $S m$	$⋯$	$S 1$ $⋯$ $S m$	$C 1$ $Y$	$⋯$	$C n$ $Y$
中间投入	$C 1$	$S 1$	$Z 11$	$⋯$	$Z 1 n$	$Y 11$	$⋯$	$Y 1 n$	$E 1$	$X 1$
		$⋮$
		$S m$
	$⋮$	$⋮$	$⋮$	$⋱$	$⋮$	$⋮$	$⋱$	$⋮$	$⋮$	$⋮$
	$C n$	$S 1$	$Z n 1$	$⋯$	$Z n n$	$Y n 1$	$⋯$	$Y n n$	$E n$	$X n$
		$⋮$
		$S m$
进口			$M 1$	$⋯$	$M n$
增加值			$V 1$	$⋯$	$V n$
总投入			$X 1'$	$⋯$	$X n'$
COD			$W 1$	$⋯$	$W n$

Tab.1 Water pollution economic multi-regional input-output table

变量			中间需求			最终需求			出口	总产出
			$C 1$	$⋯$	$C n$	$C 1$ $Y$	$⋯$	$C n$ $Y$
			$S 1$ $⋯$ $S m$	$⋯$	$S 1$ $⋯$ $S m$	$C 1$ $Y$	$⋯$	$C n$ $Y$
中间投入	$C 1$	$S 1$	$Z 11$	$⋯$	$Z 1 n$	$Y 11$	$⋯$	$Y 1 n$	$E 1$	$X 1$
		$⋮$
		$S m$
	$⋮$	$⋮$	$⋮$	$⋱$	$⋮$	$⋮$	$⋱$	$⋮$	$⋮$	$⋮$
	$C n$	$S 1$	$Z n 1$	$⋯$	$Z n n$	$Y n 1$	$⋯$	$Y n n$	$E n$	$X n$
		$⋮$
		$S m$
进口			$M 1$	$⋯$	$M n$
增加值			$V 1$	$⋯$	$V n$
总投入			$X 1'$	$⋯$	$X n'$
COD			$W 1$	$⋯$	$W n$

Fig.2 Agricultural COD emission of each province based on producer responsibility and consumer responsibility

Fig.3 Agricultural COD emission of each province based on producer responsibility and income responsibility

Fig.4 Net transfer of agricultural water pollution by province （10 000 tones）

Fig.5 Sources and destinations of agricultural water pollution transfer in various regions

Tab.2 Top 30 paths for net transfer of agricultural water pollution in each province

排名	消费侧净转移路径	转移量 /万吨	收入侧净转移路径	转移量 /万吨
1	黑龙江→广东	11.38	黑龙江→江苏	1.24
2	河北→广东	6.31	黑龙江→吉林	1.13
3	辽宁→广东	5.37	黑龙江→湖南	0.90
4	黑龙江→上海	4.87	黑龙江→陕西	0.68
5	黑龙江→山东	4.82	黑龙江→河南	0.66
6	黑龙江→浙江	4.55	辽宁→江苏	0.63
7	河南→广东	3.61	黑龙江→广西	0.56
8	湖南→广东	3.45	黑龙江→贵州	0.53
9	黑龙江→安徽	3.32	黑龙江→安徽	0.52
10	内蒙古→广东	3.29	河北→江苏	0.51
11	新疆→广东	3.20	黑龙江→上海	0.48
12	黑龙江→湖北	2.95	河南→江苏	0.46
13	吉林→广东	2.94	黑龙江→云南	0.44
14	黑龙江→河南	2.89	河南→陕西	0.42
15	黑龙江→江苏	2.71	内蒙古→江苏	0.42
16	河北→上海	2.66	河北→陕西	0.40
17	河北→浙江	2.61	山东→广西	0.39
18	河北→山东	2.57	辽宁→吉林	0.38
19	安徽→广东	2.53	山东→河北	0.37
20	内蒙古→浙江	2.46	广东→江苏	0.37
21	辽宁→上海	2.36	河南→上海	0.35
22	黑龙江→重庆	2.35	安徽→江苏	0.35
23	辽宁→浙江	2.23	安徽→上海	0.34
24	河南→浙江	2.20	黑龙江→浙江	0.34
25	辽宁→山东	2.04	山东→陕西	0.34
26	黑龙江→北京	2.00	广东→湖南	0.33
27	河北→安徽	1.88	广东→广西	0.32
28	黑龙江→天津	1.87	广东→陕西	0.32
29	陕西→广东	1.76	安徽→陕西	0.32
30	内蒙古→湖北	1.72	山东→湖南	0.32

Tab.3 Agricultural water pollution discharge responsibility of each province under different schemes

省份	方案A		方案B		方案C
省份	排放量 /万吨	排序	排放量 /万吨	排序	排放量 /万吨	排序
山东	98.61	1	108.51	1	105.77	1
广东	74.02	2	48.42	9	73.89	2
黑龙江	64.85	3	92.42	2	62.09	4
河南	63.35	4	72.63	5	64.91	3
辽宁	61.57	5	75.73	4	62.05	5
河北	58.09	6	78.98	3	60.62	6
四川	48.49	7	48.44	8	48.94	7
湖北	47	8	40.36	11	46.45	9
湖南	44.33	9	54.82	7	47.11	8
内蒙古	39.39	10	56.24	6	41.01	10
吉林	33.42	11	46.32	10	35.36	12
安徽	33.24	12	33.75	14	33.72	13
江苏	32.35	13	36.07	12	37.42	11
浙江	26.69	14	17.11	19	28.3	14
新疆	25.72	15	33.79	13	26.54	15
江西	20.52	16	21.95	15	21.72	16
福建	18.19	17	18.27	18	19.59	17
山西	17.72	18	15.1	20	17.46	21
重庆	17.64	19	11.98	22	18.34	20
广西	17.09	20	20.69	16	19.08	19
陕西	16.89	21	20.02	17	19.36	18
上海	14.57	22	4.12	29	16.21	22
天津	13.13	23	9.59	24	13.75	23
北京	12.28	24	6.28	28	12.43	24
甘肃	10.88	25	12.89	21	11.06	26
云南	10.46	26	7.88	26	12	25
宁夏	7.95	27	8.73	25	8.07	28
海南	7.12	28	9.74	23	7.64	29
贵州	7.04	29	7.2	27	8.78	27
青海	2.89	30	2.13	30	2.97	30
西藏	0.75	31	0.51	31	0.82	31

References 32

1	李秀芬,朱金兆,顾晓君,等.农业面源污染现状与防治进展.中国人口·资源与环境,2010,20(4):81-84.
	LI X, ZHU J, GU X, et al. Current situation and progress in prevention and control of agricultural non-point source pollution. China Population, Resources and Environment, 2010,20 (4): 81-84.
2	金书秦,沈贵银,魏珣,等.论农业面源污染的产生和应对.农业经济问题,2013,34(11):97-102.
	JIN S, SHEN G, WEI X, et al. On the generation and response of agricultural non-point source pollution. Agricultural Economic Issues, 2013,34(11): 97-102.
3	吴义根,冯开文,李谷成.我国农业面源污染的时空分异与动态演进.中国农业大学学报,2017,22(7):186-199.
	WU Y, FENG K, LI G. The spatiotemporal differentiation and dynamic evolution of agricultural non-point source pollution in China. Journal of China Agricultural University, 2017,22(7): 186-199.
4	丘雯文,钟涨宝,李兆亮,等.中国农业面源污染排放格局的时空特征.中国农业资源与区划,2019,40(1):26-34.
	QIU W, ZHONG Z, LI Z, et al. The spatiotemporal characteristics of agricultural non-point source pollution emission patterns in China. China Agricultural Resources and Regionalization, 2019,40(1): 26-34.
5	饶静,许翔宇,纪晓婷.我国农业面源污染现状、发生机制和对策研究.农业经济问题,2011,32(08):81-87.
	RAO J, XU X, JI X. Research on the current situation, mechanism and countermeasures of agricultural non point source pollution in China. Agricultural Economic Issues, 2011, 32(8): 81-87.
6	闵继胜,孔祥智.我国农业面源污染问题的研究进展.华中农业大学学报(社会科学版),2016(2):59-66.
	MIN J, KONG X. Research progress on agricultural non-point source pollution in China. Journal of Huazhong Agricultural University (Social Science Edition), 2016(2): 59-66.
7	李雪娇,邓金钱,安梦天.中国农业污染的理论与实证分析——政治经济学视角下的经验证明.西部论坛,2018,28(4):95-105.
	LI X, DENG Q, AN M. Theoretical and empirical analysis of agricultural pollution in China: Empirical evidence from the perspective of political economy. Western Forum, 2018,28(4): 95-105.
8	沈能,张斌.农业增长能改善环境生产率吗?——有条件"环境库兹涅茨曲线"的实证检验.中国农村经济,2015(7):17-30.
	SHEN N, ZHANG B. Can agricultural growth improve environmental productivity-- Empirical test of conditional "Environmental Kuznets Curve". China Rural Economy, 2015(7): 17-30.
9	BAI J, LI Y, SUN W. Research on emission characteristics of agricultural non-point source pollution based on Kuznets fitting curve. Arabian Journal of Geosciences,2021,14(14): 1324.
10	李守伟,李光超,李备友.农业污染背景下农业补贴政策的作用机理与效应分析.中国人口·资源与环境,2019,29(2):97-105.
	LI S, LI G, LI B. Analysis of the mechanism and effect of agricultural subsidy policies under the background of agricultural pollution. China Population, Resources and Environment, 2019, 29 (2): 97-105.
11	薛蕾,廖祖君,王理.城镇化与农业面源污染改善——基于农民收入结构调节作用的空间异质性分析.农村经济,2019(7):55-63.
	XUE L, LIAO Z, WANG L. Urbanization and improvement of agricultural non-point source pollution: spatial heterogeneity analysis based on the regulatory effect of farmers' income structure. Rural Economy, 2019(7): 55-63
12	罗斯炫,何可,张俊飚.增产加剧污染?——基于粮食主产区政策的经验研究.中国农村经济,2020(1):108-131.
	LUO S, HE K, ZHANG J. Increasing production and exacerbating pollution--Empirical research based on policies in major grain producing areas. China Rural Economy, 2020 (1): 108-131.
13	秦天,彭珏,邓宗兵,等.环境分权、环境规制对农业面源污染的影响.中国人口·资源与环境,2021,31(2):61-70.
	QIN T, PENG J, DENG Z, et al. The impact of environmental decentralization and regulation on agricultural non-point source pollution. China Population, Resources and Environment, 2021, 31(2): 61-70.
14	GAO X, LI B, JIANG S,et al. Can increasing scale efficiency curb agricultural nonpoint source pollution? International Journal of Environmental Research and Public Health,2021,18(16): 8798.
15	栾健,韩一军.农村劳动力转移对化肥面源污染的影响研究——以冀鲁豫3省为例.中国农业资源与区划,2021,42(7):183-191.
	LUAN J, HAN Y. A study on the impact of rural labor transfer on fertilizer non-point source pollution: A case study of Hebei, Shandong, and Henan Provinces. China Agricultural Resources and Zoning, 2021, 42 (7): 183-191
16	ZHOU L, LI L, HUANG J. The river chief system and agricultural non-point source water pollution control in China. Journal of Integrative Agriculture,2021,20(5): 14.
17	彭可茂,席利卿,彭开丽.中国环境规制与污染避难所区域效应——以大宗农产品为例.南开经济研究,2012(4):68-96.
	PENG K, XI L, PENG K. Regional effects of environmental regulations and pollution shelters in China: A case study of bulk agricultural products. Nankai Economic Research, 2012(4): 68-96.
18	沈坤荣,金刚,方娴.环境规制引起了污染就近转移吗?.经济研究,2017,52(5):44-59.
	SHEN K, JIN G, FANG X. Has environmental regulations caused pollution to be transferred nearby Economic Research, 2017,52(5): 44-59.
19	ZHANG Z, ZHANG Z, ZHU K.Allocating carbon responsibility: The role of spatial production fragmentation.Energy Economics,2019.
20	ZHAI M, HUANG G, LIU H, et al.Three-perspective energy-carbon nexus analysis for developing China's policies of CO₂-emission mitigation. Science of the Total Environment,2020,705: 135857.
21	WANG Y, YANG H, LIU J, et al. Analysis of multiple drivers of air pollution emissions in China via interregional trade. Journal of Cleaner Production, 2019, 244: 118507.
22	GUAN Y, HUANG G, LIU L,et al. Measurement of air-pollution inequality through a Three-perspective Accounting Model. Science of the Total Environment,2019,696: 133937.
23	庞军,石媛昌,李梓瑄,等.基于MRIO模型的京津冀地区贸易隐含污染转移.中国环境科学,2017,37(8):3190-3200.
	PANG J, SHI Y, LI Z, et al. Trade implied pollution transfer in the Beijing Tianjin Hebei region based on the MRIO model. China Environmental Science, 2017,37(8): 3190-3200.
24	WANG J, LI L, LI F, et al. Regional footprints and interregional interactions of chemical oxygen demand discharges in China. Resources, Conservation and Recycling, 2017,132: 386-397.
25	孙才志,阎晓东.基于MRIO的中国省区和产业灰水足迹测算及转移分析.地理科学进展,2020,39(2):207-218.
	SUN C, YAN X. Grey water footprint calculation and transfer analysis of provinces and industries in China based on MRIO. Progress in Geographic Science, 2020,39 (2): 207-218.
26	ZHAO D, QUAN L. Water pollution loads and shifting within China's inter-province trade. Journal of Cleaner Production,2020,259: 120879.
27	李姣,李朗,李科.隐含水污染视角下的中国省际农业生态补偿标准研究.农业经济问题,2022(6):106-121.
	LI J, LI L, LI K. Research on inter provincial agricultural ecological compensation standards in China from the perspective of implicit water pollution. Agricultural Economic Issues, 2022(6):106-121.
28	李方一,刘卫东,唐志鹏.中国区域间隐含污染转移研究.地理学报,2013,68(6):791-801.
	LI F, LIU W, TANG Z. Research on implied pollution transfer between regions in China. Journal of Geography, 2013,68 (6): 791-801.
29	余晓泓,詹夏颜.基于收益原则的碳排放转移及中国碳排放责任研究.资源科学,2018,40(1):185-194.
	YU X, ZHAN X. Research on carbon emission transfer and China's carbon emission responsibility based on the benefit principle. Resource Science, 2018,40(1): 185-194.
30	RODRIGUES J, DOMINGOS T. Consumer and producer environmental responsibility: Comparing two approaches. Ecological Economics, 2008, 66(2-3):533-546.
31	ZHENG H, ZHANG Z, WEI W, et al. Regional determinants of China's consumption-based emissions in the economic transition. Environmental Research Letters, 2020, 15(7): 1-14.
32	张亚雄,齐舒畅.2002、2007年中国区域间投入产出表.北京:中国统计出版社,2012.
	ZHANG Y, QI S. 2002, 2007 China Regional Input Output Table. Beijing: China Statistical Publishing House, 2012.