甘肃省灰水足迹变化特征及驱动因素

doi:10.13866/j.azr.2022.06.11

Abstract

Abstract:

This study examines the change in the gray water footprint in Gansu Province from 2011 to 2020 and uses the STIRPAT model to analyze the driving factors of the greywater footprint. The results show that the greywater footprint has been declining over the last ten years. The overall decrease was 378.53 billion m³; the maximum decline was 81%. The life, agricultural, and industrial greywater footprints accounted for 43%, 38%, and 19%, respectively. The graywater footprint of the planting industry is greater than that of animal husbandry. The overall intensity of the greywater footprint shows a downward trend, indicating that water resource utilization has increased yearly. According to the degree of water pollution and residual graywater footprint, the water pollution level in the Gansu Province from 2011 to 2016 was greater than one, and the water pollution is relatively severe. The research shows that the residual ash water footprint was negative from 2017 to 2020, indicating that the water quality shows an upward trend. Water environmental problems have been improved, and water resources continue to increase. From the driving factors of greywater footprint in the Gansu Province, urbanization level; per capita GDP; first, second, and third industrial output value; the intensity of greywater footprint; and total retail sales of social consumer goods will all promote the increase of greywater footprint, and the influencing coefficients are 0.142, 0.126, 0.052, 0.382, 0.132, 0.916, and 0.1, respectively. According to the size of the impact coefficient, relevant policies can be developed to reduce the graywater footprint of the Gansu Province, reducing the pressure on the water environment.

Key words: Gansu Province, gray water footprints, driving factor, STIRPAT model, ridge regression

YIN Mingcai,ZHU Hao,HU Yuanzhao,LI Zhenzhong,ZHANG Jishi. Analysis of various characteristics and driving factors of gray water footprint in Gansu Province[J].Arid Zone Research, 2022, 39(6): 1810-1818.

Figures/Tables 14

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References 28

[1]	沈满洪, 陈庆能. 水资源经济学[M]. 北京: 中国环境科学出版社, 2008.
	[ Shen Manhong, Chen Qingneng. Water Economics[M]. Beijing: China Environmental Press, 2008. ]
[2]	王雅, 冼超凡, 欧阳志云. 基于灰水足迹的中国城市水资源可持续利用综合评价[J]. 生态学报, 2021, 41(8): 2983-2995.
	[ Wang Ya, Xian Chaofan, Ouyang Zhiyun. Integrated assessment of sustainability in urban water resources utilization in China based on grey water footprint[J]. Acta Ecologica Sinica, 2021, 41(8): 2983-2995. ]
[3]	许程程. 甘肃省水资源承载力评价研究[D]. 兰州: 兰州财经大学, 2021.
	[ Xu Chengcheng. Research on Evaluation of Water Resources Carrying Capacity in Gansu Province[D]. Lanzhou: Lanzhou University of Finance and Economics, 2021. ]
[4]	李向, 管涛, 徐清. 基于BP神经网络的土壤重金属污染评价方法——以包头土壤环境质量评价为例[J]. 中国农学通报, 2012, 28(2): 250-256.
	[ Li Xiang, Guan Tao, Xu Qing. The evaluation of soil heavy metal pollution based on the BP neural network: Taking soil environmental quality assessment in Baotou as an example[J]. Chinese Agricultural Science Bulletin, 2012, 28(2): 250-256. ]
[5]	景朝霞, 夏军, 张翔, 等. 汉江中下游干流水质状况时空分布特征及变化规律[J]. 环境科学研究, 2019, 32(1): 104-115.
	[ Jing Zhaoxia, Xia Jun, Zhang Xiang, et al. Spatial and temporal distribution and variation of water quality in the middle and downstream of Hanjiang River[J]. Research of Environmental Sciences, 2019, 32(1): 104-115. ]
[6]	吴钢, 蔡井伟, 付海威, 等. 模糊综合评价在大伙房水库下游水污染风险评价中应用[J]. 环境科学, 2007, 11(3): 2438-2441.
	[ Wu Gang, Cai Jingwei, Fu Haiwei, et al. Application of fuzzy comprehensive assessment in risk assessment of water pollution conditions in downriver area of Dahuofang Reservoir[J]. Environmental Science, 2007, 11(3): 2438-2441. ]
[7]	曾昭, 刘俊国. 北京市灰水足迹评价[J]. 自然资源学报, 2013, 28(7): 1169-1178.
	[ Zeng Zhao, Liu Junguo. Historical trend of grey water footprint of Beijing, China[J]. Journal of Natural Resources, 2013, 28(7): 1169-1178. ]
[8]	申浩, 陈致君, 刘健, 等. 山东省灰水足迹区域均衡性分析[J]. 节水灌溉, 2022(3): 1-7.
	[ Sheng Hao, Chen Zhiqun, Liu Jian, et al. Analysis of the regional equilibrium of grey water footprint in Shandong Province[J]. Water Saving Irrigation, 2022(3): 1-7. ]
[9]	Hoekstra A Y, Chapagain A K. Globalization of Water: Sharing the Planet’s Freshwater Resources[M]. Oxford: Wiley-Blackwell, 2008.
[10]	Hoekstra A Y, Chapagain A K, Aldaya M M, et al. The Water Footprint Assessment Manual: Setting the Global Standard[M]. London: Earthscan, 2011:30- 40.
[11]	傅春, 陈毓迪, 刘业忠, 等. 江西省农田灰水足迹时空分析[J]. 农业环境科学学报, 2022, 41(7): 1501-1508.
	[ Fu Chun, Chen Yudi, Liu Yezhong, et al. Temporal and spatial analysis of grey water footprint in Jiangxi Province farmland[J]. Journal of Agro-Environment Science, 2022, 41(7): 1501-1508. ]
[12]	罗勇. 赣江流域灰水足迹时空演变特征研究[D]. 南昌: 南昌大学, 2021.
	[ Luo Yong. Study on the Temporal and Spatial Evolution Characteristics of Grey Water Footprint in Ganjiang River Basin[D]. Nanchang: Nanchang University, 2021. ]
[13]	贺志文, 向平安. 湖南省灰水足迹变化特征及其驱动因子分析[J]. 中国农村水利水电, 2018(10): 19-26.
	[ He Zhiwen, Xiang Pingan. An analysis of the variations and driving factors of grey water footprint in Hunan Province[J]. China Rural Water and Hydropower, 2018(10): 19-26. ]
[14]	钱秀红. 杭嘉湖平原农业非点源污染的调查评价及控制对策研究[D]. 杭州: 浙江大学, 2001.
	[ Qian Xiuhong. Investigation, Evaluation and Control Countermeasures of Agricultural Non-point Source Pollution in Hangjiahu Plain[D]. Hangzhou: Zhejiang University, 2001. ]
[15]	李飞, 董锁成. 西部地区畜禽养殖污染负荷与资源化路径研究[J]. 资源科学, 2011, 33(11): 2204-2211.
	[ Li Fei, Dong Suocheng. Pollution from livestock and poultryand. its resource strategy in West China[J]. Resources Science, 2011, 33(11): 2204-2211. ]
[16]	李中桂, 高利珍. 基于水足迹理论的污水处理厂评估[J]. 环境工程学报, 2017, 11(3): 1599-1604.
	[ Li Zhonggui, Gao Lizhen. Water footprint assessment in wastewater treatment plants[J]. Chinese Journal of Environmental Engineering, 2017, 11(3): 1599-1604. ]
[17]	王晓萌, 黄凯, 杨顺顺, 等. 中国产业部门水足迹演变及其影响因素分析[J]. 自然资源学报, 2014, 29(12): 2114-2126.
	[ Wang Xiaomeng, Huang Kai, Yang Shunshun, et al. Temporal variability and influencing factors of sectoral water footprint in China[J]. Journal of Natural Resources, 2014, 29(12): 2114-2126. ]
[18]	Ehrlich P R, Holden J P. Impact of population growth[J]. Science, 1971, 171: 1212-1217. pmid: 5545198
[19]	Dietz T, Rosa E A. Rethinking the environmental impacts of population, affluence and technology[J]. Human Ecology Review, 1994, 1: 277-300.
[20]	York R, Rosa E A, Dietz T. STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts[J]. Ecological economics, 2003, 46(3): 351-365. doi: 10.1016/S0921-8009(03)00188-5
[21]	张郁, 张峥, 苏明涛. 基于化肥污染的黑龙江垦区粮食生产灰水足迹研究[J]. 干旱区资源与环境, 2013, 27(7): 28-32.
	[ Zhang Yu, Zhang Zheng, Su Mingtao. Research on grey water footprint based on chemical fertilizer use in the grain production in Heilongjiang reclamation area[J]. Journal of Arid Land Resources and Environment, 2013, 27(7): 28-32. ]
[22]	Wu Bo, Zeng Weihua, Chen Honghan, et al. Grey water footprint combined with ecological network analysis for assessing regional water quality metabolism[J]. Journal of Cleaner Production, 2016, 112: 3138-3151. doi: 10.1016/j.jclepro.2015.11.009
[23]	Li Y, Lu L, Tan Y, et al. Decoupling water consumption and environmental impact on textile industry by using water footprint method: A case study in China[J]. Water, 2017, 9(2): 124. doi: 10.3390/w9020124
[24]	国家环境保护总局自然生态保护司. 全国规模化畜禽养殖业污染情况调查及防治对策[M]. 北京: 中国环境科学出版社, 2002.
	[ Department of Natural Ecology Protection, State Environmental Protection Administration. Investigation on the Pollution Situation of National Large-scale Livestock and Poultry Breeding Industry and Countermeasures for Prevention and Control[M]. Beijing: China Environmental Press, 2002. ]
[25]	全国污染源普查水产养殖业污染源产排污系数测算项目组. 第一次全国污染源普查水产养殖业污染源产排污系数手册[M]. 北京: 中国水产科学研究院, 2009.
	[ National Pollution Source Census Aquaculture Industry Pollution Source Production and Discharge Coefficient Calculation Project Team. The First National Pollution Source Census Aquaculture Industry Pollution Source Production Sewage Coefficient Manual[M]. Beijing: Chinese Academy of Fishery Sciences, 2009. ]
[26]	杨楠. 岭回归分析在解决多重共线性问题中的独特作用[J]. 统计与决策, 2004(3): 14-15.
	[ Yang Nan. The unique role of ridge regression analysis in solving multicollinearity problems[J]. Statistics & Decision, 2004(3): 14-15. ]
[27]	张丽丽. 基于STIRPAT模型的建筑业碳排放影响因素分析[D]. 西安: 西安建筑科技大学, 2020.
	[ Zhang Lili. Analysis of Carbon Emission Factors in Construction Industry Based on STIRPAT Model[D]. Xi’an: Xi’an University of Architecture and Technology, 2020. ]
[28]	李允洁. 杭州市灰水足迹研究[D]. 浙江: 浙江师范大学, 2017.
	[ Li Yunjie. Research on Grey Water Footprint in Hangzhou[D]. Zhejiang: Zhejiang Normal University, 2017. ]

年份	污水排放量/10⁴t		污染物排放量/10⁴t			水资源量/10⁸m³	GDP/10⁸元
年份	生活污水	工业污水	生活COD	工业COD	总氮	水资源量/10⁸m³	GDP/10⁸元
2011	59477	10218	10	0.45	3.6	410.88	9016.7
2012	59718	10409	11.23	0.87	1.28	325.88	8718.3
2013	59478	10539	11.35	0.96	1.37	354.89	8104.1
2014	54003	10426	11.31	1.39	1.35	280.79	7336.7
2015	53283	13022	13.82	1.74	1.59	209.56	6907.9
2016	48275	18760	14.66	8.36	5.13	198.81	6556.6
2017	46209	19742	14.41	8.86	5.12	230.84	6518.4
2018	44769	20171	14.54	9.05	4.74	303.209	6014.5
2019	43589	19188	14.99	9.3	4.75	300.69	5393.1
2020	39491	19720	15.23	9.61	5.19	272.14	4816.9
均值	50829.20	15219.50	13.15	5.07	3.41	288.77	6938.32

项目	牛粪	猪粪	羊粪	家禽粪	牛猪尿
COD	6.16	5.58	5.50	8.59	50
BOD	4.87	6.14	6.70	6.78	50
NH₃-N	2.22	3.04	4.10	4.15	50
TP	5.50	5.25	5.20	8.42	50
TN	5.68	5.34	5.30	8.47	50

变量名称	计算方法	符号
灰水足迹/10⁸ m³	各年灰水足迹	Y
人口/10⁴人	各年人口数量	X₁
城镇化水平/%	城镇人口占总人口比例	X₂
人均GDP/(元·人^－1)	各年人均 GDP	X₃
第一产业产值/10⁸元	提供生产物资材料的产业	X₄
第二产业产值/10⁸元	加工、制造产业	X₅
第三产业产值/10⁸元	商业、餐饮业、金融保险业等非物质生产部门	X₆
灰水足迹强度/﹝m³·(10⁴元)^-1﹞	水资源效率变化状况	X₇
社会消费品零售总额/10⁴元	指城乡居民用于生活消费的商品金额	X₈

模型	非标准化系数		标准化系数	t	Sig	共线性
模型	弹性系数B	标准误差	试用版	t	Sig	容差	VIF
变量	-14.697	42.908		-0.343	0.765
lnX₂	-3.412	5.912	-0.092	-0.577	0.622	0.006	161.101
lnX₃	4.427	1.880	2.100	2.354	0.143	0.000	5092.938
lnX₄	-.580	0.699	-0.494	-0.830	0.494	0.000	2265.950
lnX₅	1.901	0.540	0.504	3.519	0.072	0.008	131.477
lnX₆	6.131	1.518	3.811	4.039	0.056	0.000	5696.821
lnX₇	5.417	0.953	2.450	5.682	0.030	0.001	1190.048
lnX₈	-0.081	0.027	-0.253	-3.016	0.095	0.022	44.982

模型汇总
样本量	R²	调整R²	模型误差RMSE
10	0.999	0.994	0.02

Analysis of various characteristics and driving factors of gray water footprint in Gansu Province

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References 28

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ANOVA表格
	平方和	df	均方	F	P值
回归	3.063	7	0.438	217.867	0.005
残差	0.004	2	0.002
总计	3.067	9

	非标准化系数		标准化系数	t	P	R²	调整R²	F
	B	标准误	Beta	t	P	R²	调整R²	F
常数	-7.829	2.812	-	-2.784	0.108	0.999	0.994	F(7,2) =217.867 Sig F =0.005
lnX₂	0.142	0.385	0.028	0.37	0.747
lnX₃	0.126	0.096	0.045	1.34	0.322
lnX₄	0.052	0.215	0.023	0.243	0.83
lnX₅	0.382	0.283	0.049	1.348	0.31
lnX₆	0.132	0.088	0.07	1.506	0.271
lnX₇	0.916	0.051	1.203	17.974	0.003^**
lnX₈	0.1	0.215	0.042	0.464	0.688

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