Temporal and Spatial Characteristics of Net Anthropogenic Nitrogen Input and Its Influencing Factors in the Pearl River Delta

doi:10.16258/j.cnki.1674-5906.2022.08.012

Ecology and Environment ›› 2022, Vol. 31 ›› Issue (8): 1599-1609.DOI: 10.16258/j.cnki.1674-5906.2022.08.012

• Research Articles • Previous Articles Next Articles

Temporal and Spatial Characteristics of Net Anthropogenic Nitrogen Input and Its Influencing Factors in the Pearl River Delta

SU Yongsong¹(), SONG Song¹^,²^,^*(), CHEN Ye³, YE Ziqiang¹, ZHONG Runfei¹, WANG Zhaoyao¹

1. School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, P. R. China
2. Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, P. R. China
3. College of Life Science and Technology, Jinan University, Guangzhou 510632, P. R. China

Received:2021-10-28 Online:2022-08-18 Published:2022-10-10
Contact: SONG Song

珠江三角洲人类活动净氮输入时空特征及其影响因素

苏泳松¹(), 宋松¹^,²^,^*(), 陈叶³, 叶子强¹, 钟润菲¹, 王昭尧¹

1.广州大学地理科学与遥感学院,广东广州 510006
2.南方海洋科学与工程广东省实验室（广州）,广东广州 511458
3.暨南大学生命科学技术学院,广东广州 510632

通讯作者: 宋松
作者简介:苏泳松（1997年生）,男,硕士研究生,研究方向为变化环境下的生态环境响应。E-mail: 2111901028@e.gzhu.edu.cn
基金资助:
广东省自然科学基金项目(2020A1515011065);青年珠江学者资助项目(2019);南方海洋科学与工程广东省实验室（广州）人才团队引进重大专项资助项目(GML2019ZD0301)

Abstract

Abstract:

With the explosive growth of population and the long-term disturbance of intensive industrial and agricultural activities, the Net Artificial Nitrogen Input (NANI) has a profound impact on the health of natural ecosystems. In this paper, we take Pearl River Delta (PRD) urban agglomeration as a case, and construct the NANI model based on the integrated methodology of mathematical statistics, trend investigation, spatial analysis, urban grey water footprint pressure index and geographic detector, using the statistical data from 1996 to 2019. The research aims of this paper are to analyze the temporal and spatial characteristics of NANI, to reveal the component structure of NANI, and to discuss the influencing factors and water environmental pressure caused by NANI in the recent 20 years. The results showed that: (1) NANI in the PRD showed a trend of rapid decline after fluctuation. In the recent 20 years, the overall decline of NANI was about 7.20%; The early NANI input intensity showed an obvious “center-edge” structure. With the passage of time, the NANI input intensity in the core area of the PRD decreased, the NANI input intensity in the edge area increased, and the spatial heterogeneity of NANI decreased. (2) The main input source of NANI in the PRD was food/feed input nitrogen, followed by fertilizer application, while nitrogen fixation of crop and atmospheric deposition nitrogen accounted for a relatively low proportion. Among them, food/feed net nitrogen input and atmospheric deposition nitrogen showed an upward trend, and input nitrogen for fertilizer application and nitrogen fixation of crops showed a downward trend. (3) The proportion of forest land area, population density, chemical fertilizer application intensity, urbanization rate and grassland area were the main influencing factors of NANI in the PRD (P<0.01). The proportion of forest land area and population density were the main land use factors and socio-economic factors affecting NANI in the PRD respectively. (4) NANI in the PRD far exceeded the global and national average, and there was a significant positive correlation between urban grey water footprint pressure index and NANI in prefecture-level cities (P<0.01). High nitrogen input brings severe water environmental pressure. Nitrogen fertilizer reduction, population density control and restriction measures updating are important means to reduce man-made nitrogen load in the PRD.

Key words: net anthropogenic nitrogen input (NANI), Pearl River Delta (PRD), grey water footprint, nitrogen pollution, spatial and temporal characteristics, influencing factors

摘要：

随着人口的爆炸式增长与长期强烈工农业活动的干扰,氮元素的人为输入不断增长并深刻影响自然生态系统健康。该研究以珠江三角洲城市群（简称“珠三角”）为研究对象,基于1997—2019年统计数据,构建人类活动净氮输入（Net Anthropogenic Nitrogen Input,NANI）模型,运用数理统计、趋势分析、空间分析、城市灰水足迹压力指数及地理探测器等多种分析相结合的方法,探讨近20 a珠三角地区人类活动影响下氮输入的时空特征、组分结构、影响因素及其带来的水体环境压力等。研究结果表明,（1）珠三角地区NANI呈现出波动上升后迅速下降的趋势,近20 a来,NANI总体下降幅度约为7.20%;早期NANI输入强度呈现较为明显的“中心—边缘”结构,随着时间的推移,珠三角核心区NANI输入强度减弱、边缘地区NANI输入强度增强,NANI空间异质性减弱。（2）珠三角地区NANI主要输入源为食物/饲料净氮输入,其次为化肥施用氮,而作物固氮及大气沉降氮占比较低,其中食物/饲料净氮输入与大气沉降氮呈现上升的趋势,化肥施用氮与作物固氮呈现出下降的趋势。（3）林地面积占比、人口密度、化肥施用强度、城镇化率、草地面积占比为珠三角地区NANI主要影响因子（P<0.01）,其中林地面积占比与人口密度分别为影响珠三角地区NANI的首要土地利用因素与社会经济因素。（4）珠三角地区NANI远超全球与全国平均值,各地级市城市灰水足迹压力指数与NANI呈现显著的正相关关系（P<0.01）。高强度人类活动影响下氮输入带来严峻的水环境压力,减少氮肥使用、控制人口密度、更新管控措施是降低珠三角人为氮负荷的重要手段。

关键词: 人类活动净氮输入, 珠江三角洲, 灰水足迹, 氮污染, 时空特征, 影响因素

CLC Number:

X501

SU Yongsong, SONG Song, CHEN Ye, YE Ziqiang, ZHONG Runfei, WANG Zhaoyao. Temporal and Spatial Characteristics of Net Anthropogenic Nitrogen Input and Its Influencing Factors in the Pearl River Delta[J]. Ecology and Environment, 2022, 31(8): 1599-1609.

苏泳松, 宋松, 陈叶, 叶子强, 钟润菲, 王昭尧. 珠江三角洲人类活动净氮输入时空特征及其影响因素[J]. 生态环境学报, 2022, 31(8): 1599-1609.

Figures/Tables 14

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输入项 Input item	计算方法 Method of calculation	公式说明 Formula description	计量单位 Unit
人类活动净氮输入 Net anthropogenic nitrogen input (N_NANI)	N_NANI=N_Fe+N_H/L+N_De+N_NF	N_Fe——化肥施用氮量; N_H/L——食物/饲料输入氮量; N_De——大气氮沉降输入氮量; N_NF——作物固氮输入氮量	kg∙km^-2∙a^-1
化肥施用氮 Input nitrogen for fertilizer application (N_Fe)	N_Fe=100%×N_Nf+32.2% (张卫峰等, 2009; 徐浩林等, 2020)×N_Cf	N_Nf——氮肥施用量 (折纯); N_Cf——复合肥施用量 (折纯)	kg∙km^-2∙a^-1
食物/饲料输入氮 Food/feed input nitrogen (N_H/L)	N_H/L=N_Hu+N_Li-N_LiP-N_CP 式中： N_Hu——常住人口数×4.39 (武淑霞, 2005); N_Li——禽畜养殖存栏量/出栏量×不同禽畜个体摄入饲料氮量; N_LiP(N_CP)——90% (Van Horn, 1998; 韩玉国等, 2011; 徐浩林等, 2020)×禽畜 (作物) 产品产量×不同禽畜 (作物) 产品含氮量	N_Hu——人类摄入食物氮量; N_Li——禽畜摄入饲料氮量; N_LiP——禽畜产品产氮量; N_CP——作物产品产氮量; 当N_H/L>0时,为净输入,反之为净输出	kg∙km^-2∙a^-1

输入项 Input item	计算方法 Method of calculation	公式说明 Formula description	计量单位 Unit
人类活动净氮输入 Net anthropogenic nitrogen input (N_NANI)	N_NANI=N_Fe+N_H/L+N_De+N_NF	N_Fe——化肥施用氮量; N_H/L——食物/饲料输入氮量; N_De——大气氮沉降输入氮量; N_NF——作物固氮输入氮量	kg∙km^-2∙a^-1
化肥施用氮 Input nitrogen for fertilizer application (N_Fe)	N_Fe=100%×N_Nf+32.2% (张卫峰等, 2009; 徐浩林等, 2020)×N_Cf	N_Nf——氮肥施用量 (折纯); N_Cf——复合肥施用量 (折纯)	kg∙km^-2∙a^-1
食物/饲料输入氮 Food/feed input nitrogen (N_H/L)	N_H/L=N_Hu+N_Li-N_LiP-N_CP 式中： N_Hu——常住人口数×4.39 (武淑霞, 2005); N_Li——禽畜养殖存栏量/出栏量×不同禽畜个体摄入饲料氮量; N_LiP(N_CP)——90% (Van Horn, 1998; 韩玉国等, 2011; 徐浩林等, 2020)×禽畜 (作物) 产品产量×不同禽畜 (作物) 产品含氮量	N_Hu——人类摄入食物氮量; N_Li——禽畜摄入饲料氮量; N_LiP——禽畜产品产氮量; N_CP——作物产品产氮量; 当N_H/L>0时,为净输入,反之为净输出	kg∙km^-2∙a^-1

养殖禽畜类型 Livestock type	氮产品消耗量 Nitrogen product consumption/ (kg∙a^-1)	排泄系数 Excretion coefficient/ %	氮产品消耗总量 Total consumption of nitrogen products/ (kg∙a^-1)
猪 Pig	11.51	69	16.68
牛 Cattle	48.79	89	54.82
羊 Goat	5.75	84	6.85
家禽 Poultry	0.40	68	0.59

养殖禽畜类型 Livestock type	氮产品消耗量 Nitrogen product consumption/ (kg∙a^-1)	排泄系数 Excretion coefficient/ %	氮产品消耗总量 Total consumption of nitrogen products/ (kg∙a^-1)
猪 Pig	11.51	69	16.68
牛 Cattle	48.79	89	54.82
羊 Goat	5.75	84	6.85
家禽 Poultry	0.40	68	0.59

禽畜产品类型 Livestock products	含氮量 Nitrogen content/%	作物产品类型 Crop	含氮量 Nitrogen content/%
猪肉 Pork	2.13	大豆 Soybean	5.52
牛肉 Beef	2.89	甘蔗 sugarcane	0.06
羊肉 Mutton	3.01	柑桔橙 Orange	0.17
家禽肉 Domestic poultry meat	2.78	花生 Peanut	1.93
禽蛋类 Poultry and eggs	1.98	荔枝 Litchi chinensis	0.14
奶类 Dairy	0.49	薯类 Tubers	0.20
水产品 Aquatic product	2.65	蔬菜 Vegetables	0.35
		水稻 Rice	1.19
		香蕉 Banana	0.22

Temporal and Spatial Characteristics of Net Anthropogenic Nitrogen Input and Its Influencing Factors in the Pearl River Delta

珠江三角洲人类活动净氮输入时空特征及其影响因素

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作物类型 Crop	固氮系数 Nitrogen fixation coefficient/(kg∙km^-2∙a^-1)
大豆 Soybean	9600
花生 Peanut	8000
水稻 Rice	3000
薯类 Tubers	1500

城市 City	人均NANI Per capita net anthropogenic nitrogen input/(kg∙person^-1∙a^-1)			人口密度 Population density/ (person∙km^-2)
城市 City	1997-1999	2007-2009	2017-2019	1997-1999	2007-2009	2017-2019
广州Guangzhou	23.77	15.59	9.38	1254.64	1542.83	2055.78
深圳Shenzhen	8.79	5.81	4.87	2904.74	4775.47	6466.43
珠海Zhuhai	20.08	12.64	6.57	624.87	869.09	1090.38
佛山Foshan	23.57	19.25	11.11	1263.06	1733.13	2082.04
惠州Huizhou	34.24	29.64	25.49	265.44	369.13	425.56
东莞Dongguan	13.77	6.17	4.98	2031.55	3053.69	3414.41
中山Zhongshan	17.10	11.66	5.76	1168.00	1583.18	1859.46
江门Jiangmen	39.05	36.36	33.84	405.36	451.05	483.51
肇庆Zhaoqing	54.19	63.14	55.58	224.07	255.79	278.78

类别 Category	影响因子 Impact factors		单位 Unit	q值 q value	q值排序 q-value sorting
社会经济因素 Socio-economic Factors	X₁	人口密度	person∙km^-2	0.408**	2
	X₂	粮食作物产量	t∙km^-2	0.222*	6
	X₃	单位农业产值	10⁸ yuan∙km^-2	0.029	10
	X₄	化肥施用强度	t∙km^-2	0.364**	3
	X₅	水果产量	t∙km^-2	0.079	9
	X₆	城镇化率	%	0.356**	4
土地利用因素 Land use factors	X₇	耕地面积占比	%	0.116	8
	X₈	林地面积占比	%	0.484**	1
	X₉	草地面积占比	%	0.281**	5
	X₁₀	居民、工矿、城市用地面积占比	%	0.208*	7

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