Source Analysis of Soil Heavy Metals Based on Multivariate Statistical Analysis and PMF Model: A Case Study of Sanjiangyuan

doi:10.16258/j.cnki.1674-5906.2026.03.012

Ecology and Environmental Sciences ›› 2026, Vol. 35 ›› Issue (3): 458-468.DOI: 10.16258/j.cnki.1674-5906.2026.03.012

• Research Article [Environmental Science] • Previous Articles Next Articles

Source Analysis of Soil Heavy Metals Based on Multivariate Statistical Analysis and PMF Model: A Case Study of Sanjiangyuan

ZHANG Yukun¹^,²^,³^,⁴(), CHEN Dongdong¹^,²^,³^,⁴, LI Qi¹^,²^,³^,⁴, HE Fuquan¹^,²^,³^,⁴, ZHANG Li¹^,²^,³^,⁴, ZHAO Liang¹^,²^,³^,⁴^,^*()

1. Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, P. R. China
2. Key Laboratory of Plateau Adaptation and Evolution, Chinese Academy of Sciences, Xining 810008, P. R. China
3. Sanjiangyuan National Park Research Institute, Chinese Academy of Sciences, Xining 810008, P. R. China
4. Qinghai Sanjiangyuan Grassland Ecosystem National Field Scientific Observation and research Station, Xining 810008, P. R. China

Received:2025-05-28 Revised:2025-09-17 Accepted:2025-11-11 Online:2026-03-18 Published:2026-03-13

基于多元统计分析和PMF模型的土壤重金属源解析——以三江源为例

张煜坤¹^,²^,³^,⁴(), 陈懂懂¹^,²^,³^,⁴, 李奇¹^,²^,³^,⁴, 贺福全¹^,²^,³^,⁴, 张莉¹^,²^,³^,⁴, 赵亮¹^,²^,³^,⁴^,^*()

1.中国科学院西北高原生物研究所，青海西宁 810008
2.中国科学院高原生物适应与进化重点实验室，青海西宁 810008
3.中国科学院三江源国家公园研究院，青海西宁 810008
4.青海三江源草地生态系统国家野外科学观测研究站，青海西宁 810008

通讯作者: *E-mail: lzhao@nwipb.cas.cn
作者简介:张煜坤（1994年生），男，工程师，硕士，研究方向为生态环境保护。E-mail: zhangyukun@nwipb.cas.cn
基金资助:
青海省“帅才科学家”项目(2024-SF-102)

Abstract

Abstract:

Soil heavy metal pollution is become a significant concern in the Sanjiangyuan region. To investigate the characteristics of heavy metal pollution in the 0‒20 cm soil layer and identify the primary sources of this pollution, this study measured the concentrations of five heavy metal elements: lead (Pb), cadmium (Cd), chromium (Cr), arsenic (As), and mercury (Hg). The analysis incorporated Spatial interpolation, correlation analysis, principal component analysis (PCA), and positive matrix factorization (PMF) were used to identify the sources of heavy metals in soils. 1) The results indicate that chromium (Cr) and arsenic (As) levels in the soil of the southern and eastern regions of Sanjiangyuan have reached mild pollution levels, while mercury (Hg) has reached moderate pollution levels. The higher potential ecological hazard index (PEHI) and integrated pollution index (IPI) were primarily concentrated in the southern and certain eastern areas. Furthermore, the spatial distributions of PEHI and IPI were consistent across different soil layers. 2) Lead (Pb) and arsenic (As) in the 0‒20 cm soil layer were primarily influenced by traffic emissions and fuel combustion sources, whereas mercury (Hg), chromium (Cr), and cadmium (Cd) were affected by a combination of anthropogenic activities, soil parent material, industrial waste, and agricultural fertilizer sources. Among these factors, traffic emissions and fuel combustion accounted for the highest average explanatory value (32.1%), whereas industrial waste and agricultural fertilizers contributed the lowest average explanatory value (15.8%). 3) Anthropogenic disturbance factors accounted for over 70% of the heavy metal concentrations in the 0‒20 cm soil layer. As soil depth increased, the contribution of soil matrices to heavy metal concentrations became more significant, whereas the contribution from anthropogenic disturbances decreased. Notably, Hg, Pb, and Cd in various soil layers were primarily derived from anthropogenic activities, whereas As and Cr in the 10‒20 cm layer appeared to originate primarily from soil matrices. The heavy metal content of soils in the Sanjiangyuan region is mainly affected by anthropogenic disturbances, and there is a risk of increased Hg pollution in the future. Therefore, it is essential to enhance regulations on traffic emissions and fuel combustion in southern and eastern Sanjiangyuan regions. Additionally, it is crucial to raise awareness regarding the prevention and control of chromium (Cr), arsenic (As), and mercury (Hg) pollution in the northern regions of Maduo, Hoh Xil, and Zhiduo.

Key words: Sanjiangyuan, heavy metal pollution, positive matrix factorization, source resolution, anthropogenic interference

摘要：

土壤重金属污染已逐渐成为三江源范围内关注的问题。为探究0－20 cm土壤重金属污染特征及主要污染源，测定了5种重金属元素的含量（Pb、Cd、Cr、As、Hg），结合空间插值分析、相关性分析、PCA分析和正定矩阵因子分解（PMF）模型进行土壤重金属的来源解析。结果表明，1）三江源南部和东部地区土壤中的Cr、As达到轻度污染，Hg达到中度污染，潜在生态危害指数和综合污染指数较高的区域主要集中在南部和部分东部地区，不同土层的潜在生态危害指数和综合污染指数空间分布具有一致性。2）0－20 cm土层的Pb和As受交通排放和燃料燃烧来源的影响，Hg、Cr、Cd分别受人为活动、土壤母质、工业废料及农业肥料来源的影响。其中，交通排放和燃料燃烧的解释度最高平均为32.1%，工业废料及农业肥料解释度最低平均为15.8%。3）人为干扰因素对0－20 cm土层的重金属解释度均超过70%，随着土层深度的增加，土壤母质对重金属的解释度增大，人为干扰对对重金属的解释度降低，不同土层的Hg、Pb、Cd可能更多来源于人为活动，而10－20 cm的As和Cr可能更多来源于土壤母质。三江源区域土壤重金属含量主要受人为干扰因素的影响并存在Hg污染加重的风险，应加强对三江源南部和东部区域交通排放和燃料燃烧的监管以及加强玛多、可可西里、治多等北部地区Cr、As、Hg的污染防控。

关键词: 三江源, 重金属污染, PMF模型, 源解析, 人为干扰

CLC Number:

ZHANG Yukun, CHEN Dongdong, LI Qi, HE Fuquan, ZHANG Li, ZHAO Liang. Source Analysis of Soil Heavy Metals Based on Multivariate Statistical Analysis and PMF Model: A Case Study of Sanjiangyuan[J]. Ecology and Environmental Sciences, 2026, 35(3): 458-468.

张煜坤, 陈懂懂, 李奇, 贺福全, 张莉, 赵亮. 基于多元统计分析和PMF模型的土壤重金属源解析——以三江源为例[J]. 生态环境学报, 2026, 35(3): 458-468.

Figures/Tables 12

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E		R		生态风险级别
分级标准范围	本研究	分级标准范围	本研究	生态风险级别
<40	<40	<150	<100	轻微风险
40－80	40－80	150－300	100－200	中等风险
80－160	80－160	300－600	200－400	较强风险
160－320	160－320	≥600	≥400	很强风险
≥320	≥320	－	－	极强风险

E		R		生态风险级别
分级标准范围	本研究	分级标准范围	本研究	生态风险级别
<40	<40	<150	<100	轻微风险
40－80	40－80	150－300	100－200	中等风险
80－160	80－160	300－600	200－400	较强风险
160－320	160－320	≥600	≥400	很强风险
≥320	≥320	－	－	极强风险

分布方位	采样点	w_(Pb)/(mg∙kg⁻¹)		w_(Cd)/(mg∙kg⁻¹)		w_(Cr)/(mg∙kg⁻¹)		w_(As)/(mg∙kg⁻¹)		w_(Hg)/(mg∙kg⁻¹)
分布方位	土壤深度/cm	0－10	10－20	0－10	10－20	0－10	10－20	0－10	10－20	0－10	10－20
北部	QML	6.32	6.73	0.051	0.04	39.63	39.12	10.11	10.3	0.02	0.014
	WDL	7.17	6.85	0.032	0.041	17.32	19.68	7.11	6.56	0.021	0.016
	ZD	9.45	9.72	0.066	0.07	37.16	37.52	10.82	11.84	0.051	0.019
	KKXL	4.68	4.69	0.021	0.025	14.5	16.63	8.63	9.03	0.011	0.0051
	MD	8.64	8.71	0.044	0.047	40.5	39.17	12.53	14.81	0.016	0.012
	ELH	14.11	13.85	0.029	0.021	31.21	33.25	20.21	20.81	0.014	0.009
南部	YS	26.93	25.36	0.24	0.29	72.84	73.15	20.95	21.22	0.056	0.041
	JZ	11.67	12.45	0.073	0.077	58.63	58.43	13.13	13.6	0.045	0.035
	CD	9.24	10.24	0.047	0.054	53.26	47.76	12.91	15.9	0.066	0.049
	BM	10.73	10.41	0.069	0.069	56.3	56.71	13.05	12.9	0.033	0.028
	NQ	10.76	10.16	0.096	0.099	27.56	28.16	13.48	13.7	0.035	0.031
	BT	12.33	12.33	0.063	0.063	55.52	55.58	14.11	14.1	0.049	0.039
	MQ	9.41	9.56	0.063	0.069	46.52	48.52	11.82	11.5	0.032	0.028
东部	XH	9.41	9.41	0.064	0.054	39.6	39.67	8.91	8.91	0.028	0.023
	ZK	23.21	20.85	0.14	0.08	63.15	62.25	28.95	29.12	0.017	0.013
	GH	20.08	16.86	0.14	0.08	46.22	47.58	14.38	15.32	0.062	0.041
	HN	10.13	9.43	0.08	0.06	50.26	48.56	12.53	13.02	0.032	0.032
	GN	19.11	18.97	0.11	0.07	45.03	44.32	11.03	12.98	0.039	0.028

分布方位	采样点	w_(Pb)/(mg∙kg⁻¹)		w_(Cd)/(mg∙kg⁻¹)		w_(Cr)/(mg∙kg⁻¹)		w_(As)/(mg∙kg⁻¹)		w_(Hg)/(mg∙kg⁻¹)
分布方位	土壤深度/cm	0－10	10－20	0－10	10－20	0－10	10－20	0－10	10－20	0－10	10－20
北部	QML	6.32	6.73	0.051	0.04	39.63	39.12	10.11	10.3	0.02	0.014
	WDL	7.17	6.85	0.032	0.041	17.32	19.68	7.11	6.56	0.021	0.016
	ZD	9.45	9.72	0.066	0.07	37.16	37.52	10.82	11.84	0.051	0.019
	KKXL	4.68	4.69	0.021	0.025	14.5	16.63	8.63	9.03	0.011	0.0051
	MD	8.64	8.71	0.044	0.047	40.5	39.17	12.53	14.81	0.016	0.012
	ELH	14.11	13.85	0.029	0.021	31.21	33.25	20.21	20.81	0.014	0.009
南部	YS	26.93	25.36	0.24	0.29	72.84	73.15	20.95	21.22	0.056	0.041
	JZ	11.67	12.45	0.073	0.077	58.63	58.43	13.13	13.6	0.045	0.035
	CD	9.24	10.24	0.047	0.054	53.26	47.76	12.91	15.9	0.066	0.049
	BM	10.73	10.41	0.069	0.069	56.3	56.71	13.05	12.9	0.033	0.028
	NQ	10.76	10.16	0.096	0.099	27.56	28.16	13.48	13.7	0.035	0.031
	BT	12.33	12.33	0.063	0.063	55.52	55.58	14.11	14.1	0.049	0.039
	MQ	9.41	9.56	0.063	0.069	46.52	48.52	11.82	11.5	0.032	0.028
东部	XH	9.41	9.41	0.064	0.054	39.6	39.67	8.91	8.91	0.028	0.023
	ZK	23.21	20.85	0.14	0.08	63.15	62.25	28.95	29.12	0.017	0.013
	GH	20.08	16.86	0.14	0.08	46.22	47.58	14.38	15.32	0.062	0.041
	HN	10.13	9.43	0.08	0.06	50.26	48.56	12.53	13.02	0.032	0.032
	GN	19.11	18.97	0.11	0.07	45.03	44.32	11.03	12.98	0.039	0.028

重金属元素	本研究区			青藏高原其他地区土壤重金属质量分数/（mg∙kg⁻¹）
重金属元素	总样点	南部	北部	青海省背景值（郭立本等，1995）	青藏高原东北部（李雷明，2020）	青藏高原东北-西南（杨安等，2020）	环青海湖（卫佩茹，2020）	青海湖流域表土（王平等，2010）	青海省重要交通沿线（安思危，2021）	一江两河（王伟鹏等，2020）	青海木里煤矿（王佟等，2022）
Pb	9.36	12.97	8.41	20.9	72.49	28.65	21.86	20.47	32.91	35.81	240
Cd	0.06	0.1	0.04	0.14	0.68	0.17	0.62	－	0.19	0.21	0.81
Cr	45.75	52.78	30.47	70.1	83.11	70.84	41.35	54.17	74.62	82.95	350.02
As	11.69	14.45	11.89	14.00	－	－	11.73	11.66	21.61	－	20.01
Hg	0.03	0.041	0.017	0.021	0.28	0.029	0.031	0.035	0.05	0.022	1.00

Source Analysis of Soil Heavy Metals Based on Multivariate Statistical Analysis and PMF Model: A Case Study of Sanjiangyuan

基于多元统计分析和PMF模型的土壤重金属源解析——以三江源为例

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指标	富集因子指数										潜在生态风险指数
重金属元素	Pb		Cd		Cr		As		Hg		－
土壤深度/cm	0－10	10－20	0－10	10－20	0－10	10－20	0－10	10－20	0－10	10－20	0－10	10－20
QML	0.49	0.58	0.61	0.53	0.92	0.92	1.07	1.07	1.88	1.31	59.50	47.27
MQ	0.56	0.57	0.59	0.64	0.83	0.86	1.08	1.13	1.89	1.47	71.06	60.80
ZD	0.66	0.68	0.75	0.8	0.78	0.78	1.25	1.32	1.77	1.28	82.50	55.54
JZ	0.81	0.84	0.84	0.87	0.92	0.92	1.35	1.43	2.7	2.19	81.29	70.03
CD	0.65	0.72	0.53	0.61	0.91	1.00	1.55	1.59	3.81	3.37	112.46	75.72
NQ	0.75	0.71	0.96	0.94	0.58	0.59	1.37	1.41	1.93	1.84	83.61	70.76
BT	0.86	0.86	0.71	0.71	1.06	1.16	1.46	1.46	3.94	3.94	121.03	99.42
HN	0.71	0.73	0.91	0.71	0.95	0.91	1.33	1.33	1.92	1.58	96.73	64.00
XH	0.66	0.66	0.73	0.73	0.83	0.83	0.98	0.98	1.94	1.94	65.46	59.19
BM	0.75	0.73	0.79	0.79	1.07	1.18	1.19	1.2	2.17	2	80.67	74.18
KKXL	0.53	0.53	0.38	0.45	0.49	0.56	0.99	1.05	0.84	0.66	26.16	28.10
MD	0.58	0.58	0.78	0.84	0.81	0.78	1.18	1.35	1.19	0.85	50.78	45.92
GN	0.75	0.72	0.97	0.95	0.85	0.86	1.08	1.06	1.13	1.05	107.57	100.62
GH	0.92	0.87	0.77	0.75	1.26	1.35	1.26	1.28	1.29	1.09	138.07	127.19
WDL	0.43	0.42	0.32	0.39	0.49	0.51	0.75	0.69	0.71	0.59	27.34	24.49
ELH	0.52	0.53	0.41	0.42	0.52	0.53	0.92	0.88	0.79	0.69	52.43	49.56
YS	0.88	0.89	0.73	0.72	1.02	1.09	1.41	1.52	3.15	3.01	168.74	151.08
ZK	0.86	0.88	0.93	0.91	0.63	0.77	1.05	1.12	1.68	1.55	109.84	105.43

土壤深度/cm	主成分	特征值	方差	累积方差
0－10	1	3.11	62.20	62.19
	2	0.79	15.85	78.05
	3	0.49	9.87	87.92
	4	0.42	8.39	96.30
	5	0.19	3.70	100.00
10－20	1	3.20	64.95	63.95
	2	0.79	15.59	79.74
	3	0.53	10.61	90.35
	4	0.36	7.25	97.61
	5	0.12	2.39	100.00

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