烟台海岸带土壤重金属定量源解析及空间预测

doi:10.11821/dlxb202103015

摘要/Abstract

摘要：

定量解析土壤重金属污染来源并绘制空间分布图是土壤重金属调查评价的核心,可为区域土壤环境管理和修复提供科学参考。以中国北方名优农产品生产基地烟台海岸带为研究区,系统开展表层土壤样品采集和重金属分析测试;利用正定矩阵因子分解定量解析土壤重金属的来源贡献;基于独立成分分析和序贯高斯模拟构建多元地统计模拟技术,实现土壤重金属的空间预测及潜在污染区域划定。结果表明：① 研究区表层土壤中 As、Co、Cr、Mn和Ni主要为自然来源,且空间分布受成土母质的控制;② 工业和交通排放是土壤中Cd、Pb和Zn的重要来源,三者在金、铜矿的尾矿区以及烟台市区呈现出污染热点;③ 土壤中Cu主要来自铜基杀菌剂和有机肥施用等农业活动,高值区主要分布在果园土壤;④ 土壤中Hg主要来源于煤炭燃烧和混汞法炼金所排放Hg的大气沉降,高值区主要分布在金矿以及龙口、蓬莱市区周边;⑤ Cu、Hg和Cd的潜在污染区域面积占研究区总面积的37.5%、14.3%和8.6%,应给予重点关注。

关键词: 土壤重金属, 源解析, 空间分布, 地统计模拟, 烟台海岸带

Abstract:

Soil security plays an important role in the sustainable agriculture. With the rapid economic development, the soil quality faces great human-related threats from the contamination, and it is essential to conduct the investigation of heavy metals in soils of the areas with intensive human activities. Source apportionment and spatial prediction are the key issues of the investigation of soil heavy metals pollution, which could provide scientific references for the regional soil pollution management and remediation. For this purpose, a total of 1067 samples were collected in surface soils of Yantai coastal zone, eastern China; and As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, and Zn concentrations were analyzed. Positive matrix factorization (PMF) was applied to estimate source apportionment of heavy metals. Multivariate independent simulation combining Independent Component Analysis (ICA) and Sequential Gaussian Simulation (SGS) were proposed to predict the spatial distributions of heavy metals, and local and spatial uncertainty analysis was used to identify the polluted areas. As, Co, Cr, Mn, and Ni originated from natural sources, with their spatial distributions consistent with parent materials. Cd, Cu, Hg, Pb, and Zn exhibited significant accumulation in soils, but the mean contents of these five heavy metals did not exceed the risk screening values for soil contamination of agricultural land. Industrial and traffic emissions contributed 58.3%, 40.3%, and 35.8% of Cd, Pb, and Zn concentrations, respectively; and these three heavy metals presented high values in gold and copper tailings as well as the urban district of Yantai. Cu mainly came from the application of bordeaux mixture and organic fertilizer, with its high-value hotspots associated with orchard soils. Hg originated from the atmosphere deposition originated from coal combustion and gold smelting by the mixed mercury method, and its high-value hotspots were related to the surrounding of gold mine as well as urban areas of Longkou and Penglai. The potential contaminated areas of Cu, Hg, and Cd accounted for 37.5%, 14.3%, and 8.6% of the total study area, respectively.

Key words: geostatistical simulation, Yantai coastal zone, heavy metals in soils, source apportionment, spatial prediction, geostatistical simulation, Yantai coastal zone

吕建树. 烟台海岸带土壤重金属定量源解析及空间预测[J]. 地理学报, 2021, 76(3): 713-725.

LYU Jianshu. Source apportionment and spatial prediction of heavy metals in soils of Yantai coastal zone[J]. Acta Geographica Sinica, 2021, 76(3): 713-725.

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	As	Cd	Co	Cr	Cu	Hg	Mn	Ni	Pb	Zn	pH
最小值	2.2	0.01	0.6	7.2	1.1	0.006	63	3.6	16.1	6.9	4.66
最大值	99.0	8.27	45.2	206.6	302.1	3.210	1634	144.9	917.6	493.9	9.35
平均值	7.8	0.17	11.2	58.8	32.3	0.078	491	25.3	34.7	68.0	6.76
标准差	6.33	0.28	4.67	23.41	23.91	0.17	153.90	11.87	38.83	26.60	0.95
变异系数	0.82	1.66	0.42	0.40	0.74	2.23	0.31	0.47	1.12	0.39	0.14
偏度	7.69	23.13	1.17	1.40	3.56	9.50	1.61	2.43	19.05	4.85	-0.05
峰度	90.04	647.80	3.94	5.74	25.28	126.58	8.22	16.28	408.44	64.44	-1.07
K-S检验(P)	0.000	0.000	0.002	0.001	0.000	0.000	0.000	0.000	0.000	0.000	0.000
山东东部土壤重金属背景值^[27]	6.3	0.108	11.0	56.2	19.6	0.029	552	23.5	25.4	56.1	-
农用地土壤污染风险筛选值^*	30	0.3	-	200	100	2.4	-	100	120	250	-
第一类建设用地土壤污染风险筛选值	20	20	20	-^**	2000	8	-	150	400	-	-

	As	Cd	Co	Cr	Cu	Hg	Mn	Ni	Pb	Zn	pH
最小值	2.2	0.01	0.6	7.2	1.1	0.006	63	3.6	16.1	6.9	4.66
最大值	99.0	8.27	45.2	206.6	302.1	3.210	1634	144.9	917.6	493.9	9.35
平均值	7.8	0.17	11.2	58.8	32.3	0.078	491	25.3	34.7	68.0	6.76
标准差	6.33	0.28	4.67	23.41	23.91	0.17	153.90	11.87	38.83	26.60	0.95
变异系数	0.82	1.66	0.42	0.40	0.74	2.23	0.31	0.47	1.12	0.39	0.14
偏度	7.69	23.13	1.17	1.40	3.56	9.50	1.61	2.43	19.05	4.85	-0.05
峰度	90.04	647.80	3.94	5.74	25.28	126.58	8.22	16.28	408.44	64.44	-1.07
K-S检验(P)	0.000	0.000	0.002	0.001	0.000	0.000	0.000	0.000	0.000	0.000	0.000
山东东部土壤重金属背景值^[27]	6.3	0.108	11.0	56.2	19.6	0.029	552	23.5	25.4	56.1	-
农用地土壤污染风险筛选值^*	30	0.3	-	200	100	2.4	-	100	120	250	-
第一类建设用地土壤污染风险筛选值	20	20	20	-^**	2000	8	-	150	400	-	-

	模型验证		源成分谱(mg kg^-1)				源贡献率(%)
	R²	预测值/实际值	因子1	因子2	因子3	因子4	因子1	因子2	因子3	因子4
As	1.00	1.00	6.1	1.0	0.5	0.1	79.2	12.6	6.6	1.5
Cd	0.79	0.96	0.06	0.01	0.10	0.00	33.8	58.3	5.7	2.1
Co	0.93	0.98	9.3	0.7	0.8	0.2	85.0	6.2	6.9	1.9
Cr	0.83	0.98	47.9	4.6	3.6	1.3	83.4	8.1	6.4	2.2
Cu	1.00	1.00	9.9	5.7	16.3	0.4	30.7	17.6	50.5	1.2
Hg	1.00	0.98	0.010	0.006	0.003	0.059	12.7	8.1	3.5	75.7
Mn	0.88	0.96	369	66	29	8	78.2	14.0	6.2	1.6
Ni	0.85	0.96	20.8	1.3	1.7	0.5	85.3	5.5	6.9	2.3
Pb	0.83	0.93	15.5	13.1	2.8	1.1	47.7	40.3	8.5	3.5
Zn	0.63	0.94	32.6	23.0	6.8	1.8	50.8	35.8	10.6	2.8

	模型验证		源成分谱(mg kg^-1)				源贡献率(%)
	R²	预测值/实际值	因子1	因子2	因子3	因子4	因子1	因子2	因子3	因子4
As	1.00	1.00	6.1	1.0	0.5	0.1	79.2	12.6	6.6	1.5
Cd	0.79	0.96	0.06	0.01	0.10	0.00	33.8	58.3	5.7	2.1
Co	0.93	0.98	9.3	0.7	0.8	0.2	85.0	6.2	6.9	1.9
Cr	0.83	0.98	47.9	4.6	3.6	1.3	83.4	8.1	6.4	2.2
Cu	1.00	1.00	9.9	5.7	16.3	0.4	30.7	17.6	50.5	1.2
Hg	1.00	0.98	0.010	0.006	0.003	0.059	12.7	8.1	3.5	75.7
Mn	0.88	0.96	369	66	29	8	78.2	14.0	6.2	1.6
Ni	0.85	0.96	20.8	1.3	1.7	0.5	85.3	5.5	6.9	2.3
Pb	0.83	0.93	15.5	13.1	2.8	1.1	47.7	40.3	8.5	3.5
Zn	0.63	0.94	32.6	23.0	6.8	1.8	50.8	35.8	10.6	2.8

变量	模型结构	块金值	结构1		结构2		块金值/总方差
变量	模型结构	块金值	基台值	变程(m)	基台值	变程(m)	块金值/总方差
IC1	Nugget+Spherical+Spherical	0.31	0.26	7195	0.46	29307	0.30
IC2	Nugget+Spherical+Spherical	0.38	0.10	8299	0.47	29457	0.40
IC3	Nugget+Spherical+Spherical	0.46	0.32	13513	0.35	37496	0.41
IC4	Nugget+Spherical+Spherical	0.25	0.59	8674	10.08	1661216	0.02
IC5	Nugget+Spherical	0.68	0.25	18673			0.73
IC6	Nugget+Spherical+Spherical	0.38	0.30	7733	0.28	25534	0.40
IC7	Nugget+Spherical	0.65	2.73	548386			0.19
IC8	Nugget+Spherical	0.26	0.88	19044			0.23
IC9	Nugget+Spherical+Spherical	0.50	0.22	4317	0.30	20506	0.49
IC10	Nugget+Spherical+Spherical	0.55	0.27	7141	0.30	61258	0.49