珠三角某遗留造船厂场地土壤重金属人体健康风险评估及源解析

doi:10.16258/j.cnki.1674-5906.2023.04.017

生态环境学报 ›› 2023, Vol. 32 ›› Issue (4): 794-804.DOI: 10.16258/j.cnki.1674-5906.2023.04.017

珠三角某遗留造船厂场地土壤重金属人体健康风险评估及源解析

陈敏毅¹(), 朱航海², 佘伟铎¹, 尹光彩², 黄祖照¹, 杨巧玲¹^,^*

1.广州市环境技术中心，广东广州 510235
2.广东工业大学环境科学与工程学院，广东广州 510650

收稿日期:2022-10-13 出版日期:2023-04-18 发布日期:2023-07-12
通讯作者: *杨巧玲（1985年生），女，高级工程师，硕士，研究方向为环境管理。
作者简介:陈敏毅（1971年生），男，高级工程师，研究方向为环境管理、土壤污染防治。E-mail: 13922231391@163.com
基金资助:
广州市科技计划项目(202103000018)

Health Risk Assessment and Source Apportionment of Soil Heavy Metals at A Legacy Shipyard Site in Pearl River Delta

CHEN Minyi¹(), ZHU Hanghai², SHE Weiduo¹, YIN Guangcai², HUANG Zuzhao¹, YANG Qiaoling¹^,^*

1. Guangzhou Environmental Technology Center, Guangzhou 510235, P. R. China
2. School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510650, P. R. China

Received:2022-10-13 Online:2023-04-18 Published:2023-07-12

摘要/Abstract

摘要：

土壤重金属的人体健康风险评估和源解析是场地污染控制和风险防范的关键。以珠三角某造船厂场地土壤为研究对象，采集造船厂场地169个50 cm深度的表层土壤样品，测定土壤pH值及8种重金属Cu、Pb、Zn、Cd、Ni、Cr、Hg和As的含量；用反距离权重插值法（IDW）探究造船厂土壤重金属的空间分布规律，通过美国环保署（USEPA）推荐的人体健康风险评估方法量化不同人群暴露于造船厂土壤重金属的人体健康风险，并用主成分分析-多元线性回归模型（PCA-MLR）定量解析土壤重金属的来源。结果表明：（1）土壤重金属Pb、Hg和As在部分点位的含量超过一类建设用地风险筛选值，人体健康风险评估表明造船厂土壤重金属存在不同程度的非致癌和致癌风险，且Pb和As是主要贡献因子；（2）土壤Cu、Zn和As的高值出现在造船坞和涂装车间，土壤Ni和Cr高值出现在管加新车间；（3）PCA-MLR模型源解析表明造船厂场地土壤重金属来源主要有3种：Cu、Zn、As和少部分的Cd来源于船体加工过程，Ni、Cr和少部分Cd来源于自然源和管加新车间钢材的加工、堆放，Pb和Hg来源于造船厂内部的交通运输过程，上述3种来源贡献率分别为60.8%、14.8%、24.4%。为降低造船厂土壤重金属污染引起的人体健康风险，建议加强造船坞和涂装车间以及管加新车间等重点区域土壤Cu、Zn、As、Cr等污染物的风险管控。

关键词: 遗留造船厂场地, 土壤重金属, 人体健康风险评估, 主成分分析-多元线性回归模型

Abstract:

The health risk assessment and source apportionment of soil heavy metals are important for site pollution control and risk prevention. In this study, a total of 169 surface soil samples (0-50 cm) were collected and eight soil heavy metal contents (Cu, Pb, Zn, Cd, Ni, Cr, Hg and As) were measured in a legacy shipyard site in Pearl River Delta, China. The inverse distance weighted interpolation (IDW) was used to explore the spatial distribution of soil heavy metals in the shipyard site, and the human health risk assessment method recommended by the United States Environmental Protection Agency (USEPA) was used to quantify the health risk of different populations exposed to soil heavy metals. Principal component analysis combined with multiple linear regression (PCA-MLR) model was applied to analyze the main sources of soil heavy metals quantitatively. It showed that (1) the contents of soil heavy metals, Pb, Hg and As, exceeded the risk screening value of the first type residential constructed land. The human health risk assessment showed that the shipyard had different degrees of non-carcinogenic and carcinogenic risks, and Pb and As were the main contributing factors. (2) Relatively high values of Cu, Zn and As were found in shipyards manufacturing and painting workshops, and Ni and Cr in the pipe plus new workshop. (3) There were three main sources of soil heavy metals in the shipyard site. Cu, Zn, As and a small amount of Cd were derived from ship-making processes, Ni, Cr and a small amount of Cd from natural sources and stacking of steel in the pipe plus new workshop; Pb and Hg mainly originated from the transportation process inside the shipyard. According to the PCA-MLR model, the contribution rate of the above mentioned three sources was 60.8%, 14.8%, and 24.4%, respectively. The health risks from the soil heavy metals, such as Cu, Zn, As, Cr, should be paid special attention to in the ship-making workshop and pipe plus new workshop inside the shipyard site.

Key words: Legacy shipyard, Soil heavy metals, Health Risk assessment, Principal component analysis combined with multiple linear regression model

中图分类号:

X53
X820.4

陈敏毅, 朱航海, 佘伟铎, 尹光彩, 黄祖照, 杨巧玲. 珠三角某遗留造船厂场地土壤重金属人体健康风险评估及源解析[J]. 生态环境学报, 2023, 32(4): 794-804.

CHEN Minyi, ZHU Hanghai, SHE Weiduo, YIN Guangcai, HUANG Zuzhao, YANG Qiaoling. Health Risk Assessment and Source Apportionment of Soil Heavy Metals at A Legacy Shipyard Site in Pearl River Delta[J]. Ecology and Environment, 2023, 32(4): 794-804.

图/表 14

图1 土壤采样点分布

Figure 1 Distribution of soil sampling site

表1 人体健康风险评价计算参数

Table 1 Parameter values of the model for probabilistic risk assessment

参数	单位	儿童	成人
暴露频率 (F)	d∙a⁻¹	180
口腔摄入速率 (R_i)	mg∙d⁻¹	100	200
皮肤接触速率 (S)	mg∙cm⁻²	0.200
呼吸吸入速率 (R_n)	m³∙d⁻¹	7.63	14.7
暴露时间 (t)	a	6	24
重金属排放因子 (p)	m³∙kg	1.36×10⁹	1.36×10⁹
平均体质量 (m)	kg	15.9	62.0
接触污染土壤的平均暴露时间 (d)	d	365×t (非致癌) 365×70 (致癌)
暴露的皮肤面积 (G)	cm²	2.80×10³	1.60×10⁴
皮肤吸收系数 (E)	‒	0.001 (非致癌) 0.01 (致癌)

表2 非致癌慢性参考剂量（Rf）和致癌斜率系数（Sf）参考值

Table 2 Corresponding reference dose (Rf) and slope factors (Sf)

重金属	R_f/(mg∙kg⁻¹∙d⁻¹ $)$			S_f/(kg∙d∙mg⁻¹)
重金属	口腔摄入	呼吸吸入	皮肤接触	口腔摄入	呼吸吸入	皮肤接触
Cu	4.00×10⁻²	4.02×10⁻²	1.20×10⁻²	‒ ¹⁾	‒	‒
Ni	2.00×10⁻²	2.06×10⁻²	5.40×10⁻³	‒	0.84	‒
Pb	3.50×10⁻³	3.52×10⁻³	5.25×10⁻⁴	8.50×10⁻³	－	‒
Cd	1.00×10⁻³	1.00×10⁻⁵	1.00×10⁻⁵	6.10	6.30	20.0
As	3.00×10⁻⁴	1.23×10⁻⁴	1.23×10⁻⁴	1.50	15.1	3.66
Hg	3.00×10⁻⁴	8.57×10⁻⁵	2.10×10⁻⁵	‒	‒	‒

表2 非致癌慢性参考剂量（Rf）和致癌斜率系数（Sf）参考值

Table 2 Corresponding reference dose (Rf) and slope factors (Sf)

重金属	R_f/(mg∙kg⁻¹∙d⁻¹ $)$			S_f/(kg∙d∙mg⁻¹)
重金属	口腔摄入	呼吸吸入	皮肤接触	口腔摄入	呼吸吸入	皮肤接触
Cu	4.00×10⁻²	4.02×10⁻²	1.20×10⁻²	‒ ¹⁾	‒	‒
Ni	2.00×10⁻²	2.06×10⁻²	5.40×10⁻³	‒	0.84	‒
Pb	3.50×10⁻³	3.52×10⁻³	5.25×10⁻⁴	8.50×10⁻³	－	‒
Cd	1.00×10⁻³	1.00×10⁻⁵	1.00×10⁻⁵	6.10	6.30	20.0
As	3.00×10⁻⁴	1.23×10⁻⁴	1.23×10⁻⁴	1.50	15.1	3.66
Hg	3.00×10⁻⁴	8.57×10⁻⁵	2.10×10⁻⁵	‒	‒	‒

表3 土壤重金属质量分数描述性统计

Table 3 Descriptive statistics mass fraction of soil heavy metals

重金属	最小值/(mg∙kg⁻¹)	最大值/(mg∙kg⁻¹)	均值/(mg∙kg⁻¹)	标准偏差	偏度	峰度	变异系数/%	一类建设用地风险筛选值/(mg∙kg⁻¹)
Cu	8.00	1.39×10³	1.02×10²	1.86×10²	5.45	33.6	1.82	2.00×10³
Pb	14.6	4.70×10³	2.19×10²	4.53×10²	6.64	58.3	2.07	4.00×10²
Zn	19.0	7.48×10³	3.84×10²	7.59×10²	6.48	52.5	1.98	1.50×10⁴
Cd	0.01	16.6	0.59	1.34	10.3	12.1	2.27	20.0
Ni	4.0	79.0	18.7	11.1	2.56	9.33	0.60	11.5×10²
Cr	5.00	2.40×10²	55.9	36.7	2.81	12.0	0.55	7.51×10⁴
Hg	0.016	14.4	0.67	1.59	7.39	60.3	2.37	8.00
As	0.21	1.10×10²	12.6	14.4	4.14	22.0	1.14	60.0
pH	5.35	11.9	8.47	0.94	−0.08	1.52	0.11	‒

图2 土壤重金属质量分数

Figure 2 Mass fraction of soil heavy metals

图3 土壤重金属空间分布

Figure 3 Spatial distribution of soil heavy metals

表4 重金属非致癌健康风险指数

Table 4 Human non-carcinogenic health risk assessment of heavy metals

项目	人群	As	Cd	Cu	Pb	Hg	Ni	Zn	Cr
口服摄入	儿童	0.261	3.66×10⁻³	1.59×10⁻²	0.389	1.38×10⁻²	5.79×10⁻³	7.93×10⁻³	0.115
口服摄入	成人	3.34×10⁻²	4.70×10⁻⁴	2.03×10⁻³	4.99×10⁻²	1.77×10⁻³	7.43×10⁻⁴	1.02×10⁻³	1.48×10⁻²
皮肤接触	儿童	1.78×10⁻³	1.03×10⁻³	1.48×10⁻⁴	7.26×10⁻³	5.52×10⁻⁴	6.01×10⁻⁵	1.11×10⁻⁴	1.62×10⁻²
皮肤接触	成人	2.61×10⁻³	1.50×10⁻³	2.17×10⁻⁴	1.06×10⁻²	8.09×10⁻⁴	8.80×10⁻⁵	1.63×10⁻⁴	2.37×10⁻²
呼吸吸入	儿童	1.78×10⁻⁵	1.03×10⁻⁵	4.43×10⁻⁷	1.08×10⁻⁵	1.36×10⁻⁶	1.58×10⁻⁷	2.22×10⁻⁷	3.40×10⁻⁴
呼吸吸入	成人	8.82×10⁻⁶	5.08×10⁻⁶	2.19×10⁻⁷	5.36×10⁻⁶	6.70×10⁻⁷	7.79×10⁻⁸	1.10×10⁻⁷	1.68×10⁻⁴
各重金属非致癌风险 (H_q)	儿童	0.263	4.70×10⁻³	1.60×10⁻²	0.396	1.44×10⁻²	5.85×10⁻³	8.04×10⁻³	0.132
各重金属非致癌风险 (H_q)	成人	3.61×10⁻²	1.98×10⁻³	2.25×10⁻³	6.05×10⁻²	2.58×10⁻³	8.31×10⁻⁴	1.18×10⁻³	3.87×10⁻²
非致癌风险 (H_i)	儿童	0.840
非致癌风险 (H_i)	成人	0.144

图4 重金属暴露人体非致癌和致癌健康风险评估各等级样品占比

Figure 4 Proportion of samples of different grades for non-carcinogenic and carcinogenic health risk assessment of heavy metal exposure

表5 重金属致癌健康风险指数

Table 5 Human carcinogenic health risk assessment of heavy metals

项目	人群	As	Cd	Pb	Ni	Cr
口服摄入	儿童	1.01×10⁻⁵	1.92×10⁻⁶	9.92×10⁻⁷	0.00	2.52×10⁻⁷
口服摄入	成人	1.51×10⁻⁵	2.87×10⁻⁶	1.48×10⁻⁶	0.00	3.78×10⁻⁷
皮肤接触	儿童	6.87×10⁻⁸	1.76×10⁻⁸	‒	‒	‒
皮肤接触	成人	4.03×10⁻⁷	1.03×10⁻⁷	‒	‒	‒
呼吸吸入	儿童	2.84×10⁻⁹	5.55×10⁻¹¹	‒	2.34×10⁻¹⁰	3.50×10⁻⁸
呼吸吸入	成人	5.61×10⁻⁹	1.10×10⁻¹⁰	‒	4.62×10⁻¹⁰	6.91×10⁻⁸
各重金属致癌风险 (C_R)	儿童	1.01×10⁻⁵	1.93×10⁻⁶	9.92×10⁻⁷	2.34×10⁻¹⁰	2.87×10⁻⁷
各重金属致癌风险 (C_R)	成人	1.55×10⁻⁵	2.97×10⁻⁶	1.48×10⁻⁶	4.62×10⁻¹⁰	4.47×10⁻⁷
总致癌风险 (T_CR)	儿童	1.33×10⁻⁵
总致癌风险 (T_CR)	成人	2.04×10⁻⁵

图5 土壤重金属Pearson相关性分析

Figure 5 Pearson correlation analysis of heavy metals in soil

图6 土壤重金属主成分分析空间散点

Figure 6 Principal component analysis of spatial scatter of heavy metals in soil

表6 土壤中不同重金属元素的主成分分析

Table 6 Principal component analysis of different heavy metals

成分	初始特征值			提取载荷平方和			旋转载荷平方和
成分	总计	方差百分比/%	累积/%	总计	方差百分比/%	累积/%	总计	方差百分比/%	累积/%
1	3.07	38.3	830	3.07	38.3	38.3	2.35	29.3	29.3
2	1.24	15.5	53.9	1.24	15.5	53.9	1.79	22.4	51.7
3	1.14	14.2	68.1	1.14	14.2	68.1	1.31	16.4	68.1
4	0.936	11.7	79.8
5	0.629	7.86	87.6
6	0.553	6.91	94.6
7	0.253	3.18	97.7
8	0.183	2.29	100

表7 土壤中不同因子载荷

Table 7 Loading of different factors in soil

重金属	初始因子载荷			旋转后因子载荷
重金属	PC1	PC2	PC3	PC1	PC2	PC3
Cu	0.812	0.228	−0.223	0.834	0.208	0.148
Pb	0.526	0.326	0.486	0.305	0.162	0.707
Zn	0.797	0.286	−0.349	0.906	0.121	6.60×10⁻²
Cd	0.514	−0.010	0.156	0.325	0.332	0.268
Ni	0.657	−0.612	0.242	0.163	0.911	9.40×10⁻²
Cr	0.578	−0.645	0.136	0.139	0.865	−3.10×10⁻²
Hg	0.137	0.409	0.725	−8.40×10⁻²	−5.60×10⁻²	0.838
As	0.670	0.209	−0.318	0.761	0.119	2.00×10⁻²

图7 不同主成分占比

Figure 7 The proportion of different principal components

参考文献 35

[1]	CUI Z W, WANG Y, ZHAO N, et al., 2018. Spatial distribution and risk assessment of heavy metals in paddy soils of Yongshuyu irrigation area from Songhua river basin, Northeast China[J]. Chinese Geographical Science, 28: 797-809. DOI
[2]	DIETRICH M, HULING J, KREKELER M P S, 2018. Metal pollution investigation of Goldman Park, Middletown Ohio: Evidence for steel and coal pollution in a high child use setting[J]. Science of the Total Environment, 618: 1350-1362. DOI URL
[3]	DUAN X C, YU H H, YE T R, et al., 2020. Geostatistical mapping and quantitative source apportionment of potentially toxic elements in top- and sub-soils: A case of suburban area in Beijing, China[J]. Ecological Indicators, 112: 106085. DOI URL
[4]	FEI X F, LOU Z H, XIAO R, et al., 2022. Source analysis and source-oriented risk assessment of heavy metal pollution in agricultural soils of different cultivated land qualities[J]. Journal of Cleaner Production, 341: 130942. DOI URL
[5]	GAO H P, ZHONG S F, ZHANG W L, et al., 2021. Revolutionizing membrane design using Machine Learning-Bayesian optimization[J]. Environmental Science & Technology, 56(4): 2572-2581. DOI URL
[6]	HUANG J L, WU Y Y, SUN J X, et al., 2021. Health risk assessment of heavy metal(loid)s in park soils of the largest megacity in China by using Monte Carlo simulation coupled with positive matrix factorization model[J]. Journal of Hazardous materials, 415: 125629. DOI URL
[7]	IAKOVIDES M, IAKOVIDES G, STEPHANOU E G, 2021. Atmospheric particle-bound polycyclic aromatic hydrocarbons, n-alkanes, hopanes, steranes and trace metals: PM_2.5 source identification, individual and cumulative multi-pathway lifetime cancer risk assessment in the urban environment[J]. Science of the Total Environment, 752: 141834. DOI URL
[8]	JIN Y L, O’Connor D, Ok Y S, et al., 2019. Assessment of sources of heavy metals in soil and dust at children's playgrounds in Beijing using GIS and multivariate statistical analysis[J]. Environment International, 124: 320-328. DOI PMID
[9]	KE W S, ZENG J Q, ZHU F, et al., 2022. Geochemical partitioning and spatial distribution of heavy metals in soils contaminated by lead smelting[J]. Environmental Pollution, 307: 119486. DOI URL
[10]	LUO H P, WANG Q Z, GUAN Q Y, et al., 2022a. Heavy metal pollution levels, source apportionment and risk assessment in dust storms in key cities in Northwest China[J]. Journal of Hazardous Materials, 422: 126878. DOI URL
[11]	LUO Y T, PANG J L, LI C H, et al., 2022b. Long-term and high-bioavailable potentially toxic elements (PTEs) strongly influence the microbiota in electroplating sites[J]. Science of the Total Environment, 814: 151933. DOI URL
[12]	MA L, WANG L, JIA Y Y, et al., 2016. Arsenic speciation in locally grown rice grains from Hunan Province, China: Spatial distribution and potential health risk[J]. Science of the Total Environment, 557-558: 438-444. DOI URL
[13]	MEN C, LIU R M, XU L B, et al., 2020. Source-specific ecological risk analysis and critical source identification of heavy metals in road dust in Beijing, China[J]. Journal of Hazardous Materials, 388: 121763. DOI URL
[14]	ORAL R, PAGANO G, SICILIANO A, et al., 2019. Soil pollution and toxicity in an area affected by emissions from a bauxite processing plant and a power plant in Gardanne (southern France)[J]. Ecotoxicology and Environmental Safety, 170: 55-61. DOI PMID
[15]	SUN J X, ZHAO M L, HUANG J L, et al., 2022. Determination of priority control factors for the management of soil trace metal(loid)s based on source-oriented health risk assessment[J]. Journal of Hazardous materials, 423(Part A): 127116. DOI URL
[16]	WANG D, ZHONG Q D, YANG J, et al., 2023. Effects of Cr and Ni on the microstructure and corrosion resistance of high-strength low alloy steel[J]. Journal of Materials Research and Technology, 23: 36-52. DOI URL
[17]	WANG X B, LI X Y, YAN X, et al., 2021. Environmental risks for application of iron and steel slags in soils in China: A review[J]. Pedosphere, 31(1): 28-42. DOI URL
[18]	WU H H, XU C B, WANG J H, et al., 2021. Health risk assessment based on source identification of heavy metals: A case study of Beiyun River, China[J]. Ecotoxicology and Environmental Safety, 213: 112046. DOI URL
[19]	XIAO Q, ZONG Y, MALIK Z, et al., 2020. Source identification and risk assessment of heavy metals in road dust of steel industrial city (Anshan), Liaoning, Northeast China[J]. Human and Ecological Risk Assessment, 26: 1359-1378. DOI URL
[20]	YANG Q Q, LI Z Y, LU X N, et al., 2018. A review of soil heavy metal pollution from industrial and agricultural regions in China: Pollution and risk assessment[J]. Science of the Total Environment, 642: 690-700. DOI URL
[21]	YU B, LU X W, FAN X Y, et al., 2021. Analyzing environmental risk, source and spatial distribution of potentially toxic elements in dust of residential area in Xi’an urban area, China[J]. Ecotoxicology and Environmental Safety, 208: 111679. DOI URL
[22]	ZHUO H M, WANG X, LIU H, et al., 2020. Source analysis and risk assessment of heavy metals in development zones: A case study in Rizhao, China[J]. Environmental Geochemistry and Health, 42(1-3): 135-146. DOI
[23]	陈云飞, 周金龙, 胡艳, 等, 2022. 新疆塔里木盆地东南缘红枣产地土壤重金属污染及健康风险评价[J]. 环境化学, 41(11): 3629-3639.
	CHEN Y F, ZHOU J L, HU Y, et al., 2022. Heavy metal pollution and health risk assessment of the Jujube producing area on the southeastern margin of the Tarim Basin in Xinjiang[J]. Environmental Chemistry, 41(11): 3629-3639.
[24]	国家环境保护总局, 2004. 土壤环境监测技术规范: HJ/T 166—2004[S]. 北京:中国环境科学出版社: 15-17.
	State Environmental Protection Administration, 2004. The Technical Specification for soil Environmental monitoring: HJ/T 166—2004[S]. Beijing:China Environmental Science Press: 15-17.
[25]	刘丽丽, 邓一荣, 廖高明, 等, 2021. 华南某污染场地土壤重金属污染健康风险评估与来源解析[J]. 环境污染与防治, 43(7): 875-879.
	LIU L L, DENG Y R, LIAO G M, et al., 2021. Health risk assessment and source analysis of heavy metal pollution in soil of a contaminated site in South China[J]. Environmental Pollution & Control, 43(7): 875-879.
[26]	刘昭玥, 费杨, 师华定, 等, 2021. 基于UNMIX模型和莫兰指数的湖南省汝城县土壤重金属源解析[J]. 环境科学研究, 34(10): 2446-2458.
	LIU Z Y, FEI Y, SHI H D, et al., 2021. Source apportionment of soil heavy metals in Rucheng county of Hunan Province based on UNMIX model combined with Moran index[J]. Research of Environmental Sciences, 34(10): 2446-2458.
[27]	吕律, 马建华, 姜玉玲, 等, 2021. 平顶山市火葬场周边农田土壤重金属空间分布、富集与来源分析[J]. 环境科学学报, 41(12): 5117-5126.
	LÜ L, MA J H, JIANG Y L, et al., 2021. Spatial distribution, enrichment and source identification of heavy metals in agricultural soils around the crematory in Pingdingshan City, China[J]. Acta Scientiae Circumstantiae, 41(12): 5117-5126.
[28]	马杰, 沈智杰, 张萍萍, 等, 2023. 基于APCS-MLR和PMF模型的煤矸山周边耕地土壤重金属污染特征及源解析[J]. 环境科学, 44(4): 2192-2203.
	MA J, SHEN Z J, ZHANG P P, et al., 2022. Pollution characteristics and source apportionment of heavy metals in farmland soils around the gangue heap of coal mine based on APCS-MLR and PMF receptor model[J]. Environmental Science, 44(4): 2192-2203.
[29]	生态环境部,2019. 建设用地土壤污染状况调查技术导则: HJ 25.1—2019[S]. 北京:中国环境出版集团: 5-7.
	Ministry of Ecology and Environment, 2019. Technical Guidelines for Investigation on Soil Contamination of Land for Construction: HJ 25.1—2019[S]. Beijing:China Environmental Science Press: 5-7.
[30]	生态环境部, 2019. 建设用地土壤污染风险管控和修复监测技术导则: HJ 25.2—2019[S]. 北京:中国环境出版集团: 4-5.
	Ministry of Ecology and Environment, 2019. Technical Guidelines for Monitoring During Risk Control and Remediation of Soil Contamination of Land for Construction: HJ 25.2—2019[S]. Beijing:China Environmental Science Press: 4-5.
[31]	石文静, 周翰鹏, 孙涛, 等, 2022. 矿区周边土壤重金属污染优先控制因子及健康风险评价研究[J]. 生态环境学报, 31(8): 1616-1628. DOI URL
	SHI W J, ZHOU H P, SUN T, et al., 2022. Research on priority control factors and health risk assessment of heavy metal pollution in soil around mining areas[J]. Ecology and Environmental Sciences, 31(8): 1616-1628.
[32]	他维媛, 康桢, 孟昭君, 等, 2021. 秦岭典型停产关闭锌冶炼企业场地土壤重金属污染特征研究[J]. 生态环境学报, 30(7): 1513-1521. DOI URL
	TA W Y, KANG Z, MENG Z J, et al., 2021. Research of pollution characteristics of heavy metals in soil of typical closed zinc smelting enterprises in Qinling Mountains[J]. Ecology and Environmental Sciences, 30(7): 1513-1521.
[33]	肖凯琦, 许安, 郭军, 等, 2023. 洞庭湖南缘农田土壤重金属特征及源解析[J]. 环境科学, 44(2):932-943.
	XIAO K Q, XU A, GUO J, et al., 2022. Characteristics and source analysis of heavy metals in farmland soil on the South of Dongting Lake[J]. Environmental Science, 44(2):932-943.
[34]	张山岭, 杨国义, 罗薇, 等, 2012. 广东省土壤无机元素背景值的变化趋势研究[J]. 土壤, 44(6): 1009-1014.
	ZHANG S L, YANG G Y, LUO W, et al., 2012. Changes of background values of inorganic elements in soils of Gunagdong Province[J]. Soils, 44(6): 1009-1014.
[35]	张雨菲, 谭静强, 邓敏, 等, 2022. 华中某铅冶炼场地土壤重金属空间分布及其生态风险评价[J]. 中国科学院大学学报, 39(4): 481-489.
	ZHANG Y F, TAN J Q, DENG M, et al., 2022. Spatial distribution and ecological risk assessment of heavy metals in a lead smelting site in center China[J]. Journal of University of Chinese Academy of Sciences, 39(4): 481-489.

珠三角某遗留造船厂场地土壤重金属人体健康风险评估及源解析

Health Risk Assessment and Source Apportionment of Soil Heavy Metals at A Legacy Shipyard Site in Pearl River Delta

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 14

参考文献 35

相关文章 4

编辑推荐

Metrics

本文评价

[1]	肖洁芸, 周伟, 石佩琪. 土壤重金属含量高光谱反演[J]. 生态环境学报, 2023, 32(1): 175-182.
[2]	刘娣, 苏超, 张红, 秦冠宇. 典型煤炭产业聚集区土壤重金属污染特征与风险评价[J]. 生态环境学报, 2022, 31(2): 391-399.
[3]	他维媛, 康桢, 孟昭君, 金盛华, 杨幸, 郭龙飞, 赵东旭, 张馨. 秦岭典型停产关闭锌冶炼企业场地土壤重金属污染特征研究[J]. 生态环境学报, 2021, 30(7): 1513-1521.
[4]	茶丽娟, 周丹丹, 冯鸿娟, 赵淑媛, 冯凯萍. 两种野生食用菌对土壤重金属的富集特征研究[J]. 生态环境学报, 2021, 30(10): 2093-2099.