环境科学研究  2020, Vol. 33 Issue (1): 183-191  DOI: 10.13198/j.issn.1001-6929.2019.03.28

引用本文  

黄宏, 魏青青, 赵旭, 等. 嵊泗海域表层沉积物中多环芳烃污染水平、分子组成及源识别[J]. 环境科学研究, 2020, 33(1): 183-191.
HUANG Hong, WEI Qingqing, ZHAO Xu, et al. Contamination Level, Composition and Source Appointment of Polycyclic Aromatic Hydrocarbons in the Surface Sediments of Shengsi Sea Area[J]. Research of Environmental Sciences, 2020, 33(1): 183-191.

基金项目

国家自然科学基金项目(No.41807341);现代农业产业技术体系专项资金(No.CARS-50)
National Natural Science Foundation of China (No.41807341); China Agriculture Research System (No.CARS-50)

责任作者

尹方(1985-), 男, 安徽安庆人, 讲师, 博士, 主要从事海洋溢油污染与生态风险监测研究, fangyin@shmtu.edu.cn.

作者简介

黄宏(1974-), 女, 河南驻马店人, 副教授, 博士, 主要从事海洋环境污染与生态修复研究, hhuang@shou.edu.cn

文章历史

收稿日期:2018-11-26
修订日期:2019-03-25
嵊泗海域表层沉积物中多环芳烃污染水平、分子组成及源识别
黄宏1, 魏青青1, 赵旭1, 林军1, 章守宇1, 宿鹏浩2, 尹方2    
1. 上海海洋大学海洋生态与环境学院, 上海 201306;
2. 上海海事大学海洋科学与工程学院, 上海 201306
摘要:嵊泗海域是舟山渔场的重要组成部分,属于国家海洋特别保护区.为了解嵊泗海域表层沉积物中16种优控PAHs(多环芳烃)的污染特征及潜在风险,于2017年6月采集了嵊泗海域18个站点的表层沉积物样品,采用气相色谱-质谱联用技术确定PAHs质量分数及其分子组成,运用特征分子比值法和主成分分析法识别PAHs来源,并采用质量基准法与质量标准法对沉积物中PAHs潜在生态风险进行评价.结果表明:①除了Ace与Act外,其他14种PAHs均被检出.除A1站点外,w(Phe)最高,w(Flra)次之.检出的PAHs以3环和4环为主,占总量的71.21%,不同环数PAHs占比大小依次为3环> 4环> 5环> 2环> 6环.w(∑14PAHs)范围为46.38~196.36 ng/g,平均值为109.40 ng/g.整体分布上,嵊泗海域表层沉积物中w(∑14PAHs)呈近岸高于远岸的分布特征.②嵊泗海域表层沉积物中PAHs以煤炭、柴油和生物质等燃烧源为主,部分站点同时受到燃烧源与石油源影响.③各站点的w(∑14PAHs)均低于ERL和OEL,表明嵊泗海域潜在生态风险较小.④与国内外其他区域相比,嵊泗海域表层沉积物中w(∑14PAHs)处于较低污染水平,尚不足以对当地渔业生态环境造成负面影响,但作为我国重要"蓝色粮仓",仍应加强其陆源排放监管.
关键词嵊泗海域    表层沉积物    多环芳烃(PAHs)    源解析    生态风险评价    
Contamination Level, Composition and Source Appointment of Polycyclic Aromatic Hydrocarbons in the Surface Sediments of Shengsi Sea Area
HUANG Hong1, WEI Qingqing1, ZHAO Xu1, LIN Jun1, ZHANG Shouyu1, SU Penghao2, YIN Fang2    
1. College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai 201306, China;
2. College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
Abstract: The Shengsi Sea Area is one of the most important areas of the Zhoushan fishing ground, it is a national marine special protection area. We investigated the distribution patterns and ecological risks of 16 priority polycyclic aromatic hydrocarbons (PAHs) in the surface sediments of Shengsi Sea Area. A total of 18 surface sediments were collected from Shengsi Sea in June of 2017. Gas chromatography-mass spectrometry (GC-MS) was applied for the PAHs quantitation and their composition analysis. The sources of the PAHs in the collected surface sediments were identified by the specific ratios of isomeric species and the principal component analysis. The potential ecological risks of the target PAHs in the sediments were evaluated based on the quality guideline and the single molecular threshold quality standard. The results showed that:(1) 14 PAHs are detected, except acenaphthylene and acenaphthene. In addition to the A1 site, the content of phenanthrene is the highest, followed by fluoranthene. The quantified 14 PAHs were mainly composed of 3 and 4 rings, accounting for 72.21% of the total PAH. The percent order of PAHs with different rings shows as follows:3 rings > 4 rings > 5 rings > 2 rings > 6 rings. The total content of PAHs ranges fromed 46.38 to 196.36 ng/g and the mean value is 109.40 ng/g. The overall PAHs distribution pattern indicates that the PAHs content in the nearshore areas is higher and the PAHs contents in the offshore areas is lower. (2) Coal, diesel and biomass combustions are the main sources of the PAHs in the collected sediments, only a few sampling sites are affected by combustion and petroleum sources simultaneously. (3) The ecological risk assessments show that the PAH contents in all surface sediments are well below the effects range low (ERL) and the occasional effect (OEL) levels, suggesting their low potential ecological risks in the studied area. (4) Compared with other domestic and foreign regions, the PAHs contents in the surface sediments of the Shengsi Sea are low and the overall PAHs risk level will not cause negative impacts on the local fishery ecological environment. However, as one of our important 'blue granaries', it is still essential to strengthen the environmental monitoring of the terrestrial PAH emissions in the Shengsi Sea Area.
Keywords: Shengsi Sea Area    surface sediments    polycyclic aromatic hydrocarbons (PAHs)    source apportionment    ecological risk assessment    

嵊泗海域位于南北航道与长江枢纽点上,地理位置优越,是上海港口的天然外港.嵊泗列岛位于舟山群岛北部,地处长江口和杭州湾汇合处,由404个岛屿组成,其中超过百人居住的岛屿13个,海域面积约9×104 km2,2017年末人口超过7×104人,主要产业为渔业、国际外贸、港口运输业和旅游业.嵊泗海域作为舟山渔场的重要组成部分,既是石斑鱼、黄鱼等海洋生物优良的栖息场所,也是贻贝等海洋生物的重要养殖基地[1].嵊泗海域处于长江径流和近岸潮流交互作用地带[2],受长江入海口、钱塘江等径流以及附近城市污染排放影响较大,致使有机污染水平增加,对该海域的水生生物及其生境安全构成一定威胁[1, 3]. PAHs(多环芳烃)因难降解、高毒性、且易于在生物体内蓄积,对海洋生物乃至人体健康具有严重的“三致”风险而倍受关注[4].

近年来,嵊泗海域有机污染物研究多集中在OCPs(organochlorine pesticides,有机氯农药)和PCBs(polychlorinated biphenyls,多氯联苯),如白有成等[5]对嵊泗海域生物体内OCPs和PCBs的浓度与组成特征进行研究;方杰[3]分析了嵊泗海域生物体和表层沉积物中PCBs和OCPs浓度水平与污染组成.对局部或邻近区域有机污染物的研究情况亦主要集中于PCBs和OCPs等,YANG等[6]研究分析了乐清港、象山港和三门湾海域表层沉积物中PCBs;母清林等[7]对舟山群岛潮间带表层沉积物中PAHs的质量分数、来源和潜在生态风险进行相关分析及评价;WANG等[8-9]调查分析了舟山群岛与象山港海域表层沉积物中的PAHs和PCBs的来源与分布特征.关于嵊泗海域沉积物中PAHs的污染水平及源识别的详细研究目前鲜见报道.该研究采用气相色谱-质谱联用技术,确定嵊泗海域表层沉积物中的PAHs分子组成及其质量分数,并探讨其可能的来源及潜在生态风险,以期为该海域国家海洋特别保护区与渔业资源养护等提供科学参考.

1 材料与方法 1.1 样品采集

样品于2017年6月采集于嵊泗海域(122°38′40″E~ 123°13′40″E、30°31′40″N~30°56′40″N),自西向东,共设置18个站点,具体调查站点分布见图 1.

图 1 嵊泗海域站点分布 Fig.1 The distribution of sampling sites in Shengsi Sea Area

样品的采集、保存和制备均按照GB 17378.5—2007《海洋监测规范》[10]进行,取500~600 g湿样装入磨口广口瓶中,4 ℃下保存.冷冻干燥并剔除样品中砾石与动植物残骸,粉碎过筛,于-20 ℃冷冻保存备用.

1.2 试剂

硅胶(0.15~0.25 mm)、无水硫酸钠、铜粉分别购自于SIGMA-ALDRICH、国药集团化学试剂有限公司、中国上海龙昕科技发展公司.硅胶依次用丙酮、正己烷、二氯甲烷分别淋洗3次,过夜干燥,并于40 ℃烘箱中烘8 h,升温至180 ℃烘20 h,使其活化[3].丙酮、二氯甲烷、正己烷等色谱纯溶剂购自国药集团化学试剂有限公司. US EPA(美国环境保护局)所列16种优控PAHs污染物〔Nap(Naphthalene, 萘)、Ace(Acenaphthylene, 苊烯)、Act(Acenaphthene, 苊)、Flre(Fluorene, 芴)、Phe(Phenanthrene, 菲)、Ant(Anthracene, 蒽)、Flra(Fluoranthene, 荧蒽)、Pyr(Pyrene, 芘)、B[a]A(Benzo[a]anthracene, 苯并[a]蒽)、Chr(Chrysene, 䓛)、B[b]F(Benzo[b]fluoranthene, 苯并[b]荧蒽)、B[k]F(Benzo[k]fluoranthene, 苯并[k]荧蒽)、B[a]P(Benzo[a]pyrene, 苯并[a]芘)、InP(Indeno[1, 2, 3-cd]pyrene, 茚并[1, 2, 3-cd]芘)、D[a, h]A(Dibenz[a, h]anthracene, 二苯并[a, h]蒽)、B[g, h, i]P(Benzo[g, h, i]perylene, 苯并[g, h, i]苝)〕及内标物(p-Terphenyl-d14)均购自SUPELCO公司.

1.3 样品预处理与仪器分析方法

样品预处理与仪器分析方法参考US EPA 8270D及文献[11-12].称取5 g研磨过筛的沉积物置于索氏萃取装置(Extraction System B-811, BUCHI, CH),采用体积比为1 :1的正己烷与二氯甲烷混合液索提6 h,淋洗1 h,旋蒸浓缩至5 mL后,氮吹至1 mL.浓缩液过3 g硅胶、0.5 g铜粉和1 g无水硫酸钠进行柱净化分离,采用体积比为1 :1的正己烷与二氯甲烷混合液洗脱,重复2次.合并淋洗液氮吹浓缩,正己烷定容至1 mL,加入内标物(p-Terphenyl-d14),低温密闭保存待上机分析.

标准品和所有样品采用Agilent公司气相色谱-质谱联用仪(7890/5975C-GCMSD)分析,DB-5毛细管柱(15 m×0.25 mm×0.25 μm),进样口温度为290 ℃.升温程序:初始温度50 ℃,保持3 min,15 ℃/min升至180 ℃,然后6 ℃/min升至300 ℃,保持2 min,直至所有组分流出.氦气(纯度>99.9%)作为载气,1 mL/min的流速,不分流进样,进样量1 μL.离子源温度为230 ℃,四极杆温度为150 ℃.选择离子扫描(SIM),内标法定量.

1.4 质量控制与质量保证

PAHs标准溶液以5、10、20、50、100和200 ng/g浓度梯度建立标准曲线,线性方程的相关性均满足检测要求(R2 >0.99).加标回收率试验重复3次,除Nap加标回收率较低(约45.6%)外,其他15种PAHs加标回收率范围在65.0%~118.4%之间.为保证样品分析结果的准确性,实际样品中PAHs质量分数均以溶剂空白校准.

2 结果与讨论 2.1 PAHs质量分数、分子组成及分布特征

利用ChemStation定量分析确定PAHs质量分数.各站点PAHs的分子组成及其质量分数见表 1.由表 1可见,嵊泗海域表层沉积物中共检出14种PAHs,Ace与Act未被检出.除A1站点外,14种优控PAHs中,w(Phe)最高(17.18~67.66 ng/g),w(Flra)次之,介于5.38~37.93 ng/g之间,w(D[a, h]A)最低,为0.01~0.71 ng/g.检出的14种PAHs以3环和4环为主,占总量的71.21%.不同环数PAHs占比大小依次为3环>4环>5环>2环>6环.各站点w(∑14PAHs)介于46.38 ~196.36 ng/g之间,平均值为109.40 ng/g,w(∑14PAHs)最低值和最高值分别出现在A9站点(46.38 ng/g)和A5站点(196.36 ng/g),其他依次以A3、A10和A4站点w(∑14PAHs)较多. A5站点w(∑14PAHs)最高,可能因为该站点靠近陆源,港口活动频繁,受人类生产、生活排污及船舶行驶产生的燃油、溢油等影响. A3、A10和A4站点位于岛礁或岛屿附近,受洋流影响小,水文条件相对稳定,人类活动产生的PAHs沉淀滞留使其质量分数相对较高[13-14],而远离陆源与岛礁岛屿区域的其他站点w(∑14PAHs)相对较低.另外,A7站点长江入海口泥沙沉积较少,可能是其质量分数相对较低的原因[15]. A18站点远离岛屿,受人为源干扰较小,但w(∑14PAHs)较高,根据张宗雁等[15]研究发现,东海沉积物中w(PAHs)与陆源距离、沉积物的粒度、有机碳含量以及东海环流体系密切相关,由此可能对该站位w(∑14PAHs)产生一定影响,具体原因有待进一步研究.

表 1 嵊泗海域表层沉积物中PAHs分子组成及其质量分数 Table 1 Molecular composition and mass fraction of PAHs in the surface sediments of Shengsi Sea Area  

以地统计学理论为基础,结合克里金插值法,借助ArcGIS软件对嵊泗海域的w(∑14PAHs)分布进行空间预测,绘制了嵊泗海域w(∑14PAHs)的空间分布等值线(见图 2).在地统计分析时,克里金插值法假定所映射的变量差距随其采样位置间的距离缩短而减小,利用周围的测量值进行加权以此得出未测量位置的质量分数,在点稀少时插值效果好,有利于整体分布趋势分析.由图 2可见,PAHs呈现离岸距离增加而w(∑14PAHs)递减的趋势,表明陆源污染是PAHs主要来源.嵊泗海域靠近长江三角洲,该区域土壤问题显著,工业废弃物污染较为严重,PAHs为主要污染物[16].与此同时,调查站点邻近长江入海口,常年受长江的冲刷沉积影响,上游的工厂废弃污水排放与泥沙积淀也给该海域带来一定的PAHs污染[17].

图 2 嵊泗海域w(∑14PAHs)的空间分布等值线 Fig.2 Spatial distribution contour of ∑14PAHs contents in Shengsi Sea Area
2.2 PAHs的源识别 2.2.1 特征分子比值法

特征分子比值法是一种常用的定性源解析方法,该法基于热力学上同分异构体稳定性差异确定PAHs来源的方法[18],常见的特征比值有B[a]A/(B[a]A+Chr)、Ant/(Phe+Ant)、InP/(InP+B[g, h, i]P)和Flra/(Flra+Pyr).当Ant/(Phe+Ant) < 0.1、B[a]A/(B[a]A+Chr) < 0.2或Flra/(Flra+Pyr) < 0.4时,PAHs主要来源为石油源;当Ant/(Phe+Ant)>0.1、B[a]A/(B[a]A+Chr)>0.35或InP/(InP+B[g, h, i]P)> 0.5时,PAHs主要来源为燃烧源;当0.2 < B[a]A/(B[a]A+Chr) < 0.35时,PAHs主要来源为混合源;当InP/(InP+B[g, h, i]P) < 0.2时,PAHs主要来源为汽油、柴油等燃烧;当0.2 < InP/(InP+B[g, h, i]P) < 0.5或Flra/(Flra+Pyr)>0.5时,PAHs主要来源为煤、木材及草燃烧;当0.4 < Flra/(Flra+Pyr) < 0.5时,PAHs主要来源为天然气、柴油、石油等燃烧[19].

根据Flra/(Flra+Pyr)与Ant/(Phe+Ant)比值交叉结果〔见图 3(a)〕分析,A7、A13和A16站点PAHs主要来源于天然气、石油和柴油等燃烧源,而A1、A2、A12、A14、A15和A18站点主要来自煤、木材及草燃烧,其余站点为石油污染与物质燃烧的混合源.图 3(b)为InP/(InP+B[g, h, i]P)与B[a]A/(B[a]A+Chr)比值分布,结果显示,A14站点PAHs来自煤、木材及草燃烧,可能与该区域居民生活燃煤与木材等有关;其余站点PAHs都呈现混合源特征,如A7、A13和A17站点为汽油和柴油等燃烧源及石油源,A6站点来源于煤、木材及草等燃烧源与石油泄漏.从站点离岸位置看,A6和A7站点距离陆地或岛屿较近,受人们生产、生活及附近港口船只燃油影响;A17站点离岛屿较远,PAHs混合来源可能与航道船只燃油泄露及陆源污染物随水体悬浮物迁移有关[20].特征分子比值的差异均表明,该海域中PAHs污染主要受煤、木材、草和汽油、柴油等燃烧源和混合源影响,而石油源影响较小.

图 3 嵊泗海域表层沉积物中PAHs来源特征分子比值法交叉分析结果 Fig.3 The crossplots of the PAHs ratios in the surface sediments of the Shengsi Sea Area based on the specific ratios of isomeric species
2.2.2 主成分分析法

主成分分析法可确定不同污染源对样品的百分数贡献率,适合污染源数目较少的溯源解析,利用降维法减少变量数量,以此反映原始变量的大部分信息[21].通过若干综合性特征指标对样品分类识别,并对比载荷量来推测污染源[22].采用SPSS 22.0对检出的14种PAHs进行来源分析,以特征根1为标准,确定4个主成分(PC1、PC2、PC3和PC4),计算主成分累积方差贡献率,得到相关因子载荷矩阵(见表 2).

表 2 嵊泗海域表层沉积物中检出的14种PAHs的因子载荷矩阵 Table 2 Factor load matrix of 14 detected PAHs in surface sediments of the Shengsi Sea Area

通常,石油或油类物质排放是低环PAHs的主要来源,而高环PAHs主要来源于物质高温燃烧,如煤炭燃烧能够释放Phe、Pyr、Ant、Chr、B[b]F和B[k]F等,其中高环Chr、B[b]F与B[k]F大部分来源于家用燃煤排放. InP和B[g, h, i]P主要与柴油燃烧(尾气排放)相关,Pyr和Flra与秸秆、木材等生物质燃烧有关[23].因子分析结果(见表 2)表明,4个因子的累积贡献率达84.11%,PC1的贡献率为47.8%,其中Chr、B[g, h, i]P、InP、B[b]F、Flre和B[k]F具有较大的负荷值,即PC1为煤炭与柴油燃烧. PC2中较大负荷值的化合物为Pyr、Phe和Nap,其贡献率为19.77%,Pyr和Phe主要来源于煤炭燃烧,Nap与石油源有关,因此PC2来自煤炭与石油源的联合作用(混合源). PC3和PC4贡献率较低,分别为9.30%和7.24%,PC3载荷明显的化合物仅有B[a]P,且B[a]P可认为由炼焦生产排放[24],表明PC3主要来自炼焦生产过程,PC4中仅Ant和B[a]A载荷大于0.6,Ant是煤燃烧的特征指示物[25],B[a]A是天然气排放的重要指标[26],故PC4为煤与天然气的燃烧污染源.主成分分析结果表明,研究区域沉积物中的PAHs主要受煤炭、天然气、柴油和石油等燃烧源和混合源影响,石油泄漏污染较少,其分析结果与特征分子比值法源解析结果一致.

2.3 PAHs的潜在生态风险

Baumard等[27]将PAHs污染水平分为4级,即低污染(0~100 ng/g)、中等污染(100~1 000 ng/g)、高污染(1 000~5 000 ng/g)与超高污染(>5 000 ng/g).由表 1可知,嵊泗海域表层沉积物中w(∑14PAHs)处于中低污染水平,44.44%站点处于低污染水平,其余站点为中等污染水平.

沉积物中PAHs潜在生态风险常用评价方法包括质量基准法和质量标准法[28].该研究利用Long等[29]提出的沉积物质量基准法对嵊泗海域表层沉积物潜在生态风险进行评估,发现18个站点检出的14种PAHs质量分数均远低于ERL(效应区间低值),表明PAHs对其生态系统造成影响的可能性较小,但由于B[b]F、B[k]F、In[1, 2, 3-cd]P和B[g, h, i]P毒性高且各站点均被检出,因此该海域PAHs污染仍需持续关注.另外,基于加拿大学者[30]提出的沉积物质量标准,比较了各站点沉积物中w(∑14PAHs)(见表 3).由表 3可见,A2、A7、A9、A14、A15、A17站点沉积物中12种PAHs质量分数均小于REL(罕见效应浓度值),表明PAHs不会对生物造成不良影响;其余站点至少一种PAHs质量分数介于REL与TEL(临界效应浓度值)之间,表明这些站点沉积物中PAHs对生物会造成影响但不显著,由于研究海域处于海洋特别保护区,仍需加强PAHs监控;值得关注的是,A5站点w(Phe)、A1站点w(B[a]P)处于TEL与OEL(偶然效应浓度值)之间,说明对生物的不良影响风险较大,应加强监测与控制措施.

表 3 嵊泗海域表层沉积物中PAHs单分子阈值质量标准风险评价 Table 3 Ecological risk assessment of the target PAHs in the surface sediments of Shengsi Sea based on the single molecular threshold quality standard
2.4 与其他区域表层沉积物中PAHs污染比较

与国内外其他区域相比(见表 4),嵊泗海域表层沉积物中w(∑14PAHs)与吕泗渔场及东海海域相近,整体处于较低污染水平.从组成和来源来看,大多来自于工业污染、交通运输以及居民日常生活,表现为煤炭、柴油、石油、木柴等燃烧,建议通过优化能源结构、控制民用燃煤和改善海上交通等措施控制PAHs污染.

表 4 研究区域沉积物中PAHs污染情况与其他区域对比 Table 4 Comparison of PAH contaminations in the surface sediments of the studied and other areas
3 结论

a) 在嵊泗海域表层沉积物中均检出14种优控PAHs,w(∑14PAHs)范围为46.38 ~196.36 ng/g,平均值为109.40 ng/g,除A1站点外,w(Phe)最高,w(Flra)次之.检出的14种PAHs中以3环和4环为主.不同环数PAHs占比大小依次为3环>4环>5环>2环>6环.

b) 特征分子比值法和主成分分析法源识别发现,嵊泗海域表层沉积物中PAHs主要为煤炭、柴油和生物质等燃烧源,部分站点同时受到燃烧源与石油源影响,石油源污染影响较小.

c) 嵊泗海域表层沉积物中w(∑14PAHs)属于中低污染水平,均未超过ERL及OEL,表明该海域表层沉积物中PAHs潜在生态风险较小,但Phe(A5站点)、B[a]P(A1站点)两种PAHs潜在生态风险较高,需加强监测与控制.

d) 与国内外其他区域相比,嵊泗海域表层沉积物中w(∑14PAHs)处于较低污染水平,建议通过优化能源结构、控制民用燃煤和改善海上交通等措施控制PAHs污染.

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