Response of heavy metal distribution of surface sediments to aquaculture in Sansha Bay, Fujian

doi:10.3969/j.issn.1000-5641.2024.01.015

Abstract

Abstract:

The impact of rapid development of coastal aquaculture on aquatic environments is an important topic in environmental science. Quantitative assessment of the impact of aquaculture on sediment heavy metal pollution has been challenging because of the complex conservative-nonconservative behavior of heavy metals in coastal brackish waters. In this study, Sansha Bay, Fujian Province, the world’s largest yellow croaker cage culture area, was used as a research area for offshore aquaculture. Using aquaculture data recorded by remote sensing images combined with the relationships between sedimentary heavy metals and salinity, this study sought to analyze the effects of aquaculture on sediment heavy metal pollution. The results showed that over the past 15 years, the area of cage culture in Sansha bay has increased from 9.1 km² to 33.4 km², and the maximum intensity of cage culture per square kilometer has increased from 3% to 22%. As a result, the average values of Cu, Zn, Cd, and Pb levels in the cuprophilic elements in the culture area increased by 44%, 11%, 15%, and 17%, respectively, compared to non-farmed areas, and the slope of the conservative regression line with an increase in salinity decreased by 27%, 35%, 18%, and 2%, respectively. The average values of the siderophile elements Cr, Mn, and Ni in the breeding area increased by 16%, 15%, and 29%, respectively, compared to those in non-farmed areas. The results of potential ecological risk evaluation showed that Cd is a potential environmental pollutant in the surface sediments of Sansha Bay, and Sansha Bay as a whole is at a medium ecological risk level.

Key words: Sansha Bay, heavy metals, sediments, offshore aquaculture, farming intensity

CLC Number:

P736.4+1

Yixuan FANG, Maotian LI, Xiaoqiang LIU, Yan SONG, Mudong LIN, Huikun YAO. Response of heavy metal distribution of surface sediments to aquaculture in Sansha Bay, Fujian[J]. Journal of East China Normal University(Natural Science), 2024, 2024(1): 144-156.

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References 51

1	DOU Y, LI J, ZHAO J, et al.. Distribution, enrichment and source of heavy metals in surface sediments of the eastern Beibu Bay, South China Sea. Marine Pollution Bulletin, 2013, 67 (1): 137- 145.
2	ISLAM M S, AHMED M K, RAKNUZZAMAN M, et al.. Heavy metal pollution in surface water and sediment: A preliminary assessment of an urban river in a developing country. Ecological Indicators, 2015, 48, 282- 291.
3	丁新颖, 唐少霞.. 植物和玄武岩对水体重金属的生态净化效果. 安徽农业科学, 2019, 47 (10): 60- 63.
4	CHRISTOPHORIDIS C, DEDEPSIDIS D, FYTIANOS K.. Occurrence and distribution of selected heavy metals in the surface sediments of Thermaikos Gulf, N. Greece. Assessment using pollution indicators. Journal of Hazardous Materials, 2009, 168 (2/3): 1082- 1091.
5	马学文, 翁焕新, 章金骏.. 中国城市污泥重金属和养分的区域特性及变化. 中国环境科学, 2011, 31 (8): 1306- 1313.
6	BÉNÉ C, BARANGE M, SUBASINGHE R, et al.. Feeding 9 billion by 2050: Putting fish back on the menu. Food Security, 2015, 7 (2): 261- 274.
7	FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS. The State of World Fisheries and Aquaculture 2020 [EB/OL]. [2023-09-27]. https://www.fao.org/state-of-fisheries-aquaculture/2020/en.
8	DUAN Y, TIAN B, LI X, et al.. Tracking changes in aquaculture ponds on the China coast using 30 years of Landsat images. International Journal of Applied Earth Observation and Geoinformation, 2021, 102, 102383.
9	SEILER C, BERENDONK T U.. Heavy metal driven co-selection of antibiotic resistance in soil and water bodies impacted by agriculture and aquaculture. Frontiers in Microbiology, 2012, (3): 399.
10	MOKHTAR M B, ARIS A Z, MUNUSAMY V, et al.. Assessment level of heavy metals in Penaeus monodon and Oreochromis spp. in selected aquaculture ponds of high densities development area. European Journal of Scientific Research, 2009, 30 (3): 348- 360.
11	SUTHERLAND T F, PETERSEN S A, LEVINGS C D, et al.. Distinguishing between natural and aquaculture-derived sediment concentrations of heavy metals in the Broughton Archipelago, British Columbia. Marine Pollution Bulletin, 2007, 54 (9): 1451- 1460.
12	MENDIGUCHÍA C, MORENO C, MÁNUEL-VEZ M P, et al.. Preliminary investigation on the enrichment of heavy metals in marine sediments originated from intensive aquaculture effluents. Aquaculture, 2006, 254 (1/2/3/4): 317- 325.
13	宁德市统计局. 宁德统计年鉴2021年 [EB/OL]. (2021-10-26)[2023-09-27]. https://tjj.ningde.gov.cn/xxgk/tjxx/tjnj/202111/t20211104_1544289.htm.
14	韩承义, 吴雄飞, 许斌福, 等.. 2020年中国大黄鱼产业现状分析及发展建议. 渔业研究, 2022, 44 (4): 395- 406.
15	孙剑, 顾雪元, 张爱茜, 等.. 江苏省黄海海域生物质量调查及污染评价. 海洋科学, 2010, 34 (6): 28- 33.
16	吴晋强. 动物营养学 [M]. 合肥: 安徽科学技术出版社, 1999.
17	郑钦华.. 三沙湾海水增养殖区沉积物重金属变化特征及污染状况评价. 宁德师范学院学报(自然科学版), 2019, 31 (4): 432- 440.
18	杨妙峰, 郑盛华, 林永青, 等.. 三沙湾溪邳村滩涂养殖区沉积物质量状况及风险评价. 福建水产, 2015, 37 (3): 202- 210.
19	马祖友, 夏永健, 石志洲, 等.. 2011年三沙湾增养殖区水环境质量评价. 海洋开发与管理, 2013, 30 (7): 75- 78.
20	蔡清海, 杜琦, 钱小明, 等.. 福建省三沙湾海洋生态环境质量综合评价. 海洋学报(中文版), 2007, (2): 156- 160.
21	霍云龙, 陈金民, 林彩, 等.. 三沙湾表层沉积物重金属含量分布及生态风险评估. 应用海洋学学报, 2015, 4 (3): 356- 364.
22	陈凯, 黄智伟, 陈艳梅, 等.. 三沙湾表层沉积物中重金属赋存形态及环境风险评价. 渔业研究, 2019, 1 (2): 21- 129.
23	中国海湾志编纂委员会. 中国海湾志第七分册福建北部海湾 [M]. 北京: 海洋出版社, 1994.
24	农业部渔业渔政管理局. 中国渔业统计年鉴 [M]. 北京: 中国农业出版社, 2020.
25	王楠, 纪炜炜, 付婧, 等.. 三沙湾夏季大型底栖动物群落结构及其和水产养殖活动关系. 海洋渔业, 2019, 41 (4): 408- 420.
26	GORELICK N, HANCHER M, DIXON M, et al.. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 2017, 202, 18- 27.
27	JOVANOVIC N, GARCIA C L, BUGAN R D H, et al.. Validation of remotely-sensed evapotranspiration and NDWI using ground measurements at Riverlands, South Africa. Water SA, 2014, 40 (2): 211- 220.
28	PETTORELLI N, VIK J O, MYSTERUD A, et al.. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology & Evolution, 2005, 20 (9): 503- 510.
29	CHANDRASEKAR K, SESHA SAI M V R, ROY P S, et al.. Land Surface Water Index (LSWI) response to rainfall and NDVI using the MODIS Vegetation Index product. International Journal of Remote Sensing, 2010, 31 (15): 3987- 4005.
30	ZHANG Y, ODEH I O A, HAN C.. Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis. International Journal of Applied Earth Observation and Geoinformation, 2009, 11 (4): 256- 264.
31	GONG P, LIU H, ZHANG M, et al.. Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017. Science Bulletin, 2019, 64 (6): 370- 373.
32	DAUVALTER V, ROGNERUD S.. Heavy metal pollution in sediments of the Pasvik River drainage. Chemosphere, 2001, 42 (1): 9- 18.
33	刘用清.. 福建省海岸带土壤环境背景值研究及其应用. 海洋环境科学, 1995, (2): 68- 73.
34	HAKANSON L.. An ecological risk index for aquatic pollution control. a sedimentological approach. Water Research, 1980, 14 (8): 975- 1001.
35	陈静生, 王忠, 刘玉机.. 水体金属污染潜在危害应用沉积学方法评价. 环境科技, 1989, 9 (1): 16- 25.
36	郝红, 高博, 王健康, 等.. 滦河流域沉积物中重金属分布特征及风险评价. 岩矿测试, 2012, 31 (6): 1000- 1005.
37	刘成, 吴永胜, 等.. 环渤海湾诸河口潜在生态风险评价. 环境科学研究, 2002, (5): 33- 37.
38	徐争启, 倪师军, 庹先国, 等.. 潜在生态危害指数法评价中重金属毒性系数计算. 环境科学与技术, 2008, (2): 112- 115.
39	赵一阳.. 中国浅海沉积物化学元素丰度. 中国科学:B辑, 1993, 23 (10): 1084- 1090.
40	赵一阳.. 中国海大陆架沉积物地球化学的若干模式. 地质科学, 1983, (4): 307- 314.
41	张清建.. 戈尔德施密特: 地球化学和晶体化学的奠基人. 化学通报, 2016, 79 (5): 474- 479.
42	杨丽莉, 张登峰, 曾向东.. 沉积物中重金属释放规律研究. 安徽农业科学, 2007, (27): 8630- 8631.
43	ZHONG A P, GUO S H, LI F M, et al.. Impact of anions on the heavy metals release from marine sediments. Journal of Environmental Sciences, 2006, 18 (6): 1216- 1220.
44	刘振勇, 李燕平.. 闽东大黄鱼饲料的现状与对策. 台湾海峡, 2001, (S1): 180- 183.
45	訾鑫源, 张鸣, 谷孝鸿, 等.. 洪泽湖围栏养殖对表层沉积物重金属含量影响与生态风险评价. 环境科学, 2021, 42 (11): 5355- 5363.
46	王大鹏, 何安尤, 谢达祥, 等.. 龙胆石斑刺激隐核虫病防治技术研究. 水产科技情报, 2013, 40 (1): 22- 26.
47	MAGNA E K, KORANTENG S S, DONKOR A, et al.. Heavy metal pollution in the surface sediments from cage aquaculture farms in the Volta Basin of Ghana: Source identification and ecological risk assessment. Water, Air, & Soil Pollution, 2022, 233 (10): 406.
48	谢毓婧, 赵晶.. 文化景观视角下的海上聚落研究——以福建省三沙湾为例. 城市建筑, 2022, 19 (7): 174- 178.
49	GREFSRUD E S, GLOVER K, GRØSVIK B E, et al. Risk assessment–environmental impacts of Norwegian aquaculture [R]. Bergen: Institute of Marine Research, 2018.
50	马媛, 高振会, 杨应斌, 等.. 海上石油开采导致生态环境变化实例研究. 海洋学报(中文版), 2005, (5): 54- 59.
51	王炫凯, 王海姮, 燕云, 等.. 水产养殖环境中重金属污染的来源及危害. 水产养殖, 2022, 43 (4): 38- 41.

检测指标	检测标准	检测方法
Hg、As	GB17378.5—2007海洋监测规范第五部分: 沉积物分析	原子荧光法
Cr、Mn、Ni		等离子体发射光谱仪法
Cu、Zn、Cd、Pb		原子吸收分光光度法
粒度		激光粒度仪法
盐度	GB17378.4—2007海洋监测规范第四部分: 海水分析	温盐深仪法

遥感卫星	成像时间(年-月-日)	空间分辨率/m
Landsat7 ETM	2005-10-25	30
Landsat7 ETM	2010-10-31	30
Landsat8 OLI	2015-09-11	30
Sentinel-2	2020-10-26	10

${E}_{\text{r}}^{i}$ 分级标准	单个污染物生态危害程度	RI 分级标准	总潜在生态危害程度
${E}_{\text{r}}^{i} < 30$	轻微	$\text{RI} < 50$	轻微
$30 \leqslant {E}_{\text{r}}^{i} < 60$	中等	$50 \leqslant \text{RI} < 100$	中等
$60 \leqslant {E}_{\text{r}}^{i} < 120$	强	$100 \leqslant \text{RI} < 200$	强
$120 \leqslant {E}_{\text{r}}^{i} < 240$	很强	$\text{RI} \geqslant 200$	很强
${E}_{\text{r}}^{i} \geqslant 240$	极强

区域	重金属元素含量/(mg·kg^–1)							年份
区域	Cr	Mn	Ni	Cu	Zn	Cd	Pb	年份
三沙湾 (沉积物平均值)	55.4	1324.3	32.91	18.22	114.65	0.116	47.75	2020(本研究)
三沙湾 (沉积物最大值)	95.22	2125.1	43.78	32.7	146.96	0.227	68.4	2020(本研究)
三沙湾 (沉积物最小值)	37.79	686.6	17.53	7.88	92.12	0.068	33.29	2020(本研究)
福建省海岸带 (土壤)	40.7	507	17.4	22.4	83.6	0.060	39	1995(文献[33])
中国浅海 (沉积物)	60.0	530	24.0	15.0	65.0	0.065	20	1993(文献[39])

统计量	${E}_{\text{r}}^{i} $							RI
统计量	Cr	Mn	Ni	Cu	Zn	Cd	Pb	RI
最大值	4.65	4.19	12.58	8.89	1.63	113.61	8.77	154.32
最小值	1.84	1.35	5.04	1.79	0.88	26.52	4.27	41.69
平均值	2.76	2.51	9.65	4.65	1.36	55.27	6.02	82.22