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三峡库区消落带表层沉积物生物标志物时空变化与来源分析
引用本文:赵岱寅,蔡茂雪,张代钧,王锋文.三峡库区消落带表层沉积物生物标志物时空变化与来源分析[J].中国环境科学,2022,42(6):2810-2820.
作者姓名:赵岱寅  蔡茂雪  张代钧  王锋文
作者单位:1. 重庆大学, 煤矿灾害动力学与控制国家重点实验室, 重庆 400044;2. 重庆大学环境科学系, 重庆 400044
基金项目:国家自然科学基金(42077319,41603102);
摘    要:受三峡大坝季节性“蓄水-放水”影响,三峡库区消落带每年呈“淹没-落干”周期性变化,库区内有机质环境地球化学过程也随之改变.基于此,于2018年3月和9月带采集淹没期和落干期表层沉积物成对样品(n=16×2=32),GC-MS分析生物标志物(正构烷烃、未分离复杂混合物、藿烷和甾烷),探讨不同时期有机质时空变化与来源组成.结果表明,落干期和淹没期正构烷烃(C10~C40)浓度分别为(14.09±4.05)μg/g和(16.25±3.91)μg/g,UCM为4.28~28.62μg/g,表明存在石油烃类污染.正构烷烃短链与长链比(L/H)在落干期和淹没期平均值分别为(0.90±0.56)、(0.74±0.15),指示落干期为低等生物与陆源高等植物的混合有机质输入,淹没期则以陆源输入为主.碳优势指数CPI平均值分别为(1.66±0.32)、(1.70±0.33),指示化石燃料与高等植物的混合贡献.正构烷烃主峰碳数(Cmax)与浓度特征揭示落干期藻类、细菌和水生植物源输入比淹没期高.库区上游多以水生、高等植物源为主,而下游则以细菌、浮游藻类低等输入居多.藿烷类(C27、C29~C32) Ts/Tm,C31(S/S+R)以及甾烷类(C27~C29) C29ααα S/(S+R)比值结果均可指示高成熟度石油烃输入.主成分分析结果表明落干期以石油源和水生、陆生植物源混合输入为主,淹没期以低等生物与水生植物混合源输入居多.本研究探讨了季节性水位调节对消落带沉积物生物标志物的影响机制,获得了示踪信息,为进一步研究库区生物标志物环境地球化学循环提供基础数据.

关 键 词:三峡库区  消落带  生物标志物  时空变化  来源分析  
收稿时间:2021-11-29

Temporal and spatial variation and source analysis of biomarkers in surface sediments in the water-level-fluctuating zone of the Three Gorges Reservoir Region
ZHAO Dai-yin,CAI Mao-xue,ZHANG Dai-jun,WANG Feng-wen.Temporal and spatial variation and source analysis of biomarkers in surface sediments in the water-level-fluctuating zone of the Three Gorges Reservoir Region[J].China Environmental Science,2022,42(6):2810-2820.
Authors:ZHAO Dai-yin  CAI Mao-xue  ZHANG Dai-jun  WANG Feng-wen
Institution:1. State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing, 400044, China;2. Department of Environmental Science, Chongqing University, Chongqing 400044, China
Abstract:Affected by the seasonal "storage-discharge" of the Three Gorges Dam, the water level fluctuation zone (WLFZ) of the Three Gorges Reservoir Region (TGRR) show a periodic change of "submergence-exposure" each year, and the environmental geochemical processes of organic matter in this area changed accordingly. In this study, 16paired surface sediment samples (n=32) were collected from WLFZ inthe TGRR in March and September 2018, respectively. GC-MS were used to analyze several biomarkers (n-alkanes, UCM, hopanes and steranes) to discuss the concentration, composition, sources and spatial-temporal variation. The results showed that the concentration of total n-alkanes (C10~C40) in exposed and submerged period was (14.09±4.05)μg/g and (16.25±3.91) μg/g, respectively, and UCM was 4.28~28.62μg/g, indicating pollution from petroleum hydrocarbon. The average ratios of L/H in exposed and submerged period was (0.90±0.56) and (0.74±0.15), respectively. The exposed period has a mixed input of lower organisms and terrestrial higher plants, while the submerged period was mainly from land sources. The average value of CPI was (1.66±0.32), (1.70±0.33), respectively, indicating the mixed contribution from fossil fuels and higher plants. The Cmax, concentration and composition of n-alkanes revealed that the input from algae, bacteria and aquatic plants in exposed period was higher than in submerged period. The sedimentary organic matter in the upper reaches was mostly from aquatic plants and higher plants, while the downstream was imported from bacteria and planktonic algae. The results of the ratios of hopanes (C27, C29~C32) Ts/Tm, C31 (S/S+R) and steranes (C27~C29) C29 ααα S/(S+R) in the two periods could indicate the input of high-maturity petroleum hydrocarbons. PCA apportion the sources of typical nine n-alkanes and UCM:in exposed period they were mainly from petroleum sources, aquatic and terrestrial plant sources; while in submerged period, they were from a mixture of lower biological sources with aquatic plants contribute higher. As investigating the influence mechanism of seasonal water level regulation on sediment biomarkers in WLFZ, and presenting their tracer information, this study provides basic datasets for further study of environmental geochemical cycle of biomarkers in TGRR.
Keywords:Three Gorges Reservoir Region  water level fluctuation zone  biomarkers  spatial-temporal variation  source analysis  
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