【作者】 张娟；

【导师】 王仁卿；

【作者基本信息】 山东大学 ， 环境科学， 2012， 博士

【摘要】 脂肪烃和多环芳烃是石油烃的两大主要成分,而前者又是石油烃中所占比例最大的一类。运用气相色谱(GC)分析正构烷烃(N-alkanes)、类异戊二烯、不可分辨的复杂混合物(UCM)及总脂肪烃浓度(TAH),运用气相质谱(GC/MS)分析甾烷、萜烷等生物标志物浓度,不仅可以用以评估大气、水、土壤和沉积物中的石油污染情况,并且基于以上物质的浓度的地球化学参数也可以为石油的来源、沉积环境及降解程度等提供重要的信息。磷脂脂肪酸技术(PLFA)能够反映土壤中的微生物群落结构在不同的土壤类型、不同的管理模式、不同的气候条件及重金属及有机污染物的影响下的响应策略。使用软件CANOCO4.5进行主成分分析(PCA),可以对多元数据进行降维,保留其主要信息的同时将数据集简单化。在地球化学研究中,运用PCA能够将不同来源的污染物加以区分,并且能够将受到不同来源的污染物影响的大气、水、土壤和沉积物样品加以区分。使用CANOCO4.5进行冗余分析(RDA),可以用一个多元数据集去解释另外一个多元数据集。并且与CANOCO绑定的画图软件CanoDraw for Windows可以将PCA和RDA结果形象地呈现出来。此外,单体碳稳定性同位素因其特征性和相对稳定性近年来被越来越多的应用于环境中污染物质的来源解析。本论文中运用GC分析正构烷烃、类异戊二烯、UCM及总脂肪烃浓度,评估重工业城市沈阳市(中国东北)西南部的浑浦污灌区的大气、地表水、地下水及土壤中的石油污染和降解程度及识别石油烃来源,运用GC/MS分析甾烷、萜烷等生物标志物浓度,以及运用磷脂脂肪酸技术,补充性地研究浑蒲污灌区表层土壤中的石油污染和降解程度及来源；运用正构烷烃、类异戊二烯和UCM的浓度结合多元统计学分析方法(PCA和RDA)区分浑浦污灌区的大气、地表水、地下水及土壤中不同来源的污染物及对受到不同来源的污染物影响的大气、水和土壤样品加以区分,用土壤基本性质解释上壤中烃的组成,计算大气和灌溉水中的脂肪烃对土壤中脂肪烃的贡献率。此外运用正构烷烃单体碳稳定性同位素技术补充性地研究大气、地表水、地下水及土壤中脂肪烃的来源,以及结合多元统计学分析方法计算大气和灌溉水中的脂肪烃对土壤中脂肪烃的贡献率,并将同位素方法与化学指纹法比较分析。具体研究结果如下：位于正在作业的油井附近并且靠近细河下游的旱田土壤中石油烃的浓度最高(表层土中Σn-alkanes为30.4±3.2μg-1,TAH为151.9±19.9μg-1；土壤剖面中Σn-alkanes为11.0±1.4μgg-1,TAH为190.8±12.1μg g-1),而由于土壤中的水分及使用污水灌溉会促进有机污染物质在土壤中垂直向下迁移,导致细河下游水田表层土(0-10cm)中的正构烷烃、UCM和TAH的浓度最低Σn-alkanes为20.9±1.0μg g-1,TAH为82.8±4.2μg g-1)。来源于有氧的淡水湖相或海洋三角洲沉积环境,而不是缺氧的碳酸盐或泥灰土源岩的高沸点的重油是浑蒲灌区表层土中脂肪烃的主要来源,而轻油及生物源的烃也是浑蒲灌区表层土中脂肪烃的来源之一。浑蒲灌区旱田表层土壤中石油污染和降解的程度比水田表层土壤中石油污染和降解的程度要高。PCA研究发现浑蒲灌区旱田表层土壤中微生物PLFA的组成与水田表层土壤中微生物PLFA的组成存在明显的不同,而且相对于水田而言,旱田之间表层土壤中微生物PLFA的组成的相似程度较高。尤其是位于废弃10多年之久的油井附近的I-1U旱田和位于正在开采的油井附近的I-4U旱田表层土壤中微生物PLFA的组成的相似程度更高。水田土壤中微生物PLFA15：0、3-OH12：0和16：1(9)的浓度显著高于旱田,而PLFAi16：0、18：1(9)c和18：2(9,12)/18：2ω6,9的浓度显著低于旱田,这对了解不同类型的七壤中微生物对石油污染的响应及今后的修复工作都具有重要的意义。根据地球化学特征结合PCA分析浑蒲灌区土壤剖面中烃的来源发现,受来源于周围废弃的油井和正在开采的油井的石油直接输入影响的I-2U和I-6U剖面,含有丰富的烃(Σn-alkanes为1.1-16.4μgg-1dry wt.,TAH为10.9-161.12μgg-1dry wt.),具有明显的石油来源的烃的地球化学特征,通过PCA分析聚集在一起；受污水灌溉来源的石油烃影响的I-5P和I-7P剖面的烃浓度也很高,通过PCA分析来自这两个剖面的的土壤样品聚集在一起。通过PCA分析,附近没有发现明显的污染源、烃浓度较低的I-1P和I-4U剖面中的土壤样品聚集在一起(Σn-alkanes为0.5-4.0μg g-1,TAH为1.6-23.8μg-1),生物源的烃是其烃的主要来源,主干渠灌溉的I-3P与受大气沉降影响的I-8U聚集在一起。RDA结果表明土壤中脂肪烃的分布会受到土壤基本性质的影响。通过地球化学分析,研究发现除了降解的石油源的烃,浑蒲灌区的地表水和地下水也接收了少量的陆源高等植物、微生物及水生生物来源的脂肪烃的输入。尽管不同季节的大气沉降中烃的浓度和来源有差异,但是发生降解的重油也是浑蒲灌区的大气干湿沉降中烃的主要来源。此外,还有少量的生物源的烃和轻油来源的烃的输入。采油井附近和细河河段附近的地下水中的烃浓度比较高,而且2009年10月份采集的地下水受石油污染的程度和其中石油烃的降解程度显著高于2009年5月份采集的地下水。2009年5月采集的地下水样品中正构烷烃的浓度范围为88.5到855.3μg L-1,UCM的浓度范围为262.2到5946.9μg L-1,TAH的浓度范围为357.0到6802.1μg L-1。2009年10月采集的地下水样品中正构烷烃的浓度范围为37.8到1042.0μg L-1,UCM的浓度范围为871.5到9301.1μg L-1,TAH的浓度范围为909.3到10343.1μg L-1。春季采集的大气沉降中正构烷烃的浓度最高(841.2μg m-2d-1),冬季采集的大气沉降中正构烷烃的浓度最低(76.6μg m-2d-1),夏季和秋季采集的大气沉降中UCM和TAH的浓度最高(UCM和TAH的浓度分别为13173.7和13859.9μg m-2d-1),冬季采集的大气沉降中UCM和TAH的浓度最低(UCM和TAH的浓度分别为147.9和224.5μg m-2d-1)。不同时期的大气沉降样品和不同时期、不同采样点的水样品中脂肪烃浓度和脂肪烃组成的相似性和差异都能够清晰明了地成功呈现在主成分空间投影图中。浑蒲灌区不同时期灌溉水、大气干湿沉降及表层土壤中脂肪烃的组成结合冗余分析结果表明,2009年度的灌溉水及大气干湿沉降中的脂肪烃组成总共可以解释69.5%的浑蒲灌区表层土壤中脂肪烃的组成,这说明石油烃可以在不同的介质之间迁移,浑蒲灌区灌溉水和大气沉降的石油污染对表层土壤的石油污染有很大的影响。灌溉水的石油污染对表层土壤的石油污染的影响远远大于大气干湿沉降的石油污染对表层土壤的石油污染的影响,不同时期的水样品中脂肪烃的组成解释的土壤中脂肪烃的组成的方差为66.0%,不同时期的大气干湿沉降样品中脂肪烃的组成解释的土壤中脂肪烃的组成的方差为12.2%。2009年5月采集的水样品中的脂肪烃组成和2009年10月采集的水样品中的脂肪烃的组成分别能解释的土壤中的脂肪烃的组成的方差为70.5%和37.0%,表明5月份的灌溉水的石油污染对表层土的石油污染的影响比10月份的灌溉水的石油污染对表层土的石油污染的影响大,这是因为5月份是主要的灌溉季节。通过样品中正构烷烃单体碳稳定性同位素比率(δ13C)特征结合化学指纹特征的研究,在2008年10月采集的浑蒲灌区的灌溉水、2009年度采集的大气干湿沉降及2009年10月采集的表层土壤中,识别出了现代陆生C3植物来源和石油及其降解产物来源的正构烷烃的输入。地表水细河水中的正构烷烃单体碳稳定性同位素组成与地下水之间的差异十分显著,距离细河最近的水田的地下水I-3G受到细河水的影响最大,其正构烷烃单体碳稳定性同位素组成与细河水相似,与其他地下水之间的差异十分显著。位于正在作业的采油井附近的I-4G地下水中的正构烷烃的成熟度相对其他水样品较高。正构烷烃单体碳稳定性同位素组成在浑蒲灌区的水样品与大气沉降样品之间及不同时期的大气样品之间均存在显著的差异。同时,这些研究结果清晰明了地成功呈现在正构烷烃δ13C主成分空间投影图中。脂肪烃的地球化学特征和PCA分析结果都表明,沸点高的重油是2008年10月采集的浑蒲灌区的地下水和地表水以及2009年度大气沉降中脂肪烃的主要来源,受不同污染源影响的烃浓度和地化特征不同的浑蒲灌区水样品和大气沉降在主成分空间被很好地排序出来。在正构烷烃813C的主成分空间中,不同来源的高碳数、中等碳数与低碳数的正构烷烃得到更好地区分,而不同的样品由于受多种不同环境因素的影响排序结果更为分散,这说明正构烷烃δ13C包含的地球化学信息更完整。化学指纹和同位素组成的RDA结果均表明,浑蒲灌区的灌溉水的石油污染对表层土壤的石油污染的影响大于大气干湿沉降的石油污染对表层土壤的石油污染的影响,距离细河最近的I-4G地下水及细河水的石油污染对表层土壤的石油污染的影响是显著的。2008年10月的灌溉水中脂肪烃的组成和2009年度的大气沉降样品中脂肪烃的组成分别能解释的土壤中脂肪烃的组成的方差为28.2%和7.7%。2008年10月的灌溉水和2009年度的大气沉降样品中正构烷烃613C分别能解释的土壤中正构烷烃δ13C的方差为46.4%和24.4%。灌溉水和大气沉降样品中正构烷烃δ13C解释的土壤中正构烷烃613C的方差,比灌溉水和大气沉降样品中脂肪烃解释的土壤中脂肪烃的方差要多。而且相对大气样品中的脂肪烃解释的土壤中的脂肪烃,大气沉降样品中正构烷烃613C能解释的土壤中正构烷烃δ13C的方差较大,说明有可能化学指纹法会低估灌溉水和大气干湿沉降石油污染(尤其是大气沉降)对表层土壤中石油污染的影响。更多还原

【Abstract】 Aliphatic hydrocarbons and aromatic hydrocarbons are major components of petroleum hydrocarbons. Aliphatic hydrocarbons constitute the bulk of an oil. Generally, normal/isoprenoid alkanes and total resolved/unresolved (UCM) petroleum hydrocarbons were quantified on the gas chromatography (GC), whereas the terpane, sterane, and aromatic hydrocarbon were determined by GC/MS (mass spectrometry). They can be used to assess total oil concentrations and petroleum contamination in air, water, soil and sediments. Geochemical parameters based on them can also provide information on petroleum degradation, depositional environment and petroleum source. The phospholipid fatty acids (PLFA) technique can be used to elucidate different strategies employed by microorganisms to adapt to changed environmental conditions under wide ranges of soil types, management practices, climatic origins and different perturbations (such as contamination of heavy metals and petroleum hydrocarbons).Principal component analysis (PCA) with software CANACO4.5can be efficiently used to simplify the complicated data set by reducing the number of dimensions without losing information contained in the complicated data set. In geochemical studies, pollutants from various sources as well as the air, water, soil, and sediment samples containing pollutants from various sources can be partitioned into different groups. Redundancy analysis (RDA) with software CANACO4.5can be efficiently used to explain one data set by another data set. And the results from PCA and RDA can be visualized with the bounded software CanoDraw for Windows. In addition, compound-specific isotope (CSIA) has been used to identify various sources of pollutants in recent years because of their stability and specificity.In this paper, we used the concentrations of normal/isoprenoid alkanes and total resolved/unresolved petroleum hydrocarbons quantified on the GC to effectively evaluate the levels of petroleum contamination and degradation, as well as identify the petroleum sources of atmospheric deposition, surface water, groundwater, and soil in the Hunpu wastewater irrigation area, located in the southwest of Shenyang City, a heavy industrial city, in China’s northeast. We used the concentrations of terpane and sterane quantified on the GC/MS and PLFA to complementally evaluate the levels of petroleum contamination and degradation, as well as identify the petroleum sources of surface soil in the Hunpu wastewater irrigation area. We used the concentrations of normal/isoprenoid alkanes and UCM combined with multivariate statistical analysis (PCA and RDA) with the CANOCO4.5software to differentiate pollutants from various sources as well as the air, water, and soil samples containing pollutants from various sources, to explain the different distributions of hydrocarbons in soil by the basic soil properties, and to calculate the different contributions of the aliphatic hydrocarbons in groundwater and air to the aliphatic hydrocarbons in surface soil. Moreover, we used carbon isotopic composition of n-alkanes to complementally identify the petroleum sources of atmospheric deposition, surface water, groundwater, and soil. We used CSIA combined with multivariate statistical analysis (PCA and RDA) differentiate pollutants from various sources as well as the air, water, and soil samples containing pollutants from various sources, and to calculate the different contributions of the aliphatic hydrocarbons in groundwater and air to the aliphatic hydrocarbons in surface soil. Finally, we compared the results from CSIA with those from chemical fingerprinting analysis. The results were shown as follows:The aliphatic hydrocarbon concentration was highest in the samples obtained from the upland field near an operational oil well and the lower reaches of the Xihe River (Σn-alkanes in surface soil samples.30.4±3.2μg g-1and TAH in surface soil samples:151.9±19.9μg g1;Σn-alkanes in soil profiles:11.0±1.4μg g-1and TAH in soil profiles:190.8±12.1μg g1); it was lowest in surface soil samples in paddy fields where wastewater irrigation promoted the downward movement of hydrocarbons (Σ-alkanes:20.9±1.0ug g-1and TAH:82.8±4.2μg g-1). The surface soil in Hunpu region was found contaminated by heavy petroleum from oxic lacustrine fresh water or marine deltaic source rocks rather than petroleum from anoxic lacustrine, saline, marine evaporitic or marine carbonate depositional environment. Hydrocarbons from light oil and biogenic hydrocarbons were also identified in these samples. Geochemical parameters also indicated significantly heavier contamination and degradation in the upland fields compared with the paddy fields.PCA based on PLFAs showed various microbial communities and their different response to petroleum contamination between upland and paddy fields, and the PLFA compositions of upland fields were more similar than those of paddy fields, especially I-2U (near abandoned oil well more than ten years ago) and I-4U (near operating oil well). PLFA concentrations of15:0,3-OH12:0, and16:1(9) were significantly higher in paddy fields, whereas i16:0and18:1(9) c were significantly higher in upland fields (p<0.05). Poly-unsaturated PLFA (18:2ω6,9; indicative of hydrocarbon-degrading bacteria and fungi) was also significantly elevated in upland fields. These results were important for knowing about various microbial responses to petroleum contamination in different fields and implementing the following works on remediation.Geochemical parameters based on the concentrations of normal/isoprenoid alkanes and UCM combined with results from PCA indicated that the soil profiles from I-2U and I-6U (with nearby oil wells still operating or abandoned) had rich hydrocarbons (Σn-alkanes:1.1-16.4μg g-1dry wt. and TAH:10.9-161.2μg g-1dry wt.), obvious characteristics of petroleum hydrocarbons, and were grouped together by PCA. The hydrocarbon concentrations of the samples from I-5P and I-7P were also high and they were grouped together because of wastewater irrigation. Another group contained I-1P and I-4U (Σn-alkanes:0.5-4.0μg g-1and TAH:1.6-23.8μg g-1), which had a small hydrocarbons. Biogenic hydrocarbons dominated in most samples and no obvious pollution source was detected. I-8U was affected by atmospheric deposition and I-3P irrigated with water from the main canal had a similar pattern. The result from RDA indicated that the compositions of hydrocarbons in soil were also impacted by the soil properties.Geochemical analysis revealed the presence of biogenic (terrestrial plant wax, microbiota, and hydrobionts) and degraded petrogenic hydrocarbons in the surface water and the groundwater in the Hunpu region. The sources of hydrocarbons in the atmospheric deposition sampled in different seasons were various, but high carbon number hydrocarbons from degraded heavy oil were dominant in the atmospheric deposition samples in the region. Moreover, small biogenic hydrocarbons and hydrocarbons from light oil were identified in the atmospheric deposition samples. The hydrocarbon concentration in water was higher near oil wells and the Xihe River Reach. And the levels of petroleum pollution and degradation were significantly higher in groundwater in October2009[total aliphatic hydrocarbons (TAH):909.3-10343.1μg L-1] than those in May of the same year (TAH:357.0to6802.1μg L-1). For air, the concentrations of Σn-alkanes, unresolved complex mixture (UCM), and TAH were lowest in winter (Σn-alkanes:76.6μg m-2d-1, UCM:147.9μg m-2d-1, and TAH:224.5μg m-2d-1); the n-alkanes were more abundant in spring (841.2μg m-2d-1); and UCM and TAH were more abundant in summer and autumn (UCM:13173.7μg m-2d-1and TAH:13859.9μg m-2d-1).Through PCA, the water and air sampled in different seasons and sites were differentiated based on their degree of petroleum pollution and various aliphatic hydrocarbon compositions. Through RDA, we found that69.5%of the variance of hydrocarbons in the soil could be explained by all measured water and air samples, which indicated that the petroleum hydrocarbons could migrate among different medium and the petroleum contamination of the water and air had an important effect on the surface soil. The66.0%of the variance of hydrocarbons in the soil could be explained by measured water and12.2%of the variance of hydrocarbons in the soil could be explained by the bulk atmospheric deposition, which indicated that the irrigated water had a bigger effect on the surface soil than the air. The variance of hydrocarbon composition in soil explained by the hydrocarbon composition in water collected in May2009was70.5%, whereas the value for the water collected in October was37.0%. The reason is that the farmlands in the Hunpu region are mainly irrigated in May. ⅠThe n-alkanes in the atmospheric deposition (2009), the surface water (October2008), the groundwater (October2008), and the surface soil (October2009) in the Hunpu wastewater irrigation area were from modern C3plants and degraded petroleum and its products, which were indicated by the stable carbon isotope ratios (δ13C) of n-alkanes and the geochemical parameters based on the concentrations of normal/isoprenoid alkanes and UCM. The carbon isotopic composition of n-alkanes in the surface water (Xihe River) was significantly different from that in the groundwater. The groundwater I-3G (collected in the paddy fields) came from areas nearest to the Xihe River and was affected by the Xihe River. Therefore, the carbon isotopic composition of n-alkanes in I-3G was similar with that in the water from the Xihe River and significantly different from that in other groundwater. Higher maturity of δ13C of n-alkanes was discovered in the groundwater Ⅰ-4G collected in the upland fields near the operational oil well. The differences between the carbon isotopic compositions of n-alkanes in water and those in atmospheric deposition samples collected in different periods were significant. The differences between the carbon isotopic compositions of n-alkanes in atmospheric deposition samples collected in different periods were also significant. These results described above were all visualized through PCA of513C of n-alkanes.Through PCA and geochemical analysis of the concentrations of normal/isoprenoid alkanes and UCM, the hydrocarbons from heavy oil with the high boiling points was found dominant in the surface water and the groundwater samples collected in October2008and the atmospheric deposition samples collected in different periods in 2009. Various concentrations and geochemical characteristics of the aliphatic hydrocarbons were discovered in the water and the air samples affected by various pollution sources, which were well visualized in the diagram obtained from PCA.In PCA of δ13C of n-alkanes, high carbon number hydrocarbons, middle carbon number hydrocarbons and low carbon number hydrocarbons from various sources were partitioned into different groups. The samples affected by various sources and environmental factors were more dispersed in PCA of δ13C of n-alkanes, compared with the results from PCA of the concentrations of n-alkanes. Differences between the results from PCA of δ13C and those from PCA of the concentrations of n-alkanes indicated that more geochemical information could be presented by analyzing δ13C of n-alkanes.The results from RDA of δ13C and the concentrations of n-alkanes indicated that petroleum contamination in the irrigated water had a bigger effect on petroleum contamination in the surface soil than that in the atmospheric deposition in the Hunpu region. The δ13C and the concentrations of n-alkanes in the water from the Xihe River and the groundwater I-4G (upland fields, came from areas nearest to the Xihe River) were significantly correlated with those in surface soil in the region. The28.2%of the variance of hydrocarbon concentrations in the soil could be explained by measured water (October2008) and7.7%of the variance of hydrocarbon concentrations in the soil could be explained by the bulk atmospheric deposition (2009). The46.4%of the variance of δ13C in the soil could be explained by measured water (October2008) and24.4%of the variance of δ13C in the soil could be explained by the bulk atmospheric deposition (2009). The variance of δ13C in the soil explained by all measured water and air samples was higher than the variance of hydrocarbon concentrations in the soil explained by all measured water and air samples. And the variance of δ13C in the soil explained by the bulk atmospheric deposition was higher than the variance of hydrocarbon concentrations in the soil explained by the bulk atmospheric deposition. These results indicated that the effect of petroleum contamination in the irrigated water and atmospheric deposition (especially petroleum contamination in the atmospheric deposition) on petroleum contamination in the surface soil was underestimated through analyzing hydrocarbon concentrations compared with δ13C.更多还原