YIC-IR  > 中科院烟台海岸带研究所知识产出
基于同位素混合模型方法的渤海及沿岸河流氮源汇关系研究
于靖1,2
学位类型博士
导师张华
2017-11-23
学位授予单位中国科学院大学
学位授予地点北京
关键词渤海及沿岸河流 源解析 稳定同位素 Bayesian混合模型 Bohai Sea And Surrounding Rivers Nitrogen Source Apportionment Stable Isotopes Bayesian Mixing Model
摘要渤海是典型的半封闭性浅层陆架海,有包括黄河在内的数十条河流汇入,随着工农业及城市化的不断发展,人类活动对渤海及沿岸河流过量的氮输入增加了环境的氮负荷,渤海成为重要的陆源氮汇。研究渤海及周边河流不同形态氮在时间和空间尺度上的分布特征及来源差异对全面认识海岸带氮的地球化学行为和源汇关系具有重要意义。本研究以渤海沉积物和30条主要入海河流水体为研究对象,分析渤海沉积物氮的空间分布特征和河流水体溶解态无机氮(DIN)、颗粒态氮的时空变化及影响因素,探讨各地球化学参数间的相互关系,结合稳定同位素组成和Bayesian模型估算渤海沉积物氮的源贡献比,估算河流各种形态氮潜在来源贡献率的时空差异,探究海岸带地区不同受体环境硝态氮(NO3--N)、铵态氮(NH4+-N)和有机氮来源的贡献规律。取得的主要结论如下:
整个渤海表层沉积物总有机碳(TOC)与总氮(TN)含量呈显著正相关,两者浓度在渤海中部泥质区含量较高。沉积物δ13C-TOC值(-23.59‰~ -19.54‰)和δ15N-TN值(+2.80‰~+8.07‰)的定性分析表明渤海沉积物有机质主要受海洋内源、大气沉降和河流输入来源的影响。基于δ13C-TOC、δ15N-TN和MixSIR模型的源解析结果阐明,渤海沉积物主要来源为自生性内源有机质,其贡献率约为69.0%;其次是大气沉降,其贡献率高达21.4%;河流输入贡献的有机质含量仅为9.6%。空间上,海洋内源、大气沉降和河流输入对渤海不同区域沉积物的有机质贡献具有差异性。其中,大气沉降(24.9%)对渤海湾的贡献率明显高于渤海其他区域。基于渤海沿岸城市估算的大气沉降对渤海有机碳通量(180809吨)和四条大河颗粒态有机碳的平均浓度估算的河流输入通量(33905.4吨)验证了模型结果,表明环渤海地区大气沉降对渤海沉积物有机质的贡献高于河流输入,成为现阶段渤海沉积物有机质的主要陆源输入途径。
入海河流悬浮颗粒物浓度6月最高(43.76±53.06 mgL-1),12月最低(30.04±53.38 mgL-1)。氮和碳的同位素组成大小为6月>9月>12月。混合模型的定量结果显示,6月颗粒态有机质(POM)来源以污水(29.3%)、陆生植物(23.0%)和浮游藻类(20.8%)为主,9月主要来源为浮游藻类(44.2%)和陆生植物(22.7%),12月为浮游藻类(45.5%)、陆生植物(24.7%)和土壤(18.2%)。空间上,黄河POM的最大来源是土壤,其他水系主要来源为内源浮游藻类和陆生植物碎屑。河流DIN以NO3--N和NH4+-N为主且冬季(12月)浓度较高,水体δ15N-NO3-值无明显季节差异,但δ18O-NO3-值差异明显,6月最高(15.00±7.00‰),12月最低(5.99±3.87‰)。NO3-的主要来源为生活污水和畜禽粪便;大气沉降的贡献从6月到12月呈递减态势。6月NO3-的主要来源为畜禽粪便(27.1%)、大气沉降(23.4%)和生活污水(15.0%);9月畜禽粪便(23.2%)、生活污水(20.7%)、土壤氮(16.8%)和硝态氮肥(15.7%)是主要来源;12月以生活污水(23.4%)、畜禽粪便(20.6%)和土壤氮(19.6%)来源为主。空间上,NO3-来源的贡献差异与土地利用类型和悬浮颗粒含量有关:黄河流域污水和土壤氮为主要来源;滦河水系和海河水系硝态氮肥对NO3-的贡献较高;辽河水系和莱州湾诸河中土壤氮的贡献升高。河流NH4+浓度6月和9月受大气沉降影响较大,12月份主要以人畜粪肥和燃料燃烧为主。
为深入探究河流氮的来源特征,本研究选取黄河为研究对象,进行为期一年的观测,结果如下:黄河下游DIN以NO3--N为主,夏季浓度(1.31±0.14 mgL-1)低于其他季节(2.68±0.52mgL-1);冬季和春季的NH4+-N和NO2--N浓度高于夏季和秋季。汛期δ15N-NO3-和δ18O-NO3-偏低,非汛期偏高,二者呈显著正相关。MixSIAR源解析表明,全年NO3-来源的贡献依次为生活污水(24.7%)>土壤(24.4%)>铵态氮肥(19.7%)>畜禽粪便(14.8%)>硝态氮肥(10.9%)>大气沉降(5.5%);汛期土壤(28.2%)是主要来源,非汛期以生活污水(24.7%)为主。下游流量与悬浮物浓度显著正相关,且夏季PN浓度、δ15N-PN及δ13C-POC值高于秋冬季。全年土壤和河流内源是下游有机质的主要来源,依次为土壤(35.7%)、水生植物(23.0%)、浮游藻类(21.5%)、陆生植物(14.5%)、污水(5.3%)。汛期POM的最大贡献者为土壤(29.0%),非汛期以浮游藻类(35.8%)贡献为主。对比全年的源解析发现,土壤氮对NO3--N和PN两种形态贡献很大;生活污水对下游氮的贡献形态以NO3--N为主,对PN贡献率较低。基于Bayesian算法的MixSIR和MixSIAR模型可以用于不同受体的来源解析过程中,为探究海岸带不同形态氮潜在的多种来源提供有效的数值模拟方法。
其他摘要The Bohai Sea is a typical semi-closed shallow shelf, with dozens of rivers including the Yellow River flowing into it. With the rapid development of industry and agriculture, in conjunction with the rapid process of urbanization, excessive nitrogen in the Bohai Sea and surrounding rivers from human activities would increase the nitrogen load. As a result, Bohai Sea becomes a vital pool of terrigenous nitrogen. To study the distribution characteristics and source apportionment of various nitrogen species in Bohai Sea and surrounding rivers on spatio-temporal scale can offer comprehensive knowledge of geochemical characteristics and the nitrogen source-sink relationship in coastal zone. In this research, multi-medium samples, including surface sediment in Bohai Sea, riverine water and total suspended particulate matter in 30 rivers, were collected to analyze the spatial distribution characteristics of nitrogen in surface sediment of Bohai Sea, also to realize the spatio-temporal variation features and influence factors of the dissolved inorganic nitrogen (DIN) and particulate nitrogen in surrounding rivers. The relationship among various geochemical parameters were discussed in this study. The source contributions of nitrogen in surface sediment and source proportions of various nitrogen forms in water and suspended particulate matter on temporal and spatial scales were estimated by the combination of stable isotopes and Bayesian model, which can illuminate the source apportionment of nitrate-nitrogen (NO3--N), ammonium-nitrogen (NH4+-N) and organic nitrogen in different sink of coastal zone. The main formations are as follows:
The total organic carbon (TOC) contents in surface sediment of the whole Bohai Sea showed significant positive correlation with total nitrogen (TN) contents, whose highest values were in the mud zone of the Bohai Central. The qualitative analysis of the values of δ13C-TOC (-23.59‰ to -19.54‰) and δ15N-TN (+2.80‰ to +8.07‰) indicated three dominant sources including marine phytoplankton, riverine source, and atmospheric deposition contributed to surface sediments organic matter (OM). The results based on combination of δ13C-TOC, δ15N-TN and the MixSIR model revealed the dominant OM source was marine phytoplankton, with an approximate contribution of 69.0%; atmospheric deposition as another main source contributed around 21.4% and riverine input contributed only 9.6%. On the spatial scale, the contributions of marine phytoplankton, atmospheric deposition and riverine input were different in each area of Bohai Sea. Higher proportion contribution of atmospheric deposition was observed in Bohai Bay (24.9%) than other areas, which demonstrated the heavy air pollution in North China Plain. Furthermore, the MixSIR results revealed that atmospheric deposition contributed more OM than riverine input in Bohai Sea, and became the major pathway of transporting terrestrial OM to the sediment. This conclusion was confirmed by calculation of OM flux from atmospheric deposition (180809 ton) and flux from river input (33905.4 ton). The former was estimated by OC in total suspended particulates of atmosphere around coastal cities and the latter was calculated by average POC concentration of four larger rivers.
In surrounding rivers, total suspended particulate matter content was highest in June (3.76±53.06 mgL-1) and lowest in December (30.04±53.38 mgL-1). The trend of carbon and nitrogen isotopes was June > September > December. Based on Bayesian mixing model results, particulate organic matter (POM) was derived from sewage (29.3%), terrestrial plants (23.0%), planktonic algae (20.8%) in June. Plandtonic algae (44.2%) and terrestrial plants (22.7%) were two main sources of POM in September. The dominant sources of POM in December were algae (45.5%), terrestrial plants (24.7%) and soil OM (18.2%). Especially, soil OM was primary source in the Yellow River, while autochtohnous POM and land plants are main sources in other rivers. NO3--N and NH4+-N were dominant DIN species, showing highest concentrations in winter (December). The monthly variation of δ15N-NO3- was not obvious, but δ18O-NO3- values was showed significant variation by month, with highest values in June (15.00±7.00‰) and lowest values in December (5.99±3.87‰). The results of Bayesian mixing model suggested that domestic sewage and manure were dominant NO3- sources during the whole year, atmospheric deposition contributed most in June, then decreased to December gradually. Further, main sources of NO3- in June were manure (27.1%), atmospheric deposition (23.4%) and domestic sewage (15.0%); Manure (23.2%), domestic sewage (20.7%), soil (16.8%) and nitrate-N fertilizer (15.7%) were primary sources in September; NO3- were mainly derived from domestic sewage (23.4%), manure (20.6%) and soil (19.6%) in December. The spatial variations of source contribution were related to the land use type and river characteristics: NO3- in Yellow River was derived from domestic sewage and soil. Nitrate-N fertilizer contributed more NO3- in Luanhe River system and Haihe River system. The proportion of soil increased in Liaohe River system and rivers around Laizhou Bay. Moreover, contents of NH4+ in rivers were affected by atmospheric deposition in June and September, while dominant sources were livestock manure and fuel combustion in December.
In order to analyze nitrogen source characters, Yellow River was chosen to study the various nitrogen source during a whole year. The results are as follows: NO3--N was dominant DIN species at downstream of the Yellow River. The concentration of NO3--N in summer (1.31±0.14 mgL-1) was lower than that in other seasons (2.68±0.52mgL-1). The contents of NH4+-N and NO2--N in spring and winter were higher than that in summer and autumn. The δ15N-NO3- values were correlated with δ18O-NO3- values, which were lower during high flow season. The MixSIAR analysis indicated that sources of NO3- in whole year showed domestic sewage (24.7%) > soil (24.4%) > ammonium-N fertilizer (19.7%) > manure (14.8%) > nitrate-N fertilizer (10.9%) > atmospheric deposition (5.5%). Moreover, soil (28.2%) was main source during high flow season, while domestic sewage (24.7%) was primary source during other flow conditions. There were significant correlation between suspended particulate matter and water discharge, showing high values of PN, δ15N-PN and δ13C-POC in summer than autumn and winter. In the whole year, POM at downstream were derived from soil and river autochthonous OM. The contributions of each sources were followed by soil (35.7%), macrophytes (23.0%), planktonic algae (21.5%), terrestrial plants (14.5%) and sewage (5.3%). POM mainly derived from soil OM (29.0%) during high flow season, while planktonic algae (35.8%) was main source during other period. In general, compared with the various nitrogen species source apportionment in the whole year, soil was the primary source contributed both NO3--N and PN at downstream of the Yellow River. However, domestic sewage contributed more nitrogen to NO3--N rather than PN. MixSIR and MixSIAR models based on Bayesian algorithm can be used for source apportionment at various sink and provide a numerical simulation technology for study latent multiple sources of nitrogen species in coastal areas.
学科领域环境地学
文献类型学位论文
条目标识符http://ir.yic.ac.cn/handle/133337/22565
专题中科院烟台海岸带研究所知识产出
作者单位1.中国科学院烟台海岸带研究所
2.中国科学院大学
第一作者单位中国科学院烟台海岸带研究所
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于靖. 基于同位素混合模型方法的渤海及沿岸河流氮源汇关系研究[D]. 北京. 中国科学院大学,2017.
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