-
平原地区大型人工河道水质主要与汛期上游来水有关，而如何快速分析出上游来水对下游河道的影响是亟须解决的科学问题. 传统的水质参数（如：COD、TN、TP等）的测定耗时较长，无法即时分析出水质状况. 而溶解性有机物（DOM）对水质变化较为敏感、测试方便、耗时较小和可实现在线监测等优点，且DOM与水质参数之间也存在紧密联系[1].
溶解性有机质（DOM）是普遍存在于河流、土壤和沉积物中一类具有复杂结构的混合有机物，并在全球碳循环中具有重要作用[2-7]. 在自然水体中，DOM不仅可为水生生物提供能量，而且可参与水环境中物理、化学和生物反应等过程[8-12]. 同时可通过DOM荧光组分的荧光强度预测水质[13]. 此外DOM被认为是消毒副产物（DBPs）的前体，当饮用含有过量DBPs的饮用水，可能会对人体健康产生影响[14-15].
新汴河是当代挖掘的一条大型人工河流，流经安徽、江苏两省，最终汇入洪泽湖. 作为一条以引洪为主的人工河道，两岸几乎没有支流汇入，所谓支流皆为上游截引河道，有沱河上段和萧濉新河等，因此其水质多受控于上游来水，汛期时水质较差[16-17]. 新汴河不仅是“淮水北调”的重要通道，而且新汴河宿州市城区段为宿州市重要的备用水源地. 因此研究新汴河上覆水中DOM的三维荧光特征及水质状况将有利于汛期新汴河水环境管理工作的开展.
-
新汴河是位于安徽省宿州市和江苏省宿迁市境内的一条人工河流，全长127.2 km，设计流量为1460 m3·s−1，历史最大流量801 m3·s−1. 2020年统计资料显示最高水位25.54 m，最低水位20.03 m，平均水位21.24 m. 由宿州市市区西北部途径灵璧县、泗县和泗洪县最终汇入洪泽湖. 流域面积约6562 km2, 主要功能有：解决外洪内涝灾害，兼顾农业灌溉与航运. 本次研究选取新汴河宿州城区段作为研究对象（图1）. 该区属于暖温带半湿润季风气候区，四季分明，年平均气温14.5 ℃，夏季雨水较多[18].
-
根据新汴河上游来水情况，于2022年3月15日（汛期来水前）和2022年7月12日（汛期来水时）对新汴河上覆水（水面下0.5 m）进行取样，将水样置于预先用超纯水清洗烘干后聚乙烯瓶中，置于4 ℃冰箱保存，于24 h内完成样品测试.
-
总氮（TN）过硫酸钾氧化分光光度法测定，总磷（TP）采用钼酸铵分光光度法测定，氨氮（NH4+-N） 使用纳氏试剂分光光度法进行测试，化学需氧量（CODCr） 以重铬酸钾作为氧化剂使用滴定法进行测试，化学需氧量（CODMn） 以高锰酸钾作为氧化剂使用滴定法进行测试. 溶解性有机碳（DOC）使用总有机碳分析仪（德国，耶拿）测定，营养指标及DOC测定过程中平行样品之间标准偏差小于5%.
-
三维荧光光谱采用Hitachi F-7000荧光分光光度计进行测试，测试参数为：激发波长（λEx）范围为200—400，间隔5 nm；激发波长（λEm）范围为250—500 nm，间隔1 nm. 利用超纯水作为空白，扣除拉曼散射的影响. 利用Matlab 2017b 结合drEEM 工具箱完成平行因子分析（PARAFAC），并通过拆半分析和残差分析验证结果的可靠性[2]. 对于DOM的来源，常使用指数fluorescence index （FI）和humification （HIX）进行判别. FI为激发波长为370 nm时，发射波长450 nm处荧光强度与发射波长500 nm处荧光强度比值[19]. HIX为当激发波长为255 nm时，发射波长434—480 nm处荧光强度积分与发射波长434—480 nm和300—344 nm荧光强度和的比值[19]. FI值大于1.9时意味着DOM具有较强的自生源特征，当FI小于1.4时表明DOM主要为陆源. HIX是表征DOM腐殖化程度的重要指标，HIX的变化范围介于0—1之间，值越大表明腐殖化程度就越大[20].
-
自组织神经网络是由Kohonen于1981年提出的一种无监督学习模型，并与人脑思考模式相似，且不改变数据的拓扑结构[21]. 与相关性分析和主成分分析相比，自组织神经网络不但具有较好的可视化效果，而且非常适合处理较为复杂的数据，并且SOM在处理复杂数据中具有良好的分类及聚集的能力，因此被广泛地应用于探究沉积物中重金属来源、地下水水化学特征和溶解性有机质光学特性等研究中[18, 22-23]. SOM模型构建过程可参考江雅琪等研究[18].
-
利用Arcgis 10.2 绘制采样点图，统计分析及绘图由 R Studio 1.4 完成. 利用Matlab 2017 完成平行因子分析及自组织神经网络分析.
-
由图2可知，受上游来水影响，新汴河上覆水中CODCr均值从28.63 mg·L−1上升至47 mg·L−1，CODMn均值从8.0 mg·L−1 上升至13.5 mg·L−1， TN均值从2.28 mg·L−1下降至0.99 mg·L−1. NH3-N、TP和DOC汛期前后没有显著性差异（图2）. 由此表明汛期新汴河上游来水中含量大量有机物，但TN含量较低.
-
如图3所示，对上游来水前后新汴河上覆水中DOM经过PARAFAC分析，共解析出3种组分（C1、C2、C3）. 将3个荧光组分同荧光在线光谱库（https://openfluor.lablicate.com/）中前人已发表文章中组分进行对比，组分C1、C2和C3均与已发表文章中组分具有较好的匹配（表1）. 组分C1最大荧光峰所对应Em/Ex （441 nm/255 nm）, 为典型的类腐殖质组分中的富里酸且与传统A峰所在位置极为相似[24]. 组分C2最大荧光峰所对应Em/Ex （378 nm/250 nm 285 nm），为微生物代谢所产生的类腐殖质[25]. 组分C3最大荧光峰所对应Em/Ex （321 nm/280 nm），为类色氨酸或类色氨酸类物质，且其与传统T峰所在位置接近，该组分常被用于表征人类活动（污水排放等）对水环境质量的影响[15, 26].
汛期上游来水后新汴河上覆水中各荧光组分（C1、C2和C3）含量均有上升趋势（图4）. 但类腐殖质组分（C1和C2）平均含量增加但不显著. 而类蛋白质组分C3含量较上游来水前显著增加（P<0.05）. 类腐殖质组分一般与农业面源污染有关，而类蛋白质组分与生活污水及工业废水排放存在联系[27]. 且新汴河上游零星散落村庄较多[17]，相对比城区其污水处理效率较低，可能是导致上游来水后新汴河上覆水中类蛋白质组分C3含量显著提升的原因.
-
由图5可知上游来水前后新汴河FI值介于1.4—1.9之间，表明新汴河上覆水中DOM受陆源和内源的共同影响[28]. 但上游来水后水样FI更偏向1.4，表明上游来水中可能含有较多陆源类DOM. 由图5所示，上游来水后新汴河上覆水中DOM的腐殖化程度具有较大差异，而来水前DOM腐殖化程度相对集中.
-
如图6（a）所示，CODCr和CODMn具有相似的颜色变化梯度，表明其两者之间存在显著正相关. 而已有研究表明，城镇生活污水排放及城市地表径流可能是COD等有机污染物主要来源[29]. TN、TP和NH3-N具有相似的颜色变化梯度，表明TN、TP和NH3-N可能具有相同的来源[18]. 新汴河周边堤坡种植情况普遍（图1），TN、TP和NH3-N可能受农业面源污染影响[30]. 荧光组分C1和C2具有相似的颜色变化梯度，且C1和C2为陆源类腐殖质，暗示C1和C2具有显著正相关, 表明组分C1和C2可能具有相同的来源. 并且DOC与C1、C2的颜色变化梯度较为相似，表明C1和C2可能是DOC的主要构成. 值得注意的是荧光组分C3与CODCr、CODMn之间颜色变化趋势也存在相似之处，极值均位于左下角，表明荧光组分C3可能是CODCr和CODMn的间接指示指标[2]. 而TN、TP和NH3-N与荧光组分（C1、C2和C3）之间不存在明显的相关. 如Tang等[2]研究宁波市城市化程度不同的河流荧光组分与水质参数之间关系，发现类腐殖质组分与COD之间存在正相关. 由此表明可能是由于河流环境水文地质条件不同，从而导致荧光组分与水质参数之间的关系存在差异. 结合图6（b） SOM-K平均值聚类可知左下角多为上游来水之后样品，同时也表明上游来水提高了荧光组分C3、CODCr和CODMn的含量. 结合图2和图4可知C3、CODCr和CODMn的含量在上游来水后均显著提高且存在显著差异，同时也表明自组织神经网络所能够反映各水质参数之间的相关性与含量变化[18].
-
（1）新汴河上游来水后上覆水中CODCr和CODMn的含量显著提高，表明上游来水中含有大量有机污染物.
（2）新汴河上游来时前后上覆水中DOM主要包含3种荧光组分：类腐殖质、微生物源类腐殖质和类蛋白质物质，且上游来水后显著提升类蛋白质组分的含量.
（3）新汴河上游来水前后上覆水中DOM受陆源及内源的共同作用，但上游来时后水体的陆源特征更为明显.
基于三维荧光-平行因子分析和自组织神经网络分析汛期上游来水对新汴河上覆水影响
Evaluating the influence of upstream inflow in flood season on the overlying water of the Xinbian River based on EEM-PARAFAC and SOM
-
摘要: 为探究汛期上游来水对新汴河上覆水水质影响，利用三维荧光-平行因子分析（EEM-PARAFAC）及自组织神经网络（SOM）分析上游来水前后新汴河上覆水水质参数、溶解性有机质（DOM）的变化. 结果表明：（1）汛期上游来水后CODCr和CODMn显著升高（P<0.01），而总氮（TN）的含量却显著降低（P<0.05），表明新汴河汛期上游来水中含有大量有机物；（2）基于EEM-PARAFAC解析出3种荧光组分，C1和C2为类腐殖质组分、C3为类蛋白质组分，上游来水后类蛋白质组分（C3）的含量显著提升（P<0.05），表明汛期上游来水中C3的含量相对较高；（3）SOM分析结果表明：新汴河汛期水质可能与城镇生活污水排放及城市地表径流有关；（4）新汴河上覆水中DOM受控于内源及陆源的共同作用，但汛期上游来水后新汴河上覆水DOM陆源性特征更加明显. 本研究探究了典型平原地区河流（新汴河）受汛期来水影响下水质及DOM的变化，以期为新汴河水环境管理方案的制订提供科学依据.Abstract: To explore the impact of upstream water in flood season on the water quality of the Xinbian River. The fluorescence emission excitation matrix combined with parallel factor analysis (EEM-PARAFAC) and self-organizing map (SOM) were used to analyze the changes in water quality parameters and dissolved organic matter (DOM) before and after upstream inflow. The results showed that: (1) CODCr and CODMn increased significantly (P<0.01) after the upstream inflow in the flood season, while the content of Total Nitrogen (TN) decreased significantly (P<0.05), indicating that the inflow water from the upstream of the Xinbian River during the flood season contained a large amount of organic matter; (2) Based on the EEM-PARAFAC analysis, three fluorescent components were analyzed, suggesting that C1 and C2 were humic-like components, and C3 was a protein-like component. The content of C3 in the upstream inflow water during the flood season was relatively high; (3) SOM analysis results show that: the water quality of the Xinbian River during flood season may be related to urban domestic sewage discharge and urban surface runoff; (4) DOM in the overlying water of Xinbian River was controlled by the combined effect of endogenous and terrestrial sources. However, the terrigenous characteristics of DOM in the overlying water of the Xinbian River were significant after the upper reaches of the flood season. This study explored the changes in water quality and DOM of the Xinbian River in a typical plain area under the influence of inflow during the flood season to provide a scientific basis for the formulation of the water environment management plan for the Xinbian River.
-
Key words:
- Xinbian river /
- dissolved organic matter /
- emission excitation matrix /
- PARAFAC.
-
-
图 2 上游来水前后水质参数箱体图
Figure 2. Box diagram of water quality parameters before and after upstream inflow
图 3 新汴河上游来水前后上覆水中DOM荧光组分及激发发射载荷图
Figure 3. The Ex/Em loadings of the fluorescent components and split-half validated by PARAFAC model
图 4 新汴河上游来水前后上覆水中DOM荧光组分含量箱体图
Figure 4. Box diagram of DOM fluorescence component content in overlying water before and after incoming water from the upper reaches of the Xin Bian River
图 5 新汴河上游来水前后荧光指数分布
Figure 5. Fluorescence index distribution before and after incoming water from the upper reaches of the Xin Bian River
图 6 新汴河上游来水前后水质参数和荧光组分分面图（a）自组织神经网络K-平均值聚类图（b）
Figure 6. Water quality parameters and fluorescence components before and after inflow into the upper reaches of the New Bianhe River （a） Self-organizing map K-mean clustering diagram （b）
表 1 荧光组分特征与同类组分匹配数目
Table 1. Spectral characteristics of Ex/Em of there fluorescent components.
组分
ComponentEx/Em 可能来源
Probable source匹配数目
Number of matchesC1 255/441 陆源，类腐殖质，分子量大 25 C2 250（285）/378 陆源，生物降解过程中产生小分子类腐殖质 27 C3 275/330 内源，类蛋白质，与人类活动有关 12 
下载: 导出CSV
-
[1] 曹昌丽, 梁梦琦, 何桂英, 等. 城镇化河流溶解性有机质的荧光特性与水质相关性: 以宁波市北仑区芦江为例 [J]. 环境科学, 2018, 39(4): 1560-1567. CAO C L, LIANG M Q, HE G Y, et al. Fluorescent dissolved organic matter and its correlation with water quality in a urban river: A case study of the Lujiang River in Beilun, Ningbo [J]. Environmental Science, 2018, 39(4): 1560-1567(in Chinese).
[2] TANG J F, LI X H, CAO C L, et al. Compositional variety of dissolved organic matter and its correlation with water quality in peri-urban and urban river watersheds [J]. Ecological Indicators, 2019, 104: 459-469. doi: 10.1016/j.ecolind.2019.05.025 [3] HU Y, LU Y H, EDMONDS J, et al. Irrigation alters source-composition characteristics of groundwater dissolved organic matter in a large arid river basin, Northwestern China [J]. Science of the Total Environment, 2021, 767: 144372. doi: 10.1016/j.scitotenv.2020.144372 [4] 鲁宗杰, 邓娅敏, 杜尧, 等. 江汉平原高砷地下水中DOM三维荧光特征及其指示意义 [J]. 地球科学, 2017, 42(5): 771-782. LU Z J, DENG Y M, DU Y, et al. EEMs characteristics of dissolved organic matter and their implication in high arsenic groundwater of Jianghan plain [J]. Earth Science, 2017, 42(5): 771-782(in Chinese).
[5] XU R H, OU H S, YU X B, et al. Spectroscopic characterization of dissolved organic matter in coking wastewater during bio-treatment: Full-scale plant study[J]. Water Science and Technology2015, 72(8): 1411-1420. [6] GU N T, SONG Q B, YANG X L, et al. Fluorescence characteristics and biodegradability of dissolved organic matter (DOM) leached from non-point sources in southeastern China [J]. Environmental Pollution, 2020, 258: 113807. doi: 10.1016/j.envpol.2019.113807 [7] MUELLER K K, FORTIN C, CAMPBELL P G C. Spatial variation in the optical properties of dissolved organic matter (DOM) in lakes on the Canadian Precambrian shield and links to watershed characteristics [J]. Aquatic Geochemistry, 2012, 18(1): 21-44. doi: 10.1007/s10498-011-9147-y [8] REN H Y, YAO X, MA F Y, et al. Characterizing variations in dissolved organic matter (DOM) properties in Nansi Lake: A typical macrophytes-derived lake in Northern China [J]. Environmental Science and Pollution Research, 2021, 28(41): 58730-58741. doi: 10.1007/s11356-021-14266-x [9] YU K, DUAN Y H, GAN Y Q, et al. Anthropogenic influences on dissolved organic matter transport in high arsenic groundwater: Insights from stable carbon isotope analysis and electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry [J]. Science of the Total Environment, 2020, 708: 135162. doi: 10.1016/j.scitotenv.2019.135162 [10] GUO H M, LI X M, XIU W, et al. Controls of organic matter bioreactivity on arsenic mobility in shallow aquifers of the Hetao Basin, P. R. China [J]. Journal of Hydrology, 2019, 571: 448-459. doi: 10.1016/j.jhydrol.2019.01.076 [11] CHEN M L, PRICE R M, YAMASHITA Y, et al. Comparative study of dissolved organic matter from groundwater and surface water in the Florida coastal Everglades using multi-dimensional spectrofluorometry combined with multivariate statistics [J]. Applied Geochemistry, 2010, 25(6): 872-880. doi: 10.1016/j.apgeochem.2010.03.005 [12] STAHL M, WASSIK J, GEHRING J, et al. Connecting the age and reactivity of organic carbon to watershed geology and land use in tributaries of the Hudson River [J]. Journal of Geophysical Research:Biogeosciences, 2021, 126(9): 1-17. [13] SHANG Y X, SONG K S, JACINTHE P A, et al. Fluorescence spectroscopy of CDOM in urbanized waters across gradients of development/industrialization of China [J]. Journal of Hazardous Materials, 2021, 415: 125630. doi: 10.1016/j.jhazmat.2021.125630 [14] WANG Y L, HU Y Y, YANG C M, et al. Variations of DOM quantity and compositions along WWTPs-river-lake continuum: Implications for watershed environmental management [J]. Chemosphere, 2019, 218: 468-476. doi: 10.1016/j.chemosphere.2018.11.037 [15] YU H, FENG S B. Optical property of dissolved organic matter and its correlation with heavy metals in surface water around metal mines to be exploited in southern Anhui Province, China [J]. Water Supply, 2022, 22(8): 6765-6776. doi: 10.2166/ws.2022.289 [16] YU H, LIN M L, PENG W H, et al. Seasonal changes of heavy metals and health risk assessment based on Monte Carlo simulation in alternate water sources of the Xinbian River in Suzhou City, Huaibei Plain, China [J]. Ecotoxicology and Environmental Safety, 2022, 236: 113445. doi: 10.1016/j.ecoenv.2022.113445 [17] JIANG Y Q, GUI H R, LI C, et al. Evaluation of the difference in water quality between urban and suburban rivers based on self-organizing map [J]. Acta Geophysica, 2021, 69(5): 1855-1864. doi: 10.1007/s11600-021-00631-4 [18] 江雅琪, 桂和荣, 陈晨, 等. 宿州市城市景区水域底泥重金属含量特征及生态风险评价 [J]. 环境化学, 2021, 40(8): 2410-2418. doi: 10.7524/j.issn.0254-6108.2020111302 JIANG Y Q, GUI H R, CHEN C, et al. Distribution and ecological risk assessment of heavy metals in sediment in urban scenic area [J]. Environmental Chemistry, 2021, 40(8): 2410-2418(in Chinese). doi: 10.7524/j.issn.0254-6108.2020111302
[19] WICKLAND K P, NEFF J C, AIKEN G R. Dissolved organic carbon in Alaskan boreal forest: Sources, chemical characteristics, and biodegradability [J]. Ecosystems, 2007, 10(8): 1323-1340. doi: 10.1007/s10021-007-9101-4 [20] MA Y, LIU Z H, XI B D, et al. Characteristics of groundwater pollution in a vegetable cultivation area of typical facility agriculture in a developed city [J]. Ecological Indicators, 2019, 105: 709-716. doi: 10.1016/j.ecolind.2018.10.056 [21] 于会彬, 宋永会, 杨楠, 等. 三维荧光与神经网络研究城市河流沉积物孔隙水有机物组成与结构特征 [J]. 光谱学与光谱分析, 2015, 35(4): 934-939. doi: 10.3964/j.issn.1000-0593(2015)04-0934-06 YU H B, SONG Y H, YANG N, et al. Characterizing structural composition of dissolved and particulate organic matter from sediment pore water in a urban river using excitation-emission matrix fluorescence with self-organizing map [J]. Spectroscopy and Spectral Analysis, 2015, 35(4): 934-939(in Chinese). doi: 10.3964/j.issn.1000-0593(2015)04-0934-06
[22] 聂泽宇, 邬剑宇, 吴小东, 等. 荧光溶解性有机质EEMs的新旧自组织映射图解析方法比较研究 [J]. 环境科学学报, 2017, 37(1): 357-369. doi: 10.13671/j.hjkxxb.2016.0149 NIE Z Y, WU J Y, WU X D, et al. Comparative study on the interpretation of EEMs of fluorescent dissolved organic matter using the new and traditional self-organizing map methods [J]. Acta Scientiae Circumstantiae, 2017, 37(1): 357-369(in Chinese). doi: 10.13671/j.hjkxxb.2016.0149
[23] RAHMAN A T M S, KONO Y, HOSONO T. Self-organizing map improves understanding on the hydrochemical processes in aquifer systems [J]. Science of the Total Environment, 2022, 846: 157281. doi: 10.1016/j.scitotenv.2022.157281 [24] DERRIEN M, KIM M S, OCK G, et al. Estimation of different source contributions to sediment organic matter in an agricultural-forested watershed using end member mixing analyses based on stable isotope ratios and fluorescence spectroscopy [J]. Science of the Total Environment, 2018, 618: 569-578. doi: 10.1016/j.scitotenv.2017.11.067 [25] ZHUANG W E, CHEN W, CHENG Q, et al. Assessing the priming effect of dissolved organic matter from typical sources using fluorescence EEMs-PARAFAC [J]. Chemosphere, 2021, 264: 128600. doi: 10.1016/j.chemosphere.2020.128600 [26] LU K T, GAO H J, YU H B, et al. Insight into variations of DOM fractions in different latitudinal rural black-odor waterbodies of Eastern China using fluorescence spectroscopy coupled with structure equation model [J]. Science of the Total Environment, 2022, 816: 151531. doi: 10.1016/j.scitotenv.2021.151531 [27] YANG X L, YU X B, CHENG J R, et al. Impacts of land-use on surface waters at the watershed scale in southeastern China: Insight from fluorescence excitation-emission matrix and PARAFAC [J]. Science of the Total Environment, 2018, 627,15: 647-657. [28] 高凤, 邵美玲, 唐剑锋, 等. 城镇流域水体-沉积物中溶解性有机质的荧光特性及影响因素: 以宁波市小浃江为例 [J]. 环境科学, 2019, 40(9): 4009-4017. GAO F, SHAO M L, TANG J F, et al. Fluorescence characteristics and influencing factors of dissolved organic matter (DOM) in water and sediment of urban watershed: A case study of Xiaojia River in Ningbo City [J]. Environmental Science, 2019, 40(9): 4009-4017(in Chinese).
[29] 张志彬, 孟庆宇, 马征. 城市面源污染的污染特征研究 [J]. 给水排水, 2016, 52(S1): 163-167. ZHANG Z B, MENG Q Y, MA Z, Study on pollution characteristics of urban non-point source pollution [J], Water & Wastewater Engineering, 2016, 52(S1): 163-167 (in Chinese). .
[30] 后希康, 张凯, 段平洲, 等. 基于APCS-MLR模型的沱河流域污染来源解析 [J]. 环境科学研究, 2021, 34(10): 2350-2357. doi: 10.13198/j.issn.1001-6929.2021.05.30 HOU X K, ZHANG K, DUAN P Z, WANG X, TA L, GUO Y, XIA R. Pollution Source Apportionment of Tuohe River Based on Absolute Principal Component Score-Multiple Linear Regression [J]. Research of Environmental Sciences, 2021, 34(10): 2350-2357(in Chinese). doi: 10.13198/j.issn.1001-6929.2021.05.30
-
点击查看大图
计量
- 文章访问数: 738
- HTML全文浏览数: 738
- PDF下载数: 23
- 施引文献: 0
