基于浮游植物吸收光谱提取粒径参数

在南海北部、大亚湾及珠江口3个不同水体生物-光学数据的基础上, 研究了浮游植物粒径结构的变化特征, 建立了基于浮游植物吸收光谱提取的浮游植物粒径参数(S<f>)的混合光谱模型。南海海区不同的水体环境下浮游植物的粒级结构有着很大的差异: 在河口和沿岸水体小型浮游植物占优势, 在外海水体微微型浮游植物占优势。浮游植物粒径参数随小型浮游植物增多而减少, 随微微型浮游植物增多而增大。叶绿素a浓度从外海到沿岸逐渐增大, 浮游植物粒径参数随叶绿素a浓度的增大而减小, 它们之间呈幂函数关系。结果表明, 利用混合光谱模型得到的浮游植物粒径参数与南海海区不同水体的生物-光学特征(粒级结构Rpico和Rmicro、粒级指数SI、叶绿素a浓度)有一定的相关性。具体的相关性表示为: S<f>与粒级结构(Rpico和Rmicro)存在一定的关系, 与小型浮游植物和微微型浮游植物之间的线性相关系数分别是0.55和0.65; S<f>与浮游植物粒级指数(SI)有较好的线性关系, 相关系数是0.57; S<f>与叶绿素a浓度呈幂函数关系, 相关系数是0.64。这个混合光谱模型为从光学参数反演浮游植物种群的生态学信息提供了有效的手段, 同时又可用于分析浮游植物优势粒径结构对光学特性的影响。     

基于船载走航观测高光谱颗粒物吸收系数反演浮游植物粒级结构*

利用高光谱监测数据反演浮游植物种群组成是当前海洋光学和水色遥感的研究热点。文章采用大西洋经向断面航次中走航式观测系统测量的海水总颗粒物吸收光谱数据, 尝试建立了两种模型对浮游植物粒级结构(Phytoplankton size class, 简称PSC)进行反演和比较讨论。一类模型是基于总颗粒物吸收光谱高斯分解获得的典型波段高斯带强度与色素浓度之间的关系, 建立了偏最小二乘回归模型(Partial Least Squares regression model, 简称PLS回归模型); 另一类模型是采用长波波段吸收基线高度推算海水总叶绿素a浓度, 进而根据Brewin等(2010)生物量算法推算PSC的三组分模型(简称三组分模型)。模型比较验证结果显示, 两类模型对海水总叶绿素浓度的反演都有较高的精度, 相对偏差ME在15%左右; 对于三个粒级浮游植物对应的叶绿素浓度(Pico级C_p, Nano级C_n, Micro级C_m)的反演效果也相当, PLS回归模型反演的ME分别为28.4%、31.9%和41%, 三组分模型反演的ME分别为31%、35.9%、37.7%。研究结果初步表明了采用高光谱吸收系数反演浮游植物种群结构的潜在优势, 可为不同海域走航式高光谱观测系统的推广应用提供思路。     

基于浮游植物吸收的海洋初级生产力模型的不确定性分析

Satellite-derived phytoplankton pigment absorption(a_(ph)) has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production(NPP). In this study, an a_(ph)-based NPP model(Ab PM) with four input parameters including the photosynthetically available radiation(PAR), diffuse attenuation at 490 nm(K_d(490)), euphotic zone depth(Z_(eu)) and the phytoplankton pigment absorption coefficient(a_(ph)) is compared with the chlorophyll-based model and carbon-based model. It is found that the Ab PM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbonbased model. For example, Ab PM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the Ab PM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference(δ), and logarithmic difference(δ~(LOG)) between model estimates and in situ data confirm that the two input parameters(Z_(eu) and PAR) approximate the Normal Distribution, and another two input parameters(a_(ph) and K_d(490)) approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the Ab PM was assessed by using the Monte Carlo simulation. Here both the PB(percentage bias), defined as the ratio of ΔNPP to the retrieved NPP, and the CV(coefficient of variation), defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to Ab PM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV.Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of5.5% covered a range of –5%–15% for the global ocean. The PB uncertainty of Ab PM model was mainly caused by a_(ph); the PB of NPP uncertainty brought by a_(ph) had an annual mean of 4.1% for the global ocean. The CV brought by all the parameters with an annual mean of 105% covered a range of 98%–134% for global ocean. For the coastal zone of Antarctica with higher productivity, the PB and CV of NPP uncertainty brought by all parameters had annual means of 7.1% and 121%, respectively, which are significantly larger than those obtained in the global ocean. This study suggests that the NPPs estimated by Ab PM model are more accurate than others, but the magnitude and scatter range of NPP errors brought by input parameter to Ab PM model could not be neglected,especially in the coastal area with high productivity. So the improving accuracy of satellite retrieval of input parameters should be necessary. The investigation also confirmed that the SST related correction is effective for improving the model accuracy in low temperature condition.     

长江口及其邻近海域CDOM光谱吸收特性分析

研究了长江口及其邻近海域有色可溶性有机物(CDOM)的光吸收特性,分析了CDOM浓度(吸收系数a(440))、光谱斜率(S_g)与盐度的关系。结果表明:长江口及其邻近海域CDOM的a(440)变化范围为0.21~0.85 m^-1,平均值为0.44 m^-1;S_g值的范围为0.013 3~0.016 7 nm^-1,平均值为0.014 nm^-1;a(440)的水平分布表现为长江口海区比外海区高,S_g的水平分布表现为长江口海区比外海区低,反映了长江口海区CDOM中的腐殖酸成分比外海区大。研究区内a(440)与盐度、S_g与盐度明显线性相关,表明CDOM在河口混合行为中呈保守行为,CDOM具有良好的保守性质。     

Development of an Analytical Method for the Determination of Trace Lead in Lake Water Samples by Flame Atomic Absorption Spectrophotometry after Vortex Assisted-Stearic Acid Coated Magnetic Nanoparticle Based Extraction

In the present study, a method is proposed for the determination of lead at trace levels by slotted quartz tube-flame atomic absorption spectrophotometry (SQT-FAAS) after preconcentration with stearic acid coated magnetic nanoparticle-based dispersive solid phase extraction (SA-MNP-DSPE). The slotted quartz tube (SQT) is used to enhance the analyte atom residence time in the light path. Stearic acid coated magnetic iron oxide (Fe₃O₄) nanoparticles, which can be easily collected with an external magnet, are used as adsorbent in the extraction process. The limit of detection (LOD) and the limit of quantitation (LOQ) values of the proposed method are obtained as 0.90 and 2.9 µg L⁻¹, respectively. The method allows high repeatability in a wide linear range between 5.0 and 250 µg L⁻¹, and the relative standard deviation for six replicates is 5.8%. The detection power is enhanced by about 77-fold compared to the regular flame atomic absorption spectrophotometry (FAAS) system. The method is validated by recovery experiments to four different lake water samples. After the spiking tests, good recovery results are calculated between 97% and 106%. These results show that lead can be detected at low levels in lake water samples with high sensitivity, accuracy, and precision.     

环境条件对极大螺旋藻金属元素吸收的影响

研究卫不同微量元素浓度和不同ＥＤＴＡ加入量对极大螺旋藻金属元素吸收的影响。结果显示,增加培养基中的微量元素含量有利于藻细胞对金属元素的吸收。少量ＥＤＴＡ的加入,有助于部分金属元素的吸收,较大量的ＥＤＴＡ可阻碍金属元素的吸收。藻细胞的吸附实验表明,极大螺旋藻对Ｃｏ、Ｎｉ、Ｃｕ、Ｚｎ、Ｐｂ有很强的吸附能力,死细胞与活细胞的吸附能力相近,表明这一吸附过程不依赖于生理活动。     

辐射处理金刚石的谱学研究及其意义

利用傅立叶显微红外光谱、紫外-可见-近红外吸收光谱、低温光致发光谱、拉曼光谱等4种谱学方法,对10颗辐照改色（R1-R10）的彩色天然金刚石进行了研究。利用可见吸收光谱和低温光致发光谱研究了金刚石石中的点缺陷产生系列的色心峰,指出在可见吸收光谱中除了有N3心吸收峰外,还可见595和637色心峰;在低温光致发光谱中发现有色心组合峰575,595和637等的出现,此组合峰与近红外区4929cm^-1处的H1b和5156cm^-1处的H1C色心峰共同存时,不仅是辐照处理绿色金刚石的鉴定证据,也是辐照处理各种彩色金刚石的重要的标志之一。本研究为辐射处理金刚石的鉴别和工艺流程提供了新的谱学依据和思路。     

紫外辐照条件下二维填料对聚丙烯耐老化行为的影响

采用水热法合成了二维层状材料——镁镍铁水滑石(MgNiFe-LDH),考察不同水热时间和水热温度对MgNiFe-LDH合成的影响,通过X射线衍射(XRD)、傅里叶变换红外光谱(FT-IR)、扫描电镜(SEM)和热分析(TG/DTG)等测试方法,对样品的结构、形貌及热性能进行表征。将合成的MgNiFe-LDH添加至聚丙烯(PP)制备MgNiFe-LDH/PP复合材料,通过对材料加速老化测其力学性能,研究了添加MgNiFe-LDH前后材料机械性能变化。结果表明,当Mg~(2+):Ni~(2+):Fe~(3+)=2∶1∶1,水热温度140℃、水热时间24 h时,合成的MgNiFe-LDH为片状,形貌较为规整,颗粒粒径约为2μm。MgNiFe-LDH/PP复合材料经加速老化后,填充MgNiFe-LDH复合材料的抗老化性能优于纯PP,当MgNiFe-LDH的填充量为6 wt%复合材料拉伸强度不变,可明显提高PP的抗老化性能。     

西太平洋秋季130°E断面有色溶解有机物的分布特征及光降解行为研究

对2018年秋季西太平洋130°E断面上层水体有色溶解有机物(CDOM)的光学特性及光降解行为进行了研究。结果表明,西太平洋上层水体CDOM的吸收系数a(320)变化范围为0.025～0.64 m?1,平均值为(0.20±0.08) m?1;a(320)在表层相对较低,主要与表层CDOM的光漂白去除有关;在100～200 m水层较高,主要与次表层的生物活动有关。利用三维荧光光谱?平行因子分析技术,识别出两种荧光组分:类酪氨酸组分C1和海洋类腐殖质组分C2。C1主要源于棉兰老冷涡?上升流所带来的营养物质对浮游植物生产活动和微生物活动的促进作用;C2主要源于黑潮所带来的海洋类腐殖的输入。光化学降解实验发现,CDOM吸收值的损失主要发生在紫外波段;光照60 h后,类酪氨酸组分相较于海洋类腐殖质组分更易发生光降解;且光降解是西太平洋海域CDOM的重要去除途径。     

Assessing temporal variation of coloured dissolved organic matter in the coastal waters of South Eastern Arabian Sea

Coloured dissolved organic matter （CDOM） plays a major role in marine photochemical and biological processes and its optical properties are known to affect the underwater light penetration. This paper highlights in situ optical estimation and satellite retrieval of CDOM in deciphering its temporal variations in coastal waters of the South Eastern Arabian Sea. The study accentuated the source of CDOM as terrigenous origin during monsoon, of in situ productions during pre-monsoon and during post-monsoon of autochthonous-allocthonous origin. The matchup analysis for in situ and MODIS Aqua retrieved A_dg443 exhibited bias which decreased by incorporating the seasonal component. The study also identified degrading bloom of Noctiluca scintillans as the source for exceptionally high CDOM in the area during January and February. The study demands to incorporate seasonal components and phytoplankton abundance while assessing the performance of CDOM algorithms in optically complex coastal waters.