Astel Aleksander, Astel Karolina, Biziuk Marek
Biology and Environmental Protection Institute, Environmental Chemistry Research Unit, Pomeranian Academy, 22a Arciszewskiego Str., 76-200 Słupsk, Poland.
Environ Sci Pollut Res Int. 2008 Jan;15(1):41-50. doi: 10.1065/espr2007.05.422.
GOAL, SCOPE AND BACKGROUND: During the last decades, a technique for assessing atmospheric deposition of heavy elements was developed based on the principle that samples of moss are able to accumulate elements and airborne particles from rain, melting snow and dry deposition. Despite a broad interest in bioindication there are still ongoing works aimed at the preparation of a standard procedure allowing for a comparison of research carried out in various areas. This is why the comparison of living and dry moss of the same species and growth site seems to be interesting, logical and promising. A most reliable approach seems to be the application of bioindication connected with multivariate statistics and efficient visualization techniques in the interpretation of monitoring data. The aim of this study was: (i) to present cumulative properties of transplanted Sphagnum palustre moss with differentiation into dry and living biomaterial; (ii) to determine and geographically locate types of pollution sources responsible for a structure of the monitoring data set; (iii) to visualize geographical distribution of analytes in the Gdańsk metropolitan area and to identify the high-risk areas which can be targeted for environmental hazards and public health.
A six month air pollution study based on Sphagnum palustre bioindication is presented and a simplified procedure of the experiment is given. The study area was located at the mouth of the Vistula River on the Baltic Sea, in Gdańsk City (Poland). Sphagnum palustre was selected for research because of its extraordinary morphological properties and its ease in being raised. The capability of dry and living moss to accumulate elements characteristic for anthropogenic and natural sources was shown by application of Principal Component Analysis. The high-risk areas and pollution profiles are detected and visualized using surface maps based on Kriging algorithm.
The original selection of elements included all those that could be reliably determined by Neutron Activation Analysis in moss samples. Elimination of variables covered the elements whose concentrations in moss were lower than the reported detection limits for INAA for most observations or in cases where particular elements did not show any variation. Eighteen elements: a, Ca, Sc, Fe, Co, Zn, As, Br, Mo, Sb, Ba, La, Ce, Sm, Yb, Lu, Hf, Th, were selected for the research presented.
Two runs of PCA were performed since, in the first-run a heavy polluted location (Stogi - 'Sto') understood as outlier in the term of PCA approach was detected and results in the form of block diagrams and surface maps were presented. As ensues from the first-run PCA analysis, the factor layout for both indicators is similar but not identical due to the differences in the elements accumulation mechanism. Three latent factors ('phosphatic fertilizer plant impact', 'urban impact' and 'marine impact') explain over 89% and 82% of the total variance for dry and living moss respectively. In the second-run PCA three latent factors are responsible for the data structure in both moss materials. However, in the case of dry moss analysis these factors explain 85% of the total variance but they are rather hard to interpret. On the other hand living moss shows the same pattern as in first-run PCA. Three latent factors explain over 84% of the total variance in this case. The pollution profiles extracted in PCA of dry moss data differ tremendously between both runs, while no deterioration was found after removal of Stogi from data set in case of living moss. Performance of the second-run PCA with exception of Stogi as a heavy polluted location has led to the conclusion that living moss shows better indication properties than dry one.
While using moss as wet and dry deposition sampier it is not possible to calculate deposition values since the real volume of collected water and dust is hard to estimate due to a splash effect and irregular surface. Therefore, accumulation values seam to be reasonable for moss-based air pollution surveys. Both biomaterials: dry and living Sphagnum palustre show cumulative properties relative to elements under interest. Dry moss has a very loose collection of the atmospheric particles, which can also easily get lost upon rinsing with rainwater running through exposed dry moss material. The living moss may, on the contrary, incorporate the elements in its tissue, thus being less susceptible to rinsing and thus better reflecting the atmospheric conditions. Despite the differences in element uptake and uphold capabilities dry and living moss reflect characteristic anthropogenic and natural profiles. Visible differences in impacts' map coverage exist mostly due to the accumulation mechanisms differentiating dry from living moss. However, in case of each indicator 'phosphatic fertilizer plant impact' is recognized as the strongest pollution source present in examined region.
General types of pollution sources responsible for a structure of monitoring data set were determined as high-risk/low-risk areas and visualized in form of geographic distribution maps. These locations can be targeted for environmental hazards and public health. Chemometric results in the form of easy defined surface maps can became a powerful instrument in hands of decision-makers working in the field of sustainable development implementation.
目标、范围及背景:在过去几十年间,基于苔藓样本能够从降雨、融雪及干沉降中积累元素和空气传播颗粒这一原理,开发出了一种评估大气中重金属元素沉降的技术。尽管生物指示法受到广泛关注,但仍有研究致力于制定标准程序,以便对不同地区开展的研究进行比较。这就是为什么对同一物种且生长地点相同的活苔藓和干苔藓进行比较似乎既有趣、合理又有前景。一种最可靠的方法似乎是将生物指示法与多元统计及高效可视化技术相结合,用于解释监测数据。本研究的目的是:(i)展示移植的泥炭藓的累积特性,并区分干生物材料和活生物材料;(ii)确定并在地理上定位导致监测数据集结构的污染源类型;(iii)可视化格但斯克大都市区分析物的地理分布,并识别可针对环境危害和公众健康的高风险区域。
本文介绍了一项基于泥炭藓生物指示法的为期六个月的空气污染研究,并给出了简化的实验程序。研究区域位于波兰格但斯克市波罗的海维斯瓦河河口。选择泥炭藓进行研究是因为其具有特殊的形态特性且易于培育。通过主成分分析展示了干苔藓和活苔藓积累人为源和自然源特征元素的能力。基于克里金算法的表面地图用于检测和可视化高风险区域及污染特征。
最初选择的元素包括所有能通过中子活化分析在苔藓样本中可靠测定的元素。变量剔除涵盖了那些在大多数观测中苔藓中浓度低于仪器中子活化分析报告检测限的元素,或者特定元素没有任何变化的情况。本研究选择了18种元素:a、Ca、Sc、Fe、Co、Zn、As、Br、Mo、Sb、Ba、La、Ce、Sm、Yb、Lu、Hf、Th。
进行了两轮主成分分析,因为在第一轮中检测到一个重污染地点(斯托吉 - “Sto”),在主成分分析方法中被视为异常值,并给出了框图和表面地图形式的结果。从第一轮主成分分析可以看出,由于元素积累机制不同两个指标的因子布局相似但不完全相同。三个潜在因子(“磷肥厂影响”、“城市影响”和“海洋影响”)分别解释了干苔藓和活苔藓总方差的89%以上和82%以上。在第二轮主成分分析中,三个潜在因子决定了两种苔藓材料的数据结构。然而,在干苔藓分析中这些因子解释了85%的总方差,但它们很难解释。另一方面,活苔藓呈现出与第一轮主成分分析相同的模式。在这种情况下,三个潜在因子解释了总方差的84%以上。干苔藓数据主成分分析中提取的污染特征在两轮分析中差异极大,而在活苔藓数据集中剔除斯托吉后未发现恶化情况。除了将斯托吉作为重污染地点外,第二轮主成分分析的结果得出结论:活苔藓比干苔藓具有更好的指示特性。
将苔藓用作湿沉降和干沉降采样器时,由于溅水效应和不规则表面,难以估计收集到的水和灰尘的实际体积,因此无法计算沉降值。因此,积累值似乎适用于基于苔藓的空气污染调查。两种生物材料:干泥炭藓和活泥炭藓都表现出相对于感兴趣元素的累积特性。干苔藓对大气颗粒的收集非常松散,雨水冲刷暴露的干苔藓材料时这些颗粒也很容易流失。相反,活苔藓可能将元素纳入其组织中,因此不易被冲洗掉,从而能更好地反映大气状况。尽管在元素吸收和保持能力上存在差异,但干苔藓和活苔藓都反映了典型的人为和自然特征。影响地图覆盖范围的明显差异主要是由于干苔藓和活苔藓积累机制的不同。然而,对于每个指标,“磷肥厂影响”被认为是研究区域中最强的污染源。
确定了导致监测数据集结构的一般污染源类型为高风险/低风险区域,并以地理分布图的形式进行可视化。这些地点可针对环境危害和公众健康。以易于定义的表面地图形式呈现的化学计量结果可成为可持续发展实施领域决策者手中的有力工具。