cE3c, Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, FCUL , Campo Grande, Bloco C2, Piso 5, 1749-016 Lisboa, Portugal.
Centro de Recursos Naturais e Ambiente, Instituto Superior Técnico, Universidade de Lisboa (CERENA-IST-UL) , Lisboa, 1649-004 Portugal.
Environ Sci Technol. 2016 Mar 1;50(5):2434-41. doi: 10.1021/acs.est.5b04873. Epub 2016 Feb 18.
In an area with multiple sources of air pollution, it is difficult to evaluate the spatial impact of a minor source. Here, we describe the use of lichens to track minor sources of air pollution. The method was tested by transplanting lichens from a background area to the vicinity of a cement manufacturing plant that uses alternative fuel and is located in a Natural Park in an area surrounded by other important sources of pollution. After 7 months of exposure, the lichens were collected and analyzed for 17 PCDD/F congeners. The PCDD/F profiles of the exposed lichens were dominated by TCDF (50%) and OCDD (38%), which matched the profile of the emissions from the cement plant. The similarity in the profiles was greatest for lichens located northeast of the plant (i.e., in the direction of the prevailing winds during the study period), allowing us to evaluate the spatial impact of this source. The best match was found for sites located on the tops of mountains whose slopes faced the cement plant. Some of the sites with highest influence of the cement plant were the ones with the highest concentrations, whereas others were not. Thus, our newly developed lichen-based method provides a tool for tracking the spatial fate of industrially emitted PCDD/Fs regardless of their concentrations. The results showed that the method can be used to validate deposition models for PCDD/F industrial emissions in sites with several sources and characterized by complex orography.
在存在多个空气污染源的地区，评估一个次要污染源的空间影响是困难的。在这里，我们描述了使用地衣来追踪空气污染的次要来源。该方法通过将地衣从背景地区移植到附近的一家水泥厂进行测试，该水泥厂使用替代燃料，位于一个自然公园内，周围是其他重要的污染源。暴露 7 个月后，收集并分析了 17 种 PCDD/F 同系物的地衣。暴露的地衣中的 PCDD/F 图谱主要由 TCDF（50%）和 OCDD（38%）主导，与水泥厂的排放图谱相匹配。地衣位于工厂东北方向（即在研究期间盛行风向的方向）时，图谱的相似性最大，这使我们能够评估该源的空间影响。与工厂顶部朝向水泥厂的山坡上的地点的匹配度最好。一些受水泥厂影响最大的地点的浓度最高，而其他地点则不然。因此，我们新开发的基于地衣的方法提供了一种追踪工业排放 PCDD/F 空间命运的工具，无论其浓度如何。结果表明，该方法可用于验证具有多个污染源且地形复杂的地点的 PCDD/F 工业排放沉积模型。
