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通过考虑来源、协议和环境参数,对法国苔藓生物监测数据中的微量元素进行空间分析。

Spatial analysis of trace elements in a moss bio-monitoring data over France by accounting for source, protocol and environmental parameters.

机构信息

Natural Heritage Department, National Museum of Natural History, 12 Rue Buffon, F-75005 Paris, France.

Infosol, US 1106, INRA Val-de-Loire, Orléans, France.

出版信息

Sci Total Environ. 2017 Jul 15;590-591:602-610. doi: 10.1016/j.scitotenv.2017.02.240. Epub 2017 Mar 7.

DOI:10.1016/j.scitotenv.2017.02.240
PMID:28283296
Abstract

Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses.

摘要

空气中微量元素 (TE) 的污染仍然是欧洲公共健康关注的问题。出于这个原因,部署了空气污染浓度或暴露的网络,包括欧洲的苔藓生物监测计划。苔藓中 TE 浓度的空间决定因素仍不清楚。在这项研究中,通过空间自回归模型分析了法国的苔藓 TE 数据集,以考虑数据的空间结构和几个已证明或怀疑会影响苔藓中 TE 浓度的变量。这些变量包括来源(大气沉积和土壤浓度)、方案(采样月份、收集器和苔藓种类)以及环境(森林类型和树冠密度、距海岸或高速公路的距离以及海拔高度)。仅对 Cd 和 Pb 进行了模拟大气沉积,是影响苔藓中浓度的主要解释变量之一。预测的土壤含量也是除 Cr、Ni 和 Zn 以外的重要解释变量。然而,苔藓种类是所有研究的 TE 的主要因素。其他环境变量以不同的方式影响 TE。特别是,在大多数情况下,森林类型和树冠密度是重要因素。这些结果强调需要进一步研究苔藓种类对 TE 的捕获和保留的影响,以及在统计分析中考虑多个变量和数据的空间结构。

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