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利用地质统计学估计研究苔藓中铜污染的时空分布模式。

Spatio-temporal patterns of Cu contamination in mosses using geostatistical estimation.

机构信息

CERENA, Instituto Superior Técnico, Technical University of Lisbon, Lisboa, Portugal.

出版信息

Environ Pollut. 2012 Nov;170:276-84. doi: 10.1016/j.envpol.2012.07.004. Epub 2012 Jul 31.

Abstract

Several recent studies have reported temporal trends in metal contamination in mosses, but such assessments did not evaluate uncertainty in temporal changes, therefore providing weak statistical support for time comparisons. Furthermore, levels of contaminants in the environment change in both space and time, requiring space-time modelling methods for map estimation. We propose an indicator of spatial and temporal variation based on space-time estimation by indicator kriging, where uncertainty at each location is estimated from the local distribution function, thereby calculating variability intervals for comparison between several biomonitoring dates. This approach was exemplified using copper concentrations in mosses from four Portuguese surveys (1992, 1997, 2002 and 2006). Using this approach, we identified a general decrease in copper contamination, but spatial patterns were not uniform, and from the uncertainty intervals, changes could not be considered significant in the majority of the study area.

摘要

几项最近的研究报告了苔藓中金属污染的时间趋势,但这些评估没有评估时间变化的不确定性,因此为时间比较提供的统计支持较弱。此外,环境中污染物的水平在空间和时间上都在变化,这就需要时空建模方法来进行地图估计。我们提出了一个基于时空指示克里金估计的空间和时间变化指标,其中每个位置的不确定性是根据局部分布函数来估计的,从而计算出几个生物监测日期之间的可变性间隔。使用来自葡萄牙的四项调查(1992 年、1997 年、2002 年和 2006 年)中的苔藓铜浓度对该方法进行了举例说明。使用这种方法,我们发现铜污染普遍减少,但空间模式并不均匀,从不确定性区间来看,在研究区域的大多数地区,变化都不能被认为是显著的。

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