Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

BackgroundThis paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.ResultsCorrelations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=above-average) or low (=below-average) correlation coefficients.ConclusionsLDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

Mosses, epiphytic lichens and tree bark as biomonitors for air pollutants – specifically for heavy metals in regional surveys

Abstract The thesis consists of regional forest condition studies, using different biomonitors. Heavy metal deposition was investigated in 1985–2000 on the basis of the heavy metal concentrations (As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, V, Zn) in mosses in Finland. A comparison on the suitability of mosses, epiphytic lichens and pine bark as biomonitors of heavy metals was also carried. Bark was also used to study the dispersal of emissions from the Kola Peninsula into northern Finland. The occurrence of green algae on conifers in Finland was investigated in 1985 and 1995. Regional and temporal differences were found in the heavy metal concentrations of mosses in Finland. The concentrations of most metals were the highest in southern Finland, and they decreased towards the north. Some of the major emission source had a noticeable effect on the Cu, Ni and Cr concentrations of mosses in the surroundings of the emission sources. The Pb, Cd and V concentrations decreased the most during the study period. Mosses, lichens and bark gave a relatively similar result for heavy metal deposition in Finland. However, the comparisons indicated that mosses are better suited as biomonitors for regional surveys than epiphytic lichens, because the regional differences in heavy metal deposition were more readily reflected by concentrations in mosses than in lichens. Bark is relatively unsuitable for regional surveys due to the small range of variation in the concentrations. Emissions from the Kola Peninsula had a clear effect on the sulphur and heavy metal concentrations of pine bark. The concentrations in bark were at very high levels close to the smelters, but they rapidly decreased on moving towards the west. The effects of emissions were still clearly visible in north-eastern Lapland. There was strong increase in the abundance of green algae on conifers in southern and central Finland during the period 1985–1995. The increase is probably due to following factors: climate warming, and an increase in nitrogen and a decrease in sulphur in their habitats. Half of each biomonitor sample collected in the surveys has been stored in the specimen bank at Paljakka. The storage of samples offers advantages for monitoring purposes. The availability of long-term sample series makes it possible to construct retrospective time series of the pollutants. The specimen bank is to be further developed in the future by establishing a reputation as a storage facility for samples related to forest ecosystems

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

BackgroundThis paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.ResultsCorrelations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=above-average) or low (=below-average) correlation coefficients.ConclusionsLDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites