Background
This 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.
Results
Correlations 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 (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) 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.
Conclusions
LDA 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.
Monitoring of atmospheric deposition of metals in Norway on a nationwide scale using samples of terrestrial moss started in 1977 and has been repeated every 5
years. This has facilitated a detailed ...record of temporal and spatial trends of metal deposition all over the country as a supplement to measurements based on bulk deposition sampling on a small number of sites. Pb, Zn, Cd, As, Sb, V, Sn, Mo, and Bi all show highest deposition in the far south due to trans-boundary pollution from other parts of Europe, but the contribution from long-range atmospheric transport to metal deposition has decreased substantially over the years. The distributions of Fe, Ni, Cu, Cr, and Co are more affected by local sources, but a decreasing time trend is also evident for these elements. Se is mainly derived from processes in the marine environment. Deposition of metals from Cu–Ni smelters in Russia situated close to the Norwegian border has shown a steadily increasing trend over the time period concerned.
► Atmospheric deposition of key metals has been monitored at 464 sites in Norway every 5
years since 1977 using moss samples. ► Deposition of Pb, Zn, Cd, As, Sb, V, Sn, Mo, and Bi from long-range atmospheric transport is decreasing. ► Pb deposition has decreased by a factor of 20 since 1977 in the south of the country. ► Cu and Ni pollution in the far north due to emissions from Russian smelters has increased regularly over the time period. ► Deposition of Se is mainly due to supply from marine processes.
Key message
Moss surveys provide spatially dense data on environmental concentrations of heavy metals and nitrogen which, together with other biomonitoring and modelling data, can be used for ...indicating deposition to terrestrial ecosystems and related effects across time and areas of different spatial extension.
Context
For enhancing the spatial resolution of measuring and mapping atmospheric deposition by technical devices and by modelling, moss is used complementarily as bio-monitor.
Aims
This paper investigated whether nitrogen and heavy metal concentrations derived by biomonitoring of atmospheric deposition are statistically meaningful in terms of compliance with minimum sample size across several spatial levels (objective 1), whether this is also true in terms of geostatistical criteria such as spatial auto-correlation and, by this, estimated values for unsampled locations (objective 2) and whether moss indicates atmospheric deposition in a similar way as modelled deposition, tree foliage and natural surface soil at the European and country level, and whether they indicate site-specific variance due to canopy drip (objective 3).
Methods
Data from modelling and biomonitoring atmospheric deposition were statistically analysed by means of minimum sample size calculation, by geostatistics as well as by bivariate correlation analyses and by multivariate correlation analyses using the Classification and Regression Tree approach and the Random Forests method.
Results
It was found that the compliance of measurements with the minimum sample size varies by spatial scale and element measured. For unsampled locations, estimation could be derived. Statistically significant correlations between concentrations of heavy metals and nitrogen in moss and modelled atmospheric deposition, and concentrations in leaves, needles and soil were found. Significant influence of canopy drip on nitrogen concentration in moss was proven.
Conclusion
Moss surveys should complement modelled atmospheric deposition data as well as other biomonitoring approaches and offer a great potential for various terrestrial monitoring programmes dealing with exposure and effects.
Objective. This study explores the statistical relations between the accumulation of heavy metals in moss and natural surface soil and potential influencing factors such as atmospheric deposition by ...use of multivariate regression-kriging and generalized linear models. Based on data collected in 1995, 2000, 2005 and 2010 throughout Norway the statistical correlation of a set of potential predictors (elevation, precipitation, density of different land uses, population density, physical properties of soil) with concentrations of cadmium (Cd), mercury and lead in moss and natural surface soil (response variables), respectively, were evaluated. Spatio-temporal trends were estimated by applying generalized linear models and geostatistics on spatial data covering Norway. The resulting maps were used to investigate to what extent the HM concentrations in moss and natural surface soil are correlated. Results. From a set of ten potential predictor variables the modelled atmospheric deposition showed the highest correlation with heavy metals concentrations in moss and natural surface soil. Density of various land uses in a 5 km radius reveal significant correlations with lead and cadmium concentration in moss and mercury concentration in natural surface soil. Elevation also appeared as a relevant factor for accumulation of lead and mercury in moss and cadmium in natural surface soil respectively. Precipitation was found to be a significant factor for cadmium in moss and mercury in natural surface soil. The integrated use of multivariate generalized linear models and kriging interpolation enabled creating heavy metals maps at a high level of spatial resolution. The spatial patterns of cadmium and lead concentrations in moss and natural surface soil in 1995 and 2005 are similar. The heavy metals concentrations in moss and natural surface soil are correlated significantly with high coefficients for lead, medium for cadmium and moderate for mercury. From 1995 up to 2010 the modelled moss and natural surface soil estimates indicate a decrease of lead concentration in both moss and natural surface soil. In the case of the moss data the decrease of accumulation is more pronounced. By contrast, the modelled cadmium and mercury concentrations do not exhibit any significant temporal trend. Conclusions. In Europe, there is hardly any nation-wide investigation of statistical correlations between the accumulation of heavy metals in moss and natural surface soil and potential influencing factors such as atmospheric deposition. This study could show that assessments of heavy metal concentrations in natural surface soil could complement biomonitoring with moss but should not replace it since the heavy metal concentrations in mosses reliably traces the spatial pattern of respective atmospheric deposition. Generalized linear models extend established methods for estimating spatial patterns and temporal trends of HM concentration in moss and natural surface soil.
•Comprehensive analysis of correlation between heavy metal deposition and accumulation.•Generalized linear models (GLM) can reveal a better fit than respective linear models.•Integrated use of GLM and geostatistics yield a high spatial resolution.•Atmospheric deposition, land use, elevation and precipitation are relevant factors.•From 1995 to 2010 lead concentration in both moss and surface soil decreases.
This study investigated whether statistical correlation of modeled atmospheric heavy metal deposition and respective accumulation in moss and natural surface soil varies across natural landscapes in ...Norway. Target metals were cadmium, lead, and mercury, and analyses were run between 1990 and 2010 on a 5-year interval. The landscape information was derived from the Ecological Land Classification of Europe. Correlations between concentration and respective deposition data were computed for each land class. The strongest correlations between heavy metal concentrations in atmospheric deposition and corresponding levels in moss and natural surface soil were observed for lead. Correlations for mercury were weaker compared to those calculated for cadmium and lead, indicating that atmospheric transport of mercury occurs at a larger spatial scale, while accumulation additionally seems to be influenced by factors operating on smaller scales. The correlation between concentrations in atmospheric deposition and moss is landscape-specific and metal-specific. The same holds true for the relations between heavy metal concentration in modeled atmospheric deposition and natural surface soil. The results of this investigation are in line with similar calculations from across Europe. They further confirm previous studies indicating that for Norway atmospheric transport is a main source of lead and cadmium accumulation in moss as well as in natural surface soil.
This study explores the statistical relations between the concentration of nine heavy metals (HM) (arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), ...vanadium (V), zinc (Zn)), and nitrogen (N) in moss and potential explanatory variables (predictors) which were then used for mapping spatial patterns across Europe. Based on moss specimens collected in 2010 throughout Europe, the statistical relation between a set of potential predictors (such as the atmospheric deposition calculated by use of two chemical transport models (CTM), distance from emission sources, density of different land uses, population density, elevation, precipitation, clay content of soils) and concentrations of HMs and nitrogen (N) in moss (response variables) were evaluated by the use of Random Forests (RF) and Classification and Regression Trees (CART). Four spatial scales were regarded: Europe as a whole, ecological land classes covering Europe, single countries participating in the European Moss Survey (EMS), and moss species at sampling sites. Spatial patterns were estimated by applying a series of RF models on data on potential predictors covering Europe. Statistical values and resulting maps were used to investigate to what extent the models are specific for countries, units of the Ecological Land Classification of Europe (ELCE), and moss species.
Land use, atmospheric deposition and distance to technical emission sources mainly influence the element concentration in moss. The explanatory power of calculated RF models varies according to elements measured in moss specimens, country, ecological land class, and moss species. Measured and predicted medians of element concentrations agree fairly well while minima and maxima show considerable differences. The European maps derived from the RF models provide smoothed surfaces of element concentrations (As, Cd, Cr, Cu, N, Ni, Pb, Hg, V, Zn), each explained by a multivariate RF model and verified by CART, and thereby more information than the dot maps depicting the spatial patterns of measured values.
RF is an eligible method identifying and ranking boundary conditions of element concentrations in moss and related mapping including the influence of the environmental factors.
•Comprehensive analysis of relations between atmospheric deposition and accumulation.•Random Forests (RF) allows for multiple regression analysis.•Atmospheric deposition, land use and distance to emission sources are relevant factors.•Measured elements, countries and ecological land classes determine the models accuracy.•RF enables predictive mapping of element concentrations in moss.
For analysing element input into ecosystems and associated risks due to atmospheric deposition, element concentrations in moss provide complementary and time-integrated data at high spatial ...resolution every 5 years since 1990. The paper reviews (1) minimum sample sizes needed for reliable, statistical estimation of mean values at four different spatial scales (European and national level as well as landscape-specific level covering Europe and single countries); (2) trends of heavy metal (HM) and nitrogen (N) concentrations in moss in Europe (1990–2010); (3) correlations between concentrations of HM in moss and soil specimens collected across Norway (1990–2010); and (4) canopy drip-induced site-specific variation of N concentration in moss sampled in seven European countries (1990–2013). While the minimum sample sizes on the European and national level were achieved without exception, for some ecological land classes and elements, the coverage with sampling sites should be improved. The decline in emission and subsequent atmospheric deposition of HM across Europe has resulted in decreasing HM concentrations in moss between 1990 and 2010. In contrast, hardly any changes were observed for N in moss between 2005, when N was included into the survey for the first time, and 2010. In Norway, both, the moss and the soil survey data sets, were correlated, indicating a decrease of HM concentrations in moss and soil. At the site level, the average N deposition inside of forests was almost three times higher than the average N deposition outside of forests.
Purpose
Assessing effects of air pollution needs the monitoring of atmospheric deposition. At least for enhancing the spatial resolution of measuring deposition by use of technical devices and of ...deposition modeling, mosses are used complementarily as biomonitors. In Norway, since 1985, nationwide surveys have been carried out every 5 years. This study aimed at investigating statistical relationships between heavy metal concentrations in samples of moss and natural surface soil, collected in spatial dense networks covering Norway, and regional factors.
Materials and methods
Heavy metal (HM) concentrations in moss samples collected in 1990, 1995, 2000, 2005, and 2010 and in natural surface soil specimens sampled in 1995 and 2005 across Norway were assessed statistically. Classification and regression trees were computed in order to uncover multivariate relationships between HM concentrations in moss and natural surface soil and potential influencing environmental factors that were integrated into the multivariate analyses.
Results and discussion
Atmospheric deposition of HM could be proved as the strongest predictor for HM concentrations in moss and natural surface soil samples. Land use within a 5-km radius and population density around the sampling sites were identified as further predictors of HM concentrations in moss and natural surface soil.
Conclusions
HM monitoring with moss and natural surface soil samples indicates complementarily atmospheric deposition and thus should be carried out as long-term observation.
BACKGROUND. Methodology for estimation of cerebrospinal fluid (CSF) tracer clearance could have wide clinical application in predicting excretion of intrathecal drugs and metabolic solutes from brain ...metabolism and for diagnostic workup of CSF disturbances.
METHODS. The MRI contrast agent gadobutrol (Gadovist) was used as a CSF tracer and injected into the lumbar CSF. Gadobutrol is contained outside blood vessels of the CNS and is eliminated along extravascular pathways, analogous to many CNS metabolites and intrathecal drugs. Tracer enrichment was verified and assessed in CSF by MRI at the level of the cisterna magna in parallel with obtaining blood samples through 48 hours.
RESULTS. In a reference patient cohort (n = 29), both enrichment within CSF and blood coincided in time. Blood concentration profiles of gadobutrol through 48 hours varied between patients diagnosed with CSF leakage (n = 4), idiopathic normal pressure hydrocephalus dementia (n = 7), pineal cysts (n = 8), and idiopathic intracranial hypertension (n = 4).
CONCLUSION. Assessment of CSF tracer clearance is clinically feasible and may provide a way to predict extravascular clearance of intrathecal drugs and endogenous metabolites from the CNS. The peak concentration in blood (at about 10 hours) was preceded by far peak tracer enhancement at MRI in extracranial lymphatic structures (at about 24 hours), as shown in previous studies, indicating a major role of the spinal canal in CSF clearance capacity.
FUNDING. The work was supported by the Department of Neurosurgery, Oslo University Hospital; the Norwegian Institute for Air Research; and the University of Oslo.
BACKGROUND: The aim of this investigation was to inquire whether the spatial patterns and temporal trends of heavy metal concentrations in moss and soil specimen monitored in two spatial dense ...networks covering Norway are correlated. To this end, data about concentrations of cadmium, mercury and lead in moss and soil specimens collected were compiled. The data were derived from moss surveys conducted in 1990, 1995, 2000, 2005 and 2010, as well as from soil monitoring campaigns in 1995 and 2005. RESULTS: The data sets from both moss and soil surveys indicate a decrease of heavy metal concentrations in moss and soil specimen. However, in case of moss samples, the decrease is by far more pronounced and statistically significant. The heavy metal concentrations in moss and soil are correlated significantly with high positive coefficients for Pb, medium for Cd and moderate for Hg. From a set of potentially influencing boundary conditions, the modelled atmospheric deposition showed the highest correlation with the heavy metal concentrations in moss and soil. The spatial patterns of Cd and Pb concentration in moss and soil specimens 1995 and 2005 are similar. Thereby, the spatial differentiation of concentrations in moss is higher than that in soil, while the opposite holds true for the Hg concentration. CONCLUSIONS: Even if the metal concentrations in moss and soil are statistically correlated, they should not be replaced by each other but should be used as complementary monitoring systems.
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