Determination of the Geogenic Metal Background in Surface Water: Benchmarking Methodology for the Rivers of Saxony-Anhalt, Germany
Abstract
:1. Introduction
2. Materials and Methods
- A double procedure for the elimination of all sampling locations from the database which have anthropogenic influence,
- GIS-based allocation of the sampling points with respect to the respective “aggregated riverine landscapes”, being the evaluation units,
- Assessment of the geogenic background data by calculation of statistical parameters with data pre-selection in order to extract the anthropogenic uninfluenced rivers per AGL, and
- Validation of the background data using the Germany-wide background levels calculated by Birke et al. [41] as a benchmark.
- headwaters are originating in woodlands (≥95% forest),
- exclusion of sampling locations affected by point sources, and dischargers, as well as diffuse sources (agricultural land use, transport); point sources were considered sampling locations, in whose catchment areas mining activities, like mines, mining piles, and smelters are identified, as well as contaminated sites, settlements, and industry, and
- increased concentrations of nitrate (>5 mg/L), ammonium (>0.5 mg/L) and phosphate (>10 μg/L) as indicators for the identification of anthropogenic influence, including analysis of selected sampling locations in terms of the concentrations of NO3-N, NH4-N, and PO4-P as indicator parameters for agricultural land use.
3. Results
3.1. Comparison of Results without the Pre-Selection of Data
3.2. Results of the Statistical Analysis with Pre-Selection of the Data
3.3. Validation of the Results
3.4. Spatial Visualization of the Results
4. Discussion
5. Conclusions
calcareous-dolomitic riverine landscape: | Al, B, Ba, Cd, Co, Cr, Se, U |
metallogenic riverine landscape: | Al, As, Be, Cd, Co, Fe, Mn, Ni, Pb, Zn |
bogs and riverside meadows: | Fe, Mn, Mo |
saliniferous riverine landscape: | Ag, As, B, Cr, Cu, Mo, Ni, Pb, Se, Ti |
sandy-clayey riverine landscape: | Al, Fe, Mn, U |
siliceous riverine landscape: | Ag, Be, Cu, Mo, Ni, Pb, V |
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Criterion | Statistical Approach with Pre-Selection | Procedure without Pre-Selection |
---|---|---|
Genetic classification of data | aggregated riverine landscapes by Schneider et al. [33,34] | none |
Preselection of database | yes | no |
Statistical parameter for derivation of geogenic background | 50th percentile (median) 90th percentile | 50th percentile (median) 84.1st percentile (according to [17]) 90th percentile |
Advantage | Genetic classification of data (here ARLs) allows for the allocation of areas with increased concentrations to the geological setting Data for large data sets (>80,000) can be processed (meta catchment scale, here about 300 water bodies with several sampling locations) through the use of GIS Existing data from county monitoring activities can be included after verification and selection Sensitive also to very low detection limits as usually the geogenic concentrations are low | Served for the separation of the anthropogenic proportion of the concentration of an element in a groundwater from the geogenic proportion, regardless of the geological setting [17] |
Disadvantage | Database for suspended matter needs to be improved | Methodology derived from about 2800 datasets from groundwater extraction wells for groundwater [17], not applicable for surface water No pre-selection causes that there is no consideration of external effects which can affect the geogenic concentration Genetic classification of data is not foreseen |
Total Phase [μg/L] | Calcareous-Dolomitic | Siliceous | Metallogenic | Bogs/Bog Riverside Meadows | Saliniferous | Sandy-Clayey | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Parameter | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) |
Al | 215 | 1110 | 25 | 157 | 120 | 278 | 25 | 68 | 25 | 84 | 25 | 346 |
Sb | 0.5 | 1.0 | 0.5 | 1.0 | 0.25 | 1.0 | 0.55 | 1.0 | 0.25 | 1.0 | 1.0 | 1.0 |
As | 0.25 | 1.08 | 0.5 | 2.64 | 0.25 | 2.5 | 0.57 | 1.6 | 0.8 | 7.7 | 0.5 | 1.61 |
Ba | 70 | 100 | 66 | 240 | 14.5 | 56.5 | 60 | 146 | 13 | 110 | 57 | 87.6 |
Be | 0.025 | 0.166 | 0.125 | 0.39 | 0.064 | 0.22 | 0.025 | 0.46 | 0.025 | 0.071 | 0.025 | 0.09 |
Pb | 0.5 | 0.9 | 0.5 | 0.7 | 0.5 | 3.4 | 0.5 | 0.7 | 0.5 | 1.0 | 0.5 | 1.0 |
B | 25 | 51 | 25 | 108 | 25.0 | 26.4 | 56 | 138 | 80 | 320 | 25 | 100 |
Cd | 0.025 | 0.122 | 0.08 | 0.24 | 0.08 | 0.30 | 0.025 | 0.05 | 0.1 | 0.22 | 0.025 | 0.06 |
Cr | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.1 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Fe | 285 | 2337 | 25 | 787 | 160 | 664 | 800 | 1650 | 25 | 35 | 1000 | 3315 |
Co | 0.2 | 1.76 | 0.3 | 1.0 | 0.5 | 6.5 | 0.1 | 1.0 | 0.1 | 0.5 | 0.23 | 1.2 |
Cu | 1.0 | 1.0 | 1.0 | 18.0 | 1.0 | 3.5 | 1.0 | 2.9 | 1.0 | 1.0 | 1.0 | 1.4 |
Mn | 88 | 235 | 5.0 | 180 | 41 | 290 | 160 | 380 | 5.0 | 20 | 229 | 758 |
Mo | 0.5 | 0.5 | 1.0 | 5.9 | 0.5 | 0.5 | 0.5 | 1.2 | 0.5 | 7.7 | 0.5 | 0.5 |
Ni | 2.0 | 6.85 | 1.0 | 31.0 | 1.0 | 5.5 | 1.0 | 2.1 | 1.0 | 2.5 | 1.0 | 3,4 |
Hg | 0.025 | 0.025 | 0.025 | 0.025 | 0.015 | 0.05 | 0.01 | 0.04 | 0.01 | 0.025 | 0.01 | 0.025 |
Se | 0.5 | 0.8 | 0.5 | 1.5 | 0.4 | 0.6 | 0.5 | 1.2 | 1.3 | 2.4 | 0.5 | 0.5 |
Ag | 0.05 | 0.05 | 0.05 | 0.80 | 0.05 | 0.05 | 0.05 | 0.08 | 0.05 | 0.09 | 0.05 | 0.05 |
Ti | 2.5 | 2.5 | 2.5 | 8.9 | 2.5 | 2.5 | 2.5 | 11.3 | 2.5 | 2.5 | 2.5 | 2.5 |
Tl | 0.025 | 0.01 | 0.1 | 0.1 | 0.1 | 0.1 | 0.025 | 0.025 | 0.025 | 1.0 | 0.025 | 0.025 |
U | 3.8 | 6.92 | 1.2 | 4.2 | 0.25 | 0.95 | 0.257 | 2.25 | 0,93 | 4.10 | 0.25 | 5.55 |
V | 0.5 | 5.0 | 0.5 | 5.9 | 0.5 | 5.0 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
Zn | 5.0 | 32.4 | 5.0 | 24.4 | 5.0 | 25.0 | 5.0 | 14.0 | 10.0 | 19.8 | 5.0 | 21.0 |
Sn | 0.25 | 0.5 | 0.25 | 0.5 | 0.25 | 0.5 | 0.5 | 0.5 | 0.25 | 0.5 | 0.5 | 0.5 |
Total Phase [μg/L] | Calcareous-Dolomitic | Siliceous | Metallogenic | Bogs/Bog Riverside Meadows | Saliniferous | Sandy-Clayey | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Parameter | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) |
Al | 5.0 | 150 | 5.0 | 25 | 7.5 | 71 | 5.0 | 25 | 5.0 | 25 | 25 | 189 |
Sb | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
As | 0.25 | 1.0 | 0.25 | 1.30 | 0.8 | 5.3 | 0.25 | 0.9 | 1.2 | 13.0 | 0.25 | 0.8 |
Ba | 68 | 165 | 70 | 109 | 31.5 | 104 | 70 | 159 | 40 | 101 | 85 | 146 |
Be | 0.025 | 0.06 | 0.025 | 0.325 | 0.015 | 0.203 | 0.02 | 0.025 | 0.015 | 0.062 | 0.025 | 0.025 |
Pb | 0.5 | 0.5 | 0.5 | 2.9 | 0.5 | 2.8 | 0.5 | 0.5 | 0.5 | 1.3 | 0.5 | 0.5 |
B | 54 | 277 | 29 | 110 | 20.5 | 38.0 | 60 | 154 | 94 | 385 | 73 | 108 |
Cd | 0.025 | 0.376 | 0.05 | 0.28 | 0.13 | 0.45 | 0.025 | 0.025 | 0.052 | 0.28 | 0.025 | 0.05 |
Cr | 1.0 | 4.0 | 1.0 | 2.2 | 0.5 | 2.0 | 0.75 | 1.8 | 1.0 | 4.0 | 1.0 | 1.4 |
Fe | 42.5 | 729 | 40 | 252 | 146 | 1039 | 195 | 947 | 36 | 317 | 155 | 821 |
Fe(II) | 15 | 306 | 15 | 253 | 140 | 477 | 364 | 1343 | 15 | 53 | 86 | 598 |
Co | 0.1 | 2.2 | 1.0 | 0.8 | 0.1 | 8.1 | 0.1 | 0.8 | 0.1 | 1.8 | 0.1 | 1.2 |
Cu | 1.0 | 4.0 | 1.0 | 23 | 1.0 | 4.4 | 1.0 | 4.0 | 1.0 | 7.1 | 1.0 | 2.9 |
Mn | 5.0 | 156 | 5.0 | 81 | 100 | 1969 | 152 | 357 | 5.0 | 55 | 144 | 570 |
Mo | 0.15 | 0.5 | 0.15 | 2.1 | 0.15 | 0.5 | 0.25 | 1.0 | 0.5 | 7.6 | 0.5 | 0.5 |
Ni | 3.9 | 10.8 | 2.05 | 34.0 | 1.2 | 26.4 | 1.0 | 3.9 | 5.0 | 24.0 | 1.3 | 5.5 |
Hg | 0.005 | 0.01 | 0.005 | 0.01 | 0.005 | 0.01 | 0.01 | 0.01 | 0.005 | 0.01 | 0.01 | 0.01 |
Se | 0.5 | 2.5 | 0.5 | 1.4 | 0.4 | 0.5 | 0.4 | 0.5 | 1.9 | 11.2 | 0.5 | 1.5 |
Ag | 0.05 | 0.06 | 0.05 | 0.14 | 0.01 | 0.05 | 0.01 | 0.05 | 0.05 | 0.18 | 0.05 | 0.05 |
Ti | 2.5 | 6.0 | 2.5 | 6.1 | 2.5 | 2.5 | 2.5 | 2.5 | 2.5 | 14 | 2.5 | 4.1 |
Tl | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 |
U | 2.4 | 7.0 | 0.6 | 3.95 | 0.025 | 0.55 | 0.254 | 1.17 | 1.0 | 4.0 | 0.25 | 5.16 |
V | 0.15 | 0.5 | 0.15 | 2.8 | 0.15 | 0.5 | 0.15 | 0.5 | 0.15 | 0.5 | 0.5 | 0.5 |
Zn | 5.0 | 34.0 | 13.5 | 32.0 | 5.0 | 172 | 5.0 | 12.2 | 11.5 | 32.0 | 2.0 | 16.1 |
Sn | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
Total Phase [mg/kg] | Siliceous | Bogs/Bog Riverside Meadows | Sandy-Clayey | |||
---|---|---|---|---|---|---|
Parameter | P(50) | P(90) | P(50) | P(90) | P(50) | P(90) |
Sb | - | - | - | - | 10 | 10 |
As | 13 | 14.6 | 38.1 | 45 | 24 | 34.5 |
Ba | - | - | - | - | 516 | 558. |
Be | - | - | - | - | 1.5 | 2.6 |
Pb | 47 | 52.4 | 55.1 | 77.66 | 45 | 109 |
B | - | - | - | - | 13.5 | 33.3 |
Cd | 0.6 | 0.68 | 4.4 | 5.58 | 0.9 | 1.31 |
Cr | 50 | 52.4 | 126 | 210.8 | 65.5 | 109.1 |
Fe | 34,700 | 35,900 | 205,000 | 233,200 | 126,500 | 228,900 |
Co | - | - | - | - | 16 | 21.4 |
Cu | 89 | 96.2 | 49 | 65.7 | 58 | 96.2 |
Mn | 2000 | 15,040 | 16,800 | 35,200 | 4875 | 14,710 |
Mo | - | - | - | - | 1 | 2.5 |
Ni | 28 | 28 | 104 | 151.6 | 35.5 | 51.2 |
Hg | 0.4 | 0.4 | 0.9 | 1.64 | 0.2 | 0.3 |
Se | - | - | - | - | 1 | 1 |
Ag | - | - | - | - | 0.5 | 1 |
Ti | - | - | - | - | 552 | 890.4 |
Tl | - | - | - | - | 0.5 | 0.5 |
U | - | - | - | - | 1.2 | 2.27 |
V | - | - | - | - | 56 | 69.9 |
Zn | 260 | 276 | 850 | 1068 | 317 | 439,1 |
Sn | - | - | - | - | 5 | 5 |
Total Phase [μg/L] | Span over all Types of ARL in Saxony-Anhalt—with Pre-Selection | Span of the Data of the Geochemical Map for Saxony-Anhalt—without Pre-Selection | |||
---|---|---|---|---|---|
Parameter | Min P(50) | Max P(50) | Min P(50) | Mean P(50) | Max P(50) |
Al | 25 | 215 | 1 | 10 | 250 |
As | 0.25 | 0.8 | 0.19 | 1.5 | 4.5 |
Ba | 13 | 70 | 9 | 30 | 80 |
Pb | 0.5 | 0.5 | 0.02 | 0.2 | 1.1 |
B | 25 | 80 | 20 | 60 | 350 |
Cd | 0.025 | 0.1 | 0.005 | 0.05 | 0.3 |
Cr | 1.0 | 1.0 | 0.03 | 0.2 | 1.3 |
Fe | 25 | 1000 | 10 | 90 | 1800 |
Cu | 1.0 | 1.0 | 0.4 | 1.1 | 6.0 |
Se | 0.4 | 1.3 | 0.08 | 1.07 | 3.58 |
Ag | 0.05 | 0.05 | 0.002 | 0.004 | 0.006 |
Tl | 0.025 | 0.1 | 0.002 | 0.013 | 0.17 |
U | 0.25 | 3.8 | 0.07 | 0.7 | 7 |
Zn | 5.0 | 10.0 | 0.5 | 2.7 | 14 |
Para-Meter [μg/L] | EQS 2011/Since 2015 | Calcareous-Dolomitic | Metallogenic | Bogs/Riverside Meadows | Saliniferous | Sandy-Clayey | Siliceous |
---|---|---|---|---|---|---|---|
As | –/1.0 | 1.0 | 5.3 | 0.9 | 13.0 | 0.8 | 1.3 |
Ag | 0.02/0.02 | 0.06 | 0.05 | 0.05 | 0.18 | 0.05 | 0.14 |
Cd | 0.08–0.25 */0.15 | 0.376 | 0.450 | 0.025 | 0.280 | 0.050 | 0.280 |
Hg | 0.05/0.07 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 |
Ni | 20/4.0 | 10.8 | 26.4 | 3.9 | 24.0 | 5.5 | 34.0 |
Pb | 7.2/1.2 | 0.5 | 2.8 | 0.5 | 1.3 | 0.5 | 2.9 |
Se | 3.0/3.0 | 2.5 | 0.5 | 0.5 | 11.2 | 1.5 | 1.4 |
Tl | 0.2/0.2 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 | 0.025 |
Calcareous-dolomitic | 0.25 | [μg/L] | ||
Metallogenic | 0.09 | [μg/L] | Background value > EQS | |
Bogs/riverside meadows | 0.25 | [μg/L] | ||
Saliniferous | 0.15 | [μg/L] | P90 | 90th percentile |
Sandy-clayey | 0.25 | [μg/L] | italic | Value below detection limit |
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Schneider, P.; Nilius, U.; Gottschalk, N.; Süß, A.; Schaffrath, M.; Löser, R.; Lange, T. Determination of the Geogenic Metal Background in Surface Water: Benchmarking Methodology for the Rivers of Saxony-Anhalt, Germany. Water 2017, 9, 75. https://doi.org/10.3390/w9020075
Schneider P, Nilius U, Gottschalk N, Süß A, Schaffrath M, Löser R, Lange T. Determination of the Geogenic Metal Background in Surface Water: Benchmarking Methodology for the Rivers of Saxony-Anhalt, Germany. Water. 2017; 9(2):75. https://doi.org/10.3390/w9020075
Chicago/Turabian StyleSchneider, Petra, Ulf Nilius, Nicole Gottschalk, Annegret Süß, Martin Schaffrath, Ralf Löser, and Thomas Lange. 2017. "Determination of the Geogenic Metal Background in Surface Water: Benchmarking Methodology for the Rivers of Saxony-Anhalt, Germany" Water 9, no. 2: 75. https://doi.org/10.3390/w9020075
APA StyleSchneider, P., Nilius, U., Gottschalk, N., Süß, A., Schaffrath, M., Löser, R., & Lange, T. (2017). Determination of the Geogenic Metal Background in Surface Water: Benchmarking Methodology for the Rivers of Saxony-Anhalt, Germany. Water, 9(2), 75. https://doi.org/10.3390/w9020075