Modelling and mapping heavy metal and nitrogen concentrations in moss in 2010 throughout Europe by applying Random Forests models

  1. Nickel, S. 1
  2. Schröder, W. 1
  3. Wosniok, W. 25
  4. Harmens, H. 6
  5. Frontasyeva, M.V. 13
  6. Alber, R. 2
  7. Aleksiayenak, J. 8
  8. Barandovski, L. 22
  9. Blum, O. 14
  10. Danielsson, H. 10
  11. de Temmermann, L. 33
  12. Dunaev, A.M. 9
  13. Fagerli, H. 19
  14. Godzik, B. 34
  15. Ilyin, I. 12
  16. Jonkers, S. 24
  17. Jeran, Z. 11
  18. Pihl Karlsson, G.
  19. Lazo, P. 29
  20. Leblond, S. 15
  21. Liiv, S. 23
  22. Magnússon, S.H. 5
  23. Mankovska, B. 7
  24. Martínez-Abaigar, J. 26
  25. Piispanen, J. 16
  26. Poikolainen, J. 16
  27. Popescu, I.V. 32
  28. Qarri, F. 31
  29. Radnovic, D. 28
  30. Santamaria, J.M. 27
  31. Schaap, M. 24
  32. Skudnik, M. 21
  33. Špirić, Z. 4
  34. Stafilov, T. 22
  35. Steinnes, E. 17
  36. Stihi, C. 32
  37. Suchara, I. 20
  38. Thöni, L. 3
  39. Uggerud, H.T. 18
  40. Zechmeister, H.G. 30
  41. Mostrar todos los/as autores/as +
  1. 1 University of Vechta
    info

    University of Vechta

    Vechta, Alemania

    ROR https://ror.org/045y6d111

  2. 2 Environmental Agency of Bolzano, Laives, Italy
  3. 3 FUB-Research Group for Environmental Monitoring, Rapperswil, Switzerland
  4. 4 Green Infrastructure Ltd, Zagreb, Croatia
  5. 5 Icelandic Institute of Natural History, Gar�ab�r, Iceland
  6. 6 ICP Vegetation Programme Coordination Centre, Centre for Ecology and Hydrology, Bangor, Gwynedd, United Kingdom
  7. 7 Institute of Landscape Ecology, Slovak Academy of Sciences, Bratislava, Slovakia
  8. 8 International Sakharov Environmental University
    info

    International Sakharov Environmental University

    Minsk, Bielorrusia

    ROR https://ror.org/05198a862

  9. 9 Ivanovo State University of Chemistry and Technology
    info

    Ivanovo State University of Chemistry and Technology

    Ivánovo, Rusia

    ROR https://ror.org/02fjy3w42

  10. 10 IVL Swedish Environmental Research Institute, G�teborg, Sweden
  11. 11 Jožef Stefan Institute
    info

    Jožef Stefan Institute

    Liubliana, Eslovenia

    ROR https://ror.org/05060sz93

  12. 12 Meteorological Synthesizing Centre East, Moscow, Russian Federation
  13. 13 Moss Survey Coordination Centre, Frank Laboratory of Neutron Physics, Moscow Region, Russian Federation
  14. 14 National Botanical Garden, Academy of Science of Ukraine, Kiev, Ukraine
  15. 15 National Museum of Natural History, Paris, France
  16. 16 Natural Resources Institute Finland
    info

    Natural Resources Institute Finland

    Helsinki, Finlandia

    ROR https://ror.org/02hb7bm88

  17. 17 Norwegian University of Science and Technology
    info

    Norwegian University of Science and Technology

    Trondheim, Noruega

    ROR https://ror.org/05xg72x27

  18. 18 Norwegian Institute for Air Research, Kjeller, Norway
  19. 19 Norwegian Meteorological Institute
    info

    Norwegian Meteorological Institute

    Oslo, Noruega

    ROR https://ror.org/001n36p86

  20. 20 Silva Tarouca Research Institute for Landscape and Ornamental Gardening
    info

    Silva Tarouca Research Institute for Landscape and Ornamental Gardening

    Průhonice, República Checa

    ROR https://ror.org/04gf11d56

  21. 21 Slovenian Forestry Institute, Ljubljana, Slovenia
  22. 22 Saints Cyril and Methodius University of Skopje
    info

    Saints Cyril and Methodius University of Skopje

    Skopje, Macedonia

    ROR https://ror.org/02wk2vx54

  23. 23 Tallinn Botanic Garden, Tallinn, Estonia
  24. 24 TNO, Utrecht, Netherlands
  25. 25 University of Bremen
    info

    University of Bremen

    Brema, Alemania

    ROR https://ror.org/04ers2y35

  26. 26 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  27. 27 Universidad de Navarra
    info

    Universidad de Navarra

    Pamplona, España

    ROR https://ror.org/02rxc7m23

  28. 28 University of Novi Sad
    info

    University of Novi Sad

    Novi Sad, Serbia

    ROR https://ror.org/00xa57a59

  29. 29 University of Tirana
    info

    University of Tirana

    Tirana, Albania

    ROR https://ror.org/03g9v2404

  30. 30 University of Vienna
    info

    University of Vienna

    Viena, Austria

    ROR https://ror.org/03prydq77

  31. 31 University of Vlorë
    info

    University of Vlorë

    Vlorë, Albania

    ROR https://ror.org/05ger6s34

  32. 32 Valahia University of Targoviste
    info

    Valahia University of Targoviste

    Târgovişte, Rumanía

    ROR https://ror.org/00ywqar95

  33. 33 Veterinary and Agrochemical Research Centre
    info

    Veterinary and Agrochemical Research Centre

    Bruselas, Bélgica

    ROR https://ror.org/0153sam53

  34. 34 Władysław Szafer Institute of Botany
    info

    Władysław Szafer Institute of Botany

    Cracovia, Polonia

    ROR https://ror.org/05p1pn123

Mostrar afiliaciones +
Revista:
Atmospheric Environment

ISSN: 1352-2310

Año de publicación: 2017

Volumen: 156

Páginas: 146-159

Tipo: Artículo

DOI: 10.1016/J.ATMOSENV.2017.02.032 SCOPUS: 2-s2.0-85014480468 WoS: WOS:000399628900015 GOOGLE SCHOLAR

Otras publicaciones en: Atmospheric Environment

Objetivos de desarrollo sostenible

Resumen

Objective 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. Results 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. Conclusions 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. © 2017 Elsevier Ltd