Advertisement

Environmental Science and Pollution Research

, Volume 24, Issue 3, pp 2578–2588 | Cite as

Comparison of four methods for spatial interpolation of estimated atmospheric nitrogen deposition in South China

  • Linglu Qu
  • Huayun Xiao
  • Nengjian Zheng
  • Zhongyi Zhang
  • Yu Xu
Research Article

Abstract

Spatial interpolation methods have been applied in many environmental research studies. However, it is still a controversial issue to select an appropriate interpolation method for the conversion of discrete sampling sites into continuous maps. This study aimed at selecting an optimal interpolation method to analyze the spatial pattern of atmospheric N deposition in South China. N deposition was calculated by 259 moss sample data. Four spatial interpolation methods, including inverse distance weighting (IDW), radial basis function (RBF), ordinary kriging (OK), and universal kriging (UK), were utilized for modeling the spatial distribution of N deposition. It is the first time that these methods were applied to analyze N deposition in South China. Validation method was used to evaluate the interpolation precision of the various methods, and the cross-validation method was used to evaluate their interpolation accuracy. Comparison of predicted values with measured values indicated that OK was the optimal method for analyzing the spatial distribution of N deposition in this study; it had the highest precision (mean error (ME) = −0.059, root-mean-square error (RMSE) = 5.240, mean relative error (MRE) = 0.129, mean absolute error (MAE) = 4.007) and the lowest uncertainties (standard deviation (SD) = 5.47, coefficient of variation (CV) = 0.15). RBF produced similar results as good as OK, while the worst performed interpolation method was UK. By using the OK method for analyzing N deposition, this work revealed systematic temporal and spatial variations in atmospheric N deposition in South China.

Keywords

Estimated N deposition Moss biomonitoring Spatial distribution Interpolation Cross-validation 

Notes

Acknowledgments

This study was kindly supported by the National Key Research and Development Program of China through grant 2016YFA0601000 (H.Y. Xiao); the National Natural Science Foundation of China through grants 41425014, 41273027, and 41173027 (H.Y. Xiao); and the National Basic Research Program of China through grant 2013CB956703 (H.Y. Xiao).

References

  1. Atkinson PM (2005) Spatial prediction and surface modeling. Geogr Anal 37:113–123. doi: 10.1111/j.1538-4632.2005.03702002.x CrossRefGoogle Scholar
  2. Bouwman AF, Van Vuuren DP, Derwent RG, Posch M (2002) A global analysis of acidification and eutrophication of terrestrial ecosystems. Water Air Soil Pollut 141:349–382. doi: 10.1023/a:1021398008726 CrossRefGoogle Scholar
  3. Bragazza L, Limpens J, Gerdol R, Grosvernier P, Hajek M, Hajek T, Hánsen P, Iacumin P, Kutnar L (2005) Nitrogen concentration and δ15N signature of ombrotrophic Sphagnum mosses at different N deposition levels in Europe. Glob Chang Biol 11:106–114CrossRefGoogle Scholar
  4. Chang YH, Liu XJ, Li KH, Lv JL, Song W (2013) Numerical modeling atmospheric nitrogen deposition: evolution process and models’ screening. Arid Land Geograp 36:383–392 (in Chinese)Google Scholar
  5. Chen XY, Mulder J (2007) Atmospheric deposition of nitrogen at five subtropical forested sites in South China. Sci Total Environ 378:317–330. doi: 10.1016/j.scitotenv.2007.02.028 CrossRefGoogle Scholar
  6. Cheng KS, Lin YC, Liou JJ (2008) Rain-gauge network evaluation and augmentation using geostatistics. Hydrol Process 22:2554–2564. doi: 10.1002/hyp.6851 CrossRefGoogle Scholar
  7. Clark CM, Tilman D (2008) Loss of plant species after chronic low-level nitrogen deposition to prairie grasslands. Nature 451:715CrossRefGoogle Scholar
  8. Cressie N (1990) The origins of kriging. Math Geol 22:239–252. doi: 10.1007/bf00889887 CrossRefGoogle Scholar
  9. Cressie N (1992) Statistics for spatial data. Terra Nov. 4:613–617Google Scholar
  10. Cui J, Zhou J, Peng Y, He YQ, Yang H, Xu LJ, Chan A (2014) Long-term atmospheric wet deposition of dissolved organic nitrogen in a typical red-soil agro-ecosystem, southeastern China. Environ Sci Proc Imp 16:1050–1058. doi: 10.1039/C3EM00613A CrossRefGoogle Scholar
  11. ESRI R (2011) ArcGIS desktop: release 10. Environmental Systems Research Institute, CAGoogle Scholar
  12. Fenn ME, Haeuber R, Tonnesen GS, Baron JS, Grossman-Clarke S, Hope D, Jaffe DA, Copeland S, Geiser L, Rueth HM, Sickman JO (2003) Nitrogen emissions, deposition, and monitoring in the western United States. Bioscience 53:391–403. doi: 10.1641/0006-3568(2003)053[0391:nedami]2.0.co;2 CrossRefGoogle Scholar
  13. Galloway JN, Cowling EB (2002) Reactive nitrogen and the world: 200 years of change. Ambio 31:64–71. doi: 10.1639/0044-7447(2002)031[0064:rnatwy]2.0.co;2 CrossRefGoogle Scholar
  14. Galloway JN, Denterner FJ, Capone DG, Boyer EW, Howarth RW, Seitzinger SP, Asner GP, Cleveland CC, Green PA, Holland EA, Karl DM, Michaels AF, Porter JH, Townsend AR, Vorosmarty CJ (2004) Nitrogen cycles: past, present, and future. Biogeochemistry 70:153–226. doi: 10.1007/s1 0533-004-0370-0 CrossRefGoogle Scholar
  15. Galloway JN, Townsend AR, Erisman JW, Bekunda M, Cai ZC, Freney JR, Martinelli LA, Seitzinger SP, Sutton MA (2008) Transformation of the nitrogen cycle: recent trends, questions, and potential solutions. Science 320:889–892. doi: 10.1126/science.1136674 CrossRefGoogle Scholar
  16. Gong G, Mattevada S, O’Bryant SE (2014) Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas. Environ Res 130:59–69. doi: 10.1016/j.envres.2013.12.005 CrossRefGoogle Scholar
  17. Goulding KWT (1990) Nitrogen deposition to land from the atmosphere. Soil Use Manag 6:61–63. doi: 10.1111/j.1475-2743.1990.tb00801.x CrossRefGoogle Scholar
  18. Huang DY, Xu YG, Zhou B, Zhang HH, Lan JB (2010) Wet deposition of nitrogen and sulfur in Guangzhou, a subtropical area in South China Environ Monit Assess 171:429--439 doi: 10.1007/s10661-009-1289-7
  19. Huang J, Zhang W, Zhu X, Gilliam F, Chen H, Lu X, Mo J (2015) Urbanization in China changes the composition and main sources of wet inorganic nitrogen deposition. Environ Sci Pollut Res 22:6526–6534. doi: 10.1007/s11356-014-3786-7 CrossRefGoogle Scholar
  20. Huang YL, Lu XX, Chen K (2013) Wet atmospheric deposition of nitrogen: 20 years measurement in Shenzhen City, China. Environ Monit Assess 185:113–122. doi: 10.1007/s10661-012-2537-9 CrossRefGoogle Scholar
  21. Isaaks EH, Srivastava RM (1989) Applied geostatistics. Oxford University Press, New York, p. 561Google Scholar
  22. Jia YL, Yu GR, He NP, Zhan XY, Fang HJ, Sheng WP, Zuo Y, Zhang DY, Wang QF (2014) Spatial and decadal variations in inorganic nitrogen wet deposition in China induced by human activity. Sci Rep 4:3763. doi: 10.1038/srep03763 Google Scholar
  23. Journel AG, Kyriakidis PC, Mao S (2000) Correcting the smoothing effect of estimators: a spectral postprocessor. Math Geol 32:787–813CrossRefGoogle Scholar
  24. Kravchenko AN (2003) Influence of spatial structure on accuracy of interpolation methods. Soil Sci Soc Am J 67:1564–1571. doi: 10.2136/sssaj2003.1564 CrossRefGoogle Scholar
  25. Lü CQ, Tian HQ (2007) Spatial and temporal patterns of nitrogen deposition in China: synthesis of observational data. J Geophys Res Atmos 112. doi: 10.1029/2006JD007990
  26. Lü CQ, Tian HQ (2014) Half-century nitrogen deposition increase across China: a gridded time-series data set for regional environmental assessments. Atmos Environ 97:68–74. doi: 10.1016/j.atmosenv.2014.07.061 CrossRefGoogle Scholar
  27. Laslett GM, McBratney AB, Pahl PJ, Hutchinson MF (1987) Comparison of several spatial prediction methods for soil pH. J Soil Sci 38:325–341. doi: 10.1111/j.1365-2389.1987.tb02148.x CrossRefGoogle Scholar
  28. Li J, Heap AD (2011) A review of comparative studies of spatial interpolation methods in environmental sciences: performance and impact factors. Ecol Infor 6:228–241. doi: 10.1016/j.ec oinf.2010.12.003 CrossRefGoogle Scholar
  29. Liu C, Wang Q, Zou C, Hayashi Y, Yasunari T (2015) Recent trends in nitrogen flows with urbanization in the Shanghai megacity and the effects on the water environment. Environ Sci Pollut Res 22:3431–3440. doi: 10.1007/s11356-014-3825-4 CrossRefGoogle Scholar
  30. Liu R, Chen Y, Sun C, Zhang P, Wang J, Yu W, Shen Z (2014) Uncertainty analysis of total phosphorus spatial-temporal variations in the Yangtze River Estuary using different interpolation methods. Mar Pollut Bull 86:68–75. doi: 10.1016/j.marpolbul.2014.07.041 CrossRefGoogle Scholar
  31. Liu XY, Xiao HY, Liu CQ, Li YY, Xiao HW (2008a) Stable carbon and nitrogen isotopes of the moss Haplocladium microphyllum in an urban and a background area (SW China): the role of environmental conditions and atmospheric nitrogen deposition. Atmos Environ 42:5413–5423. doi: 10.1016/j.atmosenv.2008.02.038 CrossRefGoogle Scholar
  32. Liu XY, Xiao HY, Liu CQ, Li YY, Xiao HW (2008b) Tissue N content and 15N natural abundance in epilithic mosses for indicating atmospheric N deposition in the Guiyang area, SW China. Appl Geochem 23:2708–2715CrossRefGoogle Scholar
  33. Liu XJ, Duan L, Mo JM, Du EZ, Shen JL, Lu XK, Zhang Y, Zhou XB, He CE, Zhang FS (2011) Nitrogen deposition and its ecological impact in China: an overview. Environ Pollut 159:2251–2264. doi: 10.1016/j.envpol.2010.08.002 CrossRefGoogle Scholar
  34. Liu XY, Xiao HY, Liu CQ (2009) Quantification of atmospheric nitrogen deposition at Guiyang area based on nitrogen concentration of epilithic mosses. Acta Ecol Sin 29:6646–6653 (in Chinese)Google Scholar
  35. Lloyd CD (2005) Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain. J Hydrol 308:128–150. doi: 10.1016/j.jhydrol.2004.10.026 CrossRefGoogle Scholar
  36. Lu GY, Wong DW (2008) An adaptive inverse-distance weighting spatial interpolation technique. Comput Geosci 34:1044–1055. doi: 10.1016/j.cageo.2007.07.010 CrossRefGoogle Scholar
  37. Lu L, Cheng H, Pu X, Liu X, Cheng Q (2015) Nitrate behaviors and source apportionment in an aquatic system from a watershed with intensive agricultural activities. Environ Sci Proc Imp 17:131–144. doi: 10.1039/C4EM00502C CrossRefGoogle Scholar
  38. Matheron G (1969) Le krigeage universel: cahiers du Centre de Morphologie Mathematique. Fontainebleau, ParisGoogle Scholar
  39. Meyer M, Schröder W, Nickel S, Leblond S, Lindroos A-J, Mohr K, Poikolainen J, Santamaria JM, Skudnik M, Thöni L, Beudert B, Dieffenbach-Fries H, Schulte-Bisping H, Zechmeister HG (2015) Relevance of canopy drip for the accumulation of nitrogen in moss used as biomonitors for atmospheric nitrogen deposition in Europe. Sci Total Environ 538:600–610. doi: 10.1016/j.scitotenv.2015.07.069 CrossRefGoogle Scholar
  40. Mirzaei R, Sakizadeh M (2016) Comparison of interpolation methods for the estimation of groundwater contamination in Andimeshk-Shush Plain, southwest of Iran. Environ Sci Pollut Res 23:2758–2769. doi: 10.1007/s11356-015-5507-2 CrossRefGoogle Scholar
  41. Moran PAP (1948) The interpretation of statistical maps. J Royal Stat Soc Series B-Stat Method 10:243–251Google Scholar
  42. Nadim F, Trahiotis MM, Stapcinskaite S, Perkins C, Carley RJ, Hoag GE, Yang X (2001) Estimation of wet, dry and bulk deposition of atmospheric nitrogen in Connecticut. J Environ Monit 3:671–680. doi: 10.1039/B107008H CrossRefGoogle Scholar
  43. Nyberg F, Gustavsson P, Järup L, Bellander T, Berglind N, Jakobsson R, Pershagen G (2000) Urban air pollution and lung cancer in Stockholm. Epidemiology 11:487–495CrossRefGoogle Scholar
  44. Pan YP, Wang YS, Tang GQ, Wu D (2012) Wet and dry deposition of atmospheric nitrogen at ten sites in northern China. Atmos Chem Phys 12:6515–6535. doi: 10.5194/acp-12-6515-2012 CrossRefGoogle Scholar
  45. Pesch R, Schröder W, Schmidt G (2007) Nitrogen accumulation in forests. Exposure monitoring by mosses. Sci World J 7:151–158. doi: 10.1100/tsw.2007.11 CrossRefGoogle Scholar
  46. Pesch R, Schröder W, Schmidt G, Genssler L (2008) Monitoring nitrogen accumulation in mosses in central European forests. Environ Pollut 155:528–536. doi: 10.1016/j.envpol.2008.02.018 CrossRefGoogle Scholar
  47. Pitcairn C, Fowler D, Leith I, Sheppard L, Tang S, Sutton M, Famulari D (2006) Diagnostic indicators of elevated nitrogen deposition. Environ Pollut 144:941–950. doi: 10.1016/j.envpol.2006.01.049 CrossRefGoogle Scholar
  48. Pitcairn CER, Fowler D, Grace J (1995) Deposition of fixed atmospheric nitrogen and foliar nitrogen content of bryophytes and Calluna vulgaris (L.) Hull. Environ Pollut 88:193–205. doi: 10.1016/0269-7491(95)91444-P CrossRefGoogle Scholar
  49. Pitcairn CER, Leith ID, Fowler D, Hargreaves KJ, Moghaddam M, Kennedy VH, Granat L (2001) Foliar nitrogen as an indicator of nitrogen deposition and critical loads exceedance on a European scale. Water Air Soil Pollut 130:1037–1042. doi: 10.1023/a:1013908312369 CrossRefGoogle Scholar
  50. Pitcairn CER, Skiba UM, Sutton MA, Fowler D, Munro R, Kennedy V (2002) Defining the spatial impacts of poultry farm ammonia emissions on species composition of adjacent woodland ground flora using Ellenberg Nitrogen Index, nitrous oxide and nitric oxide emissions and foliar nitrogen as marker variables. Environ Pollut 119:9–21. doi: 10.1016/S0269-7491(01)00148-8 CrossRefGoogle Scholar
  51. Powell MJD (1990) The theory of radial basis function approximation in 1990. University of Cambridge Press, CambridgeGoogle Scholar
  52. Schröder W, Holy M, Pesch R, Harmens H, Fagerli H, Alber R, Coskun M, De Temmerman L, Frolova M, González-Miqueo L, Jeran Z, Kubin E, Leblond S, Liiv S, Maňkovská B, Piispanen J, Santamaria P, Suchara I, Yurukova L, Thöni L, Zechmeister HG (2010) First Europe-wide correlation analysis identifying factors best explaining the total nitrogen concentration in mosses. Atmos Environ 44:3485–3491. doi: 10.1016/j.atm os en v.2010.06.024 CrossRefGoogle Scholar
  53. Schwartz J (1994) What are people dying of on high air pollution days? Environ Res 64:26–35. doi: 10.1006/enrs.1994.1004 CrossRefGoogle Scholar
  54. Skinner RA, Ineson P, Jones H, Sleep D, Leith ID, Sheppard LJ (2006) Heathland vegetation as a bio-monitor for nitrogen deposition and source attribution using δ15N values. Atmos Environ 40:498–507. doi: 10.1016/j.atmosenv.2005.09.054 CrossRefGoogle Scholar
  55. Skudnik M, Jeran Z, Batič F, Kastelec D (2016) Spatial interpolation of N concentrations and δ15N values in the moss Hypnum cupressiforme collected in the forests of Slovenia. Ecol Indic 61(Part 2):366–377. doi: 10.1016/j.ecolind.2015.09.038 CrossRefGoogle Scholar
  56. Skudnik M, Jeran Z, Batič F, Simončič P, Kastelec D (2015) Potential environmental factors that influence the nitrogen concentration and δ15N values in the moss Hypnum cupressiforme collected inside and outside canopy drip lines. Environ Pollut 198:78–85. doi: 10.1016/j.envpol.2014.12.032 CrossRefGoogle Scholar
  57. Skudnik M, Jeran Z, Batič F, Simončič P, Lojen S, Kastelec D (2014) Influence of canopy drip on the indicative N, S and δ15N content in moss Hypnum cupressiforme. Environ Pollut 190:27–35. doi: 10.1016/j.envpol.2014.03.016 CrossRefGoogle Scholar
  58. Solga A, Burkhardt J, Zechmeister HG, Frahm JP (2005) Nitrogen content, 15 N natural abundance and biomass of the two pleurocarpous mosses Pleurozium schreberi (Brid.) Mitt. and Scleropodium purum (Hedw.) Limpr. in relation to atmospheric nitrogen deposition. Environ Pollut 134:465–473. doi: 10.1016/j.envpol.2004.09.008 CrossRefGoogle Scholar
  59. Stahl K, Moore RD, Floyer JA, Asplin MG, McKendry IG (2006) Comparison of approaches for spatial interpolation of daily air temperature in a large region with complex topography and highly variable station density. Agric For Meteorol 139:224–236. doi: 10.1016/j.agrformet.2006.07.004 CrossRefGoogle Scholar
  60. Stone M (1974) Cross-validatory choice and assessment of statistical predictions. J Royal Stat Soc Series B—Stat Method 36:111–147Google Scholar
  61. Sun Y, Kang S, Li F, Zhang L (2009) Comparison of interpolation methods for depth to groundwater and its temporal and spatial variations in the Minqin oasis of northwest China. Environ Model Softw 24:1163–1170. doi: 10.1016/j.envsoft.2009.03.009 CrossRefGoogle Scholar
  62. Varela Z, Carballeira A, Fernández JA, Aboal JR (2013) On the use of epigaeic mosses to biomonitor atmospheric deposition of nitrogen. Arch Environ Contam Toxicol 64:562–572. doi: 10.1007/s00244-012-9866-0 CrossRefGoogle Scholar
  63. Wagner PD, Fiener P, Wilken F, Kumar S, Schneider K (2012) Comparison and evaluation of spatial interpolation schemes for daily rainfall in data scarce regions. J Hydrol 464-465:–400. doi: 10.1016/j.jhydrol.2012.07.026
  64. Weber D, Englund E (1992) Evaluation and comparison of spatial interpolators. Math Geol 24:381–391. doi: 10.1007/BF00891270 CrossRefGoogle Scholar
  65. Wu X, Yan L (2007) Setting parameters and choosing optimum semivariogram models of ordinaty kriging interpolation—a case study of spatial interpolation to January average temperature of Fujian province. Geo-Inform Sci 9:104–108 (in Chinese)Google Scholar
  66. Xiao HY, Tang CG, Xiao HW, Liu XY, Liu CQ (2010a) Stable sulphur and nitrogen isotopes of the moss Haplocladium microphyllum at urban, rural and forested sites. Atmos Environ 44:4312–4317. doi: 10.1016/j.atmosenv.2010.05.023 CrossRefGoogle Scholar
  67. Xiao HY, Tang CG, Xiao HW, Liu XY, Liu CQ (2010b) Mosses indicating atmospheric nitrogen deposition and sources in the Yangtze River Drainage Basin, China. J Geophys Res Atmos (1984a) 115. doi: 10.1029/2009JD012900
  68. Xiao HY, Xie ZY, Tang CG, Wang YL, Liu CQ (2011) Epilithic moss as a bio-monitor of atmospheric N deposition in South China. J Geophys Res Atmos (1984b) 116. doi: 10.1029/2011JD016229
  69. Xie Y, Chen TB, Lei M, Yang J, Guo QJ, Song B, Zhou XY (2011) Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: accuracy and uncertainty analysis. Chemosphere 82:468–476. doi: 10.1016/j.chemosphere.2010.09.053 CrossRefGoogle Scholar
  70. Yao X, Fu B, Lu Y, Sun F, Wang S, Liu M (2013) Comparison of four spatial interpolation methods for estimating soil moisture in a complex terrain catchment. Plos One 8. doi: 10.1371/journal.pone.0054660
  71. Zhang YQ, Chen CC, Yin YX, Yang XH (2013) Spatial interpolation model selection of multi-year average precipitation in Jiangxi Province. Res Soil Water Conserv 20:69–74 (in Chinese)Google Scholar
  72. Zhong JL (2010) Study on spatial precipitation interpolation precision based on GIS in Xinjiang. Arid Environ Monitor 24:43–46 (in Chinese)Google Scholar
  73. Zhu JX, He NP, Wang QF, Yuan GF, Wen D, Yu GR, Jia YL (2015) The composition, spatial patterns, and influencing factors of atmospheric wet nitrogen deposition in Chinese terrestrial ecosystems. Sci Total Environ 511:777–785. doi: 10.1016/j.scitotenv.2014.12.038 CrossRefGoogle Scholar
  74. Zimmerman D, Pavlik C, Ruggles A, Armstrong M (1999) An experimental comparison of ordinary and universal kriging and inverse distance weighting. Math Geol 31:375–390. doi: 10.1023/A:1007586507433 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Linglu Qu
    • 1
    • 2
  • Huayun Xiao
    • 1
  • Nengjian Zheng
    • 1
    • 2
  • Zhongyi Zhang
    • 1
    • 2
  • Yu Xu
    • 1
    • 2
  1. 1.State Key Laboratory of Environmental Geochemistry, Institute of GeochemistryChinese Academy of ScienceGuiyangChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

Personalised recommendations