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Use of ordinary cokriging with magnetic susceptibility for mapping lead concentrations in soils of an urban contaminated site

  • Soils, Sec 2 • Global Change, Environ Risk Assess, Sustainable Land Use • Research Article
  • Published:
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Abstract

Purpose

Lead contamination is a prevalent issue affecting cities worldwide. Traditional fieldwork and laboratory analysis techniques can be time-consuming and costly. The purpose of this study was to evaluate the performance of ordinary cokriging (CK) when volume magnetic susceptibility (κ) is used as a co-variable for spatial interpolation of Pb in contaminated urban soils.

Materials and methods

The study was conducted in contaminated urban soils of a former unregulated landfill site. A total of 76 surface samples (0–10 cm) were collected using a systematic sampling grid separated by 20-m intervals. Magnetic susceptibility measurements were taken at a higher density of 10-m intervals with 288 measurements. Thus, it was used as an auxiliary variable to predict Pb concentrations by the CK procedure with an aim to improve spatial interpolation of Pb. To determine the effectiveness of CK over the ordinary kriging (OK) procedure, the spatial density of samples was reduced prior to interpolation. A total of ~ 15%, 25%, 35%, and 50% of the Pb samples were randomly selected and reserved for validation. Omnidirectional semivariograms and covariograms were fitted using log-transformed data prior to interpolation.

Results and discussion

Measurements of κ shared a significant relationship with Pb concentrations by the Spearman’s Rho correlation analysis (rs = 0.676, p < 0.01). The effectiveness of the CK procedure over OK was determined using validation datasets. Statistically, the results showed that lnPb when its auxiliary relations with lnκ were used in CK had overall lower “root mean square error” (RMSE) and predicted lnPb values from the CK procedure had a higher r2 value with measured lnPb than OK. A model produced by the CK procedure with a reduced spatial density of 49 Pb points provided the more accurate map with a RMSE of 0.550 and an r2 value of 0.730, p < 0.01 level.

Conclusions

This technique can potentially reduce fieldwork and soil analysis costs considerably. Measurements of Pb and κ must share a substantial level of spatial continuity to implement CK effectively. Where applicable, it can be used in the site-specific evaluation of hazard posed by Pb exposure to ecosystems, human health or water bodies in urban green spaces, roadside soils, allotments or brownfield sites.

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References

  • Adhikary SK, Yilmaz AG, Muttil N (2015) Optimal design of rain gauge network in the Middle Yarra River catchment, Australia. Hydrol Process 29:2582–2599

    Google Scholar 

  • Basaran M, Erpul G, Ozcan AU, Saygin DS, Kilbar M, Bayramin I, Yilman FE (2011) Spatial information of soil hydraulic conductivity and performance of cokriging over kriging in a semi-arid basin scale. Environ Earth Sci 63:827–838

    Google Scholar 

  • Bhunia GS, Shit PK, Maiti R (2018) Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC). J Saudi Soc Agric Sci 17:114–126

    Google Scholar 

  • Blaha U, Appel E, Stanjek H (2008) Determination of anthropogenic boundary depth in industrially polluted soil and semi-quantification of heavy metal loads using magnetic susceptibility. Environ Pollut 156:278–289

    CAS  Google Scholar 

  • Carr R, Zhang C, Moles N, Harder M (2008) Identification and mapping of heavy metal pollution in soils of a sports ground in Galway City. Ireland, using a portable XRF analyser and GIS. Environ Geochem Health 30:45–52

    Google Scholar 

  • Cambardella CA, Moorman TB, Novak JM, Parkin TB, Karlen DL, Turco RF, Konopka AE (1994) Field scale variability of soil properties in central Iowa soils. SSSAJ 58:1501–1511

    Google Scholar 

  • Canbay M, Aydin A, Kurtulus C (2010) Magnetic susceptibility and heavy-metal contamination in topsoils along the Izmit Gulf coastal area and IZAYTAS (Turkey). J Appl Geophys 70(1):46–57

    Google Scholar 

  • Cao S, Lu A, Wang J, Huo L (2017) Modeling and mapping of cadmium in soils based on qualitative and quantitative auxiliary variables in a cadmium contaminated area. Sci Total Environ 580:430–439

    CAS  Google Scholar 

  • Chen A, Cai B, Dietrich KN, Radcliffe J, Rogan WJ (2007) Lead exposure, IQ, and behavior in urban 5- to 7-year-olds: does lead affect behavior only by lowering IQ? Pediatrics 119(3):650–658

    Google Scholar 

  • Cheng H, Li M, Zhao C, Li K, Peng M, Qin A, Cheng X (2014) Overview of trace metals in the urban soil of 31 metropolises in China. J Geochem Explor 139:31–52

    CAS  Google Scholar 

  • Chlopecka A, Bacon JR, Wilson MJ, Kay J (1996) Heavy metals in the environment – forms of cadmium, lead and zinc in contaminated soils from southwest Poland. J Environ Qual 25:69–79

    CAS  Google Scholar 

  • Clark I (1979) Practical geostatistics. Applied Science Publishers Ltd., Essex

    Google Scholar 

  • Dankoub Z, Ayoubi S, Khademi H, Lu SG (2012) Spatial distribution of magnetic properties and selected heavy metals in calcareous soils as affected by land use in the Isfahan Region, Central Iran. Pedosphere 22(1):33–47

    CAS  Google Scholar 

  • Dao L, Morrison L, Kiely G, Zhang C (2013) Spatial distribution of potentially bioavailable metals in surface soils of a contaminated sports ground in Galway, Ireland. Environ Geochem Health 35:227–238

    CAS  Google Scholar 

  • Dearing JA (1999) Environmental magnetic susceptibility. Using the Bartington MS2 System, 2nd edn. Chi Publishing, Kenilworth

    Google Scholar 

  • Ďurža O (1999) Heavy metals contamination and magnetic susceptibility in soils around metallurgical plant. Phys Chem Earth A 24(6):541–543

    Google Scholar 

  • El Baghdadi M, Barakat A, Sajieddine M, Nadem S (2012) Heavy metal pollution and soil magnetic susceptibility in urban soil of Beni Mellal City (Morrocco). Environ Earth Sci 66:141–155

    Google Scholar 

  • Elbasiouny H, Abowaly M, Abu_Alkheir A, Gad AA (2014) Spatial variation of soil carbon and nitrogen pools by using ordinary Kriging method in an area of north Nile Delta, Egypt. Catena 113:70–78

    CAS  Google Scholar 

  • Fabijańczyk P, Zawadzki J, Magiera T (2017) Magnetometric assessment of soil contamination in problematic area using empirical Bayesian and indicator kriging: a case study in Upper Silesia, Poland. Geoderma 308:69–77

    Google Scholar 

  • Facchinelli A, Sacchi E, Mallen L (2001) Multivariate statistical and GIS-based approach to identify heavy metal sources in soils. Environ Pollut 114:313–324

    CAS  Google Scholar 

  • Flanders PJ (1994) Collection, measurement, and analysis of airborne magnetic particulates from pollution in the environment. J Appl Phys 75:5931–5936

    CAS  Google Scholar 

  • Flegal AR, Smith DR (1992) Current needs for increased accuracy and precision in measurements of low levels of lead in blood. Environ Res 58(1–2):25–133

    Google Scholar 

  • Fortin MJ, Dale MRT, ver Hoef J (2002) Spatial analysis in ecology. Encycl Environmetr 4:2051–2058

    Google Scholar 

  • Golden N, Morrison L, Gibson PJ, Potito AP, Zhang C (2015) Spatial patterns of metal contamination and magnetic susceptibility of soils at an urban bonfire site. Appl Geochem 52:86–96

    CAS  Google Scholar 

  • Golden N, Zhang C, Potito AP, Gibson PJ, Bargary N, Morrison L (2017) Impact of grass cover on the magnetic susceptibility measurements for assessing metal contamination in urban topsoil. Environ Res 155:294–306

    CAS  Google Scholar 

  • Gu YG, Gao YP, Lin Q (2016) Contamination, bioaccessibility and human health risk of heavy metals in exposed-lawn soils from 28 urban parks in southern China's largest city, Guangzhou. Appl Geochem 67:52–58

    CAS  Google Scholar 

  • Hanesch M, Scholger R (2002) Mapping of heavy metal loadings in soils by means of magnetic susceptibility measurements. Environ Geol 42:857–870

    CAS  Google Scholar 

  • Heller F (1998) Magnetic record of industrial pollution in forest soils of Upper Silesia, Poland. J Geophys Res 103(B8):17,767–17,774

    CAS  Google Scholar 

  • Hengl T (2009) A practical guide to geostatistical mapping. JRC Scientific and Technical Reports, 2nd edn. Office for Official Publication of the European Communities, Luxembourg

    Google Scholar 

  • Hooker PJ, Nathanail CP (2006) Risk-based characterisation of lead in urban soils. Chem Geol 226:340–351

    CAS  Google Scholar 

  • Hou D, O’Connor D, Nathanail P, Tian L, Ma Y (2017) Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: a critical review. Environ Pollut 231:1188–1200

    CAS  Google Scholar 

  • Innov-X Systems, Inc. (2019) Handheld XRF tests lead (Pb) in soil, dusts, and on surfaces https://www.olympus-ims.com/en/applications/xrf-tests-lead-soil-surfaces/ Last viewed on 04.03.2019

  • Johnston K, ver Hoef JM, Krivoruchko K, Lucas N (2001) Using ArcGIS™ Geostatistical Analyst - GIS by ESRI™. ESRI, Redlands

    Google Scholar 

  • Jordanova NV, Jordanova DV, Veneva L, Yorova K, Petrovský E (2003) Magnetic response of soils and vegetation to heavy metal pollution – a case study. Environ Sci Technol 37:4417–4424

    CAS  Google Scholar 

  • Juang KW, Lee DY (1998) A comparison of three kriging methods using auxiliary variables in heavy-metal contaminated soils. J Environ Qual 27(2):355–363

    CAS  Google Scholar 

  • Kapička A, Petrovský E, Ustjak S, Macháčková K (1999) Proxy mapping of fly-ash pollution of soils around a coal-burning power plant: a case study in the Czech Republic. J Geochem Explor 66:291–297

    Google Scholar 

  • Karimi R, Aoyoubi S, Jalalian A, Sheikh-Hosseini AR, Afyuni M (2011) Relationships between magnetic susceptibility and heavy metals in urban topsoils in the arid region of Isfahan, central Iran. J Appl Geophys 74:1–7

    Google Scholar 

  • Knotters M, Brus DJ, Oude Voshaar JH (1995) A comparison of kriging, co-kriging and kriging combined with regression for spatial interpolation of horizon depth with censored observations. Geoderma 67:227–246

    Google Scholar 

  • Li J (2016) Assessing spatial predictive models in the environmental sciences: accuracy measures, data variation and variance explained. Environ Model Softw 80:1–8

    CAS  Google Scholar 

  • Louis GB, Damstra T, Diaz-Barriga F et al (2006) Principles for evaluating health risks associated with exposure to chemicals. World Health Organization Environmental Health Criteria 237

  • Lu X, Wang L, Lei K, Huang J, Zhai Y (2009) Contamination assessment of copper, lead, zinc, manganese and nickel in street dust of Baoji, NW China. J Hazard Mater 161:1058–1062

    CAS  Google Scholar 

  • Lu S, Yu X, Chen Y (2016) Magnetic properties, microstructure and mineralogical phases of technogenic magnetic particles (TMPs) in urban soils: their source identification and environmental implications. Sci Total Environ 543:239–247

    CAS  Google Scholar 

  • Magiera T, Mendakiewicz M, Szuszkiewicz M, Jabłońska M, Chróst L (2016) Technogenic magnetic particles in soils as evidence of historical mining and smelting activity: a case of the Brynica River Valley, Poland. Sci Total Environ 566-567:536–551

    CAS  Google Scholar 

  • Mielke HW (1994) Lead in New Orleans soils: new images of an urban environment. Environ Geochem Health 16(3–4):123–128

    CAS  Google Scholar 

  • Mielke HW, Laidlaw MAS, Gonzales CR (2011) Estimation of leaded (Pb) gasoline’s continuing material and health impacts on 90 US urbanized areas. Environ Int 37:248–257

    CAS  Google Scholar 

  • Moioli P, Seccaroni C (2000) Analysis of art objects using a portable x-ray fluorescence spectrometer. X-Ray Spectrom 29:48–52

    CAS  Google Scholar 

  • Möller A, Müller HW, Abdullah A, Abdelgawad G, Uttermann J (2005) Urban soil pollution in Damascus, Syria: concentrations and patterns of heavy metals in the soils of the Damascus Ghouta. Geoderma 124:63–71

    Google Scholar 

  • Motuzova GV, Minkina TM, Karpova EA, Barsova NU, Mandzhieva SS (2014) Soil contamination with heavy metals as a potential and real risk to the environment. J Geochem Explor 144(B):241–246

    CAS  Google Scholar 

  • Muxworthy AR, Matzka J, Fernandez Davila A, Petersen N (2003) Magnetic signature of daily sampled urban atmospheric particles. Atmos Environ 37(29):4163–4169

    CAS  Google Scholar 

  • Pereira P, Brevik E, Muñoz-Rojas M, Miller B, Brevik E (2017) Soil mapping and process modeling for sustainable land use management. Elsevier, Saint Louis

    Google Scholar 

  • Petrovský E, Kapička A, Jordanova N, Knab M, Hoffmann V (2000) Low-field magnetic susceptibility: a proxy method of estimating increased pollution of different environmental systems. Environ Geol 39(3–4):312–318

    Google Scholar 

  • Posthuma L, Eijsackers HJP, Koelmans AA, Vijver MG (2008) Ecological effects of diffuse mixed pollution are site-specific and require higher-tier risk assessment to improve site management decisions: a discussion paper. Sci Total Environ 406:503–517

    Google Scholar 

  • Rachwał M, Kardel K, Magiera T, Bens O (2017) Application of magnetic susceptibility in assessment of heavy metal contamination of Saxonian soil (Germany) caused by industrial dust deposition. Geoderma 295:10–21

    Google Scholar 

  • Rossiter DG (2007) Technical note: co-kriging with the gstat package of the R environment for statistical computing, 2nd edn. International Institute for Geo-information Science & Earth Observation (ITC), Enschede

    Google Scholar 

  • Salo H, Bucko MS, Vaahhtovuo E, Limo J, Makinen J, Pesonen LJ (2012) Biomonitoring of air pollution in SW Finland by magnetic and chemical measurements of moss bags and lichens. J Geochem Explor 115:69–81

    CAS  Google Scholar 

  • Schibler L, Boyko T, Ferdyn M, Gajda M, Höll S, Jordanova N, Rösler N, MAGPROX Team (2002) Topsoil magnetic susceptibility mapping: data reproducibility and compatibility, measurement strategy. Stud Geophys Geod 46(1):43–57

    Google Scholar 

  • Shahandeh H, Wright AL, Hons FM, Lascano RJ (2005) Spatial and temporal variation of soil nitrogen parameters related to soil texture and corn yield. Agron J 97:772–782

    Google Scholar 

  • Strzyszcz Z, Magiera T (1998) Magnetic susceptibility and heavy metals contamination in soils of southern Poland. Phys Chem Earth 23(9–10):1127–1131

    Google Scholar 

  • Strzyszcz Z, Magiera T, Heller F (1996) The influence of industrial immissions on the magnetic susceptibility of soils in the Upper Silesia. Stud Geophys Geod 40:276–286

    Google Scholar 

  • Wang B, Xia D, Yu Y, Chen H, Jia J (2018) Source apportionment of soil-contamination in Baotou City (North China) based on a combined magnetic and geochemical approach. Sci Total Environ 642:95–104

    CAS  Google Scholar 

  • Wawer M, Magiera T, Ojha G, Appel E, Kusza G, Hu S, Basavaiah N (2015) Traffic-related pollutants in roadside soils of different countries in Europe and Asia. Water Air Soil Pollut 226(216):1–14

    CAS  Google Scholar 

  • Waychunas GA, Kim CS, Banfield JF (2005) Nanoparticulate iron oxide minerals in soils and sediments: unique properties and contaminant scavenging mechanisms. J Nanopart Res 7:409–433

    CAS  Google Scholar 

  • Weindorf DC, Bakr N, Zhu Y (2014) Chapter one - advances in portable X-ray fluorescence (PXRF) for environmental, pedological, and agronomic applications. Adv Agron 128:1–45

    Google Scholar 

  • 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

    CAS  Google Scholar 

  • Zawadzki J, Fabijańczyk P (2008) Reduction of soil contamination uncertainty assessment using magnetic susceptibility measurements and CO_EST method. Proc ECOpole 2(1):169–174

    CAS  Google Scholar 

  • Zawadzki J, Magiera T, Fabijańczyk P (2009) Geostatistical evaluation of magnetic indicators of forest soil contamination with heavy metals. Stud Geophys Geod 53:132–149

    Google Scholar 

  • Zawadzki J, Szuszkiewicz M, Fabijańczyk P, Magiera T (2016) Geostatistical discrimination between different sources of soil pollutants using a magneto-geochemical data set. Chemosphere 164:668–676

    CAS  Google Scholar 

  • Zhang C (2006) Using multivariate analyses and GIS to identify pollutants and their spatial patterns in urban soils in Galway, Ireland. Environ Pollut 142(3): 501–511

    CAS  Google Scholar 

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Correspondence to Nessa Golden or Liam Morrison.

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Golden, N., Zhang, C., Potito, A. et al. Use of ordinary cokriging with magnetic susceptibility for mapping lead concentrations in soils of an urban contaminated site. J Soils Sediments 20, 1357–1370 (2020). https://doi.org/10.1007/s11368-019-02537-7

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  • DOI: https://doi.org/10.1007/s11368-019-02537-7

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