JRC Ispra - IES1

A framework to estimate the distribution of heavy metals in

European Soils VIENNA, August 27th 2007

Luis Rodríguez-Lado, H. Reuter & T. Hengl

Eurosoil 2008 / Vienna

JRC Ispra - IES2

Soil data

• FOREGS database• Association of the Geological Surveys

of the European Union

• Geochemical Atlas of Europe

JRC Ispra - IES3

Maps of Heavy Metals: Situation at present

JRC Ispra - IES4

Why geostatistics?

• It gives an objective estimate:– of the HMC values– of the associated uncertainty

• A high number of auxiliary predictors can be used

• An in-depth analysis of HMC sources is possible (is it random?)

• It can be automated (R scripts)

JRC Ispra - IES5

FOREGS soil database

JRC Ispra - IES6

Targeted variables

• 8 heavy metals in soils:– As, Cd, Cr, Cu, Hg, Ni, Pb, Zn

JRC Ispra - IES7

FOREGS soil database: Exploratory analysisAS

foregs$AS

Freq

uenc

y

0 100 300

050

010

0015

00

CD

foregs$CD

Freq

uenc

y

0 5 10 15 20

050

010

0015

00

CR

foregs$CRFr

eque

ncy

0 500 1500

050

010

0015

00

CU

foregs$CU

Freq

uenc

y

0 100 300

050

010

0015

00

HG

foregs$HG

Freq

uenc

y

0 1 2 3 4

050

010

0015

00

NI

foregs$NI

Freq

uenc

y

0 1000 2000

050

010

0015

00

PB

foregs$PB

Freq

uenc

y

0 2000 4000

050

010

0015

00

ZN

foregs$ZN

Freq

uenc

y

0 1000 2000 3000

050

010

0015

00

logAS

log(foregs$AS)

Freq

uenc

y

1 2 3 4 5 6

020

040

060

0

logCD

log(foregs$CD)

Freq

uenc

y

0.0 1.0 2.0 3.0

050

100

150

logCR

log(foregs$CR)

Freq

uenc

y

0 2 4 6 8

010

020

030

040

0logCU

log(foregs$CU)

Freq

uenc

y

0 1 2 3 4 5 6

010

020

030

040

0

logHG

log(foregs$HG)

Freq

uenc

y

0.0 0.4 0.8 1.2

05

1015

logNI

log(foregs$NI)

Freq

uenc

y

0 2 4 6 8

010

020

030

0

logPB

log(foregs$PB)

Freq

uenc

y

2 4 6 8

010

020

030

040

0

logZN

log(foregs$ZN)

Freq

uenc

y

1 2 3 4 5 6 7 8

010

020

030

040

0

TAS

foregs$TAS

Freq

uenc

y

-13 -11 -9 -8

020

040

060

0

TCD

foregs$TCD

Freq

uenc

y

-18 -16 -14 -12

020

040

060

0

TCR

foregs$TCR

Freq

uenc

y

-14 -12 -10 -8 -6

020

040

060

0

TCU

foregs$TCU

Freq

uenc

y

-14 -12 -10 -8

020

040

060

0

THG

foregs$THG

Freq

uenc

y

-20 -18 -16 -14 -12

020

040

060

0

TNI

foregs$TNIFr

eque

ncy

-14 -12 -10 -8 -6

020

040

060

0

TPB

foregs$TPB

Freq

uenc

y

-12 -10 -8 -6

020

040

060

0

TZN

foregs$TZN

Freq

uenc

y

-12 -10 -8 -6

020

040

060

080

0

JRC Ispra - IES8

FOREGS soil database: Exploratory analysis

TAS

foregs$TAS

Freq

uenc

y

-13 -11 -9 -8

020

040

060

0

TCD

foregs$TCD

Freq

uenc

y

-18 -16 -14 -12

020

040

060

0

TCR

foregs$TCR

Freq

uenc

y-14 -12 -10 -8 -6

020

040

060

0

TCU

foregs$TCU

Freq

uenc

y

-14 -12 -10 -8

020

040

060

0

THG

foregs$THG

Freq

uenc

y

-20 -18 -16 -14 -12

020

040

060

0

TNI

foregs$TNI

Freq

uenc

y

-14 -12 -10 -8 -6

020

040

060

0

TPB

foregs$TPB

Freq

uenc

y

-12 -10 -8 -6

020

040

060

0

TZN

foregs$TZN

Freq

uenc

y

-12 -10 -8 -6

020

040

060

080

0

TAS = ln(ASstand/1-ASstand)

ASstand= (AS-ASmin)/(ASmax-ASmin)

JRC Ispra - IES9

-0.10 -0.05 0.00 0.05 0.10-0

.10

-0.0

50.

000.

050.

10

Principal Component Analysis

PC1

PC

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-30 -20 -10 0 10 20 30

-30

-20

-10

010

2030

TASTCD

TCR

TCU

THG

TNI

TPB

TZN

FOREGS soil database: Exploratory analysis

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

Principal Component Analysis

PC1

PC

2

1234567891011121314

1516171819

202122232526272829303135363738394041424445464748495051525354555657

58

59

60616263646566676869

707172

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83848586

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888990919293949596979899100101102104 105106107108109111112113114 115116118119120121122 123124125126128129130131132133134135136137138139140141

142143

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257258259260261262263264265266267269270271272274275276277278279280281284286287289291292293294295296297298299

300301302303304305306307308309310311312313314315316317318319320321322323 324325326327328329330331333334335336337338339

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343344345346347348349350351352353354355356357358360362363364365366367368369370373375376377378379380381382383384385386387388389390391392393394396397398399400

401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434

435436437438439440441

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514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557

558

559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624

625

626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691692693694695696697698699700701702703705706707709710712713714715716717718719720721722723724725726727728729730731732733734735736737738739740741742743744745746747748749750751752753754755756757758759

760761762763764765766767768769770 771772773774775776777778

779780781782783784785786787788 789790791792793794795796797798799800801802803804805806807808809810811812813814815816817818819820822823824825826827828829

830

831832833834835836837838839840841842843844845846847848849850851852853854855856857858859860861862863864865866867868869870871872873874875876877878879880881882883884885886887888889890891892893894895896897898899900901902903904905906907908909910911912913914915916917918919920921922923924925926927928929930931932933934935936937938939940941942943944945946947948949950951952953954955956957958959

9609619629639649659669679689699709719729739749759769779789799809819829839849859869879889899909919929939949959979989991000100110021003100410051006100710081009101010111012 10131014101510161017101810191020102110221023102410251026102710281029103010311032103310341035103610371038103910401041104210431044

1045104610471048104910501051105210531054105510561057105810591060106110621063106410651066106710681069107010711072107310741075107610771078107910801081108210831084108510861087108810901091109210931094109510961097109810991100110111021103110411051106110711081109111011111112111311141115111611171118111911201121112211231124112511261127112811291130113111321133113411351136113711381139114011411142114311441145114611471148114911501151115211531154115611571158115911601161116211631164

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-40 -20 0 20

-40

-20

020

ASCD

CR

CU

HG

NI

PBZN

JRC Ispra - IES10

Regression-kriging

Multiple Linear Regression

Yj = a1 X1 + a2X2 + … + an Xn + εj

Soil variable j residuals j

Kriging

Yj

...

... ..... ...

.

. .. ..

..

∑ aiXii

.

..

...

. .... .. ..

γεj

distance (m)

Sem

i-var

ianc

e

(interpolation process according to spatial autocorrelations of the variable)

Auxiliary data i

Spatially continuous Punctual

Summation of the two maps

regression

kriging

regression-kriging

auxiliary data

residuals

soil variables

JRC Ispra - IES11

Predictors

JRC Ispra - IES12

Principal Component Analysis

PCA of the auxiliary variables

JRC Ispra - IES13

Multiple Regression Analysis

PCA of the auxiliary variables

JRC Ispra - IES14

Regression-kriging

Multiple Linear Regression

Yj = a1 X1 + a2X2 + … + an Xn + εj

Soil variable j residuals j

Kriging

Yj

...

... ..... ...

.

. .. ..

..

∑ aiXii

.

..

...

. .... .. ..

γεj

distance (m)

Sem

i-var

ianc

e

(interpolation process according to spatial autocorrelations of the variable)

Auxiliary data i

Spatially continuous Punctual

Summation of the two maps

regression

kriging

regression-kriging

auxiliary data

residuals

soil variables

JRC Ispra - IES15

Spatial dependency:Semivariograms

JRC Ispra - IES16

Results

JRC Ispra - IES17

Results #1 Pb

JRC Ispra - IES18

Results of RK and OK

JRC Ispra - IES19

Results #2 Ni

JRC Ispra - IES20

Correlations for Ni

3DPlot of Ni content over PC2, PC4 & PC14

JRC Ispra - IES21

Results #3 Cd

JRC Ispra - IES22

Overall concentration of HM in European soils

(1) Liege (Arrondissement) (BE), Attiki (GR), Darlington (UK), Coventry (UK), Sunderland (UK), Kozani (GR), Grevena (GR), Hartlepool & Stockton (UK), Huy (BE), Aachen (DE) (As, Cd, Cu, Hg and Pb)

(2) central Greece and Liguria region in Italy (Cr and Ni).

JRC Ispra - IES23

Estimation errors

JRC Ispra - IES24

Validation

• Comparison OK vs RK

• Moderate good: Ni, Pb• Medium: As, Cd, Hg• Poor: Cr, Cu, Zn

JRC Ispra - IES25

Conclusions• FOREGS is an examplary pan-european

dataset that is well-suited for geostatistical analysis.

• In many cases, spatial distribution of HMCs is closely connected with relief, urbanization, vegetation cover.

• All variables also show distinct spatial autocorrelation.

JRC Ispra - IES26

Conclusions

• As far as we have more detailed auxiliary maps, more accurate results are expected from these models.– Additional data (other existing soil

samples, field data description)– Accurate GIS datasets (geological map of

Europe)

JRC Ispra - IES27

Thanks for your attention

JRC Ispra - IES28

Maps of Heavy Metals: Situation at present

Soil Organic Carbon derived from PTR using soil type, land use and temperature as covariates.

Soil dataMaps of Heavy Metals: Situation at present Correlations for NiMaps of Heavy Metals: Situation at present