Environmental Applications of Chemometrics

35
Environmental Applications of Chemometrics Pentti Minkkinen Lappeenranta University of Technology e-mail: [email protected] WSC2, Barnaul, March 2003

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WSC2, Barnaul, March 2003. Environmental Applications of Chemometrics. Pentti Minkkinen Lappeenranta University of Technology. e-mail: [email protected]. General. - PowerPoint PPT Presentation

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Page 1: Environmental Applications of Chemometrics

Environmental Applications of Chemometrics

Pentti MinkkinenLappeenranta University of Technology

e-mail: [email protected]

WSC2, Barnaul, March 2003

Page 2: Environmental Applications of Chemometrics

General

• Many environmental data sets (problems) are a challenge to a data analyst: multivariate, long time series, missing values, new analytical methods adopted

• Needs: Data compression, visualization, modeling • Problem types: classification, process modeling,

monitoring and detection of trends , new information from old data

• Standard chemometric methods, PCA, PLS and DPLS can be used for many different problems

Page 3: Environmental Applications of Chemometrics

Contents

• Dependence of emission of diesel engine on its running speed and load

• Effect of exposure to vanadium dust in industrial environment

• Effects of industrial effluents in the recipient lake

• Multivariate study on urban aerosol samples• Periodicities of the surface level fluctuation

of two large Finnish lakes

Page 4: Environmental Applications of Chemometrics

Emissions of a Diesel Engine

RUN SO4 NO3 ORG OCO elC PAH TOT

A100 11.77 4.16 20.44 24.53 33.87 0.040 73.34

A50 4.63 2.48 37.23 44.67 25.88 0.027 77.65

A25 2.34 2.88 48.05 57.66 24.58 0.036 87.45

Mean 6.247 3.173 35.24 42.87 28.11 0.043 79.48

Stand. dev. 4.92 0.88 13.91 16.7 5.03 0.0067 7.23

B100 5.39 1.83 20.38 24.46 51.52 0.026 83.21

B50 4.09 1.75 24.06 28.87 47.30 0.024 82.04

B25 1.71 1.64 41.58 49.89 35.16 0.036 88.39

Mean 3.73 1.74 28.67 34.41 44.66 0.287 84.55

Stand. dev. 1.87 0.095 11.32 13.59 8.49 0.064 3.38

A=1600 rpm; B =2600 rpm Ji Ping Shi et al. Environ.Sci & Techn. 34 (No. 5,2000) 748-755

Page 5: Environmental Applications of Chemometrics

Covariance and correlation matrices of X

SO4 12.97 2.70 -30.34 -36.40 3.65 0.007 -18.42NO3 2.67 0.93 -1.54 -1.85 -5.14 0.004 -3.71ORG -30.34 -1.54 141.68 169.99 -97.92 0.02 42.33OCO -36.40 -1.85 169.99 203.96 -117.49 0.03 50.80elC 3.65 -5.14 -97.92 -117.49 121.15 -0.04 2.81PAH 0.007 0.004 0.02 0.03 -0.04 0.000 -0.001TOT -18.42 -3.71 42.33 50.80 2.81 -0.002 33.18

cov(X) =

SO4 NO3 ORG OCO elC PAH TOT

SO4 1.00 0.78 -0.71 -0.71 0.09 0.31 -0.89NO3 0.78 1.00 -0.13 -0.13 -0.49 0.67 -0.67ORG -0.71 -0.13 1.00 1.00 -0.75 0.30 0.62OCO -0.71 -0.13 1.00 1.00 -0.75 0.30 0.62elC 0.09 -0.49 -0.75 -0.75 1.00 -0.54 0.04PAH 0.31 0.67 0.30 0.30 -0.54 1.00 -0.04TOT -0.89 -0.67 0.62 0.62 0.04 -0.04 1.00

corcoef(X)=

Page 6: Environmental Applications of Chemometrics

Diesel: Variables OAT

100 50 25 100 50 250

50

100

150

200

250

1600 rpm 2600 rpm

tot

PAHelC

oco

orgC

NO3

SO4

Page 7: Environmental Applications of Chemometrics

Two at a time

0 5 10 150

2

4

6

A100

A50 A25 B100B50 B25

NO

3

0 5 10 1520

30

40

50

A100

A50

A25

B100B50

B25

org

0 5 10 1520

40

60

A100

A50

A25

B100B50

B25

oco

0 5 10 1520

40

60

A100

A50 A25

B100B50

B25 elC

0 5 10 150.02

0.03

0.04 A100

A50

A25

B100B50

B25

SO4

PA

H

0 5 10 1570

80

90

A100

A50

A25

B100B50

B25

SO4

tot

Page 8: Environmental Applications of Chemometrics

1 2 3 4 520

30

40

50

A100

A50

A25

B100B50

B25 o

rg

1 2 3 4 520

40

60

A100

A50

A25

B100B50

B25

oco

1 2 3 4 520

40

60

A100

A50 A25

B100B50

B25 elC

1 2 3 4 50.02

0.03

0.04 A100

A50

A25

B100B50

B25

NO3

PA

H

1 2 3 4 570

80

90

A100

A50

A25

B100B50

B25

NO3

tot

Page 9: Environmental Applications of Chemometrics

20 30 40 5020

30

40

50

60

A100

A50

A25

B100B50

B25

org

oco

20 30 40 5020

30

40

50

60

A100

A50 A25

B100B50

B25

org

elC

20 30 40 500.02

0.025

0.03

0.035

0.04 A100

A50

A25

B100B50

B25

org

PA

H

20 30 40 5070

75

80

85

90

A100

A50

A25

B100B50

B25

org

tot

Page 10: Environmental Applications of Chemometrics

20 30 40 50 6020

30

40

50

60

A100

A50 A25

B100B50

B25

oco

elC

20 30 40 50 600.02

0.025

0.03

0.035

0.04 A100

A50

A25

B100B50

B25

oco

PA

H

20 30 40 50 6070

75

80

85

90

A100

A50

A25

B100B50

B25

oco

tot

Page 11: Environmental Applications of Chemometrics

20 30 40 50 600.02

0.025

0.03

0.035

0.04 A100

A50

A25

B100B50

B25

elC

PA

H

20 30 40 50 6070

75

80

85

90

A100

A50

A25

B100B50

B25

elC

tot

0.02 0.025 0.03 0.035 0.0470

75

80

85

90

A100

A50

A25

B100B50

B25

PAH

tot

Page 12: Environmental Applications of Chemometrics

PCA: X=T P’, A=3

2.80 -2.12 0.39 -0.35 -0.48 -1.40 -2.25 -1.29 0.15 1.12 1.89 0.34 0.63 1.81 -0.24 -1.95 0.19 0.76

T=

0.47 0.24 -0.49 -0.49 0.24 -0.04 -0.43-0.26 -0.53 -0.21 -0.21 0.50 -0.51 0.22 0.06 0.01 -0.12 -0.12 0.43 0.71 0.53

P’=

52.8 90.7 99.0

R2 =

Object scores Variable loadings

Index of determination

Page 13: Environmental Applications of Chemometrics

-3 -2 -1 0 1 2 3-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

A100

A50

A25

B100B50

B25

T1 (52.8 %)

T2

(90.

7 %

)

SO4

-0.5-0.4-0.3-0.2-0.1 0 0.1 0.2 0.3 0.4 0.5-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

NO3

orgoco

elC

PAH

tot

P1 (52.8 %)P

2 (9

0.7

%)

Scores and loadings: PC1 vs. PC2

Page 14: Environmental Applications of Chemometrics

Biplot of scores and loadings

-3 -2 -1 0 1 2 3-3

-2

-1

0

1

2

3

A100

A50

A25

B100B50

B25

SO4

NO3

orgoco

elC

PAH

tot

T1, P1 (52.8 %)

T2,

P2

(90.

7 %

)

Page 15: Environmental Applications of Chemometrics

-3-2

-10

12

3

-3-2

-10

12

-1.5

-1

-0.5

0

0.5

1

A100

A50

B100

B50

A25

B25

T2

T3

T1

3-D graph of the scores (99 % variance explained)

Page 16: Environmental Applications of Chemometrics

Can we make a predictive model?

1600 1001600 501600 252600 1002600 502600 25

Y=

Given X (emissions) can we predict Y (engine speed and load)?

Inverse calibration problem for PLS

Page 17: Environmental Applications of Chemometrics

PLSPartial Least Squares or Projection to Latent Structure

ui

ti

Xx1 xk

x1

t iX

x2

x3

Yy1 yn

y2

Y

y1

ui

y3

??

X = TP’ +E Y = UQ’ +F

U = T d + G

bpls = W (P' W)-1 Q'

Page 18: Environmental Applications of Chemometrics

PLS results between autoscaled LOG(X) and autoscaled Y

Percent Variance Captured by PLS Model -----X-Block----- -----Y-Block----- LV # This LV Total This LV Total ---- ------- ------- ------- ------- 1 54.15 54.15 43.21 43.21 2 35.23 89.38 45.29 88.50 3 9.03 98.41 3.89 92.39

Page 19: Environmental Applications of Chemometrics

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

SO4

NO3

orgoco

elC

PAH

tot

W1, Q1

W2,

Q2

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

SO4

NO3

orgoco

elC

PAH

tot

rev

Load

W1, Q1

W2,

Q2

Diesel, PLS model

Biplot of PLS loading weights (W) and Y variable loadings

Page 20: Environmental Applications of Chemometrics

1 2 3 4 5 6 7-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

SO4 NO3 org oco

elC PAH tot

1 2 3 4 5 6 7-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

SO4 NO3 org oco

elC PAH tot

1 2 3 4 5 6 7-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

SO4 NO3

org oco

elC PAH

tot

1 2 3 4 5 6 7-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

SO4 NO3

org oco

elC PAH

tot

Regression coefficients from PLS

ENGINEREVOLUTIONS

ENGINELOAD

Page 21: Environmental Applications of Chemometrics

PR

ED

ICT

ED

RE

V1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600

1400

1800

2200

2600

2800

A100A50

A25

MEASUDERED REV

1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 26001400

1800

2200

2600

2800

A100A50

A25

B100

B50 B25

Diesel: PLS prediction

100100

PR

ED

ICT

ED

LO

AD

20 30 40 50 60 70 80 9020

30

40

50

60

70

80

90

100

110

A50

A25

B50

B25

Diesel: PLS

MEASURED LOAD

20 30 40 50 60 70 80 9020

30

40

50

60

70

80

90

100

110A100

A50

A25

B100

B50

B25

Diesel: PLS prediction

Page 22: Environmental Applications of Chemometrics

Clinical effects of exposure to vanadium dust

26 clinical variables on blood serum measured on two matched groups: Test group (18 persons exposed to vanadium dust in V2O5 factory and control group (17 persons not exposed to vanadium dust)

Data measured by Lauri Pyy et al.

Page 23: Environmental Applications of Chemometrics

0 2 4 6 8 10 120

5

10

15

20

25

30

GlucAlb Cl K Na CreaUreaUratCa PI Bil B-cfAfosAlatAsatLD CholTrigFe gCT IGE IGA IGG IGM BSP Prot

Var

iab

le N

o.

Scaled concentrations

Exposure to vanadium - comparison by variables OAT

Page 24: Environmental Applications of Chemometrics

-5 0 5-5

-4

-3

-2

-1

0

1

2

3

4

5

VV

V

V

V

VV

V

V

V

V

V

V

V

VV

V

VCC

C

C

C

CC

C

C

C

CCC

C

C

C

C

T1 (17.5 %)

T2

(29.

9 %

)

PCA SCORE PLOT

Page 25: Environmental Applications of Chemometrics

x11 x12 … … x1k

x21 x22 … … x2k

… … … …

… … … …

xi1 xi2 … … xik

xi+1,1 xi+1,2 … … x1+1,k

… … …

… … …

xn1 xn2 xnk

1 0

1 0

1 0

1 0

1 0

0 1

0 1

0 1

0 1

0 1

DESCRIPTOR MATRIX X

DUMMY MATRIX Y

PLSCLASS 1

CLASS 2

Construction of the dummy or indicator matrix for DPLS (PLS discriminant analysis) which is used to find the projections of X space that discriminate best the classes of the training set.

Page 26: Environmental Applications of Chemometrics

-5 -4 -3 -2 -1 0 1 2 3 4-3

-2

-1

0

1

2

3

V

VV

V

V

VV

VV

V

V

V

V

V

V

VV

V

CC

C

C

C

C

CC

C

CC

C

C

C

C

C

C

T1

T2

D-PLS SCORE PLOT

Percent Variance Captured by PLS Model -----X-Block----- -----Y-Block----- LV # This LV Total This LV Total ----- -------- ------- ------- ------- 1 11.8 11.9 76.2 76.2 2 5.6 17.4 13.3 89.5

Page 27: Environmental Applications of Chemometrics

-4 -3 -2 -1 0 1 2 3-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

V

V

VV

V

V

V

VV

V

V

V

V

V

V

V

V

V

Gluc

Alb

Cl

K

Na

Crea

Urea

Urat

Ca

PI

Bil

B-cf

Afos

Alat

AsatLD

CholTrig

Fe

gCT

IGE

IGA

IGG

IGM

BSP

Prot

CC

C

C

C

C

CC

C

C

C

C

C

C

C

C

C

T1, W1

T2,

W2

BIPLOT OF THE D-PLS MODEL

Page 28: Environmental Applications of Chemometrics

Effect of Industrial Effluents on Trace Element Patterns of Aquatic Plants

Field work: Jukka SärkkäAnalyses: Inkeri Yliruokanen

Page 29: Environmental Applications of Chemometrics

Study Area in Lake Päijänne: Aquatic plants (3 species of Nympheids) collected in two summers, follow up in Site 1. Samples were analysedfor Ash % and 13 minor and trace elements.

1 = Jyväsjärvi: Industrial and municipal effluents, follow-up after remedial measures

4 = Tehinselkä: Clean Area

3 = Judinsalonselkä: Intermediate zone

2 = Tiirinselkä: heavily polluted

by industrial effluents

Page 30: Environmental Applications of Chemometrics

Species/ Location

Ash %

V µ/g

Mn µ/g

Fe µ/g

Cu µ/g

Zn µ/g

Rb µ/g

Sr µ/g

Ba µ/g

Y µ/g

La µ/g

Ce µ/g

Pr µ/g

Pb µ/g

A1 12.3 2.4 1200 2800 24 59 24 120 160 2.0 3.0 6.0 1.0 8.6

A2 12.9 7.7 1600 2200 20 110 28 77 130 1.8 3.8 5.1 0.4 5.1

A2 18.9 30.0 1600 5300 56 140 40 94 190 7.5 13 34 1.5 9.4

A3 9.5 1.0 290 360 9.5 66 19 87 95 1.1 1.5 1.9 0.2 1.3

A3 7.2 0.7 250 280 3.6 57 14 86 36 0.2 0.5 0.7 0 1.4

A4 9.0 0.9 650 1100 5.4 36 16 99 27 0.4 0.6 0.9 0.1 0.9

A4 7.5 3.0 540 970 6.0 22 15 97 75 0.5 3.0 3.3 0.2 3.7

B1 12.4 3.7 740 2300 12 42 32 60 93 2.4 1.2 2.4 0.2 2.4

B1 7.1 2.8 300 2000 14 30 26 36 42 1.4 2.1 2.8 0.2 3.5

B3 6.9 0.7 320 590 3.5 21 22 52 31 1.0 1.4 1.4 0.2 1.4

B3 9.7 5.8 610 1600 2.9 23 33 62 38 1.0 1.0 2.4 0.2 1.9

B4 8.1 0.8 120 340 4.1 21 30 51 36 0.6 0.6 0.4 0.1 2.4

B4 5.5 0.8 209 310 2.7 10 17 40 16 0.2 0.6 0.6 0.05 1.7

C1 13.4 2.7 250 270 20 20 53 19 180 0.3 0.1 0.3 0 21

C2 10.8 2.1 960 520 11 41 38 16 150 0.5 0.6 0.6 0.1 1.0

C2 8.4 1.1 840 400 17 45 50 15 84 0.2 0.3 0.7 0.08 1.7

C3 11.5 0.6 240 140 3.4 65 31 24 180 0.3 0.5 0.9 0.1 2.1

C3 10.1 1 300 110 3.0 40 36 23 120 0.3 0.7 0.8 0.1 0.8

C4 9.0 0.3 93 93 1.9 18 28 65 48 0.1 0.2 0.5 0 0.3

C4 8.5 0.9 140 190 2.6 12 30 29 93 0.2 0.4 0.4 0 1.4

a1 7.91 1.0 1200 240 10 27 20 79 110 0.3 1.2 1.7 0.2 1.0

a1 8.29 0.9 360 250 8.3 21 11 65 41 0.1 1.4 0.9 0.2 8.3

b1 9.17 0.9 1200 440 17 27 29 68 50 0.5 1.3 2.4 0.2 1.1

b1 6.46 1.9 340 430 6.5 9 17 34 29 0.1 1.1 1.4 0.2 1.0

c1 9.24 1.0 1200 160 5.9 19 21 13 130 0.3 1.0 1.1 0.3 1.2

c1 9.27 0.7 650 100 10 18 25 25 140 0.3 0.5 0.5 0.1 1.0

c1 9.02 0.7 330 100 4.7 14 31 12 52 0.3 0.5 0.6 0.1 1.8

SPECIES: A and a = Potamogeton natans, B and b = Polygonum amphibium, C and c = Nuphar luteum

Page 31: Environmental Applications of Chemometrics

-2 -1 0 1 2 3-1.5

-1

-0.5

0

0.5

1

A1A2

A2

A3

A3

A4

A4

B1

B1

B3

B3B4

B4

C1

C2C2C3C3

C4

C4ar

ar

br

br

crcr

cr

CLASSIFICATION ACCORDING TO SPECIES

T1 (49.1 %)

T2

(69.

5 %

)

Page 32: Environmental Applications of Chemometrics

-2 0 2 4-1

01

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

T1T2

T3

Nympheids

C4

B4

A3

A4

ar

B3brB4

A4

C4

A3ar

br

B3

crB1

C3

C3

crcr

A1

B1

C2

A2

C2C1

A2

SAMPLE SCORES

-0.2 0 0.2 0.4 0.6-1

-0.50

0.5

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Fe

CeLa

Sr

Y

Pr

V

P1

Pb

MnCu

Zn

Nympheids

A%

Rb

Ba

P2P

3

VARIABLE LOADINGS

Page 33: Environmental Applications of Chemometrics

B3

C3

br

cr

A3

C2C2

A2 A2

B3

C3

arbr

cr

T1 (65.3 %)

-3 -2 -1 0 1 2 3 4-2

-1.5

-1

-0.5

0

0.5

1

1.5

A1

A4

A4

B1B1B4

B4

C1

C4

C4

A3

arcr

EFFECT OF REMEDIAL MEASURES ON JYVÄSJÄRVI (Sites 1 and r)

T2

(85.

5 %

)

EFFECT OF REMEDIAL MEASURES ON JYVÄSJÄRVI (Site 1 and 1r):DPLS model with Site 1 and Site 4 objects, other objects fitted to this model

Page 34: Environmental Applications of Chemometrics

-1 -0.5 0 0.5 1-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

A1

A4A4

B1B1

B4

B4

C1

C4

C4

T1

T2

-1 -0.5 0 0.5 1-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

A2

A3

A3

B3

B3

C2C2

C3

C3

ararbr

br

crcr

EFFECT OF REMEDIAL MEASURES ON JYVÄSJÄRVI (Site 1 and 1r):DPLS model with Site 1 and Site 4 objects, other objects fitted to this model (different scaling from previous figure – information still the same)

Page 35: Environmental Applications of Chemometrics

THANK YOU

Спасибо