Implementation of Hasse Diagram technique in environmental ...€¦ · Hasse Diagram technique in...

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Implementation ofHasse Diagram technique

in environmental risk assessment

Stefan Tsakovski

Group of Chemometrics and Environmetrics,Chair of Analytical Chemistry, Faculty of Chemistry and Pharmacy,

University of Sofia “St. Kl. Okhridski”

Benefits of HDT usage

• The results obtained could be used for environmental management with respect to the future monitoring and remediation activities:

Pollutant (quality indicator) prioritization;

Optimization of monitoring scheme: chains, HDT “branches”.

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

S. Tsakovski, A. Astel and V. Simeonov. Assessment of the water quality of a river catchment by

chemometric expertise. J. Chemomet., 24 (11-12), 2010, 694-702.

Ts. Voyslavov, S. Tsakovski and V. Simeonov. Surface Water Quality Assessment using Self-

organizing Maps and Hasse Diagram Technique. Chemom. Intel. Lab. Syst., 118, 2012, 280-

286.

Backstage work

“Proper” set of indicators;

Creation of equivalence classes;

Introducing of expert and/or legislation information.

Rank index environmental authorities

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Environmental monitoring

“Not everything that can be counted counts, and not everything that counts can be counted.“(oft attributed to Albert Einstein)

corollary for environmental monitoring

Not everything that can be measured is worth measuring, and not everything worth measuring

is measurable.

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Environmental monitoring data

• Much more than 6 variables (K);

• Observations: sampling points, sampling situations, objects etc. (N);

• Most of the phenomena are characterized by 2 to 6 factors;

• Source apportioning – receptor modeling.

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Pre-treatment procedure for

Hasse diagram technique is searching for!!!

MULTIVARIATE ANALYSIS

• Using all variables (K) and experiments (N);

• No loss of substantial information;

• Revealing of “latent” factors explaining data variation;

• Detection and/or recognition of similarity groups.

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Principal Component Analysis

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Principal Component Analysis(source apportioning)

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Thurston, G.D., Spengler, J.D., 1985. A quantitative assessment of source contributions to inhalable particulate

matter pollution in metropolitan Boston. Atmospheric Environment 19 (1), 9–25

measured variable i for day k

number of sources

fraction concentration of variable i for source p

contribution mass of factor p for day k

1

ip

pk

ik

p

f

g

e error

p

ipik pk ikj

ik

x f g e

x

Multivariate curve resolution (1)

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Multivariate Curve resolution applied to Spectral Data from Multiple Runs of an Industrial

Process. R.Tauler, B.R.Kowalski and S.Fleming. Analytical Chemistry, 1993, 65, 2040-2047

Multivariate curve resolution (2)

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

WWTP data - sampling map

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Sampling…

Sampling period: august 2018

Monitored WWTPs: 22

Samples: three samples per WWTP

PO – prior to inflow (n)

ZO – after release (n+1)

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Water quality indicators

• EC – conductivity-;

• COD – chemical oxygen demand;

• TSS – total suspended solids;

• P – total phosphorous;

• N – total total nitrogen;

• Cl- – chloride;

• SO42- - sulphates.

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Sources…

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0.00

0.10

0.20

0.30

0.40

0.50

EC COD TSS P N Cl SO4

PC1

-0.90

-0.40

0.10

0.60

EC COD TSS P N Cl SO4

PC2

0.00

0.20

0.40

0.60

0.80

EC COD TSS P N Cl SO4

C1

0.00

0.20

0.40

0.60

EC COD TSS P N Cl SO4

C2

„oxygen

demand“

„conductivity“

Hasse diagram based on PCA factor scores

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wate

r qualit

y

Hasse diagram based on MCR spectra

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wate

r qualit

y

LPOM analysis

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2

3

5

6

8

9

1112

14

15

17

18

23

24

2627

29

30

3233

35

36

38

39

44

45

47

48

5051

53

54

5657

58

60

62 63

65

66

68

69

7172

0 5 10 15 20 25 30 35 40 45 50

PCA

0

5

10

15

20

25

30

35

40

45

50

MC

R

2

3

5

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8

9

1112

14

15

17

18

23

24

2627

29

30

3233

35

36

38

39

44

45

47

48

5051

53

54

5657

58

60

62 63

65

66

68

69

7172

LPOM analysis by WWTP

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𝑷𝑶 − 𝒁𝑶

2

5

8

1114

17

23

26

29

32

35

38

44

47

50

53

56

58

62

65

68

71

-20 -15 -10 -5 0 5 10 15

PCA

-30

-25

-20

-15

-10

-5

0

5

10

15

MC

R 2

5

8

1114

17

23

26

29

32

35

38

44

47

50

53

56

58

62

65

68

71

(-) quality decrease

(+) quality increase

Livestock breeding

Illegal discharge

No ZO sources

Conclusions

• PCA and MCR extract similar sources controlling surface water quality as MCR “concentration profiles” seem more appropriate concerning processes in natural waters;

• HDT based on MCR spectra gives more reliable results concerning a prior knowledge for “conflict” WWTPs ;

• MCR-HDT could be appropriate approach for estimating of WWTPs’ impact on receiving water bodies.

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Future work…

• To complete data set;

• To work by loads then concentrations;

• To estimate WWTPs’ impact based on gray water footprint;

• To have look inside HDT…

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland

Acknowledgments

• H2020-TWINN-2015 - project “Materials Networking”, Project ID: 692146

• NSF DN 19/15 (20.12.2017) – “Environmental impact assessment of WWTP on receiving water bodies”

12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland