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.
12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland
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…
12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland
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
12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland
wate
r qualit
y
Hasse diagram based on MCR spectra
12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland
wate
r qualit
y
LPOM analysis
12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland
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
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
LPOM analysis by WWTP
12th ICPOAS 26-27 October 2018, Neuchatel, Switzerland
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