models and methods for assessment of interactions in a city-region system
DESCRIPTION
MODELS AND METHODS for assessment of interactions in a city-region system. Penenko Vladimir Tsvetova Elena. Interdisiplinary project of SD RAS “Ecological problems of Siberian cites”. Modeling aspects. 1. Assessment of mutual risks and unintended pollutants - PowerPoint PPT PresentationTRANSCRIPT
MODELS AND METHODS
for assessment of interactions in a city-region system
Penenko VladimirTsvetova Elena
1. Assessment of mutual risks and unintended pollutants exchange between the cities of the Siberian Federal District.2. Observability studies for monitoring system situatedin the Siberian cites ( SibAeroNet). Connection with risk domains (jointly with Institute of atmospheric optics SD RAS)3. Tracing of long-distance transport of biological aerosols. Combination of Eulerian and Lagrangean approaches, forward and inverse modeling ( jointly with Federal Center «Vector» and IOA SD RAS)4. Revealing of peculiarities of mesoclimates in Siberian cities ( Novosibirsk as an example)5. Atmospheric chemistry ( jointly with the Institute of chemical kinetics and combustion SD RAS)
Interdisiplinary project of SD RAS
“Ecological problems of Siberian cites”
Modeling aspects
ModelsHydrodynamics and transport of pollutants:• global scale• regional scale• meso and city scale.
Atmospheric chemistry:• methane & sulfur & nitrogen cycle• + acetaldehyde cycle
Data assimilation system
M a t h e m a t i c a l m o d e l f o r g e n e r a l o u t l o o ka n d c r e a t i o n o f a l g o r i t h m c o n s t r u c t i o n
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Risk functions
Fragment of scenario
Risk functions
Risk functions
Risk functions
Risk functions
Assessment of informativityof the monitoring system “SibAeroNet” with the help of numerical modeling
TomskToryMondyUssuriiskYakutskEkaterinburgKhanti-MansiiskUlan-UdeKrasnoyarsk
1
11
1
2
3
4
5
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Ekaterinburg
1
1
1
2
2
3457
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Yakutsk
1
1
1
2
2
3
3
45
7
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Khanti-Mansiisk
1
11
2
2
3
3
4
66
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Krasnoyarsk
1
1
2
23
3
4
5
67
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Mondy
1
1
1
3
23
3
3
4
5
6
7
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Tomsk
1
1
1
2 23
4 6
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Tori
1
1
2
2
3
4
76
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Ulan-Ude1
1
1
2
2
3
3
4
45
9 18 0.57 0.16 0.055 0.014 0.0053 0.0012 0.00051 0.0001
Ussuriisk
1
1
1
1
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34
5
6
7 16 0.55 0.14 0.053 0.012 0.0051 0.001
Joint estimation of observability domains and informativity measures for monotoring system
AeroSibNet
Period of 1-14 June 2002
1 1
21
1
2
3
2
2
2
3
2
3
3 3
4
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4
4
5
5
6
6
6
7
7
8
89
10 109 98 87 76 65 54 43 32 21 1
1
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2
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10 109 98 87 76 65 54 43 32 21 1
Assessment of AeroSibNet informativity for revealingpotentially dangerous sources of pollutants
Significance level > 0.001
Significance level > 0.0001
Conclusion: AeroSibNet system in the combination with inverse modeling setcan be used for revealing the sources of specific pollutants
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5
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7
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Analysis of receptor-source interaction
Risk function for Novosibirsk regiondemonstrates the domainof potentially dangerouspollutant sources
Receptor near Novosibirsk
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10009008007006005004003002001000
F
10009008007006005004003002001000
pressure, mb
Backward trajectories, 31.05-1.05.2002
Receptor coordinates 54.23 N, 82.09 E, 850 mb , 31.05.2002, 08.00 GMT
NovosibirskAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
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10009008007006005004003002001000
F
10009008007006005004003002001000
pressure, mb
Backward trajectories, 31.05-1.05.2002
Receptor coordinates 54.23 N, 82.09 E, 700 mb , 31.05.2002, 08.00 GMT
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10009008007006005004003002001000
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FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF 10009008007006005004003002001000
F
10009008007006005004003002001000
pressure, mb
Backward trajectories, 31.05-1.05.2002
Receptor coordinates 54.23 N, 82.09 E, 400 mb , 31.05.2002, 08.00 GMT
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9008007006005004003002001000
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10009008007006005004003002001000
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10009008007006005004003002001000
F10009008007006005004003002001000
pressure, mb
Backward trajectories, 31.05-1.05.2002
Receptor coordinates 54.23 N, 82.09 E, 500 mb , 31.05.2002, 08.00 GMT
Tracingof long-distance transport
of biological aerosols
Mathematical modeling of atmospheric circulation and transport of pollutantsin the Novosibirsk region
x
y
0 50 1000
10
20
30
40
50
60
70
80
90
100
57
The Novosibirsk industrial region
Temperatureand circulation
x
y
0 50 1000
10
20
30
40
50
60
70
80
90
100
178
The Novosibirsk industrial region
Conclusion
The theoretical background and some elements of computational technology are developedfor studies of interaction in the region-city systemin direct and feedback regimes.
The construction of modeling tools are based on the variational principles in the combination with splitting technique and sensitivity theory
