Transcript Climate change and Urban Vulnerability in Africa

Climate change and Urban
Vulnerability in Africa
Modeling Activity within T21 Framework
Freising 2012
4/25/2012
Eric S. Traore & Hamidou Toure
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Modeling Activity within T21 Framework
Contents
• Questions
• What is System Dynamics Modeling
• What is T21
• Institutional anchorage of T21 in Burkina Faso
• Stakeholders involved in the development of T21
• Sectors to be dealt with, in relation to Climate Change
• Activity Schedule
• A proposal as mitigation action
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Questions
• Is it relevant to deal with vulnerability assesment in T21 ?
• What information from other tasks could be used ?
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Slide 3
What is System Dynamics Modeling
• Complex systems
A set of factors interacting with many feed-back loops
Causal diagram for the market of a given product (source : Michel KARSKY)
• SDM aims to catch the structure of such complex systems and
their behaviour through the time
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Slide 4
Causal diagram # cognitive or conceptual map
This is not a causal diagram in the acceptation of SDM :
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Slide 5
Modeling process
•
•
•
•
Causal analysis
Model bulding
Formalizing and quantification
Simulation, calibration and validation
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Slide 6
What is T21
• An Integrated Socio-economic-environmental Modeling and
Planning Tool based on System Dynamics
The highlights:
1. Good representation of
complexity
2. Multidisciplinary
3. Transparency - Usability
4. Flexibility
5. Powerful designing software:
Vensim
Source : Millenium Institute
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Slide 7
What is T21
Source : Millenium Institute
Multi-sector integrated model promoted by The Millenium Institute and ECOWAS
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Slide 8
What is T21
Example : T21 for Mali
downloadable from the web site of Millenium Institute
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Slide 9
Institutional anchorage of T21
Ministère de
l’Environnement et du
Développement Durable
SP/CONEDD : Secrétariat
Permanent du Comité
National pour l’Environnement
et le Développement Durable
PANA-BF : National Action
Plan for Adaptation in BF
Ministère de l’Économie et
des Finances
Millenium
Institute
Experts
T21
SP/CNPE : Secrétariat
Permanent du Comité National
de la Politique Économique
ECOWAS ( Economic
Community of West African
states ) T21 Project
ECOWAS
Team
CLUVA
Team
– CLUVA Team of UO will also act as a capacity building resource for PANA
– It has been obtained a free participation of CLUVA Team of Saint – Louis at all
workshops organised by AAP (African Adaptation Program) in Ouagadougou
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Slide 10
Stakeholders involved
• Accredited representatives of :
– Direction de la Météorologie
– Secrétariat Permanent du Conseil National pour l’Environnement et le
Développement Durable (SP/CONEDD)
– Secrétariat Permanent du Commission Nationale de Politique Economique
(SP/CNPE)
– Ministère de l’Agriculture et de l’Hydraulique
– Ministère de l’Economie et des Finances
– Ministère des Infrastructures
– Ministère de l’Habitat et de l’Urbanisme
– Ministère de la Santé
– Ministère des ressources animales
– Ministère de la Recherche Scientifique et de l’Innovation
– Ministère des Mines, des Carrières et de l’Energie
– Ministère de l’Environnement et du Développement Durable
– Millenium Institute & African Adaptation Programme Coordination /Dakar
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Slide 11
Sectors we shall be interested in
• Water resources
• Forestry
• Agriculture
• Health
• Energy
• Human habitat and infrastructures
• Natural disasters
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Slide 12
Activity Schedule
• Strategy
– Improve modeling skills step by step with applications to multi-sector
modeling and integration.
– Collaborate with involved stakeholders to model vulnerability and CC
adaptation issues and integrate them to T21.
• What is already done or going on
Period
Action
Oct – Nov
2011
Creation of a site on a Moodle Learning Management System dedicated to
collaborative work between CLUVA modelers
Jan-Feb
2012
Discussions and agreement with PANA coordination and SP/CNPE for
collaboration in model building with integration to T21
1-2 and 6 of
March 2012
A 3 days introductory workshop for all partners on :
- basics of System Dynamics,
- introduction to Stock-Flow diagrams and Vensim software
- examining the structure and simulation results of the T21 model for Mali,
downloaded from Millenium Institute web site
March 2012
Setting up an agreement with Millenium Institute for a 7 months work plan
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Slide 13
Activity Schedule
Period
Action
26 March to 7
April 2012
- Distance learning : same topics as for the 3 days workshop in
March. The goal is to bring up CLUVA modelers to a suitable level of
skills so that they can attend the Millenium Institute’s first
workshop on 10-11 April, and discuss further issues with them.
10 – 11 April
2012
-Kick-off in Ouagadougou with Millenium Institute, ECOWAS Team,
CLUVA Teams and sectors’ representatives
- Choice of sectors to be modelled by CLUVA
15 – 30 April
2012
-Distance collaboration on modeling a Bayesian Network in T21
- Participation in Munich Workshop on Vulnerability of eco-systems
and discussion about the ways to model it.
1st May – 15
June 2012
- Training : advanced modeling Techniques with Vensim.
- Case study: Building causal diagrams for sectors related to CC
- Writing a first report on progress
16 June – 31 July - Collecting the data we need to build equations that link the
2012
factors in causal diagrams
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Slide 14
Activity Schedule
• Further Actions from September 2012
Duration
Action
2 months
- Modeling the choosen sectors
- Integrating CC adaptation costs and profits
- Report on progress
2 months
- Running simulations and analising results
- Formulating multisetorial strategies for CC adaptation
- Report multisectorial analisis of vulnerability to CC
• Long term activity
1 month
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- Validation of results
- Final report
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Slide 15
A First Causal Diagram
depenses de
secours
+
offre energie non
renouvelable
offre energie
renouvellable
deforestation +
+
inondation
offre energie
+
foyer de maladies
contagieuses animales
duree de pluie
+
+
+
Vent
pluie annuelle
- secheresse
demande d
energie
+
--
+
-
+ transpiration
repartition de pluie pendant
la periode de croissance
vegetale
+
+
demande d eau
agricole
+
biodiversite
+
+
medicine traditionelle
+
offre d eau pertinent
pour l agriculture
-
+
produits forestiers
non ligneux
+
+
attractivite de tourisme
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densite de
population
+
total population
-
-
paturage
+
zone d
habitation
migration
rurale-urbaine
desertification
- indice de stress
hydrique
+
+
- esperance
de vie
+
maladie
hydrique
+
-
+ PIB
terre arable
effectivite d
+
elevage
production
d
+
elevage
- viande d anim
+
rendement d +
aux sauvages
+
production agricole
elevage
totale
+
+demande d eau
production
+
+
agricole
totale
population par
+
region
+
rendement
+
indice de stress hydrique
agricole
+ productivite totale des
facteurs agricole
- malnutrition
-
mortalite de la
faune
+ evaporation
poussiere
+
+
-
+
-
-
+
maladies de voies
respiratoires et occulaires
erosion
offre d eau
foret
-
+
-
+
+
Temperature
- infrastructure
- productivite totale
des facteurs
+
intensite de pluie
-
vulnerabilite d
habitat
production d energie
de bois
+
Eric S. Traore & Hamidou Toure
production des
services
Slide 16
A proposal as mitigation action
Design and experiment of a low
energy consumption cooling system
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Slide 17
Introduction
Global warming has several consequences, among which:
 increased need to air-condition buildings and houses, thus
increasing electricity bills : in 2009 in Burkina, 15 billion CFA for
public buildings, of which 60% to 75% for air-conditioning alone, not
to mention the negative impact on the environment;
abrupt temperature variations suffered by users, harmful to their
health;
 management of peak consumption periods made difficult for
electricity companies .
An ΔT reduction ( in general ranging from 10°C to 15°C ) in ambient
temperature through air-conditioning, requires a quantity W of
energy proportional to ΔT.
Hence, any process capable of reducing ΔT to1°C or2°C could induce
considerable savings. That’s the goal of this study.
Definition of an acceptable thermal comfort
Surveys with users allowed to determine according to humidity rate
and the ambient air temperature, a thermal comfort zone (Figure 1)
Air-conditioning and thermal comfort
0,03
50%
0,025
80%
Très chaud
et humide
Chaud et
humide
0,02
0,015
20%
Zone de
confort
Tempéré
0,01
Très chaud
et sec
0,005
Chaud et sec
0
10
15
20
25
30
35
40
45
50
Fig.1 : thermal comfort zone according to temperature and humidity rate
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Temperature below the ground
Fig. 2 : Compared evolution of underground and surface temperatures
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The cost-effective air-conditioning system
The cost-effective air-conditioning system that we propose will
combine four processes :
 Controlled mechanical ventilation (CMV) : moderate air circulation allows
to shift up the thermal comfort zone for a few degrees to high temperatures
(typically 30°C).
 The « compressor-free A/C or humidificator: allows to considerably lower
( below 20°C) the temperature of a hot and dry air by drawing from it the
heat necessary for the evaporation of the water used to humidify that air.
 Canadian wells : experiences conducted in Ouagadougou have showed
that at about 1.8 m below ground, , temperature oscillates very weakly
around de 31°C, in phase opposition with large amplitudes observed at
surface.( Figure 2)
 The classical compressor A/C, equipped with compressor powered
through an electronic speed variator: it will be turned on to reach the
thermal comfort zone only in case previous processes have failed to do so.
Thus, for very hot periods where air conditioning use is usually intense and
costly,
a judicious combination of these
processes allows to do
without air
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conditioners equipped with compressors
The automatic regulator’s technology
The regulator is in charge of bringing to and maintaining at a
determined point of the thermal comfort zone by judiciously
implementing the processes mentioned previously. To do so, it uses entry
information vector : temperature, humidity rate, wind speed and possibly
other parameters.
Diagram of the model’s principle
Diagram of the physicam installations
r
E
Internal
thermometer
Fuzzification
External
thermometer
Hygrometer
Rules
Inference
engine
Evaluation of
rules
Defuzzification
Fuzzy system
r
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Intelligent electronic box
A/C
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Compressor-free
A/C
VMC
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Fuzzy controler
1
COLD
COOL
WARM
VERY HOT
HOT
°C
0
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10
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4
3
2
1
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If x=A1 and y=B1
So z=C1
x
Fuzzification
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29
30
31
32
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34
35
36
37
38
w1
If x=A2 and y=B2
So z=C2
w2

Defuzzification
y
wn
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If x=An and y=Bn
So z=Cn
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z
Work steps
• Dynamic multi-sector model including CC adaptation issues to
establish the relevance of developping the system
– Assesment of energy and money savings due to such a system in relation with
renewable energy development costs
– Assesment of gains related to gaz emissions, labour offer, wellfare in rural
areas
– Etc.
• Design of a fuzzy controler for comfort point tracing
– Software in a chip card
– Card reader device with monitoring ability
• Experimental installation
–
–
–
–
–
–
–
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House
Canadian well
Fan
Humidifier
Fuzzy controler prototype
Remote sensors
Zigbee connexion devices
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Expected gains








subtantial energy savings
reduce negative impact on the environment;
easier management of peak electrical energy consumption;
possibility to air-condition rural areas by using photovoltaic
cells;
ability to adapt to existing buildings;
is automatic and does not rely on users’ active behaviour;
development and adaptation, mainly carried out by software,
are easy and cheap;
Its production and installation will create new competences
and opportunities on the job market.
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Climate change and Urban Vulnerability
in Africa
Modeling Activity within T21 Framework
Thank you for attention
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