Energy and Environment Laboratory, RCE Curitiba Parana, Brazil
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Coordinator: Prof. Marcelo Risso Errera, Ph.D. UFPR – Federal University of Paraná Telefone: +55(41) 3361-3230 / 3030 E-mail: [email protected] Energy and Environment Laboratory Member of CRIE (RCE-Curitiba) Curitiba, Oct. 19, 2016
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Transcript of Energy and Environment Laboratory, RCE Curitiba Parana, Brazil
Coordinator: Prof. Marcelo Risso Errera, Ph.D.
UFPR – Federal University of ParanáTelefone: +55(41) 3361-3230 / 3030 E-mail: [email protected]
Energy and Environment Laboratory
Member of CRIE (RCE-Curitiba)
Curitiba, Oct. 19, 2016
100 yearsUFPR – Federal University of Paraná
(historic building downtown Curitiba)
100 years33.000 students and 2.500 faculty members
Curitiba and its sustainability initiatives
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1st 3rd Curitba
http://grist.org/article/cities3/
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Theory to assess the contributions of zero emission vehicles (ZEV) in
paradigm shift in urban fleets: the effect of the effect of urban fleet size on automotive vehicles
emissions
Errera, Marin and Stanescu
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We love cars.
We love cars
Do Zero Emission Vehicles
(electric, hydrogen) contribute do
urban emissions ?
(in paradigm shift of urban fleets:
the effect of the effect of urban fleet size on automotive
vehicles emissions)
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Errera/set/09 28
Summary
Problem statement (factors) Urban mobility (needs, desires, choice criteria, ....) Modes (types, mass or individual transit) Infra-structure (city form, traffic management) Air quality conditions (emissions and dispersion)
Model types for traffic simulation First simulators (Lighthill and Whitman, 1955) Deterministic, statistic and automatons
Validation, calibration and limitations Usual traffic parameters Field data
The problem
The matter of urban fleet emissions Factors that determine the emissions What is needed to control (stabilize or reduce)
Vehicles emissions Lab tests, summed emissions, scale, technology,
vehicle use, fuel, driving skills, traffic management
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Purpose of the Model
Purpose: To develop a model to estimate vehicle emissions
associated to traffic conditions (mainly fleet size) Model type:
Macroscopic, deterministic and empirical, saturated traffic, speed dependent emissions, unchanging infra-estructure
Adapted data
The model
Fleet size (N ) Mean speed (v
)
Emission Factors (FE )
Fleet composition ( ) and average yearly mileage (x)
Total anual emissions (Et )
traffic data
Lab tests
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Present model (traffic)
k=N
route extension=
NL
Fundamental relations (Smit, R., 2006):
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v = -0,0277(k) + 30,725R 2 = 0,9703
0
5
10
15
20
25
30
0 100 200 300 400 500
k ( v e h i c l e s / k m )
V m
e a
n ( k
m /
h )
After data from CET, 2007
Estimative based on field data (traffic engineering company of The City of São Paulo) (L≈18 thousand km):
Curitiba (L = 4381km, IPPUC)
Present model (traffic)
Present model (emissions)
Average speed varies solely with traffic conditions
Fuel burning pollutants (CO, NOx, HC, pm) Category (diesel and gasoline) Grouped by category and fuels Engine @ hot regime Stop-go traffic not detailed
Lab tests Chassi dinamometer
Gasoline vehicles (passenger cars)
CETESB / IPEA, 1998
Diesels vehicles (bus and trucks)
Present model (emissions)
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Present model (emissions)
Total yearly emissions [ton poll / year]
Pollutant, k; category j, period (year) i Mean Yearly Traveled distance, xj Category (j) fleet size nj EFj average speed and pollutant dependent
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Goal: To estimate fleet size effect on the overall yearly emissions [ton pollt / year]
Scenario: Curitiba Registered fleet Average mileage Average speed profile adapted from São Paulo vfree = 40 km/h
CO e NOx emissions Parametric variation
respect to fleet size
After DETRAN ref. 1996-2005
Grouped categories
Composition (aj ) typical, %
Year mileage, xj , km/yr
Automobiles 82,84 12.000
Bus + Trucks 17,16 80.000
Others 0,0 -
Total 100,00 -
Data input
Errera/set/09 40
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
0,0 0,5 1,0 1,5 2,0 2,5 3,0fleet size, Ni in vehicles [ millions ]
ETa
,CO
, E
Ta,
NO
x [
ton
/ yea
r ]
CO
____ with congestion effects - - - - without congestion effects
NOx
Variation of the overall yearly emissions according to fleet expasion
Traffic saturation effects
results
Errera/set/09
0
500
1000
1500
2000
2500
3000
3500
4000
0,0 0,5 1,0 1,5 2,0 2,5 3,0fleet size, Ni in vehicles [ millions ]
dE
Ta,k
/ dN
[ to
n / 1
000
veh.
]
CO
____ with congestion effects - - - - without congestion effects
NOx
results
Emissions variation rate with fleet size
Traffic saturation effect
Marginal emissions
Equivalent to emissions caused by ZEVs in the fleet
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Conclusion
The model captured marginal pollution phenomena and provided estimates under simplified conditions
Marginal pollution would be present even for ZEVs That is ZEVs create traffic that in turn creates marginal emissions
from other conventional fuel cars Validation, calibration for each city is needed
Mais sobre CT & CL• http://www.scoop.it/t/constructal-design
Agradecimentos
Marcelo Risso ErreraEnergy and Environment Lab / GEANEXEnvironmental Engineering Department – UFPRUniversidade Federal do Paraná
