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1

Traffic Model System and Emission Calculations of the Helsinki Metropolitan Area Council

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General information about the area

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Location of Helsinki in Europe

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Definitions of areal divisions

YTV area includes the cities of Helsinki, Espoo, Vantaa and Kauniainen.

Surrounding areas include eight municipalities around the YTV area.

Helsinki region = YTV area + surrounding area = 12 municipalities

Metropolitan area is used to describe an area contained within approximately a 100 kilometre radius from Helsinki. It consists of 72 municipalities.

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Tampere

Mikkeli

LahtiHämeenlinna

Tammisaari

Kotka

Hämeenlinna

Lahti

Kotka

YTVTammisaari

PKS

47,000 commutersin 1980

88,000 commutersin 1990

108,000 commutersin 2002

YTV

Turku

YTV

Proportion of commuters in the municipality’s work force

Over 35 %10 - 35 % 2 - 10 %

Commuting in the Helsinki Metropolitan Area 1980–2002

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Population Jobs 31.12.2004 31.12.2003 in YTV area

HelsinkiEspoo

Kauniainen

Vantaa

559 000

369 000

227 400

104 000

8 500 2 700

185 40095 000

980 300

0

200000

400000

600000

800000

570 700

Population and the number of jobs in the YTV Area

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YTV area target network in 2030

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Journeys made daily by public transport and by car within the YTV area

Journeys (1000/day)

66

53

42 39 39

0

25

50

75

100

1966 1976 1988 1995 2000 2005

Share taken by public transport (%)

(38)

0

500

1 000

1 500

1966 1976 1988 2000 2005

Private car

Public transport

1995

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Traffic model system

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Traffic model system

Traffic is divided into three parts• internal trips made by the

inhabitants of the region• trips generated by Helsinki-

Vantaa airport (air passengers and employees)

• external trips (cars only)• freight transport (vans and

lorries)

•Modes• walk, bicycle• public transit• car (as driver or passenger)

Trip categories• home-based work trips• home-based school trips• other home-based trips• non-home-based trips

•Time periods• morning peak hour• average hour of the day• evening peak hour

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Traffic model system

Tools• Emme/2 macros (contain Unix file handling commands)• SAS programs (preparation of input, writing some macros)• FORTRAN programs (summary of results)• Unix scripts (renaming output files)

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Feedback in the four-step model system

internal trips airport trips

trip generation trip generation

destination choice destination choice external trips

mode choice mode choicecommercial trips

total demand and route choice

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Model types

trip category trip generation mode choice destination choice

home-based work trips

trips / person working

logit model logit model

home-based school trips

trips / person of school age

distance table (distribution)

logit model

other home-based trips

trips / inhabitant logit model logit model

non-home-based trips

trips / inhabitant logit model logit model

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Logit model and logsum

probability of alternative i

.

1

J

j

V

V

ij

i

e

eP

logsum = ln (

J

j

V je1

)

where

where,2211 niniii xxxV

k. ealternativin variableof value=x

n),1,2,=(j variableoft coefficien

ealternativ offunction benefit

jk j

jj

i

x

x

iV

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Variables used in models

•Mode choice models• nr of transfers, transit• travel time, transit or car• travel cost, transit or car• parking place availability

(arriving trips / parking place)• parking cost• cars/household• ln(distance), walk or bicycle• distance 0-5 km, walk or bicycle• distance 5-10 km, walk or

bicycle• dummy variables

•Destination choice models• logsum of mode choice• scale factor (inhabitants, jobs)• ln(jobs)• dummy variables

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Mode combinations possible

Influence of the number of modes (ms149, ms199, ms249, ms299)

on text registers and description fields of matrices

(e.g. ”morning peak %t2% work trips”)

text register 3 4 -4 5

t1 Walk+bicycle Walk+bicycle Walk Walk

t2 transit Bus+tram transit Bus+tram

t3 Car Car Car Car

t4 NO BIKE NO BIKE bicycle bicycle

t5 NO RAIL Heavy rail NO RAIL Heavy rail

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Principles applied in coding macros

• The same selection of possible variables in all models (except school trips)

• No constants in the model formulas but the coefficients of the models are in scalars

• Systematics in matrix numbers• If a variable is not in the model, its coefficient is zero• Only the number of the first input matrix is given as a macro

parameter, other consecutive numbers are calculated (e.g. nr of transfers in matrix %2%, transit time in matrix r2=%2%+1)

• Logical scalars (school trip models in macro school_%ms250%.mac, where ms250=96 or ms250=2001)

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Scalars containing the coefficients

model variables coefficientshome-based other home- non-home- work trips based trips based trips

destination logsum ms106 ms156 ms206destination scale factor ms107 ms157 ms207destination ln(jobs) ms108 ms158 ms208mode dummy, walk ms110 ms160 ms210mode dummy, bus+tram ms111 ms161 ms211mode dummy, car ms112 ms162 ms212mode travel cost, heavy rail ms115 ms165 ms215mode travel cost, bus+tram ms116 ms166 ms216mode travel cost, car ms117 ms167 ms217mode parking ratio ms118 ms168 ms218mode parking cost ms119 ms169 ms219

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Writing an Emme/2 macro with a SAS program

Why?

Do you want to copy and paste this section 24 times and edit the parts which are underlined?

Solution: Give the changing part as data cards and write the rest of the macro with a SAS program (or with some programming language).

1 y ms311 y wt24h home-based work trips~?q=1 y

mf301

y gn01,gn04

o

+ +~?b=1 2

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Essential parts of the SAS programfilename outfi2 'K:\Emme2\summary_matr_demo2.mac';

data matr;length mxnro msnro $ 5 name $ 6 descr $ 40;input mxnro $ 4-8 msnro $ 10-14 name $ 16-21 descr $ 23-62 ;cards; mo09 ms301 nrinha total nr of inhabitants mf301 ms311 wt24h home-based work trips 24h ms999 last line ;

data _null_;

set matr;

file outfi2;

if _N_ = 1 then do; put "~#" / "~#** calculate sums of vectors" / " 3.21" ;end;

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Essential parts of the SAS program

nro = substr(msnro,3,3);if (nro ne '999') then do; put "~# *** matrix " _N_ " *** " ; put " 1" / " y" / msnro $ 2-6 / " y" / name $ 2-7 / descr $ 2-41 / "~?q=1" / " y" // mxnro $ 2-6 /// " y" ; if (substr(mxnro,1,2) = 'mo') then put " gn01,gn04" // " +" ; else if nro in ('311') then put " gn01,gn04" // " o" // " +" / " +" ; put "~?b=1" / " 2" ;end;

if nro = '999' then do;

put " q" / "~#** output the list of scalars" /

" reports=summary_matr_demo.txt" /

" 3.14" / " 2" / " ms" / "~?b=1" / " 2" / " q" /

" reports=%1%" / "~/ *** summary_matr_demo.mac ***" ;

end;run;

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Estimation of models

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Traffic surveys

Internal trips• trips made by the inhabitants of the YTV area (four cities)

during one day (24 h) in autumn 2000• personal trip diary interview, 8,666 persons and 28,553 trips

Trips generated by Helsinki-Vantaa airport• 875 air passengers and 801 employees (flying and non-flying)• survey made in autumn 2001

External trips and freight transport• origin-destination study made in autumn 1988

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Model estimation

Internal trips• estimation made by Ms Nina Karasmaa (Helsinki University of

Technology, Transportation Engineering)• Alogit program• More than 50 model sets were estimated and tested• Differences e.g. in number of modes and model hierarchy

(mode choice after destination choice or vice versa)• Three modes in the model set selected.

Trips generated by Helsinki-Vantaa airport• estimation made by Mr Jyrki Rinta-Piirto (Strafica Ltd)

External trips and freight transport• models estimated in 1990 are based in changes in land use.

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Emission calculations

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”Minor” problem in emission calculations

• Traffic models produce demand matrices for three weekday hours.

• Finnish Meteorological Institute needs emissions for every hour of the year for dispersion calculations.

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Principle of emission calculations

auto demand matrices (car+van, lorry) transit demand matrices* morning peak * morning peak* average hour of the day * average hour of the day* evening peak

transit assignment (speed, @voltr)regression models * two hours

auto demand matrices emissions of bus links* 10 weekday hours (fuel, CO2, SO2, CO, NOx, PM, HC)* 7 Saturday hours and rail links (@energy, CO2, NOx, PM)* 7 Sunday hours * morning peak

* average hour of the dayauto assignment (speed, volau, volad)* 10+7+7 hours regression models

emissions of auto links and centroids emissions of bus and rail links(fuel, CO2, SO2, CO, NOx, PM, HC) (CO2, SO2, CO, NOx, PM, HC)* 10 weekday hours * 24 weekday hours* 7 Saturday hours * 24 Saturday hours* 7 Sunday hours * 24 Sunday hours

copying or interpolation

emissions of other hours* 14 weekday hours* 17 Saturday hours* 17 Sunday hours

total emissions

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Emission calculations

Tools• Emme/2 macros (contain Unix file handling commands)• FORTRAN programs (copying or interpolation from link data

of 10+7+7 hours to 14+17+17 hours and summary of results)• Unix scripts (dialog of FORTRAN run, renaming output files)

Emission factors• fuel consumption, CO2, SO2, NOx, particles (PM), CO, HC• polynomial functions of average speed (from assignment)

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Examples of emission factors:NOx emissions of cars and vans

0

0,2

0,4

0,6

0,8

1

1,2

1,4

10 20 30 40 50 60 70 80 90 100 110 120

average speed (km/h)

em

iss

ion

(g

/km

/ve

h)

car kat 2005

car diesel 2005

van diesel 2000

car kat 2030

car&van diesel 2025

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Examples of emission factors:NOx emissions of trucks and buses

0

2

4

6

8

10

12

14

16

10 20 30 40 50 60 70 80 90 100

average speed (km/h)

em

iss

ion

(g

/km

/ve

h)

trailer truck 2000 (EU 2)

single-unit truck 2000 (EU 2)

bus 2000 (EU 2)

trailer truck 2025 (EU 5)

single-unit truck 2025 (EU 5)

bus 2025 (EU 5)

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Examples of emission factors:CO2 emissions of cars and vans

0

50

100

150

200

250

300

350

10 20 30 40 50 60 70 80 90 100 110 120

average speed (km/h)

em

iss

ion

(g

/km

/ve

h)

car kat 2000

car diesel 2005

van diesel 2000

car kat 2025

car diesel 2030

van diesel 2025

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Examples of emission factors:CO2 emissions of trucks and buses

0

500

1000

1500

2000

2500

10 20 30 40 50 60 70 80 90 100

average speed (km/h)

em

iss

ion

(g

/km

/ve

h)

trailer truck 2000&2025

single-unit truck 2000&2025

bus 2000&2025

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Proportions of vehicle types in emission calculations (volau)

4) emission factors for average petrol car in 2000 (43 % non-kat, 52 % EU0-2, 5 % EU3, 0 % EU4-5)5) emission factors for average petrol car in 2025 ( 0 % non-kat, 0 % EU0-2, 25 % EU3, 75 % EU4-5)

percentage2005 2030 in scalar

cars and vans cars, non-kat 0 0 ms80 cars, kat-1995 80 4) 0 ms81 cars, kat-2020 - 85 5) ms82 cars, diesel 1995 10 0 ms83 cars, diesel 2020 - 5 ms84 vans, diesel 1995 10 0 ms69 vans, diesel 2020 - 10 ms85total 100 100

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Proportions of vehicle types in emission calculations (volad and bus)

percentage2005 2030 in scalar

trucks single-unit trucks EU 0-2 70 5 ms86 trailer combination trucks EU 0-2 30 2 ms87 single-unit trucks EU 4-5 - 65 ms88 trailer combination trucks EU 4-5 - 28 ms89total 100 100

buses LPG or CNG buses buses in Helsinki EU 0-2 100 0 ms81 regional buses EU 0-2 100 0 ms83 buses in Helsinki EU 4-5 - 100 ms82 regional buses EU 4-5 - 100 ms84

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Regression models in emission calculations

• The regression models have been estimated using volume counts on four cordon lines.

• For auto assignment, the volumes (car+van and truck) for each hour of the day (10+7+7) are used as regressands and three forecasted hours (morning peak, evening peak and an average hour of the day) as regressors of the model. The models are used for calculating the demand matrices for each hour.

• For transit assignment, the bus volumes for each hour of the day (3*24) are used as regressands and two forecasted hours (morning peak and an average hour of the day) as regressors of the model. The models are used for calculating the link volumes and emissions for each hour.

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Emission calculations

• emission on regular link [kg/h] = volume [veh/h] * length [km] * emission [g/km/veh] / 1000

• cold starts (three classes of motor temperature) and emissions of connector links handled as emissions of the area (in the centroid)

• example of copying and interpolation of the emission (from 10+7+7 hours to 14+17+17 hours)

hour hour weekday emission 4am- 5am 4- 5 EMIS_WD_23_5 5am- 6am 5- 6 EMIS_WD_23_5 6am- 7am 6- 7 (EMIS_WD_23_5 + EMIS_WD_7)/2. 7am- 8am 7- 8 EMIS_WD_7 8am- 9am 8- 9 EMIS_WD_8 9am-10am 9-10 EMIS_WD_9_1310am-11am 10-11 EMIS_WD_9_13

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Principle of emission calculations (repeated)

auto demand matrices (car+van, lorry) transit demand matrices* morning peak * morning peak* average hour of the day * average hour of the day* evening peak

transit assignment (speed, @voltr)regression models * two hours

auto demand matrices emissions of bus links* 10 weekday hours (fuel, CO2, SO2, CO, NOx, PM, HC)* 7 Saturday hours and rail links (@energy, CO2, NOx, PM)* 7 Sunday hours * morning peak

* average hour of the dayauto assignment (speed, volau, volad)* 10+7+7 hours regression models

emissions of auto links and centroids emissions of bus and rail links(fuel, CO2, SO2, CO, NOx, PM, HC) (CO2, SO2, CO, NOx, PM, HC)* 10 weekday hours * 24 weekday hours* 7 Saturday hours * 24 Saturday hours* 7 Sunday hours * 24 Sunday hours

copying or interpolation

emissions of other hours* 14 weekday hours* 17 Saturday hours* 17 Sunday hours

total emissions

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Thank you for your patience and interest!

Any questions?