emission factors, non-regulated pollutants air pollution …€¦ · use of emission models within...

1 26/09/2014

Emission factors, Non-regulated pollutants

Air pollution assessment methodologies

- works in link with ERMES Issues:

Non-regulated pollutants,

Guidance on and benchmarking of models

ERMES

Graz, 17 September 2014 Yao LIU, Michel ANDRÉ

Transports and Environment Laboratory

2 26/09/2014

A high concern, due to health and environment impacts with

emerging technologies and fuels

Different topics were suggested in ERMES

1. Identify key non-regulated pollutants with evolution of vehicle

technologies

2. Collect literature and data into a database of emission factors

3. Literature review on current sampling and analysis methods for

each family of compounds (PAH, VOC, Aldehyde…)

4. Design a test program on 30-40 diesel and gasoline vehicles (more

or less recent Euro 2-6), with several partner laboratories (JRC,

EMPA, LAT…), to measure emissions data around the key NRP

5. Data synthesis and elaboration of emission factors

ERMES – Non-regulated-pollutants issue

3 26/09/2014

1. Identify key NR pollutants with evolution of vehicle technologies

2. Collect literature and data into a database of emission factors

3. Literature review on current sampling and analysis methods

A literature review and laboratory experiments enabled identification of non-regulated pollutants BTEX: Benzene, Toluene, Ethylbenzene, Xylenes

PAH: Naphtalene, Phenanthrene, Fluoranthene, Pyrene, Benzo(a) antracene, Chrysene, Benzo(b+j) fluorenthene, Benzo(a) pyrene

Carbonyl compounds: formaldehyde, acetaldehyde, acetone, benzaldehyde,

black carbon (BC)

NO2, NH3….

A short report in French on PAH, VOC and black carbon EF A synthesis could be written in English, if needed

Sampling and analysis methods reported by Pillot (2006) to be completed / updated


Preliminary works by IFSTTAR (Ademe funding)

4 26/09/2014

0

0.1

0.2

0.3

Emis

sio

n f

acto

rs (

mg

/km

) Tenax

TA/Carb (70/30)

TA/Carb (85/15)

Air Toxic

4. Design a test program …, to measure key NRP

Sampling definition (2014):

4 BTEX cartridge-types tested with Euro 4 gasoline vehicle

– Tenax, Tenax/Carboxen 1000 with 70/30% or 85/15% and Air Toxic

Tenax:

best sampling and

efficiency

for all BTEX



5 26/09/2014


Sampling flow and system optimisation (2014), for

BTEX, PAH, Carbonyl compounds, black carbon and

particle number

Different sampling conditions tested with high polluting (Euro 4

diesel), and low polluting vehicles (Euro 5 diesel with DPF and Euro

5 gasoline with direct injection system)

Suitable sampling systems designed,

Detailed results : a report in French, possible synthesis in English



6 26/09/2014


Emission factors measurements on 3 vehicles

Detailed results : a report available in French, possible synthesis

Data



Vehicle Cycle NRP Regulated

Compounds

Date and

Lab

Euro 4:

- Diesel

Euro 5:

- Diesel DPF

- Gasoline (DI)

Artemis:

Urban

Motorway

PAH, BTEX,

Carbonyl

compounds,

NO2, BC

HC, NOx, CO,

CO2, NMHC,

Particle number

May -

June

2014

IFSTTAR

7 26/09/2014

Emission factors measurements

6-8 cars to be tested by IFSTTAR (2014-16)


Future works (Ademe, French Research Agency funding)

Vehicle Cycle NRP Regulated

compounds

Date

Euro 5:

Diesel DPF (additive filter)

Diesel DPF (catalysed filter)

Gasoline

Euro 4:

Diesel DPF (additive filter)

Diesel DPF (catalysed filter)

Gasoline

Artemis:

Urban

Road

Motorway

PAH, BTEX,

Carbonyl

compounds,

NO2, BC

HC, NOx,

CO, CO2,

NMHC,

Particle

mass and

number

Oct 2014

– Mars

2015

Euro 6

Diesel DPF

Gasoline 2016

8 26/09/2014

To complete the review

More vehicles for larger samples, by other labs?

A cooperative process is needed

Data synthesis and elaboration of emission factors

for their taking into account in the emissions models


to go further …

9 26/09/2014

Four phases were proposed in ERMES

1. Emission models : accuracy, validity, review, inter-

comparisons.

2. Data and assumptions for emission estimation

Fleet and traffic data, prospective scenario, etc. and their variability

Sensitivity of the emissions calculation.

3. Use of emission models within larger chains of models.

Assumptions and interfaces.

Validity of the coupling with micro or macro traffic models.

4. Practices for the assessment of the air pollution from

transports

Lessons from applications, real-world practices, benefits from the

implementation of transport / traffic measures

5. Expected results : a better knowledge of the contexts,

recommendation around the assessment approaches.

ERMES issue: Guidance on and benchmarking of

models, uncertainty, test cases

10 26/09/2014

Different Case studies :

City of Nantes and urban area

Eval-PDU project, funding by the French Research Agency (ANR)

simulated hourly traffic

Grenoble ring,

MOCOPO res. proj., funding by Dept of Sust. Dev.

Traffic and fleet, and air quality monitoring

Paris area - Assessment of Low Emission Zones (ZaParC, Ademe)

Fleet monitoring in different places, trafic and emission simulation over the whole Île-de-France

An urban district in Villeurbanne (CoerT-P, Dept of Sust. Dev.)

Micro and macro traffic simulation

An urban district in Paris area (Trafipollu, French ANR)

Heavy experiment including air and water quality, traffic and fleet monitoring; macro and micro simulation


models - IFSTTAR preliminary works

11 26/09/2014

Different Case studies : City of Nantes and area (Eval-PDU)

Hourly traffic

(DAVISUM travel and traffic modelling - 4 steps static approach)

2002 and 2008 reference situations as well as different scenarios

Urban mobility plan implementation (actual status)

+20% of mobility ; -25% passenger cars ; +30 and +50% public

transport

Busway implementation: high service bus lines along a main road

Voluntary urban mobility plan

Speed limits (90 -> 70 km/h on ring / motorway, 30 km/h in city centre)

Fleet renewal scenarios

Emission calculation using 2 plate-forms derived from COPERT4

Analysis of the whole chain of models (from travel to air quality),

assumptions and data, assessment practices

Development of a Health impact indicator



12 26/09/2014

City of Nantes and urban area - a few results

A review of emission models

Different implementations of the same COPERT4 methodology can induce strong differences for certain pollutant estimation 20 to 40% for PM, Cd, Benzene, CO, while others are within 1%

Due to different interpretation, updates, etc.

Weaknesses of the overall approach Due to its principles and data, the Static Traffic model addresses

weakly the congestion (hourly step), the speed level (overestimated), the heavy vehicles, the spatial and temporal distribution of the traffic

Cold start and evaporative emission : difficult to distribute spatially

Insufficient taking into account of local specificities (fleet, driving and use conditions)



13 26/09/2014

City of Nantes and urban area - a few results

Sensitivity to Vehicle fleet is high

A 2-years fleet evolution induces a difference of the pollutant estimation by 15 to 27% of most pollutants (except CO2, N2O, PAH)

– a 4-years fleet evolution induces differences by 30 to 45%

Low differences in Car Diesel rate (by 2%) and of recent cars (by 1%) induce variations of the estimations (CO by 26%, COV by 9%)

However the taking-into account of local fleet specificities is difficult :

– Lack of data

– NGV Bus (Natural Gas Veh) which are predominant cannot be computed

City-centre, peak-hour, passenger cars (which are the focus of most public actions) do not represent the main of the emission quantities

Heavy duty vehicles - although poorly assessed - are significant (8% of the traffic, but 25% CO2, 18% PM, 42% NOx)

Cold start (CO, VOC, …), and Non-Exhaust emissions (PM) are highly significant



14 26/09/2014

Different Case studies

Grenoble ring, (MOCOPO):

A frequently congested sector

Traffic monitoring (6 minutes counting and speeds)

Air quality monitoring (near the road and urban background)

Fleet composition monitoring through 4 video cameras

– Around 1,7 Million of observations during one month

– 350,000 identified French registration

Emission calculation by steps of 6 min, using the COPCETE plate-

form derived from COPERT4

Coupling with Dispersion / deposition models was also realised



15 26/09/2014

Grenoble ring, (MOCOPO research project) - a few results

Local fleet

Significant differences with national estimation (less Diesel and

recent cars)

Strong variability week / week-end (HGV, LCV traffics)

Lighter variations between peak (older cars, less Diesel) and off-

peak hours

Important temporal variability (6 minutes steps)

See influence on emissions

Congestion

5-8% of the time, 9-15% of the traffic

But only 13 to 20% of the total emissions

Limited influence on the emissions as speeds are rarely very low

(under 40 km/h) and emission vary few over 40-90 km/h



16 26/09/2014

Grenoble ring, (MOCOPO research project) - a few results

Incidence of the fleet variability on the emissions Current observed variations of HGV, LCV traffic rate induce

emissions variations by 30 to 70% (CO2, NOx, PM)

Car Diesel rate variations influence the overall CO, COV by 10%

Current observed variations in the EURO distribution of cars induce quite limited variations of the overall emission (4 to 5%)

Time resolution Emissions were computed at 6, 15 min and 1 hour time-resolutions

When estimations are aggregated over long periods (1 day, 1 week) or when estimations concern stable periods as regards traffic, the time resolution does not induce significant influence (1-2%)

When estimations are focused on congested periods or when traffic is varying (from free-flow to congestion), 15min and 1h resolutions underestimates emissions by 4 to 14%



17 26/09/2014

Different Case studies

In the Paris area - Assessment of Low Emission Zones

Large scale measurements of air quality, black carbon

Tunnel experiment to assess traffic emissions

Vehicle fleet monitoring; 9 places ; around 500,000 observations,

Detailed technological data identified through the National

registration file

Analysis of the spatial vriability of the fleet composition

– from a large-scale mobility survey (15,000 households in Île-de-France)

– From the in-situ video monitoring

Île de France area: traffic simulation (morning peak hour)

20,200 km of road, 37,700 road segments

Analysis of the sensitivity of the emission calculation

Emission calculation using COPERT4 methodology



18 26/09/2014

Paris area and Low emissions zones - Results

Significant fleet variability according to territories

“Well-off” territories have a younger car fleet, with less Diesel and

would be also less affected by selective driving restriction measures

High interest of mobility surveys to apprehend differences in car

buying and renewal behaviours according to the areas

Results confirmed by the video observations

Cars Diesel rate : from 57 to 70% according to areas

Cars Euro 4+5 rate : from 58 to 44%

Induced differences in the overall emission estimations:

7% CO2, 13% PM, 35% CO et COV, 30% NOx



20 26/09/2014

Case study : An urban district of Villeurbanne (near Lyon, France)

110 permanent traffic counting

points and 70 directional counting

at junctions

37 junctions monitored by video

and survey

Macroscopic traffic model

SIMBAD tool, static approach

Lyon area and focus on the district

Dynamic traffic simulation

AIMSUN tool

District area, input from the SIMBAD

Emission simulation using COPERT4, HBEFA emission

factors, and PHEM model


models - IFSTTAR works in progress

21 26/09/2014

Application of HBEFA and PHEM to the above case studies

Inter-comparison of tools at different spatial - temporal scales

Sensitivity studies : A simulation plan is already drafted input data; local versus national data

temporal / spatial aggregation

Real-world versus simulated speeds

Parameters specific to the different emission calculation tools

Synthesis

Other European application cases

Integration of emission models within chains of models State-of-the-art, review, synthesis (a PhD at IFSTTAR)

Methodologies for assessing air pollution from transport and measures to limit it (PhD at IFSTTAR)


models - to go further

22 26/09/2014

Currently, a strong concern around the 2 ERMES issues

Non-regulated pollutants and emissions factors

Guidance on and benchmarking of models

Other topics of interest

Fleet and traffic data (update of HBEFA with French data)

Ultrafine particles emission and evolution in atmosphere

Black carbon characterization from chassis dyno and in-situ

measurements (tunnel, urban and rural), summer and winter

High-Emitters

Their detection on the road, and number assessment

Dedicated emission factors

Their taking into account in fleet-model and emission models

Conclusions

emission factors, non-regulated pollutants air pollution …€¦ · use of emission models within...

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