552 Air Pollution - WIT Press

The potential impacts of electric vehicles on

air quality in large urban areas. Milan case

study

M. Giugliano, S. Cernuschi, A. Cemin

D.I.I.A.R. - Environmental Section, Politecnico di Milano,

via Fratelli Gorlini, 1 20151, Milano, Italy

ABSTRACT

The methodological approach for the evaluation of the contribution of electricvehicles to the reduction in traffic related atmospheric emissions and of theresulting expected effects on air quality is illustrated. The methodology isapplied to a most probable introduction scenario of electric vehicles over thenext 20 years derived for Milan urban area, which provides for a maximum10% penetration of the circulating fleet at full regime. Results are reported forthe estimated reduction in the emissions of the main traffic related pollutantsand for the expected effects on the concentrations of CO and NO% in areference dispersion situation typical of the area of concern.

INTRODUCTION

In the metropolitan area of Milan, the continuous increase of atmosphericemissions from traffic (in the last 20 years the vehicles circulating daily in anarea of 18 x 18 km increased from 500,000 up to 1,000,000 of units), jointedwith high frequencies of calm winds and stable atmospheric conditions typicalof the Po valley, makes the air quality standards far to be respected. Moreover,in order to avoid potential health risk situations the area has already beensubject, in the framework of specific oriented regulations issued for 11 criticalItalian urban areas, to emergency interventions which also include severetraffic restriction measures.

Medium and long term intervention strategies for the area include twoimportant measures influencing traffic related emissions: the first, generalisedover the whole country, provides from 1993 for the renovation of the actualgasoline vehicle fleet with cars equipped with three-way catalytic converters,in order to comply with the last EEC (European Economic Community)

Transactions on Ecology and the Environment vol 1, © 1993 WIT Press, www.witpress.com, ISSN 1743-3541

552 Air Pollution

standards on vehicle emissions (regulation ECE 08, 1991), while the secondconcerns the completion of the regional transport system (a mix of train andunderground collective transport) which, from 1995, is expected to take up theannual predicted increase in the private vehicles fleet (roughly 10 to 15thousands units per year). The expected improvements in air and noiseenvironmental quality, following the outlined interventions, are not exclusiveof other initiatives which could also give important contributions to mitigatethe situation. In this context, the introduction of electric driven motor vehiclesappears to be a perspective of particular interest for areas with a high mobilityrequest and with the absolute necessity to avoid any further environmentaldeterioration, and is carefully evaluated and even also included in futureremediation plans (FMT*, CEC%, Boyd ).

Present work reports the expected implications on traffic emissions and onair quality obtained for the most practicable potential introduction scenario ofelectric vehicles in Milan urban area. Emissions evolution was evaluated withan appropriate model, capable of utilizing all input data related to regulatoryand infrastructural constraints, which was applied over the time periodpredicted either for the completion of the interventions already planned thanfor the penetration of the electric vehicle fleet (from 1990 to 2010). Theexpected impacts on air quality were evaluated through the simulation of theintroduction of electric vehicles, following the estimated penetration scenario,in a synthetic situation of traffic related pollution phenomena typical of thearea of concern and represented by a canyon street dispersion model.

TRAFFIC EMISSIONS EVOLUTION IN MILAN URBAN AREA

Methodology for the evaluation of emissionsThe methodology developed for the evaluation of the emissions, implementedin the personal computer model EMISMOB, considers the fundamentalelements required for the calculation of mobile source emissions: the totalnumber of vehicles circulating in the area, the mean driven distance in the timeunit considered and the emission factors for every pollutant of interest. Thecalculation is performed following a methodological approach, outlined in theflow sheet reported in Fig. 1, which disaggregates the circulating fleet inappropriate vehicle classes, defined on the basis of the different emissioncharacteristics of every combination between vehicle category and trafficregime. Vehicles are categorized, following the approach proposed in theEEC CORINAIR project on European atmospheric emissions inventory(ENEA ), in terms of engine type (gasoline and diesel), of gross vehicleweight (light, medium and heavy duty) and , for light duty vehicles, in terms oftheir age, in order to consider the progressive restrictions on the emissionstandards imposed by the EEC directives since the last 15 years (regulationsECE 15/00-08) (CONCAWE ). Traffic regimes considered are defined inaccordance with the availability of reliable relationships for the evaluation of


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emission factors in different driving conditions. Gasoline light duty vehiclesare subdivided in terms of classes of mean speed and by cold or hot conditions,where the fraction of vehicles in cold drive conditions is evaluated through theambient temperature and the mean travel length (ENEA , Joumard") or, forvehicles equipped with three-way catalytic converters (following regulationECE 15/05-07), from the estimated time required to heat the catalyst to theoptimum temperature range (300°C - 400°C). All other vehicle categories areclassified just in terms of three distinct traffic regimes (urban, extraurban,freeway) without consideration of the cold driven distance, as a consequenceof the lower detail actually available in the description of emission factors. Thelast subdivision, related to the maintenance conditions of the vehicle, is appliedonly to the light duty category, for which information on the effects of suchfactor on the emissions are available. The distribution obtained is then coupledwith the mean driven distance, typical of the area of concern for every vehiclecategory, in order to obtain the total distance travelled by each class, and theemissions are finally calculated utilizing, for every class of vehicles, thecorresponding emission factors.

Baseline data and results.Total annual traffic related emissions were evaluated for a square area 18x18km, which includes the metropolitan area of Milan and its main access routesand ring freeways. The evaluation was conducted for a base scenario and for amost probable electric vehicle introduction scenario.

Base scenario was defined (Giugliano ) with statistical data available on thecomposition by vehicle categories of the total circulating fleet in the area . Theevolution of the vehicle fleet was estimated with proper values of the annualgrowth and renewal rate, derived from the trends observed in the last few yearsand from hypothesis related to the expected effects of the plannedinfrastructural interventions. The electric scenario was generated (MIP&) byfirst evaluating the maximum potential penetration of electric driven vehiclesthrough a comparison between factors limiting their utilization and the vehicletechnology, available at present and in the projected future, in terms ofmedium and high energy density advanced batteries. From the maximumpotential penetration obtained, which results near 18% of the totalcorresponding circulating fleet at regime, an effective penetration was thenestimated by considering the market competition between electric andtraditional vehicles, in terms of factors related to costs, vehicle performanceand utilization possibilities and taking also into account the effects of differentfinancial, fiscal and regulatory incentive actions that could be undertaken topromote the market penetration of the electric vehicle: the results obtainedindicate a maximum effective penetration at regime of roughly 10% withrespect to the projected circulating fleet, corresponding to nearly 140,000electric vehicles introduced by 2010.


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I Total vehicle number I I Vehicle categories

Circulating fleet compositionby vehicle categories

Yes

1

\

% of vehicles bymean travel speed classes

iJ

% of vehicles by type of traffic regime(urban, extraurban, freeway)

%of vehicles incold drive conditions

% of vehicles in I Yespoor maintenance conditions j

J_

Distribution of circulating fleet in classeson the basis of vehicle category,

travel regime and maintenance conditions

Mean driven distancefor each vehicle category

O

Emission factorsby vehicle classes

Emissions for eachvehicle class

Figure 1. Methodology for the evaluation of traffic emissions.

Baseline values of the emissions factors utilized (Giugliano?) follow theapproach of CORINAIR methodology. For light duty gasoline vehicles, thecalculation is performed for four distinct travel speed classes typical of the areaand evaluated with an appropriate on road measurement campaign; for thecategories most recently introduced by EEC directives, the values adopted are


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the standards imposed by the corresponding regulations, constant over all thespeed range. Evaporative losses are considered in the evaluation of VOCemissions by adding a mean factor of 1.5 g km"!, also derived fromCORINAIR methodology (ENEA ). Cold drive portions of the circulatinglight duty gasoline fleet, and the corresponding corrections for emissionfactors, are derived with proper values of the annual mean temperature, meantravel length, catalyst heating time and overall efficiency during transient coldand at regime hot conditions (ENEA , Kitagawa ). For diesel vehicles andmotorcycle categories emission factors are derived from CORINAIR data forurban regime of traffic (ENEA ), with the exception of values for the latestEEC directive light duty diesel category which correspond to the standardsincluded in the regulation. Heavy duty diesel trucks circulation, mainlylocalized in the outer ring freeway of the area, has emission valuescorresponding to a freeway regime of traffic. The effect of vehiclemaintenance conditions on emission factors, although included in the model,was not considered in the evaluation due to the uncertainty still present in thecorresponding correction factors to be adopted.

Annual emissions were evaluated for the main pollutants related with traffic(CO, NOx, VOC, paniculate matter and SO2). For the base scenario, the timeprojected reductions in emission figures, with respect to the actual 1990baseline values, are reported in Fig. 2, and result essentially dependent on thecapability of the catalytic converter in containing the emissions from gasolinelight duty vehicles and on the relative contribution of the latter category to theglobal emissions budget. The highest reduction is, consequently, predicted forCO (around 70% at regime); VOC has a similar expected evolution, with asmaller reduction (about 40%) mainly attributable to the conservativeassumption related to the absence of any future control measure to limitevaporative losses. On the other hand, the evolution of NOx and particulatematter emissions results significantly different, with much lower expectedreductions (30% for particulates and not over 10% for NO%) in accordanceboth with the considerable contribution of diesel vehicles, which remainsessentially unchanged, and with the small reduction operated by the catalyticconverter, in comparison with that obtained for CO, on gasoline light dutyvehicles emissions. The particular evolution estimated for SO2 emissions,almost entirely attributable to diesel vehicles, results from the expectedenforcement by 1992 of a recently issued regulation for some critical urbanareas, including Milan, which provides for the introduction of low sulfur fuel(maximum content of 0.1 wt%, as opposed to the actual mean percentage of0.3 wt%).

The time projected reductions of annual emissions due to the substitution oftraditional vehicles with electric vehicles, within the most probableintroduction scenario previously outlined (10% of expected penetration by theyear 2010), are reported in Fig. 3. Mean values of around 12% are obtained for


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NO.voc

***** Particulate matteroeeeeso,

1992 1994 1996 1996 2000 2002 2004 2006 2006 2010Year

Figure 2. Emissions reduction for the base scenario

-10

14

12

10

CONO,vocParticulate matter

oeeeeso.

1*0*1 d62*f<&4 1996 ' 1996 2000 2002 20042006 2008 2010

14

12

10

Year

Figure 3. Emissions reduction for the electric scenario with respect to the basescenario


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all pollutants at regime, mainly attributable to the share of high CO and VOCemitters substituted by that time (8% of private light duty gasoline vehicles)and to the very effective penetration (over 60%) expected in the private andpublic company fleets utilization module for the substitution of both light andmedium duty diesel vehicles. The results should be of particular interest takingalso in appropriate consideration the significance of the emission figures,calculated as mean annual values for the whole urban area of concern, and therather limited reduction levels attainable in the base scenario for somepollutants, like NOx, even after the complete renovation of the fleet with lowemission traditional vehicles.

POTENTIAL IMPACTS ON AIR QUALITY OF ELECTRIC VEHICLES

Methodology of evaluationA quantitative estimation of the expected effects which could be carried out bythe electric vehicle to attain and maintain air quality can be obtained throughthe simulation of their introduction, following the estimated scenario ofpenetration, in synthetic situations representative of the traffic related pollutionphenomena typical of the area of concern. For the inner city district of Milan,characterized mainly by streets of limited width bordered with tall buildings,the above situation can be adequately described through the application of acanyon street dispersion model, in order to simulate the concentration of thepollutants of interest in fixed receptors located along the sides of the street.The canyon street model, widely described in the literature (Johnson 10), wasmodified in order to more precisely consider site specific factors related tolocal accumulation effects and background concentration values for thepollutants of interest, not accounted for in the generalized version of themodel. The modification applied was derived from the simulation of hourlyCO and NO% concentrations, considered as the main tracers of traffic relatedemissions, performed along a street located in the central business district ofthe city and with a geometrical configuration typical of a canyon road. Themodel was evaluated with hourly concentration data monitored by an airquality station located along the street, utilizing hourly traffic flow volume andcomposition obtained with an appropriate measurement campaign conductedduring four consecutive typical days and with hourly values of the wind speedtypical of the area and the time period considered. The empirical evaluation ofthe differences between measured and calculated values provided for theproper modification to be introduced, resulting in a correction to be applied toconcentration values C^{ estimated by the model which takes the form of twoadditional terms related, respectively, to local accumulation effects,proportional to the corrected concentration value C^rj-l estimated one hourbefore, and to the background concentration of pollutant present in the air flowentering the canyon vortex:


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The parameters k, correlated with the meteorological conditions, and €5,accounting for the background concentration, are derived from regressionanalysis between measured and calculated data. The values of Cy obtainedfrom the correction of the model for CO and NO% compare well withbackground values estimated, for comparison, by a box model extended overthe whole urban area (Hanna ), with mean daily values of the total emissions,the mixing height and the wind speed typical of the time period evaluated(Table 1): the empirical approach followed in deriving the correction shouldthen be considered fairly acceptable, and is further validated by the goodagreement displayed by the CO and NO% hourly concentration valuescalculated with the corrected model and the corresponding monitored dataduring the time period considered for the evaluation, as illustrated in Figs. 4and 5.

Table 1 - Background concentration values obtained from canyon modelempirical correction and box model application.

Pollutant

CONO*

Background concentration v

Box model Canyon1.030.087

alues (mg

model cor1.060.056

m

re<

-3)

:tion

Thurvdaj

Figure 4. Time plot of measured and model calculated CO concentrations.


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Day

Figure 5. Time plot of measured and model calculated NO% concentrations.

ResultsThe model developed was applied for the comparison between air qualityimpacts expected from the base and electric scenarios. The evaluation wasperformed by calculating CO and NO% concentrations in the same referencesituation utilized for the evaluation of the model, with respect to hourly trafficflow volumes and meteorology, extrapolated to the year 2003, characterized bya significative penetration of electric vehicles (9% of the total circulating fleetby that time) and by the expected complete renovation of the gasoline lightduty vehicles with low emission catalised cars.

Results obtained for the base scenario, reported in Figs. 6 and 7 in terms ofthe time plot of concentrations during the four consecutive days, indicate highsignificant reductions for CO with respect to the 1990 baseline situation andfairly lower reduction levels for NO%, with mean percentage reduction valueson the same order attained by the corresponding emission figures. Theexpected effects of the electric vehicles scenario developed (9% penetration byyear 2003) are illustrated, in the same terms as before, in Figs. 8 and 9, andresult in average reductions of around 9% with respect to the base scenariosituation, again in accordance with the corresponding emission reductionlevels. In the simulated situation, the reductions obtained for COconcentrations appear to be able to comply with the actual air quality standard,whereas for NO% the lower attained reduction levels either in the base scenariothan with the rather small penetration predicted for the electric vehicle will not


560 Air Pollution

mitigate the situation as well with respect to the standard compliance.Concerning this, it should also be taken in proper account the additionalcontribution of fixed emission sources, which were not active during the periodof the simulation. The same conclusions as before are essentially obtained bythe application of the HIWAY-2 (Petersen ) open street model, in order tosimulate dispersion conditions typical of the outer suburbs of the urban areaconsidered.

For the electric scenario, however, the expected effects could be much morerelevant if the penetration of the electric vehicles, instead of been projecteduniformly over the entire urban area of concern as in the previous simulations,is planned as a localized intervention in restricted zones with actual heavyflows of traffic and more significant consequent deterioration in air and noisequality.

REFERENCES

1. FMT (Federal Minister of Transport), Electric road vehicles, UrbanTransport Research, 32 (special issue), Hamburg/Berlin (Germany), 1983.2. CEC (Commission of the European Community), COST 302 - Technicaland economic conditions for the use of electric road vehicles, Fabre J. et al.,eds., EEC Directorate General of Transport, Luxembourg, 1987.3. Boyd, J.D. 'California's zero-emission vehicle regulations', in EVS-11FLORENCE, Proc. llth International Electric Vehicle Symposium, Florence,Italy, 1992.4. ENEA, CORINAIR Project. Atmospheric emissions inventory for Italy in1985 (in it.), report RTI/STUDI-VASA(89) 8, ENEA, Rome (Italy), 1989.5. CONCAWE, Motor vehicle emissions regulations and fuel specifications -1991 update, report 3/91, Bruxelles (Belgium), 1991.6. Joumard, R. and Andre, M. 'Cold start emissions of traffic' The Science ofthe Total Environment, Vol. 93, pp. 175-186, 1990.7. Giugliano M., Cernuschi S. and Cemin, A. The contribution of electricvehicles to air quality maintenance in large urban areas', in EVS-11FLORENCE, Proc. llth International Electric Vehicle Symposium, Florence,Italy, 1992.8. MIP, Electric vehicle project (in it.), Milano (Italy), 1992.9. Kitagawa J. and Machida M. 'Characteristics of thin wall honeycombsubstrates for automotive catalysts', in Proceedings of the 24th ISATA Int.Symposium on Automotive Technology and Automation, pp. 107-114, Firenze,Italy, 1991.10. Johnson W.B., Ludwig, F. and Dabbert, W.F. 'An urban diffusionsimulation model for carbon monoxide" Journal of Air Pollution ControlAssociation, Vol. 23, pp. 490-494, 1973.11. Hanna, S.R. Handbook on atmospheric diffusion NTIS - U.S. Dept. OfEnergy, Springfield, U.S.A., 1983.


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12. Petersen, W.B. 'User's guide for HIWAY-2, a highway air pollution model',EPA-600/8-80-018, U.S. Environmental Protection Agency, Research TrianglePark, N.Ca. (U.S.A.), 1980.

Thundaj Sunday

Figure 6. Time plot of CO concentrations predicted for the base scenario

O 300z

Baa* to. 1000B*M w. 2003

Thunday Friday 3*turtl*rDay

Sunday

Figure 7. Time plot ofNO% concentrations predicted for the base scenario


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Frid*/

Daj

Bm*« mo. ZOOSElect. «c. 2003

Bunda?

Figure 8. Time plot of CO concentrations predicted for the base and electricscenarios

7 300a

150

100Bmm* ic. 2003Elect, ic. 2003

SatartajDay

Figure 9. Time plot of NO^ concentrations predicted for the base and electricscenarios


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552 Air Pollution - WIT Press