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Abstract—This study estimates the emission reductions brought by the Vehicle Inspection and Maintenance Program in São Paulo City, and quantifies its benefits. The reference data for the present analysis were the results of the measurements carried out by CONTROLAR in 2011 to measure free acceleration exhaust gas opacity of Diesel vehicles and exhaust emission of carbon monoxide and hydrocarbons at idle from vehicles equipped with Otto cycle engines. These measurements are part of the inspection procedures conducted routinely to assess the state of vehicle maintenance. The calculation of emission reduction was done with the aid of a methodology that correlates the emission levels of type approval certification with the statistics relating to concentrations of pollutants, engine size, maximum RPM of the engine and the annual average mileage. Such correlations allow assessing the relative reduction of the inspected fleet annual emissions and are expressed as equivalent percentages of the fleet that would be withdrawn from circulation to produce the same effect. The purpose of this methodology is to translate the achieved benefits to a language easily understood by the general population. Keywords—air pollution, emissions, environmental impact,

vehicle inspection.

1. INTRODUCTION

One of the biggest air pollution sources in metropolitan areas is the vehicle fleet. Technology improvements are highly necessary to control this problem, but vehicle owners are also key for successful emission reduction. Therefore, annual In-Use Vehicle Inspection and Maintenance Programs - I&M are necessary to increase the effectiveness of emission control measures.

While type approval emission control certification requires sophisticated laboratories and complex tests procedures I&M tests must be simple, expedite and low cost. Therefore,

Gabriel M. Branco is Associate and Director of EnvironMentality – Tecnologia com Conceitos Ambientais Ltda – Rua Michigan 177, CEP 04566_000 -São Paulo/SP, Brasil (gabriel.tcl@uol.com.br)

Fábio C. Branco is Associate and Project Manager of EnvironMentality – Tecnologia com Conceitos Ambientais Ltda – Rua Michigan 177, CEP 04566-000 -São Paulo/SP, Brasil(fabio.tcl@uol.com.br)

Marcelo C. Branco is a PhD student at Escola Politécnica of the Universidade de São Paulo (Polytechnic School of the University of São Paulo) (marcelobranco@uol.com.br)

Eduardo M. Dias is full professor of the Escola Politécnica of the Universidade de São Paulo and coordinator of GAESI - Grupo de Automação Elétrica em Sistemas Industriais, a reseach group of the Electrical Energy and Automation Department, Escola Politécnica, Universidade de São Paulo, Av. Prof. Luciano Gualberto, trav. 3, n. 158, São Paulo/SP, Brazil, CEP 05508-970 (emdias@pea.usp.br)

José M. Napoleone is a technical consultant of CONTROLAR (I&M operator) (napoleone@terra.com.br)

Alfred Szwarc is Director of ADS – Tecnologia e Desenvolvimento Sustentável – Rua Albuquerque Lins, 848 / 11 CEP 01230-000 São Paulo/SP, Brasil (alfred.ads@terra.com.br)

emission measurement of pollutants in some key engine operating conditions must be sufficient to evaluate vital maintenance failures, mistuning and illegal modifications that result in emission degradation. This can be accomplished with the free acceleration smoke opacity measurement of Diesel vehicles and the carbon monoxide – CO and hydrocarbon – HC emission measurement at idle, in vehicles with Otto cycle engines. In order to have a meaningful inspection, vehicles are also submitted to a visual evaluation to check abnormal engine and muffler noise, water, fuel and oil leaks, and integrity of engine and emission control systems.

These tests should be regarded as indicative, since the test vehicles are under only one engine condition instead of following a full driving cycle, with forces and speeds representative of normal driving. However, although simple, these test procedures submit engines and emission control systems to operating conditions that are able to expose problems. To do so they have to be associated to representative emission inspection limits. The so-called “emission inspection limits” are, in fact, only reference parameters for relative comparisons between similar vehicles having new vehicles as the benchmark.

Despite not directly comparable to driving cycle results, the relative differences and variations showed by these measurements present very good statistical correlation of the fleet averages to the emissions determined in mass per kilometer for each model year. Therefore it can be said that they allow accurate determination of emission deterioration factors and annual emissions inventories calculations to quantify the overall benefits of the I&M program.

Therefore, based on the extensive data obtained during the period of 2008-2013 from the São Paulo I&M program (I/M-SP) it is safe to say that simple test procedures as those mentioned before provide valuable knowledge to control the emission of in-use vehicles.

2. FUNDAMENTALS OF VEHICLE EMISSION DETERMINATIONS

The emission certification of new vehicles (type approval) requires representative vehicles to run tests simulating “real world” driving conditions. Light duty vehicles are tested in chassis dynamometers following a speed time cycle, under inertia and friction forces determined on the road. Emission results are integrated and expressed as grams/km of the regulated pollutant of interest. The exhaust CO and HC concentrations are measured at idle, since this condition is the most susceptible to ignition failures and catalytic converter malfunction due to engine mistuning, and is a robust indicator of common emission problems.

Criteria for Efficiency Determination of Inspection Maintenance Programs

Gabriel M. Branco, Fábio C. Branco, Marcelo C. Branco, Eduardo M. Dias, José M. Napoleone, Alfred Szwarc

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Heavy duty vehicles have their engines tested in a dynamometer test bench in a sequence designed to cover the entire engine map of torque and angular speed. This is a standard representation of all possible combinations of both parameters in a given engine, as follows:

RPM is represented within zero (idle) and 100% (maximum allowed);

Torque is plotted within -5% (engine friction) and 100% (maximum possible in each RPM)

Fig. 1 presents the European Transient Driving Cycle – ETC plotted in the engine map of a typical truck. The triangles relate to a statistical distribution of city driving, the round dots are representative of rural road driving and crosses are correspond to highways. This test protocol is used to certify the engine’s technological ability to comply to emission limits, given in grams/kWh. These results may also be converted into grams/km using the specific fuel consumption averaged in the emission test and the fuel consumption measured in the vehicle in km/liter. This indirect parameter is the key to estimate the annual emissions in the inventory calculations [1].

Fig. 1 – The ETC test cycle in a Diesel engine map

The emissions are measured in each point and weighted

through the entire test, in grams/kWh. In this test, the upper points have the highest influence on the particulates emission. On the other hand, the free acceleration test uses the rotating parts inertia to produce torque under acceleration and identify the smoke opacity near these points. Therefore, these results are a good parameter to indicate particles emission - PM. Other protocols are possible and used in some countries, but the simple free acceleration test is adequate to characterize the most common engine maintenance failures.

2.1 Smoke and PM correlations The highest mass constituent of Diesel smoke particles is

unburned black carbon. Sulfates, hydrocarbons, metals and ashes are also contained in the particle mass. Smoke is the main target of Diesel vehicle inspection, because it greatly depends on engine tuning, fuel injection system and nozzles wear and air filters blockage.

Smoke opacity, measured in m-1, also correlates to Filter Smoke Number – - FSN (Bacharach or Bosch gray scales to be used in a filtered sample of exhaust gases) [2] and may be

converted to mass concentration in the exhaust according to several studies, as illustrated in Fig. 2.

Fig. 2 – Interrelations of opacity, smoke and particulates mass (source AVL)

The numerical correlation of smoke opacity and FSN was

observed experimentally by AVL in distinct Diesel technologies and engine sizes and presented in Fig. 3, showing very good repetitiveness. In general, opacity is the preferred protocol because it is easy and rapid to measure. Moreover, it is also valid for transient measurements 1.

Fig. 3 – Smoke measurement FSN and opacity correlation (source AVL)

The equivalence of opacity and smoke was firstly

established by The Motor Industry Research Association - MIRA and was adopted internationally [3]. The equivalence factors were transformed into a linear regression equation, valid for opacimeters with optical length of 43 cm, operating under 75°C, as established by the following equation:

Concentration (mg/Nm3) = 147,509 * opacity (m-1) (Eq.1)

Considering the ETC driving cycle, smoke opacity varies a

lot, as showed in Fig. 4 for the same test in two time scales.

1 The FSN measurement requires 30 seconds sampling, while opacimeters

have 0,1 second to 90% total signal variation.

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But when ordering all points from zero to maximum and integrating the smoke mass conversion it is possible to see that total particle mass is proportional to maximum allowed peak value. In other words, the maximum peak is a representative parameter of the particle emission of a given engine.

Fig. 4 – Diesel exhaust opacity curve during an ETC test

In this case, of an EURO II Diesel engine, the allowed limit

is 2,0 m-1 and was exceeded in 4,5% of test time, but these exceedances correspond to 53% of total emitted particle mass during the driving cycle. Therefore, reducing smoke peaks to the allowed limit, decreases its emission in the same order of magnitude in 95,5% of the running conditions.

Considering the linear correlations between smoke and particle emission, the average variation of smoke prompted by proper maintenance may also estimate its particle mass emission reduction for the same vehicle.

Comparing the particle mass emission according to the Brazilian emission certification procedure and its corresponding free acceleration tests, it is also possible to establish linear correlations between them for each technology level, as shown in Fig. 5.

Fig. 5 – Observed correlations in certification tests in Brazil

In the I/M-SP, the opacity is averaged for each category

(vehicle size) and model year (technology level 2) to characterize the proportional parameter of each one in the

2 The Brazilian Vehicle Emission Control Program has established several

technology stages in a long term chronogram. For heavy duty vehicles, these levels are identified as P1 to P7; for light duty vehicles L1 to L6; and for motorcycles M1 to M4, being the last ones in each group representative of current vehicles.

annual emission inventory. The smoke averages of approved vehicles are several times lower when compared to the averages of the vehicles failed in the same category. However, when properly maintained and reinspected, this average is reduced to near the same level of the approved ones, as shown in Fig. 6.

Fig. 6 – Smoke opacity levels compared for each technology level

Therefore, in an I&M Program, the average reduction of

smoke opacity, converted to mass concentration in mg/m3 for each vehicle category and technology can be calculated for two cases:

• “initial” status of the fleet, estimated by the first inspections of all vehicles (approved + failed), properly weighted according to the failure rate;

• “final” status” of the fleet, estimated by the initially approved and the last reinspection of the failed vehicles;

The emission reduction rate is calculated by the ratio of both final and initial status averages for each vehicle category and model year, and therefore can be used as tons per year in an annual emission inventory.

2.2 Correlations for carbon monoxide and hydrocarbons The emission measurement of CO and HC in the Otto cycle

is done at idle, which is an engine operating regime especially sensitive to engine failures.

Theoretically, the results at idle are not convertible into the emission measured in a driving cycle, since it is possible to tamper the idle tuning without changing the engine behavior under load. However, the comparison of thousands or millions of measurements in an I&M inspection shows a clear evidence of a statistical correlation between the concentrations of CO and HC idle and their respective emissions measured in the driving cycle, in g/km 3, as shown in Fig. 7 for carbon monoxide measured in gasoline vehicles, in the 2012 calendar year. Similar curves were obtained for hydrocarbons, both for all vehicle categories, which are also used to determine the statistical trends of the emission deterioration factors in the “real word”. Usually I&M statistics identify two distinct

3 In Brazil, the adopted driving cycle for light duty vehicles is the US FTP-75

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groups of vehicles: “normal maintenance”, defined by the average of the best 90% of the fleet; and “tampered” vehicles, defined by the average of the worst 10% of the fleet.

Fig.7 – Carbon monoxide levels for gasoline vehicles

Similarly to the smoke case, the averages of CO and HC

also show a significant difference between the approved/reinspected and failed vehicles. Therefore, the emission reductions may be estimated through the same calculation concepts, based on the “initial” and “final” statuses of the fleet, outlined in 2.1.

3. FINAL CALCULATION TO ESTIMATE THE ENVIRONMENTAL BENEFITS OF AN I&M PROGRAM

Based on the “final and initial” pollutant concentration averages, the environmental benefits are given by ratios between them, multiplied to the correspondent annual emissions calculated in the official inventory for each vehicle category. The relative reduction of annual emissions are calculated based on the current (initial) emission basis, as follows:

RPM (%) = (PMinitial - PMfinal ) / PMinitial (Eq.2) RCO (%) = (COinitial - COfinal ) / COinitial (Eq.3) RHC (%) = (HCinitial - HCfinal ) / HCinitial (Eq.4) where: R = reduction of annual emission from the considered fleet;

PMinitial, COinitial and HCinitial = PM, CO and HC average concentrations calculated for the initial inspection, for each vehicle category and model year

PMfinal, COfinal e HCfinal = PM, CO and HC average concentrations calculated for the final inspection, for each vehicle category and model year

The emission benefits are then determined in tons/year multiplying the inventory annual emissions by the relative reductions calculated above, and may be applied to estimate the relative decrease in atmospheric concentrations, as a comparative parameter.

ERannual,i = ∑Ri(%)*N * EFcert,i*DFnormal,i * kmannual *10-6

(Eq.5) where: ERannual,i = reference average reduction annual emission of

pollutant “i”, in ton/year; N = number of considered vehicles in each category

and model year EFcert,i = average of certified emission factors of pollutant

“i”, in g/km DFnormal,i = “normal” deterioration factors of pollutant “i”

emission, ≥1,00 (vehicles in good maintenance conditions)

kmannual = annual average mileage for each vehicle category and age, in km/yr

Once calculated according to the above criteria, the

emission reduction of each part of the fleet may be added and compared under the same basis and independently of being different vehicles categories and technologies, i.e. proportionally to their final effect on the environment.

4. FINAL REMARKS

In order to achieve the adequate parameters for the environmental benefits estimate, some approaches might be assumed, if there are shortages in some inspections, as the absence of emission measurements in rejected vehicles earlier during visual inspection. Therefore, the estimation might consider: a) the “INITIAL” emission concentration averages

calculations for each category and model year is based on all vehicles at the first inspection, no matter if they are approved, failed in the test or rejected in the visual inspection;

b) in the rejection cases, when the appointed failure is related to emission increase, as loosen hoses, broken canister etc., it is assumed the emission is as high as the failed vehicles average. Other items that are not necessarily linked to exhaust emission increase, as lubricant leaks for example, it is assumed that this vehicle may be represented by the overall average taken from the first inspection of measured vehicles;

c) the “FINAL” emission concentration averages calculations is based on the last inspection of all vehicles failed and the ones approved at the first inspection;

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d) The “normal” fleet annual emission shall be calculated for the certified emission factors (EF) and deterioration factors (DF) for each category and model year and summed up to estimate the total inventory benefit;

e) The “final” fleet annual emission may consider the residual percentage of failed vehicles, per category and model year, or assumed as the normal fleet annual emission if this residue is negligible;

f) The “initial” annual emission shall be calculated by multiplying the “final” fleet emission by the correspondent “% reduction” rate” calculated from equations 2 to 4, above, for each category and model year and summed up to estimate the total inventory benefit.

All these results can be grouped by technology level, or vehicle category, or the whole fleet, according to the purpose of the study and environmental control strategy.

Fig. 8 presents the particles control benefits from the diesel fleet in 2012, as an example, segregated by technology level according to the Brazilian Vehicle Emission Program to Control Air Pollution – PROCONVE, where the blanks represent the total reduction per group and the colored bars represent each vehicle category in the tech group.

Fig. 8 – Particles reduction in diesel fleet in São Paulo - 2012

Considering each homogeneous group separately, it is also

interesting to calculate the “number of equivalent vehicles”, which is the number of vehicles that would produce equivalent environmental effect if removed from the fleet. This is another parameter that may be useful to translate these abstract calculations into a more understandable Fig. to the general population, as shown in Fig. 9.

Fig. 9 – Particles reduction in diesel fleet in São Paulo expressed in “equivalent vehicles” - 2012

Integrating all different vehicle classes and ages, the above

calculations result in two weighted estimates of the fleet initial and final annual emissions. Differences between them provide the annual “net” benefit and their series shows the evolution in subsequent years, the remanent benefit from the previous year to the next and the influence of other associated environmental strategies. Fig. 10 shows the diesel PM emission as an example. The reduced gain from one year to the other indicates an evolution of the I/M-SP program and this effect can be associated to the improvement of maintenance services being other factors equal.

Fig. 10 – Diesel particles environmental benefits compared annually

The annual balance of I/M-SP environmental benefits is

shown on table 1. Based on the particles (particulate matter – PM) emission reduction, it was estimated the annual PM reduction in the inventory and this indicated 10,5% reduction in PM atmospheric concentration. The Experimental Air Pollution Laboratory of the Medical School of the University of São Paulo (LPAE/FMUSP), used these results to estimate the public health benefits, and concluded that I/M-SP has potentially avoided 580 premature death per year [4]. Their study demonstrated that the costs of inspections distributed by the number of saved lives by the I/M-SP Program resulted extremely low when compared to other public health programs.

Table 1 – I&M emission reductions in São Paulo

inspected vehicles CO HC PM

LDV - Otto 2.700.000 49% 39% Motorcycles 268.000 34% 42% Diesel vehicles 128.000 28%

5. CONCLUSIONS

The methodology presented in this paper was developed to evaluate the I/M-SP effectiveness, not only in terms of

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operational performance, generally given by the numbers of inspections, vehicle failures and other statistics, but also through the estimation of its main objective: the environmental benefits produced by the preventative and corrective vehicle maintenance.

The statistical correlation of the measured concentrations and true emission factors in real use was found as the best parameter to evaluate the environmental benefits. Despite there is no direct conversion from pollutant concentrations at idle or under free acceleration into its mass emission determination in a dynamic driving cycle, the variations of the average concentrations measured in the fleet does correlates to the variation of the true emission in grams per kilometer, and represents a very valuable tool for fleet management and transport strategies.

Planning and proposing solutions to problems that affect large cities in the world, both in the area of urban transport, health and environment, certainly would benefit from the concepts developed in this paper, since they provide a simple way to quantify the results of an I&M program and create valuable data that could help to compare different transport strategies and also quantify the associated environmental impacts.

REFERENCES [1] Branco, G.M.; Ryan, J.J.; Branco, F.C. - IMPACTO AMBIENTAL DA

FROTA DIESEL ATÉ 2030 - ESTUDO DE CASO: RMSP - XIII Congresso e Exposição Internacionais de Tecnologia da Mobilidade - SAE BRASIL 2004 - 16 de novembro de 2004 – São Paulo – Brasil.

[2] Westlund, A. - Measuring and Predicting Transient Diesel Engine Emissions – Licentiate thesis; KTH CICERO; Department of Machine Design - Royal Institute of Technology – Stockholm – 2009..

[3] DX250 SMOKEMETER PROGRAM UK MOT 2002 - Conversion chart for k, HSU, FSN and mg/m3, extracted from MIRA Report No. 1965/10, Nuneaton Warwickshire, UK - 1965, AG Dodd and Z. Holubecki.

[4] Saldiva, P.H.N.; André, P.A. de; Miraglia, S.G.K. - Impact of diesel vehicle inspection on health: the experience of São Paulo, Brazil - ISEE - International Society for Environmental Epidemiology - http://www.iseepi.org/About/history.htm - Basel 2013.

ABOUT AUTHORS Branco, Gabriel Murgel – born in São Paulo, in 1949, graduated in Mechanical Engineering at Polytechnic School of the University of São Paulo, worked at the State Environmental Agency for 20 years in the development and implementation the vehicle emission control program in Brazil, consultant for vehicle emission control at EnvironMentality since 1996. Branco, Fábio Cardinale – born in São Paulo, in 1969, graduated in geology at the University of São Paulo, master of science in satellite images processing, consultant of the vehicle emission strategies and I&M Program at EnvironMentality since 1996. Branco, Marcelo Cardinale – born in São Paulo, in 1967, graduated in Administration, taking master of science degree in transportation, environment and energy conservation, Secretary of Transport in the city of São Paulo until 2012, member of the State Transportation Council 2011-13, and vice-president of ANTP – Public Transportation National Association since 2011. Dias, Eduardo Mario – born in São Paulo, in 1951, is full professor of the Escola Politécnica of the Universidade de São Paulo and coordinator of GAESI - Grupo de Automação Elétrica em Sistemas Industriais, a reseach

group of the Electrical Energy and Automation Department, Escola Politécnica, Universidade de São Paulo. Napoleone, José Mauro - born in Agudos – SP, in 1946, graduated in mechanical engineering at the Military Engineering Institute, worked in CONTROLAR (the I&M company) since 2007 until January 2014. Szwarc, Alfred – born in Lodz, Poland, in 1952, graduated in mechanical engineering at Taubaté Engineering School, SP, worked at the State Environmental Agency for 20 years in the development and implementation of the vehicle emission control program in Brazil, presently consultant for vehicle emission control at ADS since 1998.

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