Evaluating Mitigation Plans over Traffic Sector to Improve NO2 Levels in Andalusia (Spain) Using a Regional-Local Scale Photochemical Modelling System

In this contribution, we present an evaluation of different mitigation plans to improve NO2 levels in Andalusia, a region in the south of Spain. Specifically, we consider four possible mitigation plans: the effects over NO2 concentration of apply changes in the distribution of Vehicles Park; the effect of realize traffic restrictions (affecting to the density flow of vehicles) over highways and main roads; the effect of replacement of diesel use by natural gas in urban areas; and the effect of applying new velocity limits to access to urban areas. A sophisticated air quality modelling (AQM) system has been used to evaluate these mitigation plans. AQM implemented is composed on WRF meteorological model, an emission model created by the authors and CMAQ photochemical model. AQM analyzes mitigation plans during fifteen episodes of 2011 where NO2 levels were the highest of the year; so we analyze the effect of mitigation plans in worst conditions. Results provided by the AQM system show that: 1-h maximum daily NO2 is reduced to 10μg∙m−3 near circulation roads when traffic restrictions and velocity limits plans are applied (NOx emissions are reduced in 9% 15%); 1-h maximum daily NO2 is reduced to 12 μg∙m−3 affecting all municipalities when changes in the distribution of Vehicles Park are applied (NOx emissions are reduced in 25% 26%); and the replacement of fuel of urban buses does not affect considerably NO2 levels.


Introduction
Cities, which concentrate 50% of population in 0.1% of land area, generate the largest amount of gases and aerosols emitted into the atmosphere, influencing weather and climate [1].In Europe, air emissions have been reduced significantly in recent years [2], although pollutant concentrations remain high, particularly in urban areas.Recently, the World Health Organization [3] has included pollution as one of the cancer-causing agents for the first time.In urban areas and conurbations, the main cause of pollution is road traffic emissions associated with combustion and road dust resuspension processes [4]- [7].In these areas, nitrogen dioxide (NO 2 ) is one of the pollutants having higher levels [8] in reference with the air quality standards (European Directive EC/2008/50).In Spain, annual average values of NO 2 are elevated in many urban air quality measurement stations with traffic influence [8].In this sense, scientific studies have demonstrated that exposure to a NO 2 concentration higher than 150 µg•m −3 by the population, can increase respiratory problems as inflammation [9], can lead to asthmatic responses in sensitive people to allergens [10] or even cause premature death [11].
In order to improve air quality levels in urban areas, international and national action plans have been developed in the last years [12] [13].In the same way, numerous regional and local air quality plans have been designed in Spain [14].Policies to improve air quality have followed different strategies associated: to decrease variables associated with traffic which directly affect the amount of pollutant emissions (velocity or intensity vehicles flow); and to change Vehicles Park distribution introducing new technologies or alternative fuels [15] [16].
Models are a very useful tool for local administrations for planning and managing production, human resources, activities and emergency proceedings; and to introduce improvement plans of air quality in urban areas.During the last years, air quality models have been used in numerous studies providing the difference of pollutants concentration and a quantitative assessment of the effect of policies and mitigation plans [17]- [21].
This work aims to investigate the effect on urban NO 2 concentrations of four possible mitigation plans: the effect of apply changes in the distribution of Vehicles Park; the effect of realize traffic restrictions over highways and main roads; the effect of replacement of diesel use by natural gas in urban buses; and the effect of apply new velocity limits to access to urban areas.We have used WRF-ARW/AEMM/CMAQ modelling system (section 2.2) to evaluate the impact of each scenario by sensitive analysis.To develop this air quality modelling system focused on NO 2 in this study, we have followed the recommendations proposed by [22] on the Guide on modelling Nitrogen Dioxide (NO 2 ) for air quality assessment and planning to the European Air Quality Directive.
Description of the modelling system used, is presented in Section 2, as well as the area characteristic, data used, episode selection and mitigation plans proposed.A detailed analysis of the results obtained is presented in Section 3, and finally, some conclusions are reported in Section 4.

Studied Area and Methodology
In the following sections, we comment a description of the modelling system, the features of the studied area, the period analyzed, action plans considered and its corresponding scenarios.

Area Characteristic and Episode Selection
The area of study has been Andalusia in the south of Spain (Figure 1).Andalusia covers 17.3 percent of the territory of Spain.Andalusia is surrounded by Portugal and the Atlantic Ocean in the east, and by the Mediterranean Sea in the west.Andalusia is one of the main points of entry to Europe for international ships and in the Strait of Gibraltar sail more than 100,000 ships per year.Andalusia provides the main point of connection between Europe and Africa, with a high traffic of vehicles and facilitates the passage of people and goods between both continents.
The population of Andalusia reached in 2012 a population of 8,421,274 (around 18% of Spain).Andalusia is divided into eight provinces: Almeria, Cadiz, Cordova (Figure 1  The Iberian Massif and the Baetic System are separated by a large depression corresponding to the Guadalquivir basin that crosses Andalusia from NE to SW. Different climate and topographic patterns can be associated to each one of these three zones. Since a climate point of view Andalusia is located in a transition zone from temperate to subtropical climates, presenting a Mediterranean climate ruled by the Azores high.Andalusia's interior is the hottest area of Europe and temperatures rises above 40˚C during summer time.Most precipitation in Andalusia occurs from autumn to spring, associated mainly with Atlantic frontal systems.And in Andalusia is the unique desert area in the Europe (Desierto de Tabernas).
Pollutant air emissions in Andalusia are diverse, considering important natural and anthropogenic contributions.As anthropogenic contributions we can remark traffic emissions from urban areas of Seville and Malaga, industrial emissions from Huelva and Algeciras Bay, and emissions from ships crossing the Strait of Gibraltar.Furthermore, as the authors have analyzed, natural emissions contribute considerably to the air quality levels in the region.In this sense, and depending on the weather conditions, biogenic emissions in Andalusia can contribute up 10% of ozone levels, and sea-salt aerosols and erosion dust can contribute up 10% and 20% respectively.
Regarding the air quality levels, levels of PM 10 and PM 2.5 was low during 2011 (without considers Saharan dust) with exceedances of the daily limit value of PM 10 only in points of Jaen and Granada.NO 2 annual limit value was exceeded in Granada and Seville associated to traffic emissions.O 3 information threshold value was exceeded in three occasions in Seville decreasing considerably regarding the last years.And SO 2 daily limit value only was exceeded in Cadiz associated to the petrochemistry industry in the Algeciras Bay.
In Figure 1, we show models domains used for simulations (section 2.2) that represents different areas of Andalusia.
To analyze the effect of mitigation plans we have considered an amount of fifteen meteorological episodes (corresponding five for Seville, five for Cordova and five for Malaga) of 96 hours in 2011.During this year, the NO 2 limit value fixed by the European Directive EC/2008/50 (200 µg•m −3 ) was exceeded on 18 times.We have selected meteorological episodes with the highest NO 2 concentration measured, evaluating mitigation scenarios in the worst case since an air quality point of view.For this analysis we have not considered holidays and we have tried to consider all climatic stations.
We have characterized episodes using air quality measurements from the Air Quality Network that belongs to the Environmental and Water Agency of Andalusia.In Table 1, we show the date of every episode selected and the maximum 1-h measured in each station.

Modelling Approach
Authors have an extensive experience as modellers [23]- [26] designing and implementing air quality modelling systems and configuring these ones with the optimum parameterizations to reduce the uncertainty of the models [27] [28].The authors have applied this kind of models as forecast tool as assessment tool of mitigation plans working in collaboration with different regional and local administrations (Environmental and Water Agency of Andalusia Government, Environment and Planning Agency of Madrid Government and Territory and sustainability Agency of Catalan Government).
The air quality modelling system used is composed by a meteorological model, an emission model and a photochemical model.To configure models we have used the recommendations and requirements indicated in the Guideline on modelling Nitrogen Dioxide (NO 2 ) for air quality assessment and planning relevant to the European Air Quality Directive [22].We have used these guidelines to choose the kind of models more optimum to evaluate mitigation plans of NO 2 levels.
This coupled air quality modelling system has been applied and tested successfully in urban, industrial and mine areas.Urban areas as Madrid, Barcelona (Spain) or Nice (France); industrial areas as Ponferrada or Tarragona (Spain); and mine areas as Calama (Chile).The air quality modelling system showed has been evaluated using Maximum Relative Directive Error [29] referred in the European Directive EC/2008/50.Results obtained from this evaluation accomplish the model uncertainty limits according to the Directive for the pollutants O 3 , NO 2 , PM 10 , SO 2 and CO, having used measurements from more than 120 stations (urban, suburban and rural locations) during a period of three years.In the following lines we present the main features of the models involved in the coupled modelling system.
Weather Research and Forecasting-Advanced Research (WRF-ARW) version 3.3 was used as mesoscale meteorological model [30].WRF model was configured with six nested domains with 15 (first domain), 3 (sec-ond domain) and 0.5 km (inner domains) of horizontal resolution, as we can see in Figure 1.First domain, called d01, covers the whole Iberian Peninsula, south of France and north of Africa with 100 × 100 grid cells.Second domain (d02), covers the region of Andalusia with 201 × 136 cells.And the inner domains cover Seville and its metropolitan area (d03 with 115 × 115 cells), Cordova (d04 with 115 × 115 cells) and Malaga-Costa del Sol (d05 with 127 × 103 and d06 with 133 × 97 cells) areas.The vertical resolution includes 32 levels, 22 below 1500 meters, with the first level at approximately 15 meters and the domain top at about 100 hPa.Initial and boundary conditions for domain d01 are updated every six hours using GFS (Global Forecast System) model from the National Oceanic and Atmospheric Administration (NOAA).Planetary boundary layer scheme used in the simulations is Yonsey University [31].Microphysics scheme corresponds on Lin scheme [32].GFDL [33] and MM5 [34] scheme are used as long wave and short wave radiation scheme respectively.Noah LSM is the land surface model [35] used, Eta similarity is considered as surface layer scheme [36] and Grell 3D [37] is the cumulus parameterization applied.Two-way nesting is used as relationship between domains.
Emissions are obtained by the Air Emission Model of Meteosim (AEMM) [38].AEMM is a numerical, deterministic, Eulerian, regional and local-scale model developed by Meteosim S.L.It allows obtaining the intensity of emissions in different areas, either anthropogenic (traffic, industry, residential, etc.) or natural (emissions caused by vegetation or erosion dust) for the area of interest.This model combines two emission calculation methods: top-down and bottom-up.The first is based on the space-time disaggregation of lower-resolution inventories (e.g.: EMEP or EDGAR) in accordance with land use and statistical functions associated with different socio-economical variables.Through the second method the model calculates the cell-to-cell emissions from the relevant domains based on emission factors (EMEP/EEA or EPA) or local emission inventories (e.g.: PRTR or autonomic inventories).AEMM is designed to work with various chemical mechanisms (CB4, CB5, SAPRC, AERO4 and AERO5) and it is adaptable to other chemical mechanisms.AEMM is coupled to the meteorological model WRF and to the CMAQ photochemical model, and may be coupled to other models.AEMM takes into account elevated sources, considering 8 vertical levels for industrial emissions.Monthly, weekly and vertical profiles from the Unified EMEP model are applied to determine the value of an emission for every month and day of the year, and vertical level.To obtain emissions in every domain of simulation, we use the two methods of AEMM.By one hand, we use top-down methodology to calculate emissions for d02 domain using the European annual inventory EMEP/MSC (EMEP Chemical Transport Model www.emep.int),and our disaggregation is based on land used CLC2006 (Corine Land Class 2006) with 250 meters of resolution, coupled with different statistical functions depending on socio-economic variables [39].On the other hand, we use bottom-up methodology to calculate emissions for d03, d04, d05 and d06 domains.In any cell we consider industrial, residential and institutional, traffic, solvent, ships traffic, airports, waste treatment and natural emissions.
To simulate NO 2 physical and chemical processes into the atmosphere, we use the US Environmental Protection Agency models-3/CMAQ model [40].CMAQ is an open-source photochemical model which is updated periodically by the research community.In this contribution we use CMAQv4.7.1 (www.cmascenter.org),considering CB-5 chemical mechanism and associated EBI solver [41], and AERO5 aerosol module [42].Regarding NO 2 atmospheric chemistry, CB-5 considers 155 chemical reactions that involve NOx, non-methanic volatile organic compounds (NMVOCs) or ozone (O 3 ).CMAQ model uses the same domain configuration as the WRF simulation.Initial and boundary conditions for d02 domain are provided by the results of simulation of d01 domain.And inner domains with very high resolution are initialized using Andalusia domain results.Meteorology-Chemistry Interface Processor (MCIP) version 3.6 is used to prepare WRF output to CMAQ model.And AEMM model prepares emissions as AERO5 and CB-5 modules require.
In Figure 2, we show an example of CMAQ output for NO 2 daily maximum 1-h in each domain of high resolution.
Numerical simulations are executed for 96 hours corresponding on every episode selected, taking the first 24 hours as spin-up time to minimize the effects of initial conditions.Air Quality modelling system works operationally in a computing cluster own of Meteosim with 27 nodes and more than 150 cores.

Mitigation Plans and Scenarios
In this research, four different scenarios over traffic sector have been considered.Every scenario is associated with a mitigation plan.The first one is based on traffic restrictions.Five different areas have been defined, in which a reduction in traffic volume has been imposed.The centre of each city has been defined as Zone 0. In this area no traffic has been allowed.Other routes inside the city are defined as Zone 1 and a traffic reduction of 20% has been imposed.Big motorways form the Zone 2, with a reduction of 15%.Regional and national roads make up the Zone 3 with a traffic reduction of 10%.Finally, the rest of routes away of the city are defined as Zone 4 with a traffic reduction of 5%.The main idea is to impose an effective traffic reduction in the analysed cities.Other forms of public transport have to balance the private traffic reduction, in order to maintain the economical activity in these areas.
In Figure 3 we can see geographical distribution of traffic restriction designed.
The second scenario imposes a reduction in the velocity.The maximum velocity is decreased between 10 and 20 km•h −1 , in function of the type of route analysed.The maximum velocity for motorways comes down from 120 km•h −1 to 100 km•h −1 .In regional and national routes, the maximum velocity is reduced from 100 km   The last scenario supposes a replacement of the current urban public buses by a new fleet of buses powered by natural gas.This replacement affects the emission factors applied for the traffic emission calculation.In Table 2 we present the emission factor used for urban buses powered by natural gas and by diesel.

Results and Discussion
Every defined scenario has been compared with the base case from sensitivity analysis, as [22] [34] recommends.The sensitivity analysis consists in the comparison between the results obtained by the AQM for the real scenario, defined as base scenario, and the results from simulations introducing different emissions, corresponding to the emissions resulting from the implementation of mitigation plans.This approach using air quality models can directly determine the effect of emission reduction measures on pollutant concentrations at any point in space and time.
Base scenario is calculated applying the coupled air quality modelling system developed considering real emissions (industry, traffic, natural, etc.) in the region, whilst every defined scenario is calculated by the same way modifying Vehicles Park Distribution, velocity of circulation or intensity vehicles flow in AEMM.To analyze the effect of every mitigation plan, we have considered the effect over several statistical values of NO 2 (daily value and daily maximum 1-hour value) and O 3 (daily maximum 1-h and daily maximum 8-h value).We show the results in air quality stations (considering the grid cell that corresponds to every station) and over municipalities.In the last case we analyze two kinds of results: the average value over municipalities that correspond on the average value for all grid cells of modelling domain that cover the municipality; and the maximum reduction obtained in any cell that cover the municipality.
In Table 3 we present the comparison of the effect over NO 2 daily maximum 1-h and daily value of every mitigation plan designed in each air quality measurement station.
Results show that the mitigation plans designed affects NO 2 levels with different intensity.In any case NO 2 concentration is reduced when mitigation plans are applied.Traffic restriction plan reduce up a 7% NO 2 levels in the air quality stations near the city of Seville and Cordova and up an 11% in the case of Malaga.Velocity limiting plan reduce a 3% NO 2 levels in Seville, 1% in Cordova and up a 10% in the case of Malaga.The effect of rejuvenation of Vehicles Park plan is the most intensive and we can observe reductions up a 12% in Seville, a 9% in Cordova and a 13% in Malaga.And finally, the effect of transport public plan is very low with reductions lower than 0.3%.
In Table 4 we present the comparison of the effect over NO 2 daily maximum 1-h of every mitigation plan designed in the municipalities that present greater NO 2 levels evaluated by the air quality modelling.
Maximum reduction of NO 2 levels in the domain of Seville obtained applying traffic restriction plan and rejuvenation of Vehicles Park is reproduced in the city of Seville (reducing a 19% and a 26% NO 2 daily maximum 1-h respectively.However, is in Tomares where is reproduced the most important change of NO 2 concentration applying velocity limiting access plan (reducing a 20%).
In the case of Cordova we reproduce the maximum effect of mitigation plans in the city of Cordova and the effect is significantly greater than in the rest of municipalities.Otherwise, in the domain of Malaga-Costa del Sol, Malaga, Fuengirola, Marbella, Torremolinos and Benalmádena show similar results between them.
In the following sections we present individually the effect of mitigation plans defined over NO 2 and O 3 levels in meteorological periods associated with high NO 2 concentration.

Traffic Restrictions
The application of this plan reduces a 13% traffic nitrogen monoxide emissions in Seville and its metropolitan area; a 14% in Cordoba; and a 15% in Malaga-Costa del Sol.
In Figure 5 we present the difference between NO 2 daily maximum 1-h between traffic restriction scenario and base scenario averaged for all meteorological periods considered.
As the Figure 5(a) shows, the main reduction of NO 2 levels in Seville is obtained in the city centre and in the main routes that connect the centre with the big neighbour towns.This action offers the biggest reduction of the NO 2 levels.In a similar way, the reductions reached in the other analysed areas are bigger in the centre of the cities than in the suburban areas.City centres are the most complicated areas from the point of view of pollutants, because the emission levels are bigger in comparison with other zones.The reduction in these areas is the most important step in order to improve the air quality.This mitigation plan is associated with reductions of NO 2 maximum 1-h greater than 4 µg•m −3 , reducing up 10% NO 2 levels.

Velocity Limiting Access to Urban Areas
The application of this plan reduces a 9% traffic nitrogen monoxide emissions in Seville and its metropolitan area; a 10% in Cordoba; and a 10% in Malaga-Costa del Sol.
In Figure 6, we present the difference between NO 2 daily maximum 1-h between traffic restriction scenario and base scenario averaged for all meteorological periods considered.
Main results are obtained in the access to big cities.This scenario does not suppose big reduction in the city centre but it is possible to reduce an important quantity of pollutants in the entry to the cities, near to 4µgm-3 in this areas.The effect of this measure focuses on the main access roads to Seville (A-4, A-92, AP-4 and A-49), roadways A-4 and A-45 as it passes through Cordoba, and A-7, AP-7 and A-45 near Malaga.It is necessary to remark the results obtained in Malaga western because it is a zone with a high number of motorways, even along the main cities.

Rejuvenation of Vehicles Park
The application of this plan reduces a 25% traffic nitrogen monoxide emissions in Seville and its metropolitan area; a 26% in Cordoba; and a 25% in Malaga-Costa del Sol.Table 4. Effect of mitigation plans over NO 2 values in municipalities.* These values correspond on average value for all grid cells that cover the municipality.** These values correspond on the maximum reduction obtained for all grid cells that cover the municipality.In Figure 7, we present the difference between NO 2 daily maximum 1-h between traffic restriction scenario and base scenario averaged for all meteorological periods considered.

Municipality
The mitigation plan of rejuvenation of Vehicles Park on NO 2 levels causes differences in some municipalities up to 17 µg•m −3 .The effect of this measure has a global impact in every area of application, being its highest intensity in traffic ways where a greater contribution of NO emissions to the atmosphere occurs.

Replacement of Diesel Use by Natural Gas in Urban Buses
The application of this mitigation plan reduces a 0.4% traffic nitrogen monoxide emission in Seville and its metropolitan area; a 0.4% in Cordoba; and a 0.4% in Malaga-Costa del Sol.
In Figure 8, we present the difference between NO 2 daily maximum 1-h between traffic restriction scenario and base scenario averaged for all meteorological periods considered.
The effect individualized of this mitigation plan over NO 2 levels can be considered negligible, causing decreases in NO 2 concentration below 0.3 µg•m −3 in all cases.This feature is explained because the number of vehicles associated with urban public transport is low compared to the total fleet of vehicles, being this contribution lower than 0.6%.

Effect of Action Plans over Ozone Levels
As shown in the above results, a significant reduction in the volume of vehicles or in its form of action directly results in a reduction of the levels of primary pollutants, such as NO 2 .But the same does not occur with a secondary pollutant, such as ozone.The effect of mitigation plans over ozone depends on the kind of area (urban, suburban or rural), on the effect over volatile organic compounds (VOCs) emissions of every measure, and on the weekend effect.This phenomenon refers to the weekly behaviour shown by surface ozone concentrations in urban atmospheres, in which a reduction of the levels of its precursors (nitrogen oxides and volatile organic compounds) during the weekend carries an increase of ozone concentrations [43]- [45].
However, depending on the weather scenarios and levels of reducing emissions of precursors, the so-called weekend effect in ozone can or not be produced.There may be a reduction of NOx and VOCs, but this reduction may not be sufficient to reduce ozone or other factors could involve the elimination of the potential ozone depletion.In this sense, the influence of the actions that lead to the reduction of pollutants should be considered in a potential increase in tropospheric ozone concentrations in the study area.Table 5 and Figure 9 shows the variation of ozone levels between scenario base and the other scenarios analyzed.It is possible to find an increase of ozone concentration around the city centre because of the reduction of primary pollutants.This fact is especially relevant in Seville (Figure 9(a)) and Malaga (Figure 9(c) and Figure 9(d)).In Seville, the higher increase of ozone concentration is observed in the west of the city centre, in an area called Aljarafe.This area usually shows the highest values of ozone in Seville, and probably in Andalusia.The expected increase is between 1 µg•m −3 and 3 µg•m −3 .The legal for comparison is the threshold value for the information of the public (one-hour ozone concentration 180 µg•m −3 ).Then, the actions to reduce the primary pollutants lead an increment of about 1.5% of the legal value whereas the reduction for primary pollutants means a reduction of 2% over the legal value (reduction of 4 µg•m −3 over the 1-hour limit value 200 µg•m −3 ).

Conclusions
A numerical experiment has been developed to evaluate different mitigation plans over traffic sector to improve NO 2 levels in Andalusia.We have considered four mitigation plans: traffic restrictions, velocity limiting access to urban areas, rejuvenation of Vehicles Park, and replacement of diesel use by natural gas in urban buses.We are evaluated the mitigation plans in worst conditions, where NO 2 levels were the highest of the year, and the results are representative of the effect of these plans during environmental episodes of this pollutant.
Every scenario designed reduces into a 14% NO emissions, 10%, 25%, and 0.4% respectively, in the urban areas of Seville, Cordova and Malaga.
We have observed that mitigation plans defined as restriction of traffic and velocity limitations have a local impact and its effect is observed directly near the roads where the measures are applied.In both cases the maximum reductions of daily NO 2 maximum value is around 10 µg•m −3 .The plan defined as rejuvenation of the fleet has an overall impact and we can note the effect over every municipality that covers model domains.Re-ductions up 17 µg•m −3 have been obtained.The measure designed over transport public has not significant effects on NO 2 levels due to the low number of vehicles that affects the plan.
Mitigation plans has the effect with opposite sign and provide an increase (1.5%) of ozone concentration in areas where typically ozone levels are high.Nevertheless, the analysis is representative of high NO 2 conditions and in the future the authors extend the study to high O 3 conditions to obtain a better evaluation of the effect of mitigation plans over this atmospheric pollutant.
(b)), Granada, Huelva, Jaen, Malaga (Figure 1(c) and Figure 1(d)) and Seville (Figure 1(a)), being the city of Seville its capital and the largest urban agglomeration in Andalusia with a population of 1,217,811.Andalusia has around 1000 km of coast line and presents a varied and complex topography.Main mountain ranges are the Sierra Morena, including Sierra Nevada (Mulhacén Peak, 3481 m.a.s.l), and the Baetic System.
•h −1 to 90 km•h −1 .Finally, in the rest of routes, maximum velocity decreases from 90 km•h −1 to 80 km•h −1 .Traffic emissions are calculated using AEMM model based on emission factors from EEA/EMEP CORINAIR and these emission factors depends on the velocity of circulation.In Figure 4, we can see geographical distribution of velocity limitation designed.With the third scenario, a renewal of the vehicle fleet is assumed.Each private vehicle with more than 12 years is replaced by a new vehicle with the same cubic capacity and fuel, but according with the new laws about vehicle emissions.Traffic emissions are calculated using AEMM model based on emissions factors from EEA/EMEP CORINAIR.Emission factors relate emissions of a pollutant with a vehicle type depending on the directive to which they belong (age of the vehicles).For this reason, variations in the distribution of the fleet cause different emission values.

Figure 3 .
Figure 3. Geographical distribution of traffic restriction plan over Seville, Cordova and Malaga.

Figure 4 .
Figure 4. Geographical distribution of velocity limiting access plan over Seville, Cordova and Malaga.

Figure 5 .Figure 6 .
Figure 5. Absolute difference between NO 2 1-h maximum between traffic restriction scenario and base scenario in Seville (a), Cordova (b); Malaga western (c) and Malaga eastern (d).

Figure 7 .Figure 8 .
Figure 7. Absolute difference between NO 2 1-h maximum between rejuvenation Vehicles Park scenario and base scenario in Seville (a); Cordova (b); Malaga western (c) and Malaga eastern (d).

Figure 9 .
Figure 9. Absolute difference between O3 1-h maximum between rejuvenation Vehicles Park scenario and base scenario in Seville (a); Cordova (b); Malaga western (c) and Malaga eastern (d).

Table 1 .
Daily maximum 1-h value measured in the air quality stations in meteorological episodes selected.

Table 2 .
Emission factors used for urban public buses powered by natural gas and by diesel from EEA/EMEP CORINAIR.

Table 3 .
Effect of mitigation plans over NO 2 values in air quality stations.* These values correspond on average value for all meteorological periods selected.** These values correspond on the difference between the average value of mitigation plan and base scenario.

Table 5 .
Effect of mitigation plans over O 3 values in air quality stations.* These values correspond on average value for all meteorological periods selected.**T hese values correspond on the difference between the average value of mitigation plan and base scenario.