EXPAH - ACTIONS 4.3-4.4: Calculation and integration of traffic emissions with the updated Lazio Region inventory. Spatial, temporal and chemical disaggregation of the emission inventory

(1)

EXPAH - ACTIONS 4.3-4.4: Calculation and integration of traffic emissions with the updated Lazio Region inventory. Spatial, temporal and chemical disaggregation of

the emission inventory

Authors

P. Radice, P. Smith, M.P. Costa, A. D'Allura, C. Pozzi, A. Nanni, S.Finardi

Riferimento

ARIANET R2012.05

(2)

1 Executive summary ... 2

2 Rome Metropolitan area traffic emission modelling... 4

2.1 Upgrade of traffic emission model TREFIC to include PAHs ... 5

2.2 Bottom-up traffic emissions estimation ... 6

2.2.1 Rome Fleet ... 11

3 Traffic emissions in the other provinces of Lazio Region ... 13

4 Resulting traffic emissions in Lazio Region ... 18

5 Revision of Lazio Regional emission inventory ... 24

6 Emission input ... 28

7 Model ready hourly gridded emissions ... 29

8 Conclusions ... 34

9 References ... 35

10 Appendix ... 37

(3)

LIFE+ Project EXPAH - ACTIONS 4.3-4.4: Calculation and integration of traffic emissions with the updated Lazio Region inventory. Spatial, temporal and chemical disaggregation of emission inventory

1 Executive summary

This technical report describes the work carried out under actions 4.3 and 4.4 of the Population Exposure to PAH (EXPAH) LIFE+ project. A reference Policyclic Aromatic Hydrocarbons (PAHs) emission data set has been constructed on the basis of emission inventories available at national and international level and of supplementary data collected in the frame of action 4.1 and 4.2. The developed emission inventory will be later used by a Chemical Transport Model (CTM) to simulate the emission, dispersion, transformation and deposition of PAHs and other gaseous pollutants. The simulations will be carried out under action 4.5 of the EXPAH project. Data included within inventories have been integrated with information available at local level for Lazio Region and Rome Province to reach the better possible detail in the emission downscaling to the space resolution requested by planned model simulations (1 km). Due to the specific objectives of EXPAH project, it has given preference to emission data with higher space resolution over the target area of Rome. This aim has been fulfilled starting from the national emission inventory ISPRA2005 (http://www.sinanet.isprambiente.it/it/inventaria/disaggregazione_prov2005/) characterized by province level resolution and its downscaling at municipal level resolution INCOM2005. These inventories include total PAH emissions for each source sector but they do not include information on the different congeners. Emissions of the 4 PAHs identified in the UNECE POPs protocol (http://www.unece.org/env/lrtap/pops_h1.html; benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene and indeno[123-cd]pyrene) have been estimated by means of the profiles available in literature for the various emission sources. The results have been analyzed and compared with the European scale emission inventory developed and provided by TNO (http://www.tno.nl). The inter-comparison highlights the large degree of uncertainty that affects PAHs emissions and that can generally be considered larger than that associated to other pollutants. The analysis of the emissions inventory of Lazio Region and Rome metropolitan area confirmed that combustion in residential heating is the main source of PAHs accounting for 73% of emissions in Lazio region, growing to 92% within Rome municipality. Waste treatment contribution is the second main contribution with 22% of emissions over the Region, 9% over the Province and 3% over Rome municipality. Road transport contribution remains in the 3-4% range over the different considered areas. Details on the PAHs emission inventory and inter-comparison analysis can be found in EXPAH Action 4.1 technical report (Radice and Finardi, 2011) available at project web site (http://www.ispesl.it/expah/pubbl.asp).

The national inventory PAHs data have been downscaled from Province to municipal resolution using the same proxies previously employed to implement INCOM2005 inventory (municipal level inventory elaborated from ISPRA2005 for the Italian Ministry of Environment). All the emissions have been updated to the reference year 2009 using historical trends obtained from the national

(4)

Industrial emissions (point sources) have been updated to year 2009 on the basis of a survey provided by ARPA Lazio. Civitavecchia port activity emissions has been revised starting from data concerning ship movements.

The most detailed and innovative evaluation of PAHs emission regarded road transport. Traffic fluxes on Lazio Region road network have been estimated from AISCAT (Associazione Italiana Società Concessionarie Autostrade e Trafori; http://www.aiscat.it/), ASTRAL (Azienda Strade Lazio; http://www.astralspa.it/) and ATAC (Azienda per la mobilità; http://www.atac.roma.it/) information for year 2009 through the application of a traffic assignment model. Vehicle fluxes on each link of Rome Province road network have been estimated by Rome Municipality Mobility Agency by means of a traffic assignment model representing the traffic flows on the road network, on the basis of origin–destination (OD) matrices and observed traffic data. Hourly emissions of all the pollutants, including PAHs, have been calculated for each road link and each vehicle class by means of TREFIC model (Nanni et al., 2005), based on the COPERT IV methodology. TREFIC software has been updated to include PAH congeners emissions. Bottom-up traffic emissions estimated from vehicles flow on each road link have been compared with corresponding values included in the national inventory ISPRA2005 to verify their general consistency and identify possible relevant discrepancies.

The following Sections contain a detailed description of the different elaboration steps that carried to produce hourly gridded emission with format required for air quality simulations to be performed with the chemical transport model FARM.

(5)

2 Rome Metropolitan area traffic emission modelling

The calculation of traffic emissions was performed by TREFIC (http://www.arianet.it/front/ENG/codes/files/7.pdf), a code which implements the European COPERT IV methodology for estimating emission factors of road vehicles. TREFIC (“TRaffic Emission Factor Improved Calculation”) has been conceived to answer to the many specific requests which arise when calculating the atmospheric pollutant emissions from road sources. Such requirements can be related both to emissions estimates in a project/planning framework (emission inventory) and to specific emissions calculation in order to use modelling methodologies with diagnosis/forecast objectives (compliance of emission scenarios with air quality standards). COPERT IV methodology includes, for road transport typical atmospheric pollutants, the calculation of EFs, i.e. coefficients expressing specific emissions of a single vehicle, in terms of mass per travel unit (g/km). These coefficients depend on:

fuel type (leaded or unleaded gasoline, Diesel, LPG);

vehicle type (2 wheeler, passenger car, light duty vehicle, heavy duty vehicle, bus);

road average travelling speed and type (urban, rural, highway);

engine displacement, for passenger vehicles, and capacity, for duty vehicles;

vehicle age (registration year);

.efficiency and maintenance state of the vehicles.

Where specific information is available, emission factors may also depend on:

 ambient temperature (for cold start, extra emissions in urban driving and evaporative emissions)

 average slope of road link;

 actual average load (for heavy duty vehicles, the default load is 50%).

Vehicle age allows to determine engine and abatement technology, regulated by European directives stating, year by year, limits for emissions of newly produced engines. Among the new features in version 4.0 there is also the emission degradation due to the total mileage.

The number of vehicle categories provided in COPERT IV is 241, some of them regulated by specific national laws not in force in Italy. The complete list of COPERT IV vehicle categories is presented in the Appendix Chapter 10. For a description of single categories please refer to official

(6)

The input of the program consists of traffic flows and average speeds associated to the considered street grapho. Information is specified for the four major categories of vehicles (motorcycles, passenger cars, light commercial vehicles and heavy duty vehicles). In addition, the distribution of vehicles within each macro-category must be specified, in terms of COPERT classes, subdivided by power supply, capacity, load (in the case of commercial vehicles) and the European Directive of reference with regard to compliance with the limits emissions.

2.1 Upgrade of traffic emission model TREFIC to include PAHs

TREFIC was updated to its version 4.3 to make use of PAH emission factors obtained from the COPERT database, according to six vehicle macrocategories, and estimate emissions of the different PAH congeners included in COPERT dataset. With previous versions, only the total PAH emission was output for each road link, while individual congeners needed to be calculated afterwards using speciation profiles.

PAH congeners emission factors (in μg/km) are given in Table 1 and illustrated in Figure 1 for the congeners included in the emission inventories, while Table A1 (in the Appendix Chaper 10) shows the mapping between all vehicle categories and emission factors. For gasoline passenger (PC) cars and light-duty vehicles (LDV), distinction is made between conventional (pre-Euro I) and closed-loop catalyst vehicles (Euro I and later). For diesel passenger cars and light-duty vehicles, different emission factors are given for direct injection (DI) and indirect injection (IDI) vehicles. All heavy duty vehicles (HDV) are considered to have direct injection diesel engines. The last category accounts for LPG (liquefied petroleum gas) vehicles, and conventionally includes also CNG (compressed natural gas) engines. 4-stroke motorbikes are associated to Euro I & larger gasoline cars, while 2-stroke motorbikes emission factors are assumed to be the same of pre-EURO gasoline cars.

The emission factors are considered as bulk values, independent of vehicle speed and with no distinction between hot and cold-start emissions. They have been developed on the basis of a literature review, including the following sources: BUWAL (1994), Rijkeboer and Hendriksen (1993), Volkswagen (1989).

Table 1: COPERT bulk (hot + cold) emission factors for PAHs (μg/km)

Gasoline PC & LDV Diesel PC & LDV HDV LPG

Species Conventional Euro I & on DI IDI DI

indeno(1,2,3-cd)pyrene 1.03 0.39 0.7 2.54 1.4 0.01

benzo(k)fluoranthene 0.3 0.26 0.19 2.87 6.09 0.01

benzo(b)fluoranthene 0.88 0.36 0.6 3.3 5.45

benzo(ghi)perylene 2.9 0.56 0.95 6 0.77 0.02

fluoranthene 18.22 2.8 18 38.32 21.39 1.36

benzo(a)pyrene 0.48 0.32 0.63 2.85 0.9 0.01

pyrene 5.78 1.8 12.3 38.96 31.59 1.06

perylene 0.11 0.11 0.47 0.41 0.2

anthanthrene 0.07 0.01 0.07 0.17

benzo(b)fluorene 4.08 0.42 24 5.21 10.58 0.71

benzo(e)pyrene 0.12 0.27 4.75 8.65 2.04

triphenylene 7.18 0.36 11.8 5.25 0.96 0.48

benzo(j)fluoranthene 2.85 0.06 0.32 0.16 13.07

dibenzo(a,j)anthracene 0.28 0.05 0.11 0.12

dibenzo(a,l)pyrene 0.23 0.01 0.12

3,6-dimethyl-phenanthrene 4.37 0.09 4.85 1.25 0.18

(7)

chrysene 0.43 0.53 2.4 7.53 16.24

phenanthrene 61.72 4.68 85.5 27.63 23 4.91

naphthalene 11.2 610.19 2100 650.5 56.66 40.28

anthracene 7.66 0.8 3.4 1.37 8.65 0.38

coronene 0.9 0.05 0.06 0.05 0.15

dibenzo(ah)anthracene 0.01 0.03 0.24 0.56 0.34

Figure 1. COPERT emission factors (μg/km) for the main four PAH congeners

2.2 Bottom-up traffic emissions estimation

Starting traffic data were provided by ATAC for the Province of Rome. The data include the geometrical information (geographical map of the roads) and the traffic modelling results to estimate the volumes of traffic. The simulations were carried out by ATAC and referred to the year 2009. The road graph of ATAC is shown in Figure 2.

0 1 2 3 4 5 6 7

benzo(a)pyrene

benzo(b)fluoranthene

benzo(k)fluoranthene

indeno(1,2,3-cd)pyrene

emission factors for PAHs (μg/km)

Gasoline PC & LDV (pre EURO) Gasoline PC & LDV (Euro I & later) Diesel PC & LDV (IDI)

Diesel PC & LDV (DI) HDV (DI)

(8)

Figure 2. Detailed road network of Rome Province

The network was divided into two parts, separating the network relating to Rome’s urban area from the rest of the province. The resulting grapho of Rome municipality was further divided in 5 concentric zones called “PGTU" (from Piano Generale del Traffico Urbano) to take into account the different characteristics of travel demand between the city centre and the surrounding areas, The following diagram (Figure 3) identifies with different colors the 5 mentioned areas within the city of Rome while the arcs outside the municipal boundary of the city are represented in black.

(9)

Figure 3. A graphical representation of Rome’s “PGTU zones” within: Rome Province (top panel) and zoomed over Rome city core (bottom panel).

(10)

Each arc is associated to traffic data calculated at the peak hour, specified as follows:

Unique arc identifier Name

Arc length

Number of light commercial vehicles from A to B Number of light commercial vehicles from B to A Number of HDV from A to B

Number of HDV from B to A

Number of passenger cars from A to B Number of passenger cars from B to A Number of motorbikes from A to B Number of motorbikes from B to A Average speed in the direction AB Average speed in the direction BA

(11)

Figure 4. Representation of hourly traffic volumes calculated by ATAC at the rush hour for the whole Rome Province (top panel) and zoomed over Rome city core (bottom panel).

The distribution of hourly movements of vehicles was calculated according to the mobility demand, built through telephone surveys and conducted on origin-destination (OD) shifts into the province.

This distribution is divided into 5 time periods of homogeneous vehicular flow:

Night time: from 0:00 to 5:00 (maximum between 4:00 and 5:00) End of morning rush: from 5:00 to 10:00 (peak between 8:00 and 9:00) Range of soft morning: from 10:00 to 15:00 (peak between 13:00 and 14:00) Evening peak times: from 15:00 to 20:00 (peak between 18:00 and 19:00) Range of soft evening: from 20:00 to 24:00 (peak between 20:00 and 21:00).

Starting from these data, modulation slots were reconstructed, allowing the daily, monthly and yearly calculation of emissions. The diagram in Figure 5 shows how the traffic volumes vary throughout the day in the urban area of Rome.

(12)

Figure 5. Time modulation of traffic emissions in Rome: week days (orange), Saturday and Sunday (green).

The above Figure shows a typical time evolution for large urban areas in Italy, with a very pronounced evening peak, which in this case is the daily maximum, and a secondary morning peak, lower but more extended in time. During early afternoon the traffic volume is reduced although it remains significant, because of many "unsystematic" movements of different nature (school exits, lunch, work, etc.), typical of large urban areas.

2.2.1 Rome Fleet

ACI (Automobile Club d’Italia) data concerning vehicles registered in the PRA (Pubblico Registro Automobilistico) for the municipality of Rome, on 31/12/2009, have been used to characterize the circulating fleet in the current scenario, in terms of COPERT categories.

This characterization of the traffic has to be corrected in the two areas where circulation is limited:

the Limited Traffic Zone (ZTL) and the area enclosed by the so-called Railway Ring (AF). Figure 6 displays the zoning. In AF area, access is prohibited to non-catalyzed passenger cars , from 00.00 to 24.00 on weekdays. In addition to this restriction, in ZTL circulation is allowed only to authorized vehicles (residents, goods vehicles, etc..) from 6.30 to 18.00 on weekdays and from 14.00 to 18.00 on Saturday.

0.00E+00 2.00E-01 4.00E-01 6.00E-01 8.00E-01 1.00E+00 1.20E+00 1.40E+00 1.60E+00 1.80E+00 2.00E+00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 hours

week days Sat and Sun

(13)

Figure 6. Limited traffic zones: city center ZTL (orange) and AF (blue)

To take into account these limitations, within this zones:

the presence of non-catalyzed vehicles was set equal to zero;

commercial vehicles distribution has been based on ATAC data previously used for the ITALIA project (Gariazzo et al., 2007).

Outside the municipality boundaries and on highways the fleet changes according to the differences in vehicles distribution in extra-urban areas.

(14)

3 Traffic emissions in the other provinces of Lazio Region

As there are no traffic flow data available for the other provinces of Lazio Region, outside Rome Province the traffic flows need to be assigned by using the transport model CarUSO (CAR Usage Optimization; http://www.aria-net.it/front/ENG/codes/files/6.pdf). The domain of interest for the study covers the whole territory of the Lazio Region, in which two different sub domains can be distinguished:

- the urban area of Rome and its Province, in which all the connections available in the GIS file (Straditalia, 2007) are considered ;

- a wider area including the territory of other provinces (Rieti, Viterbo, Latina and Frosinone) where only the main road categories (motorway and suburban) are kept, according to the hierarchical classification provided.

The model requires a description of the road network as input, including geometrical and functional data related to its elements (links and crosses) together with available vehicular data collected at some road sections. Traffic counts were carried out by three different authorities during the year 2009 (Figure 7):

- AISCAT, who provided the annual average value of daily vehicles circulating on Lazio highways;

- ASTRAL, who collected hourly traffic counting at 25 monitoring stations related to extra- urban roads;

- ATAC, who provided the circulating flows at the peak hour concerning the province of Rome, used as boundary condition for the simulation carried out over the remaining provinces.

(15)

Figure 7. Spatial distribution of traffic measuring sections

The traffic simulation is based on the hourly average vehicle flow at counting sections, for which reason the following steps were required:

- average the hourly data provided for each travel direction by ASTRAL ; - convert the mean daily values collected by AISCAT into hourly ones;

- turn the ATAC peak hour value into hourly mean data by applying a conversion coefficient equal to 0.6, which was obtained from time modulation referring to ASTRAL measurement campaign over Rome Province.

The CARUSO model evaluates traffic flows together with speeds on different links of the traffic network, as well as the number of origin/destination trips between different zones (see e.g. Figure 8).

(16)

Figure 8. Result of traffic assignment (vehicles/hour) over the main road network.

The quantified vehicular activity represents the input for the emission model and will be multiplied by proper emission factors (pollutant mass per trip unit) in order to obtain the total road vehicle emission from the main network.

The emission contribution from secondary roads was further estimated and aggregated into area sources, taking into account the estimated O/D values and the average distances travelled on the secondary network (Figure 9), according to an experimental methodology validated in many urban projects (Nanni et al., 2010; Nanni et al., 2011).

(17)

Figure 9. Selected area sources according to homogeneity of secondary road texture

As observed in previous case studies (Kaliningrad, Doha and Tunis) a good conventional average internal trip length for each zone (selected according to the homogeneity of the secondary network texture) is ¼ of the circumference of a circle having the same area (CCSA), which value is corrected with a proxy variable of road density corresponding to the square root of the total length of roads. The linear correlation between these quantities leads to the equation shown in Figure 10, where y represents the distance that vehicles travel on the secondary network inside each area, now influenced by zone extent as well as road density.

(18)

Figure 10. Linear regression model of 1/4 of the CCSA vs the square root of total length of secondary roads

Finally the total number of kilometers run by vehicles on the secondary network was estimated by combining the internal trip length and the aggregated O/D flux. It was found to be 3 times smaller than the total number of kilometers observed on the main network, which value already provides a first suggestion about the contribution of area sources to the total traffic emission. Later on, this result will be used as input for the emission model, considering an average speed equal to 30 km/h for vehicles running on secondary roads network.

y = 0.6254x + 3.043 R² = 0.9603

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

18.00 23.00 28.00 33.00 38.00 43.00 48.00

C/4 [km]

(sum(lenght))^0.5

(19)

4 Resulting traffic emissions in Lazio Region

The following Figures 11-12 show examples of different vehicles emissions calculated by TREFIC for all the zones described in the Chapter 3 and some of the most representative pollutants.

Figure 11. NOx emissions (Kg/Km²) associated to cars on homogenous traffic zones.

(20)

Figure 12. PM10 emissions (Kg/Km²) associated to heavy duty vehicles on homogenous traffic zones.

The following pictures describe NOx (Figure 13) and B[a]P (Figure 14) emissions calculated for linear sources using methodologies described in Chapters 2 and 3. Emissions refer to cars and heavy duty vehicles contribution.

The overall contribution to NOx emissions from cars and HDV is rather similar, with a prevalence of car traffic inside the main Rome ring and maximum HDV emissions on the ring and on the major motorways. The relatively minor contribution to B[a]P emissions from HDV, with respect to what observed for other pollutants like NOx, can be interpreted keeping into account both the emission factors and the number of circulating vehicles. Figure 1 shows that HDV have a B[a]P emission factor roughly triple of that of catalyzed gasoline cars and 40% larger of the new generation diesel cars one, but the number of circulating cars is much larger than that of HDV and it makes their contribution to B[a]P emissions more relevant, as shown in Figure 14. A larger contribution from HDV emissions is expected for benzo(b)fluoranthene and benzo(k)fluoranthene, due to their emission factors that are one order of magnitude larger than those of gasoline fired vehicles (Figure 1).

(21)

Figure 13. NOx emissions (ton/Km) associated to cars (left) and to heavy duty vehicles (right) over the entire Lazio Region road network.

Figure 14. B[a]P emissions (ton/Km) associated to cars (left) and to heavy duty vehicles (right) over the entire Lazio Region road network.

In order to create a dataset comparable with other available emission inventories and possibly to update or integrate them, the two types of traffic emissions (line and area sources) were combined and spatialized at the municipal level. The following Figures show the comparison of results obtained over Lazio Region respectively for NOx (Figure 15) and total PAHs (Figure 16) emissions.

It can be observed that PAHs emission from road traffic estimated for Rome municipality with bottom-up methodology is 29% lower that that estimated from 2005 national emission inventory, while NOx emission is slightly larger than that evaluated from the national inventory. For both pollutants an increase of emission for the municipalities located all around Rome borders is produced by the bottom-up method, possibly due to a more realistic evaluation of commuting traffic

(22)

Figure 18 shows the road traffic emissions for all the congeners included in COPERT IV and estimated by TREFIC emission model. Those data cannot be compared with other evaluations because the congeners covered are not included in any available national or international inventory. However a phase of validation based on fuel consumption has been performed, which relies on the comparison between modeling results and real fuel sales data.

Figure 15. NOx emissions (ton/year) from all type of vehicles from 2005 ISPRA national inventory downscaled at municipal level (left) and estimated from 2009 road network traffic

flows spatialized at the municipal level (right).

Figure 16. Total PAHs emissions (Kg/year) from all type of vehicles from 2005 ISPRA national

(23)

Figure 17. PAH main congeners emissions (tons/year) over Lazio Region estimated from 2005 ISPRA national inventory and computed by TREFIC from 2009 road network traffic flows.

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20

ISPRA2005 TREFIC2009

t/anno

Indeno-123cd-pyrene

Benzo-a-pyrene

Benzo-k-fluoranthene

Benzo-b-fluoranthene

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00

ISPRA2005 TREFIC2009

t/anno

benzo_ghi_pe benzo_e_pyre chrysene pyrene fluoranthene dibenzo_ah_a benzo_j_fluo benzo_a_anth Indeno-123cd-pyrene Benzo-a-pyrene Benzo-k-fluoranthene Benzo-b-fluoranthene

(24)

The comparison has been carried out for each province separately and the non-homogeneity of results in the individual provinces can be attributed to the different spatial distribution of initial traffic data. However they show an overall slight underestimation of the calculated global emissions, as the calculated fuel consumption represents 87% of total sales. This result is considered satisfactory because the remaining 13% can be related to the contribution of trips not intercepted by the main network and to the model inability to consider traffic flows where source and destination correspond (because of the modeling discretization). The validation results are shown in Table 2

Table 2: Fuel consumption comparison between fuel sales and model estimations Provinces Estimated/Sold Fuel

Viterbo 95.4%

Rieti 132.1%

Frosinone 87.3%

Latina 40.2%

Rome 81.8%

MEAN 87.3%

(25)

5 Revision of Lazio Regional emission inventory

The starting point of the construction of Lazio regional inventory is the National municipal level inventory downscaled from ISPRA2005 (hereby named INCOM05); this database contains information about all Italian municipalities at the activity level, considering emissions from different sources (point and area).

To update 2005 data to 2009, ISPRA national historical trends has been used, specified for sectors and pollutants (see e.g. Figure 19 for PAHs trend). For different pollutants, emissions at national level have been considered, and from these data a specific multiplier (positive or negative) was estimated. Where data weren’t available, coefficients were defined equal to one, in order to maintain emissions constant. In this way 2005 emissions were multiplied getting ready to be the input for the air quality simulation.

Figure 19. Example of historical series (PAHs) used to update INCOM05 inventory.

An important improvement in the knowledge of emissions generated in Lazio region is the collection and updating of point source database made by ARPA Lazio: about 120 point sources (Figure 20, reference year 2009) have been characterized both from a physical point of view and for the emissions produced.

0 10000 20000 30000 40000 50000 60000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

kg/year

Energy Production Comb in Residential

Comb.in Industry Prod. Processes

Solvent Use Road Transport

Other Transport & Mobile Machinery Waste Treatment

(26)

Another important improvement concerns the Civitavecchia Port, whose emissions were estimated starting from ship movements recording.

The emissions produced by navigation are a consequence of fuel burning in an internal combustion (marine) engine. Consequently, the principal pollutants concerned are: CO, VOC, NOx and PM derived from soot, which is mainly related to the engine technology, and CO₂, SOx, heavy metals and further PM (mainly sulphate-derived) which originates from the fuel composition (EEA,2009). The methodology employed considers the movement of every ship. It has been possible to use this approach thanks to the availability of detailed ship movement data and knowledge of time spent in the different activities, while technical information on the ships features (e.g. engine size and technology, power installed or fuel use) were not available and the hypothesis of the methodology employed based on literature data have been retained and applied.

As it has been mentioned in the executive summary chapter, road transport is surely the sector for which PAHs emissions have been evaluated in a very detailed way, but there’s another source sector very relevant for PAHs emissions whose contribution has been re-evaluated carrying to interesting differences from INCOM05 dataset: residential heating.

From information coming from different studies and datasets it has been possible to give a different space distribution to different fuels consumption, and this aspect has a great importance for its influence on biomass burning emissions of PM, NMVOC and PAHs.

The most important sources of information used in this evaluation are:

Province detailed emissions by fuel type for year 2005;

Fuels sales for year 2005;

Fuels sales for year 2009;

Methane network served municipalities;

Wood use for house heating data from the project “Stima dei consumi di legna da ardere per riscaldamento ed uso domestico in Italia” (Caserini et al., 2008)

Data concerning fuel selling are provided by the Ministry of Economic Development, that reports information at Province level (Tables 3 and 4) These data allowed to update the emissions produced by LPG, natural gas and diesel fuel with a satisfactory detail.

Table 3: Fuel sold in Lazio Region in 2005 (source: Ministry of Economic Development)

(27)

Table 4: Fuel sold in Lazio Region in 2009 (source: Ministry of Economic Development)

For other fuels this kind of information is not available. For wood, which is the major producer of PM, NMVOC and PAHs emissions, the only information available at regional level is the analysis produced by ARPA Lombardia and APAT project “Stima dei consumi di legna da ardere per riscaldamento ed uso domestico in Italia” (Caserini et al., 2008); from this study the amount of wood used within Lazio Region for year 2007 is estimated to be 1707416 tons, and this value has been kept constant for year 2009. In the same way, due to the lack of updated or more detailed information, emissions produced by waste and other fuels have been kept constant in time.

Differently from all others sectors, emissions produced by domestic heating have been upgraded at provincial level, and later distributed at municipal level using the new procedure resumed in the following.

First of all municipalities not reached by methane supply have been excluded from methane distribution and their heating needs have been covered with other fuels (Figure 21).

(28)

Following the methodology described in ARPA Lombardy study (Caserini et al., 2008), as a second step, municipalities were subdivided in three altimetric zones (Figure 22); wood consumption has been distributed keeping into account the topographic height of municipalities using results produced by the mentioned study on wood burning for house heating for different topographic conditions.

Figure 22. Non industrial combustion – altimetric zones.

Mountain Hill

Plain

(29)

6 Emission input

The emission input for air quality modelling has been prepared with the complex approach described in the previous sections: integrating the bottom-up evaluation of traffic emissions with INCOM 2005 inventory supplemented with complementary data concerning residential combustion and ports activities. Results are summarized in Figure 23 and 24 for the whole Lazio Region and Rome Province. For all PAHs species the most important source is residential heating, that produces an average of 75% of total emissions for Lazio Region (Figure 23, emission sectors absolute contribution). Looking at the different congeners emission, the contribution of residential combustion to Benzo[a]pyrene is 69% while it reaches the 78% for Benzo[b]fluoranthene and Benzo[k]fluoranthene. Waste treatment emissions represent the 21% of total PAHs but its contribution varies very much with the different species: it gives the 29% of total B[a]p and the 18%of B[b]f. Looking at Figure 24, related only to the Province of Rome, it’s possible to stress the increase of non industrial heating contribution that reaches an average contribution of 87%, varying from the 84% of B[a]p to the 89% of B[b]f total emissions. The contribution of Road Transport is almost the same, in absolute terms, over the Region and the Province domains, probably because the largest part of Lazio Region road network of is concentrated around (and within) the city of Rome.

200 400 600 800 1000 1200 1400 1600 1800 2000

kg/year

Nature

Agriculture Forestry & Land Use Change Waste Treatment

Other Transport & Mobile Machinery Road Transport

Solvent Use

Extraction Fossil Fuels Prod. Processes Comb.in Industry Comb in Residential Energy Production

(30)

Figure 24. Province of Rome: PAHs emissions (kg/year) from all type of sources.

7 Model ready hourly gridded emissions

In order to prepare model-ready emission inputs, the processing system Emission Manager (EMGR) has been used (Calori et al., 2007; Finardi et al., 2008).

The area sources coming from the different databases described above have been ingested to be disaggregated on the target grids with use of thematic layers. Spatial disaggregation is performed intersecting the emission polygons (municipalities or provinces boundaries) with the target simulation grids (see e.g. Figure 25 for the Lazio Region computational domain with 4 km space resolution): for each polygon, emissions are partitioned according to the portion of the grid cell area that overlaps the area of the emission polygon. Such partition can be optionally weighted by the information contained in a gridded thematic layer, specifying for each cell the percentage of the area occupied by a selected feature (an example for built-up areas is given in Figure 26 for both target grids). Different thematic layers have been employed for each emission category. Areas indicated in Figure 25 have been employed to distribute the major influence of ports activities.

Along with spatial disaggregation, chemical species splitting/speciation have been performed for the following “splitting schemes”:

PAH speciation according with EMEP/CORINAIR Emission Inventory Guidebook 2009 NMVOC speciation according with SAPRC99 scheme

PM speciation according with aero3 scheme PM subdivision in dimensional classes NOx split into NO and NO

0 200 400 600 800 1000 1200

B[a]P B[b]F B[k]F indeno

kg/year

Nature

Agriculture Forestry & Land Use Change Waste Treatment

Other Transport & Mobile Machinery Road Transport

Solvent Use

Extraction Fossil Fuels Prod. Processes Comb.in Industry Comb in Residential Energy Production

(31)

Figure 25. Polygons associated to emissions. Red lines enclose the areas interested by port’s activities for Lazio Region.

(32)

Figure 27. Regional averaged temporal modulations for domestic heating (SNAP sub-sector 0202).

The following Figures panels show the gridded emissions for PAHs and other pollutants. Plotted values refer to total yearly emissions or emission fluxes.

0 0.5 1 1.5 2 2.5 3

Gen Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Monthly Modulation

Domestic Heating

0 0.2 0.4 0.6 0.8 1

Mon Tue Wed Thu Fri Sat Sun

Weekly Modulation

Domestic Heating

0 0.5 1 1.5 2 2.5 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hourly Modulation

Domestic Heating

(33)

largest mass is emitted for Benzo[b]fluoranthene and Benzo[a]pyrene, as expected from total emissions over Rome Province (Figure 24). Figure 29 shows total PAHs (the sum of the four congeners included in the emission inventory) emission for Lazio Region and Rome metropolitan area computational domains. The concentration of emissions inside and around Rome city is the more relevant feature of the mentioned emission maps. The contribution of transport emission is more evident for other pollutants as PM10, PM2.5 and NO (Figure 30) for which e.g. the contribution of Rome main ring (Grande Raccordo Anulare) is responsible of the maximum per cell emission values. Benzene emissions (Figure 30) allow to identify the contribution of ports and airports activities.

Benzo[a]pyrene

Mg/year

Benzo[b]fluoranthene

Benzo[k]fluoranthene indeno[1,2,3-cd]pyrene

(34)

TOTAL PAHs (Mg/m²/year)

Figure 29. gridded emitions fields for PAHs at 4km (left) and 1km (right) resolution (Mg/m²/year).

PM10 PM25

NO BENZENE

(35)

8 Conclusions

A reference pollutants emission inventory including PAHs with municipal reference resolution has been built for Lazio Region. The reference emission inventory INCOM2005, previously upgraded to include the description of PAH congeners (Radice and Finardi, 2011), has been updated to the reference year 2009 and upgraded for different source sectors for Lazio Region: residential combustion, ports activities, road transport and point sources.

The space distribution of residential heating emissions has been reallocated at municipal level on the basis of information about Lazio Region municipalities reached by natural gas distribution and data concerning fuels sold in the different Provinces during years 2005 and 2009. Published studies concerning investigations on biomass burning for residential heating have been used to support the evaluation and space distribution of this fuel consumption, that has a major relevance for PM, VOC and PAHs emission. Civitavecchia port activity emissions has been evaluated starting from data concerning ship movements. Industrial emissions (point sources) have been updated to year 2009 on the basis of a survey provided by ARPA Lazio.

PAHs and other pollutants emission from road transport have been estimated on the basis of COPERT IV methodology from traffic fluxes on Lazio Region road network. Vehicle fluxes on each road link have been evaluated from observed traffic data and by means of a traffic assignment model representing the traffic flows on the road network (data provided by Rome Mobility Agency).

This has been the first experience of estimation of PAHs emission in a large conurbation using a bottom-up approach and is one of the innovative tasks of the EXPAH project.

The improved emission inventory for Lazio Region allowed to produce high resolution gridded emission data sets over the target areas of EXPAH project modelling program: Lazio Region (4 km resolution grid) and Rome metropolitan area (1 km resolution grid).

PAHs emission from road transport can be therefore considered estimated with the more detailed and updated methodology presently available. A larger uncertainty has to be considered associated to residential heating sources, which are by far the major contribution to PAHs emission. No data is presently available about wood sales in Lazio Region and it has to be considered that the procurement of wood for house heating for a large fraction works out of the market including direct gathering and non-commercial supplies. Nonetheless the improved inventory realized can be considered the best possible estimation with data and methodologies presently available for the considered area.

(36)

9 References

BUWAL (1994). Emissionfaktoren ausgewählter nichtlimitierter Schadstoffe des Strassenverkehrs, CD Data Version 2.2.

Calori G., Finardi S., Nanni A., Radice P., Riccardo S., Bertello A. and Pavone F. (2008) Long-term air quality assessment: modeling sources contribution and scenarios in Ivrea and Torino areas", Environmental Modelling and Assessment, 13, 329–335.

Caserini S., Fraccaroli A., Monguzzi A., Moretti M., Angelino E. (2008) Stima dei consumi di legna da ardere per riscaldamento ed uso domestico in Italia, Rapporto ARPA Lombardia e APAT, ISBN 978-88-448-0346-9, available at:

http://www.apat.gov.it/site/it-it/apat/pubblicazioni/altre_pubblicazioni.html.

EEA, 2009: EMEP/EEA Air Pollutant Emission Inventory Guidebook 2009, Last update march 2011, http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009

Finardi, S., De Maria, R., D’Allura, A., Cascone, C., Calori, G., and Lollobrigida, F., (2008) A Deterministic Air Quality Forecasting System For Torino Urban Area, Italy. Environmental Modelling and Software, 23, 344-355.

Gariazzo, C., C. Silibello, S. Finardi, P. Radice, A. Piersanti, G. Calori, A. Cecinato, C. Perrino, F.

Nussio, M. Cagnoli , A. Pelliccioni, G.P. Gobbi, P. Di Filippo, 2007: A gas/aerosol air pollutants study over the urban area of Rome using a comprehensive chemical transport model. Atmos.

Environ., 41, 7286-7303.

IIASA (2006). RAINS-Europe Homepage. http://www.iiasa.ac.at/rains/Rains-online.html.

IIASA (2002). Modelling Particulate Emissions in Europe. Interim Report IR-02-076.

Nanni., A., Radice, P., Piersanti, A. (2005) TRaffic Emission Factor Improved Calculation (TREFIC). User manual - Version 4.0, ARIANET R2005.02, Milan, Italy.

Nanni A., Velay-Lasry F., Eriksson E., Soudani A., Abid S. (2010) Bottom-up road traffic emission calculation for the Tunisian road network. 13th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, 1-4 June 2010, Paris, France.

Nanni A., Pozzi C., Eriksson E., Lungu P. (2011) Bottom-up road traffic flows and emissions calculation for the assessment of future traffic scenarios and public transportation expansion plans in Bucharest and Romania. 14th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purpose. 2-6 October 2011, Kos Island, Greece.

Ntziachristos L., Samaras Z. (2009) Methodology for the calculation of exhaust emissions. SNAPs

(37)

StradItalia; CSH/Istituto Geografico DeAgostini, http://www.csh.it, 2007.

Rijkeboer R. C., and Hendriksen P. (1993) Regulated and Unregulated Exhaust Components from LD Vehicles on Petrol, Diesel, LPG and CNG, TNO-report 93.OR.VM.029-1-PHE-RR.

Volkswagen AG (1989). Nicht limitierte Automobil-Abgaskomponenten, Wolfsburg, Germany.

(38)

10 Appendix

Table A1: Mapping between COPERT emission factors and vehicle categories

Vehicle category Type of PAH emission factor

1 Passenger Cars Gasoline <1,4 l PRE ECE Gasoline conventional

2 Passenger Cars Gasoline <1,4 l ECE 15/00-01 Gasoline conventional

3 Passenger Cars Gasoline <1,4 l ECE 15/02 Gasoline conventional

6 Passenger Cars Gasoline <1,4 l Improved Conventional Gasoline conventional

7 Passenger Cars Gasoline <1,4 l Open Loop Gasoline conventional

8 Passenger Cars Gasoline <1,4 l PC Euro 1 - 91/441/EEC Gasoline EURO I & on 9 Passenger Cars Gasoline <1,4 l PC Euro 2 - 94/12/EEC Gasoline EURO I & on 10 Passenger Cars Gasoline <1,4 l PC Euro 3 - 98/69/EC Stage2000 Gasoline EURO I & on 11 Passenger Cars Gasoline <1,4 l PC Euro 4 - 98/69/EC Stage2005 Gasoline EURO I & on 12 Passenger Cars Gasoline <1,4 l PC Euro 5 (post 2005) Gasoline EURO I & on

13 Passenger Cars Gasoline 1,4 - 2,0 l PRE ECE Gasoline conventional

14 Passenger Cars Gasoline 1,4 - 2,0 l ECE 15/00-01 Gasoline conventional

15 Passenger Cars Gasoline 1,4 - 2,0 l ECE 15/02 Gasoline conventional

18 Passenger Cars Gasoline 1,4 - 2,0 l Improved Conventional Gasoline conventional

19 Passenger Cars Gasoline 1,4 - 2,0 l Open Loop Gasoline conventional

20 Passenger Cars Gasoline 1,4 - 2,0 l PC Euro 1 - 91/441/EEC Gasoline EURO I & on 21 Passenger Cars Gasoline 1,4 - 2,0 l PC Euro 2 - 94/12/EEC Gasoline EURO I & on 22 Passenger Cars Gasoline 1,4 - 2,0 l PC Euro 3 - 98/69/EC Stage2000 Gasoline EURO I & on 23 Passenger Cars Gasoline 1,4 - 2,0 l PC Euro 4 - 98/69/EC Stage2005 Gasoline EURO I & on 24 Passenger Cars Gasoline 1,4 - 2,0 l PC Euro 5 (post 2005) Gasoline EURO I & on

25 Passenger Cars Gasoline >2,0 l PRE ECE Gasoline conventional

26 Passenger Cars Gasoline >2,0 l ECE 15/00-01 Gasoline conventional

27 Passenger Cars Gasoline >2,0 l ECE 15/02 Gasoline conventional

30 Passenger Cars Gasoline >2,0 l PC Euro 1 - 91/441/EEC Gasoline EURO I & on 31 Passenger Cars Gasoline >2,0 l PC Euro 2 - 94/12/EEC Gasoline EURO I & on 32 Passenger Cars Gasoline >2,0 l PC Euro 3 - 98/69/EC Stage2000 Gasoline EURO I & on 33 Passenger Cars Gasoline >2,0 l PC Euro 4 - 98/69/EC Stage2005 Gasoline EURO I & on 34 Passenger Cars Gasoline >2,0 l PC Euro 5 (post 2005) Gasoline EURO I & on 35 Passenger Cars Diesel <2,0 l Conventional IDI Diesel PC & LDV 36 Passenger Cars Diesel <2,0 l PC Euro 1 - 91/441/EEC IDI Diesel PC & LDV 37 Passenger Cars Diesel <2,0 l PC Euro 2 - 94/12/EEC DI Diesel PC & LDV 38 Passenger Cars Diesel <2,0 l PC Euro 3 - 98/69/EC Stage2000 DI Diesel PC & LDV 39 Passenger Cars Diesel <2,0 l PC Euro 4 - 98/69/EC Stage2005 DI Diesel PC & LDV 40 Passenger Cars Diesel <2,0 l PC Euro 5 (post 2005) DI Diesel PC & LDV 41 Passenger Cars Diesel >2,0 l Conventional IDI Diesel PC & LDV 42 Passenger Cars Diesel >2,0 l PC Euro 1 - 91/441/EEC IDI Diesel PC & LDV 43 Passenger Cars Diesel >2,0 l PC Euro 2 - 94/12/EEC DI Diesel PC & LDV 44 Passenger Cars Diesel >2,0 l PC Euro 3 - 98/69/EC Stage2000 DI Diesel PC & LDV 45 Passenger Cars Diesel >2,0 l PC Euro 4 - 98/69/EC Stage2005 DI Diesel PC & LDV 46 Passenger Cars Diesel >2,0 l PC Euro 5 (post 2005) DI Diesel PC & LDV

47 Passenger Cars LPG Conventional LPG

48 Passenger Cars LPG PC Euro 1 - 91/441/EEC LPG

49 Passenger Cars LPG PC Euro 2 - 94/12/EEC LPG

50 Passenger Cars LPG PC Euro 3 - 98/69/EC Stage2000 LPG

51 Passenger Cars LPG PC Euro 4 - 98/69/EC Stage2005 LPG

52 Passenger Cars LPG PC Euro 5 (post 2005) LPG

53 Passenger Cars 2-Stroke Conventional Gasoline conventional

54 Light Duty Vehicles Gasoline <3,5t Conventional Gasoline conventional 55 Light Duty Vehicles Gasoline <3,5t LD Euro 1 - 93/59/EEC Gasoline EURO I & on 56 Light Duty Vehicles Gasoline <3,5t LD Euro 2 - 96/69/EEC Gasoline EURO I & on 57 Light Duty Vehicles Gasoline <3,5t LD Euro 3 - 98/69/EC Stage2000 Gasoline EURO I & on 58 Light Duty Vehicles Gasoline <3,5t LD Euro 4 - 98/69/EC Stage2005 Gasoline EURO I & on