Airport Local Air Quality Studies (ALAQS):
Perspective for Airport Emissions and Dispersion “Lyon Pilot Study”
Ayce Celikel
Serge Peeters
Marcel Silue
1 Abstract / Summary
The study aims to address strategic, methodological and practical issues surrounding air quality assessment around airports and will provide guidance for airports and practitioners regarding best practice methodology and supporting toolset that can be applied at Pan-European level. The methodology consists of developing Pan-European emission inventory methodology and prepare for the future development of application of dispersion modeling.
This paper provides an overview of why and how we are conducting local air quality studies around airports and describe the methodologies and pilot study used for this purpose. It shows the results achieved during the year 2003 for harmonized emissions inventory methodology and gives indications for the under-going and future work for dispersion modeling.
Topic Area:”F4 Transport and the Environment: Air Quality, Noise and Local Impacts”
2 Introduction
Local air quality at airports is an increasingly important issue for airports operators, particularly in Europe, where national and international air quality directives and strategies are requiring detailed assessments of impacts. At the local level, airports are working alongside regional partners and stakeholders to assess the contribution of airport emissions on local air quality and developing management strategies and plans.
Airports across Europe have to be aware of their responsibility to work with key regional partners in the assessment of aviation-induced impacts on local air quality. For an individual airport this will require a detailed understanding of emission sources and strengths and an appreciation of source receptor relationships.
Main issue for an airport is generally to find out <1>:
• The annual (or for specific period) pollution of a certain substance caused by the operation of the airport (air traffic, infrastructure/handling and induced landside traffic) at any given location in the vicinity of the airport.
• The contribution to the total pollution.
• The expectation in the future, given some development scenario.
In Europe there is not any standardised European approach for such studies and there are some uncertainties about the accuracy or the consistency of the data used. For example for emission inventories it is important to gather all the necessary information about the pollution sources, their operations and, appropriate emission factors. Therefore the aim here is to identify all those deficiencies and harmonisation of the approach using existing European data and methods.
Typical air quality assessment; consist of emission inventory and spatial allocation, dispersion modelling, determination of background concentration and, visualization of the results. Similarly, our methodology consists of developing Pan-European emission inventory methodology with spatial information and future application of dispersion modelling to this inventory with use of GIS technologies. Hence the toolset and database to support ALAQS of European airports are:
• Pan-European ALAQS central databank for emission factors of different sources: All related emissions factors for different pollution sources are defined and aggregated from different sources and harmonised in Access database. This will provide the opportunity to change or compare different emissions factors used for the same type of sources.
• Scaleable approach for developing emission inventory and dispersion modelling Considering that there are several methods and models to conduct air quality studies, the initiative is to find best practice approach and validate with real airport data. Besides the air traffic emissions methodology, other airport related source emission methodologies as well, have been developed (such as Roadway Traffic, GSE, Stationary Sources etc.).
• ALAQS-AV GIS application. Optional interface to GIS software will allow:
1. The capture of the data i.e. spatial location and attributes
2. Testing and implementing different methods to calculate emissions by means of Emission Toolbox
3. Option to use emission factors from different sources
4. Preparing emission sources for dispersion modelling
5. Importing/exporting data to and from different models
6. Importing and analysis of dispersion results
7. Calculation of emission for gates, taxiways and runways based on aircraft LTO cycles.
8. Improved data capture interface
During the building of the databank various data and information are gathered from our stakeholders. To explore the practical issues and validation of the methodology with real data, we used Lyon Airport as a pilot study.
Pilot Study
Pilot study gave us the opportunity to evaluate the applicability of the methodology through the use of real airport case study (Lyon Airport) and actual airport data. The investigation also assess how data available to airports or their consultants can be used in a consistent way, with necessary quality controls, to develop inventories that may then be evaluated at a European level.
For future work it is our intention to use selected dispersion model(s) to compare modelled concentrations of pollutants with on site measurements, for given meteorological conditions. This will include for a selected scenario; with the use of GIS application, visualisation of the evolution of the pollution plumes through the selected period. Combination of features such as buildings, roads, protected land and demographics will be integrated to pollution maps. With such modelling we will be able to define the significance of the pollution contribution of the different sources and compare with each other (i.e. roadway emissions versus air traffic emissions).
3 ERC ALAQS Methodology Outline
In order to estimate air polution due to airport operations, we first need to quatify the emission generated by each source then use a dispersion model to find the plume concentration (this will come at a later stage of the project).
For each airport pollution source, the method to calculate emissions is identified. Where more than one calculation method is in use the activity data requirements for the alternative methods are also included in the approach.
The current approach is to use different emission methodologies and emissions factors data and harmonised them in to ALAQS toolset.
3.1 Aircrafts Emission methodology
Flight operations encompass the entire landing and take-off (LTO) cycle as defined by the ICAO. Emissions of each aircraft type are computed by knowing the emission factors for the aircraft’s specific engines at each power setting or mode of operation and the time spent in each mode.
In ALAQS-AV methodology for a specific scenario, aircraft movements table is prepared for this specific period. For each movement: date, time, aircraft type, arrival/departure flag, gate (stand) and runway are specified. ALAQS-AV toolset uses the movements table to calculate hourly emissions at gates, taxiways, queues and runways.
Aircraft exhaust emissions are calculated for the following operating modes.
• Engine Start
• Taxi in and taxi out (TX, 7% thrust )
• Queuing (TX, 7% thrust)
• Approach (AP, 30% thrust)
• Landing roll (AP, 30% thrust)
• Takeoff roll (TO, 100% thrust)
• Climb-out (CL, 85% thrust)
Except for engine start emissions - aircraft engine emissions during a particular operating mode of the Landing and Take-Off (LTO) cycle are given by the product of the time-in-mode, the fuel flow rate and the emission index for the appropriate engine thrust setting engaged. Data is extracted from the system database. (i.e. aircraft-engine combination, number of engines etc..)
| ACe = FFmode * EFmode * T * N |
| ACe | Aircraft total engine emissions |
| FFmode | Fuel flow rate (kg/s) per engine in mode |
| EFmode | Emission factor (kg/kg) per engine in mode |
| T | Time-in-mode (s) |
| N | Number of engines |
3.1.1 APU / GPU
APU (Auxiliary Power Units) are on-board generators in larger aircrafts that provide electrical power while its engines are shut down (For example when the aircraft is parked away from the terminal building), GPU (Ground Power Units) are mobile diesel powered units that provide power to an Aircraft. Those are operated on mostly gates. Therefore emission calculation for APU/GPU is integrated to the gate emissions calculations.
Start emissions are the Volatile Organic Compounds (VOC) emitted when the aircraft engines are started before departure.
The amount of emission released by GSE, APU and GPU are a function of aircraft size and type of stand. However, VOC emissions released at engine start are a function of the aircraft class only.
For APU and GPU an emission rate (grams per minute) is specified. The total GPU and APU emissions are obtained by multiplying the running time in minutes specified for arrival or departure with the emission rate.
For engine start emissions a total amount of HC (VOC) emissions (grams per aircraft) is specified.
Calculation Method:
1. For each hour get all aircraft movements and regroup movements by gate.
2. For each gate:
• Get aircraft group from aircraft system table.
• Get gate scenario from project gate shapefile.
• Get scenario emission parameters for aircraft group from project gate scenario table.
• Calculate GSE, APU, GPU and Start emissions.
• Add emissions to gate totals.
3. Store each gate total in hourly emissions table.
3.1.2 Taxiway Emissions
Taxiway emissions are released by aircraft engines while an aircraft travels from gate to runway and vice versa. Emissions are calculated on the assumption that all engines are idling on a 7% (ICAO settings) power thrust setting (mode TX).
For taxiway emissions, a more refined approach is implemented. Instead of allocating fix idle times to all aircraft (such as in ICAO database), for each aircraft movement and gate scenario taxi routes are defined. Based on taxi speed, total taxiing times are calculated. Then from aircraft –engine emission table emission factors for idle phase is extracted to calculate taxiing emissions.
In ALAQS-AV taxi routes between gates and runways are selected automatically from the user-defined taxi routes based on the end roll position. The end roll position is the sum of the arrival profile’s landing roll and the touchdown offset specified for the runway. The selection of taxi route is thus done on four criteria: Gate, Runway, Arrival/Departure flag (A or D) and End Roll Position. For a gate-runway combination the end roll position is compared to the routes’ exit positions. The route corresponding to the exit position situated immediately ahead of the end roll position is selected.
Engine Emission Indices or obtained from the Engine Table based on Engine ID and Aircraft Mode (taxi mode = TX).
Taxi Times are obtained from the Taxiway Shapefile and emissions.
For each taxiway, calculated hourly emissions totals are stored in the Hourly Emission table.
3.1.3 Queue Emissions
Flights incur at some percentage of the delay on the ground during the departure process between their schedule departure from the gate and take-off. This cause queuing at the runways and has to be calculated for their emissions.
Queue emissions are emissions released by aircraft on the last taxiway section before entering the runway for take-off. In ALAQS-AV the amount of time an aircraft spends in the queue is a function of the maximum queue velocity, the maximum queue time and the number of departures that can be handled by the runway.
Queue time per aircraft at selected hour:
| Nk < Nmax | Nk > Nmax |
| Qtk = Qtmin + (Qtmax - Qtmin)(Nk / Nmax) p | Qtk = Qtmax |
| Qtk | Queue time at hour h | Queue time at hour h |
| Qtmax | The maximum queue time | Maximum holding time observed for a runway at maximum capacity |
| Qtmin | Minimum queue time | Queue length / maximum queue velocity(i.e. the aircraft does not have to wait before accessing the runway) |
| Nmax | Runway capacity | Maximum number of departures that can be handled by the runway |
| Nk | Departure count | Total number of departure for hour h (obtained from movements table) |
| p | Exponential factor (p=2) | Controls the shape of the queue time curve. The queue time increases faster with increasing traffic |
Those queuing parameters are extracted in ALAQS-AV tool. Engine emissions are calculated on the assumption that all engine are idling on a 7% power thrust setting. Emission Indices are obtained from the engine table based on Engine ID and Aircraft Mode (taxi mode = TX).
Calculation Method:
1. For each hour get all aircraft departures.
2. For each hour process each departure one at a time.
a. Count the number of departures and calculate the queue time.
b. From movements table get Aircraft Type and Runway.
c. From aircraft table get Engine ID and Engine Count.
d. From engine table get Engine Emission Indices.
e. For each queue calculate emissions and add to queue totals.
3. Store each queue total in hourly emissions table.
3.1.4 Runway Emissions
Runway emissions are emissions released by aircraft on or above the runway during takeoff roll, climb-out, approach and landing roll. Conventionally runway emissions for inventory purpose are calculated up to an elevation of 3000ft (914.4m) above the runway. However, emissions released above an elevation of 400m above the runway have little impact on the air quality at ground level.
In ALAQS-AV the maximum elevation for which emissions are calculated is determined by the parameters specified for the runway space in the merge system file. The runway space is subdivided into blocks; the maximum elevation is the sum of the block-rows heights. However, the maximum elevation cannot be higher than the highest point of the aircraft profiles.
Figure 1.Runway space subdivided in three block bands
Calculation Method:
- For each hour get Aircraft Type, Runway and Arrival/Departure flag from movements table.
- From aircrafts table get for each aircraft Arrival Profile ID, Departure Profile ID, Engine ID and Engine Count.
- Based on Runway and Profile ID get profile segment data (Time-in-mode and Mode) from runway space table.
- From engine table get Engine Emission Indices based on Engine ID and Mode (takeoff [TO], climb-out [CL] or approach [AP]).
- For each segment calculate emissions and add runway space block totals.
- Store each block total in hourly emissions table (hr_emis).
Runway emissions include also runway roll emissions (takeoff roll and landing roll) and emissions released in the vertical plane above the runway (climb-out and approach).Additionally there is a pre-processor which intersects profile trajectories with runway space blocks.(See user manual for more detail information)
Figure 2.Runway Emission Calculation Process
3.2 GSE Emissions Methodogy
GSE emissions correspond to pollutants released by support equipment while an aircraft is standing still at an aircraft stand e.g. emissions released during loading, unloading or refueling. GSE emissions are generated at the gate area before an aircraft leaves the stand or after it parks at the gate. Emission released by support equipment travelling from one point to the other on defined routes on the apron should be treated as roadway emissions (airside traffic).
For GSE emissions in ALAQS-AV tool, total amounts of emission per aircraft (grams per aircraft) are specified. These emissions are split between departures and arrivals according to a specified percentage (e.g. 60% arrival and 40% departure).
The GSE emission estimation is implementade as a stand alone tool. Emission factors for GSE are aggregated from different sources such as EDMS, STNA, Zurich Airport. LASPORT, EEC EUNRMM etc.. <9>
In this study data from EC Non Road Mobile Machinery (EEC EUNRMM Stage 1 and 2 - emission factors provided by Perkins Powerpart, through Mineli, CH-Paffikon, 30.7.1999) was used. <10>
• Load Factor
• Power in kW
• Operating time
• Emission indices (g/kW-hr)
Table 1. EC Non Road Mobile Machinery (EEC EUNRMM Stage 1) Emission Factors
| g/kW-hr | Power Band | CO | HC | NOx | PM | Introduction |
| Stage 1 | 37-75 kW | 6.50 | 1.30 | 9.20 | 0.85 | 1 April 1999 |
| 75-130 kW | 5.00 | 1.30 | 9.20 | 0.70 | 1 January 1999 | |
| 130-650 kW | 5.00 | 1.30 | 9.20 | 0.54 | 1 January 1999 | |
| Stage 2 | 18-37 kW | 5.50 | 1.50 | 8.00 | 0.80 | 1 January 2001 |
| 37-75 kW | 5.00 | 1.30 | 7.00 | 0.40 | 1 January 2004 | |
| 75-130 kW | 5.00 | 1.00 | 6.00 | 0.30 | 1 January 2003 | |
| 130-560 kW | 3.50 | 1.00 | 6.00 | 0.20 | 1 January 2002 |
Figure 3.ALAQS GSE Tool Overview
Theoretically emissions calculation for GSE equipment is <2>:
| Eit = (Power of equipmentt * LFt * Ut * EIit) |
Eit Emission of pollutant I
LFt Load factor
Ut Hours of use
EIit Emission index for pollutant I, which is specific to a given engine size and fuel type
i Pollutant Type
t Equipment Type
For all different GSE types there is an option to choose different emission factors from the database.
3.3 Roadways methodology/Airport Landside Traffic <3>
Emission source calculation methodologies are necessary to estimates the amount of emission generated by airport activities such as air traffic, handling, infrastructures and land side traffic. Modelling of road traffic emission can accomplished using CITEPA, COPERT III and the German/Swiss Scenario method. The CITEPA methodology has the advantage of being specially developed for airports. The different sub-categories of vehicle defined in the COPERT methodology are grouped in eight or so aggregated categories
• The gasoline, diesel or LPG passenger cars (PC)
• The gasoline or diesel light duty vehicle (LDV)
• The gasoline or diesel heavy duty vehicles (HDV)
• The buses and coaches
This method is straightforward but introduces inaccuracies because the aggregated emission factors are obtained by averaging the COPERT emission factors.
The COPERT methodology is very detailed. The vehicle sub-categories are given in the vehicle category split table. The COPERT methodology can be adapted to produce good airport emission estimation. However, it is very difficult to classify the vehicle driving in and out an airport according to the detailed COPERT sub-categories. This is because all the statistics required by the method are not ready available.
The aim here is to use the COPERT III methodology to elaborate a road traffic emission method around airports.
In the ALAQS roadways methodology, the very detailed COPERT vehicle sub-categories are aggregated to three types i.e. Passenger Cars (PC), Light Duty Vehicle (LDV) and Heavy Duty Vehicles (HDV includes buses and coaches). It is assumed that traffic distribution around airport is similar to the national traffic distribution.
Emission factors from COPERT III methodology for CO, NOx , VOC and PM10 for vehicle categories are used to calculate the emission factors for PC, LDV and HDV. This is implemented in an Access Database Application which contains national fleet statistics and distribution most for European countries. In other words ALAQS roadways methodology the aggregated emission factors of PC, LDV and HDV are computed based on the national fleer statistics available in the database. The aggregated emission factors are computed using the following formula:
(E4)
| EFi,j,s | Aggregated emission in g/km for pollutant j of COPERT sub-category i and vehicle aggregated category s (PC, LDV, HDV) |
| efi,j,s | emission factor in g/km for pollutant j of COPERT sub-category i and vehicle aggregated category s (PC, LDV, HDV) |
| ni | the number of vehicles of COPERT sub-category i |
| li |
the national annual average distance in km traveled by a vehicle of COPERT sub-category i |
ALAQS emission factors are calculated as weighted averages. This is done by weighting COPERT III emission factors by the number of vehicles of the type in the national fleet and the number the averaged annual distance traveled. More detailed report can be found in the reference <4-5>.
Figure 4. Overview of ALAQS Roadway Methodology.
3.4 Stationary Sources
Stationary sources at an airport include power and heating plants, incinerators, training fires, fuel storage tanks etc. They are represented as point sources.
The general methodology for calculating emissions from these sources considers the hourly quantity of material used or processed multiplied by the corresponding emission factor. The hourly quantity is derived from the total yearly figure and the operational activity profiles.
4 ERC ALAQS-AV Emission Inventory Toolset
ALAQS-AV is an ArcView 8 application designed for the capture and preparation of airport emission sources, conduction of emission inventories and future use for dispersion calculations. For further detail see the reference <6>
The application handles three groups of emission sources:
• Aircrafts and aircraft support equipment
• Road vehicles (roadway and parking lots)
• Stationary sources (e.g. power plants, fuel tanks and training fires)
Standard ArcView functionalities are used for data manipulation and handling. Based on the background airport map the user captures the different emission sources. For aircraft emissions four feature layers need to be captured: runways, queues, taxiways and gates (or stands). For non-aircraft emissions an additional three layers are captured: stationary, roadways and parking lots. For each feature captured the user has to enter the required attributes.
Activity profiles are important attributes of non-aircraft emission data. They determine the intensity of the source activity for each hour of the year relative to a year’s total. Activity profiles are derived from available hourly, daily and monthly operational data and statistics.
Once all the emission sources and their attributes have been captured the hourly emission can be calculated. Data for aircraft engine emissions and aircraft profiles are stored in ALAQS-AV system tables. The application merges first all the different types of emission features in a single layer called Merged Sources. Subsequently it calculates for selected period hourly emissions for each source.
The pollutants currently included in the emission inventory are CO, HC, NOx, SOx and PM10.
Results of the calculation process can be displayed by means of a visualisation tool. The user selects a period and a pollutant, the intensity of the emission is then represented by means of a graduated colour scheme so that strong and weak emissions are easily identified. Since runway emissions (climb-out and approach) occur in a vertical plane above the runway they are projected on the horizontal plane along the runways for visualisation.
Figure 5.ALAQS-AV emissions results visualisation.
5 Application of ALAQS-AV to Lyon Airport Pilot Study <7>
In this section the pilot study conducted for Lyon airport is described for emission inventory estimations.
5.1 Airport Data Collection
All the operational data is provided by Lyon Airport and the data processing is conducted in ALAQS-AV tool with the use of GIS.
5.2 Airport Graphical Data
Lyon airport provides data on the airport mapping and layout, enhanced by the ALAQS-AV tool.
Figure 6.Lyon Airport Emission Sources Capture with use of GIS.
This information has been used for the spatial allocation of emission sources.
5.3 Data provided by Lyon Airport
Airport operation data was provided for the year 2002. However some emissions sources didn’t have spatial and temporal information.
Table 2. Lyon Data for Emission Inventory Calculation
| Source Group | Emission Source | Operational Data | Emission Data | Spatial Information | Temporal Information |
| Air Traffic | Aircraft (year 2002) | y | y | y | y |
|
Handling |
Aircraft Main Engine Ignition | - | - | - | - |
| Aircraft APU | - | - | - | - | |
| GPU | y | y | - | - | |
| GSE | y | y | - | - | |
| Airside Traffic | - | - | - | - | |
| Refuelling | y | y | y | - | |
| Aircraft De-icing | y | y | y | - | |
| Infrastructure | Power Generation Plant | y | y | y | y |
| Emergency Power Stations | - | - | - | - | |
| Aircraft Maintenance | - | - | - | - | |
| Airport Maintenance | - | - | - | - | |
| Fuel Farm | y | y | y | - | |
| Fire Exercice | y | y |
y |
- |
|
|
Construction |
- |
- |
- |
- |
|
|
Landside Traffic |
Road Traffic |
y |
y |
y |
y |
5.4 Data Required by ALAQS-AV
This step classifies received operational airport data and process for its use in the ALAQS-AV application. As shown in Table 3, a number of data elements were not available through the airport. In most cases, ALAQS-AV has pre-defined default values in the system extracted from different sources, but in some cases assumptions had to be made.
Table 3. In ALAQS-AV required operational data
|
Emission Source |
Data required by ALAQS-AV |
Availability |
Data used |
|
Aircraft* |
- aircraft identification |
yes |
Lyon data |
|
- aircraft group |
yes |
Lyon data |
|
|
- departure profile |
no |
assumption |
|
|
- arrival profile |
no |
assumption |
|
|
- D or A for Arrival or Departure |
yes |
Lyon data |
|
|
- on-block-time |
yes |
Lyon data |
|
|
- off-block-time |
yes |
Lyon data |
|
|
- actual time of arriving |
no |
assumption |
|
|
- actual time of departure |
no |
assumption |
|
|
- runway used |
yes |
Lyon data |
|
|
- landing distance |
no |
assumption |
|
|
- route |
no |
assumption |
|
|
- gate |
yes |
Lyon data |
|
|
APU |
- running time arrival |
no |
assumption |
|
- running time departure |
no |
assumption |
|
|
GPU |
- running time arrival |
yes(as a total) |
Lyon data |
|
- running time departure |
|||
|
Main engine start |
- no data required |
- |
- |
|
Handling |
- no data required |
- |
- |
|
Vehicles airside |
- movements per category and speed |
no |
Estimated using Lyon data |
|
- movements per road |
no |
||
|
- yearcourse |
no |
||
|
Vehicles landside |
- movements per category and speed |
yes |
Lyon data |
|
- yearcourse |
yes |
Lyon data |
|
|
Other sources |
possible to calculate emissions in ALAQS-AV as stationary sources |
||
*excl. Helicopters
5.5 Emission Calculation with ALAQS-AV Model
In this final step ALAQS-AV is used to calculate the emissions. For this study, emissions calculations are made for entire year 2002 for all airport LTO operations and, by aircraft by aircraft basis.
For roadway emissions externally to ALAQS-AV tool; ERC methodology which is based on COPERT III and CITEPA methods are used.
The results file from ALAQS-AV was too big for the basic post-processor available in the tool, therefore the results were imported to Access so that the total emission per emission sources type could be compiled.
6 Results and Discussions
The emission calculation was done in ALAQS-AV for the entire year an the results are summarized below.
Table 4. Comparison of ALAQS-AV NOx emissions results with Lyon Airport on-site calculation for 2002
|
Source Group |
Emission Source |
Lyon |
Alaqs |
|
(t NOx/a) |
(t NOx/a) |
||
|
Air Traffic |
Aircraft |
371.37 |
209.63 |
|
Handling |
Aircraft Main Engine Ignition |
0 |
28.53 |
|
Aircraft APU |
93.02 |
||
|
GPU |
|||
|
GSE |
47.35 |
||
|
Airside Traffic |
4.63 |
||
|
Refuelling (Aircraft & Vehicles) |
0 |
0 |
|
|
Aircraft De-icing |
0 |
0 |
|
|
Infrastructure |
Power Generation Plant |
16.69 |
16.69 |
|
Emergency Power Stations |
0 |
0 |
|
|
Aircraft Maintenance |
0 |
0 |
|
|
Airport Maintenance |
0 |
0 |
|
|
Fuel Farm |
0 |
0 |
|
|
Fire Exercise |
0.15 |
0.15 |
|
|
Construction |
0 |
0 |
|
|
Landside Traffic |
Road traffic |
72.98 |
53.62 |
|
Total |
|
554.21 |
360.6 |
Italics : Values copied from Lyon 2002 results without own calculation in ALAQS-AV
Table 5. Comparison of ALAQS-AV CO emissions results with Lyon Airport on-site calculation for 2002
|
Source Group |
Emission Source |
Lyon |
Alaqs |
|
(t CO/a) |
(t CO/a) |
||
|
Air Traffic |
Aircraft |
253.22 |
219.6 |
|
Handling |
Aircraft Main Engine Ignition |
0 |
30.74 |
|
Aircraft APU |
37.02 |
||
|
GPU |
|||
|
GSE |
26.53 |
||
|
Airside Traffic |
13.31 |
||
|
Refuelling (Aircraft & Vehicles) |
0 |
0 |
|
|
Aircraft De-icing |
0 |
0 |
|
|
Infrastructure |
Power Generation Plant |
3.88 |
3.88 |
|
Emergency Power Stations |
0 |
0 |
|
|
Aircraft Maintenance |
0 |
0 |
|
|
Airport Maintenance |
0 |
0 |
|
|
Fuel Farm |
0 |
0 |
|
|
Fire Exercise |
0.18 |
0.18 |
|
|
Construction |
0 |
0 |
|
|
Landside Traffic |
Road traffic |
171.32 |
151.23 |
|
Total |
|
465.62 |
445.47 |
Table 6. Comparison of ALAQS-AV VOC emissions results with Lyon Airport on-site calculation for 2002
|
Source Group |
Emission Source |
Lyon |
Alaqs |
|
(t VOC/a) |
(t VOC/a) |
||
|
Air Traffic |
Aircraft |
32.82 |
30.74 |
|
Handling |
Aircraft Main Engine Ignition |
0 |
23.07 |
|
Aircraft APU |
10.72 |
||
|
GPU |
|||
|
GSE |
6.69 |
||
|
Airside Traffic |
1.87 |
||
|
Refuelling (Aircraft & Vehicles) |
2.41 |
2.41 |
|
|
Aircraft De-icing |
0.01 |
0.01 |
|
|
Infrastructure |
Power Generation Plant |
1.44 |
1.44 |
|
Emergency Power Stations |
0 |
0 |
|
|
Aircraft Maintenance |
0 |
0 |
|
|
Airport Maintenance |
0 |
0 |
|
|
Fuel Farm |
127.53 |
127.53 |
|
|
Fire Exercise |
0.06 |
0.06 |
|
|
Construction |
0 |
0 |
|
|
Landside Traffic |
Road traffic |
28.67 |
18.72 |
|
Total |
|
203.66 |
212.54 |
6.1 Interpretation of the Results
There are some significant differences among the emissions computed by two approaches.
For aircraft emissions, main difference is for NOx emissions. ALAQS-AV NOx results defers from Lyon by 43.6%. The difference represents more than 100 tones which is very large. Although, the numbers of aircraft movements used in the calculation process are the same, matching of aircraft/engine combination which is used for emission calculation might be different. This is due to a fact that ICAO emission databank is limited to some numbers of aircraft/engine combinations. Thus aircraft grouping is made for the ones which are not available in ICAO databank. This can explain some of the differences. Further investigations are needed to improve NOX predictions.
For GSE emissions the difference can be explained by the lack of content operational data, therefore some assumptions had to be made.
For landside traffic the emissions estimations correlates well. Lyon roadways estimations were based on the CITEPA roadways method <8> while ALAQS-AV used a modified COPERT methodology adapted to airports.
7 Conclusion
This paper gives an overview of ERC ALAQS methodology for Local Air quality assessment of Airports operations. This includes how different emission methodologies were integrated in ALAQS-AV Toolset with the view of developing a Pan-European approach. The application of ALAQS-AV toolset to Lyon Airport gives us a good opportunity to work with real airport data and investigate the practical problems of an Airport. The comparison of ALAQS-AV results with Lyon Airport on-site inventory demonstrated that potential users should rather choose a methodology first and then obtain the necessary data instead of randomly collecting data and then try to fit it into a particular methodology. The ALAQS-AV results were also compared with LASPORT system to consolidate and validate the approach which is available in ERC SEE Business Area.
8 Future Work
For this project future work consists of developing the dispersion modeling part and integrating with Pan-European emission inventory approach. With the use of GIS system there will be possibility of visualization of concentration plumes on populated area. In addition the physical and chemical processes and meteo data will be integrated in dispersion modeling part.
References
1. Local Air Pollution Dispersion Model for Airports. UNIQUE/Zurich Airport. Fl/ZRH/15.09.2000
2. Air Quality Procedures for Civilian Airports & Air Force Bases. (Downloadable from website: http://www.aee.faa.gov)
3. ALAQS Roadway Methodology Report (ERC SEE Business Area)
4. COPERT III : Computer Program to calculate Emissions from Road Transport. Methodology and emission factors (version 2.1). European Environment Agency, technical report n°49, November 2000.
5. Methodologies for estimating air pollutant emissions from transport. Evaporative emissions. Task 1.9/deliverable 14. LAT report No : 9717. Aristotle University of Thessaloniki, August 1997.
6. ALAQS-AV Application Reference Manual (ERC SEE Business Area)
7. ERC and Unique 2003, Emission Inventory for Lyon saint-Exupery Airport
8. Outil d’évaluation des émissions dues aux sources aéroportuaires. STNA, Avril 2000.
9. EDMS User Guide Manual (Downloadable from website: http://www.aee.faa.gov)
10. Perkins Powerpart, through Mineli, CH-Paffikon,30.7.1999
Key Words:
Airport Operations, Local Air Quality, Emission, Inventory, Aircraft, Ground Support Equipment (GSE), Roadway emissions, Pollution.