ALAQS AERMOD Dispersion Modelling Verification EEC/SEE/2007/006

Transcription

1 ALAQS AERMOD Dispersion Modelling EEC/SEE/2007/006

2 This report was prepared for EUROCONTROL Experimental Centre ALAQS by: ENVISA. Author(s): Nicolas Duchene, Serge Peeters ENVISA 38 rue des Gravilliers PARIS Ian Fuller, EUROCONTROL Experimental Centre Review: List of reviewers if applicable. EEC Note : EEC/SEE/2007/006 European Organisation for the Safety of Air Navigation EUROCONTROL 2007 This document is published by EUROCONTROL in the interest of the exchange of information. It may be copied in whole or in part providing that the copyright notice and disclaimer are included. The information contained in this document may not be modified without prior written permission from EUROCONTROL. EUROCONTROL makes no warranty, either implied or express, for the information contained in this document, neither does it assume any legal liability or responsibility for the accuracy, completeness or usefulness of this information.

3 EXECUTIVE SUMMARY This report reports on the verification of using ALAQS-AV emission inventory results, in the form of 3D hourly emission grids, to create input files for various dispersion models. In particular, the report focuses on the Gaussian model AERMOD and compares dispersion results using AERMOD (integrated into ALAS-AV) against the Lagrangian model LASAT (in stand-alone mode and coupled with ALAQS-AV via the ALAQS-TRANS module. The test scenario was a simplified airport modelled in ALAQS-AV, consisting of a single runway with aircraft in take-off mode only. The results of the emission inventory were transformed for use in AERMOD and LASAT. The emissions inventory spanned a period of 36 hours, this made It feasible to apply an isotropic wind rose with a change in wind direction of 10º every hour. In addition, the same scenario was modelled in LASAT stand-alone for verification purposes. The choice of LASAT as a reference complicated the verification because the meteorological requirements for AERMOD and its meteorology pre-processor are significantly different from LASAT. AERMOD requires many more details to define the planet boundary layer. As a consequence, a number of meteo parameters had to be estimated using a best educated guess. That being said, The concentrations from ALAQS-AERMOD and ALAQS-LASAT were found not to be significantly different, except in the area close to the start of take-off run where AERMOD estimated the peak concentration around 7 µg/m 3 as opposed to above 10 µg/m 3 in ALAQS- LASAT (and above 20 µg/m 3 ) in LASAT alone. Further away from the start of the runway, the concentrations modelled using the three approaches were comparable. An important issue highlighted in the report is the evaluation of the uncertainties related to emission inventory and dispersion calculations (including the uncertainties on meteorology). A detailed analysis of those uncertainties and their potential impact on both emissions and concentrations is a critical step toward a solid verification and validation of air quality models for airports.

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5 REPORT DOCUMENTATION PAGE Reference: SEE Note No. EEC/SEE/2007/006 Originator: ENVISA 38 rue des Gravilliers PARIS - FR For Society, Environment, Economy Research Area Sponsor: Security Classification: Unclassified Originator (Corporate Author) Name/Location: EUROCONTROL Experimental Centre Centre de Bois des Bordes B.P BRETIGNY SUR ORGE CEDEX France Telephone: Sponsor (Contract Authority) Name/Location: EUROCONTROL EATM EUROCONTROL Agency Rue de la Fusée, 96 B 1130 BRUXELLES Telephone: TITLE: ALAQS : AERMOD Dispersion Modelling Authors : Nicolas Duchene, Serge Peeters Date 08/07 Pages 36 Figures 8 Tables 2 Appendix 4 Reference s EEC Contact: Ian Fuller EATMP Task Project Task No. Sponsor Period Specification ALAQS A03 TRSA03PT/D7.2c Distribution Statement: (a) Controlled by: EUROCONTROL Project Manager (b) Special Limitations: None (c) Copy to NTIS: YES / NO Descriptors (keywords): Dispersion, model verification, uncertainties, airport local air quality, Gaussian, Lagrangian Abstract: This report reports on the verification of using ALAQS-AV emission inventory results, in the form of 3D hourly emission grids, to create the required input files for the AERMOD dispersion model integrated into ALAQS-AV. The verification was based a comparison of dispersion results from the AERMOD gaussian and LASAT lagrangian models using a simplified airport modelled in ALAQS-AV, consisting of a single runway with aircraft in take-off mode only. The concentrations from ALAQS-AERMOD and ALAQS-LASAT were found to be comparable, except in the area close to the start of take-off run where AERMOD estimated the peak concentration around 7 µg/m 3 as opposed to above 10 µg/m 3 in ALAQS-LASAT (and above 20 µg/m 3 ) in LASAT alone. The study highlighted the importance of evaluating the uncertainties and their potential impact related to emission inventory and dispersion calculations (including the uncertainties on meteorology) when attempting to verify or validation air quality models for airports. 6 EEC/SEE/2007/006 v

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7 TABLE OF CONTENTS 1 INTRODUCTION Background of the Study Presentation of ALAQS-AV, LASAT and AERMOD Objectives of the Report METHODOLOGY AND PARAMETERS DEFINITION Definition of Common Parameters Setting Up the Simple Scenario in ALAQS-AV D Grid in ALAQS-AV CONVERTING ALAQS-AV OUTPUT TO AERMOD INPUT ALAQS-AV Interface Meteorology in AERMOD AERMOD RESULTS COMPARISON OF DISPERSION RESULTS Comparison of Ground Level Concentration Maps Discussion on Uncertainties CONCLUSIONS REFERENCES...16 EEC/SEE/2007/006 vii

8 LIST OF TABLES TABLE 1: TAKE OFF ROLL CORRESPONDING TO THE AIRCRAFT TRAJECTORY IN ALAQS-AV... 5 TABLE 2: VERTICAL LAYERS CONSIDERED IN ALAQS-AV FOR COMPATIBILITY WITH AERMOD... 6 LIST OF FIGURES FIGURE 1: DATA FLOW IN THE AERMOD MODELLING SYSTEM FROM US EPA [REF 1.]... 3 FIGURE 2: RELATIONSHIPS FOR CALCULATING AIRCRAFT EMISSIONS IN ALAQS-AV... 5 FIGURE 3: THE AERMOD BUTTON (A) IN THE ALAQS-AV TOOLBAR... 7 FIGURE 4: AERMOD RESULTS (FOR THE FIRST 8 HOURS) FIGURE 5: AERMOD RESULTS (FOR THE LAST 8-HOURS) FIGURE 6: ALAQS-LASAT GRID SOURCE CONCENTRATION RESULTS AT GROUND LEVEL FIGURE 7: ALAQS-AERMOD CONCENTRATION RESULTS AT GROUND LEVEL FIGURE 8: LASAT STAND-ALONE SOURCE DYNAMICS CONCENTRATION RESULTS AT GROUND LEVEL EEC/SEE/2007/006

9 ABBREVIATIONS ALAQS ALAQS-AV ALAQS-TRANS APU BADA CAEP EDMS EPA FAA GIS ICAO INM LAQ PBL PM TAS Airport Local Air Quality Studies ALAQS - ArcView Emission Inventory tool ALAQS inventory to dispersion model transformation tool Auxiliary Power Unit Base of Aircraft Data Committee on Aviation Environmental Protection Emission and Dispersion Modelling System US Environmental Protection Agency US Federal Aviation Administration Geographical Information System International Civil Aviation Organization FAA Integrated Noise Model Local Air Quality Planet Boundary Layer Particulate Matter True Air Speed EEC/SEE/2007/006 ix

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11 1 INTRODUCTION 1.1 Background of the Study The Airport Local Air Quality Studies (ALAQS) was initiated by EUROCONTROL to respond to the growing demand for the evaluation of the impact of aviation on the environment. In previous phases of the project, an emission inventory tool, ALAQS-AV, was designed to produce airport emission inventories, i.e. indicating the total amount of pollution released during airport operations. However, it was necessary to evaluate the subsequent concentrations (i.e. to follow the evolution of the quantities emitted in time as a function of their position at the airport and depending on meteorology) in order to assess the compliance of the airport with the European legislation. This is because the European Directives on Ambient Air Quality (96/62/EC, 1999/30/EC, 2000/69/EC, 2002/3/EC and 2004/107/EC) express targets in terms of number of occurrences of a polluting event above a limit concentration (over a year generally). Considering the fact that a wide range of Gaussian (e.g. AERMOD), Lagrangian (e.g. LASPORT/LASAT) and Eulerian dispersion models are already commercially available worldwide, it would not be productive to develop an additional dispersion tool. Instead, ALAQS- AV should be used to provide inputs to various dispersion tools facilitating thereby their comparison. Based on the consultation of dispersion experts, it appeared that interfacing emission and dispersion models with the highest compatibility could be done using a 3D grid source approach. Roughly, it consists in using the emission inventory results to create a 3D grid in which each cell was assigned an emission rate, depending on the sources that contribute to the total emissions within that cell (for a defined period of time, generally one hour). The newly created grid source can then be directly plugged into a dispersion model which no longer requires the information about individual sources. 1.2 Presentation of ALAQS-AV, LASAT and AERMOD ALAQS-AV ALAQS-AV is an airport emission inventory tool developed by EUROCONTROL. It is characterised by its embedment within a Geographical Information System (GIS) ArcView which allows for a very fine geographical location of the emission sources. It contains emission factors for aircraft emissions (engines and Auxiliary Power Units APU), stationary sources (power and heating plants, fuel tanks ) and roadways (airside and landside, based on four commonly used methodologies for calculating road emissions). The output of an ALAQS-AV airport study is composed of hourly three dimension emission grids considering initial source dynamics for compatibility with dispersion models. A consequence of the use of a grid source is that the source dynamics (the initial dispersion of the pollution due to the exhaust characteristics of the source such as the exhaust speed, temperature and plume ) have to be dealt with before the emission rates were assigned to individual grid cells. It was decided to use the Smooth and Shift Approach proposed by Dr Ulf Janicke. This approach consists in extending the width and depth of a line source and shifting it backwards according to the exhaust characteristics. The smooth and shift parameters used in ALAQS-AV were derived from the Lagrangian model LASAT 2.15 as part of the ALAQS project. EEC/SEE/2007/006 1

12 1.2.2 ALAQS-TRANS ALAQS-TRANS is a program developed to transform the 3D grids resulting from ALAQS-AV studies in input for a range of dispersion models (Gaussian, Lagrangian and Eulerian). In a first step, transformations for two models were foreseen: AERMOD (Gaussian model developed by the FAA, which is the regulatory model for airport air quality in the United States) and LASAT (Lagrangian model which was used as a basis for the development of the German regulatory model for dispersion studies AUSTAL 2000) LASAT 2.16 LASAT (Lagrange Simulation of Aerosol Transport) is a Lagrangian model developed by Janicke Consulting, Dunum (Germany), for the simulation of the dispersion of trace elements in the atmosphere. LASAT is an episode model, i.e. it calculates the temporal development of a substance concentration within a given simulation area. All the parameters necessary were specified as time series, and the transport and turbulent diffusion is simulated by means of a stochastic process. The LASAT model was used in the ALAQS project to derive smooth and shift parameters to account for source dynamics in ALAQS-AV emission grids. Based on this experience it was decided to use LASAT as a reference to verify the ALAQS-AV grid sources and ALAQS- TRANS. It is especially possible to conduct dispersion calculations in two ways in LASAT: either using smooth and shift parameters or using detailed source dynamics (LASAT default settings). Those two modes of calculations have been used to validate ALAQS-AV grid sources and ALAQS-TRANS as explained in the body of this report AERMOD The AERMOD dispersion model has been developed since the 1990's by the US Environment Protection Agency (EPA). It is a Gaussian dispersion model that was originally designed to estimate near-fields impacts from a variety of industrial source types. It has also been coupled to the Emission and Dispersion Modelling System (EDMS) for airport air quality considerations. The AERMOD system is composed of two pre-processors on top of the dispersion model: AERMET (for the preparation of meteorological data) and AERMAP (for the preparation of terrain data). AERMET provides information to AERMOD for the characterisation of the planet boundary layer (PBL) such as friction velocity, mixing height. AERMAP describes the terrain and generates receptor grids for the dispersion model. Both AERMET and AERMAP have been used for this verification study. The flow of data during an AERMOD dispersion study is shown in Figure 1. 2 EEC/SEE/2007/006

13 Figure 1: Data Flow in the AERMOD modelling system from US EPA [Ref 1.] 1.3 Objectives of the Report The previous phase of the ALAQS project focused on the development of tools to allow running dispersion models based on ALAQS-AV emission inventory results. A 3D grid version of ALAQS-AV has been implemented taking into consideration initial source dynamics. Additionally, the transformation program ALAQS-TRANS has been written to provide grid sources to the LASAT dispersion model in the proper format. Also, an interface to prepare AERMOD input files based on ALAQS-AV emission inventory results has been developed together with a tool to visualize AERMOD emission in the GIS ArcView. The verification of those new developments composes the main objectives of the present report as detailed in the list below: Verify the use of ALAQS-AV to create AERMOD input files Verify the AERMOD concentration visualization and the receptor grid feature of ALAQS- AV Compare the results of ALAQS-TRANS + LASAT and AERMOD for a simple case including meteorology data (few hours of simulation, take off roll only) The following explains the methodology used to create comparable test-cases and to obtain reliable dispersion results and thus meaningful comparisons. Also the parameters used in ALAQS-AV, LASAT 2.15 and AERMOD were expressed. The results of this study were expected to validate the use of ALAQS-AV for the creation of input files for the AERMOD dispersion model. EEC/SEE/2007/006 3

14 2 METHODOLOGY AND PARAMETERS DEFINITION The basis of the verification undertaken here is the comparison of the dispersion results obtained by ALAQS-AV+LASAT, ALAQ-AV+AERMOD against LASAT stand-alone. First of all, a similar scenario had to be defined in ALAQS-AV and in LASAT. Then, the dispersion model had to be run for the two approaches with similar meteorological conditions. The test scenario was the simplified inventory scenario used to derive shift and smooth parameters [Ref 6.]. This simple scenario consisted of one runway with ten small aircraft take offs per hour. Only the take off roll of aircraft was considered, i.e. only ground emissions. The climb-out of the aircraft was not covered. The period of the simulation was 36 hours so that an isotropic wind rose could be applied covering all the wind directions by 10 steps. In order to simplify the analysis of the results, only one trace substance was considered in the following of the report: NOx. 2.1 Definition of Common Parameters Simulation Set Up The duration of the simulation was 36 hours. The runway of interest extents from (-1350, 0) to (450, 0) and measured 1800m. The wind speed was fixed at 3m/s and the wind direction was incremented by 10º each hour, starting from 10º (thus at hour 36, the wind direction is 360 º covering all the directions of a wind rose) Vertical Layers Considered { } Note that only ground emissions were covered by the example, i.e. emissions from the take off roll only were considered. Consequently, the upper emissions correspond to the maximum vertical extent of the plume of an aircraft during the take off engine mode. This vertical extent was estimated to be 181m after Janicke [Ref 6.]. Therefore, no emissions above this value would be calculated. As a consequence, the upper vertical layer in ALAQS-AV was rounded up at 185m and there was no need to consider greater altitudes in the dispersion Grid Parameters Grid cell size was 50 meters for all the vertical layers defined above. Domain size was 6000m x 4000m centred on the runway. The coordinates of the origin of the domain onto which the dispersion was calculated were (-2500 ; -2000) Meteorology for LASAT Dispersion was calculated over an isotropic wind rose. The following meteorological parameters have been defined after Janicke [Ref 6.]: Wind speed = 3 m/s Monin-Obukhov length = 300 m Roughness length = 0.3 m Displacement height = 1.8 m 4 EEC/SEE/2007/006

15 Anemometer height = 12 m Note that the parameters presented above correspond to LASAT only. For the AERMOD run and its meteo pre-processor AERMET, it was necessary to collect a significantly larger number of parameters. Those were detailed in a later section, dealing specifically with AERMET requirements. 2.2 Setting Up the Simple Scenario in ALAQS-AV Aircraft emissions calculations in ALAQS-AV were based on three tables as shown in Error! Reference source not found.2: the aircraft definition table, the trajectories (aircraft profiles) and the engine emission factors. Aircraft definition table Aircraft trajectories table Engine emission factor TOTAL EMISSIONS Figure 2: Relationships for calculating aircraft emissions in ALAQS-AV The aircraft definition table indicates the engine and the profile identifiers to use as a function of the aircraft identifier, which was used also in the movement table. In accordance with the simple scenario defined in the report, the movement table contained ten aircraft movements per hour during 36 hours. Since the results were aggregated per hour in ALAQS-AV output; the exact time at which one aircraft movement occurred was of no interest. Similarly, since only take-off roll emissions were considered, neither the taxiing phase nor the climb-out was considered. Therefore it was sufficient to define the engine fuel flow and emission factors for the take off mode only. The following values were used similar to Janicke [Ref 6.]. : Fuel flow kg / s NOx emission factor g / kg of fuel burnt Again, considering the aircraft trajectories, it was sufficient to define the take off roll only. In accordance with the LASAT simple scenario, the following profile was derived: Table 1: Take off roll corresponding to the aircraft trajectory in ALAQS-AV The speed (True Air Speed column) was derived from an average velocity of 45 m/s on the segment of 1800m in accordance with the specifications of the source document. EEC/SEE/2007/006 5

16 Finally the following emission dynamics parameters were used to define source initial dynamics for the take off mode only: Width 301 m Height 181 m Horizontal shift 360 m The default ALAQS shift and smooth parameters were used [Ref 6.] D Grid in ALAQS-AV Table 2: Vertical layers considered in ALAQS-AV for compatibility with AERMOD Once the same horizontal and vertical grid parameters were defined in ALAQS-AV and in the LASAT input files, it was necessary to ensure that the grid-source from ALAQS-AV was correctly geo-referenced. The point of reference used for this duty was the south west corner of the emission inventory in ALAQS-AV. It was important to consider the source dynamics during this operation. In the case of the simple runway as defined in the scenarios above, the point the furthest west was located at coordinates (-1350 ; 0), i.e. it was the western extremity of the runway. Since the aircraft moving direction was toward the west; the backward shift of the exhaust was toward the east by 360 m. Therefore the furthest west emission point was situated at ( ; 0) that is to say (-990 ; 0). On the contrary, the horizontal extent of the exhaust will influence the south extremity of the emission domain. The plume of an aircraft taking off has been estimated at 301 m centred on the line source, which means the extent of the line source once smoothed and shifted was from m to m in the y direction. From those findings, it was possible to estimate that the south-west corner of the emissions was located at (-990 ; ). The default ALAQS shift and smooth parameters were used [Ref 6.]. However, in ALAQS-AV, a discretization process is used to assign an emission value to an individual cell. It is specified in the ALAQS-AV user manual that the horizontal spacing of the discretization points is a function of half the size of the smallest cell size. Therefore the final extension of the emission domain is greater than what is calculated considering emissions and source dynamics only. In the present case, the cell size was 50m, therefore the south west corner point due to emission location and then discretization was located at ( ; ) that is (-1015 ; ). 6 EEC/SEE/2007/006

17 3 CONVERTING ALAQS-AV OUTPUT TO AERMOD INPUT 3.1 ALAQS-AV Interface ALAQS-AV can convert emission inventories into AERMOD 1 input files (*.INP & *.HRE). The interface was launched simply by clicking on the AERMOD button on the ALAQS Toolbar. Figure 3: The AERMOD button (A) in the ALAQS-AV toolbar ALAQS-AV identifies all the Emission Inventories located in the project directory that have 3D Grid Cells. To proceed, select an emission inventory and then select the Surface and Profile meteorological files. Compare the start and end hours from the inventory database to those of the meteorological files. The period to be processed corresponds to the hours between the start hour and the end hour (end hour was not included). The three start hours should be the same. The end hour for both meteorological files should also be identical. The end hour of the inventory database should be smaller or equal to meteorological end hours. In addition the following steps should be completed: Select a pollutant from the pollutants list. Select a height from the Max Height drop-down list. Only heights appearing in the list were valid. The heights list corresponds to the max_elev field in the tbl_gridlevel table. Enter a receptor height (default value 1.8m). Enter the Receptors Grid definition. 1 User's Guide for the AMS/EPA Regulatory Model AERMOD, U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Emissions Monitoring and Analysis Division Research Triangle Park, North Carolina (EPA-454/B September 2004). EEC/SEE/2007/006 7

18 The Extend of Sources frame is for information only; it provides an indication of the spatial extend of the emission sources. The coordinates displayed were ALAQS-AV project coordinates. Once all the required information has been entered click on the Generate button to generate the AERMOD input files (text files). If Auto Run AERMOD box was ticked, AERMOD will be launched automatically straight after the files have been created. The AERMOD input file names were the same as the emission inventory database with the code of the pollutant appended and the extensions INP and HRE. The input file (INP) contains the geometric definition of the sources as well as source parameters. A flat terrain was assumed. The Hourly file HRE contains the Hourly Emission rates for each source. Stationary Sources were processed separately from Grid Cell sources to take advantage of the built-in AERMOD point source algorithms to model releases from stacks and other source types. Grid Cells were modelled as area sources with an initial vertical dimension corresponding to the cell height. Grid Cell emissions in the hourly emission file exclude emissions from stationary sources. The AERMOD application (AERMOD.EXE) should be located in the ALAQS-AV system directory i.e. C:\ALAQS_Sys or D:\ALAQS_Sys. AERMOD produces an output file (OUT) and a concentrations files (CON). 3.2 Meteorology in AERMOD AERMOD meteorological input consists of two files: the surface meteorological data and the profile meteorological data, the content of which is shown below: The AERMOD surface meteorological data file consists of a header record containing information on the meteorological station locations, and one record for each hour of data. These data were delimited by at least one space between each element, i.e., the data may be read as free format. The contents of the surface file were as follows: 8 EEC/SEE/2007/006

19 Year Month (1-12) Day (1-31) Julian day (1-366) Hour (1-24) Sensible heat flux (W m-2) Surface friction velocity, u* (ms-1) Convective velocity scale, w* (ms-1) Vertical potential temperature gradient in the 500 m layer above the planetary boundary layer Height of the convectively-generated boundary layer (m) Height of the mechanically-generated boundary layer (m) Monin-Obukhov length, L (m) Surface roughness length, z0 (m) Bowen ratio Albedo Wind speed (ms-1) used in the computations Wind direction (degrees) corresponding to the wind speed above Height at which the wind above was measured (m) Temperature (K) used in the computations Height at which the temperature above was measured (m) The sensible heat flux, Bowen ratio and albedo were not used by the AERMOD model, but were passed through AERMET for information purposes only. Nevertheless, the quantity of meteorological data necessary was significantly greater than for the LASAT tool. The file that has been used to perform the AERMOD verification is shown in Appendix C. Some verification by a meteorology expert was still necessary to ensure that the meteorological situation described in ALAQS-AV + LASAT was as much as possible similar to the AERMOD one. The profile meteorological data file consisted of one or more records for each hour of data. As with the surface data file, the data were delimited by at least one space between each element and may be read as Fortran free format. The contents of the profile meteorological data file were as follows: Year Month (1-12) Day (1-31) Hour (1-24) Measurement height (m) Top flag = 1, if this is the last (highest) level for this hour; 0, otherwise Wind direction for the current level (degrees) Wind speed for the current level (ms-1) Temperature at the current level (K) Standard deviation of the wind direction, F2 (degrees) Standard deviation of the vertical wind speed, Fw (ms-1) The data in this file included the on-site meteorological data that were processed by AERMET. Since AERMET was designed to be able to perform dispersion parameter calculations with NWS data only, i.e., no on-site data, the profile data may consist of a one-level "profile" based on the NWS winds and temperature. The file that was used to perform the AERMOD verification is shown in Appendix D. Some verification by a meteorology expert was still necessary to ensure that the meteorological situation described in ALAQS-AV + LASAT was as similar as possible to the AERMOD one. EEC/SEE/2007/006 9

20 4 AERMOD RESULTS Figure 4: AERMOD results (for the first 8 hours) 10 EEC/SEE/2007/006

21 Figure 5: AERMOD results (for the last 8-hours) Figure 4 and Figure 5 were obtained after running AERMOD from the ALAQS-AV toolbar and using the AERMOD visualization tool developed under ArcView in ALAQS-AV. It can be seen from Figure 4 and Figure 5 that ALAQS-AERMOD gave the expected results with regard to the simple meteorological situation modelled. The evolution of the concentration EEC/SEE/2007/006 11

22 pattern was in accordance with the wind direction set up for each hour of the simulation. However, to perform a better verification, ground concentrations from ALAQS-LASAT and ALAQS-AERMOD were compared in the next section. 5 COMPARISON OF DISPERSION RESULTS 5.1 Comparison of Ground Level Concentration Maps The result maps were presented in Figure 6 (ALAQS-LASAT), Figure 7 (ALAQS-AERMOD) and Figure 8 (LASAT stand-alone). When comparing the ALAQS-LASAT and ALAQS-AERMOD results, it appears that the concentrations as calculated by AERMOD showed lower pollution levels. In particular, in the close area to the runway, the AERMOD concentration was about 7 µg/m 3 while in the case of LASAT (ALAQS) it was above 10 µg/m 3. The highest concentration was calculated by LASAT alone and it was above 20 µg/m 3. However, in all three cases, the concentration levels rapidly decreased below 5 µg/m 3. At a distance greater than one kilometre east from the peak areas, the concentrations modelled by the three approaches were below 1.5 µg/m 3. Below the two LASAT figures, the subsequent range of uncertainty (in percentage) was shown. In general, the higher uncertainty corresponds to lower concentrations as a result of the Lagrangian transport of particles model. This was because the concentration in a cell was a function of the number of particles that were in that cell at a certain time. Therefore, fewer particles mean smaller concentrations but also higher uncertainties. In the case of ALAQS-AV gridsource, the uncertainties were calculated by LASAT ranging from 0.6% to 8.2%, while in the case of LASAT alone they ranged between 0.2% and 11.2%. In all cases the same particle emission rate of 100 particles per second was used. The immediate conclusion is that somehow the concentrations resulting from ALAQS-AV + ALAQS-TRANS + LASAT show a greater reliability far away from the runway while the most reliable result close to the runway comes from the LASAT detailed source dynamics approach. At this early stage of the verification, there was no uncertainty figure related to the run of AERMOD. This will be necessary in the future. Figure 6: ALAQS-LASAT grid source concentration results at ground level 12 EEC/SEE/2007/006

23 Uncertainty range 0.6% to 8.2% Figure 7: ALAQS-AERMOD concentration results at ground level Figure 8: LASAT stand-alone source dynamics concentration results at ground level Uncertainty range = 0.2% to 11.2% EEC/SEE/2007/006 13

24 5.2 Discussion on Uncertainties The estimation of uncertainties is a critical step for the analysis of the results from any dispersion modelling tool. There were uncertainties arising from the following areas: the emission model the meteorology the dispersion model the method used for the chemical transformation NOx / NO2 if any In particular, the topics below have been identified as critical for aircraft emission inventories in the course of the PSDH (Project for Sustainable Development of Heathrow, 2006) study characterisation of the aircraft NOx emissions (ICAO emission factors Vs performance based emission factors) consideration of operational procedures such as reduced thrust / reverse thrust aircraft sources most sensitive to airport operating scenarios Considering the dispersion models, a number of improvements were possible, in particular a better characterisation of aircraft plumes would be very valuable. In any case, it is necessary to provide methods to estimate the range of uncertainty of both emissions and concentrations using well defined emission inventory conditions. 14 EEC/SEE/2007/006

25 6 CONCLUSIONS The ALAQS-AV gridsource approach leads to comparable concentration results between AERMOD and LASAT. However, at ground level and close to the runway, a difference in the area of high concentration has been observed. This was particularly true when comparing the ALAQS-AV based results with the ones from LASAT only, as the peak concentration was even higher. For concentrations further away from the runway, there was only limited difference in the dispersion results from the three approaches. It was still possible to conclude that the ALAQS-AV gridsource approach and smooth and shift parameters were a suitable way to provide input to the AERMOD and LASAT dispersion models since comparable results have been obtained when using the same modelling parameters in AERMOD and LASAT. A big difference that arose between AERMOD and LASAT was the meteorological requirements, which were much more detailed in AERMOD. by a meteorology expert would be necessary to ensure that the situation described in both tools was as similar as it can be. It is worth noticing that full studies on the uncertainties generated by both the emission inventory process and the dispersion model (incl. on meteorological data) were key steps for the verification and validation of the air quality model. In the case of ALAQ-AV, it will be especially important to estimate the error caused by the use of "smooth and shift" parameters to described aircraft plume dynamics combined with their assignments on 3D grids. EEC/SEE/2007/006 15

26 7 REFERENCES [Ref 1.] [Ref 2.] [Ref 3.] [Ref 4.] [Ref 5.] [Ref 6.] US EPA, 2004, AERMOD: Description of Model Formulation, available online at US EPA, 1998, AERMOD user manual EUROCONTROL, 2006, ALAQS user manual Janicke Consulting, 2006, LASAT v2.14 user manual EUROCONTROL, 2006, study of ALAQS-AV 3D gridsource approach and smooth and shift parameters Janicke Consulting, 2005, Derivation of smooth and shift parameters to account for source dynamics in ALAQS-AV emission grids 16 EEC/SEE/2007/006

27 Appendix A Sample AERMOD Input File generated by ALAQS-AV ** File generated by ALAQS-AV on 08-May :40:01 ** ALAQQS-AV version: MAY 2007 (MAY07) CO STARTING TITLEONE LYON_ALAQS MODELOPT DFAULT CONC AVERTIME 1 POLLUTID CO FLAGPOLE 1.8 RUNORNOT RUN CO FINISHED SO STARTING ELEVUNIT METERS ** SrcId - Source identification code (8 characters maximum) ** for grid cells SrcId = ObjectId in 3D Cell Indices table (shp_3dgridpt) ** for Stationary Sources SrcId = 'ST' & Souce_Id ** SrcTyp - Source type: POINT, VOLUME, AREA, AREAPOLY, AREACIRC ** SrcType= 'AREA' for grid cells ** SrcType= 'POINT' for stationary sources ** Xs - x-coord of source location, SW corner for AREA (in m) ** Ys - y-coord of source location, SW corner for AREA (in m) ** for area sources Xs and Ys refer to SW corner of 3D grid cell ** Zs - Optional z-coord of source location (elevation above mean sea level) ** Zs = Airport Elevation, assumingh flat terrain ** LOCATION SrcId SrcTyp Xs(m) Ys(m) Zs(m) LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION ST POINT LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA EEC/SEE/2007/006 17

28 LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA LOCATION AREA ** LOCATION Summary ** Number of Stationary Sources: 16 ** Number of 3D Grid Sources: 6133 ** Total: 6149 ** POINT SOURCE PARAMETERS: ** PtEmis - point emission rate in g/s ** actual point emission rates were in hourly emission file (.hre) ** StkHgt - release height above ground in meters ** StkHgt = H in Source Geometry table (tbl_sourcegeometry) ** StkTmp - stack gas exit temperature in degrees Kelvin ** actual temperatures were in hourly emission file (.hre) ** StkTmp = ExitTemp in Emissions Dynamic table (tbl_emissiondynamic) ** StkVel - stack gas exit velocity in m/s ** actual exit velocities in hourly emission file (.hre) ** StkTmp = ExitVel in Emissions Dynamic table (tbl_emissiondynamic) ** StkDia - stack inside diameter in meters ** StkDia = Width in Emissions Dynamic table (tbl_emissiondynamic) ** SRCPARAM SrcId PtEmis StkHgt StkTmp StkVel StkDia SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST SRCPARAM ST ** AREA SOURCE PARAMETERS: ** ArEmis - area emission rate in g/(s-m2) ** actual area emission rates were in hourly emission file (.hre) ** RelHgt - release height above ground in meters ** RelHgt = min_elev in the Grid Level table (tbl_gridlevel) ** Xinit - length of X side of the area (in the east-west ** direction if Angle is 0 degrees)in meters ** Xinit = cell_size in the Grid Level table (tbl_gridlevel) ** Yinit - length of Y side of the area (in the north-south ** direction if Angle is 0 ) in meters (optional) ** Yinit = Xinit for all 3D grid cells i.e. square cell base ** Angle - orientation angle for the rectangular area in degrees from North, ** measured positive in the clockwise direction (optional) ** Angle always = 0, grid cells were aligned to X/Y coord axes ** SZinit - initial vertical dimension of the area source plume in meters (optional) ** SZinit = max_elev - min_elev in the Grid Level table (tbl_gridlevel) ** SRCPARAM SrcId ArEmis RelHgt Xinit Yinit Angle SZinit SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM EEC/SEE/2007/006

29 SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM SRCPARAM ** SRCPARAM Summary ** Number of Stationary Parameters: 16 ** Number of 3D Grid Parameters: 6133 ** Total: 6149 ** HOUREMIS - HOURLY EMISSION FILES HOUREMIS LYON_ALAQS_ _1500_CO.HRE ST ST HOUREMIS LYON_ALAQS_ _1500_CO.HRE ** SRCGROUP - SOURCE GROUP DEFINITIONS SRCGROUP ALL SRCGROUP STPOINT ST ST SRCGROUP 3DGRID SO FINISHED ** GRIDCART - RECEPTOR DEFINITIONS RE STARTING ELEVUNIT METERS ** GRIDCART - CARTESIAN GRID RECEPTOR NETWORK ** XYInc - Keyword identifying uniform grid network generated from x and y increments ** Xinit - Starting x-axis grid location in meters ** XNum - Number of x-axis receptors ** XDelta -Spacing in meters between x-axis receptors ** Yinit - Starting y-axis grid location in meters ** YNum - Number of y-axis receptors ** YDelta - Spacing in meters between y-axis receptors EEC/SEE/2007/006 19

30 ** STA Indicates the STArt of GRIDCART inputs for a particular network ** END Indicates the END of GRIDCART inputs for a particular network ** ELEV - Keyword to specify that receptor elevations follow (optional) ** HILL - Keyword to specify that hill height scales follow (optional) ** FLAG - Keyword to specify that flagpole receptor heights follow (optional) ** Xinit XNum XDelta Yinit Ynum YDelta GRIDCART GRID STA XYINC FLAG 1 3*1.80 ELEV 1 3* HILL 1 3* FLAG 2 3*1.80 ELEV 2 3* HILL 2 3* FLAG 3 3*1.80 ELEV 3 3* HILL 3 3* GRIDCART GRID END ** DISCCART - DISCRETE CARTESIAN RECEPTORS ** Xcoord x-coordinate for discrete receptor location ** Ycoord y-coordinate for discrete receptor location ** Zelev Elevation above sea level for discrete receptor ** Zhill location (optional), used only for ELEV terrain ** Zflag Hill height scale corresponding with a discrete receptor location (optional) ** Xcoord Ycoord Zelev Zhill Zflag RE FINISHED ** ME - METEOROLOGICAL INFORMATION ** SURFFILE - Describes input meteorological surface data file ** PROFFILE - Describes input meteorological profile data file ** SURFDATA - Describes surface meteorological station ** UAIRDATA - Describes upper air meteorological station ** AERMOD compares the station number from the runstream input file ** with values provided in the first record of the surface meteorology file, ** and issues warning messages if there were any mismatches ** PROFBASE - Specifies the base elevation above MSL for the potential temperature profile ** Used in the plume rise calculations ME STARTING SURFFILE D:\ALAQS\Airport_Lyon\LYON_ALAQS1\LYONTEST1.SFC PROFFILE D:\ALAQS\Airport_Lyon\LYON_ALAQS1\LYONTEST1.PFL SURFDATA UAIRDATA PROFBASE METERS STARTEND ME FINISHED ** OU - OUTPUT FILES ** POSTFILE - Produces file of concurrent (raw) results at each receptor suitable for post-processing; ** Aveper - Specifies averaging period to be output to file, e.g., 24 for 24-hr averages, ** Grpid - Specifies source group to be output to file ** Format - Specifies format of file, either UNFORM for unformatted files or PLOT for formatted files for plotting ** Filnam - Specifies filename for output file ** PLOTFILE AVERPER GRPID FORMAT FILNAM OU STARTING POSTFILE 1 ALL PLOT LYON_ALAQS_ _1500_CO.CON OU FINISHED ** end 08-May :40:21 20 EEC/SEE/2007/006

31 Appendix B Sample AERMOD Hourly Emissions File generated by ALAQS-AV The format of each record of the hourly emissions file includes the keywords SO and HOUREMIS followed by the Year, Month, Day, Hour, Source ID, and emission rate. For point sources, the stack gas exit temperature (K), and stack gas exit 'velocity (m/s) were also specified. SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS ST SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS EEC/SEE/2007/006 21

32 SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS SO HOUREMIS EEC/SEE/2007/006

33 Appendix C METEOROLOGICAL PROFILE FOR ALAQS-AV / AERMOD VERIFICATION EEC/SEE/2007/006 23

34 Appendix D SURFACE PROFILE FOR ALAQS-AV / AERMOD VERIFICATION 24 EEC/SEE/2007/006