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Manual for THOR-AirPAS - air pollution assessment system

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1. Motorcycles 0705 00 0 00 5468 011 0O11 0O11 015 oso 006 Railways 0802 255 52 016 4298 876 876 8 76 000 0 00 0 00 0 00 Maritime activities Aviation Agriculture Indust Spatial data To distribute the emissions some spatial datasets are required Table 5 5 shows some of the spatial datasets that could be relevant for different sec tors Table 5 5 Examples of relevant spatial data for different sectors Features Demarcation of the area of the city Industrial areas Road network Urban areas Road types urban rural highway Rural areas Road width Heating districts Annual average mileage Building types tall one storey Annual average mileage per vehicle type Port facilities Annual average number of vehicles Construction areas Annual average number of vehicles per vehicle type Railway network Settlement areas Airport areas Commercial areas Population density Below are some illustrative examples of the type of spatial data presented in Table 5 5 The first example Figure 5 2 focusses on the road network and il lustrates three spatial datasets for the same area but with different level of detail Figure 5 3 illustrates different land use maps J y m i a LAN Road type f gt ARE Road type Annual Average Daily Traffic lt 200 iy 9 A A UJ e 144 I s y dU fi LA Nu il E Pf tin J e Lf D i d S
2. J New Project Single Street M 2 x Country Denmark Street Storegad el Scenario Year 2013 Name Input Data and Files m Accept calculations without File cial IM D Sel Street Configuration nput Files Special Mode Set Traffic Data Meteorology B ackground Measured Concentrations g Pre defined diurnal traffic r User defined Pre defined r User defined Ie DOE data meteorological and data background data none od Isi Average Dady Traffic Veh day y Traffic Data in City Size inhabitants Hourly User Files H B Can be set with other User defined data Output Files user defined optional Hourly Output Files Statistics and other Output Files Add File Add File File Names File Names Figure 4 2 The New Project window filled with values according to the example Now as an example go through the steps outlined below As Street name choose Example Street Choose 2013 as Scenario Year This year might be already pre selected depending on the Scenarios List file for Denmark which is distributed with the installation package The choice of the Scenario Year affects the choice of files with emission data data on national car fleet composition and fuel quality Leave the check box concerning Special Mode unchecked Special Mode is a tool for studying how air quality depends on wind speed and direction for a given street geometry Special Mode requires less
3. Benz a pyrene as indicator for polycyclic aromatic hydrocarbons PAH 9 AOT4O ug m hours means the sum of the difference between hourly concentrations greater than 80 ug m 40 parts per billion and 80 ug m over a given period using only the one hour values measured between 8 00 and 20 00 Central European Time CET each day a Under revision Human health Table A2 Parameter unit day month year hour UTC GMT NO NO Os ppb CO ppb SO ppb SO NO NH ppb EC OC TSP ug m PM 10 PM ug m TotN constant Hmix m U m s WD direction from N T Celcius temp Global radiation W m wstar m s ustar m s sw m s sheat W m Monin Obukhov Length m MOL air density kg m rho surface pressure hPa spres cloud cover 0 1 Precipitation mm hour RelHum 9 Appendix 2 Meteorological and background input data This section describes a The structure formats of the meteorological and regional background input file b How to use your own user provided in put data and c how to use the model for other than the standards pollu tants A Description of the meteorological and regional background input file The meteorological and regional background input file eg AOG hourly Danmark cph dat has been calculated by the DEHM model and various variables and parameters in the file are described in the table below Description Date and time in UTC GMT time c
4. vehicies heur Scenario Year 889 096 CAT 2013 143 8 627 451 39 8 3 4 v Al vehicles _ 301 6 V PAS Car D lI 11144 I Vans 1817 5 v Truck 1 E j 1760 2 iv Truck 2 1508 2 v Buses _ o 1482 6 1599 5 1617 4 J 1689 7 1902 6 2196 0 2360 4 1859 0 1370 7 29 953 2 697 3 715 5 662 3 374 0 T 26463 2 1340 4 Average Dady Traffic e Emission Factors g km Wim x 1 E 14 for Particle Numbers Travel Speed km h i 0 329 5510 7797 0 919 0 821 1 689 0 735 Lancet oK 0 0106 0 0041 Figure 4 6 The traffic window 24 Emission data The COPERT IV emission module is integrated into the OSPMO EEA 2013 The emissions are calculated based on the traffic volume vehicle distribution and travel speed and related to vehicle specific emission factors To be able to calculate emission factors it is necessary to obtain data on the national car fleet The distribution of vehicles in different emission classes and engine sizes has to be obtained for different fuel types The vehicle categories include passenger cars and vans gasoline diesel LPG electricity trucks and buses gasoline and diesel in different weight groups Information about average mileage for the different vehicles and different emission classes is important because it is used to estimate mileage correction of emissions Information of the fraction of directly emitted NO for the different veh
5. 2001 Operational air pollution forecasts from European to local scale Atmospheric Environment Vol 35 Sup No 1 pp 591 598 2001 Brandt J Christensen J H Frohn L M amp Berkovicz R 2001a Operational air pollution forecast from regional scale to urban street scale Part 1 system description Physics and Chemistry of the Earth B Vol 26 No 10 pp 781 786 2001 Brandt J Christensen J H amp Frohn L M 2001b Operational air pollution forecast from regional scale to urban street scale Part 2 performance evalua tion Physics and Chemistry of the Earth B Vol 26 No 10 pp 825 830 2001 Brandt J Christensen J H Frohn L M amp Berkowicz R 2003 Air pollu tion forecasting from regional to urban street scale implementation and validation for two cities in Denmark Physics and Chemistry of the Earth Vol 28 pp 335 344 2003 Brandt J Silver J D Frohn L M Geels C Gross A Hansen A B Han sen K M Hedegaard G B Skjeth C A Villadsen H Zare A amp Christen sen J H 2012 An integrated model study for Europe and North America us ing the Danish Eulerian Hemispheric Model with focus on intercontinental transport Atmospheric Environment Volume 53 June 2012 pp 156 176 doi 10 1016 j atmosenv 2012 01 011 Christensen J H 1997 The Danish Eulerian Hemispheric Model a three dimensional air pollution model used for the Arctic Atmospheric Environ me
6. 46 Nitrogen dioxide NO 200 1 hour 18 hours per year Human health 2010 40 Average year Human health 2010 Nitrogen oxides NO 30 Average year Vegetation 2010 Sulphur dioxide SO 350 1 hour 24 times per year Human health 2005 125 24 hours 3 times per year Human health 2005 20 Average year and Okosystemer 2001 winter Particles less than 2 5 um 25 Average year Human health 2010 PMs 25 Average year X Human health 2015 20 Average year Human health 2020 Particles less than 10 um 50 24 hours 35 times per year Human health 2005 PM10 40 Average year Human health 2005 Lead 0 5 Average year Human health 2005 Benzene 5 Average year Human health 2010 Carbon monioxide CO 10 000 8 hours running Max Human health 2005 Ozone 120 Max 8 hours 25 days per year Human health 2010 running average over 3 year 120 Max 8 hours 1 day per year Human health Not defined running 180 1 hour Max Human health 2003 240 1 hour Max over 3 hour Human health 2003 18 000 AOT40 May July Vegetation 2010 ug m hours 6 000 AOT40 May July Vegetation Not defined ug m hours Arsenic 0 006 Average year Human health 2010 Cadmium 0 005 Average year Human health 2010 Nickel 0 02 Average year Human health 2010 Benz a pyrene 0 001 Average year Human health 2010 Mercury Notes Target value 2 Long term objective Information threshold Alert threshold In PMio 9 Trends are followed
7. 6 4 24 43 93 4 84 0 0 81 0 37 0 89 33 63 137 1 1 31 1008 97 1 0 02 92 42 28 0 0 0 4000 576 28 0 0 0 4000 465 28 0 0 0 4000 424 27 0 0 0 4000 574 27 0 0 0 4000 601 27 0 0 0 4000 553 42 0 0 0 4000 573 42 0 0 0 4000 623 22 0 42 0 0 0 4000 496 85 4 24 44 77 4 99 0 0 82 0 37 0 9 33 45 138 3 1 31 1008 91 1 0 02 92 35 49 4 27 45 87 5 12 0 0 8 0 37 0 88 32 93 143 25 1 31 1008 86 1 0 02 92 19 67 4 3 47 32 5 18 0 0 79 0 38 0 88 31 57 153 68 1 31 1008 89 1 0 02 91 88 13 4 35 48 35 5 27 2 71 0 81 0 38 0 9 31 22 157 86 1 31 1008 93 1 0 02 91 8 76 4 38 48 41 5 37 11 53 0 75 0 38 0 85 31 19 160 3 1 31 1008 98 1 0 02 91 6 0 38 0 0 0 4000 872 39 4 54 48 69 5 31 19 71 1 06 0 41 1 14 49 26 123 61 1 31 1009 22 1 0 02 90 57 0 38 0 0 0 4000 801 89 4 58 48 17 5 28 18 5 1 06 0 41 1 14 54 56 116 87 1 31 1009 42 1 0 03 90 32 19 0 35 0 0 0 4000 784 09 4 63 47 67 5 26 13 79 1 06 0 42 1 14 55 22 119 14 1 31 1009 68 1 0 03 90 24 Rename your newly created file as AQG_hourly_UserData dat and place it in the folder C NTHOR AirPASNUBM urban Nmetinput and select this file in the DEHM file drop down menu before you run UBM C Using the UBM model for a different list of pollutants The UBM model in the THOR AirPAS system is as standard set to calculate for six emitting pollutants NOx SO CO TSP PMi0 PM25 as found in the emission spreadsheets For NO the chemical reactions with NO and O3 ar
8. ATTE MA i RAO EEE SOT E n m we ot tot ee e a Tali oro DON E oem TE LEE PN a Te tet E reos Te E af al mera pr oo Re T piti taa Jes re EI Ed O dll Je el d 1 aw ewm ema ARI 5 C bee pue ims a d mde PENS L T mee codi Faria rele Misak SNERRE J a O A ELA LES A a veta _ DAI UU e Dg Bs rd tom MA hy OL AA EARL PULL EE AE e adds DABA Bs rd tom au ol a A EM EF PLE ER ELE isicing s dia i dd A A IA Ca AM Ma edendi Mes Mem beag Deed Wake Mp Dana Bs crum eL Hi LATENTE PR E AE O DA ap A ot 37 Continued A AA A E E Rad e ve e a A de e ee Cum DeHHx OT RPPZPDBAaugcesBRpa emums aa MM LULA DAD 1 LIDERES AA A EAT ans WIN ena Gr e a a es aa r 5 TIDCLER HIE om LL DEBA ACOs SF ZPDAauc oa ammo mas ipn eem rem mmn 15 Aem ie rns s Ed EL a t A A M P F 3 Whetutth ferri Pagea Pa me r pa e epa Fumiga lpi agente Rd ELE od TITIO den EEFEFEEEEERERE iino lL EEEEREEEEEEEREE i POE caca NUI IDO APP ae m TTE INGA X x P EE EAE SS 53547 APEC 24 PINTA AA EX P ae aw ZAE T a E ra T p o Rr AS ORNAME ER CASE ee aC Se Os Gee ASS ACI rige Bu E SIA ARA de DN SEATS ER J 55 sd j 1 4 B dubi 4 LAF
9. However you can download a program that will allow you to view Help created in the Windows Help format For more information go to the Microsoft Help and Support website When you follow the link you will arrive at a page like this gt I cannot open Help that was created in the Windows Help format WinHIp32 exe Windows Help WinHlp32 exe is a Help program that has been included with Microsoft Windows versions starting with the Microsoft Windows 3 1 operating system However the Windows Help program has not had a ma jor update for many releases and no longer meets Microsoft s standards Therefore starting with the release of Windows Vista and continuing in Windows 7 the Windows Help program will not ship as a feature of Win dows If you want to view 32 bit hlp files you must download and install the program WinHIp32 exe from the Microsoft Download Center You can download and install depending on your system a file like gt Windows6 1 KB917607 x64 msu During the installation process you may also be asked to verify the validity of your Windows license You only have to go through this entire process once After installing the update the Help function should work normally under WinOSPM 9 Optional Install Q GIS textpad TC from c Apps InstallationFiles ol MANUAL FOR THOR AIRPAS AIR POLLUTION ASSESSMENT SYSTEM Technical Project Report for AirQGov Regional Pilot Project 3 AirQGov RPP3 The rep
10. a v ki A l 7 m i a H NZ ES ma ES AA a a La r x Pis ASA It ve we Va UE 9 4 A a Az 4 de C Ld a A n aa Ever B 835 am e rd ES IX cere cop fum E Tad RIA ALAS Mou a ao Ae y T L4 AA 4 E Ax 3i ni DEO ot s ES als lara T mr Tr omi E i rs vu rmm J 3 Se E ant mun iul nri omen t LA m S _ 4 E m menn ru A mE a REC tmm perra pee SS s CECI TEIL Ss Sere meee ER er mem Sr es LS E Io m Figure 5 7 Procedures step 5 9 in QGIS 38 rt te cd T E z y Tini 3 061078 209 mia COR 2 2i irit s AERE FU La Amb de EpL oF Aib din a ETT ee 9 M il ee da Boum m LII V ium jim pa im ab lim sik dI jim anri shi CTER TOE iE 31 TER gk Plim aT d pia Arp a Sim ser del N gie ARMS P4 zim Abb gif jim Hi dd pie REM di jim Aib dii Him ARMS AE jim axem dd d b deti amp jtm ttm Sen A dup ias iam saj d umen m H al ELIT sel _d GEI aiam E Lint og dT i iiit uh dd ro apt mg tab ml AFT Adim and T NT ium mui Ad anh tim mud y din ail Figure 5 8 The attribute table imported to Excel as a pivot table ELT LL J pm J a pem aa ea bury dn ems mari iz po Fn dat a p tmm Ri Ye dramma a at De Le Hera Sebas de mhi ds rr a oe umm DE Dans oe nn iaces P mee nhe zm mi Psm F ege m oral mem acr jp Mail 3 L
11. 0 3 02 1km 6089 600 600500 6089500 WGS84 UTM32N 0 0 0 0 0 0 0 4 02 1km_6090_599 599500 6090500 WGS84 UTM32N 0 006573 0 001573 0 181415 0 027619 0 026379 0 02576 0 020106 5 02 1km 6090 600 600500 6090500 WGS84 UTM32N 0 003486 0 000834 0 096216 0 014648 0 013991 0 013662 0 010664 6 02 1km 6090 601 601500 6090500 WGS84 UTM32N 0 000265 6 35E 05 0 007324 0 001115 0 001065 0 00104 0 000812 7 02 1km 6090 602 602500 6090500 WGS84 UTM32N 0 004826 0 001155 0 133198 0 020278 0 019368 0 018913 0 014762 3 C km 6090 60 503500 6090500 WGS amp M32N 0 0066 0 001583 0 182567 0 027794 0 026547 0 025923 0 020234 I gt M GridEmis 0705 GridEmis_0802 GridEmis 0805 GridEmis 0806 Point sources Mobile sources Area sources 41 Table 5 10 Example of data output for mobile sources from the spatial model after running macro GenerateMobileSources used as input for air quality modelling GridID 1km_6092 605 1km 6092 606 1km 6093 604 1km 6093 605 1km 6094 603 C D E X Y Projection 605500 6092500 WGS84 UTM32N 606500 6092500 WGS84 UTM32N 604500 6093500 WGS84 UTM32N 605500 6093500 WGS84 UTM32N 603500 6094500 WGS84 UTM32N B G H NOx tons SO2 tons CO tons 0 216539 0 062023 0 220278 0 027584 0 115093 0 00054 0 000155 0 00055 6 88E 05 0 000287 2 577517 0 73827 2 622021 0 32834 1 369978 TSP sum PM10 sum PM2_5_sum_ TSP_exh_ TSP tons PMI10 tons tons 0 023083 0 006612 0 023482 0 0
12. 1 06 041 1 14 340 36 123 61 131 1000 22 4 6 48 17 5 28 18 5 1 06 O41 1 14 54 56 116 87 131 100947 0 Dd 4 6 47 67 5 26 13 79 1 06 042 1 14 55 22 119 14 1 331 1005 68 The green marked columns are not used and you do not need to care about the content but the columns as such have to remain there to maintain the correct format The yellow marked columns are the primary pollutants re gional background concentration You may change and copy your own data in the corresponding columns of the EXCEL worksheet and when you are ready save the worksheet as com ma separated values CSV in a text file as displayed below The decimal separator should be dot and values are separated by space or by comma as shown below 1 1 2010 1 0 1 1 1 2010 2 0 1 1 1 2010 3 0 1 1 1 2010 4 0 1 1 1 2010 5 0 1 1 1 2010 6 0 1 1 1 2010 7 0 2 1 1 2010 8 0 2 1 1 2010 9 0 2 1 1 2010 10 0 2 19 26 1 1 2010 11 0 2 19 26 1 1 2010 12 0 2 19 26 1 1 2010 13 0 2 39 25 48 46 26 4 4 i 4 9 r r 6 0 0 0 0 0 0 r O 34 0 0 3 0 0 2 0 38 0 0 0 4000 622 71 4 48 48 67 5 32 17 33 0 89 0 4 0 97 40 43 139 32 1 31 1009 07 1 0 02 90 97 56 3 89 42 39 a 08 0 o 78 o 32 0 84 29 84 99 227 15354 1009 02 0 71 0 01 93 47 19 4 06 42 49 4 41 0 0 73 0 35 0 81 30 27 126 55 1 31 1009 01 0 86 0 01 92 95 21 4 17 43 05 4 65 0 0 73 0 36 0 81 32 61 131 12 1 31 1008 97 1 0 01 92 74
13. Calibration and Regulation factors 1 02no regulation NOx SO2 CO TSP PM10 PM2 5 SNAP sector SNAP 01 COMBUSTION IN ENERGY AND TRANSF INDUSTRIES SNAP 02 NON INDUSTRIAL COMBUSTION PLANTS SNAP 03 COMBUSTION IN MANUFACTURING INDUSTRY SNAP 04 PRODUCTION PROCESSES SNAP 05 EXTR AND DISTR OF FOSSIL FUELS SNAP 06 SOLVENT AND OTHER PRODUCT USE SNAP 07 ROAD TRANSPORT SNAP 08 OTHER MOBILE SOURCES AND MACHINERY SNAP 09 WASTE TREATMENT AND DISPOSAL SNAP 10 AGRICULTURE Figure 3 5 Advanced options for adjustment of emissions and scenarios for emissions Once StartDate EndDate RunName and FolderName have been specified and the choice of whole grid or selected receptor points and optional scaling of emissions have been done click the button Run UBM to start UBM calculations After starting UBM by pressing Run UBM a black Command Prompt Window will open During the running of UBM the actual date in the processing is displayed to show progress The black window will close after the run and you need to confirm this in a message box The resulting files are saved as Excel sheets The Excel sheet Hourly Conc includes an hourly time series of the first receptor point in Rec_eval and this file is also used as input for the OSPM Note that this file only contains data if a receptor point is available in Rec eval The Excel sheet Average Conc includes the average concentrations for the specified time period for all receptor points in
14. and included in the city inventory e g maritime activities non road machinery in construc tion work or railways additional land use maps are required Addition al land use classes include port facilities construction areas railway network and airport areas respectively The projection of all spatial data provided should be Universal Transverse Mercator UTM coordinate system The relevant UTM zone must be speci fied in the data template If data cannot be provided in the UTM coordinate system datum and projection must be specified unequivocally Re projection tools are available in the GIS programs and handle the most well known projections It is not possible to include spatial data with projections other than the standard projections included in ArcGIS or OGIS The follow ing UTM zones are used in the model see Table 5 1 Table 5 1 UTM zones for the project cities Country City UTM zone Armenia Yerevan 38N Azerbajan Sumgait 39N Belarus Novopolotsk 35N Georgia Batumi 37N Moldova Chisinau 35N Russia Tver 36N Ukraine Kiev 34N 5 2 1 Software The spatial distribution in this project has been carried out using ArcMap This software requires a license but the open source software QGIS can perform the same functions A detailed user manual and training manual to QGIS is available both in English http docs qgis org 2 0 pdf en and in Russian http docs qgis org 2 0 pdf ru For point sources it can be necessar
15. can be significant the contribution of the individual plant will be small and emission data are rarely available Examples of area sources are stoves boilers in households and small combustion installations within the commercial institutional sector and small manufacturing industries Point sources The emission estimation model for point sources requires information on the fuel consumption of the individual plant In addition the spreadsheet pro vides the possibility for using measured data for the point sources In cases where measured emissions or measurements of pollutants are not available default emission factors are used Fuel consumption can be reported in energy units GJ or physical units m3 for natural gas tonnes for liquid and solid fuels If it is reported in physical units the values are converted using the net calorific value of the specific fuels The source of the calorific values is from Intergovernmental Panel on Climate Change IPCC 2006 Guidelines except for natural gas which is tak en from the Energy Statistics Manual published by the International Energy Agency If country specific or city specific values are available the standard values can be replaced in the model The emission factors are based on the EMEP EEA Guidebook Tier 2 and are included in the model as a worksheet containing the precise reference to the specific emission factor table in the EMEP EEA Guidebook If country specific or city specific emissi
16. for a particular street you must specify an Average Daily Traffic vehicles per day as an average over the year and an average travel speed for the street The travel speed is an average speed for a street section of length 100 200 meter close to the receptors In this example choose 25400 vehicles per day and 30 km h This completes the specification of traffic data You can now press the button View Edit Traffic in order to study or edit the distribution of the number of vehicles and their speed hour by hour Data for the various vehicle types are shown for each vehicle type Further there are several Day cases representing different days of the week and months of the year The window with these traffic patterns is shown in Figure 4 6 The window displays information on the amount of traffic and on emission including a graphical representation In the window it is possible to change values but we will not use this feature now A click on OK leads back to the New Project window C WinOSPM Data Traffic National DK Type_A trf File Edit Emissions Help 8 amp Y e Wi New Vehicle List C Lists Nationa DK VehiclesDK12_201 mil vi New Open T Print Past EmiFact New Fuel List CAWinOSPMWListsiWNationaNDKAFuek_ 1933 El FC_PN M Traffic Data ID ADT spit up 25403 3 20340 4 3057 7 1186 7 287 5 531 0 Average Dural Traffic Show as Number of Vehicles 7 Show as fraction of Dady Total Show as fraction of All Vehicles
17. machinery e g in industry forklifts etc construction dozers excavators etc commercial institutional residential lawn mowers trimmers etc and agriculture trac tors harvesters etc For a city some of these sources will be negligible since the activity does not occur within the city limits This is for instance frequently the case for navi gation aviation and agriculture The dominating source in all cities will be road transport and therefore the main focus has been to develop this part of the model Road transport In the model it is possible to provide activity data at different levels level 1 4 To move up in levels means that more detailed information is needed However to get a reliable emission estimate it is necessary to have detailed data on vehicle stock and mileage data Level 1 only requires the number of vehicles and total mileage per vehicle category Level 2 requires split per vehicle sub category and fuel type Lev el 3 requires a further split into engine size passenger cars and gross vehi cle weight trucks and buses Finally level 4 requires a further split into the emission details In addition information is needed regarding the sulphur content of the fuel and the ambient temperature The activity data are then imported to a MS Access database model to calcu late the emissions The model uses the methodology and emission factors from the COPERT IV model Version 10 together with ass
18. placed in the specified folder name By specifying RunName and FolderName the user can keep track of different simulations with UBM In most cases the start and end dates should be within the same year to ensure that regional background data meteorological data and emission data is for the same year However UBM can run for any period with regional background data and meteorological data 2000 2012 The longer time period that is chosen the longer UBM calculation time In the drop down list under Grid or Rec val it is possible to choose between calculations for the whole grid or calculations for the receptor points specified in the Excel sheet Rec eval By clicking the button Edit Rec val it is possible to view receptor points and edit them or add more The more receptor points that are included the longer the UBM calculation time The first receptor point is used as urban background data for subsequent OSPM calculations Advanced options are available for adjustment of emissions see Figure 3 5 These options are available next to the front end user interface in the sheet RunModels Emissions for individual pollutants and different emissions SNAP codes can be scaled This option may be used to calibrate the UBM model to fit measurements by scaling emissions The option may also be used for scenarios of different policy options e g reduction of NO emissions from road transport ADVANCED UBM Options EMISSIONS
19. software e g a GIS Geographic Information System Therefore the free GIS software QGIS software http www qgis org is provided with THOR AirPAS For conversion of OSPM results into a point shape file follow the procedure described at the end of Chapter 3 27 28 5 Emissions and spatial distribution This chapter describes the emission estimation methodology as well as the spatial distribution of emissions The methodology is also referred to as the SPREAD emission model and provides emissions data for UBM 5 1 Emission estimation The calculations of the emissions cover both stationary and mobile combus tion sources The emphasis has been on the stationary combustion sources and road transport However emissions from other types of mobile combus tion are also addressed The emission calculations are for the most part built into a MS Excel spread sheet However due to the complexity of the model used to estimate emis sions from road transport this has been done in a MS Access database 5 1 1 Stationary combustion Stationary combustion sources can be split into two distinct categories point sources and area sources Point sources are typically larger plants with significant emissions and in many cases emission measurement data will be available for these plants The primary examples are power plants or CHP plants refineries and large industrial plants Area sources are smaller and even if the overall emission
20. the run When UBM is finished it is possible to view the applied urban emission data under the heading Export of UBM emissions Sum of Transport and Area or Point including Scaling The button Export T A polygon shape file will export an ESRI Shape polygon file with the sum of the transport and area emissions sum over all emissions in all SNAP codes per 1x1 km grid cell This Shape file can be imported into a GIS e g QGIS where is can be displayed as coloured 1x1 km grid cells to see the geographic distribution of emissions The sum of emission data may also be viewed as a text file by clicking the button Open in TextPad Additional the point sources can be converted into a Shape point file by pressing the button Export Point Emi as Shape file There are several options for viewing UBM calculated concentration data under the headings of Export of UBM concentration results averages only The button Export as GIS polygon shp file will export an ESRI Shape polygon file and the concentrations can be displayed in a GIS as coloured 1x1 km grid cells to see the geographic distribution of concentrations Instead of visualizing concentrations on grid cells data may also be exported as points by clicking Export as GIS point shp file Concentration data may also be viewed as a text file by clicking the button Open in TextPad The above export features visualise the average concentrations from the Excel sheet Ave
21. to select data for available files via a drop drown list DEHM file By clicking the button Open DEHM file in TextPad the content of the file is viewed in the text editor TextPad The file includes calculated regional background concentrations and meteorological data as an hourly time series from 2000 to 2012 and it is used as input for UBM for urban background calculations DEHM Regional background and meteorology Open DEHM file in TextPad DEHM file AQG hourly Rusland Tver dat AQG hourly Armenien Yerevan dat AQG hourly Danmark cph dat AQG hourly Azerbajan Sumgait dat Figure 3 2 Graphical user interface for DEHM data It is possible to use you own user provided meteorological regional background data as input for the THOR AirPAS modelling system the formats and procedure are described in Appendix 2 SPREAD Urban emissions Urban emissions are divided into three types transport emissions other area emissions and point sources emissions Transport emissions include road traffic emissions other area sources include area sources that are not traffic e g residential heating Point sources include emissions from stacks from industry and energy production Urban emissions are input for UBM The emission input data need to be pasted into Excel from the output of the gridded emissions For more information see Chapter 5 2 1 The emission input data can be viewed in Excel by pressing one of the three
22. 02941 0 012269 J tons 0 01827487 0 00523441 0 01859041 0 00232796 0 00971329 K tons 0 013439164 0 003849337 0 013671207 0 001711963 0 007143061 L M tons nonexh 0 008101 0 0149828 0 00232 0 0042915 0 008241 0 0152415 0 001032 0 0019086 0 004306 0 0079635 N O PM2_5_tons _nonexh 0 00533853 0 001529098 0 005430706 nonexh 0 010174237 0 002914175 0 010349908 0 001296056 0 000680054 0 005407717 0 002837486 _7 10701 1km 6094 604 604500 6094500 WGS84 UTM32N 0 101425 0 000253 1 207292 0 010812 0 00855983 0 006294814 0 003794 0 0070178 GridEmis 0705 GridEmis 0802 GridEmis 0804 GridEmis 0805 GridEmis_0806 GridEmis 0808 GridEmis point _ Point sources Mobile sources 0 004765545 0 002500532 Area sources t4 The calculation of gridded emissions is performed in the spreadsheet City name Gridded emissions xlsm The spreadsheet takes the emission inven tory data and the spatial distribution keys and calculates the gridded emis sions as shown in Table 5 6 The spreadsheet only needs updating if a new spatial distribution key is used for a specific source category e g if a new spatial theme for industrial areas becomes available and can replace e g a population density key The final input to the air quality modelling is made by running three sepa rate macros one for point sources one for stationary area sources and one for mobile sources By pressing Alt F8 in Excel the r
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24. Ketzel Jorgen Branat Marlene Plejdrup Ole Kenneth Nielsen Morten Winther Olga Evdokimova Allan Gross Aarhus University Department of Environmental Science Denmark and Aarhus University s Department with focus on business and technology AU Herning Denmark Aarhus University DCE Danish Centre for Environment and Energy O http dce au dk en December 2014 November 2014 Allan Gross Aarhus University Department of Environmental Science Denmark Vibeke Vestergaard Nielsen Danish Centre for Environmental and Energy DCE Aarhus University Denmark EUROPEAID European Commission Steen Solvang Jensen Matthias Ketzel Jargen Brandt Marlene Plejdrup Ole Kenneth Nielsen Morten Winther Olga Evdokimova Allan Gross 201 4 Manual for THOR AirPAS air pollution assessment system Technical project Report for AirQGov Regional Pilot Project 3 AirQGov RPP3 Aarhus University DCE Danish Centre for Environment and Energy 51 pp Technical Report from DCE Danish Centre for Environment and Energy No A6 http dce2 au dk pub TRA6 pdf Reproduction permitted provided the source is explicitly acknowledged The report provides an outline of the THOR AirPAS air pollution assessment system and a brief manual for getting started with the air quality models and input data included in THOR AirPAS RPP3 The Regional Pilot Project 3 Development and Implementation of an air pollution assessment system to estimate effec
25. MANUAL FOR THOR AIRPAS AIR POLLUTION ASSESSMENT SYSTEM Technical Project Report for AirQ Gov Regional Pilot Project 3 AirQGov RPP3 Technical Report from DCE Danish Centre for Environment and Energy No 46 2014 AARHUS We UNIVERSITY DCE DANISH CENTRE FOR ENVIRONMENT AND ENERGY Blank page MANUAL FOR THOR AIRPAS AIR POLLUTION ASSESSMENT SYSTEM Technical Project Report for AirQGov Regional Pilot Project 3 AirQGov RPP3 Technical Report from DCE Danish Centre for Environment and Energy No 46 2014 Steen Solvang Jensen Matthias Ketzel J rgen Brandt Marlene Plejdrup Ole Kenneth Nielsen Morten Winther Olga Evdokimova Allan Gross 1 Aarhus University Department of Environmental Science 2 Aarhus University s Department with focus on business and technology AU Herning AARHUS Ww UNIVERSITY DCE DANISH CENTRE FOR ENVIRONMENT AND ENERGY Series title and no Title Subtitle Authors Institutions Publisher URL Year of publication Editing completed Referee Quality assurance DCE Financial support Please cite as Abstract Keywords Layout ISBN ISSN electronic Number of pages Internet version Data sheet Technical Report from DCE Danish Centre for Environment and Energy No 46 Manual for THOR AirPAS air pollution assessment system Technical project Report for AirQGov Regional Pilot Project 3 AirQGov RPP3 Steen Solvang Jensen Matthias
26. Road width gt 6 m Road width 3 6 m Other road V g YL y LETT L 1 Pil 4 WA A AA I Es y ES a aa ai Ly L T ay em XE ENS ea e if t Wig e ILI m V M SO 7 Ze BA M ae Sax Y r7 c wi cR Va E D PASES AERE s OS y e US Ky CATR NS y H th 9 IN B p Te ARES A SX SS G Su Q ACE x a 713 EL y L uni Vn EN CX A a W S ex AMAN ps N A T E To S y i NE gas Ni gt EL EI Ja SON ch e y mH Est Ni gt dS AV C FAS ASAE RAT S SN A ea LIN SPX EG D S EN o UE TS NIU We SS ics A ees YS LAS S e s w ei SA N j 4 Y SUR M TNA y at 23 Pe phe XY y 7 ip Kix gt Ny Bc ES ecl by BAIR PNY ANI S M e rae i Ne abcd STAN 27 REY x Mz 4 SV ee NO j NS M K WV SIG Y WE N A A INS ES XE XL DEN E S EA ATE e SU E A RGA Ta N SS IEN gt a j AY uU E RS A X A SIS NR SESION MENE EN ESOS ESAS Du SISSI Sd PERE MEN OE SIE OH 7 j LES HS S POS foU Nps SA ASA AER Ry RRE Lo oh LE AS I occ e SSA AS SEY L L I2 fis lei buiicing One storage building Figure 5 3 Examples of spatial themes of building type dwelling type and district heating area If national data are not available some international datasets are available e g for population density and road networks These data are less deta
27. VnstallationFiles to the same location on the new PC 3 Remove previous installations of WinOSPM on the new PC In case you have a previous version of WinOSPM installed on your PC please follow the steps below Navigate to the program folder where WinOSPM is installed and note this path for later use Uninstall WinOSPM via Control Panel gt Add Remove Programs Delete all files in the WinOSPM program folder that remain after unin stalling 4 Install WinOSPM from the files located on c Apps InstallationFiles into the Folder c Apps WinOSPM Under latest Windows versions e g Windows 7 Windows 8 the security settings and writing permissions have become much more restrictive than previously In order to get the WinOSPM installation process working as smooth as possible it is recommended that you have administrator rights i e you are member of the User Group Administrators and you are logged in with the account you are later to use for running WinOSPM Start the installation by running setup exe in the installation package The installation path that is suggested can be changed manually and should be a the same as any previous installation of WinOSPM and in case of a first time installation b it is recommended to use an easy accessible path with full writing permissions e g C Apps WinOSPM V 49 50 5 First time starting WinOSPM You will be asked for Country settings please mark Denmark and press OK Addin
28. ality and cleaner air for Europe establishes limit values target values long term objectives and information and alert thresholds for different substances A limit value is legally binding and determined on a scientific basis in order to avoid prevent or reduce harmful effects on human health and or the environment In addition to scientific considerations also technical and economic considerations are taking into account Limit values must be met within a given time frame Compliance with limit values does not necessarily ensure that there are no health effects at concentrations below the limit For example health studies indicate that there is no lower threshold beyond which exposure to particulate matter does not lead to health impacts Designated legal authorities in the member states of the European Union EU have the overall responsibility for compliance with limit values In the case of exceeding the limit an air quality plan has to be developed Similar a short term action plan has to be drawn up if alert thresholds are exceeded The aim of a target value is to reduce the adverse effects on human health and or environment The target value must as far as possible be reached during a given period A long term objective means a level to be attained in the long term with the aim of providing effective protection of human health and the environment An information threshold is a level where there is a risk to human health from short t
29. ants SPATIAL DISTRIBUTION KEY GRIDDED EMISSIONS GridID ShareOfArea NO tonnes SO tonnes CO tonnes TSP tonnes E cell E city ShareOfArea 11 3927 0 6911 4 4288 4 4246 0 0000 1 0000 1 403 229 7 016 701 614 51 452 5 2 3 Output data The output from the spatial modelling is both emission maps that can be used for visualization of the emissions within the city limits and data input to air quality modelling Emission maps Based on the spatial modelling city emission maps can be produced If only very crude spatial data are available then the emission maps will not give an accurate representation of the actual emission levels Below are Danish ex amples that illustrate a very crude and a very detailed spatial distribution PM o from small combustion Figure 5 9 and NH from agriculture Figure 5 10 respectively Small combustion tonnes PM10 m lt 0 EM 0 1 b 0 2 EN 0 2 0 3 DU 0 3 0 5 EN 0 5 0 7 E 0 7 1 0 EM 10 20 aM gt 20 Figure 5 9 Danish national emissions of PM from small combustion crude spatial distribution a Denmark and b zoom to smaller area Agriculture tonnes NH3 EM lt 0 001 EN 0 001 0 01 HA 0 01 0 1 BENI 0 1 1 0 EN 10 20 EN 2 0 20 EN 20 100 HE gt 100 Figure 5 10 Danish national emissions of NH3 from agriculture detailed spatial distribution a Denmark and b zoom to smaller area Input to air quality modelling The most im
30. ariables have to be specified according to the convention in OSPM Possible variables can be shown in a drop down list and the list of used variables can be saved for future reuse see Figure 4 8 Receptor points The receptor points are by default at both sides of the street located at the facade of the buildings The vertical receptor height can be specified by the user Output files Hourly concentrations are calculated for pollutants or and statistical parameters as average values and percentiles for specified receptor points In the standard output modelled concentrations are related to EU air quality limits EU 2008 gt Format File FATekst114435 AitQGov Guidance e report Example datalUBM sample inclHea Help View File Header View File Al day month year hour cNOX b cNO2_b c03 b cCO b cPM10_b cPM2 n b Variable List cPMExh obs 1 cFMExh obs 2 cPMExh tr cPNumber b cPNumber obs 1 cPNumber obs 2 cPNumber_t Date Scal Load Saved List Show Vanables Load from Project Save Variable List OK Cancel c e Figure 4 8 Names of variables of the meteorology and urban background file have to be specified In the standard installation the following substances are included NO NO O3 CO benzene PM25 PMio and particle number concentrations OSPMO includes emissions of non exhaust particles and these are included in modelled street concentrations
31. ations that measure urban background concentrations are usually located in a park or on top of a building and are referred to as urban background stations The increment from regional to urban background concentrations is named the urban increment Street concentrations are concentrations in the street at a receptor height of 2 9 m Street concentrations include the urban background and the contribution from vehicle emissions in the specific street The difference between the street and urban background concentrations is called the street increment Air quality monitor stations that measure street concentrations are usually placed at kerb side and are named kerb street or traffic stations The air pollution assessment model system includes three air quality models one for predicting regional air quality levels DEHM Danish Eulerian Hemispheric Model one for predicting urban background air quality levels UBM Urban Background Model and one for predicting street levels OSPM Operational Street Pollution Model More details on the UBM and OSPM are given in Chapter 4 and 5 respectively 2 2 Overall data flow A diagram of the overall data flow between the air quality models in the air pollution assessment system is shown in Figure 2 2 Global meteorological data from NCEP Global emissions Meteorological model EMEP emissions MMS5 Regional chemistry transport model DEHM Regional background concentrations and m
32. buttons for Show Transport Emi Show Area Emis or Show Point Emis To return to the front end user interface after viewing the input data click the Excel sheet with the name RunModels or Press CTRL m Emissions will reflect a specific year SPREAD Urban Emissions Show Transport Emi Transport emissions Funen_Transport csv Show Area Emi Other area emissions Funen Area csv Show Point Emi Point source emissions Funen Point csv Figure 3 3 Graphical user interface for urban emissions 11 UBM Urban Background Model Once the selection of regional background concentrations and urban emissions has been made input data are automatically made available for UBM UBM Urban Background Model Ena or Rec_val calculate only For receptors in Rec el _ Edit Rec val Rec val StartDate Run UBM EndDate RunName FolderName Export of UBM Emissions Sum of Transport and Area or Point including Scaling Export T A as polygon shape Open in TextPad Export Point Emi as shape file Export of UBM concentration results averages only Export as GIS polygon shp file Open in TextPad Export as GIS point shp file Figure 3 4 Graphical user interface for UBM In the green highlighted cells the user can select the StartDate and EndDate and specify the RunName and FolderName Dates follow the format DD MM YYYY HH where DD is day MM month YYYY year and HH hour Output is
33. commended 50 135 EU Limit Vale 2010 40 200 o0 E Street Modeled 107760 J 1 am 7 EU Limit Vake 2005 5 0 7 owwa T MEM Steet Modeled _______l _______ 05 73 81 77 Background o 1 57 83 64 EU Limit Vales 20104 0 0 0 0 0 0 0 0 ____ PU LH Pg EULmiVaue 2020 0 Sweet Modeled 8 EEE 153174 EULmtVae 2008 8 49 manowo NEN A SweMoked 22568 T r 1 100 27 Background 158 um j 26 43 4653 EU Limit Value 2005 e0 0 75 9 EU Lim Valve 2010 20 Pd 2222 SS Figure 4 10 The Result window summarises the results compared to limit values Note that the reason why the Data Cover age is 100 27 is that the calculations are done for the meteorological year 2012 which is a leap year The percentage of the Data Coverage is calculated with respect to standard year with 365 days Provided that the geographic location of receptor points are provided as X Y coordinates these will also be in the output for subsequent visualisation OSPMO has a simple built in graphical user interface for visualisation of results but results are usually visualised using external
34. e considered while the rest of the pollutants are not regarded as chemical reac tive You may run the model for any other pollutants as long as they can be regarded as inert i e no chemical reactions will be considered on the short urban transport time scales In order to run the model for other pollutants you have to replace both the emissions of one pollutant e g TSP in the three emission spreadsheets in the THOR AirPAS workbook e g THOR AirPAS Funen v14 xls and the background concentrations e g AQG hourly UserData dat with your new pollutant e g NMVOC Due to the implanted chemical reaction it is rec ommended to not use replace NO but the remaining five pollutants in case of model runs for new pollutants Appendix 3 Installation instructions for THOR AirPAS This section describes how the THOR AirPAS system can be installed on a second computer besides the one installed and used in the AirQGov project The following system requirements should be fulfilled on the PC where THOR AirPAS is to be installed e Windows XP or newer e EXCEL 2007 or newer e GIS software optional by Q GIS e Textpad TotalCommander optional but recommended Below the instruction of how to copy install THOR AirPAS on a new PC provided you have one valid THOR AirPAS compuer available 1 Copy the folder and all sub folders from c 7HOR_AirPAS to the same lo cation on the new PC 2 Copy the folder and all sub folders from c VApps
35. e ground much sooner than it would if a building or structure were not present The effect can greatly increase the resulting near by ground level pollutant concentrations downstream of the building or structure Buoyancy effect refers to the effect that buoyant plumes have on plume rise that also influences dispersion and concentrations For example the emissions from the flue gas stacks of industrial furnaces are buoyant because they are considerably warmer and less dense than the ambient air Hence UBM cannot replace a detailed modelling of point sources for estimation of stack heights or regulatory purposes but serves well for estimation of urban background concentrations In UBM a simple typical diurnal weekly time variation of the emissions distributed over the entire year is implemented i e no seasonal variation For this and other reasons only annual means are calculated when running UBM for the entire domain no other statistical parameters e g percentiles However some limit values are defined based on different statistical parameters See Appendix 1 These can be obtained in two ways in THOR AirPAS however only for limited number of receptor points As first option the user might use the hourly time series calculated with UBM for selected receptor points and use EXCEL or other software for post processing the data into the required statistics Another option is to use the very flexible and sophisticated statistics output facilitie
36. eptor 2 check boxes checked This indicates that calculations will be performed for receptor points on both sides of the street Next specify that the buildings along the street are different from 18 m within a certain section This is done by specifying the relevant wind sector Within the group Wind Sectors with Building Height Exceptions check the box below column 1 As an example enter 45 degrees for Lower Bound and 55 for Upper Bound The corresponding Height is set at 0 m The convention for direction is 0 or 360 for north 90 east etc The exception indicates that the building height is 0 m in the sector from 45 to 55 degrees More exceptions are entered see Figure 4 3 Finally press OK which brings you back to the New Project window Traffic variation Three options are available e Use the Pre defined Diurnal traffic types e Select a User File with the Average Diurnal Traffic data e Select a User File with Hourly Traffic Data Pre defined diurnal traffic For this option the Average Diurnal Traffic ADT in the street and the travel speed has to be specified The type of street has to be selected e g down town street The type of street defines the diurnal variation of traffic The temporal variation of the traffic is given by pre defined files for different types of streets For Danish conditions eight different pre defined street types have been identified based on a comprehensive analysis o
37. erm exposure for particularly sensitive population groups and where necessary immediate and appropriate information is required The in formation threshold for ozone has a value of 180 ug n for an hour and if exceeded information to the public about elevated ozone concentrations and recommended actions to particularly vulnerable population groups has to be given An alert information threshold is a level where human health is at risk if ex ceeded and the Member States must take immediate action The alert threshold for ozone is 240 ug m for more than 3 hours and it requires in formation to the public about the elevated ozone concentrations and also recommended actions In the case of Denmark evaluation of compliance with limit values etc takes place in the National Monitoring Programme for the Aquatic and Terres trial Environment NOVANA based primarily on measurements at fixed stations in the largest Danish cities but also supplemented by modelling at selected locations Ellermann et al 2013 The Danish Environmental Protec tion Agency has the overall responsibility for compliance with air quality limit values Table A1 summaries most limit values target values and information and alert thresholds in the air quality directives 45 Table A1 Summary of limit values target values long term objectives and information and alert thresholds Substance Limit value ug m Averaging period Statistics Protection of Year to be met
38. eteorological data Landuse 5 SPREAD emissions Urban background model Urban backgrou nd UBM concentrations COPERT 4 Street pollution model p Street concentrations emissions OSPM Street geometry and traffic data Figure 2 2 Diagram for over all data flow between air quality models in air pollution as sessment system The regional model DEHM requires emission and meteorological inputs and provides regional background concentrations to the urban background model UBM and also outputs of meteorological data for UBM Apart from meteorological data UBM also requires emission data that is provided by the SPREAD emission model This model makes a geographical distribution of national emissions based on different geographic variables for the different emission sources or it uses a locally generated emission inventory The spatial resolution is usually 1 km x 1 km Street concentrations are modelled with the OSPM UBM provides urban background concentrations and also meteorological data as input for the OSPM The COPERT IV emission model is integrated into OSPM OSPMO also requires input about the street geometry and traffic data at the location where calculations are carried out 2 3 Outcomes The air pollution assessment system generates regional background concentrations for a city urban background concentrations for a city and street concentrations for selected streets in the city Hence the system provides the spat
39. f measured traffic data from different types of streets in different regions of Denmark These files come with the OSPM installation and have the extension trf The percentage distribution as a faction between the following vehicle categories has to be provided passenger cars incl small vans 0 2 ton vans trucks 32 ton heavy duty trucks 32 ton and busses There are eight different diurnal variations in the following order Monday Thursday not July Friday not July Saturday not July and Sunday not July and Monday Thursday July Friday July Saturday July and Sunday July The temporal variation of traffic is different for July compared to other months of the year since it is holiday month in Denmark The diurnal variation for travel speed of passenger cars and vans and for trucks and buses has to be specified The diurnal variation of the travel speed is given as a factor of the mean diurnal travel The diurnal variation of cold starts for petrol powered passenger cars has to be given as a percentage of passenger cars A cold engine is defined as an engine that has been turned on less than 2 5 minutes ago and that has not been running for the last two hours Default values are provided for Danish conditions for the above described parameters Select a User Defined File with the Average Diurnal Traffic data The temporal variation of traffic may also be given in absolute numbers in a file format similar t
40. f the street with buildings as a folded piece of cardboard Figure 4 4 The drawing in the Street Configuration window shows the street with the buildings unfolded Figure 4 4 Visualisation of the street configuration 19 20 As an example enter the following data Enter 18 m for Default Height indicating that most buildings on both sides of the street are 18 m Later it is possible to define exceptions from this default value When you move the cursor from the field with numbers e g by pressing Enter or Tab the drawing is updated OSPM calculates the general building height based on the data entered The general building height is used internally in the OSPM to calculate residence time and downscaling roof top wind speed to street level Leave Width the width of the street at 25 m Leave Length 1 at 70 m and Length 2 at 50 meter These values are the distance from the receptors Rec 1 and Rec 2 where concentrations are calculated to the beginning and end of the street The beginning and the end of the street should be interpreted as beginning and end of a street section between two intersections Note however that you should not indicate values larger than 200 m even if the distances may be greater Set Orientation at 30 thus indicating that the street s orientation is 30 degrees in relation to north Define the Receptor Height at 2 m Leave the Receptor 1 and the Rec
41. fs dh os ja ja eh mm uam Dsum DE nem E 11 500000506560 G urc GMT NO 03 pob 27 85 27 85 1 35 6 09 28 09 28 09 zB 74 zb 74 25 74 26 4 16 4 26 4 25 96 coo oa eo oeoeetebs c G8 oDOe et ooo oe imm B Using your own meteorological and regional background input file You may produce you own input file ASCII text format based on your modelled or measured data provided you keep exactly the same structure One recommended method is to use an EXCEL file having the correct col umns and data structure See Figure below 5 T Lu Y Ww x Fi AA AB AC AD Uu Wo T Global Monin air surface Hmix fmf direction Celci radiation sheat Obukhov density pressure s fromN us W m wstar ustar sw W m Length m kg m hPa 3 9 47 79 4 08 D 078 037 053 9 54 95 22 1 31 1009 07 g 0 o 4 1 4249 4 41 D 0 73 035 081 30 27 126 55 131 1009 01 5 7 43 05 4 55 0 073 036 081 32 61 131 12 L31 1008 57 al 43 93 4 84 O 081 U3f 0835 33 53 137 1 131 1008 97 482 44 77 4 99 087 037 05 33 45 138 3 131 100831 4 3 AS BI 5 12 D 0 037 088 32 03 43 25 1 31 1008 86 4 3 47 37 5 18 D 0 79 035 088 31 57 153 68 131 1008 89 0 44 48 35 5 27 271 081 3B 0 6 31 22 157 86 1 31 1006 94 o 0 ou 4 44 48 41 5 47 1153 O75 038 085 31 19 160 4 131 1008 98 Q 0 ora 2 3 38 67 5 34 17 33 0 89 04 097 20 43 139 34 131 1009 0 0 4 5 4460 5 31 19 71
42. g a new country is a very tricky procedure and should not be done until later when you have gained some experience with WinOSPM If you have previously entered a valid license key on this PC this key will remain valid otherwise you have to enter your license key 6 Synchronise files between old new PC in c Apps WinOSPM and subfol des Use e g TotalCommander 7 Decimal separator should be dot The recommendation is to use dot as decimal separator and as digit grouping use nothing or space Our aim is to have WinOSPM running with all kind of regional settings and it works for database files EXCEL ACCESS However there may still be problems to get things running properly if text ASCII files are involved since number formatting can be very confusing e g the number 23456 can be written in various version 23 456 23 456 23 456 23 456 0 8 Install OSPM help Windows Path update WinOSPM is using an older version of Windows Help that is not installed from the beginning any longer on newer Windows systems however it can be installed manually First time you try to use Help in WinOSPM e g by pressing the key F1 you will be guided and can download and install the missing components WinHIp32 exe Messages could look like this gt Why can t I get Help from this program The Help for this program was created in Windows Help format which de pends on a feature that isn t included in this version of Windows
43. ial distribution of air quality levels of health related pollutants in a city and these results can be compared with air quality limit values or guidelines The system is able to predict past present and future air quality levels provided emission and other required input data is available The system also provides information about total emissions and their distribution on different sources It is possible to attribute emissions from different type of sources to air quality levels The system enables impact assessment of different policy measures on emissions and air quality levels e g impacts of urban planning and transportation schemes Details on limit values target values long term objectives and information and alert thresholds for different substances of the air quality directive from 2008 2008 50 EC on ambient air quality and cleaner air for Europe is given in Appendix 1 2 4 Specifications and model limitations This section describes specific features of the THOR AirPAS modelling system which is of interest for the users The spatial resolution in both the emission distribution and UBM is presently fixed to 1 km x 1 km In principle it is possible to change the spatial resolution to smaller or larger values However this would require changes in the input data and model parameters Therefore it is not part of this project In the present version of the model meteorological input and regional background concentrations a
44. icles and different emission classes is also built into the emission model Default information about the Danish car fleet comes with the OSPMO but the user is able to modify the emission model or set up another emission model based on the methodology built into OSPM Meteorology and background data The OSPM model requires hourly wind speed wind direction temperature and global radiation and urban background pollution data as input The wind speed and wind direction must be those above roof level in 23 24 the city The rest of the data should be from an urban background station top of roof or surface station nearby Data from atmospheric chemical transport models can also be used if urban background data are not available In the AirQGov RPP3 project meteorological data from DEHM are available for OSPM and the background air pollution data from UBM can be calculated for OSPM The choice of Predefined meteorological and background data refers to predefined data for Danish conditions However in the example choose User defined data and click Add file see Figure 4 7 Meteorology B ackground Measured Concentrations Pre defined User defined meteorological and data backaround data File Names NENNEN Figure 4 7 Meteorology and urban background data are defined in this section of the New Project window Navigate to file that includes the meteorology and urban background data The names of the v
45. iled and might be updated less frequently than national data Sources of free spatial data are e g e OpenStreetMap e g roads buildings land use and railways examples are given in Figure 5 4 http download geofabrik de e Landscan population density at a resolution of approximately 1x1 km example is given in Figure 5 5a http web ornl gov sci landscan index shtml e Centre for International Earth Science Information Network CIESIN population density at a resolution of 2 5 arc minutes 5km at the equa 33 34 tor example is given in Figure 5 5b http sedac ciesin columbia edu data collection gpw v3 Examples of international datasets a d railways roads buildings and land use from OpenStreetMap e population density from Landscan and f population density from CIESIN roads cycleway railways footway abandoned living street construction path light_rail pedestrian platform 9 residential preserved 1 road rail E service subway p lt y steps traverser amp tertiary wm turntable Woo T TERRIER Tear unclassified E i ME De Grego buildings EH ofice EE pening apartments EJ place of worship EZ bicycle parking E prison ERU cate BI pudre EN church MI public building Es cinema EX residential EE garages mE ruins ES house a school Ea hut raum social centre Lo industrial E theatre EN kindergarten em uni
46. ily average emission factors are displayed and will be updated when another scenario year is selected Any detailed information about travel speed diurnal variation of the traffic distribution between vehicle categories at the specific street can be changed and the edited traffic file can be saved under a user defined name Since this information is usually difficult to obtain the traffic standard type C was preselected as a first suggestion Two output files are also automatically specified Hourly Output Files will include an hourly time series of street concentrations and a file under Statistics and other that will include statistical parameters like average etc These files are filled with data when the OSPM run is finished Click the button Run to start the OSPM simulation The calculated street concentrations can be viewed in the output files that OSPM provides an interface for A pop up window also automatically appears with summary statistics Not explained here for reference see Figure 4 10 Additionally 2 EXCEL files are produced named OSPM Hourly XXX xls and OSPM StatOut XXX xls with XXX replaced by the RunName specified in the UBM inputs They contain the hourly results and the statistics Average concentration in the background and the two sides of the street number of hours calculated respectively for the specified calculation period The THOR AirPAS user interface includes a tool to convert OSPM res
47. input data than normal calculations it requires only information about street configuration Street configuration Information is required about the street geometry also named street configuration Default building height of buildings in the street building height in wind sectors that differ from the default height exceptions street orientation street width between building facades distances from receptor point to street intersections receptors one or two sides and height of receptors Press the button Set Street Configuration in order to define the street configuration ie the width of the street building heights and the orientation of the street You are brought to the Street Configuration window Figure 4 3 where these street configurations are set W Street Configuration ui titled File Edit Graph ee Street Geometry Default Height m Width m Length 1 m Length 2 m da E Street Name Example Street Receptor Height mM 2 Iw Receptor 1 Iw Receptor 2 18 62222 Wind sacon with Bunding Ts Exceptions 10 11 12 fores miae ed ooo ela Ure Bouna Wi wei ec SS SSS Sal pmi m o o ed ee e MOMENTE AS SEE EET I ESI ISI E Beset OK Cancel Help Figure 4 3 The Street Configuration window with drawing indicating the placement of receptor 1 and 2 and variable building heights along both sides of the street You may think o
48. ion factors are available the default emission factors from the EMEP EEA Guidebook can be re placed in the model The output of the emission model for other mobile sources is presented in a separate worksheet that forms the input to the spatial distribution 5 2 Spatial distribution In order to add a geographical component to the emission inventories for relevant sectors it is necessary to include various digitized spatial data The data have to be in a format shape files raster files personal geodatabase or file geodatabase compatible with a GIS program ArcGIS or OGIS open source The minimum requirements to create a reliable spatial distribution are to have the following spatial datasets e City boundary defining the area for the city inventory e Road network e Land use map including settlement commercial institutional and in dustrial areas e Population density Other spatial datasets that could significantly improve the spatial distribu tion are for example e Road map including road types urban rural high way road width annual average number of vehicles and annual average mileage e Land use including settlement commercial institutional industrial ar eas urban rural areas and building types e Heating districts including information on one or more available heat ing types and the share of accommodations connected to the district heating network e If additional major emissions sources are identified
49. n F Tekst 14435_AirQGov Guidance report Example data VOSPM example osp File Project View Tools Settings Mode Help A 8 Wd iE rm iwi d m m New Open Save Street TrfFile V List Fist Units Traffic Vehicles Fuels NI zy TrafEdit EmiFact Graphics Output Files Scenario Year Input Files CAT Hourly Input Files F Tekst 14435 AwOGov Guidance repor E xample data y Trt Fite CA Datas Traffic National DE Type_A tf W List File CX XX x ADK MehiclesDK 12 2013rmd vil y F List Fie CNN ADK Muels 1993 EI FC PN fll Average Diumal Traffic File uii Average Daily Traffic C Apps win0SPM Data T raffic amp M ationaNDKAT ype_A4 tf il Travel Speed km h I City Size inhabitants Hourly Output Files Move File i CondFile none Down Street Data Input Name Example Street iis g m CET E Height 18m Width 25m Onentation 30 deg Start End Dates v Auto Iv Auto Start Date End Date dd mmeyy hh dd mm yy hh lO ES Figure 4 9 The Calculation window This window is the central working window Result window At the end of calculations you are brought to the Result window Figure 4 10 This window shows statistical summary data compared to various air quality limit values These limit values are country specific The parameters are computed for receptor number 1 and 2 at each side of the street There is a sheet with results for each receptor As default a sheet is presented which contains ma
50. nding distribution keys as shown in Table 5 8 A more detailed description is give in the training exercise Spa tial distribution of emissions handed out at the training work shop Loses sisi ris 3 ee oe ee EJ z i J la ds e dei e a ai CA e Sp aaa n ENS AZ d Bs RE IU Hi im Rangni es E i a a a i D ETE de ld E g 1 s u om m HE ssi pp ed b a lanuen e ik mL Hg eta ee apon ab aag 3 E niie m c imm llas mie T c pm HR si ta sena trip gi ee a gl Sete enge piera o a Ln aem dede bri is T arpa a ima ubt ficare rt Ferien el react p el rer es a a DII n TAE Hpi dii mnn l dde e de eer a ai A da rdg ia diu Ms rursum bes lerem ei A ed ud maua Bs gt cz od A sr Bs onm cz M ol A Lang HI S E 40 SACA Wc x Kai a Add en i Rang Hi te p 9 ey B Wm m Heb as 24 Ren A LT Uns LES E Fidis DE nint oe E jjo rT y D Lama EI E e mo bue B ica it m Qm m gn ist TO c i D Mnisi i damad IT 2 ham pa prs Ba biym y rita babes Lom s m Nauk To gt diini 3 A F Wibi la Raga RSS AN ST n uea Labri H tare H Jars mo Dami d parum ia ager M EIL Urn ES IU IL Md A a Cr Rea Pe Liesl DAA A p r 19 RI a ls dde ee ei de PII km Seda my la d s ee di ees a ii A e yg ar as Mole od LA Am dd TELLE Diii Ld ol E E A S
51. ng From a drop down list allows you to choose country The country setting defines the choice of data for national car fleet composition and for fuel quality Furthermore this setting determines which standard predefined data will be available The program is currently distributed with a set of predefined data for Denmark A new country entry can be created by selecting the Add New item For this example choose Denmark A new project Select File Create New Project or click on the New button in order to start a new project You will be asked to choose a Working Directory ie a folder where project related files are kept The next window is the Project Type window Figure 4 1 _ Single Street Multi Streets OK Cancel Help Figure 4 1 Two different project types can be created for the WinOSPM calculations Two different project types can be created for the WinOSPM calculations e Single Street e Multi Streets For this example select the Single Street project type Multi Streets refer to running OSPM with more than one street at the time 17 Accepting the Single Street project type click OK or double click on the icon leads you to the New Project window Figure 4 2 Please note that you will only meet the New Project window when you create a new project The central working window for existing projects is a different one the Calculation window Figure 4 9
52. nt 31 4169 4191 EEA 2013 EMEP EEA air pollutant emission inventory guidebook 2013 Technical guidance to prepare national emission inventories EEA Technical report No 12 2013 Ellermann T Nejgaard J K Nordstrem C Brandt J Christensen J Ket Zel M Jansen S Massling A amp Jensen S S 2013 The Danish Air Quality Monitoring Programme Annual Summary for 2012 Aarhus University DCE Danish Centre for Environment and Energy 59 pp Scientific Report from DCE Danish Centre for Environment and Energy No 67 Available at http dce2 au dk pub SR67 pdf 43 44 EU 2008 DIRECTIVE 2008 50 EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 21 May 2008 on ambient air quality and cleaner air for Europe Kakosimos K E Hertel O Ketzel M amp Berkowicz R 2011 Operational Street Pollution Model OSPM a review of performed validation studies and future prospects Environmental Chemistry 7 485 503 http www publish csiro au paper EN10070 Plejdrup M S amp Gyldenk rne S 2011 Spatial distribution of emissions to air the SPREAD model National Environmental Research Institute Aar hus University Denmark 72 pp NERI Technical Report no FR823 http www dmu dk Pub FR823 pdf WHO 2006 Air quality guidelines Global update 2005 Appendix 1 EU limit values Air Quality Limit Values in the European Union The air quality directive from 2008 2008 50 EC on ambient air qu
53. nt csv UBM Urban Background Model Grid or Rec val Calculate for whole grid o EditRec val StartDate Run UBM EndDate RunName FolderName Export of UBM Emissions Sum of Transport and Area or Point including Scaling Export T A as polygon shape Open in TextPad Export Point Emi as shape file Export of UBM concentration results averages only Export as GIS polygon shp file Open in TextPad Export as GIS point shp file OSPM Operational Street Pollution model StreetName OSPM Project Name Height m OSPMproject_Funen_Example osp Width m ProjPathName as in UBM Orientation deg Funen_v14 Daily Traffic veh day Vehicle Speed km h Start OSPM with selected options Export data from OSPM_Results Show OSPM result sheet Export as GIS point shp file Figure 3 1 Graphical user interface for THOR AirPAS modelling system Sample data is shown for Copenhagen 10 All input and output data are associated to the Excel file e g THOR AirPAS Funen v14 xls and the name of the Excel file should be used to specify e g different scenarios that have different assumptions of scenario years emissions etc The front end graphical user interface is placed in the Excel sheet named RunModels DEHM Regional background and meteorology An interface is provided to the regional background concentrations calculated with DEHM and the meteorological data Figure 3 2 It is possible
54. o o ala amas roam ke m Fami ors ceras cia nan aiam DLL LL Qum mcm nmgr E tar ees oca sk ay came Peur LIE bh La ora c ana afa aca rome tes be br copter tre em E imus menis nma EEN ru LADA A LP F D n mn Q aia ie s Bien a orm n ee eae Eia bad di Sone d um heee opem He Fe RS ebd ou eT iter slm wu ma marrk Far TSUEDSH TENTE e Eidem eis P tie p a ss j pam ARTS dI bim RETS ddr liem mii di lim di di Jim AUN AL Lee REM dij lim aum amd m RENS ic sum dig lim ARM FIR jim REM D ihe and dx m aii dul Sarl T A wil m Bi ail jim REPE m lire i 4TT jim abi mis lie Ai Ad AB mi ALT Hu BP an Hem ELI mua lim AP ms ies REIP mas lim AIT 51 iem al Jim SUN Mk im ak wit lies ARI Gd m si win REM EIE im Ail REN NJ Aug xr Deux boa her jar ami iuge ara Dm Ln Jg d A LT eiii ESH BELI og did F ciel m LEINLETES E 144110 mp wa My aan Lad Ta Vasto be aul bes reget apap a a La hn entis en o ia Table 5 6 Example of total sectoral emissions for SNAP 02 for selected pollutants rob Fae eet Da gem EE ee as owe lo Lir b Lid cw s ma dmm o mom Ld her plam es te omms tr Y lA JU PI Ee O me ome C e G ttt 224 40 Table 5 7 Example of distribution key for area sources for SNAP 02 and calculation of spatial emis sions for selected pollut
55. o the pre defined format Select a User Defined File with Hourly Traffic Data Traffic data may also be imported as hourly time series of traffic data for a whole year Your next task is to specify Traffic Data i e the distribution of traffic flow over time for all types of vehicles An easy way to do this is by applying standard values Do so by choosing Pre defined diurnal traffic types Alternatively it is possible to apply files with user defined data The relevant part of the New Project window is shown in Figure 4 5 21 22 Set Traffic Data e Pre defined diurnal traffic C User defined lypes data fpe A amp Average Daily Traffic Veh day 25400 e Traffic Data in Travel Speed Hourly User Files km h Po 30 N B Can be set with other User defined data Traffic File Name C Sw inDSPM D ata T raffic amp N ational Dk View E dit Traffic Figure 4 5 Traffic data are defined in this section of the New Project window As an example choose Type_A When the cursor moves over the field a brief explanatory note is shown In this case Transit road in medium sized or smaller cities A pre defined traffic data set like the one used is a file with information on the relative distribution of vehicle types such as e g passenger cars vans trucks and buses over time The country setting determines the availability of pre defined traffic data In order to use the pre defined traffic data
56. of PM25 and PMio Non exhaust includes particles from road wear tyre wear brake wear and re suspension of particles Furthermore fuel consumption can be outputted and then CO emission can be calculated OSPMO is extremely flexible in its ability to create user defined output files of various contents and formats However in the current example we will not use this potential but just rely on standard output which summarises the results of the calculations Press OK to leave the New Project window Note It is not possible to return to the New Project window later It is not necessary to return here because all options can be changed from other windows Calculation wndow You are brought to the Calculation window Figure 4 9 This is the central working window where all further modifications of the project can be defined It is recommended that you save all data specified so far by pressing the Save button and supplying a name e g Example Street The default file extension for WinOSPM Single Street projects osp is automatically added to the file name Next time you want to open this project it s enough to double click on the project name in the Windows Explorer and this will start the project in WinOSPM Press Run to perform calculations for a year A counter in the lower left corner shows the progress The calculations will take about 10 seconds on a strong PC 25 LU WinOSPM Calculatio
57. of the same resolution The method to set up a distribution key for a given source is outlined below road transport has been chosen as an example and GIS file refers to a format appropriate for the GIS program used 1 Define the area of interest e g the city and create a corresponding GIS file 2 Create a grid that cover the area of interest with the decided resolution GIS file 3 Calculate the total emissions from road transport for the area of interest using the road transport model 4 Select the most appropriate road transport data set road network GIS file 5 Intersect the grid and the road network ArcMap Figure 5 6 a c and QGIS Figure 5 7 a c 6 Open the attribute table and add a column ArcMap Figure 5 6 d f and QGIS Figure 5 7 d f 7 Calculate the length of each line segment ArcMap Figure 5 6 g h OGIS Figure 5 7 g Note to set up a distribution key use calculate area instead of calculate length 8 Open the attribute table and add a column ArcMap Figure 5 6 i OGIS Figure 5 7 h 9 Calculate the sum of Shape Length for all rows ArcMap Figure 5 6 j OGIS Figure 5 7 i k 35 10 Calculate ShareOfLength ArcMap Figure 5 6 k n OGIS Figure 5 7 l n 11 Import the attribute table to Excel as a pivot table Figure 5 8 a g 12 Calculate spatial emissions using the total sectorial emissions Table 5 4 for point sources area sources and mobile sources and the cor respo
58. oject USERKbh 3src OSPMproject_20140618 0sp File Project View Tools TrafEdit EmiFact Graphics CAT i Tif File List File ala ls la CALA ADataWTrafficANationaMDKAType_C tf CAA ALA ADK WehiclesDK12_2013mil_M2_F Settings tt H e Y R Street Trf File V List F List Units Traffic Vehicles Fuels esuli Denmark Start Special 2013 Input Files Hourly Input Files Qu f C THOR_AwPAS UBM_urban output 201 2010101 _hourly A 3 7 Move File F List File CX NDKNFuels 1989 EI FC PN fl Average Diumal Traffic File Up Average Daily Traffic 22000 v AType C tf Travel Speed km h 45 MCN ACH Output Files xr iri Move File Cond File none v C ATHOR_AuPAS Project_USER Kbh_3stc 0SPM_Hourly Down Street Data Concentration Units Input Output NO pgm pgn AT EA T Height 23m NO2 ug im arme CATHOR_A0PAS Project USERAKbh_3s1c10SPM_StatO a 03 ug m ug me Width 20 m co Wg mP palm Benzene n m Orientation 120 deg PM10 vs aes PM25 pg m palm Start End Dates E mitted Compounds p Auto v Auto Remove Fie Change Fie Start Date End Date dd mm yy hh dd mm yy hh Figure 3 7 Graphical user interface for OSPM As described above the urban background concentrations calculated by UBM and meteorological data are automatically carried on to OSPM and appear under Hourly Input Files This file is the resulting file from UBM calculations and was
59. on factors are available the default emission factors from the EMEP EEA Guidebook can simply be replaced in the mod el 1 http www eea europa eu publications emep eea guidebook 2013 Russian ver sion should be available during 2014 The output of the emission model for point sources is presented in a sepa rate worksheet that forms the input to the spatial distribution Area sources As mentioned area sources mainly cover the residential sector and small combustion installations in industry and the commercial institutional sec tor The required input is fuel consumption data for different fuels coal brown coal residual oil gas oil natural gas and wood and fuel burning technologies e g boiler stove engine and turbine The fuel consumption data can be reported in energy or physical units and is converted in the same way as explained under point sources The fuel consumption is then multiplied with emission factors In the model the standard emission factors are taken from the EMEP EEA Guidebook and refer to both Tier 1 and Tier 2 emission factors Similarly to point sources country specific and city specific values can be implemented if available The output of the emission model for area sources is presented in a separate worksheet that forms the input to the spatial distribution 5 1 2 Mobile combustion Mobile combustion covers a variety of sources including road transport navigation railways aviation and non road
60. oordinates Concentrations in ppb of NO NO and Os Concentration of CO in ppb Notice in the met file the unit is wrongly denoted as ppm Concentration of SO in ppb Concentrations of secondary inorganic particles NOT PRESENTLY USED but is included as a part of PM 5 PM10 and TSP Concentrations of primary particles NOT PRESENTLY USED but is included as a part of PM25 PMio and TSP Concentrations of Total Suspended Matter Total Particle mass included both primary and secondary particles Particle number concentration NOT PRESENT LY USED Mixing height Wind speed Wind direction Temperature Global radiation Can be calculated from cloud cover if not available Convective velocity scale Can be calculated from the following if sheat gt 0 then wstar ustar hmix 0 4 abs MOL 1 3 else wstar 0 Endif Friction velocity Standard deviation of vertical velocity Can be calculated from the following sw0 0 06 sw sqrt ustar 2 sw0 2 wstar 2 Surface heat flux Can be calculated from the following MOL 1004 0 rho temp 273 15 ustar 3 3 9 sheat Can be calculated from the following rho spres 100 287 temp 273 15 Surface pressure NOT PRESENTLY USED can be used to calculate global radiation NOT PRESENTLY USED Relative humidity 47 A B E D hour da Y ma nth year 1 010 1 010 2010 2010 010 2010 010 2010 2010 2010 2010 2010 010 uuu j h gi pi fs ja
61. ort provides an outline of the THOR AirPAS air pollution assessment system and a brief manual for getting started with the air quality models and input data included in THOR AIrPAS RPP3 The Regional Pilot Project 3 Development and Implementation of an air pollution assessment system to estimate effects of different urban planning and transpor tation schemes in the partner countries ISBN 978 87 7156 107 4 ISSN 2245 019X
62. portant outcome of the spatial modelling is to provide input for the air quality modelling Table 5 8 5 9 and 5 10 below are examples of the output format for the spatial distribution that is used by air quality models For more information see Chapters 3 and 4 Table 5 8 Example of data output for point sources from the spatial model after running macro GeneratePointSources used as input for air quality modelling F z i A A BT e D e Ee TA A a PA 1 SNAP X coordinate Y coordinate Projection Stack height NOx SO2 CO TSP PM10 PM2 5 NMVOC 2 fos 586759 6134661 WGS84 UTM32N 150 134 805 528 9 5 6115 7 353 4 9665 2 193 0 645 3 01 571936 6126988 WGS84 UTM32N 90 372 892 1299 87 39 6526 92 9604 66 1752 50 6818 6 0398 4 01 610964 6129059 WGS84 UTM32N 130 2 669285 0 011906 1 665125 0 037709 0 037709 0 037709 0 109314 E 103 609779 6105713 WGS84 UTM32N 60 231 8646 909 708 9 65178 12 64716 8 54238 3 77196 1 1094 6 03 555718 6147392 WGS84 UTM32N 60 0 154346 0 000904 0 015435 0 000643 0 000643 0 000643 0 005145 01 566007 90 0 003535 0 003535 0 003535 0 010328 Area sources Table 5 9 Example of data output for area sources from the spatial model after running macro GenerateAreaSources used as input for air quality modelling A B C D E F G H k L SNAP GridID X 7 Projection Nox S02 co TSP PM10 PM2 5 NMVOC 2 02 1km 6089 599 599500 6089500 WGS84 UTM32N 0 0 0 0 0 0
63. r point sources to the spatial distribution 01 135 ME 2 1o 93 03 os sem cemnmpeecumam eal e el as 11 01 594258 61092010WGS84 UTM32N 150 82 286 9 20 A B E D E G H J K L SNAP X coordinate Y coordinate Projection Stack height co 61 150 a A 01 571936 6126988 WGS84 UTM32N 2 o 01 610964 6129059 WGS84 UTM32N L 001 1e 00 03 555718 6147392 WG584 UTM32N 60 RE 566007 6153496 WGS84_UTM32N L so ess woof osf ooo 9 604547 6156635 WGS84 UTM32N 150 1706 227 1895 3622 10 03 557126 6123019 WGS84 UTM32N 60 573 2247 ME a 12 01 574901 6106759 WGS84 UTM32N of azs 001 ote o o 13 01 601583 6112165 WGS84 UTM32N 2696 10578 1 Sector TSP non exh PM10 non exh PM2 5 non exh NMVOC 2 3 p easel al sana sua pal po 1020 9 03 27179 43 50 294 73 29 07 27 62 2660 PMA Residential combustion Industrial commercial plants Table 5 4 Example of input from the emission model for road transport to the spatial distribution A C D E F B H J K L Sector SNAP Nox 02 co TSP PMi10 PM2 5 TSP non exh PM10 non exh PM2 5 non exh NMVOC Passenger cars 207 71 0 52 2472 44 7 77 7 77 7 77 14 37 9 76 5 12 Light duty vehicles 0702 65 08 0 12 12435 5 69 5 69 569 343 242 126 Heavy duty vehicles amp buses 0703 19991 0 18 6123 275 275 275 601 398 X 235 Mopeds 07004 029 ooo 1437 015 015 015 O06 ooa 002
64. rage_Conc 13 Under the Excel sheet ParameterUBM the advanced user can specify a number of parameters for UBM This sheet is hidden by default but can be unhidden for advanced users OSPM Operational Street Pollution Model The front end interface to OSPM is shown in Figure 3 6 OSPM Operational Street Pollution model StreetName OSPM Project Name Height m OSPMproject Funen Example osp Width m ProjPathName as in UBM Orientation deg Funen v14 Start OSPM with selected options Export data from OSPM Results Show OSPM result sheet Export as GIS point shp file Figure 3 6 Graphical user interface for OSPM Daily Traffic veh day Vehicle Speed km h The user may change the green highlighted cells The following parameters can be specified for one street within a project street name StreetName the general building height in the street defined as the most abundant building height Height m the street width between opposite building facades in the street Width m the street orientation in relation to north Orientation deg the annual average daily traffic Daily Traffic veh day and the travel speed Vehicle Speed km h Once the above parameters have been specified click the button Start OSPM with selected options and the start up window for OSPMQ appears see Figure 3 7 AJ 3 ud New Open Save w 3 WinOSPM Calculation CATHOR AirPAS Pr
65. re provided for the years 2000 2012 And UBM is set up to calculate the following pollutants NO nitrogen oxides NO nitrogen dioxide Oz ozone SO sulphur dioxide CO carbon monoxide TSP total suspended particulate matter PMio particles less than 10 micrometer in diameter and PM particles less than 10 micrometer in diameter The OSPM will calculate results for NOx NO Os CO PMio and PM 5 The model can also be set up to run for other years and pollutants as described in Appendix 2 The emissions are presently regarded as the largest uncertainty in the modelling system It is therefore recommended that calibration of the UBM model for local conditions should be done via the advanced emission scaling options described in Figure 3 5 For proper calibration of UBM regional background and in urban background measurements are required The present version of DEHM does not yet include natural wind blown dust emissions This might lead to an underestimation of especially TSP in the dry season in regions with high emissions from natural wind blown dust UBM includes a relatively simple point source module not taking downwash or buoyancy effects into account Downwash refers to the effect can have on dispersion and concentrations When an air pollution plume flows over nearby buildings or other structures turbulent eddies are formed in the downwind side of the building Those eddies cause a plume to be forced down to th
66. s in WinOSPM for both background and street concentrations See WinOSPM online help or user manual The chemical reactivity of most of the typical urban pollutants is relatively slow compared to the short transport times in the urban areas Therefore no deposition chemistry or particle transformation except for the NO NO2 O3 chemistry is considered in UBM and OSPM The share of direct NO in the NO emissions is presently set to a typical average value of 15 If the user has more detailed information the value can be changed in the advanced options In order to have the UBM easy to use and fast to run on a PC no relief orography or variation of meteorology within the domain is considered in the model In most cases this has shown to produce satisfying results in typical urban settings 3 Front end system user interface The front end graphical user interface of THOR AirPAS is included in MS Excel The interface provides an overview of input data and eases data flow between air quality models and visualisation of results see Figure 3 1 THOR AirPAS Air Pollution Assessment System Setup for Denmark Funen years 2000 2012 DEHM Regional background and meteorology Open DEHM file in TextPad DEHM file AQG_hourly_ Danmark cph dat SPREAD Urban Emissions Show Transport Emi Transport emissions Funen Transport csv Show Area Emi Other area emissions Funen_Area csv Show Point Emi Point source emissions Funen Poi
67. saved as an Excel sheet with the name Hourly Conc that includes an hourly time series of the first receptor point in Rec_eval Information about traffic and speed are also carried on to OSPM and appear under Average Daily Traffic and Travel Speed The parameters about the street name and street geometry appear under Street Data and the street data can be visualised if you click the button Street The start and end dates do not appear under Start End Dates but OSPM will run for the time period defined by the hourly input file of the urban background concentrations However if you specify other start and end dates under Start End Dates then these will be used Make sure that specified start and end dates are within the time period that was used for UBM calculations otherwise there will be no urban background and meteorological data for the OSPM simulations The scenario year has to be specified under Scenario year The scenario year defines the year of the emission factors Only Danish emission factors 15 are installed at the moment In order to compensate for higher emission factors in the ENPI East countries earlier Danish years could be used accordingly Double click on Average Diurnal Traffic File in the Input Files section displayed in Figure 3 7 here Type C is preselected will open the Traffic window see Figure 4 6 for more details In the lower part of the traffic window the da
68. set up in pilot cities in Armenia Azerbaijan Belarus Georgia Moldova Russian Federation and Ukraine The target group for the report is administrators planners and technicians involved in hand on use of the air pollution assessment system named THOR AirPAS A simple front end user interface has been developed to easy interact with the input data air quality models and output data The report provides an outline of the air pollution assessment system and a general description of the user interface to the system It provides a getting started manual for UBM OSPMO and the SPREAD emission model THOR AirPAS is based on parts of the Integrated Air Pollution Forecasting and Management System THOR developed by Aarhus University Department of Environmental Science Denmark The model system includes three air quality models one for predicting regional air quality levels DEHM one for predicting urban background air quality levels UBM and one for predicting street levels OSPM OSPM is a registered trademark The air quality models require input data about emissions and meteorology as well as other inputs The spatial distribution of emissions for UBM for the individual cities has been prepared using the SPREAD emission model 2 Outline of air pollution assessment system This chapter provides a conceptual outline of the air pollution assessment system an overview of the general data flow in the system and outlines the outcomes of
69. the system 2 1 Conceptual system outline A conceptual outline of the air quality assessment system is given in Figure 2 Street level concentrations Concentration Local increment street increment OSPM Urban background concentrations urban increment UBM regional background DEHM Figure 2 1 Conceptual outline for air pollution assessment system for estimation of intra urban variability in air quality e city 3 distance The system models regional background concentrations urban background concentrations and street concentrations Regional background concentrations are influenced by emissions on the Northern hemisphere including national emissions and represent the long range transported air pollution Regional concentration levels represent the air quality of a larger area and air quality monitor stations measuring regional concentration are named regional rural or background stations The regional concentrations provide the background concentrations to e g a city Urban background concentrations include the regional contribution and the contribution from emissions of the city in question Urban background concentrations exhibit geographical variation over a city depending of the geographical variation of emissions Urban background concentrations represent the air quality at roof top level or in a park and are not directly influenced by a single nearby local emissions Air quality monitor st
70. ts of different urban planning and transportation schemes in the partner countries Air pollution manual user interface air quality models emissions Ann Katrine Holme Christoffersen Department of Environmental Science Aarhus University 978 87 7156 107 4 2245 019X 5 The report is available in electronic format pdf at http dce2 au dk pub TR46 pdf Content 1 Introduction 2 Outline of air pollution assessment system 2 1 Conceptual system outline 2 2 Overall data flow 2 3 Outcomes 2 4 Specifications and model limitations 3 Front end system user interface 4 OSPM street concentrations 5 Emissions and spatial distribution 5 1 Emission estimation 5 2 Spatial distribution References Appendix 1 EU limit values Appendix 2 Meteorological and background input data Appendix 3 Installation instructions for THOR AirPAS CON NJ Os o1 10 17 28 28 30 43 45 47 49 Blank page Introduction The overall objective of the AirQGov Regional Pilot Project 3 AirOGov RPP3 is to set up the integrated air pollution assessment system THOR AirPAS for one pilot city per partner country EU project on air quality governance see http airgovernance eu THOR AirPAS can be used for high resolution urban air quality modelling with potential applications for assessment of policy measures within urban planning and transportation schemes During the project the air pollution assessment system will be
71. ults for one or several streets into GIS point shape files in order to display them on a GIS map together with e g a background map the SPREAD emissions or the UBM results The OSPM section of the RunModels sheet provides two buttons in the lower part for this Press Show OSPM result sheet to open the worksheet OSPM results Into this worksheet you have to copy paste the OSPM results for one or more streets eg from the OSPM StatOut XXX xls mentioned in the previous paragraph After this copy paste is completed pressing the Export as GIS point shp file button in the OSPM section of RunModels will export the data from the worksheet OSPM results into a point shape file using the FolderName and RunName specified earlier The interface to OSPMQ is very complex and provide a lot of options and features and hence a lot of flexibility More details on the OSPMQ interface are given in Chapter 4 OSPMO street concentrations 4 OSPMO street concentrations WinOSPM is a Windows version of OSPM This chapter takes you through an example that shows how WinOSPM can be used WinOSPM is very flexible with respect to input and output and the example illustrates the most important options necessary to run WinOSPM For more details you are referred to the English user manual that comes together with the installation of WinOSPM You may start the program through Start Programs OSPM WinOSPM or use the desktop icon Country setti
72. umptions for spe cific vehicle type emission information which are used in the cities but are not present in the current COPERT IV model e g CNG cars and trucks The database contains the emission factors and the queries calculating the emis sions From the database the results can be exported to MS Excel where they 29 30 serve as input to the spatial distribution together with the other emissions estimated from stationary and other mobile sources Other mobile sources As mentioned other mobile sources are not usually of great importance for city emission inventories However there can be exceptions based on the specific circumstances of a city Furthermore emissions from indus try construction can frequently be relevant within a city The emission model includes the following categories of other mobile com bustion railways maritime activities aviation and non road machinery The required input for these sources are fuel consumption split into fuel type and in the case of gasoline non road machinery also technology type 2 stroke or 4 stroke engines For aviation the required input data is the num ber of domestic and international landings and take offs LTOs The emission factors for other mobile sources refer to relevant chapters in the EMEP EEA Guidebook The emission factors available in the EMEP EEA Guidebook are expressed in the same activity data unit as the data input If country specific or city specific emiss
73. un macro dialog box will show up Select a macro and press Run note that the macro can take several minutes to run Running those macros will generate new work sheets named Area sources Mobile sources and Point sources respective ly If a given macro has been run before the corresponding sheet will have to be deleted or renamed before the macro can run again The content of the three generated sheets has the correct structure and formatting and is ready to be copied in the corresponding work sheets in the THOR AirPAS work book e g THOR AirPAS Funen v14 xls The sheets correspond as shown in Table 5 11 below Table 5 11 Correspondence between output sheets in the gridded emissions and the in put to the air quality modelling THOR Airpas Country Point Gridded emissions Point sources Area sources Country Area Mobile sources Country Transport 42 References Berkowicz R Hertel O Sorensen N N and Michelsen J A 1997 Model ling traffic pollution in streets National Environmental Research Institute Roskilde Denmark 55p Berkowicz R 2000a A Simple Model for Urban Background Pollution En vironmental Monitoring and Assessment Vol 65 Issue 1 2 pp 259 267 Berkowicz R 2000b OSPM A parameterised street pollution model Envi ronmental Monitoring and Assessment Volume 65 Issue 1 2 pp 323 331 Brandt J Christensen J H Frohn L M Palmgren F Berkowicz R amp Zlat ev Z
74. versity E nightclub landuse E allotments EZ basin E brown field mm cemetery gei commercial Ea conservation RR construction En depot jl farmyard A garages ES grass ES greenfield hedge eme industrial E meadow mU niitan EE pasture E pitch 3 railway Em recreation groun Sa reservoir En residential E retail Ec rowing EA village_green C Figure 5 4 Examples of international datasets a d railways roads buildings and land use from OpenStreetMap us PopDens2010 PopDens2008 61 100 0 400 a mM 101 __ 401 500 EH 51 501 1 000 E B 20 1 001 2 000 BM 30 I 2 001 4 000 Bl 5o 1500 4 001 8 000 MI 1501 3000 8 001 12 000 f oc Re BE gt 3000 0255 10 15 e Figure 5 5 Examples of international datasets a population density from Landscan and b population density from CIESIN 5 2 2 Setting up spatial distribution keys To be able to calculate spatial emissions the spatial data have to be processed and spatial distribution keys set up The distribution keys define how large part of the emissions from a source that should be allocated to each grid cell The resolution of the grid should reflect the level of detail of the spatial data the more detailed spatial data the higher resolution can be used As the spatial emissions for different emission sources have to be summarized to calculate the total spatial emissions for the case area all distribution keys have to be
75. ximum values for the two receptors If you are interested in the concentrations in the street look at the lines labelled Street Modelled These values represent the total concentration in the street including the background contribution The numbers labelled Background indicate concentrations in the urban background away from the street Please note that a certain set of options determines which set of parameters is displayed These options are set through the menu Project Options The results can be saved in a file for later retrieval use File Save or the button Save or printed use File Print or the button Print E E AA Tp R Summary of Results for Example Street Calculated on 08 05 2014 11 35 12 untitled 7E File Format Window ld a e i Save Open Prnt Street Example Street Calculated on 08 05 2014 11 35 12 Average Daily Traffic 25400 Calculated 25390 Default Traffic Type_A trf Emission Scenario Year 2013 Period Covered User provided Meteorological Data 01 January 2012 00 00 31 December 2012 23 00 User Comments Urban Background User provided AnS Max Al Fieceptors 7 Page 0 Hm MeDap8husmen 5 DA eras Component 175th Highest 18th Highest fe Corerace Max 25th Highest eve Cevereze 35th Highest 7th Highest Street Modelled Background DK LimiVale 200 _______ _______ DK Re
76. y to convert geographical coordinates from Longitude Latitude degrees to UTM meters This can be done by Franson CoordTrans This software requires a license but different free tools can perform similar conversions http www whoi edu marine ndsf utility NDSFutility html see Figure 5 1 File Tosi Help Longhade La Longhada Latics Regen C Eae Mato er E Easting Hara mas Sets ton pin S E B ea n bes iw nonas me gt Logisk 1290367 From te z Mose EAR AT uL NENNEN Bear Pp C Da E Decmal dee Mes x Ve M Ye e Prac E F KE SR Conven Reset u t 3 1 _ 5 1 Result 5181079 62004485 E wn Figure 5 1 Software for conversion of geographic coordinates to UTM 3 32 Input data Two different types of input data are required emission data from the emis sion models and spatial datasets to allow for distribution of emissions Emission data The output from the emission models depends on whether it is point sources or area sources For point sources information on the stack height and the geographical distribution of the emission at the exact location X Y is need ed rather than the 1x1 km grid cell Examples of the input data to the spa tial distribution from the emission models for point sources Table 5 2 5 4 respectively are provided below gt NO WP WIN Table 5 2 Example of input from the emission model fo

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