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AirDART User Guide

ContentsAirDART Overview.................................................................................................................................2

Data Guide.............................................................................................................................................4

Model Scenarios............................................................................................................................4

Data Types and Variables...............................................................................................................4

Spatial selection.............................................................................................................................5

Time Period and Summaries..........................................................................................................5

Data tables, graphs and maps generated......................................................................................5

User Guide.............................................................................................................................................8

Required software.........................................................................................................................8

Access to AirDART..........................................................................................................................8

Worked example of using AirDART................................................................................................9

Appendix.............................................................................................................................................12

Appendix 1: List of variables............................................................................................................12

Appendix 2: Model Scenario Descriptions.......................................................................................16

Appendix 3: Locations for air quality monitoring site......................................................................25

AirDART OverviewThe Environment Agency supports projects to develop and demonstrate the value of using the Community Multiscale Air Quality (CMAQ) modelling system1 to inform Agency policy decisions. Of particular importance to the Agency is the management of regulated industrial emissions sources to develop a cost-effective strategy to meet pollutant-specific limit and target values for ambient pollutant concentrations set by legislative bodies. Previous projects encompass modelling of present and future concentrations of PM2.5 pollution under a number of scenarios which are of interest to the Environment Agency. This modelling provides projections out to 2020 of the contribution to ambient concentrations of PM2.5 of emissions from regulated industrial sources under the most likely emission scenarios.

Environment Agency supported projects include:

comparison of simple and advanced REgional MOdels (CREMO) estimates of PM2.5 reductions and future regulation scenarios using the CMAQ modelling

system

These have generated massive datasets, equivalent to several terabytes of data. The aim of AirDART is to make CMAQ, and other air quality model data more easily accessible by scientific and regulatory communities who can use the data in support of policy or research. It will make data available to those who do not have access to the technical computing environment required to run the models.

It is designed primarily as a data retrieval tool with simple visualisation to allow basic quality checking. Selected data can be downloaded to allow further analysis within a spread sheet programme such as Excel, with R statistical packages including openair or other specialised data analysis and visualisation tools.

At the beginning of the project it became apparent that to be of the greatest value the tool required flexibility and that it should:

allow selection of data for any latitude and longitude coordinates only allow choice of species and species combinations which are comprehensible. only include ground layer conditions provide simple graphs and maps for basic data quality checks, but not attempt development

of a data visualization or model evaluation tool ensure all data selected are accompanied by model metadata and have an option to

download the data as a file suitable for import into Excel. where possible use R for development provide interactive data retrieval sufficiently quickly so there is no need to return data files

by email. give consideration to utilisation of the tool within the wider modelling community

1 www.cmaq-model.org

http://www.cmaq-model.org/

Data from AirDART are accessed by making selections on a webpage, which uses interactive data selection in order to extract, visualise and download data. AirDART is written in R - the R function that extracts data has been designed to work with the AirDART model data and as an independent function. Providing a tool for more specialised data requirements from CMAQ data is not included within AirDART.

AirDART can retrieve data from CMAQ air quality and deposition data for 2003, 2006 and 2020.

This first section of the guide outlines the types of data available and the second how to access it via AirDART.

Figure 1 AirDART schematic

Data Guide

The Environment Agency has supported projects to develop and demonstrate the potential to use CMAQ model in support of Agency policy decisions. CMAQ is designed to treat air quality in a manner adopting a ‘one atmosphere’ perspective that simultaneously addresses multiple pollutants gases, particulate matter (PM – including PM10 and PM2.5) in terms of atmospheric concentrations as well as their total deposition. The focus of the more recent project was PM2.5, AirDART will make available a range of modelled gas, PM and deposition data along with basic meteorological conditions and pollutant emissions.

This section provides a summary of data available via AirDART.

Model Scenarios The modelling projects encompass modelling of present and future concentrations of PM2.5 pollution under a number of scenarios which are of interest to the Environment Agency and research. This modelling provides projections out to 2020 of the contribution to ambient concentrations of PM2.5 of emissions from regulated industrial sources under the most likely emission scenarios.

Table 1 summarises the model scenarios available within AirDART, a complete description of the scenarios is in Appendix 2: Model Scenario Descriptions.

Table 1 Summary of model scenarios

Scenario name DescriptionUH 2003 all emissions

2003 all sources Comparison of simple and advanced REgional MOdels (CREMO) project

UH 2003 minus Didcot Power Station

2003 all sources minus Didcot Power Station, Comparison of simple and advanced REgional MOdels (CREMO) project

UH 2003 minus Fawley Refinery

2003 all sources minus Fawley Refinery, Comparison of simple and advanced REgional MOdels (CREMO) project

UH 2006 all emissions

2006 all sources “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project

UH 2006 minus industrial sources

2006 all sources minus industrial sources “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project

UH 2020 emissions with 2006 meteorology

2020 all sources with 2006 meteorology “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project

UH 2020 minus industrial sources with 2006 meteorology

2020 all sources minus industrial sources with 2006 meteorology “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project

Data Types and VariablesData are accessed as separate data types for gas (µgm-3 and ppb), PM, deposition, emissions and meteorology. Details of the variable in each data type are listed in Appendix 1: List of variables. This is a subset of the full list of variables available from CMAQ and includes species and combination of species most frequently required. In some cases e.g. PM2.5 the variables are a combination of several CMAQ species these are shown in Table 4. A technical description of how the CMAQ variables are combined is available in the AirDART Data Requirements.

Spatial selectionLatitude and longitude are used to identify the point of interest. Time series data extract the data from the corresponding grid cell. Grid data extract in a 3x3 or 5x5 grid of cells centred on the selected location. Maps are produced for the whole area.

Time Period and SummariesThe data are available as hourly gridded data, however these are large files (up to 20GB) to speed data access the most common data subsets daily, monthly and yearly have been pre prepared e.g. daily maximum and hourly average. Maximum and hourly averages are calculated for gas and PM species, with period totals (sum) for deposition and emissions. Pre-calculating the summary files assures data consistency.

Meteorological data are generally associated with hourly data. Selected variables can be included in daily, monthly and yearly data subsets e.g. max temperature, mean temperature, total amount of rainfall (to be determined).

Data tables, graphs and maps generatedNot all tables, graphs and maps are suitable for all combinations of temporal and spatial selection. However all valid options produce a data file of the values to download for use in other data analysis tools. These are produce in two forms.

csv - comma separated values, suitable for importing into Excel rda – R data object, suitable for using in R and compatible with openair

Both files contain the data and a brief summary of the scenario and selected options. Data downloaded separately using the same spatial and temporal selections for can be combined later.

Figure 2 Example of a time series data table produced for 1 variable

a) Screen shot of the selections details in the header

b) Screen shot of the data

Figure 3 Example of a data table for a 3x3 grid of locations (csv download imported into Excel)

Blue marks the cell containing the selected location.

Model scenario: 2006 all sources (PM2.5 project)Variable type: Particulate Matter (ug m-3)Variable: PM2.5_SO4Variable description: PM2.5 sulphate aerosolDataset: UH004_pm_20130204.ncLatitude: 51.571078Longitude: -1.325283Start date-time: 2006-07-01 12:00:00End date-time: 2006-07-01 12:00:00Grid width:

3datetime PM2.5_SO4 lat long

01/07/2006 12:00 3.8478 51.52778 -1.4166601/07/2006 12:00 3.8772 51.58335 -1.4182401/07/2006 12:00 4.3064 51.63893 -1.4198301/07/2006 12:00 3.7852 51.52874 -1.3273301/07/2006 12:00 3.7504 51.5843 -1.3288301/07/2006 12:00 4.3089 51.63988 -1.3302901/07/2006 12:00 3.6389 51.52962 -1.2380101/07/2006 12:00 3.5735 51.5852 -1.2393801/07/2006 12:00 4.0939 51.64077 -1.24075

Figure 4 Example of a map, annual average PM2.5 for 2006 all emissions.

User GuideThis section provides a description of how to access data from AirDART. A crib sheet containing a brief summary of the options and variables available is available from the website.

Required software AirDART has been built using R tools that are in a rapidly developing area. To achieve the best results it requires the most up-to-date browsers. The R tools are designed to work with Google Chrome internet browser; it has been tested successfully on Internet Explorer 10, and up-to- date versions of Firefox and Safari, however problems may arise using earlier versions of Internet Explorer and access has been restricted. The recommended browser is Chrome.

There are no other software requirements.

Access to AirDARTAirDART is accessed from the website http://airdart.ricardo-aea.com/index access is password protected, contact [email protected] and [email protected] for details. Documentation and examples of data interpretation are available on the website.

AirDART opens using the default settings (see below), this shows the Output header tab summarising the data selection.

2006 including all emissions Emissions Time series (default) Harwell latitude and longitude. The first time step The first variable in the file.

mailto:[email protected]

mailto:[email protected]

http://airdart.ricardo-aea.com/index

The webpage is arranged with the data selection on the left hand side and output in a series of output tabs on the right. Each tab displays different output (not all are valid for each selection).

Output header - shows the data selection and includes a description of the variable selected. Output data - shows the time series and grid numerical data with the option to download it as a

file. Output grid - a Google map showing the locations of the time series and grid data. Output map - shows mapped output for the whole area.

Worked example of using AirDART

The worked example is based on using the hourly data.

Time series

AirDART uses Time series as the default.

Move to the Output data tab, this shows the CO emission on 1/1/2006. Wind speed and direction are added to all time series data tables.

Change the date and emission species. In the selection panel change the start month to 2 and the model parameter to PM2.5 using the drop down box.

- Output data now shows PM2.5 value for 1/2/2006 - Output header has changed to reflect the new data. - NOTE the latitude and longitude refer to selection in the header and the centre of the cell in

data table.

Change the variable type to Particulate Matter. This stage may be slower as the data are in a different file. An error message in the Output data tab indicates a miss match between the start time of the PM and meteorology data. This only occurs for Jan 1st – change the start hour from 0 to 1.

Change the end day to 3, to display 3 days of data.

Select 2 model parameters; select the first PM2.5 hold the control key whilst selecting the second PM10

Selecting PM2.5_SO4, PM2.5_NH4, PM2.5_NO3, PM2.5_SS, PM2.5_EC, PM2.5_POC, PM2.5_SOAA, PM2.5_SOAB and PM2.5_CM will include all PM2.5 components.

Grids

Change the Time series button to Grid. This displays an extra selection ‘Grid width’.

Change this to 3 then 5, this produces a grid of results for 1 time, centred on the selected latitude and longitude.

Cells are ordered from bottom left to top right e.g.

7 8 94 5 61 2 3

The selected location is in the centre marked in Blue

The box to the left of the save data button defaults to create a R data object (rda). Change this to csv then select the Save data option.

A file will be created and download using a file name AirDART_date_time.csv e.g. AirDART_20130322_124601.csv. A summary of the data selection is at the top of each file.

Example of a csv file."Model scenario: 2006 all sources (PM2.5 project)","","","""Variable type: Meteorological data","","","""Variable: TEMP","","","""Variable description: Temperature (C)","","","""Dataset: UHP05_2006_met_20130204.nc","","","""Latitude: 51.571078","","","""Longitude: -1.325283","","","""Start date-time: 2006-01-01 01:00:00","","","""End date-time: 2006-12-30 00:00:00","","","""Grid width: 1 (default for time series)","","","""datetime","TEMP","lat","long""2006-01-01 01:00:00","4.34356689453125","51.5843048095703","-1.32882690429688""2006-01-01 02:00:00","5.02090454101562","51.5843048095703","-1.32882690429688""2006-01-01 03:00:00","6.39254760742188","51.5843048095703","-1.32882690429688""2006-01-01 04:00:00","6.98434448242188","51.5843048095703","-1.32882690429688""2006-01-01 05:00:00","7.13650512695312","51.5843048095703","-1.32882690429688"

Maps

Change the time model parameter to PM2.5 Change the Grid button to Map. The Output map tab shows map for the selected variable and

time (the facility to download the data will follow) Change the variable and time to see the map change.

Example map of PM2.5 01/08/2006 08:00

Appendix

Appendix 1: List of variablesTable 2 Gas Deposition and Emission variables available in AirDART

Deposition (DEP) Concentrations Emissio

nDry Wet GAS GAS_ppb PM (EMIS)

Ozone DRY_O3 O3 O3_ppb

Carbon monoxide CO CO_ppb CO

Hydrogen peroxide DRY_H2O2 H2O2 H2O2_ppb

Hydroperoxy radical HO2 HO2_ppb

Hydroxyl radical OH OH_ppb

Sulphur dioxide DRY_SO2 WET_SO2 SO2 SO2_ppb SO2

Hydrogen chloride HCLOxidised sulphur (for deposition) DRY_SOX WET_SOX

Non sea-salt oxidised sulphur (for deposition)

DRY_NSS_SOX

WET_NSS_SOX

Nitrogen containing Species

Nitric acid DRY_HNO3 HNO3 HNO3_ppb

Nitrous acid HONO HONO_ppb

Dinitrogen pentoxide N2O5 N2O5_ppb

Ammonia DRY_NH3 NH3 NH3_ppb NH3

Nitric oxide NO NO_ppb

Nitrogen dioxide DRY_NO2 NO2 NO2_ppb

Peroxyacetyl nitrate DRY_PAN PAN PAN_ppb

Nitrogen oxide (NOX=NO+NO2) NOX NOX_ppb NOX

Oxidised nitrogen (for deposition) DRY_NOY WET_NOY NOY NOY_ppb

Nitrogen reservoir species (NOZ=NOY-NOX) NOZ NOZ_ppb

Reduced nitrogen ( for deposition) WET_NHX

Organic Species

Ethene ETH ETH_ppb ETH

Formaldehyde DRY_FORM FORM FORM_ppb FORM

Isoprene ISOP ISOP_ppb ISOP

Sesquiterpenes SESQ SESQ_ppb SESQ

Terpene TERP TERP_ppb TERP

Toluene and other monoalkyl aromatics TOL TOL_ppb TOL

Xylene and other polyalkyl aromatics XYL XYL_ppb XYL

Non methyl VOC NMVOC

Other VOCs OVOC

Table 3 PM variables available in AirDART

Particulate MatterDeposition (DEP) Concentrations Emission

Dry Wet GAS GAS_ppb PM (EMIS)

PM2.5 total aerosol DRY_PM2.5 PM2.5 PM2.5

PM10 total aerosol PM10 PM10

PM2.5 Components

PM2.5 sulphate aerosol DRY_PM2.5_SO4 PM2.5_SO4PM2.5 ammonium aerosol DRY_PM2.5_NH4 PM2.5_NH4

PM2.5 nitrate aerosol DRY_PM2.5_NO3 PM2.5_NO3

PM2.5 elemental carbon aerosol DRY_PM2.5_EC PM2.5_EC

PM2.5 primary organic carbon aerosol DRY_PM2.5_POC PM2.5_POC

PM2.5 anthropogenic SOA DRY_PM2.5_SOAA PM2.5_SOAA

PM2.5 biogenic SOA DRY_PM2.5_SOAB PM2.5_SOABPM2.5 crustal material aerosol DRY_PM2.5_CM PM2.5_CM

PM2.5 sea salt aerosol DRY_PM2.5_SS PM2.5_SS

PM2.5 total organic matter aerosol DRY_PM2.5_TOM PM2.5_TOM

PM10 Components

PM10 sulphate aerosol WET_PM10_SO4 PM10_SO4

PM10 ammonium aerosol WET_PM10_NH4 PM10_NH4

PM10 nitrate aerosol WET_PM10_NO3 PM10_NO3

PM10 sea salt aerosol PM10_SS

Table 4 Summary of species combined to form AirDART variables

SOX Oxidised sulphur (for deposition) SOX=SO2+SULF+ASO4J+ASO4I+ASO4K for deposition

NSS_SOX Non sea-salt oxidised sulphur (for deposition) SOX=SO2+SULF+ASO4J+ASO4I for deposition

Nitrogen containing Species

NOX Nitrogen oxide (NOX=NO+NO2) NOX=NO+NO2

NOY Oxidised nitrogen (for deposition)

NOY=NOX+NO3+2*N2O5+HONO+HNO3+PAN+PANX+PNA+NTR for concentration and NOY=NOY+ANO3J+ANO3I or NOY=NOY+ANO3J+ANO3I+ANO3K for deposition

NOZ Nitrogen reservoir species (NOZ=NOY-NOX) NOZ=NOY-NOX

NHX Reduced nitrogen ( for deposition) NHX=NH3+ANH4J+ANH4I+ANH4K for deposition

Organic Species

OVOC Other VOCsFORM*1+ALD2*2+ALDX*2+PAR*1+MEOH*1+OLE*2+ETH*2+IOLE*4+ETOH*2+ETHA*2+NR*12.01*3600./1000./dx/dy with NR=Non-reactive VOCs

PM Components

PM2.5 PM2.5 total aerosol PM2.5=PM2.5_SO4+PM2.5_NH4+PM2.5_NO3+PM2.5_EC+PM2.5_POC+PM2.5_SOAA+PM2.5_SOAB+PM2.5_CM+PM2.5_SS

PM10 PM10 total aerosol PM10=PM2.5+ACORS+ASOIL+ASO4K or PM10=PM2.5+ACORS+ASOIL+PM10_SS+ANH4K+ANO3K

PM2.5 Components

PM2.5_SO4 PM2.5 sulphate aerosol PM2.5_SO4=ASO4J+ASO4I

PM2.5_NH4 PM2.5 ammonium aerosol PM2.5_NH4=ANH4J+ANH4I

PM2.5_NO3 PM2.5 nitrate aerosol PM2.5_NO3=ANO3J+ANO3I

PM2.5_EC PM2.5 elemental carbon aerosol PM2.5_EC=AECJ+AECI

PM2.5_POC PM2.5 primary organic carbon aerosol AORGPAJ+AORGPAI/1.2 or PM2.5_POC=AORGPAJ+AORGPAI

PM2.5_SOAA PM2.5 anthropogenic SOA

PM2.5_SOAA=AORGAJ+AORGAI or PM2.5_SOAA=AALKJ+AXYL1J+AXYL2J+AXYL3J+ATOL1J+ATOL2J+ATOL3J+ABNZ1J+ABNZ2J+ABNZ3J+AOLGAJ+AORGCJ/2.

PM2.5_SOAB PM2.5 biogenic SOAPM2.5_SOAB=AORGBJ+AORGBI or PM2.5_SOAB=ATRP1J+ATRP2J+AISO1J+AISO2J+AISO3J+ASQTJ+AOLGBJ+AORGCJ/2.

PM2.5_CM PM2.5 crustal material aerosol PM2.5_CM=A25J+A25I

PM2.5_SS PM2.5 sea salt aerosol PM2.5_SS=

PM2.5_TOM PM2.5 total organic matter aerosol PM2.5_TOM=PM2.5_POC+PM2.5_SOAA+PM2.5_SOAB

PM10 Components

PM10_SO4 PM10 sulphate aerosol PM10_SO4=PM2.5_SO4+ASO4K

PM10_NH4 PM10 ammonium aerosol PM10_NH4=PM2.5_NH4+ANH4K

PM10_NO3 PM10 nitrate aerosol PM10_NO3=PM2.5_NO3+ANO3K

PM10_SS PM10 sea salt aerosol PM10_SS=ANAK*0.78+ACLK+ASO4KTable 5 Meteorology Variables available in AirDART

Variables Description Units

PBL Boundary Layer (PBL) height (m) m

SWR Short wave radiation (W m-2) W m-2

TEMP Temperature (C) CPRESS Pressure (hPa) hPaPRECIP Precipitation (cm) cm

MIXRAT Water vapour mixing ratio (g kg-1) g kg-1

RH Relative humidity (%) %TD Dew point temperature (C) CCFRAC Total cloud fraction (fraction from 0 to 1) fraction

WS Wind speed (m s-1) m s-1

WD Wind direction (deg N) deg N

PHI Used to calculate dew point temperature (TD) using the Magnus formula.

Magnus formula used to calculate dew point temperature.

TD = (a * PHI) / (b - PHI)

with

PHI = (b * T) / (a + T) + ln(RH/100)

a = 237.7b = 17.271

Appendix 2: Model Scenario Descriptions

Model Scenario

UH001UH 2003 all emissions2003 all sources, Comparison of simple and advanced REgional MOdels (CREMO) project

Meteorology WRF v3.0.1.1The simulation utilized the NOAH LSM, Yonsei University (YSU) PBL scheme (Hong et al., 2006), the microphysics scheme by Thompson et al. (2004, 2006), Grell and Devenyi CuP scheme, and CAM3 radiation package (Collins et al., 2006). Initial and lateral BCs were provided by the European Center for Medium-Range Weather Forecasts model. Outputs from the WRF simulations were preprocessed for input into CMAQ using v3.4.1 of the Meteorology-Chemistry Interface Processor (MCIP; Otte et al., 2005). FDDA were used to improve model performance. More specific details regarding the WRF simulations, including references for the various schemes used can be found in Chemel et al. (2010).

Air Quality Model

CMAQ v4.6

Model options employed include the CB05 chemical mechanism, the AERO4 aerosol module, the Asymmetric Cloud Model 2 (ACM2) PBL scheme (Pleim, 2007a,b). See Chemel et al. (2010) for details.

Boundary conditions

STOCHEM

Chemical initial and boundary conditions for the outer domain were derived from monthly mean concentrations, modelled by the UK Met Office Lagrangian chemistry-transport model STOCHEM (Collins et al., 2000), for the year 2000. See Chemel et al. (2010) for details.

Emissions Annual anthropogenic emissions data from the European Monitoring and Evaluation Programme (EMEP, Vestreng et al., 2005) for area sources using a horizontal resolution of 50 km and from the European Pollutant Emission Register (EPER, Pulles et al., 2007) for point sources were used for grid cells outside the UK. For the UK, we used the UK National Atmospheric Emissions Inventory (NAEI, Dore et al., 2005), which provides annual emissions from point sources and area sources at a horizontal resolution of 1 km. Biogenic emissions were calculated using the methodology proposed by Guenther et al. (1995). See Chemel et al. (2010) for details.

Project Environment Agency funded Comparison of simple and advanced REgional MOdels (CREMO) R&D project No. SC060037

Reference Chemel, C., Sokhi, R. S., Yu, Y., Hayman, G. D., Vincent, K. J., Dore, A. J., Prain, H. D., and Fisher, B. E. A., 2010. Evaluation of a CMAQ simulation at high resolution over the UK for the calendar year 2003. Atmos. Environ., 44, 2927-2939.

Notes

Model Scenario

UH002UH 2003 minus Didcot Power Station2003 all sources minus Didcot Power Station, Comparison of simple and advanced REgional MOdels (CREMO) project


Air Quality Model

CMAQ v4.6


Boundary conditions

STOCHEM

Chemical initial and boundary conditions for the outer domain were derived from monthly mean concentrations, modelled by the UK Met Office Lagrangian chemistry-transport model STOCHEM (Collins et al., 2000), for the year 2000. See Chemel et al. (2010) for details.

Emissions Annual anthropogenic emissions data from the European Monitoring and Evaluation Programme (EMEP, Vestreng et al., 2005) for area sources using a horizontal resolution of 50 km and from the European Pollutant Emission Register (EPER, Pulles et al., 2007) for point sources were used for grid cells outside the UK. For the UK, we used the UK National Atmospheric Emissions Inventory (NAEI, Dore et al., 2005), which provides annual emissions from point sources and area sources at a horizontal resolution of 1 km. Biogenic emissions were calculated using the methodology proposed by Guenther et al. (1995). See Chemel et al. (2010) for details. Emissions from Didcot Power Station were removed from the emission inventory.


Reference Chemel, C., Sokhi, R. S., Dore, A. J., Sutton, P., Vincent, K. J., Griffiths, S. J., Hayman, G. D., Wright, R. D., Baggaley, M., Hallsworth, S., Prain, H. D., and Fisher, B. E. A., 2011. Predictions of U.K. regulated power station contributions to regional air pollution and deposition: a model comparison exercise. J. Air & Waste Manage. Assoc., 61, 1236-1245.

Notes

Model Scenario

UH003UH 2003 minus Fawley Refinery2003 all sources minus Fawley Refinery, Comparison of simple and advanced REgional MOdels (CREMO) project


Air Quality Model

CMAQ v4.6


Boundary conditions

STOCHEMChemical initial and boundary conditions for the outer domain were derived from monthly mean concentrations, modelled by the UK Met Office Lagrangian chemistry-transport model STOCHEM (Collins et al., 2000), for the year 2000. See Chemel et al. (2010) for details.

Emissions Annual anthropogenic emissions data from the European Monitoring and Evaluation Programme (EMEP, Vestreng et al., 2005) for area sources using a horizontal resolution of 50 km and from the European Pollutant Emission Register (EPER, Pulles et al., 2007) for point sources were used for grid cells outside the UK. For the UK, we used the UK National Atmospheric Emissions Inventory (NAEI, Dore et al., 2005), which provides annual emissions from point sources and area sources at a horizontal resolution of 1 km. Biogenic emissions were calculated using the methodology proposed by Guenther et al. (1995). See Chemel et al. (2010) for details. Emissions from Fawley refinery were removed from the emission inventory.


Reference Hayman, G., Sokhi, R., Chemel, C., Griffiths, S., Vincent, K., Dore, A. J., Sutton, P. and Wright, D. R., 2012. Comparison of simple and advanced regional models (CREMO): Model evaluation: Ground-level ozone. Report SC060037d/R. Bristol: Environment Agency.

Notes

Model Scenario

UH004UH 2006 all emissions2006 all sources, “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project

Meteorology WRF v3.2.1The simulation utilized the NOAH LSM, Yonsei University (YSU) PBL scheme (Hong et al., 2006), Morrison microphysics scheme, Grell and Devenyi CuP scheme, and RRTMG LWR scheme. Initial and lateral BCs were provided by the European Center for Medium-Range Weather Forecasts model. Outputs from the WRF simulations were preprocessed for input into CMAQ using v3.6 of the Meteorology-Chemistry Interface Processor (MCIP; Otte et al., 2005). FDDA were used to improve model performance. More specific details regarding the WRF simulations, including references for the various schemes used and an operational performance evaluation of the simulations can be found in Vautard et al. (2012).

Air Quality Model

CMAQ v4.7.1

Model options employed include the CB05 chemical mechanism with chlorine chemistry extensions, the AERO5 aerosol module (Carlton et al., 2010), the Asymmetric Cloud Model 2 (ACM2) PBL scheme (Pleim, 2007a,b). See Appel et al. (2012) for details.

Boundary conditions

GEOS-Chem

The simulation was performed using lateral boundary concentration data provided by the GEOS-Chem global model (Bey et al., 2001). A more detailed description of the data as used as lateral boundary concentrations can be found in Schere et al. (2012).

Emissions The AQMEII standard emissions data were used and are based on the TNO (http://www.tno.nl/) inventory for 2005. Biogenic emissions of isoprene and terpene, calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN; Guenther and Wiedinmyer, 2007; Sakulyanontvittaya et al., 2008), are included on the same resolution as the anthropogenic emissions. The fire emissions were based on 2006 daily fire estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power product (Sofiev et al., 2009). Plume rise was calculated offline with SMOKE. A more detailed description of the emission is available in Pouliot et al. (2012).

Project Environment Agency funded “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” R&D project No. 26137

Reference Appel, K. W., Chemel, C., Roselle, S. J., Francis, X. V., Hu, R.-M., Sokhi, R. S., Rao, S. T., and Galmarini, S., 2012. Examination of the Community Multiscale Air Quality (CMAQ) model performance over the North American and European domains. Atmos. Environ., 53, 142-155.

Notes

Model Scenario

UH005UH 2006 minus industrial sources

2006 all sources minus industrial sources, “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project


Air Quality Model

CMAQ v4.7.1Model options employed include the CB05 chemical mechanism with chlorine chemistry extensions, the AERO5 aerosol module (Carlton et al., 2010), the Asymmetric Cloud Model 2 (ACM2) PBL scheme (Pleim, 2007a,b). See Appel et al. (2012) for details.

Boundary conditions

GEOS-ChemThe simulation was performed using lateral boundary concentration data provided by the GEOS-Chem global model (Bey et al., 2001). A more detailed description of the data as used as lateral boundary concentrations can be found in Schere et al. (2012).

Emissions The AQMEII standard emissions data were used and are based on the TNO (http://www.tno.nl/) inventory for 2005. Biogenic emissions of isoprene and terpene, calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN; Guenther and Wiedinmyer, 2007; Sakulyanontvittaya et al., 2008), are included on the same resolution as the anthropogenic emissions. The fire emissions were based on 2006 daily fire estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power product (Sofiev et al., 2009). Plume rise was calculated offline with SMOKE. A more detailed description of the emission is available in Pouliot et al. (2012). Emissions from all major industrial sources in the United Kingdom were removed from the emission inventory.


Reference Chemel, C., Fisher, B. E. A., Francis, X. V., Good, N., Kong, X., Sokhi, R. S., Collins, W. J., and Folberth, G. A., 2013. Environmental and health impacts of major industrial emissions sources in the United Kingdom in 2020, in preparation.

Notes

Model Scenario

UH006UH 2020 emissions with 2006 meteorology2020 all sources with 2006 meteorology, “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project


Air Quality Model

CMAQ v4.7.1


Boundary conditions

GEOS-Chem

The simulation was performed using lateral boundary concentration data provided by the GEOS-Chem global model (Bey et al., 2001).

Emissions The AQMEII standard emissions data were used and are based on the TNO (http://www.tno.nl/) inventory for 2005 scaled to 2020. Biogenic emissions of isoprene and terpene, calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN; Guenther and Wiedinmyer, 2007; Sakulyanontvittaya et al., 2008), are included on the same resolution as the anthropogenic emissions. Plume rise was calculated offline with SMOKE. A more detailed description of the emission is available in Pouliot et al. (2012).



Notes

Model Scenario

UH007UH 2020 minus industrial sources with 2006 meteorology2020 all sources minus industrial sources with 2006 meteorology, “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project


Air Quality Model

CMAQ v4.7.1


Boundary conditions

GEOS-Chem

The simulation was performed using lateral boundary concentration data provided by the GEOS-Chem global model (Bey et al., 2001).

Emissions The AQMEII standard emissions data were used and are based on the TNO (http://www.tno.nl/) inventory for 2005 scaled to 2020. Biogenic emissions of isoprene and terpene, calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN; Guenther and Wiedinmyer, 2007; Sakulyanontvittaya et al., 2008), are included on the same resolution as the anthropogenic emissions. Plume rise was calculated offline with SMOKE. A more detailed description of the emission is available in Pouliot et al. (2012). Emissions from all major industrial sources in the United Kingdom were removed from the emission inventory.



Notes

Model Scenario

UH008UH 2020 emissions under 2020 Climate Conditions

2020 all sources under climate change conditions, “Estimates using the CMAQ modelling system of PM2.5 reductions and future regulation scenarios” project

Meteorology WRF v3.2.1

The simulation utilized the NOAH LSM, Yonsei University (YSU) PBL scheme (Hong et al., 2006), Morrison microphysics scheme, Grell and Devenyi CuP scheme, and RRTMG LWR scheme. Initial and lateral BCs were provided by the Hadley Centre Global Environmental Model, version 2, with an added Earth-System component (HadGEM2-ES) model. Outputs from the WRF simulations were preprocessed for input into CMAQ using v3.6 of the Meteorology-Chemistry Interface Processor (MCIP; Otte et al., 2005). FDDA were used to improve model performance. More specific details regarding the WRF simulations, including references for the various schemes used and an operational performance evaluation of the simulations can be found in Vautard et al. (2012).

Air Quality Model

CMAQ v4.7.1


Boundary conditions

HadGEM2-ES

The simulation was performed using lateral boundary concentration data provided by the Hadley Centre Global Environmental Model, version 2, with an added Earth-System component (HadGEM2-ES) model.

Emissions The AQMEII standard emissions data were used and are based on the TNO (http://www.tno.nl/) inventory for 2005 scaled to 2020. Biogenic emissions of isoprene and terpene, calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN; Guenther and Wiedinmyer, 2007; Sakulyanontvittaya et al., 2008), are included on the same resolution as the anthropogenic emissions. Plume rise was calculated offline with SMOKE. A more detailed description of the emission is available in Pouliot et al. (2012).



Notes This "climate" simulation used a 360-day calendar. The climate community is mostly interested in seasonal and yearly averages. The seasons are DJF, MAM, JJA and SON. The seasonal averages are constructed by averaging the 3 30-day months corresponding to the seasons. Comparing hourly data does not make much sense.

Projection UHP03CREMOUK 5 km, 38 WRF layers collapsed in MCIP to 15 CMAQ layers

Resolution 05KM

Number of layers 15

layers 1.000, 0.995, 0.990, 0.980, 0.960, 0.940, 0.910, 0.860, 0.800, 0.740, 0.680, 0.600, 0.480, 0.360, 0.200, 0.000

Top of layers 5000 PaCMAQ GRIDDESC 30.000,60.000,3.000,-4.749,54.593

-440000.000,-545000.000,5000.000,5000.000,177,219,1

Projection UHP05AQMEIIUK 6 km, 52 WRF layers collapsed in MCIP to 34 CMAQ layers

Resolution 06KM

Number of layers 34

layers 1.00000, 0.99691, 0.99381, 0.98643, 0.97786, 0.96815, 0.95731, 0.94538, 0.93122, 0.91490, 0.89653, 0.87621, 0.85405, 0.82911, 0.80160, 0.77175, 0.73981, 0.70509, 0.62889, 0.54957, 0.47788, 0.41323, 0.35503, 0.30276, 0.25592, 0.21405, 0.17672, 0.14352, 0.11410, 0.08811, 0.06523, 0.04517, 0.02765, 0.01243, 0.00000

Top of layers 5000 PaCMAQ GRIDDESC 30.000,60.000,0.000,0.000,54.000

-728000.000,-461500.000,6000.000,6000.000,147,180,1

Appendix 3: Locations for air quality monitoring site

Code Site Name Long Lat Code Site Name Long Lat

ABD Aberdeen -2.094 57.157 BEX London Bexley 0.185 51.466

ABD1 Aberdeen Anderson Dr -2.125 57.129 CLL2 London Bloomsbury -0.126 51.522

AD1 Aberdeen King Street -2.095 57.170 BRI London Bridge Place -0.142 51.495

ABD0 Aberdeen Market Street 2 -2.092 57.142 LON6 London Eltham 0.071 51.453

ABD7 Aberdeen Union Street Roadside

-2.106 57.145 HG2 London Haringey -0.126 51.586

ABD8 Aberdeen Wellington Road -2.094 57.134 HRL London Harlington -0.442 51.489

ALOA Alloa -3.792 56.117 HR3 London Harrow Stanmore

-0.299 51.617

ANG5 Anglesey Brynteg -4.274 53.307 HIL London Hillingdon -0.461 51.496

ANG2 Anglesey Llynfaes -4.407 53.291 MY1 London Marylebone Road

-0.155 51.523

ANG7 Anglesey Penhesgyn -4.200 53.245 KC1 London N. Kensington -0.213 51.521

FFAR Angus Forfar -2.884 56.644 SK1 London Southwark -0.097 51.491

ARM6 Armagh Roadside -6.655 54.354 TED London Teddington -0.340 51.421

AH Aston Hill -3.034 52.504 WA2 London Wandsworth -0.191 51.457

ACTH Auchencorth Moss -3.243 55.792 HORS London Westminster -0.132 51.495

BALM Ballymena Ballykeel -6.251 54.862 DER4 Londonderry Dale' Corner

-7.312 54.996

BALN Ballymena North Road -6.278 54.863 LN Lough Navar -7.900 54.440

BAR3 Barnsley Gawber -1.510 53.563 LH Lullington Heath 0.181 50.794

BATH Bath Roadside -2.354 51.391 MH Mace Head -9.904 53.326

BEL2 Belfast Centre -5.929 54.600 MAN3 Manchester Piccadilly -2.238 53.482

BEL5 Belfast Newtownards Road -5.858 54.595 MAN4 Manchester South -2.243 53.369

BEL0 Belfast Ormeau Road -5.924 54.588 MAN Manchester Town Hall -2.245 53.479

BEL1 Belfast Stockman' Lane -5.975 54.573 MAWR Marchlyn Mawr -4.075 53.136

BE2 Belfast Westlink Roden Street -5.950 54.592 MKTH Market Harborough -0.772 52.554

BIL Billingham -1.275 54.605 MID Middlesbrough -1.221 54.569

AGRN Birmingham Acocks Green -1.830 52.437 MID2 Midlothian Dalkeith -3.070 55.894

BIRM Birmingham Centre -1.908 52.480 MID1 Midlothian Pathhead -2.967 55.867

BIR1 Birmingham Tyburn -1.831 52.512 MOLD Mold -3.145 53.162

BLCB Blackburn Darwen Roadside -2.484 53.716 NL3 N Lanarkshire Chapelhall -3.947 55.846

BLC2 Blackpool Marton -3.007 53.805 NL1 N Lanarkshire Coatbridge Whifflet

-4.019 55.852

BOT Bottesford -0.815 52.930 NL4 N Lanarkshire Croy -4.039 55.958

BORN Bournemouth -1.827 50.740 NL9 N Lanarkshire Moodiesburn

-4.082 55.909

BECR Bridgend Ewenny Cross Roundabout

-3.578 51.495 NL6 N Lanarkshire Motherwell

-3.986 55.788

BRT3 Brighton Preston Park -0.148 50.841 NL7 N Lanarkshire Shawhead Coatbridge

-4.023 55.844

BRS2 Bristol Old Market -2.584 51.456 CAE7 Nantgarw Road -3.232 51.575

BRS8 Bristol St Paul's -2.584 51.463 PEMB Narberth -4.691 51.782

BURY Bury Roadside -2.290 53.539 NEWC Newcastle Centre -1.611 54.978

BUSH Bush Estate -3.206 55.862 NCA3 Newcastle Cradlewell Roadside

-1.595 54.986

CAE5 Caerphilly Blackwood High Street

-3.195 51.667 NPT3 Newport -2.977 51.601

CAE4 Caerphilly White Street -3.218 51.574 NPT4 Newport M4 Junction 25 -2.973 51.601

CAM Cambridge Roadside 0.124 52.202 NWY5 Newry Canal Street -6.339 54.180

CA1 Camden Kerbside -0.175 51.544 NWY2 Newry Monaghan Row -6.348 54.179

CANT Canterbury 1.098 51.274 NWY1 Newry Trevor Hill -6.336 54.178

CARD Cardiff Centre -3.176 51.482 NWT5 Newtownabbey Antrim Road

-5.950 54.666

GNC Carlisle -2.950 54.930 NWT4 Newtownabbey Ballyclare Main St

-6.000 54.752

CARL Carlisle Roadside -2.945 54.895 NWT2 Newtownabbey Sandyknowes

-5.977 54.678

CAS3 Castlereagh Dundonald -5.803 54.595 IRV North Ayrshire Irvine High St

-4.667 55.615

MACK Charlton Mackrell -2.683 51.056 ND2 North Down Holywood A2

-5.838 54.642

CHAT Chatham Roadside 0.548 51.374 NL10 North Lanarkshire Cumbernauld

-4.016 55.943

CHP Chepstow A48 -2.679 51.638 NTN3 Northampton Kingsthorpe

-0.880 52.272

CHS6 Chesterfield -1.434 53.231 NO12 Norwich Lakenfields 1.302 52.614

CHS7 Chesterfield Roadside -1.457 53.232 NOTT Nottingham Centre -1.146 52.955

NTH1 Cimla Road / Victoria Gardens -3.802 51.660 OX Oxford Centre Roadside -1.257 51.752

COK Cork -8.475 51.900 OX3 Oxford St Ebbes -1.260 51.745

COV3 Coventry Memorial Park -1.520 52.394 PAIS Paisley Central Road -4.422 55.847

CWMB Cwmbran -3.007 51.654 PAI2 Paisley Glasgow Airport -4.426 55.868

DERY Derry -7.329 55.001 PAI3 Paisley Gordon Street -4.424 55.842

DER9 Derry Marlborough Street -7.330 55.000 PAI4 Paisley St James St -4.427 55.848

DPK1 Downpatrick Roadside -5.716 54.328 PEEB Peebles -3.197 55.657

DUB Dublin -6.278 53.354 PET2 Perth Atholl Street -3.434 56.399

DUD1 Dudley Centre -2.085 52.511 PET1 Perth Crieff -3.841 56.373

DUMB Dumbarton Roadside -4.560 55.943 PETH Perth High Street -3.432 56.397

DUMF Dumfries -3.614 55.070 PET3 Perth Muirton -3.450 56.415

DUN4 Dundee Broughty Ferry Road -2.943 56.467 PLYM Plymouth Centre -4.142 50.372

DUN6 Dundee Lochee Road -2.994 56.465 PD1 Pontardawe Swansea Road

-3.854 51.720

DUN1 Dundee Mains Loan -2.960 56.475 PT7 Port Talbot Docks -3.786 51.590

DUNM Dundee Meadowside -2.971 56.464 PT6 Port Talbot Dyffryn School

-3.751 51.572

DUN5 Dundee Seagate -2.967 56.462 PTLW Port Talbot Little Warren

-3.801 51.585

DUN3 Dundee Union Street -2.971 56.459 PT4 Port Talbot Margam -3.771 51.584

DUN7 Dundee Whitehall Street -2.971 56.460 MMF6 Port Talbot Prince Street -3.767 51.580

MARN E Ayrshire Kilmarnock St Marnock St

-4.498 55.607 PT8 Port Talbot Talbot Road -3.779 51.591

FINI East Ayrshire Kilmarnock John Finnie St

-4.499 55.611 PT10 Port Talbot Theodore Road

-3.772 51.590

EDB2 East Dunbartonshire Bearsden -4.334 55.920 PT9 Port Talbot Twll-yn-y-Wal Park

-3.759 51.577

EDB1 East Dunbartonshire Bishopbriggs

-4.225 55.904 PMTH Portsmouth -1.069 50.829

EDB3 East Dunbartonshire Kirkintilloch

-4.152 55.936 PRES Preston -2.680 53.766

EDB4 East Dunbartonshire -4.318 55.938 REA1 Reading New Town -0.944 51.453

MilngavieMUSS East Lothian Musselburgh N

High St-3.059 55.944 RHD6 Rhondda Pontypridd

Gelliwastad Rd-3.339 51.605

SHED East Renfrewshire Sheddens -4.275 55.786 RHD4 Rhondda-Cynon-Taf Broadway

-3.332 51.598

EB Eastbourne 0.272 50.806 RHD2 Rhondda-Cynon-Taf Nantgarw

-3.256 51.565

ED10 Edinburgh Glasgow Road -3.393 55.939 ROCH Rochester Stoke 0.635 51.456

ED5 Edinburgh Gorgie Road -3.232 55.938 ECCL Salford Eccles -2.334 53.485

ED7 Edinburgh Queen Street -3.205 55.954 SALT Saltash Roadside -4.230 50.413

ED9 Edinburgh Queensferry Road -3.303 55.960 WBRO Sandwell West Bromwich

-1.996 52.521

ED4 Edinburgh Roseburn -3.235 55.946 SDY Sandy Roadside -0.300 52.132

ED8 Edinburgh Salamander St -3.161 55.975 SCN2 Scunthorpe Town -0.637 53.586ED1 Edinburgh St John' Road -3.281 55.943 SHE2 Sheffield Centre -1.473 53.378

ED3 Edinburgh St Leonards -3.182 55.946 SHE Sheffield Tinsley -1.396 53.411

FALK Falkirk Grangemouth MC -3.721 56.019 SIB Sibton 1.463 52.294

FAL5 Falkirk Haggs -3.942 55.991 HARB South Ayrshire Ayr Harbour

-4.634 55.470

FAL3 Falkirk Hope St -3.786 56.002 AYR South Ayrshire Ayr High St

-4.632 55.465

FAL2 Falkirk Park St -3.783 56.001 SL02 South Lanarkshire Glespin

-3.895 55.532

FAL6 Falkirk West Bridge Street -3.790 56.001 SL03 South Lanarkshire Lanark

-3.776 55.674

CUPA Fife Cupar -3.014 56.319 SL01 South Lanarkshire Raith Interchange

-4.058 55.800

DUNF Fife Dunfermline -3.449 56.074 SL04 South Lanarkshire Rutherglen

-4.219 55.828

KIR Fife Kirkcaldy -3.141 56.124 SOUT Southampton Centre -1.396 50.908

ROSY Fife Rosyth -3.418 56.036 SEND Southend-on-Sea 0.678 51.544

ZF1 Folkestone Suburban 1.159 51.087 SK5 Southwark A2 Old Kent Road

-0.060 51.480

FW Fort William -5.101 56.823 OSY St Osyth 1.049 51.778

GL1 Glasgow Abercromby Street -4.231 55.851 HOPE Stanford-le-Hope Roadside

0.440 51.518

GLA5 Glasgow Anderston -4.271 55.862 STRL Stirling Craig' Roundabout

-3.932 56.115

GL3 Glasgow Broomhill -4.319 55.876 EAGL Stockton-on-Tees Eaglescliffe

-1.359 54.517

GL6 Glasgow Burgher St. -4.197 55.851 STOK Stoke-on-Trent Centre -2.175 53.028

GLA6 Glasgow Byres Road -4.295 55.874 STOR Storrington Roadside -0.450 50.917

GLA3 Glasgow Centre -4.255 55.858 SBAN Strabane Springhill Park -7.453 54.821

GL9 Glasgow Dumbarton Road -4.318 55.871 SV Strathvaich -4.777 57.734

GLA4 Glasgow Kerbside -4.259 55.859 SUN2 Sunderland Silksworth -1.407 54.884

GL2 Glasgow Nithsdale Road -4.271 55.836 SWA9 Swansea Cwm Level Park

-3.939 51.646

GLA7 Glasgow Waulkmillglen Reservoir

-4.355 55.794 SWA7 Swansea Hafod DOAS -3.939 51.633

GLAZ Glazebury -2.472 53.460 SWA5 Swansea Morriston Roadside

-3.921 51.662

GRAN Grangemouth -3.704 56.010 SWA1 Swansea Roadside -3.947 51.633

GRA2 Grangemouth Moray -3.711 56.013 THUR Thurrock 0.318 51.477

GDF Great Dun Fell -2.451 54.684 TH2 Tower Hamlets Roadside

-0.042 51.523

CAE6 Hafodyrynys -3.134 51.681 TWYN Twynyrodyn -3.366 51.744

HG1 Haringey Roadside -0.068 51.599 GLM7 V Glamorgan Dinas Powys Roadside

-3.212 51.436

HAR Harwell -1.325 51.571 GLM2 V Glamorgan Fonmon -3.354 51.397

HM High Muffles -0.809 54.335 GLM5 V Glamorgan Penarth -3.188 51.445

HONI Honiton -3.197 50.792 WAL4 Walsall Woodlands -2.031 52.606

HORE Horley -0.168 51.166 WAR Warrington -2.615 53.389

HULL Hull Centre -0.338 53.745 WDB3 West Dunbartonshire Clydebank

-4.406 55.918

HUL2 Hull Freetown -0.341 53.749 WL West London -0.200 51.494

INC1 Inverclyde Greenock Dunlop Street

-4.785 55.941 BRX West Lothian Broxburn -3.469 55.934

INV2 Inverness -4.241 57.481 WLN4 West Lothian Newton -3.456 55.984

LB Ladybower -1.752 53.403 WEYB Weybourne 1.122 52.950

LEAM Leamington Spa -1.533 52.289 WC Wharleycroft -2.469 54.617

LEAR Leamington Spa Rugby Road -1.543 52.295 WFEN Wicken Fen 0.291 52.299

LEED Leeds Centre -1.546 53.804 WIG5 Wigan Centre -2.638 53.549

LED6 Leeds Headingley Kerbside -1.576 53.820 TRAN Wirral Tranmere -3.023 53.373

LEIC Leicester Centre -1.133 52.631 WREX Wrexham -3.003 53.042

LEOM Leominster -2.737 52.222 WRX4 Wrexham Isycoed -2.901 53.048

LERW Lerwick -1.185 60.139 YW Yarner Wood -3.717 50.598

LVD2 Limavady Dungiven -6.927 54.928 YK10 York Bootham -1.087 53.968

LV6 Liverpool Queen's Drive Roadside

-2.963 53.447 YK11 York Fishergate -1.076 53.952

LVP Liverpool Speke -2.844 53.346

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