Title of Example

Example

Introduction

The Environmental Quality Team was engaged by the Transport Initiatives Team in DETL to provide consultancy services in respect of assessing the environmental impact of different scenarios of a potential Road User Charging (RUC) scheme in Bristol.

The requirements of the project were to assess the relative difference in emissions of major pollutants under the scenarios and to conduct some dispersion modelling on specified links within the network to ascertain the concentrations of major pollutants attributable to the operation of the scheme. This report will focus on the work to assess relative differences in emissions under each scenario.

Methodology

Traffic modelling of the different scenarios was conducted using the SATURN model by WS Atkins Ltd. The output from the traffic model was processed in emissions inventory software called EMIT supplied by CERC Ltd. EMIT is designed to be used in conjunction with dispersion modelling software, also supplied by CERC called ADMS. EMIT can be used to hold emissions data from various source types and can aggregate point and line sources into a grid of 1km squares so that changes in emissions can be displayed using GIS as a thematic map.

1.1 Data Processing

The output from the model was processed by the modelling team within DETL to provide spreadsheets giving a list of pairs of nodes with associated grid references. Each linked pair of nodes represents a link, and a speed and flow (AADT) was associated with each link. The speeds and flows were derived from the SATURN model by the transport planning modelling staff. Only AM and PM peak flows are available from the model. The emissions calculation requires an AADT (Annual Average Daily Traffic) figure, so the calculation to derive AADT from peak flows uses assumptions about the general relationship between these two measures of traffic flow.

The road networks for each of the scenarios were imported into ArcView GIS by modifying an Avenue script.

The flow and speed data were modified in the following way to enable import to the emissions inventory software, EMIT.

· Speeds were rounded up to multiples of five

· A split in the fleet makeup of motorcycles \ cars \ HGV was assumed as follows

1% motorcycles

92% cars

7% HGV

This split was determined by analysing data from recent classified traffic counts. The traffic model is unable to provide this information.

The speed and flow data were joined to the road network shapefiles in ArcView to give eight input shapefiles to be imported into EMIT. On importing the files, certain links were not imported due to having zero speed. In the region of 290 links out of the 5500 for each scenario were not imported.

Emissions per 1km grid square within the city boundary were calculated using EMIT, and the exported output from EMIT was converted to shapefiles. The emissions data was then exported to a spreadsheet and the difference in emissions from the “Do Minimum” scenario for each year was calculated. This difference is expressed in relative term (as a percentage) due to the inherent errors in using output from a traffic model.

1.2 Scenarios

Four scenarios for each of the future years were modelled, giving eight in total. The scenarios are as follows.

· Do Minimum

· Option 1

· Option6

· Complementary Measures

The years for which these scenarios were to be modelled were 2007 and 2017.

A separate EMIT database was used for each scenario, as errors were encountered when all the scenarios were included in one database. The latest available emissions factors (Euro Feb 2002) were used. The road type of Euro Urban Roads was used for all scenarios. The emissions factors are only available up until 2010, so the emissions factors for the 2017 scenarios were based on the 2010 factors. Emissions for the 2007 scenarios were calculated using 2007 emissions factors.

Results

Figure 1 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000D0000005F00520065006600350033003300380036003500340034000000 shows a typical aggregated output of emissions data in the form of 1km grid squares. The road network as represented by the traffic model is shown overlaid.

· Figure 1 Example of RUC Emissions Modelling Output

· Figure 2 Emissions estimates within central AQMA under different RUC scenarios

Figure 2 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000D0000005F00520065006600350033003300380036003600370030000000 shows the estimated emissions of key pollutants as calculated from the sum of all the grid squares intersecting the polygon representing the central AQMA of 2003. This is shown in Figure 3 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000D0000005F00520065006600350033003300380037003400340037000000 .

· Figure 3 Central AQMA and intersecting grid squares

Last Updated

13th January 2005