A methodology for estimation of vehicle emissions in ... - Springer Link

0 downloads 0 Views 140KB Size Report
Environmental Health and Science, University of the West of England, ... qua lity management in the UK will require objective test procedures to evaluate and.
The Environmentalist 18, 175±182 (1998)

A methodology for estimation of vehicle emissions in an urban environment: an example from Greater Manchester D. RAYFIELD, J.W.S. LONGHURST*, A.F.R. WATSON, T. HEWISON, D.W. RAPER, D.E. CONLAN, AND B. OWEN Environmental Health and Science, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY

Summary Road transport is a major contributor to urban air pollution. The introduction of local air qua lity management in the UK will require objective test procedures to evaluate and prioritise the air pollution bene®ts of existing transport systems and proposed developments. This methodology has been developed to assist the land use and transport planning professionals in evaluating current and potential future impacts on air quality. The method couples an emissions estimation procedure to a traf®c ¯ow database. It requires data on emission factors, the composition of the vehicle ¯eet, vehicle control technologies and the daily traf®c ¯ow pro®le. With these data, it is possible to generate emission estimates per kilometre, link or road as selected by the user. Forecasts can be made by varying input variables. The current methodology allows prediction of ®ve or more pollutant species/classes, limited only by availability of emission factors. The method utilises a commercially available personal computer based spreadsheet. Further coupling of the method to a geographical information system will improve the decision support capability of the method. Introduction In the UK the recent Royal Commission on Environmental Pollution report (RCEP, 1994) identi®ed many of the issues that relate to trac pollution, particularly in major urban environments where many of the problems are most acute. The recognition of the importance of this issue, allied to awareness that catalysts on petrol vehicles will only o€er a partial solution, is leading many Local Authorities in the UK to consider more carefully both the e€ects of road trac in urban areas and the policies used to reduce the impact that emissions of pollutants have on urban air quality (Ramsden et al., 1993). In parallel with this has been the development of the UK Government's policies for strategic management * Prof. James W.S. Longhurst is the senior correspondent with regard to this paper and he is situated at the given address. All other authors are based at the Atmospheric Research and Information Centre, Department of Environmental and Geographical Sciences, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, UK.

0960-3115 Ó 1998 Kluwer Academic Publishers

of air quality (Longhurst et al., 1994). This recognises the crucial role of Local Authorities in managing and improving air quality (DoE, 1995). Whilst there remain important research questions regarding road trac emissions, it is clear that policy makers will require tools, particularly at the local level, to assess the scale of transport induced air quality problems. In turn, these tools must assist in the evaluation and prioritisation of alternative futures, so that decisions are made in the light of the best available knowledge of their air quality impacts. The emission estimation methodology This coupled trac ¯ow-emissions estimation methodology is designed to provide Local Authorities with a suitable decision making tool to assist in the integration of air quality management, transport planning and land use planning (Ray®eld et al., 1995, in press). It provides a capability for estimating emissions from road trac in a current case and then, by manipulation of input variables, provides a predictive capability 175

Ray®eld et al.

to assess the e€ect of changing transport parameters on emissions. The method also provides a retrospective emission estimation capability. The methodology is designed to produce an output in the form of an emission total either per kilometre of road or by road link. Initially the method considers ®ve pollutant species/classes, although more can be included and will be incorporated as the range of emission factors increases. The methodology could, in the long term, provide direct input to a dispersion model. The design rationale for this is that an objective decision making tool is required to enable alternative futures to be assessed by transport/land use planners (Ramsden et al., 1993; Longhurst et al., 1994). It is believed that emissions represent a more acceptable performance indicator for the intended user community than a dispersion model estimate of concentration (Longhurst et al., 1994). The computational procedures are designed for ease of use and are performed on a personal computer (PC) platform within a commercially available spreadsheet package.

road network' and covers 1398 km spread across the ten administrative districts of the conurbation. The de®nition of principal road includes motorways, `A' roads and `B' roads. The daily ¯ow exceeds 8 million vehicle kilometres across the network (GMTU, 1993). Some of the UK's busiest roads are located in this part of the North West of the UK. In 1992, sections of the M62 carried 160 000 vehicles per day. As well as forming part of the orbital motorway around Greater Manchester, the M62 is also the transPennine motorway, linking Liverpool, Manchester, Leeds and Hull. Locally some of the most congested `A' roads in the conurbation support up to 105 000 vehicles in an average weekday 24 hour period.

Trac ¯ow in Greater Manchester

DoT code number e.g. 6029 Road number e.g. M63

Information on the volume and type of trac in the conurbation is routinely collected and used in models to provide forecasts of future road usage and to assist in the complex task of planning and managing an area's transport infrastructure (GMTU, 1993). Trac counts are carried out on motorways, `A' roads, `B' roads and some minor roads in the Greater Manchester area. In all there are routine counts on 70 motorway links, 595 `A' road links and 291 on `B' road links spread across the conurbation. These are performed using a combination of automatic and manual counts. The count is conducted for both directions of the carriageway and whenever a particular count is undertaken it is repeated after three years on the same day of the year. The count procedure provides data on cars, buses, motor cycles, vans and three categories of goods vehicles for each link. The counts of trac ¯ow include a variety of time periods. A standard twelve hour count is carried out from 7am to 7pm and provides data on the morning rush hour, o€ peak and evening rush hour. The ¯ow on the motorway and `A' road links is available on an hour by hour basis for the whole 24 hour period as a representative sample of these are monitored automatically. By undertaking a small sample of surveys over 16, 18 and 24 hour periods, a set of conversion factors have been derived which enable a trac ¯ow estimate for any of these periods to be calculated from the standard 12 hour count. Similarly there are conversion factors to enable an annual average daily trac ¯ow to be calculated for a particular day of the year (GMTU, 1990). Trac ¯ows on 956 road links are used in this methodology. This set is known as the `principal 176

Trac ¯ow data The trac ¯ow data is available for each of the 956 road links. Two forms of data are available, 24 hour annual average weekday trac (AAWT) and 24 hour annual average daily trac (AADT). This is presented in the following format:-

Ordnance survey grid number e.g. 35684020 Duration of count e.g. 12 (Hours) Day of week count conducted e.g. 4 (1 ˆ Monday,...., 7 ˆ Sunday) Date of count e.g. 9/6/94 Car ¯ows e.g. 10111

Light Goods Vehicle ¯ows e.g. 3087 Medium Goods Vehicle ¯ows e.g. 1427 Heavy Goods Vehicle 3 axle ¯ows e.g. 99 Heavy Goods Vehicle 4+ axle ¯ows e.g.1004 Bus & coach ¯ows e.g. 87 Motor cycle ¯ows e.g. 92 Tota ¯ow e.g. 15907

In Fig. 1 the principal road network AAWT ¯ows are shown for each of the ten administrative districts. In Fig. 2 the length in kilometres of principal roads is shown. Vehicle ¯eet information Within the coupled ¯ow-emission estimation methodology vehicle ¯eet and ¯ow information provided by the counting procedures is statistically manipulated to provide subdivisions based upon engine size (cars only), fuel type and emission control technology. In the case of cars this is achieved by ®rstly determining from statistical sources the percentage of cars that are petrol (leaded or unleaded) or diesel fuelled, and those that have a catalytic converter ®tted. The total number of cars in each of these groups is apportioned to the number of car movements in the trac ¯ow data. The car category is further divided into engine size by applying statistical The Environmentalist

A methodology for estimation of vehicle emissions

Fig. 1. Greater Manchester conurbation, N.W. England. 1992 Principal road 24 hour annual average weekday trac ¯ow (AAWT ¯ow) by district.

factors to the ¯ow data representative of the proportion of cars that are small (2.0 l) engine sized. Data

from national publications are utilised in this stage of the methodology (ETSU, 1994; DoT, 1993)

Fig. 2. Greater Manchester conurbation, N.W. England. 1992 Principal road length in kilometres, by district.

177

Ray®eld et al.

Emission factors

Output and results

Emission factors are applied to the trac ¯ow data and are selected as representative of the driving conditions experienced on the individual link. Factors are applied to each of the di€erent vehicle categories and the vehicle fuel classes. Emission factors currently used are those recommended by the National Atmospheric Emissions Inventory (Eggleston , 1992), and ETSU (1994). Together these sources have enabled a suite of emission factors to be constructed for use with 19 categories of vehicles.

In the following example the emission total for a section of the M61 in Bolton has been estimated. This is based on AAWT data and is the estimated emission of NOx in a 24 hour period by the car group (Petrol, No Catalyst, Leaded fuel with engine size less than 1.4 l).

Emission calculation The emission estimation procedure and the process needed to prepare the original trac ¯ow data for use is shown in Fig. 3. The box termed `emission estimates' on this diagram, encapsulates the equation for determining the emission totals and is the culmination of all the steps described earlier. The equation for determining estimated emission totals can be given as thus:Ts;t ˆ Vv  Lr  EFp;v;r

…1†

Where T ˆ Emission Total (Tonnes), L ˆ Road Length (km), V ˆ Vehicle Flow (Annual Average Weekday Trac, Annual Average Daily Trac), EF ˆ Emission Factor (g km)1) and can be given by s ˆ scale descriptor (road, district, conurbation), r ˆ road type (motorway, `A', `B'), t ˆ time period (hour, day, week, month, year), p ˆ pollutant species, v ˆ vehicle type (fuel, control technology, engine size)

Fig. 3. Emission estimation procedure and the process needed to prepare the original trac ¯ow data.

178

(V)11566:1  …L† 0:724 km  …EF† 4:21 g kmÿ1 ˆ 0:035 Tonnes In addition to deriving individual road, link or kilometre estimates, these may be summed to provide totals for individual administrative districts in the conurbation or for the Greater Manchester area as a whole. The estimates include the total amount of emissions in each of the 19 vehicle groups for each road type. The total emissions for all roads in all 10 administrative districts can be calculated and the emission per kilometre of the road network determined. This is easily calculated by dividing the net totals given above, by the length of the appropriate part of the road network. Calculating this emission total enables comparisons to be made between each district and road type. Examples of the graphical output from the methodology are shown in Figs. 4, 5 and 6. In each of these AAWT emissions from road trac sources in the year 1992 are shown. The proportion of the total emission due to cars is also shown. The annual totals of CO, NOx and VOCs derived from AADT data are shown in Fig. 7. The data presented in Tables 1±5 are further examples of the output available from the coupled ¯owemission estimation methodology. The results given in these examples are derived from 24 hour AADT trac data. Tables 1 and 2 provide an emission estimate for the total road trac sector in Greater Manchester. In addition to CO, NOx and VOCs, CO2 and particulate matter (PTC) estimates are also given. As expected these data indicate that the emission tonnages for carbon monoxide and carbon dioxide are far higher than those for nitrogen oxides, particulate matter and volatile organic compounds. In addition, the emission from cars is clearly the dominant subsource within the overall Greater Manchester road trac source. Table 3 shows the emissions of carbon monoxide by cars on `B' roads in Bolton over a 24 hour average day. The large contribution made by small cars powered by leaded petrol (27%), re¯ects the fact that a large proportion of cars in 1992 used leaded petrol and that almost half the cars in 1992 were of the small engined variety (