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Page 1: Using of ADMS-Urban Model to Study the Air Quality ...€¦ · the UK (Farias and ApSimon, 2006). ADMS-Urban is one of the most popular packages and is widely used for air quality

International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

International Journal of Environmental Sciences Vol.1 No.2. 2012. Pp. 118-125 ©Copyright by CRDEEP. All Rights Reserved Full Length Research Paper Using of ADMS-Urban Model to Study the Air Quality Problems in Norwich, UK T. M. Habeebullah(1,2), S. Dorling(2) (1)The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al Qura University-Makkah-Kingdom of Saudi Arabia (2)School of Environmental Sciences, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK

Corresponding Author: T. M. Habeebullah; E-mail: [email protected]

ABSTRACT.

The main purpose of using ADMS-Urban is to study the air quality problems in Norwich, and assess how sensitive the results are to long-term meteorological conditions. NO2 pollutant was focused on in particular because of the excellent coverage provided by the diffusion tube data in Norwich. The availability of local pollution and weather measurements were produced better agreements between modeled and monitored data. The research findings were shown that the ADMS-Urban was a very sensitive tool and that selecting the input parameters was critical for successful modelling. Norwich’s air quality with respect to many different parameters was thus successfully modelled NO2 in this study, and notwithstanding the underprediction, the modelling has provided a basis on which to build pictures in the future of NO2 exceedence patterns in the city. This research was used rural background data as a more rigorous test of the model. In this regard, this research was found that the location characteristics of the point measurement stations had an impact on the modelling, particularly the height above ground of the wind instruments.

Key words: ADMS-Urban Model, Weather, Air Quality, Rural Background and Norwich.

INTRODUCTION Throughout Europe, there was increasing activity to assess and improve air quality in urban areas by using a variety of models (Carruthers et al., 1999b). The ESCOMPTE program was produced a relevant set of data for testing and evaluating regional pollution models in Marseilles, south-eastern France (Cros et al., 2004; Dufour et al., 2005). In Berlin, the BERLIOZ model was used to study the effect of different meteorological conditions on pollution episodes (Volz-Thomas et al., 2000). The European wide project COST715 was provided a framework in which the relationship between meteorology and urban air pollution problems was studied in 19 European countries (Fisher et al., 2005). A number of air quality dispersion models were used as supporting tools for local urban air pollution management in the UK (Farias and ApSimon, 2006). ADMS-Urban is one of the most popular packages and is widely used for air quality management by 60 local authorities in the UK (Leksmono et al., 2006; Sriyaraj et al., 2004). Various studies were introduced in terms of the use of the ADMS-Urban model. The performance of an urban emission inventory (1×1km grid) and a dispersion model (ADMS-Urban) was examined to assess air quality from emission sources by comparing model predictions with monitored concentrations of NOx and SO2 at four locations, in two areas, Central London and East London (Owen et al., 1999; Owen et al., 2000). Predicted concentrations for a summer and winter period were calculated and modelled, and measured time series data were compared. The winter mean NO2 predicted value (46ppb) represents an

underprediction for the winter period when compared with the observed kerbside concentration (71ppb). The tendency for underprediction during the winter may also be linked to the colder more stable conditions experienced during this period. The model and emissions inventory were provided fairly good estimates of mean and percentile values of NOx when compared to monitored data during the summer period of the study. The conclusion was that the model may show a tendency to under-predict concentrations of NOx during cold, stable atmospheric conditions but the chemistry model performed reasonably well for the summer period. A situation where traffic is not the sole cause of an AQMA declaration was investigated, from a theoretical perspective, by Leksmono et al. (2006). The research was presented air quality assessments in different scenarios, which were modelled using ADMS-Urban to predict concentrations of NO2. Modelling was carried out using simple scenarios with a combination of traffic and industrial emissions, different types of roads, meteorological data and approaches to derive nitrogen dioxide from oxides of nitrogen. The modelling results were shown the significance of the NOx: NO2 relationship and meteorological data as parameters inputted into the model. The maximum modelled NO2 concentration arising from traffic emissions in an open road, calculated with the GRS scheme, is 31.2µgm-3, whilst under the same conditions, a single industrial source, with no road, produces a higher concentration of 42.0µgm-3. Even though the emissions from an industrial source were very much larger than from traffic in one road, the concentrations at the ground level were

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International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

similar. An open road situation, using the GRS scheme and including industrial emissions, was given rise to a slightly higher modelled NO2 concentration of 42.3µgm-3. The ‘street canyon’ effect was resulted in a much higher modelled NO2 concentration than an open road with the same parameters (Leksmono et al., 2006). This study was used the ADMS-Urban model to improve understanding of air quality problems in Norwich, based on an existing detailed local Emissions Inventory and on long-term weather datasets. This approach was tested the sensitivity of model output to the choice of input meteorological data, in terms of period, through making comparisons between monitored and modelled data (especially exceedences and episodes).

MATERIALS AND METHODS Study area Norwich is the most eastern city in the UK (Fig. 1), and is influenced by continental weather conditions (Chatterton et al., 2000). These continental conditions affect the UK climate in terms of precipitation, air temperature and absolute humidity. Moreover, Norwich is influenced by the proximity of the North Sea and, in late Spring and summer, by its sea breezes (Glenn, 1987). The city is also particularly exposed to strong winds when a depression develops over the North Sea, especially in winter, as this draws down Arctic winds making Norwich, at times, much colder than the other two cities (Wheeler and Mayes, 1997). Being further inland than other UK cities (and therefore less windy), and with the influence of the nearby continent at certain times of the year (especially during winter), night-time temperature inversions occur and these may cause pollution to accumulate in the area, allowing their concentrations to increase (Kasprzok, 2001).

Figure 1: Map of Norwich location.

INSTRUMENTATION AND MEASUREMENT Part of the ADMS-Urban model by Wood (2007) was involved the creation of a 2003 Norfolk pollution emissions inventory. Wood’s inventory contained the air pollutants; benzene, 1,3 - butadiene, CO, Lead, Mercury, NO2, NOx, PM10, SO2 and NMVOC, and the greenhouse gases CO2, N2O and Methane. Emissions of all the relevant pollutants were calculated using a set of government emission factors. These were based on emissions data for 2003 taken from different sources. Traffic fleet composition for 2003 was used to calculate the number of vehicles of different ages and engine sizes on the roads for each year. The sources included in

Wood’s thesis were: roads, rail, airport take off and landing, inland boating, industry, agriculture and the energy consumption from the domestic, commercial and public sectors. The Wood’s inventory was spatially resolved to a 1x1km grid of Norfolk using ArcGIS v9.1, geographical information system software, and EMITS software. The emissions inventory produced for this study were required road sources that were not included in Wood’s inventories because traffic flows in the city centre have changed since 2003, partly because of new retail developments with large car parks. It was therefore necessary to create data relating to 52 additional roads, some located between the Inner and the

Norwich

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International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

Outer Ring Roads, and some inside the Inner Ring Road close to the Norwich Urban Centre station and diffusion tube measurement sites. The reasons for including these roads are:

1. To enhance the existing available data.

2. To develop a new baseline emissions inventory for Norwich.

3. To model the effect of pollutants from individual line sources on air quality elsewhere in the city.

4. To highlight areas that could be high risk or problem areas.

Surface hourly weather data for this modelling study were obtained from the UK Meteorological Office weather station at Coltishall which is located 14km northeast of Norwich. This site is the most representative meteorological station, measuring the required parameters which supply the relevant input for ADMS-Urban for the study area. The wind measurements are made at a height of 10m above ground level, and therefore can broadly be considered representative of air flow over the city. The ADMS-Urban model requires appropriate background concentrations for a range of pollutants in order to simulate chemical reactions correctly (CERC, 2006). Hourly average concentrations of NOx, NO2, O3 and SO2 were taken from the rural station site at Wicken Fen and PM10 was obtained from the Harwell station as there were no PM10 measurements at the Wicken Fen station. All data were downloaded from the UK Air Quality Archive website for the years from 2003 to 2005, as required for this study. In order to verify the accuracy of the model, it is necessary to compare it with observation data. There were two stations within the area of the city centre in Norwich. Norwich Urban Centre and Norwich Roadside stations, and were the only automatic stations that can be compared with the model results. In addition, there were non-automatic monitors which also can be compared with the model results. The non-automatic monitors were diffusion tubes distributed inside the Outer and the Inner Ring Road zones. RESULTS AND DISCUSSION The modelling in this research was produced three gridded outputs for annual NO2 concentrations for Norwich, and these were 2003, 2004 and 2005 (Fig. 2). It can be seen that the differences between 2004 and 2005 were relatively minor with the street canyon and emission inventory data. The concentrations at the various levels (18-20µgm-3, 20-22µgm-3 and 22-24µgm-3) cover largely the same areas although 2005 has slightly larger areas with the higher levels of pollution. On the other hand, the year 2003 was markedly different from 2004 and 2005 although they used the same emission

inventories, showing that 2003 was a year with much higher levels in Norwich. The spatial variations still match those of 2004 and 2005 but the highest levels of NO2 were to be found more noticeably along the main traffic arteries. Generally, the wind roses for 2004 and 2005 were very similar to each other but different from 2003. It is therefore consistent that the NO2 concentration patterns reflect this, supporting the close relationship between prevailing winds and local NO2 concentrations. The weather for 2003 can be characterized as abnormal; there were more frequent winter temperature inversions, and the summer was hotter than average. Abnormal weather conditions could possibly explain the elevated levels of NO2 in 2003 but perhaps of more significance was the wind rose as one aspect of the weather conditions, which shown that there were increased easterlies. These winds came from the more industrialized areas of north-western Europe and were therefore associated with elevated levels of pollution. Norwich is the most easterly city in the UK and is therefore the one most likely to be affected by this. A previous study (Chatterton et al., 2000) has suggested that levels of NO2 were almost entirely related to local sources but another study (Cardenas et al., 1998) was used a trajectory model to investigate the transfer of NO2 to the UK by easterly winds from Northern Europe, confirming the finding here.

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International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

Figure 2. Annual comparison of NO2 (µgm-3) between three years of model outputs, including wind roses (2003, 2004 and 2005).

Comparisons between the monitored and the modelled data for each of the years 2003, 2004 and 2005 were presented as Figure 3, 4 and 5. These were shown a continued decline in NO2 background concentrations, part of the European wide trend previously mentioned. These three Figures were very similar but some differences and aspects are worthy of note. There were only two automatic air quality stations (Norwich Urban Centre and Norwich Roadside); all the others are diffusion tubes. The modelled data consistently underpredicts the monitored data for all diffusion tubes, with the exception of Ber Street, for all three years. This may reflect the fact that

the diffusion tubes were directly exposed to the traffic and so were particularly sensitive to the traffic flow. Nevertheless, there were variations in the percentage values of this underprediction and this may be because each site has its own characteristics. Furthermore, it should be noted that many researchers (Carruthers et al., 1999a; Carruthers et al., 1999b; Chatterton et al., 2000; Huang et al., 2002; McHugh et al., 2005) around the world were also derived underpredicted values in their ADMS-Urban modelling. In this case, the underpredictions results from employing Coltishall meteorological data.

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International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

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Figure 3. Comparison of NO2 (µgm-3) between monitored and modelled results, 2003.

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Figure 4. Comparison of NO2 (µgm-3) between monitored and modelled results, 2004. (St Augustines diffusion tube data were missing).

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International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

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Figure 5. Comparison of NO2 (µgm-3) between monitored and modelled results, 2005. (St Stephens St (mid) diffusion tube data were missing).

On the other hand, the automatic air quality stations have been quite accurately modelled, with only one over-estimation (Norwich Urban Centre in 2003). Another interesting aspect of 2003 was the significantly higher level of background NO2 (measured from the rural site at Wicken Fen). This would have contributed to the two exceedences in the modelled data (Tombland and Castle Meadow Shire), both of which are traversed by large numbers of buses. Castle Meadow Shire is also next to the major junction with Prince of Wales Road, leading to even higher concentrations of NO2. Also of note was the Riverside diffusion tube site which returned the highest measured values for NO2 in 2003 (St Augustines Street returned the highest values for 2004 and 2005). The City Council is already in the process of including Riverside in its AQMA as it has already done with St Augustines Street. Furthermore, Riverside was returned values much higher than the modelled ones because the traffic behaviour was

characterized by lengthy queues as the researcher found during his traffic flow count (more details shown in Figure 6), and the tubes were located very close to these queues. Additionally, there was a great deal of traffic associated with the adjacent Norwich Railway Station where many cars and taxis drop off and pick up passengers at an access road close to the main Riverside junction with Prince of Wales Road. Most taxis and buses have diesel engines, which can lead to a significant increase in primary NO2 emissions (Defra, 2008). Prevailing south-westerly winds carry pollutants from the Railway Station area, in addition to London pollution, up Riverside Road to the diffusion tube. This is further exacerbated by the local topography; there is a hill to the east which tends to funnel northerlies, westerlies and southerlies up and down the length of Riverside. This road is thus a form of canyon and therefore elevated values should be expected.

Figure 6. Map for Riverside area (Source: Google Earth).

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International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

A further three areas, Tombland, Cattlemarket Street and Johnson Place (adjacent to Chapel Field Road), were recorded concentrations of NO2 above the annual objective standard of 40µmg-3, in the diffusion tube data. The researcher was studied these areas and noted the traffic behaviour. In all these locations, the traffic was very heavy and was subject to frequent build-ups; in the case of Chapel Field Road because it was waiting to access the roundabout at each end, in Tombland because of parking, access to Norwich Cathedral, and a busy pedestrian crossing, and in Cattlemarket Street because it was on a hill with two sets of traffic lights and access to an underground car park. The high buildings and location of the Cathedral also create a street canyon effect in Tombland. On the basis of the monitored data, Norwich City Council should consider including these sites in their list of AQMAs as exposure is a key criterion for declaring an AQMA. Furthermore, with respect to Tombland, which was currently not an AQMA, not only did the monitored data show exceedences, but the modelled data were also shown exceedence of the 40µgm-3 standard objective for 2003. Finally, it is important to note, vis-à-vis the under-estimations in the modelled data, that Coltishall meteorological data was used in the modelling; Coltishall is a village close to Norwich but no such data were available from the Norwich Weather Centre station as it had closed. CONCLUSION The aim of this study was to identify a relationship between air quality and weather patterns by using the ADMS-Urban model. This model was used here in conjunction with a local emissions inventory to model concentrations of NO2 PM10 and O3 in the City of Norwich. A summary and description of the key results of the study are presented and discussed as follows: 1- The inclusion of new road sources were shown to be

important in improving accuracy, but perhaps of greater importance has been the inclusion of canyon effect. All of these have helped to improve the accuracy of the modelling with respect to building an overall picture of NO2 concentrations in Norwich during winter and summer, and therefore should be included when assessing street-level pollution.

2- Several sites in Norwich (Tombland, Cattlemarket St, Johnson Place and Exchange St) were shown high NO2 concentrations in both monitoring and modelling and the City Council must consider including these in their AQMAs.

3- The tendency of the model to overpredict values of NO2 concentrations in the summer and mostly underpredict in the winter would suggest that there might be seasonal variations in the emission data which were not reflected in the inventory database.

4- There was evidence that pollutants are wind-shifted slightly, taking them from their sources into residential.

5- The model results were shown that air quality station data were more accurate than passive sampling data.

6- The abnormal weather conditions in 2003 were reflected in the model output, thus providing additional evidence of the model’s accuracy.

7- Comparing November 2003, 2004 and 2005 (monitored and modelled data) were presented a test for the

modelling because of the high concentrations of NO2 and the varying wind speeds and directions. The modelling in this case was made some encouragingly accurate predictions, but also some heavy underpredictions. The reasons for these were addressed in terms of diffusion tube location and the use of remote data sources.

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International Journal of Environmental Sciences Habeebullah and Dorling Vol.1 No.2 ISSN: 2277-1948

Online version is available at: www.crdeep.org

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