using of adms-urban model to study the air quality ... the uk (farias and apsimon, 2006). adms-urban

Download Using of ADMS-Urban Model to Study the Air Quality ... the UK (Farias and ApSimon, 2006). ADMS-Urban

Post on 17-Jun-2020




0 download

Embed Size (px)


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

    Online version is available at:

    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:


    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


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

    Online version is available at:

    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



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

    Online version is available at:

    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 da