Showing papers by "Margaret Bell published in 2004"

The Effect of Ambient Temperature on Cold Start Urban Traffic Emissions for a Real World SI Car

Abstract: The influence of ambient temperature on exhaust emissions for an instrumented Euro 1 SI car was determined. A real world test cycle was used, based on an urban drive cycle that was similar to the ECE urban drive cycle. It was based on four laps of a street circuit and an emissions sample bag was taken for each lap. The bag for the first lap was for the cold start emissions. An in-vehicle direct exhaust dual bag sampling technique was used to simultaneously collect exhaust samples upstream and downstream of the three-way catalyst (TWC). The cold start tests were conducted over a year, with ambient temperatures ranging from – 2°C to 32°C. The exhaust system was instrumented with thermocouples so that the catalyst light off temperature could be determined. The results showed that CO emissions for the cold start were reduced by a factor of 8 downstream of catalyst when ambient temperature rose from -2°C to 32°C, the corresponding hydrocarbon emissions were reduced by a factor of 4. There was no clear relationship between NOx emissions and ambient temperature. For subsequent laps of the test circuit the reduction of CO and HC emissions as a function of ambient temperature was lower. The time for catalyst light off increased by 50% as the ambient temperature was reduced. The results show that the vehicle used is unlikely to meet the new – 7oC cold start CO emission regulations.

Reducing Urban Pollution Exposure from Road Transport (RUPERT)

Abstract: This paper presents the preliminary results of a two-year study on reducing urban pollution exposure from road transport (RUPERT). The main aim of this project is to develop a new modelling framework for nitrogen dioxide, carbon monoxide and particulate matter to simulate exposures of different population groups across a city, and to assess the impact of roadside concentrations on these exposures. This will be achieved by modelling the frequency distribution of personal exposures (PEFDs) as a function of urban background and roadside concentrations, under different traffic conditions. The modelling approach combines new and existing models relating traffic and air pollution data, with particular emphasis of the impact of congestion, and the probabilistic modelling framework of personal exposure. Modelling of roadside concentrations consists of two main elements, namely the analysis of concentrations patterns at different roadside sites and of the relationship between traffic conditions and added roadside pollution. Roadside concentrations are predicted using empirically derived relationships; statistical models, novel statistics and artificial neural networks namely feed forward neural network and radial basis neural network. The exposure modelling is carried out by linking two models: the INDAIR model, which is designed to simulate probabilistically diurnal profiles of air pollutant concentrations in a range of microenvironments, and the EXPAIR model, which is designed to simulate population exposure patterns based on population time-activity patterns and a library of micro-environmental concentrations derived from the INDAIR model.

Air quality modelling of strategic traffic demand modelling strategies

Abstract: This paper presents the results of the air quality modelling study carried out within the HEAVEN (Healthier Environment through Abatement of Vehicle Emission and Noise) EU: Fifth Framework Information Society Programme. The HEAVEN system in Leicester has identified potential scenarios for better air quality through improved control and management of traffic. These measures have been of two types; short-term tactical and long-term strategic measures. In the HEAVEN project emphasis was placed on developing and quantifying the impact of the more strategic citywide traffic demand management strategies (TDMS). Four TDMS scenarios were designed to assess the sensitivity to changes in speed and fleet composition of the network against the base case. However, two of the TDMS, namely those to assess the effect of reducing speed of traffic by 20% on all links across the network and to remove all HGV, were not realistic because they did not also consider the changes in the capacity of the network for traffic that would result. When the capacity reducing effects of the road network were investigated it was found that if a speed reduction of 20% were imposed the capacity would be substantially reduced and if all HGV were banned the capacity would increase. This capacity effect was measured using the TRIPS model and the results inputted into the air quality model Airviro. This paper presents the air quality impacts of the realistic scenarios and compares them to those for the sensitivity tests.

Personal exposure to air pollution at a street canyon intersection: implications for air quality management in the context of sustainable development

Abstract: R.N. Colvile, S. Kaur, S. Belcher, M. Bell, R. Britter, M. Nieuwenhuijsen, A. Robins, A. Tomlin, D. Shallcross Imperial College London, Department of Environmental Science & Technology, London, UK University of Reading Department of Meteorology, Reading, UK University of Leeds Institute for Transport Studies, Leeds, UK University of Cambridge, Department of Engineering, Cambridge, UK University of Surrey, School of Mechanical Engineering, Guildford, UK University of Leeds Department of Fuel & Energy, Leeds, UK University of Bristol Department of Chemistry Bristol, UK