An evaluation of the potential impacts of traffic management strategies on air pollution, emissions and public health in Dublin.

Abstract

Nowadays, air pollution is a huge threat to human health. It is responsible for 6.4 million premature deaths worldwide per year, which is 72% of the 9 million deaths per year from all types of pollution. Vulnerable groups, e.g. children and the elderly, have been noted to be more affected by air pollution. In urban areas, traffic is one of the major sources of air pollution. Traffic management strategies have been proposed and introduced in many cities as an important part of urban management. Some of these strategies are designed in order to solve the problem of congestion, to shape better land use, to meet the needs of a more strategic plan of a city or a nation, etc. While others are aimed at improving the environment. These traffic management strategies can potentially have significant impacts on air quality and human health. Therefore, it is important to try and predict the impact of different traffic management strategies on pollutant emissions, air quality, and thus on public health. The analysis of traffic management strategies in relation to their potential health impact can help the public and policy makers to be aware of the effectiveness of these strategies, and to attract public attention about the human health impacts of traffic management strategies that are not designed to protect the environment. There are few examples in the literature that compare different traffic management strategies with regard to their possible health impacts. In this thesis, using the city of Dublin as an example, the impacts of different traffic management strategies on traffic, emissions, air quality and public health were evaluated and compared. On the other hand, as transport is an important source of GHGs (Greenhouse Gases) and thus a significant contributor to global warming, the impact of traffic management strategies on the emission of GHGs was also discussed. Four typical traffic management strategies were included in this research: an infrastructure construction, a traffic management regulation, speed limit changes and fleet composition changes. In order to assess the impacts of these strategies, a traffic model, emission model, dispersion model and health impact model were developed and integrated into a modelling chain to evaluate the traffic, air quality and health outcome changes brought about by these strategies against a baseline scenario. To achieve this goal, the evaluation of these strategies was divided into three steps. Each step served the same goal of evaluating the impacts of different traffic management strategies, but each had its own focus. In the first step, as presented in Chapter 3, a traffic model was established in VISUM and an emission model was developed by using COPERT to assess the impact of an infrastructural change and a traffic regulation change in Dublin. These were the opening of the Dublin Port Tunnel and the implementation of a city centre 5-axel HGV ban. The impacts on traffic conditions, total vehicle travelling distances, travelling speed distributions, total emissions and standardized emissions adjusted by travelling demand distances, brought about by these two strategies were evaluated. It was found that the infrastructural change and the traffic management regulation change, though only in operation in the city centre, had impacts on the traffic of the whole city. These strategies reduced the traffic in the city centre and improved traffic speed distribution for the whole city. However, these strategies resulted in HGVs travelling further with increased total emissions. This chapter emphasised that the impacts of traffic management strategies on a local scale and on a whole city scale were different and thus it?s important to find the suitable focus area for a holistic assessment of a traffic management strategies. In the second step, as demonstrated in Chapter 4, VISUM again was utilized to develop a traffic model, and OSPM was employed to develop an emission and dispersion model to evaluate the impact of the changes in traffic speed limits and fleet compositions on air quality on roads near a school in Dublin city centre. This was conducted to investigate the influence of these changes on vulnerable population groups. The results suggested that traffic speed limit reduction and fleet changes can influence the traffic-induced air pollutant concentrations significantly, such that these strategies had larger impacts on air quality in streets with higher traffic volumes and hence higher pollutant concentrations. This study highlighted that while speed limit reduction regulation near the roads of schools has been widely adopted, its impact on air quality and health of vulnerable people (i.e. pupils) should not be neglected as it can influence the air quality notably. Also, petrol and diesel vehicles had different and sometimes contrasting impacts on different pollutants, therefore the health impacts of incentivising either type of vehicle are complex. The final step of the evaluation was outlined in Chapter 5. The traffic model, emission and dispersion model developed in previous chapters were utilized. A Gaussian plume model was also developed in the form of finite line sources, and a health impact model developed in BenMAP was added to the modelling chain to estimate the air quality changes and health impacts brought about by four types of traffic management strategies throughout Dublin. It was predicted that the infrastructure construction and the traffic management regulation, which were estimated to increase the pollutant emissions in Chapter 3, had little health impacts on the city as a whole since they had contrasting effects, positive and negative, in different parts of the city. Speed limits were predicted to have the same order of impact on mortality incidences as fatalities caused by traffic accidents in Dublin in 2013, which again emphasised the consideration of health impact of air pollution in the design of traffic speed limit, especially for vulnerable population sub-groups. The fleet composition change from diesel to petrol vehicles was predicted to reduce total mortality incidence significantly. Finally, the impacts of these strategies were discussed in Chapter 6, regarding their impacts on public health through affecting emissions of different air pollutants and on climate change through influencing emissions of GHGs. A cross-comparison of the cost and benefits between them was conducted. Practical suggestions for traffic management strategy implementation were derived from these analyses and cross-comparison.