Optimal Methodology to Generate Road Traffic Emissions for Air Quality Modeling

Growing population, consuming a large amount of energy such as combustion of fossil fuel, increasing pollutant emissions in the atmosphere are the threats to the sustainable development of our planet in general, and of the air quality in particular. According to the World Health Organization, air pollution causes the death of more than 2 million people per year in developing countries, and millions of people also suffer from various respiratory illnesses. Road traffic is the main source of air pollution in cities and there are large uncertainties associated to this source of pollution. Different models are available to quantify the amount of pollutants released by road traffic. However, these models always require a large amount of information and work, and thus their use results expensive. These limitations are difficult for the study and the management of air quality in cities from the developing world. Thus, it is extremely difficult to design efficient abatement strategies to reduce air pollution. For this reason, it is necessary to develop a new methodology for generating road traffic emissions to contribute to a better management of the urban air quality. The first aim of this PhD thesis is to develop and to validate a new model for generating road traffic emissions in several steps with different levels of complexity. The developed model is called EMISENS. Its main specifications are: (i) EMISENS is able to compute a total amount of emissions and to distribute it in time and in space using a methodology which combines the top-down and the bottom-up approaches; (ii) the model is able to compute the emissions and the uncertainties within a reasonable computing time and (iii) the model formulation is based on well referenced methodology (COPERT IV). The validation of EMISENS model was carried out by its application over Strasbourg, France. The results of EMISENS have been compared with the results of the more complete and complex model Circul'air which is currently used to manage the Strasbourg air quality. After comparing the results of the two models, it appeared that they are very close. This example of application illustrates the capacity of EMISENS to calculate road traffic emission inventory (EI) for cities in developed countries as well as in developing countries. Further on, a complete EI is carried out over Ho Chi Minh City (HCMC) by applying an innovative methodology based on the application of the EMISENS model. HCMC is the largest city in Vietnam, it had more than 6 million inhabitants in 2006. It has more than three million vehicles and 28,500 factories in the city. High levels of air pollution are thus very often detected. The purpose of this part of the research consists in applying the EMISENS model to generate road traffic emissions. For the other emission sources, the top-down approach is used for generating the EI. The results show that the road traffic is the main emission source in the city. The motorcycles are responsible of the traffic emissions (94 % of CO, 68% of Non-Methane Volatile Organic Compound (NMVOC), 61 % of SO2 and 99 % of CH4). Two scenarios for reducing traffic emissions are evaluated to reduce the HCMC emissions for the year 2015 and 2020. In addition, two other scenarios are the Business as Usual scenarios for the year 2015 and 2020 are also studied to evaluate the traffic emissions in HCMC. The third part of this work consists in applying air quality models to the region of HCMC, the aim here is to study abatement strategies for emission reduction in the city. The results of the simulation show that the plume of O3 is developed in the north-western part of the city. These results are in good agreement with the measurements. Among the four previous emission scenarios, we chose only two reduction emission scenarios to study the effective abatement strategies for the year 2015 and 2020 in using air quality model. These two affective abatement strategies are adopted to help the local government to take decision for managing air quality in HCMC. The 100 Monte Carlo (MC) simulations are run for estimating the uncertainty in the results of air quality simulations. The results of these two abatement strategies showed that if the local government follows the emission control plan: For 2015, the O3 concentration in 2015 will be similar to the present O3 concentration. For 2020, the O3 concentration in 2020 will decrease of around 10% to 30% of O3 in comparison to the actual level. However, the O3 concentration in 2020 is still higher than standard limit. The developed methodology for generating road traffic emissions offers several advantages. It is able to calculate a road traffic emission for both developing and developed countries. The calculation is divided in several steps with different level of complexity. Therefore, this methodology provides the new approach to manage air quality in cities.