This thesis discusses on air quality in Oslo and how it has been changed during the time from 2003 to 2013. It also goes through the existing and upcoming technologies for the collection of air quality data. The trend is changing for data collection as the use of low-cost sensors is increasing along with the concept so called big data. The research is based on the air quality data received from the official air quality monitoring stations in the city of Oslo since 2003 and data from low-cost static sensors deployed in the city of Oslo for 2015. The main goal of this thesis is to evaluate and improve the reliability of low-cost sensors or public air quality information and to have a user-friendly visualization of pollutant data collected by the sensors so the people can have a better understanding of the air pollution in their surroundings and take actions to reduce their exposure. We propose a linear regression model which is able to calibrate these sensors and rectify the errors and provide reliable readings to some extent. However, the values are sensitive to meteorological conditions, which stresses the need of frequent calibration, especially to account for seasonal changes. The application of field of calibration can help reduce the bias in the data. Hence it is concluded that the data from low-cost sensors cannot be used for regulatory purposes and where high data accuracy is required. Finally, we also have researched on different air quality indices around the world and the usability of air quality data to public. We have proposed a user interface for mobile applications that can help visualize the personalized air quality index based on the health conditions of the users. However, the proposed visualization needs to go into extensive evaluation before we proceed further towards visualization. The output of the project will be useful to the people who are more sensitive towards air pollution as for instance children, asthmatics, pregnant woman, etc., but also for the general public, scientific and environmental agencies. The thesis is completed with an exhaustive annex, presenting breakpoints for AQI, health recommendations, as well as the temporal and spatial variation of different pollutants and the statistics of the regression models used in this study.