Diploma Research/ master’s thesis/ PhD thesis  by ” Noor Waleed ”  Department of  Statistics and Informatics

Discussion of the Diploma Research/ master’s thesis/ PhD thesis in the College of Computer Science and Mathematics -Department of (  Statistics and Informatics   ) entitled:

supervised by  Dr. Mohammed Qasim Yahya

The thesis addressed       . Using Hidden Markov Models to Model Air Pollution in Mosul: An Applied Study on PM2.5 Concentrations.

The study addressed Using Hidden Markov Models to Model Air Pollution in Mosul: An Applied Study on PM2.5 Concentrations.

  The study addressed the modeling and analysis of air pollution levels in the city of Mosul, focusing on concentrations of fine airborne suspended particles (PM2.5) for the period from the beginning of 2018 to the end of 2025, and on the study and development of hidden Markov models.

The thesis aimed to build and evaluate an AR-HMM (Autoregressive Hidden Markov Model), which allows the integration of Markov transition probabilities with autoregressive dynamics to address the limitations of traditional models. The data consisted of pollution time series for Mosul city from 2018 to 2025, with four statistically defined states.

This thesis/dissertation contributes to achieving the following Sustainable Development Goals: The developed statistical model (AR-HMM) helps provide accurate forecasts of fine particulate matter (PM2.5) levels, which contributes to reducing diseases caused by air pollution and alerting the most vulnerable groups. The study provides an analytical tool for decision-makers to monitor air quality in Mosul and improve the city’s environmental management, supporting sustainable urban planning and reducing direct environmental impact. Modeling pollution time-series data also helps in understanding patterns of environmental change and emissions, which calls for proactive climate measures and policies at the local level.