Air Quality Monitoring

Air Quality Monitoring

Air pollution in large cities is considered a severe environmental problem worldwide; hence, many countries originated air quality monitoring plans to control pollution levels around big cities. Harmful emissions into the air are a symbol of an environmental force that seriously affects man’s health, natural life, and agriculture, thus leading to a significant loss on the national economy. The government in industrialized countries deployed many regulations to apply restrictions on emission limits, thus reducing the air levels and enforcing the international standards for air quality levels. A recently published research work [1,2] showed how machine learning techniques could help in forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models. Dr. Sheta extended his research and developed an enhanced evolutionary-based model for air quality prediction. A hybrid neural network model for forecasting ozone and particulate matter concentrations in the Republic of China was presented in [3]

Publications

1. E. Kovaˇc-Andri ́c, H. Sheta, Alaa and Faris, and M.ˇS. Gajdoˇsik, “Forecasting ozone concentrations in the east of Croatia using nonparametric neural network models,” Journal of Earth System Science, vol. 125, no. 5, pp. 997–1006, 2016.

2. A. Sheta, H. Faris, A. Rodan, E. Kovac-Andric, and A. Al-Zoubi, “Cycle reservoir with regular jumps for forecasting ozone concentrations: two real cases from the east of Croatia,” Air Quality Atmosphere and Health, March 2018.

3. M. Braik, A. F. Sheta, and H. Al-Hiary, “Hybrid neural network models for forecasting ozone and particulate matter concentrations in the Republic of China Hybrid neural network models for forecasting ozone and particulate matter concentrations in the republic of china,” Air Quality, Atmosphere & Health, vol. 13, pp. 839–851, 2020.