Application of the Use of Time Series Models: Tropospheric Nitrogen Dioxide (NO2) in Different Meteorological Systems in Two Districts of the City of Lima
Abstract
This research will address air pollution, a severe problem in all world cities, because it negatively affects people's health and deteriorates the ecosystem. NO2 is a gas linked to acid rain formation and various reactions with greenhouse gases. Meteorological variables influence the behavior of tropospheric NO2 concentration. During the period of confinement due to the COVID-19 pandemic, the concentration levels of pollutants dropped abruptly, which meant relief for the ecosystem. The application of Time Series models allows us to graphically identify the concentration of contaminants in various areas and make accurate forecasts to mitigate environmental problems in the future. The research analysis shows that the SARIMA model effectively forecasts the pollutant concentration in the San Borja and San Martin de Porres districts in Lima. Error tests such as R2, MAE, MAPE, MSE, and RSME, as well as Dickey-Fuller Test, AIC, BIC, Skew, and Kurtosis, provide information on the performance of the SARIMA model and show that it is the most suitable.
How to cite
Molina-Cueva, A. F., Cueva-Roldan, R. A., Garcia-Lopez, I J., & Quiroz-Flores, J. C. (2023). Application of the use of Time Series Models: Tropospheric Nitrogen Dioxide (NO2) in Different Meteorological Systems in Two Districts of the City of Lima. International Journal of Engineering Trends and Technology, 71(10), 1-10. https://doi.org/10.14445/22315381/IJETT-V71I10P201Publisher
Seventh Sense Research GroupResearch area / line
Recursos naturales y medio ambiente / Agua, suelo y aireJournal
International Journal of Engineering Trends and TechnologyISSN
2231–5381Collections
- Ingeniería Industrial [204]