Forecasting the concentration of NO2 using statistical and machine learning methods: A case study in the UAE.

ABSTRACT: Nitrogen dioxide (NO2) is the most active pollutant gas emitted in the industrial era and is highly correlated with human activities. Tracking NO2 emissions and predicting their concentrations represent important steps toward controlling pollution and setting rules to protect people's health indoors, such as in factories, and in outdoor environments. The concentration of NO2 was affected by the COVID-19 lockdown period and decreased because of restrictions on outdoor activities. In this study, the concentration of NO2 was predicted at 14 ground stations in the United Arab Emirates (UAE) during December 2020 based on training over a full time period of two years (2019-2020). Statistical and machine learning models, such as autoregressive integrated moving average (ARIMA), seasonal autoregre

SUBMITTER: Al Yammahi A 

PROVIDER: S-EPMC9922785 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature