Trend estimation and forecasting of atmospheric pollutants in the Mexico City Metropolitan Area through a non-parametric perspective

Abstract

Trends and forecasts of the main atmospheric pollutants (O₃, SO₂, NO₂, CO, PM₁₀, PM_2.5, NO and NO_x) are estimated by regions in the Mexico City Metropolitan Area (MCMA) with maximum daily data from 2008 to 2018. A non-parametric statistical smoothing controlled technique based on the Hodrick and Prescott filter and estimated through the Kalman filter, is used. Both point and interval estimates, as well as their respective forecasts are generated. Estimates are compared against the environmental standard for Mexico City (NADF-009-AIRE-2017), and it is evident that, in general, they are still distant from good air quality in the MCMA, as opposed to CO and NO₂. The remaining pollutants have trends and forecasts that are far from the permissible limits.