Report: Evolution of the PM2.5 concentration at Escuelas Aguirre after Madrid Central implementation

TL;DR

This study analyzes PM2.5 pollution levels at a Madrid monitoring station before and after Madrid Central's implementation, revealing potential increases in pollution due to traffic changes using statistical sign tests.

Contribution

It applies the Binomial Sign Test to evaluate the impact of Madrid Central on PM2.5 levels, accounting for wind effects, providing a novel statistical approach for pollution impact assessment.

Findings

No significant reduction in PM2.5 levels post-implementation

Increased traffic may have led to higher pollution levels

Wind intensity analysis helps distinguish pollution changes due to traffic

Abstract

In this report, the evolution of PM2.5 concentration at Escuelas Aguirre monitoring station during the quarters of 2019 and the significance of the differences with the concentration of the quarters of previous years is analysed. These periods include the activation of Madrid Central, which is a major initiative for reducing motor traffic and the associated pollution at the city centre. These periods correspond to the initialisation of, 2019Q1; and to tree fully-operational quarters of Madrid Central, 2019Q2, 2019Q3 and 2019Q4. Escuelas Aguirre monitoring station is not inside Madrid Central but 2 km away. The analysis of the PM2.5 concentration at this station allows discerning the rise of negative effects due to an increment of the motor traffic around the traffic restricted area. The analysis is based on the Binomial Sign Test for a Single Sample. The sample of signs is generated by subtracting the daily mean concentration of PM2.5 for the measurements of the period of two years: 20xx and 2019. Samples for the pair-wise comparisons for the year 2019 versus the years of the periods from 2010 to 2018 are evaluated. An excess of positive or negative sign indicates that the differences between the measurements of concentrations in the comparison of two years are significant. Conversely, a balanced number of positive and negative signs points to no impact of the action. Since wind is an efficient pollution remover, the Binomial Sign Test is also applied to its intensity in the two-periods comparison. This allows discerning if the pollution reduction could be associated to a larger number of windy days in the 2019 quarter under comparison.