Finding Trends of Airborne Harmful Pollutants by Using Recurrence Quantification Analysis

In this work, the use of Recurrence Plots and Recurrence Quantification Analysis explores the changes in the non-linear behavior of harmful airborne particle concentration in four sites around London simultaneously. This research has been carried out for 6 years, using large datasets of raw data (hourly) for harmful particles such as CO, SO2, NO2, NO and Particulate Matter (PMx). Recurrence analysis has been shown to be a useful tool in many disciplines to find trends, rates and predictions. Nevertheless, it has not been shown before the feasibility of using these algorithms to extract information for pollution monitoring and control. Also, observations are made with the results and conclusions drawn from these observations, showing the feasibility of this approach in finding trends of airborne pollution.