Is there a causal relationship between Particulate Matter (PM10) and air Temperature data? An analysis based on the Liang-Kleeman information transfer theory

In the literature, it is well known that mineral dust play a key role in the atmospheric radiation budget. How to identify the cause-effect relationship between mineral dust and climatic parameters remains a crucial issue in atmospheric science and environment. In this study, the causal relation between particulate matter that have an aerodynamic diameter less than 10 mu m diameter (PM10) and air Temperature (T) is investigated for different time scales. For this purpose, two normalization schemes based on San Liang (2014)'s information flow formula and the classical convergent cross mapping introduced by Sugihara et al. (2012) were applied to eleven years of daily time series recorded in Guadeloupe archipelago. Both methods showed there is a bidirectional causality between the studied parameters. Indeed, we noticed that PM10 concentrations tend to stabilize T values. This phenomenon has been attributed to a greenhouse effect which is strongly linked to African dust seasonality. During the high dust season, this effect is 13.2 times greater than in the low season. On the other hand, we found that T values tend to make PM10 concentrations more uncertain in the low dust season while they homogenize PM10 fluctuations in the high season. All these behaviors could be assigned to the impact of T values on PM10 dry deposition velocity. To conclude, our results showed that information flow approach is an efficient tool to extract the cause-effect relationship between two dynamical events in atmospheric science, i.e. a field where several parameters interact simultaneously.

Automated summary

The study investigates the causal relationship between PM10 and air temperature, finding a bidirectional causality between the two parameters. PM10 concentrations tend to stabilize air temperature values, while air temperature values influence PM10 concentrations differently in high and low dust seasons.