22- Application of aggregation operators for forecasting PM10 fluctuations : From available Caribbean data sites to unequipped ones [Plocoste et al (2024)]
Air pollution is a major issue for public health. Predicting levels of airborne particles, particularly those of natural origin like African sand mists, enables more effective warnings for affected populations. Currently, only three islands continuously measure PM10 concentrations in the Caribbean area. Thus, there is a significant issue in forecasting these particulate pollutants for unequipped […]
21- Multifractal detrended fluctuation analysis of rainfall time series in the Guadeloupe archipelago [Gómez-Gómez et al (2023)]
Due to the fragility of the Caribbean islands in the face of climate change, it is crucial to understand precipitation patterns. Additionally, the soils of the French Antilles islands have been contaminated by an organochlorine insecticide (Chlordane), which undergoes decontamination primarily through natural soil leaching. Therefore, it is essential to study the spatiotemporal variations of […]
20- Multiscale correlation analysis between wind direction and meteorological parameters in Guadeloupe archipelago [Plocoste and Sankaran (2023)]
In island contexts, waste management is a major problem due to the lack of space. Open dumps are often located in the heart of urban areas. In these places where there are many microclimates, it is crucial to better understand the fate of air pollutants from landfills. It is well known that meteorological parameters play […]
19- Study of the dynamical relationships between PM2.5 and PM10 in the Caribbean area using a multiscale framework [Plocoste et al (2023)]
Due to the high health impact of mineral dust in the Caribbean basin, it is important to know the relationship between particles less than or equal to 2.5 and 10 µm in diameter (PM2.5 and PM10). For the first time in the field of atmospheric pollution, a dynamic cross-correlation analysis was carried out between these […]
18- Forecasting PM10 Concentrations in the Caribbean Area Using Machine Learning Models [Plocoste and Laventure (2023)]
In the Caribbean basin, particles less than or equal to 10 µm in diameter (PM10) have a significant epidemiological impact due mainly to the transport of desert dust. For the first time in this geographical area, the theoretical framework of artificial intelligence has been applied to predict PM10 concentrations. Six machine learning models were therefore […]
17- Analysis of particulate matter (PM10) behavior in the Caribbean area using a coupled SARIMA-GARCH model [Esdra et al (2022)]
The periodic transport of sand mists over the Atlantic towards the arc of the Lesser Antilles is the major particulate pollution factor in the Caribbean area. Given the impact of desert dust on human health and the climate, it is necessary to model and predict the fluctuations in the concentrations of particles with a diameter […]
16- Quantifying spatio-temporal dynamics of African dust detection threshold for PM10 concentrations in the Caribbean area using multiscale decomposition [Plocoste et al (2022)]
The Caribbean basin is one of the regions on earth with a very high rate of asthma due to the presence of sand mists. Therefore, it is crucial to precisely quantify the presence of these hazes in the atmospheric boundary layer of this area. This article statistically and dynamically determines a new detection threshold for […]
15- Detecting the Causal Nexus between Particulate Matter (PM10) and Rainfall in the Caribbean Area [Plocoste (2022)]
Aerosol characteristics are key parameters that define cloud properties. This article analyzes the interactions between particles (PM10) and precipitation (RR) in the framework of entropy. Our results showed that there is a bidirectional causality between PM10 concentrations and RR values. This means that PM10 concentrations influence RR values while RR also acts on PM10. Rainfall […]
14- Multiscale analysis of the dynamic relationship between particulate matter (PM10) and meteorological parameters using CEEMDAN: A focus on ‘‘Godzilla’’ African dust event [Plocoste (2022)]
Sand mists have a strong impact on climatic conditions. This article analyzes the dynamic relationship between PM10 particles and meteorological parameters (solar radiation (𝑆𝑅), air temperature (𝑇), wind speed and direction (𝑈 and 𝐷), rainfall (𝑅), relative humidity (𝑅ℎ ) and visibility (𝑉)) using time-dependent intrinsic correlation (TDIC) analysis. TDIC analysis captured both negative and […]
13- Is there a causal relationship between Particulate Matter (PM10) and air Temperature data? An analysis based on the Liang–Kleeman information transfer theory [Plocoste and Calif (2021)]
This article presents the results of the study of the causal relationship between PM10 particles and atmospheric temperature (T) in the Caribbean basin using entropy methods. To our knowledge, this work is the first to analyze the causal relationship between these two parameters for different time scales. Our results proved that there is a bidirectional […]
