Recurrent challenges of the theoretical estimation of aerosol optical thickness (AOT) are traceable to bogus assumption in its mathematical model. The objective of this paper is to propound a model that could describe the aerosol distribution sizes per time. The physics of the salient properties of aerosol within the Stokes regime was discussed. The mathematical model was applied to six locations within 335 ˟ 230 Km2 area of a selected portion of south-west, Nigeria. Though the climatic change is evident via thirteen years ground data set assimilation, the sensitivity of the proposed model was proven to increase by 0.1%. The research affirmed the use of some parameters (e.g. minimum temperature, cloud cover, relative humidity and rainfall) to estimate aerosol optical thickness and by extension the aerosol distribution size over an area.

/pdf/aerosol-optical-depth-trends-over-different-regions-of-1j6w216gs3.pdf

Aerosol Optical Depth Trends over Different Regions of Nigeria: Thirteen Years Analysis

Formation, dispersion and accumulation of terra rossa on the Cayman Islands

This current study was conducted on rainfall and air temperature data obtained from the archive of the HelioClim website to determine the relationship between the two parameters. The study aimed at the relationship between rainfall and air temperature. The data of thirty-four (34) years spanning from 1985 to 2019 was analyzed using Mann-Kendal statistics on the trend of the rainfall series while the normality of rainfall series was determined using Kolmogorov- Smirnov test across six southwest stations of Nigeria. The results revealed the highest mean rainfall in Akure (198.9 mm) while the least rainfall in Ado-Ekiti (163.4 mm). The maximum rainfall was in Abeokuta (865.8 mm) with Iwo having the highest disparity in rainfall (SD=148.8 mm) compared with other stations. The skewness in Abeokuta (Skewness = 0.9 mm) was higher compared with Ado-Ekiti, Akure, Ibadan, Ikeja and Iwo with skewness values of 0.7 mm, 0.4 mm, 0.7 mm, 0.6 mm and 0.7 mm, respectively. The maximum air temperature was recorded in Iwo (301.7 K) and the minimum air temperature in Ado-Ekiti (293.3 K). The skewness obtained in Akure (-0.2) and Ikeja (-0.3) was less than zero indicating that air temperature decreased more than it increased in these areas while in other stations, Abeokuta (0.01), Ado-Ekiti (0.22), Ibadan (0.02) and Iwo (0.24), the skewness was greater than zero meaning that air temperature increased more than it decreased in these stations.

/pdf/relationship-between-air-temperature-and-rainfall-3e1sw63y.pdf

Relationship between Air Temperature and Rainfall Variability of Selected Stations in Sub-Sahara Africa

Harmattan dust and traffic-related pollution have been a serious environmental concern in the West African sub-region. In order to further contribute to the understanding of ambient levels of atmospheric pollution and chemical composition in the region, this study monitored harmattan dust and traffic-related particulate matter at four locations across southwestern (Ile-Ife) and north-western (Zaria) geo-political zones of Nigeria. The collected samples were characterized for their chemical composition using Energy-Dispersive X-Ray Fluorescence spectrometer equipped with an optimized secondary target x-ray excitation conditions (Al, CaF2, Fe, Ge, Zr, Mo, Ag, Al2O3). The objectives are to assess spatio-temporal mass concentrations, chemical footprints, enrichment factors, elemental correlations, and ratios at all locations. The X-ray analytical method was validated with a NIST SRM 2783 air particulate standard, and detection limits for each chemical specie were determined. Validation results showed good reproducibility of the certified reference material with relative standard deviations of the elements much lower by about 1–13% than the corresponding reference values. Mass concentrations reached up to 2200 μgm−3 in the north and 1500 μgm−3 in the south. The range of mean concentration of crustal marker elements were Al (5–27 μgm−3), Si (5–856 μgm−3), Ca (0.78–13 μgm−3), and Fe (2–13 μgm−3), and were most abundant during the harmattan particularly in the southwestern region. Highest mean concentration values of 380, 810, and 420 ngm−3 were recorded for Cr, Cu, and Pb respectively at the traffic corridor which also recorded the highest enrichment factors. Black carbon and elemental concentrations contributed between 1 to 54% and 9 to 94% across the locations respectively. Backward trajectories of atmospheric flow over the locations showed two dominant sources; dust laden source from the Sahara desert and maritime flow over the Gulf of Guinea. This study found that chemical footprints (Al, Si, K, Ca, Ti, and Fe) of harmattan-related dust were more correlated (r2 between 0.88 and 0.99) than those attributed to dust re-suspension at the traffic location.

Chemical footprints of harmattan dust and traffic corridor particulates monitored at two environmentally distinct geopolitical zones in Nigeria

Since the coronavirus pandemic started, many people have died due to the disease. The epidemic has been challenging to predict, as it progresses and spreads throughout the world. We used Auto-Regressive Integrated Moving Average (ARIMA) models to predict the outbreak of COVID-19 in the upcoming months in Morocco. In this work, we measured the effective reproduction number using the real data and the forecasted data produced by the two commonly used approaches, to reveal how effective the measures taken by the Moroccan government have been in controlling the COVID-19 outbreak. The prediction results for the next few months show a strong evolution in the number of confirmed and death cases in Morocco. We study the spread of COVID-19 in Morocco to see how many cases are discovered, recovered, and dead, and the forecasting of further cases is used as a basic novel method. It is based on time series models. We used coronavirus outbreak data from March 02, 2020, to August 04, 2021. ARIMA (Autoregressive integrated moving average) and Prophet time-series models are used to forecast the development of COVID-19, which is not a novel method. The mean absolute error, root mean square error, and coefficient of determination R2 were computed to assess the model's performance. Our study aims to provide a better understanding of the infectious disease outbreak that affected Morocco. It also provides information on the disease outbreak's epidemiology. Our study shows that the FBProphet model is more accurate in predicting the prevalence of COVID-19. It can help guide the government's efforts to prevent the virus' spread.

/pdf/forecasting-of-the-epidemiological-situation-case-of-covid-29m0429z.pdf

Forecasting of the epidemiological situation: Case of COVID-19 in Morocco

Mineralogical study was carried out on harmattan dust samples collected over Ilorin (8° 32' N, 4° 34' E) sub-Sahara region of West Africa. Minerals such as quartz [SiO 2 ] (76.5%), gibbsite [Al(OH) 3 ] (7.1%), rutile [TiO2 ](5.8%), goethite [Fe 2 O 3 .H 2 O] (4.6%), halloysite [Al 4 Si 4 O 10 (OH) 8 ·8H 2 O] (3.9%) and kaolinite [Al 4 Si 4 O 10 (OH) 8 ](2.1%) were detected. Quartz, halloysite, microcline and mica were similarly identified in harmattan dust sampled at Ile-Ife. However, gibbsite, rutile, goethite which were identified at Ilorin were not detected at Ile-Ife, while microcline and mica detected in Ile-Ife were not observed at Ilorin. The mineralogical composition of the harmattan dust at a locality is most probably determined by the source and the distance from the source of the harmattan dust. Keywords: Bodele Depression, Harmattan Dust, Mineralogy, Ilorin.

/pdf/mineralogical-characteristics-of-harmattan-dust-in-ilorin-53i97cdp3n.pdf

Mineralogical characteristics of harmattan dust in Ilorin, Sub-sahara africa

The study and forecast of climatic phenomena have progressed over time, but the huge knowledge with information gathered has aided in comprehending and anticipating weather changes. The goal of this research was to look at some specific meteorological characteristics and forecast air temperature over a number of stations in Osun State, Nigeria. Monthly rainfall, relative humidity, air temperature, air pressure, wind speed and direction for four stations were gathered from the HelioClim website archives and used in this study. For each variable, descriptive statistics were calculated. The normality of the data was determined using the Shapiro-Wilks test. The data was tested for stationarity using the Augmented Dickey Fuller (ADF) test, and different types of Autoregressive Integrated Moving Average (ARIMA) models were fitted. According to the statistics, the highest average temperature was observed in March (𝑇=23.90𝐶). The months of June, July, August, and September had the highest mean relative humidity (𝑅𝐻=88.4%), pressure (𝑃=987ℎ𝑃𝑎), wind speed (𝑊𝑆=1.8𝑚/𝑠), wind direction (𝑊𝐷=225.10), and rainfall (𝑅𝐹=413𝑚𝑚). In January, the coefficient of variation (COV) for temperature was larger than in other months. In June, January, and December, relative humidity (RH), air pressure, rainfall, and wind speed and direction were all higher. The air temperature stationarity was tested using the Augmented Dickey Fuller (ADF) test, which revealed (p>0.05) but became stationary after the first difference (p<0.05). The temperature effect follows the same trend in ARIMA (1, 1, 1) forecasts for 2021 and 2022. As a result, air temperature modeling and forecasting are difficult tasks for any monthly time series. It is advised that all-time series models for any investigated location be considered, as well as meteorological conditions, in order to select the most appropriate model.

Meteorological parameters study and temperature forecasting in selected stations in Sub-Sahara Africa using MERRA-2 data

Trace metals and mineralogical composition of harmattan dust haze was carried out on samples collected at Ilorin (80 32'N, 40 34'E) a guinea  Savanna African City located at the central state of Nigeria. These dusts were gathered at different locations using clean Petri-dishes and plastic bowls of 10cm in diameter. These were analyzed using X-ray Florescence (XRF) and Particle Induce X-ray Emission (PIXE) machine. The average concentration of the metals was (13351.75±45) mg/kg and minerals  (7.22%).The mean soil content of the total size of particles for the harmattan season for the station was calculated to be1.79765 μg/m. In conclusion, it was observed that harmattan dusts that blow across Nigeria predominantly comprise quartz and high elements.Keywords: Harmattan, Ilorin, X-ray Fluorescence and Particle Induce X-ray Emission

/pdf/trace-metals-and-mineral-composition-of-harmattan-dust-haze-4lz2obp86d.pdf

Trace metals and mineral composition of harmattan dust haze in Ilorin City, Kwara State, Nigeria

Radio refractivity is very crucial in the optimal performance of radio systems and is one of the attributes that affect electromagnetic waves in the troposphere. This study presented a comparison of different variants of recurrent neural networks to predict radio refractivity index. The radio refractivity index is predicted based on forty-one years (1980 to 2020) metrological data obtained from the MERRA-2 data re-analysis database. The refractivity index was computed using International Telecommunication Union (ITU) standard. The correlation refractivity index was categorized into strong, weak and no correlation. Rainfall, relative humidity, and air pressure fall in the first category, the temperature falls in the second category while wind speed falls in the last one. The true future and predicted values of the radio refractivity index are close with GRU performing better than the other two models (LSTM and BiLSTM) which proves the accuracy of the proposed model. In conclusion, the proposed model can establish a radio refractivity status of locations at different times of the season, which is of great importance in the effective design, development, and deployment of radio communication systems.

/pdf/refractive-index-perception-and-prediction-of-radio-wave-tt6qs4kx.pdf

Refractive Index Perception and Prediction of Radio wave through Recursive Neural Networks using Meteorological Data Parameters

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