Mapping of Soil Properties Using Geographical Information System (GIS): A Case Study of Hassan Usman Katsina Polytechnic

GIS relates and integrates spatial data from various sources, for storage, retrieval, analyses and display. This paper presents the analysis and mapping of Geotechnical data using natural neighbour interpolation tool of GIS. The Campus of Hassan Usman Katsina Polytechnic Nigeria was as the study area, and Arc GIS 10.2.1 was used to perform the analyses. The study used soils samples from ten trial pit distributed within the study area and subjected to various laboratory tests. Index and engineering properties of the samples were determined. Map database developed in a GIS environment and the result of the laboratory tests stored, were analysed and displayed using GIS. The research results show maps of various soil properties. The research result provides estimated data for preliminary designing of engineering infrastructures in the area.

Lead Accumulation in Surface Soils and Components of Balenites Aegyptica Specie in a Katsina Urban Area, Nigeria

The main objective of this paper is to assess the impact of various vehicular traffic densities on lead (Pb) accumulations in some environmental components in Katsina, a semi-arid urban area of Nigeria. Methods This was achieved by collecting and analyzing samples of surface soils, fruits, kernels, leaves, and barks of Balenites aegyptica from locations of different vehicular traffic densities in the area, and analyzing them for lead, using atomic absorption spectrophotometry. Results The results obtained revealed that the Pb concentration in the high, medium, low, and zero traffic density areas are, 75, 53, 35, and 12 μg·g-1 respectively for the fruit pulp. They are also16, 13, 8, and 6 μg·g-1 for fruit kernel and 44, 28, 17, and 9μg·g-1 respectively for leaves. For tree barks, the values are 138, 97, 64, and 18 μg·g-1 respectively while for under-tree-canopy soil samples the mean values are 99, 74, 44, and 17 μg·g-1. In the case of outside-canopy soil samples, the mean values are 113, 91, 50, and 18 μg·g-1 respectively for the various classes of vehicular traffic density. Conclusion These results indicate a strong influence of vehicular traffic density on Pb emission into surrounding atmosphere and its subsequent precipitation on soil and components of B. aegyptica specie in the area. Of all the samples, tree bark should be the best index of assessing Pb pollution in the area, as it maintains the closest contact with the surrounding atmosphere. Since Pb has no known lower limit for human tolerance, there is an urgent need for Pb pollution control in the area to be effectively enforced.

Hydration Process and Crack Tendency of Concrete Based on Resistivity and Restrained Shrinkage Crack

Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were monitored by using a non-contact electrical resistivity apparatus, a novel plastic ring mould and penetration resistance methods, respectively. The results show the highest resistivity of C30 at the early stage until a point when C50 accelerated and overtook the others. It has been experimentally confirmed that the crossing point of C30 and C50 corresponds to the final setting time of C50. From resistivity derivative curve, four different stages were observed upon which the hydration process is classified; these are dissolution, induction, acceleration and deceleration periods. Consequently, restrained shrinkage crack and setting time results demonstrated that C50 set and cracked the earliest. The cracking time of all the samples occurred within a reasonable experimental period thus the novel plastic ring is a convenient method for predicting concrete＇s crack potential. The highest inflection time（t_i） obtained from resistivity curve and the final setting time（t_f） were used with crack time（t_c） in coming up with mathematical models for the prediction of concrete＇s cracking age for the range of concrete grade considered. Finally, an ANSYS numerical simulation supports the experimental findings in terms of the earliest crack age of C50 and the crack location.

Seasonal Variations of Aerosol Optical Properties and Identification of Different Aerosol Types Based on AERONET Data over Sub-Sahara West-Africa

The uncertainty in the quantification of aerosol properties such as concentration, size, and composition, spatially and temporally makes regional studies important. Therefore, this study presents seasonal variations of aerosol optical properties over Ilorin (8&#17632'N, 4&#17634'E), Nigeria. Long-term (1998-2013) records of aerosol optical depth (AOD) and angstrom exponent α, from ground-based Aerosol Robotic Network (AERONET) are used to study the seasonal variability, characteristics and types of aerosol. The study showed that seasonal variations (Harmattan and Summer) result in different aerosol concentration, characteristics, and types. The magnitude and sensitivity of AOD to wavelength are found low in Summer with significant increase during Saharan dust transport season (Harmattan). The average mean AODs are 0.73 ± 0.50, 0.97 ± 0.52 and 0.46 ± 0.29 with corresponding mean angstrom of 0.66 ± 0.36, 0.68 ± 0.34, and 0.64 ± 0.37 for the entire period, Harmattan and Summer seasons. High frequency of occurrence of angstrom exponent below 1 (78% and 81%) which were observed during Harmattan and Summer indicates that the particles are generally coarse in mode. The results revealed that for both Harmattan and Summer seasons, the dominant aerosol was dust (DA) with frequency of occurrence of 82% and 79%. However, mixed aerosol (MIXA) (14.4%) is the second dominant case during Harmattan while in Summer maritime aerosol (MA) (9.1%) associated with transport due to southwesterly trade wind is the second dominant aerosol. This conclusion is supported by size distribution data for the study site which showed that large volume of aerosol particle size are enclosed in largely coarse mode range in all seasons. A 7-day back trajectory seasonal frequency plot sourced from the Hysplit Single Particles Lagrangian Integrated Trajectory model (Hysplit_4 model) shows that dust are transported from the Sahara during north-easterly trade wind flow while the observed marine aerosols are conveyed by the southwesterly trade wind influences to the study site.

Improving Bearing Capacity of Weak Soils:A Review

Weak soils,such as soft clay and loose sand,have a poor bearing capaci­ty,making them incapable of bearing the load of superstructures that will be imposed on them.As a result,engineers must have a solution to the is­sue of poor bearing capacity in weak soils before embanking into building on them.This paper reviewed the use of stone columns,piled rafts,and geogrids for improving the bearing capability of weak soils.Important findings from recent research are also discussed.From the review of the previous researcher’s findings,it was found that modelling approaches such as physical modelling(full scale,centrifuge,laboratory scale)and numerical modelling are used to study bearing capacity improvement.

Monthly Temporal-Spatial Variability and Estimation of Absorbing Aerosol Index Using Ground-Based Meteorological Data in Nigeria

The objective of this work is to analyze the temporal and spatial variability of the monthly mean aerosol index (AI) obtained from the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) in comparison with the available ground observations in Nigeria during 1984-2013. It also aims at developing a regression model to allow the estimation of the values of AI in Nigeria based on the data from ground observations. TOMS and OMI data are considered and treated separately to provide continuity and consistency in the long-term data observations, together with the meteorological variable such as wind speed, visibility, air temperature and relative humidity that can be used to characterize the dust activity in Nigeria. The results revealed a strong seasonal pattern of the monthly distribution and variability of absorbing aerosols along a north to south gradient. The monthly mean AI showed higher values during the dry months (Harmattan) and lower values during the wet months (Summer) in all zones. From December to February, higher AI values are observed in the southern region, decreasing progressively towards the north, while during March-October, the opposite pattern is observed. The AI showed clear maximum values of 2.06, 1.93, and 1.87 (TOMS) and 2.32, 2.27 and 2.24 (OMI) in the month of January and minimum values in September over the north-central, southern and coastal zones, while showing maximum values of 1.76 (TOMS) and 2.10 (OMI) during March in the Sahel. New empirical algorithms for predicting missing AI data were proposed using TOMS data and multiple linear regression, and the model co-efficient was determined. The generated coefficients were applied to another dataset for cross-validation. The accuracy of the model was determined using the coefficient of determination R2 and the root mean square error (RMSE) calculated at the 95% confidence level. The AI values for the missing years were retrieved, plotted and compared with the measured monthly AI cycle. It is concluded that the meteorological variables can significantly explain the AI variability and can be used efficiently to predict the missing AI data.