Environmental Policies and Strategies in Nigeria Oil and Gas Industry: Gains, Challenges and Prospects

The paper reviews environmental policies and strategies in the Nigerian oil and gas industry sector, assessing its efficiency, challenges and prospects. Essentially, the study established that the Environmental Policies and Strategies of Nigeria Oil and Gas Industry have impacted positively on the Nigerian environment over the years, especially in the area of awareness creation for all stake-holders. In terms of challenges, inefficiency of the regulators due to inadequacy of logistics, poor environmental data base, duplication and overlaps of regulators functions are some of the challenges identified. The prospect of environmental policies and strategies in Nigeria is generally considered to be bright, considering the fact that the industry is still evolving. Relevant recommendations were made on how to achieve improvements.

Environmental Degradation Resulting from Oil Exploitation, and Population Displacement in the NigerDelta, Nigeria

Oil and gas exploration in the Niger Delta region of Nigeria began some fifty four （54） years ago. Since the early sixties till now, oil from this region of the Nigeria has been the major foreign exchange earner for the sustenance of the economy. Unfortunate to note is the fact that since oil exploration and exploitation began in the country in the Niger Delta, the region had not been at peace. The region had suffered all forms of environmental degradation resulting from crude oil spillage and gas flares. The peoples＇ source of livelihood has been destabilized thereby leading to high rate of poverty, social crises/conflict and involuntary migration of people for both security and succour. The people of the region are thus in severe pains and risk of extermination should the present trend of environmental degradation and negligence persist. Thus, this paper addresses the plight of the Niger Delta as a case study of the effect of environmental degradation on human vulnerability. It is believed that continuous existence of the Niger Delta people as a social sect is dependent on how prompt efforts are made to combat the environment nuisance in the region.

Hydrological Modeling of Aquifers and Their Ground Water Potentials: Implications for Water Resources Planning and Management in Parts of Obio/Akpor L.G.A, Rivers State, Nigeria

This study examined the hydrological modeling of aquifers and their ground water potentials for the purposes of water resources planning and management. This was done using the electrical resistivity method employing the schlumberger electrode configuration at randomly selected stations to obtain the thicknesses and resistivities of each layer and depth to the presumably conglomeratic sand stone and its resistivity. Findings showed that the top soil layer resistivity values vary from 59.3 to 248.4 ohm-m and thickness of 0.6 to 3.9 m. The second layer has resistivity values ranging from 45.0 to 743.5 ohm-m and a thickness range of 1.5 to 13.8 m. The wet sand is characterized by resistivity values ranging from 144.8 to 1930.2 ohm-m and a thickness range of 3.8 to 65.8 m. The conglomeratic sand/sand stone has resistivity values ranging from 55.8 to 7719.8 ohm-m. The depth to this bottom layer varies from 6.6 to 89.5 m. Findings indicate that the entire profile is a sedimentary formation represented by lithological units of sand and clayey sand which make for a good groundwater potentials. However, the groundwater potential zones of the study area in terms of transmisivity revealed four distinct classes representing “very good” (Mgbuosimini, Rumuigbo, Okporo, Rumuomasi and Rumuodara), “good” (Alakahia, Rumuodomaya, Oginigba and Rumuola), “moderate” (Aluu, Rumuekeni, Rumuokoro, Rumuobiakani and Rumueme), and “low” (Ogbogoro, Ozuoba, Akpajio, Elelenwo, Eliozu, Rumuepirikon, Rumuokwuta, Rumuebekwe and Rumurolu) groundwater potential in the area. Well logging should therefore be incorporated in borehole development process for safe and sustainable yield of groundwater in Obio/Akpor.

Multiclass stand-alone and ensemble machine learning algorithms utilised to classify soils based on their physico-chemical characteristics

This study has provided an approach to classify soil using machine learning.Multiclass elements of stand-alone machine learning algorithms(i.e.logistic regression(LR)and artificial neural network(ANN)),decision tree ensembles(i.e.decision forest(DF)and decision jungle(DJ)),and meta-ensemble models(i.e.stacking ensemble(SE)and voting ensemble(VE))were used to classify soils based on their intrinsic physico-chemical properties.Also,the multiclass prediction was carried out across multiple cross-validation(CV)methods,i.e.train validation split(TVS),k-fold cross-validation(KFCV),and Monte Carlo cross-validation(MCCV).Results indicated that the soils’clay fraction(CF)had the most influence on the multiclass prediction of natural soils’plasticity while specific surface and carbonate content(CC)possessed the least within the nature of the dataset used in this study.Stand-alone machine learning models(LR and ANN)produced relatively less accurate predictive performance(accuracy of 0.45,average precision of 0.5,and average recall of 0.44)compared to tree-based models(accuracy of 0.68,average precision of 0.71,and recall rate of 0.68),while the meta-ensembles(SE and VE)outperformed(accuracy of 0.75,average precision of 0.74,and average recall rate of 0.72)all the models utilised for multiclass classification.Sensitivity analysis of the meta-ensembles proved their capacities to discriminate between soil classes across the methods of CV considered.Machine learning training and validation using MCCV and KFCV methods enabled better prediction while also ensuring that the dataset was not overfitted by the machine learning models.Further confirmation of this phenomenon was depicted by the continuous rise of the cumulative lift curve(LC)of the best performing models when using the MCCV technique.Overall,this study demonstrated that soil’s physico-chemical properties do have a direct influence on plastic behaviour and,therefore,can be relied upon to classify soils.

The role of land use on the local climate and air quality during calm inter-monsoon in a tropical city

The modification of land use is known to be a major climate change driver to the local warming and air quality in cities. Despite the reduction of NOx over the years, the Selangor state has captured a higher level of O_3 in year 2011. The measurement result has shown that the surge in O_3 level was attributed to the reduction of NO_x/NMHC ratio. This paper hence attempted to identify the role of land use change from 1999 to 2011 on the ground ozone air quality in the tropical urban conurbation, Greater Kuala Lumpur(GKL), Selangor, Malaysia. With the state-of-the-art chemical weather prediction tool, WRFChem, the external synoptic factors and emission inventory were controlled when comparing the chronological land use changes. The results showed that the urban-induced temperature and wind bias in the tropical region has induced stronger wind to disperse the NO_x and carries the TVOC from the suburban to the downwind urban region. The reduction of NO_x/TVOC has gradually shifted towards the optimum O_3 formation regime in 2011. The formation of highly concentrated ozone becomes more sensitive to the increment of TVOC as the NO_x level reduces in the urban. This highlights the essential involvement of TVOC in the ozone formation in lieu of the NOx reduction in the tropical city, a region with growing emitter of reactive biogenic ozone precursors.

Improved prediction of clay soil expansion using machine learning algorithms and meta-heuristic dichotomous ensemble classifiers

Soil swelling-related disaster is considered as one of the most devastating geo-hazards in modern history.Hence,proper determination of a soil’s ability to expand is very vital for achieving a secure and safe ground for infrastructures.Accordingly,this study has provided a novel and intelligent approach that enables an improved estimation of swelling by using kernelised machines(Bayesian linear regression(BLR)&bayes point machine(BPM)support vector machine(SVM)and deep-support vector machine(D-SVM));(multiple linear regressor(REG),logistic regressor(LR)and artificial neural network(ANN)),tree-based algorithms such as decision forest(RDF)&boosted trees(BDT).Also,and for the first time,meta-heuristic classifiers incorporating the techniques of voting(VE)and stacking(SE)were utilised.Different independent scenarios of explanatory features’combination that influence soil behaviour in swelling were investigated.Preliminary results indicated BLR as possessing the highest amount of deviation from the predictor variable(the actual swell-strain).REG and BLR performed slightly better than ANN while the meta-heuristic learners(VE and SE)produced the best overall performance(greatest R2 value of 0.94 and RMSE of 0.06%exhibited by VE).CEC,plasticity index and moisture content were the features considered to have the highest level of importance.Kernelized binary classifiers(SVM,D-SVM and BPM)gave better accuracy(average accuracy and recall rate of 0.93 and 0.60)compared to ANN,LR and RDF.Sensitivity-driven diagnostic test indicated that the meta-heuristic models’best performance occurred when ML training was conducted using k-fold validation technique.Finally,it is recommended that the concepts developed herein be deployed during the preliminary phases of a geotechnical or geological site characterisation by using the best performing meta-heuristic models via their background coding resource.

GIS-based spatial prediction of landslide using road factors and random forest for Sichuan-Tibet Highway

Accurate evaluation of landslide susceptibility is very important to ensure the safe operation of mountain highways.The Sichuan-Tibet Highway,which traverses the east of the Tibetan Plateau,frequently encounters natural hazards.Previous studies generally use statistical methods to analyze the hazards along the Sichuan-Tibet Highway.In this research,we present two road factors,namely aspect to road and road profile to increase the accuracy of landslide susceptibility mapping by considering the influence of landslide movement direction on road.First,the aspect to road,which represents the impact of different landslide movement directions on the highway,was extracted by combining road direction with mountain aspect.Then,the road profile,which reflects the subgrade structure between the road and surrounding mountains,was extracted according to the terrain data.Finally,the landslide susceptibility maps were produced based on the random forest(RF)method by using 473 landslides and 10 conditioning factors,including road factors(aspect to road,road profile)and primitive factors(slope,aspect,curvature,relief amplitude,peak ground acceleration,crustal movement velocity,faults,rainfall).The area under the receiver operating characteristic curve(AUC)and the Gini importance were used to evaluate the performance of proposed road factors.The AUC values on two groups that add road factors and only use primitive factors were 0.8517 and 0.8243,respectively.The Gini importance indicated that road profile(0.123)and aspect to road(0.116)have a significant contribution to landslides compared with the primitive factors.The results of multi-collinearity analysis and frequency ratio confirmed the suitability of the road factors for predicting hazards along the highway.

Spatial-temporal characteristics and influencing factors of relative humidity in arid region of Northwest China during 1966–2017

Playing an important role in global warming and plant growth,relative humidity(RH)has profound impacts on production and living,and can be used as an integrated indicator for evaluating the wet-dry conditions in the arid and semi-arid area.However,information on the spatial-temporal variation and the influencing factors of RH in these regions is still limited.This study attempted to use daily meteorological data during 1966–2017 to reveal the spatial-temporal characteristics of RH in the arid region of Northwest China through rotated empirical orthogonal function and statistical analysis method,and the path analysis was used to clarify the impact of temperature(T),precipitation(P),actual evapotranspiration(ETa),wind speed(W)and sunshine duration(S)on RH.The results demonstrated that climatic conditions in North Xinjiang(NXJ)was more humid than those in Hexi Corridor(HXC)and South Xinjiang(SXJ).RH had a less significant downtrend in NXJ than that in HXC,but an increasingly rising trend was observed in SXJ during the last five decades,implying that HXC and NXJ were under the process of droughts,while SXJ was getting wetter.There was a turning point for the trend of RH in Xinjiang,which occurred in 2000.Path analysis indicated that RH was negatively correlated to T,ETa,W and S,but it increased with increase of P.S,T and W had the greatest direct effects on RH in HXC,NXJ and SXJ,respectively.ETa was the factor which had the greatest indirect effect on RH in HXC and NXJ,while T was the dominant factor in SXJ.

The Effects of Road and Other Pavement Materials on Urban Heat Island (A Case Study of Port Harcourt City)

Urban centers are consistently exhibiting higher temperature than its surrounding suburban rural areas. The large amount of heat generated from urban structures such as road materials and pavement materials and other anthropogenic heat sources are the main causes of Urban Heat Island (UHI). The sources of data for this research included primary and secondary sources. Other techniques employed for data collection were direct measurement and readings on the road and pavement materials. The research found out that, there was consistency in rising temperature at different time of the day by the different road and pavement materials. Asphalt has the greatest effect of increasing the urban temperature four degrees higher, followed by concrete, three degree rise in temperature, and earth (ordinary ground) by two degree rise and vegetation (grass) by one degree rise in temperature. The overall effect on the residents of the study area ranges from increase in hotness of the day;44.6% respondents agrees;while 34.3% says it affects the ambient air quality of the area, and other effects such as increased ground level ozone, suffocation, sleeplessness and restlessness as a result of excessive high temperature especially at night are identified in this paper. The research recommends the review or redesigning of the entire Port Harcourt city Master Plan to make provision for creation of more green areas rather than pavements and concreted areas to reduce the effects of (UHI) and ultimately improve the comfort and living conditions of the people in a the garden city Port Harcourt.

Climate and Epidemiology of Malaria in Port Harcourt Region, Nigeria

The study examines the effect of climate on the occurrence of malaria in Port Harcourt. To achieve this, the study adopted the survey designs which involved the use of archival data of climate parameters and the survey of hospitals for epidemiological data of malaria cases reports within Port Harcourt and environs. The archival weather data on temperature and rainfall were collected from the Nigeria Meteorological Service Agency (NIMET) for a period of sixty-five (65) years (1950-2014), and those for medical records of malaria cases were extracted from the University of Port Harcourt Teaching Hospitals (UPTH), Braithwaite Memorial Hospital (BMH) and some renowned private hospitals in Port Harcourt and environs for a period of sixty-five (65) years. The multiple regression analysis was used to determine the relative effect of rainfall and temperature on malaria incidence. The polynomial and linear trend analysis was used for the trend pattern of malaria cases, rainfall and temperature. The results revealed an annual rainfall of 2375 mm, with an increase of 1581 mm of rainfall from 1950 till date. It also showed an urban warming of 3°C from 1950 to 2014, and a mean of 27.2°C in temperature in Port Harcourt. The results of the multiple regression reveal that the prevalence of malaria is significantly dependent on the increase in rainfall and temperature in Port Harcourt. There are double maxima of malaria cases with 1006 cases in July and 1540 cases in September, which coincide with the months with double rain maxima. On this premise and health care planning and development, it is recommended that regular clearing of drains and the surrounding environment on monthly basis should be intensified, as well as the distribution of mosquito’s insecticide net by the three tier of government.

Assessing the Impact of Climate Change on Maize (<i>Zea mays</i>) and Cassava (<i>Manihot esculenta</i>) Yields in Rivers State, Nigeria

Globally climate change has threatened agriculture and food security which is of great importance to the economy of a nation. In Nigeria it has become a great concern to the government and people because of the obvious changes in the climate systems, therefore, assessing the impact of climate change on crop yield in an oil producing state is of great importance especially where rain fed agriculture is the main determinant for crop yield. Expost-facto research method in the context of quasi experimental research design was adopted for the study. Data for rainfall and temperature and that for crop yields were obtained from Nigerian Meteorological Agency (NIMET) and federal ministry of Agriculture;Agricultural Development Program (ADP) respectively. Analysis of data was achieved using descriptive statistics, trend graphs and multiple linear regressions. Results showed that there had been a steady but gradual increase in the annual minimum, maximum and mean temperatures over the study period of thirty years and a decrease in rainfall. Mean temperature is increasing annually at the rate of 0.0253 per annum and rainfall is decreasing at the rate of -0.5817 mm per annum. The multiple regression model showed r2 values of 0.28 for maize and 0.29 for cassava revealing that only 28% - 29% of maize and cassava yields could be explained by rainfall and temperature in the state and the result was significant at p < 0.05 revealing that cassava and maize yields significantly depended on rainfall and temperature. This study strongly advocates for a better and practicable environmental policies and improved agricultural techniques alternative source of water which will include irrigation farming, mulching since it is evident that there is a reduction in rainfall and increase in temperature in the state while creating sustainable food security.

Spatiotemporal Characteristics of Wetlands Ecosystem in the Niger Delta Region

Wetlands are classified as essential and valuable components of the ecosystem. Wetlands are significant for ecosystem services such as nutrient cycles, soil formation and water treatment. Nearly half of the world’s wetlands have vanished in the last century because of anthropogenic activities, agricultural land use, and urban development, one of such places that are faced with the challenges of sustainability is the wetland habitats. This study aimed at assessing the spatial temporal characteristics of wetlands ecosystem in the Niger Delta Region of Nigeria from 1986-2016. The secondary data include raw satellite imageries obtained from the archive of the United States Geological Survey and Earth Explorer. The data set includes a notable period of four years landsat images for, 1986, 1996, 2006 and 2016. The maps were projected using Universal Transverse Mercator (UTM) projection system and datum WGS 84 of zone 32. Satellite images of the study area were acquired from the United States Geological Survey (USGS). The USGS uses the LandSat5 Thematic Mapper (TM) Landsat7 Thematic Mapper, Enhanced Thematic Mapper (ETM+), Thermal Infrared Sensor (TIRS) and Landsa8 Operational Land Imager (OLI) to generate high resolution images that are useful for this type of study. The satellite imageries were also analyzed using GIS and Remote Sensing techniques by computing of Normalized Differential Vegetation Index (NDVI) values for the entire study area by conversion of spectral reflectance values into NDVI values. The satellite images covering the area were acquired and analyzed using ArcGIS10.6. A total area of 25,053.93 (km2) was delineated in the study area. After processing the imagery, five land use/land cover (LULC) classes were developed in ArcGIS environment, such as Built-up area, Fallow land, Vegetation, Wetland and Waterbody. This study concludes that changes in wetland landscape patterns will produce profound impacts in urban areas where there are rapid anthropogenic activities. Anova table showed a huge significant relationship between time and vegetation decrease across the study area at 0.027 which is less than 0.05 significance level. Wetlands warming and drying will cause the shrinking and reduction of wetland in sizes from accelerated wetland degradation. Therefore, there is an interaction and mutual influence between dynamic changes of wetland landscape patterns and other land use classes.

Hydrogeochemical and Multivariate Statistical Techniques to Trace the Sources of Ground Water Contaminants and Affecting Factors of Groundwater Pollution in an Oil and Gas Producing Wetland in Rivers State, Nigeria

Background: Groundwater is an important source of drinking water for the indigenous communities of Ebocha-Obrikom. Access to safe drinking water, in particular, is critical to one’s health and, by extension, one’s income and well-being. Underground wells are the primary supply of drinking water in the Niger Delta, and the groundwater is not always treated before consumption. As a result, water continues to be a vital environmental component that affects both humans and other life forms. Objectives: The aims of the research are to trace the sources and affecting factors of groundwater pollution via statistical and multivariate statistical techniques. Method: The investigation made use of standard analytical procedures. All sampling, conservation, transportation and analysis followed standard procedures described in APHA (2012). To prevent degradation of the organic substances, all obtained samples were transferred to the laboratory, while kept in an icebox. Results: The study reveals that the greater the number of principal components extracted the greater variation in geochemical composition of the ground waters. It indicated that 34 parameters were distributed into six (6) and nine (9) principal components (PCs) extracted for groundwater samples for both rainy and dry seasons, potentially suggesting the input of different pollutants from different sources. Gas flaring, mineral dissolution/precipitation and anthropogenic input are the main sources of the physicochemical indices and trace elements in the groundwater. Groundwater chemistry is predominantly regulated by natural processes such as dissolution of carbonates, silicates, and evaporates and soil leaching, followed by human activities. Climatic factors and land use types are also important in affecting groundwater chemistry. Conclusion: Greater efforts should be made to safeguard groundwater, which is hampered by geogenic and anthropogenic activities, in order to achieve sustainable groundwater development. As a result, communities are recommended to maintain a groundwater management policy to ensure long-term sustainability. The study is useful for understanding groundwater trace sources in Rivers State’s Ebocha-Obrikom districts. Such understanding would enable informed mitigation or eradication of the possible detri-mental health consequences of this groundwater, whether through its use as drinking water or indirectly through consumption of groundwater-irrigated crops. As a result, determining its primary probable source of pollution (MPSP) is critical since it provides a clearer and more immediate interpretation. Furthermore, the research findings can be used as a reference for groundwater pollution prevention and water resource protection in the Niger Delta region of Nigeria.

Impact of Crude Oil Storage Tank Emissions and Gas Flaring on Air/Rainwater Quality and Weather Conditions in Bonny Industrial Island, Nigeria

This study investigated the effects of gaseous emissions from crude storage tank and gas flaring on air and rainwater quality in Bonny Industrial Island. Ambient air quality parameters, rainwater and weather parameters were collected at 60 m, 80 m, 100 m, 200 m and control plot for 4 weeks at the Bonny. Rainwater parameters were investigated using standard laboratory tests. Data analyses were done using Analysis of variance, pairwise t-test and Pearson’s correlation statistical tools. Results show that emission rates, volatile organic compound (VOC) noise and flare temperature decreased with increasing distance from flare points and crude oil storage tanks. Findings further revealed the emission rates varied significantly with distance away from the gas flaring point (F = 6.196;p = 0.004). The mean concentration of pollutants between gas flare site and crude oil storage tank showed that CO (0.02 ± 0.001 - 0.002 ±0.001), SPM (0.011 ± 0.001 - 0.01 ± 0.001), VOC (0.005 ± 0.001 - 0.01 ± 0.001) and NO2 (0.04 ± 0.001 - 0.005 ± 0.000) had significant variations (p > 0.05) with CO, O3 and NO2 having higher concentrations at the gas flare site while SPM, and VOC were higher around the crude oil storage tank site. Wind turbulence was higher around the gas flaring point (4.93 TKE) than the crude oil storage tank (4.55 TKE). Similarly, there was significant variation in the sun radiation, precipitation, and wind speed caused by gas flaring (1582.25 w/m2, 436.25 mm, 0.53 m/s) and crude oil storage tank (1536.25 w/m2, 3.91.41 mm, 0.51 m/s). There were also significant variations in flared temperature (F = 22.144;p = 0.001);NO2 (F = 8.250;p = 0.001), CO (F = 6.000;p = 0.004) and VOC (F = 5.574;p = 0.006) with distance from the gas flaring point. The variation in the rainwater parameters with distance from the gas flaring indicated significant variations in pH (F = 5.594;p = 0.006). The study showed that the concentration of VOC and particulates were high in the supposedly control area which is perceived to be safe for human habitation. Significant variations exist in emission rate (p = 0.015), flare temperature (p = 0.001), NO2 (p = 0.003), VOC (p = 0.001), noise (p = 0.041), hydrogen carbonate (p = 0.037) and chromium (p = 0.032) between the gas flaring and crude oil storage tank. Regular monitoring is advocated to mitigate the harmful effects of the pollutants.

Short-Term Air Quality Gains of COVID-19 Pandemic Lockdown of Port Harcourt, Nigeria

The air quality index (AQI) of a location informs how clean or unhealthy the ambient air is. While COVID-19 pandemic on one hand threatened the health of mankind globally, on the other hand was a respite to poor air quality of most cities. This study evaluated the positive effects of the brief COVID-19 lockdown on the air quality of Port Harcourt city, Nigeria. Air quality parameters aimed at assessing air quality index of Port Harcourt Metropolis before, during and after COVID-19 pandemic lockdown were monitored and compared. Data were analysed and AQI of sampled locations computed using the US EPA recommended standard procedure. Results from the study showed that, the ambient air quality of Port Harcourt was hazardous for breathing before lockdown. During shutdown of activities, the air quality improved to unhealthy status, with an average reduction AQI of 261.7 points. However, an average increase of 100.7 points, resulting to very unhealthy air status for residents after lockdown was observed. The unhealthy status during lockdown shows that anthropogenic activities were still on despite the Pandemic shutdown of economic activities. Also, decrease in levels of the criteria air pollutants was observed. Before lock down, the range levels of SO3, NO2, CO, O3, PM2.5 and PM10 were <0.1 - 1.2 ppm, <0.1 - 0.1 ppm, 8 - 28 ppm, <0.1 ppm, 20 - 140 μg/m3, 15 - 135 μg/m3, respectively. In the period of lockdown, the levels reduced considerably, especially CO and PM2.5 and PM10 (1 - 12 ppm, 5 - 60 μg/m3, and 10 - 50 μg/ m3). Conversely, after lockdown, there was upsurge in levels of the pollutants, especially CO and PM2.5 and PM10 (4 - 16 ppm, 10 - 110 μg/m3, 10 - 90 μg/m3). Authorities are expected to establish routine air quality measurements stations and communicate daily air quality to residents, for public health precaution purposes. Shutdown of industrial activities instituted by Government in curtailing the surge of COVID-19 pandemic could likely be a novel environmental model for mitigating air pollution in highly hazardous air pollution emergency domains.

Analysis of Rainfall Variability Using Remote Sensing and GIS in North Central Nigeria

The importance of rainfall variability in successfully understanding the dynamics of climate change in any region cannot be overemphasized. This study examines rainfall variability in the North Central region including the Federal Capital Territory Abuja using remote sensing and geographic information system (GIS) application. The study employed satellite data basically from near real time data of Moderate Resolution Imaging Spectroradiometer (MODIS). Thereafter, the point data of rainfall was clipped to the shape file of Nigeria Boundary and interpolation using Inverse Distance Weight (IDW) was done to generate rainfall spatial maps from 2000-2017. The result reveal high temporal variation in rainfall particularly Niger, Plateau, Benue and Nassarawa states. The study therefore recommends close monitoring of periodic pattern of rainfall characteristics in the region by the Nigerian meteorological agency and to encourage farmers into drought tolerant and irrigation farming.

Assessment of Drought Vulnerability and Occurrence Zones in North Central Nigeria

Assessment of drought vulnerability and occurrence zones in North Central Nigeria was carried out in this study using standardized Precipitation Index (SPI). The Standardized Precipitation Index (SPI) 12 months’ time scale was computed from long-term rainfall data between 1960 and 2015 obtained from the Nigerian Meteorological Agency (NIMET) Abuja. The SPI results were further subjected to Mann-Kendal and Sen’s slope analysis for trend detection. To assess the vulnerability of drought and occurrence zones, the SPI and other geo-spatial techniques were employed to generate drought vulnerability maps for three epochs: 2000-2005, 2005-2010 and 2010-2015 respectively. The SPI values were interpolated using Inverse Weighted (IDW) techniques in ArcGIS10.5 to generate the vulnerability maps for the selected model years. The outcome of drought trend and vulnerability maps reveals increasing drought trend dominated by near normal and moderate conditions in Abuja, Ilorin and Lokoja while moderate and severe droughts were observed in Minna and Jos. The study therefore recommends holistic drought monitoring and management strategies in order to mitigate its adverse impact on water resources and rainfall-dependent agriculture.

Impact of Flooding on Wheel Shafts and Wheel Bearings in Abraka, and Way Forward

This study aimed at examining the impact of flooding on wheel-bearings and wheel-shaft in Abraka. The empirical and survey research designs were employed for the study. 42 checklists were dropped at the various mechanic workshops to collect data on the number of wheel-shaft and wheel-bearing changed weekly for five years and flood depths were measured for a period of five years. The simple linear regression was employed for data analysis. Findings include that: when the flood depth is at 0.10 feet in January the number of wheel-shaft and wheel-bearings changed is 396 and 220 pcs respectively. When flood depth is at 4.57 feet in August 3749 shafts and 1451 bearings were changed respectively. The regressions analysis showed that the relationship between wheel-shaft and flooding was r = 0.64, and the model was significant at p (0.00) < 0.05. Similarly, regressions analysis showed that the relationship between wheel-bearing and flooding was r = 0.62, and the model was significant at p (0.00) < 0.05. It therefore follows that impairment of wheel-shaft and wheel-bearing significantly depends on flooding events in Abraka. The following recommendations were made: construction of street side channels to drain of flood from the streets;checking the shafts and wheels hubs at regular intervals and re-grease when necessary etc.

Rice and Climate Change:It’s Significance towards Achieving Food Security in Nigeria:A Review

Climate change is already impacting on every aspect of man life on earth especially in the agricultural sectors of developing nations.In Nigeria,and indeed the world over,seasons are shifting,temperatures are rising,landscapes are changing and sea levels are rising.Extreme weather events like drought and flood are becoming more frequent and pronounced.[3]stressed on the fact that Agriculture will suffer from major damage caused by changes in climate especially in the African continent.Nigeria is one of the African country that is highly vulnerable to the adverse effects of climate change,as Nigeria is still practicing rain fed agriculture[16].The impact of climate change is experienced in form of extreme climatic events like flooding,severe heats,and droughts which has led to the degradation of soil and consequently low yield in crops.This will have consequences for rice cultivation in Nigeria,where the dominating climatic factor relied on by farmers in the choice of when to prepare the land for planting,the actual planting,the types of crop variety to plant and harvesting of crop is rainfall[23,24].The implication of this will be interference with food security as rice is an essential food crop in Nigeria that is consumed by a large number of the population.[26]has warned that hunger in Africa will be worsen by adverse effects of climate change,as it threatens the capacity of vulnerable countries like Nigeria to guarantee food security,eradicate poverty and actualize sustainable development in agriculture.The increasing rate of inadequacy in food supply in the world leading to different form of malnutrition is worrisome and more needs to be done in the areas of agriculture so as to guarantee food security to some extent and improve on nourishment,if a world without hunger is to be achieved by 2030.

The Minimum and Maximum Temperature Forecast Using Statistical Downscaling Techniques for Port-Harcourt Metropolis, Nigeria

This study centers on applying the statistical downscaling technique to the daily minimum and maximum temperatures of Port Harcourt from the period 1985-2014. To select the period of calibration, the wilby and wigley assumption of 2014 was adopted. However, the Bruckner circle assumption was adopted in selecting the normal under review. Secondary data of minimum and maximum temperatures for Port Harcourt were collected from the archive of Nigerian meteorological agency (NIMET). The grid cell of the HadCM3 corresponding to the Port Harcourt meteorological station was selected from the HadCM3 website to generate the largescale predictors. Data for temperature was there after normalized for the period of calibration. To analyze data, ANOVA and Paired t tests were used. Result showed that, the model was significant at p °C from 1960-2080, while for B2 the increase will be 0.18°C for same period. For minimum temperature, the ANOVA also showed a difference of 0.21°C and 0.11°C for A2 and B2 respectively. The paired t test statistics showed that these variations in temperatures for both maximum and minimum at A2 and B2 scenarios are significant at p < 0.05. Reforestation, afforestation, carbon sequestration are strongly advocated.