Climate and weather play significant role in spread of some diseases such as malaria. Global estimates show that about 300 million acute cases of malaria occur every year, resulting in more than one million deaths. Effect of weather elements on malaria prevalence in Agbani, Nkanu West local government area of Enugu state was examined in this study. Climate data of rainfall, temperature and relative humidity (2005 – 2014) were gotten from the ESUT Meteorological Observatory, Ebeano city for a period of ten years, Medical records was obtained from the pathological test register of University of Nigerian Teaching Hospital (UNTH) of different tests for malaria parasite among patients for ten years, well design oral interviews and structured questionnaires were used to get necessary information pertaining to the study. Pearson's product moment correlation and the students't' test for significance was employed to analyze the data to determine the strength of the relationship between weather parameters and frequency of malaria occurrence. Findings indicate that weather element which occurred naturally has a direct effect on malaria prevalence in the study area; findings show positive relationship between rainfall amount and malaria cases; an increase in amount of rainfall led to a decrease in malaria prevalence in the area .The correlation (rp) value of (6.63) between temperature and malaria cases shows that an increase in temperature values led to an increase in the frequency of malaria occurrence. Furthermore, the correlation value of (-4.32) between relative humidity and malaria cases shows that a decrease in relative humidity led to a decrease in malaria causative organism attack thus decrease in malaria occurrence. Based on the findings people are advised to sleep under mosquito treated net during high temperatures, clear stagnant water which are good breeding sites for mosquitoes, take anti-malaria vaccine and incorporate climatological information in urban planning, building designs as well as modernizing of old ones, since weather factors influences malaria incidence.

Flood is one of the most devastating, frequently occurring and costliest natural hazard in the world. The establishment of early warning systems which could be a step in the right direction towards reducing this menace could be limited by the level of knowledge of the causes. This study was conducted to assess the social factors that could affect the efficiency of early warning systems using their respective relationships with the knowledge on flood causative factors in a rural community of Kogi State, Nigeria. A  cross  sectional  study  was conducted  among  325 households  in  Oforachi community using quantitative  method  of  data  collection.  Pearson’s Chi Square Measure of Association and student t-test were used to assess the respective associations of the social factors with the level of knowledge using STATA/SE statistical software version 13.1 at 95% confidence level. The results showed that 8.00 % of the respondents had fair knowledge, 80.92% had good knowledge while, 11.08% had excellent knowledge of the causes of flood. The factors that influenced the knowledge level of the respondents in decreasing order of associations are Age, Education, Occupation, Flood experience, Marital Status and Ward. The knowledge of these associating factors will be very instrumental for the development of effective early warning signals and non-structural flood control measures.

The Niger Delta Region of Nigeria has suffered severe environmental pollution due to ever increasing oil exploration and exploitation activities in the region making the communities highly vulnerable to the effects of oil spill and other associated environmental degradation. Using eight soil samples collected from two oil-rich communities in two Local Government Areas of Delta State, the effects of oil spill on the load bearing properties of the soils were examined and used to develop regression models for the bearing capacity (for strip foundation footing) of oil contaminated soils. The triaxial test showed the mean values of the bearing capacity of the uncontaminated soil samples (which served as control) as 170.718 KN/m² and 601.49KN/m² . The samples were then thoroughly mixed with crude oil(to simulate the site conditions) at 5%, 10%, 15%, and 20%. The result of the triaxial test showed that oil reduces the bearing capacity of the soil and as the percentage increased to 20% oil, the bearing capacity dropped to 56.60KN/m² and 61.50 KN/m² respectively for the two study locations. Regression models were then developed to estimate the bearing capacity of the oil contaminated soils at any level of contamination in the study locations.

The study compared the air pollution tolerance indices (APTI) of five plant species and five ornamental shrubs in Enugu Urban Center. Laboratory analysis was performed on the four physiological and biological parameters including leaf relative water content (RWC), ascorbic acid (AA) content, total leaf chlorophyll (TCH) and leaf extract pH. These parameters were used to develop an air pollution tolerance index. Factor analysis and descriptive statistics were utilized in the analysis to examine the interactions between these parameters. Vegetation monitoring in terms of its APTI acts as a \'Bioindicator\' of air pollution. The study also showed the possibility of utilizing APTI as a tool for selecting plants or ornamental shrubs for urban heat Island mitigation in Enugu City. The result of APTI showed order of tolerance for plants as Anacarduim occidentale (23.20), Pinus spp (22.35), Catalpa burgei (22.57), Magifera indica (23.37), and Psidum guajava (24.15).The result of APTI showed increasing order of sensitivity for ornamental shrubs from ixora red (14.32), yellow ficus(12.63), masquerade pine(12.26), Tuja pine(11.000),to Yellow bush(10.60). The APTI of all the plants examined were higher than those of ornamental shrubs. Thus suggesting that plants in general were more tolerant to air pollution than ornamental shrubs. The ornamental shrubs with lower APTI values (sensitive) were recommended as bioindicator of poor urban air quality while plants with high APTI values (tolerant) are planted around areas anticipated to have high air pollution load. The result of this current study is therefore handy for future planning and as well provides tolerant species for streetscape and urban heat island mitigation.