Jamiu Adetayo Adeniran

Air Emissions of Sulphur Dioxide From Gasoline and Diesel Consumption in the Southwestern States of Nigeria

The contribution of SO2 emissions from the consumption of petroleum products to Nigerian airshed has been of great concern over the years because of the resulting adverse environmental and health effects. It is in the light of this that air emissions of SO2 from gasoline and diesel consumed in the Southwestern States of Nigeria were estimated in this study. Lagos state being the highest consumer of gasoline and diesel in Southwestern Nigeria emitted the highest quantity.

Ground level concentration of some air pollutants from Nigeria thermal power plants

ABSTRACT Power sector in Nigeria is undergoing structural reforms aimed at improving and expanding the current generation capacity, using thermal power plants. Ground level concentrations of air pollutants emitted from natural gas-powered thermal power plants were estimated using the American Meteorological Society-Environmental Protection Agency Regulatory Model (AERMOD). The average 24-h ground level concentrations of CO, NO x , SO2, particulate matter (PM), and volatile organic compounds (VOCs) were 31.88–72.79; 61.33–104; 0.61–3.91; 0.21–1.52; and 0.19–1.09 µg/m3, respectively. There is need for continuous monitoring of ground level concentration of pollutants around the thermal power plants to guarantee the safety of the environment in the host communities.

Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM1.0, PM2.5, PM10 and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811xa0m/s while solar radiation periods ranged from 0.3 to 3.5xa0h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36xa0°C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8xa0μg/m3 for PM1.0, PM2.5, PM10 and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.

Analytical modeling of human exposure from short-term point source releases of aerosols from household spray products

Indoor air measurements of aerosols emitted from the use of household spray products are expensive and time-consuming. An analytical model was developed and incorporated into a graphical user interface to quantify exposure as a function of distance and time. The model considered point-source dispersion with reflection from a wall and aerosol concentration decay due to air exchange rate and deposition. Aerosol concentration decreased with respect to increase in time and distance from the release point. There was no significant difference between the developed model and experimental results. The developed model could be used to adequately predict indoor human exposure to aerosols as a function of distance and time.

Optimisation and performance evaluation of an environmentally friendly rocket composite propellant

ABSTRACT This paper investigated the effects of laboratory synthesised rocket composite propellants’ formulations on propellant performance parameters using response surface methodology (RSM). For the sake of a safe environment, the propellant is made of chemical constituents that have less severe effects on air quality. Experimental measurements of propellant performance parameters were carried out using the ballistic evaluation method. The thrust generated during combustion, the burn time and the propellant combustion temperature were measured using a data acquisition facility equipped with a button load cell and a thermocouple. Specific impulse, density, temperature, characteristic velocity, molecular weight and heat ratio were computed from the measured parameters. The resulting optimum rocket composite propellant formulations were 65.1%, 18.1%, 9.1%, 3.6%, 2.2% and 1.9% for the oxidiser, binder, fuel, opacifier, burning rate enhancer and catalysts, respectively. The corresponding performance indices including specific impulse, propellant density, propellant temperature, propellant characteristic velocity, molecular weight and heat ratio were 122.03u2005s, 1697.08u2005kgu2005m−3, 2025.07u2005K, 987.65u2005mu2005s−1 , 31.50u2005kgu2005mol−1 and 1.02, respectively. Findings revealed the accuracy and the adequacy of RSM in analysing and optimising the effects of composite rocket propellant formulation on its performance parameters and also a step towards producing an environmentally friendly rocket composite propellant.

Spatiotemporal distributions of polycyclic aromatic hydrocarbons close to a typical medical waste incinerator

Environmental contaminations by polycyclic aromatic hydrocarbons (PAHs) especially from incinerators occur subtly, and PAH contribution from this source is underestimated. However, as environmental PAH concentrations build up, this may be a serious concern around the incinerator vicinity due to the potential consequences of PAHs on ecosystems and human health. Thus, the contribution of selected (12) PAHs from the Obafemi Awolowo University Teaching Hospital medical waste incinerator (or source, HWI_0) was determined by sampling stack gas and ambient air around incinerator vicinity from June 2014 to May 2015. Results showed that the 12 PAH source (HWI_0) concentrations were in the range of NA (for phenanthrene, pyrene, anthracene, benz[e]acephenanthrylene, and indeno[2,1-b]chromene) to 10.9xa0ng/m3 (pyrelene) and generally higher than the receptor points (hospital waste incinerators (HWIs)). The average total PAH concentrations per month at HWI_0 and the receptors—HWI_1, HWI_2, HWI_3, HWI_4 and HWI_5—were 73.0xa0±xa027.9, 60.4xa0±xa030.8, 42.5xa0±xa023.6, 38.7xa0±xa021.9, 35.0xa0±xa027.2, and 39.2xa0±xa022.9xa0ng/m3, respectively. These results and multivariate receptor model analysis indicated high correlations between source PAH contributions and the receptor points. The PAH concentrations in the dry season were higher than the wet season suggesting that hydrological condition affects ambient PAH concentrations. The average PAH concentrations in the HWIs as well as the cumulative exposure concentrations observed throughout the period are of major health concern because PAH concentrations detected are several times higher than both the European Union standard and the WHO guideline level.

Kinetics and neuro-fuzzy soft computing modelling of river turbid water coag-flocculation using mango (Mangifera indica) kernel coagulant

Abstract This study investigates kinetics and Adaptive Neuro-Fuzzy Modeling (ANFM) of river turbid water coagulation-flocculation (CF) process using mango kernel coagulant (MKC). CF experiments were performed using jar test apparatus and the process kinetic-transport parameters (coagulation rate constant, half-life time, and particle diffusivity) were determined using kinetic-transport models. Grid-partitioning neuro-fuzzy programming codes were written and implemented in Matlab 9.2 software environment for the development of neuro-fuzzy architecture. The ANFM input data include initial water pH, initial water turbidity, biocoagulant dosage, CF time, and turbidity removal percentage (TRP) as output data. Generalized bell membership function was optimally selected for fuzzification of input variables and a hybrid algorithm was considered for the learning method of input-output data with constant output membership type. The minimum turbidity (0.51 NTU) of treated water was achieved at pH 12 and coagulant dosage of 2.5u2009mg/L with coagulation rate constant, half-life (t1/2) and particle diffusivity 0.0194u2009s−1, 10.01u2009min, and 7.267u2009×u200910−14 m2/s, respectively. The correlation coefficient (R2) between the experimental and neuro-fuzzy predicted values was 0.9924 and the ratio (K) of training error to testing error was 0.68. Thus, this study shows that ANFM can be used as a reliable tool for modeling river water CF and kinetic-transport parameter results are useful in process design, optimization, and control.