An analysis of air pollution at some industrial areas of Kano using the AERMOD Model

The effect of pollution on air quality has been a concern for mankind for a long time. In some cases the problem is essentially one of local emissions in a given urban area leading to an adverse effect on air quality in that same area. However, in the general case, the problem is more diverse in that the problem of air pollution has multiplicity effects beyond the point source and these effects are dynamic in nature. Such effects are usually evaluated using dynamical equations. In this study, a comprehensive review on effect of air polluting variables was described on the basis of evaluation of formulation equations of the American Meteorological Society and U.S. Environmental protection Agency Regulatory Model (AERMOD view 9.6.5). The AERMOD model was also used to simulate the dispersion and deposition of the hourly and daily H2S and NO2 concentrations from two domains: Challawa and Sharada industrial estates /areas respectively. The AERMOD model evaluation showed that there was good correlation between the modelled and observed H2S concentration for the daily and hourly comparison at Challawa  (0.53 and 0.91 respectively) but the daily and hourly comparison of H2S at Sharada (0.13 and 0.46 respectively) was seen to drop indicating poor correlation and model skill. However, model evaluation of NO2 shows poor agreements and model skill at Challawa as well as daily comparison at Sharada. However, the modelling shows good agreement (R2= 0.64) in the trend for the hourly value modelled versus observed concentrations at Sharada. Moreover, the mean absolute percentage error (MAPE) for the two pollutants (H2S and NO2) at all the two domains indicates highly accurate result for both daily and hourly concentrations. AERMOD software can therefore be used to estimate the dispersion and deposition of the pollutants at some domains considered in this study. Key Words: AERMOD model, Air pollutant, Industrial sources, Dispersion and Depositio

Efficient N-to-M Checkpointing Algorithm for Finite Element Simulations

In this work, we introduce a new algorithm for N-to-M checkpointing in finite element simulations. This new algorithm allows efficient saving/loading of functions representing physical quantities associated with the mesh representing the physical domain. Specifically, the algorithm allows for using different numbers of parallel processes for saving and loading, allowing for restarting and post-processing on the process count appropriate to the given phase of the simulation and other conditions. For demonstration, we implemented this algorithm in PETSc, the Portable, Extensible Toolkit for Scientific Computation, and added a convenient high-level interface into Firedrake, a system for solving partial differential equations using finite element methods. We evaluated our new implementation by saving and loading data involving 8.2 billion finite element degrees of freedom using 8,192 parallel processes on ARCHER2, the UK National Supercomputing Service

The X-ray luminosity function of Active Galactic Nuclei in the redshift interval z=3-5

We combine deep X-ray survey data from the Chandra observatory and the wide-area/shallow XMM-XXL field to estimate the AGN X-ray luminosity function in the redshift range z=3-5. The sample consists of nearly 340 sources with either photometric (212) or spectroscopic (128) redshift in the above range. The combination of deep and shallow survey fields provides a luminosity baseline of three orders of magnitude, Lx(2-10keV)~1e43-1e46erg/s at z>3. We follow a Bayesian approach to determine the binned AGN space density and explore their evolution in a model-independent way. Our methodology accounts for Poisson errors in the determination of X-ray fluxes and uncertainties in photometric redshift estimates. We demonstrate that the latter is essential for unbiased measurement of space densities. We find that the AGN X-ray luminosity function evolves strongly between the redshift intervals z=3-4 and z=4-5. There is also suggestive evidence that the amplitude of this evolution is luminosity dependent. The space density of AGN with Lx<1e45erg/s drops by a factor of 5 between the redshift intervals above, while the evolution of brighter AGN appears to be milder. Comparison of our X-ray luminosity function with that of UV/optical selected QSOs at similar redshifts shows broad agreement at bright luminosities, Lx>1e45erg/s. The faint-end slope of UV/optical luminosity functions however, is steeper than for X-ray selected AGN. This implies that the type-I AGN fraction increases with decreasing luminosity at z>3, opposite to trends established at lower redshift. We also assess the significance of AGN in keeping the hydrogen ionised at high redshift. Our X-ray luminosity function yields ionising photon rate densities that are insufficient to keep the Universe ionised at redshift z>4. A source of uncertainty in this calculation is the escape fraction of UV photons for X-ray selected AGN.Comment: MNRAS accepte

Association Between Glomerular Filtration Rate And Body Mass Index Among Orthopaedic Patients In Kano-Nigeria

Any association between body mass index and kidney disease has so far proved inconclusive. Therefore, this study is aimed to provide association between glomerular filtration rate and body mass index among orthopaedic patients. A total of sixty (60) patients irrespective of gender were recruited. Weight and height were measured prior to the sample collection. A structured questionnaire was administered to obtain the demographic data of the subjects. Blood samples were collected from each patient by venepuncture from the antecubital vein of the forearm using disposable syringes. Serum creatinine was determined by method of Rosano et al. Body Mass Index and Glomerular Filtration Rate (eGFR) were calculated using creatinine-based equation of Modification of Diet in Renal Disease. Mean BMI was found to be higher in females (25.48±5.65) than their male counterparts (21.44±4.52), while eGFR was found to be higher in males (184.14±53.23) than in females (152.06±32.71). Subjects with eGFR ≥60 were observed to be more frequent (98.30%); normal weight individuals had higher frequency (48.33%). Positive correlation exists between BMI and eGFR in males whereas negative correlation was found in females which indicates association between body mass index and kidney function is gender related