Indexing
All Issues
Submission
Author Guidelines
Reviewers
Editorial Members
Publication Fee
Vol.1 , No. 2, Publication Date: Apr. 27, 2018, Page: 71-81
 meteorological data for temperature and wind speed at 1000mbar pressure level was retrieved and processed from ECMWF Era-Interim Re-analysis platform. The data were for 6-hourly synoptic hours: 0000H, 0600H, 1200H and 1800H at 0.125° grid resolution. The gradient Richardson (R<sub>ig</sub>) number technique was used to assess stability conditions across distinct layers: 10-50m (surface layer); 50-100m (mid layer) and 100-1300m (upper layer). Results indicated that the surface layer is always in unstable state as over 90% and 100% of R<sub>ig</sub> values were below Richardson Critical (R<sub>ic</sub>) value of 0.25 and Richardson Termination level (R<sub>T</sub>) of 1, respectively. Stable conditions exist at the mid layer across the hours and all R<sub>ig</sub> values were greater than R<sub>T</sub> level of 1. R<sub>ig</sub> values for the upper layer were largely negative and ranged between -52 to -360. This indicates very strong unstable conditions. Atmospheric stability generated through mixed convection prevailed at the surface layer and upper layer but with more of forced and free convection. This shows that mechanical turbulence is dominant at the surface while thermal buoyancy prevails at the upper level. Linking results to emission dispersion proposes that air pollutants will be dispersed across far and near expanses at the upper layer and surface layers. This is due to the laminar pattern of the mid layer that will restrict altitudinal and horizontal emission dispersion. Authorities should certify that prospective emission sources are above 50m to safeguard the health of sensitive receptors as regards emissions concentrations. Also, wind energy could be utilised as surface R<sub>ig</sub> values concur with obtainable wind shear values.&picture=http://www.aascit.org/aascit/decorators/img/journal/810.jpg)
| [1] | David Onojiede Edokpa, Department of Geography and Environmental Management, University of Port Harcourt, Port Harcourt, Nigeria. |
| [2] | Precious Nwobidi Ede, Institute of Geosciences and Space Technology, Rivers State University of Science and Technology, Port Harcourt, Nigeria. |
This study surveyed the levels of atmospheric stability across the atmospheric boundary layer in Jos, north-central Nigeria. Five years (2011-2015) meteorological data for temperature and wind speed at 1000mbar pressure level was retrieved and processed from ECMWF Era-Interim Re-analysis platform. The data were for 6-hourly synoptic hours: 0000H, 0600H, 1200H and 1800H at 0.125° grid resolution. The gradient Richardson (Rig) number technique was used to assess stability conditions across distinct layers: 10-50m (surface layer); 50-100m (mid layer) and 100-1300m (upper layer). Results indicated that the surface layer is always in unstable state as over 90% and 100% of Rig values were below Richardson Critical (Ric) value of 0.25 and Richardson Termination level (RT) of 1, respectively. Stable conditions exist at the mid layer across the hours and all Rig values were greater than RT level of 1. Rig values for the upper layer were largely negative and ranged between -52 to -360. This indicates very strong unstable conditions. Atmospheric stability generated through mixed convection prevailed at the surface layer and upper layer but with more of forced and free convection. This shows that mechanical turbulence is dominant at the surface while thermal buoyancy prevails at the upper level. Linking results to emission dispersion proposes that air pollutants will be dispersed across far and near expanses at the upper layer and surface layers. This is due to the laminar pattern of the mid layer that will restrict altitudinal and horizontal emission dispersion. Authorities should certify that prospective emission sources are above 50m to safeguard the health of sensitive receptors as regards emissions concentrations. Also, wind energy could be utilised as surface Rig values concur with obtainable wind shear values.
Keywords
Atmospheric Stability, Gradient Richardson Number, Boundary Layer, Jos, Emissions
Reference
| [01] | Hutschemaekers, J. J. N. (2014). Comparison of Classification Systems to define Atmospheric Stability and their impact on Wind Turbine Design. A Published Master of Science Thesis from the Delft University of Technology, The Netherlands. September 8. |
| [02] | Ashrafi, K. and Hoshyaripour, G. A. A model to determine atmospheric stability and its correlation with CO concentration. International Journal of Civil and Environmental Engineering. 2 (2), 82-88. 2010. |
| [03] | Koblitz, T., Bechmann, A., Berg, J., Sogachev, A., Sørensen, N and Réthoré, P-E. Atmospheric stability and complex terrain: comparing measurements and CFD. Journal of Physis. 555 (1), 1-11. 2014. |
| [04] | Jayasudha, G. T., Vijayakumar, B., Ravi, P. M., Bhatt, B. C., and Kulkarni, M. S. (Eds.). A case study of atmospheric stability pattern at Kudankulam site and its correlation with suspended particulate matter. India: Bhabha Atomic Research Centre. 2014. |
| [05] | Lanigan, D., Stout, J. and Anderson, W. Atmospheric stability and diurnal patterns of Aeolian saltation on the Llano Estacado. Aeolian Research. 21 (2016), 131-137. |
| [06] | Newman, J. F. and Klein, P. M. (2014). The impacts of Atmospheric Stability on the Accuracy of Wind speed Extrapolation Methods. Resources, 3, 81-105. Doi: 10.3390/resources3010081. |
| [07] | Arya, P. (1998). Introduction to Micrometeorology, 2ND Edition. San Diego: Academic Press. |
| [08] | Oke, T. R. (1987). Boundary Layer Climates, 2ND Edition. Lagos: Methuen Publishers. |
| [09] | Mikkelson, T. (2003). Modeling of Pollutant Transport in the Atmosphere. Atmospheric physics division, wind department, Risq National Laboratory, Denmark. |
| [10] | Stull, R. B. (2012). An Introduction to Boundary Layer Meteorology. Netherland: Springer. Available from: https://books.google.com.ng/books?id=2PjrCAAAQBAJ&dq=boundary+layer+turbulence&source=gbs_navlinks_s |
| [11] | Agbo, G. A. (2011). Tropospheric Refractivity Dependence on Atmospheric Weather Conditions in Jos Nigeria. Journal of Basic Physical Research, 2 (1), 1-6. Available from: http://www.jbasicphyres-unizik.org/files/2011files/1-Basic%20Correct.pdf |
| [12] | Ajuzie, C. C. (2012). A First Survey of Phytoplankton Community Richness in Lamingo Reservoir, Jos, Nigeria: A Wake-up Call for the Continuous Monitoring of Microalgae in Surface Waters Serving as Drinking Water Sources in Nigeria. New York Science Journal, 5 (2), 1-8. Available from: http://www.sciencepub_new_york_science_journal.pdf. |
| [13] | Jos climate history (2016). Retrieved from http://www.myweather2.com/City-Town/Nigeria/Jos/climate-profile.aspx |
| [14] | Idris, N. A., Lamin, H. S., Ladan, M. J. and Yusuf, B. H. (2012) Nigeria’s Wind Energy Potentials: the Path to a Diversified Electricity Generation-Mix. International Journal of Modern Engineering Research (IJMER), 2 (4) 2434-2437. |
| [15] | Lawal, J. R., Bello, A. M., Balami, S. Y., Dauda, J., Malgwi, K. D., Ezema, K. U., Kazim, M. and Biu, A. A. (2016). Prevalence of Haemoparasites in Village Chickens (Gallus gallus domesticus) Slaughtered at Poultry Markets in Maiduguri, North-eastern Nigeria. Journal of Animal Science and Veterinary Medicine, 1, 39-45. Available from: http://www.integrityresjournals.org/jasvm/publications/2016/pdf/04lawal%20et%20al.pdf |
| [16] | Stull, R. B. (1988).An Introduction to Boundary Layer Meteorology. Netherland: Springer.url={https://books.google.com.ng/books?id=BK8P9rl- CB4C}.isbn={9789027727688}, lccn={88015564}. |
| [17] | Ward, D. (2012). ATMO 336: Weather, Climate and Society. Department of Atmospheric Science, University of Arizona. Lecture Training Materials. |
| [18] | Gastel, P. V. and Pelegri, J. L. (2004). Estimates of gradient Richardson numbers from vertically smoothed data in the Gulf Stream region. SCI. MAR., 68 (4), 459-482. |
| [19] | Vieira, C. F. A. and Sampaio, E. F. (2012). Analysing the impact of atmospheric stability on wind parameters in North East Region of Brazil. Brazil Wind Power. Siemens Energy International, August 29 and 31. |
| [20] | Murty, K. P. R. V., Filho, E. P. M., Prasad, G. S. S. D. and Deane de Abreu Sá, L. (1998). Intercomparison of Flux, Bulk and Gradient Richardson Number and its Spatial and Temporal Variation as Revealed by Interdisciplinary Pantanal Experiment (IPE-1). http://www.academia.edu/20968829/Intercomparison_of_flux_bluk_and_gradient_Richardson_number_and_its_spatial_and_temporal_variation_as_revealed_by_interdiciplinary_Pantanal_experiment_IPE-1_may_1998 |
| [21] | Jacobson, M. Z. (1999). Fundamentals of Atmospheric Modelling. Cambridge: University Press. url={https://books.google.com.ng/books?id=QnzHkFN3v8AC}isbn={9780521637176}, lccn={98015180}. |
| [22] | Grachev, A. A., Andreas, E. L., Fairall, C. W., Guest, P. S. and Persson, P. O. G. (2012). The Critical Richardson Number and Limits of Applicability of Local Similarity Theory in the Stable Boundary Layer. Boundary Layer Meteorology. Available from: https://arxiv.org/ftp/arxiv/papers/1202/1202.5066.pdf. |
| [23] | Bailey, D. T. (2000). Meteorological monitoring guidance for regulatory modelling applications. U.S Environmental Protection Agency. Office of Air and Radiation; Office of Air Quality Planning and Standards. url={https://books.google.com.ng/books?id=\_86ik7kVtAUC}, lsbn= 9781428901940. |
| [24] | Kaimal, J. C. and Finnigan, J. J. (1994). Atmospheric Boundary Layer Flows: There Structure and Measurement. New York: Oxford University Press. 289pp. |
| [25] | Eresmas, N., Harkonen, J., Joffre, S. M. Schultz, D. M., Karppinen, A. and Kukkonen, J. (2012). A Three-Step Method for Estimating the Mixing Height Using Ceilometer Data from the Helsinki Test bed. Journal of Applied Meteorology and Climatology, 51, 2172-2187. DOI: 10.1175/JAMC-D-12-058.1 |
| [26] | Ayoade, J. O. (2004). Introduction to Climatology for the Tropics (2nd Edition). Ibadan: Spectrum Books. |
