A Mathematical Model of Indoor Air Pollution and Its Effects on Human Respiratory Health

Autor/innen

  • Lubem Kwaghkor Department of Mathematics, Nigerian Army University Biu Autor/in https://orcid.org/0000-0001-7160-6534
  • Hycienth Orapine Department of Mathematics, Nigerian Army University Biu Autor/in
  • Usama Salihu Department of Mathematics, Nigerian Army University Biu Autor/in

DOI:

https://doi.org/10.62054/ijdm/0201.11

Schlagwörter:

Mathematical Model, Indoor Air Quality, Pollution, Stability, Simulation.

Abstract

Indoor air quality (IAQ) refers to the quality of air within and around buildings and structures, which is known to affect the comfort and well-being of the building occupants. Research on the urban population has confirmed that people spend more than 90% of their daily life span in indoor environments. This study aims to formulate a mathematical model that can help study indoor air quality dynamics and its impact on the human respiratory system. The formulated seven linear differential equations of first order were found to be uniform and asymptotically stable and the model has a unique solution using the Picard – Lindelof Method. Numerical simulations were carried out to study the effect of indoor pollutants on the human respiratory system and the results were graphed. The results indicate that this model can be used to study the effect of indoor pollutants on the human respiratory system perfectly and hence recommended.

Literaturhinweise

Apte, K.; Salvi, S. (2016). Household air pollution and its effects on health. F1000Research 5, 2593.

Blum J. J. (1960). Concentration profiles in and around capillaries. Am. J. Physiology, 198, 991-8.

Clark A. R., Stokes Y. M., Lane M., Thompson J. G. (2006). Mathematical modelling of oxygen concentration in bovine and murine cumlus-oocyte complexes, Reproduction, 131, 999-1006.

Guyton A. C. and Hall, J. E. (2011). Text Book of Medical Physiology, W. B. Saunders, 12th ed. 465-523.

Jones, A.P. (1999). Indoor air quality and health. Atmos. Environ. 33, 4535–4564.

Khanday M. A., Najar A. A. (2015a). Mathematical model for the transport of oxygen in the living tissue through capillary bed, Journal of Mechanics in Medicine and Biology, 15(4):1550055.

Khanday M. A., Najar A. A. (2015b). Maclaurin's series approach for the analytical solution of oxygen transport to the biological tissues through capillary bed, Journal of Medical Imaging and Health Informatics, 5(5):959-963.

Klepeis, N.E.; Nelson, W.C.; Ott, W.R.; Robinson, J.P.; Tsang, A.M.; Switzer, P.; Behar, J.V.; Hern, S.C.; Engelmann, W.H. (2001). The National Human Activity Pattern Survey (NHAPS): A resource for assessing exposure to environmental pollutants. J. Expo. Anal. Environ. Epidemiol. 11, 231–252.

Krogh A. (1919). The supply of oxygen to the tissue and the regulation of the capillary circulation, J. Physiology, 52, 457-464.

Kwaghkor L. M., Onah E. S. and Bassi I. G. (2018). Stochastic Modelling of the Effect of Deforestation in Nigeria. Journal of the Nigerian Association of Mathematical Physics. 45 (1). Pp.379 – 387.

Kwaghkor L. M., Onah E. S., Aboiyar, T. and Ikughur, J. A. (2019). Derivation of a Stochastic Labour Market Model from a Semi – Markov Model. International Journal of Mathematical Analysis and Optimization: Theory and Applications. 2019(2). Pp.610-630.

Kwaghkor, L. M. and Luga, T. (2016). Mathematical Model for the Detection and Control of Diabetes. Journal of the Nigerian Association of Mathematical Physics. 35 (2). Pp.253 – 260.

Kwaghkor, L. M., Adamu, S., Mohammed, A. and Suleiman, M. (2024). A Nonlinear Mathematical Model for the Effect of Diabetes Population on a Community. International Journal of Development Mathematics, 1(1), Pp. 172-185. http://doi.org/10.62054/ijdm/0101.13

Kwaghkor, L. M., Onah, E. S., Bassi, I. G. and Danjuma, T. (2021). Stochastic Transmission Dynamics of Covid-19 within a Density Dependent Population. FUDMA Journal of Science. Vol.5(2). Pp. 567 – 573. https://doi.org/10.33003/fjs-2021-0502-569

Kwaghkor, L.M., Mohammed, A & Nyamtswam, E. V. (2022). A Mathematical Model for Diabetes Management. FUDMA Journal of Science. Vol. 6 (5). Pp 36 – 40. https://doi.org/10.33003/fjs-2022-0605-1091

Lin S. H. (1976). Oxygen diffusion in a spherical cell with non-linear oxygen uptake kinetics, J. Theoret. Biol., 60, 449-457.

Lone, A. U. H.; Khanday, M. A. and Mubarak, S. (2021). A four-compartment model to estimate oxygen and carbon dioxide exchange concentrations via blood using eigenvalue approach. South east Asian J. of Mathematics and Mathematical Sciences. 17(2):367-384.

Mannan, M. and Al-Ghamdi, S. G. (2021). Indoor Air Quality in Buildings: A Comprehensive Review on the Factors Influencing Air Pollution in Residential and Commercial Structure. Int. J. Environ. Res. Public Health,18, 3276.

Nunn J. F. (1987). Applied Respiratory Physiology, Elsevier, 3rd ed.

Orapine, H. O., Baidu, A. A., and Kwaghkor, L. M. (2023). The Cauchy Problem for Nonlinear Higher Order Partial Differential Equations Using Projected Differential Transform Method. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 9(2), Pp. 74-89. https://doi.org/10.5281/zenodo.10202651

Ottesen J. T., Olufsen M. S., Larsen J. K. (2004). Applied Mathematical Models in Human Physiology, SIAM, 13-34.

Prajakta, P. (2013). Shrimandilkar, Indoor Air Quality Monitoring for Human Health. Ijmer 3, 891–897. Available online: http://www.ijmer.com/papers/Vol3_Issue2/BV32891897.pdf

Salathe E. P., Wang T. C., Gross G. F. (1980). Mathematical analysis of oxygen transport to tissues, Mathematical Bioscience, 51, 89-115.

Simpson M. J. and Ellery A. J. (2012). An analytic solution for diffusion and non-linear uptake of oxygen in a spherical cell, Applied Mathematical Modelling, 36, 3329-3334.

Sisask, M.; Värnik, P.; Värnik, A.; Apter, A.; Balazs, J.; Balint, M.; Bobes, J.; Brunner, R.; Corcoran, P.; Cosman, D.; et al. (2014). Teacher satisfaction with school and psychological well-being affects their readiness to help children with mental health problems. Health Educ. J. 73, 382–393.

Sundell, J. (2004). On the history of indoor air quality and health. Indoor Air Suppl. 14, 51–58.

USEPA. (2013). Indoor Air Pollution and Health. Report Series No. 104. 2013. Available online:https://www.epa.ie/pubs/reports/research/health/IndoorAirPollutionandHealth.pdf

Vilˇceková, S.; Apostoloski, I.Z.; Meˇciarová, L’.; Burdová, E.K.; Kisel’ák, J. (2017). Investigation of indoor air quality in houses of Macedonia. Int. J. Environ. Res. Public Health 14, 37.

World Health Organization. (2007). Indoor Air Pollution: National Burden of Disease Estimates; WHO: Geneva, Switzerland. Available online: https://www.who.int/airpollution/publications/indoor_air_national_burden_estimate_revised.pdf?ua=1.

Veröffentlicht

2025-04-02

Zitationsvorschlag

A Mathematical Model of Indoor Air Pollution and Its Effects on Human Respiratory Health. (2025). International Journal of Development Mathematics (IJDM), 2(1), 145-155. https://doi.org/10.62054/ijdm/0201.11

Ähnliche Artikel

1-10 von 136

Sie können auch eine erweiterte Ähnlichkeitssuche starten für diesen Artikel nutzen.