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June  2022, 27(6): 2979-3003. doi: 10.3934/dcdsb.2021169

Modeling the influence of human population and human population augmented pollution on rainfall

1. 

Department of Mathematics, Institute of Science, Banaras Hindu University, Varanasi - 221 005, India

2. 

Department of Mathematics, Amity University, Uttar Pradesh, Lucknow, India

3. 

Department of Mathematical & Statistical Sciences,, Shri Ramswaroop Memorial University, Barabanki 225 003, India

* Corresponding author: kusum41@gmail.com

Received  March 2021 Revised  May 2021 Published  June 2022 Early access  June 2021

Worldwide, human population is increasing continuously and this has magnified the level of pollutants in the environment. Pollutants affect the human population as well as the environmental ecology including rainfall. Here, we formulate a mathematical model comprising ordinary differential equations to see the effect of human population and pollution caused by human population on the dynamics of rainfall. In the modeling process, it is assumed that the augmentation in the density of human population increases the concentration of pollutants; however, decreases the rate of formation of cloud droplets. It is also assumed that pollutants have negative impact on human population and affect the precipitation. The feasibility of all equilibrium and their stability properties are discussed. Further, to capture the effect of environmental randomness, the proposed model is also analyzed by incorporating white noise terms. For the proposed stochastic model, we have established the existence and uniqueness of global positive solution. It is also shown that system possesses a unique stationary distribution with some restrictions. The model analysis reveals that rainfall may decrease or increase due to the anthropogenic emission of pollutants in the atmospheric environment. Finally, for the validation of analytical findings, numerical simulations are presented.

Citation: A. K. Misra, Gauri Agrawal, Kusum Lata. Modeling the influence of human population and human population augmented pollution on rainfall. Discrete and Continuous Dynamical Systems - B, 2022, 27 (6) : 2979-3003. doi: 10.3934/dcdsb.2021169
References:
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L. Arnold, Stochastic Differential Equations: Theory and Applications, Wiley, New York (1972).

[2]

N. DalalD. Greenhalgh and X. Mao, A stochastic model for internal HIV dynamics, J. Math. Anal. Appl., 341 (2008), 1084-1101.  doi: 10.1016/j.jmaa.2007.11.005.

[3]

B. Dubey and A. S. Narayanan, Modelling effects of Industrialization, population and pollution on a renewable resource, Nonlinear Anal. Real World Appl., 11 (2010), 2833-2848.  doi: 10.1016/j.nonrwa.2009.10.007.

[4]

J. Fan, L. R. Leung, Z. Li, H. Morrison, H. Chen, Y. Zhou, Y. Qian and Y. Wang, Aerosol impacts on clouds and precipitation in eastern China: Results from bin and bulk microphysics, Journal of Geophysical Research, 117 (2012), D00K36. doi: 10.1029/2011JD016537.

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J. A. FoleyR. DeFriesG. P. AsnerC. BarfordG. BonanS. T. Carpenter and R. K. Snyder, Global consequences of land use, Science, 309 (2005), 570-574. 

[6] A. Friedman, Stochastic Differential Equations and their Applications, Academic Press, New York, 1976. 
[7]

R. Z. Hasminskii, Stochastic stability in differential equations, in Mechanics and Analysis, Monogr. Textb. Mech. Solids Fluids, 7, Sijthoff & Noordhoff, Alphen aan den Rijn, The Netherlands, 1980.

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D. J. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev., 43 (2001), 525-546.  doi: 10.1137/S0036144500378302.

[9]

Z. HuangQ. Yang and J. Cao, A stochastic model for interactions of hot gases with cloud droplets and raindrops, Nonlinear Anal. Real World Appl., 12 (2011), 203-214.  doi: 10.1016/j.nonrwa.2010.06.008.

[10]

V. Jha, W. R. Cotton, G. G. Carrió and R. Walko, Sensitivity studies on the impact of dust and aerosol pollution acting as cloud nucleating aerosol on Orographic precipitation in the Colorado river basin, Advances in Meteorology, (2018), 3041893. doi: 10.1155/2018/3041893.

[11]

C. Ji and D. Jiang., Threshold behaviour of a stochastic SIR model, Appl. Math. Model., 38 (2014), 5067-5079.  doi: 10.1016/j.apm.2014.03.037.

[12]

J. H. Jiang, H. Su, L. Huang, Y. Wang, S. Massie, B. Zhao, A. Omar and Z. Wang, Contrasting effects on deep convective clouds by different types of aerosols, Nature Communications, 9 (2018). doi: 10.1038/s41467-018-06280-4.

[13]

K. Lata and A. K. Misra, The influence of forestry resources on rainfall: A deterministic and stochastic model, Appl Math Model., 81 (2020), 673-689.  doi: 10.1016/j.apm.2020.01.009.

[14]

S. Li and S. Wang, Analysis of astochastic predator-prey model with disease in the predator and Beddington-DeAngelis functional response, Advances in Difference Equations, 224 (2015). doi: 10.1186/s13662-015-0448-0.

[15]

X. Mao, Stochastic Differential Equations and Applications, Horwood, New York, 1997.

[16]

X. MaoG. Marion and E. Renshaw, Environmental Brownian noise suppresses explosions in population dynamics, Stochastic Process Appl., 97 (2002), 95-110.  doi: 10.1016/S0304-4149(01)00126-0.

[17]

A. K. Misra and K. Lata, Modeling the effect of time delay on the conservation of forestry biomass, Chaos Soltions Fract., 46 (2013), 1-11. 

[18]

A. K. Misra and A. Tripathi, A stochastic model for making artificial rain using aerosols, Physica A., 505 (2018), 1113-1126.  doi: 10.1016/j.physa.2018.04.054.

[19]

A. K. Misra and A. Tripathi., Stochastic stability of aerosols-stimulated rainfall model, Physica A., 527 (2019), 121337. doi: 10.1016/j.physa.2019.121337.

[20]

B. G. Pachpatte, A Note on Gronwall-Bellman Inequality, J. Math Anal. Appl., 44 (1973), 758-762.  doi: 10.1016/0022-247X(73)90014-0.

[21]

Pollution and Health Metrics: Global, Regional, and Country, Analysis December 2019. Available from: https://gahp.net/wp-content/uploads/2019/12/PollutionandHealthMetrics-final-12_18_2019.pdf

[22]

Y. Qian, D. Gong, J. Fan, L. R. Leung, R. Bennartz, D. Chen and W. Wang, Heavy pollution suppresses light rain in China: Observations and Modeling, Journal of Geophysical Research, 114 (2009), D00K02. doi: 10.1029/2008JD011575.

[23]

D. Rosenfeld, Suppression of rain and snow by urban and Industrial air pollution, Science, 287 (2000), 1793-1796. 

[24]

D. Rosenfeld and W. Woodley, Pollution and Clouds, 14 (2001), 33., doi: 10.1088/2058-7058/14/2/30.

[25]

D. RosenfeldU. LohmannG. B. RagaC. D. O. DowdM. KulmalaS. FuzziA. Reissell and M. O. Andreae, Flood or drought: How do aerosols affect precipitation?, Science, 321 (2008), 1309-1313. 

[26]

J. B. ShuklaM. Verma and A. K. Misra, Effect of global warming on sea level rise: A modeling study, Ecol. Complex., 32 (2017), 99-110. 

[27]

J. B. ShuklaA. K. MisraR. Naresh and P. Chandra, How artificial rain can be produced? A mathematical model, Nonlinear Anal. Real World Appl., 11 (2010), 2659-2668. 

[28]

J. B. ShuklaS. SundarA. K. Misra and R. Naresh, Modeling the effects of aerosols to increase rainfall in regions with shortage, Meteorol .Atmos. Phys., 120 (2013), 157-163. 

[29]

S. Sundar and R. K. Sharma, The role of aerosols to increase rainfall in the regions with less intensity rain: A modeling study, Comput. Ecol. Softw., 3 (2013), 1-8. 

[30]

S. SundarR. NareshA. K. Misra and J. B. Shukla, A nonlinear mathematical model to study the interactions of hot gases with cloud droplets and raindrops, Appl Math Model., 33 (2009), 3015-3024.  doi: 10.1016/j.apm.2008.10.032.

[31]

R. K. UpadhyayR. D. ParshadK. Antwi-FordjourE. Quansah and S. Kumari, Global dynamics of stochastic predator-prey model with mutual interference and prey defense, J. Appl. Math. Comput., 60 (2019), 169-190.  doi: 10.1007/s12190-018-1207-7.

[32]

Y. WangM. WangR. ZhangS. J. GhanY. LinJ. HuB. PanM. LevyJ. H. Jiang and M. J. Molina, Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model, Proc. Natl. Acad. Sci. USA., 111 (2014), 6894-6899. 

[33]

B. P. Yadav, A. K. Das, K. V. Singh and S. K. Manik, Rainfall Statistics of India - $(2017)$. http://www.imd.gov.in.,

[34]

C. Zhao, X. Tie and Y. Lin, A possible positive feedback of reduction of precipitation and increase in aerosols over eastern central China, Geophysical Research Letters, 33 (2006), L11814. doi: 10.1029/2006GL025959.

show all references

References:
[1]

L. Arnold, Stochastic Differential Equations: Theory and Applications, Wiley, New York (1972).

[2]

N. DalalD. Greenhalgh and X. Mao, A stochastic model for internal HIV dynamics, J. Math. Anal. Appl., 341 (2008), 1084-1101.  doi: 10.1016/j.jmaa.2007.11.005.

[3]

B. Dubey and A. S. Narayanan, Modelling effects of Industrialization, population and pollution on a renewable resource, Nonlinear Anal. Real World Appl., 11 (2010), 2833-2848.  doi: 10.1016/j.nonrwa.2009.10.007.

[4]

J. Fan, L. R. Leung, Z. Li, H. Morrison, H. Chen, Y. Zhou, Y. Qian and Y. Wang, Aerosol impacts on clouds and precipitation in eastern China: Results from bin and bulk microphysics, Journal of Geophysical Research, 117 (2012), D00K36. doi: 10.1029/2011JD016537.

[5]

J. A. FoleyR. DeFriesG. P. AsnerC. BarfordG. BonanS. T. Carpenter and R. K. Snyder, Global consequences of land use, Science, 309 (2005), 570-574. 

[6] A. Friedman, Stochastic Differential Equations and their Applications, Academic Press, New York, 1976. 
[7]

R. Z. Hasminskii, Stochastic stability in differential equations, in Mechanics and Analysis, Monogr. Textb. Mech. Solids Fluids, 7, Sijthoff & Noordhoff, Alphen aan den Rijn, The Netherlands, 1980.

[8]

D. J. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev., 43 (2001), 525-546.  doi: 10.1137/S0036144500378302.

[9]

Z. HuangQ. Yang and J. Cao, A stochastic model for interactions of hot gases with cloud droplets and raindrops, Nonlinear Anal. Real World Appl., 12 (2011), 203-214.  doi: 10.1016/j.nonrwa.2010.06.008.

[10]

V. Jha, W. R. Cotton, G. G. Carrió and R. Walko, Sensitivity studies on the impact of dust and aerosol pollution acting as cloud nucleating aerosol on Orographic precipitation in the Colorado river basin, Advances in Meteorology, (2018), 3041893. doi: 10.1155/2018/3041893.

[11]

C. Ji and D. Jiang., Threshold behaviour of a stochastic SIR model, Appl. Math. Model., 38 (2014), 5067-5079.  doi: 10.1016/j.apm.2014.03.037.

[12]

J. H. Jiang, H. Su, L. Huang, Y. Wang, S. Massie, B. Zhao, A. Omar and Z. Wang, Contrasting effects on deep convective clouds by different types of aerosols, Nature Communications, 9 (2018). doi: 10.1038/s41467-018-06280-4.

[13]

K. Lata and A. K. Misra, The influence of forestry resources on rainfall: A deterministic and stochastic model, Appl Math Model., 81 (2020), 673-689.  doi: 10.1016/j.apm.2020.01.009.

[14]

S. Li and S. Wang, Analysis of astochastic predator-prey model with disease in the predator and Beddington-DeAngelis functional response, Advances in Difference Equations, 224 (2015). doi: 10.1186/s13662-015-0448-0.

[15]

X. Mao, Stochastic Differential Equations and Applications, Horwood, New York, 1997.

[16]

X. MaoG. Marion and E. Renshaw, Environmental Brownian noise suppresses explosions in population dynamics, Stochastic Process Appl., 97 (2002), 95-110.  doi: 10.1016/S0304-4149(01)00126-0.

[17]

A. K. Misra and K. Lata, Modeling the effect of time delay on the conservation of forestry biomass, Chaos Soltions Fract., 46 (2013), 1-11. 

[18]

A. K. Misra and A. Tripathi, A stochastic model for making artificial rain using aerosols, Physica A., 505 (2018), 1113-1126.  doi: 10.1016/j.physa.2018.04.054.

[19]

A. K. Misra and A. Tripathi., Stochastic stability of aerosols-stimulated rainfall model, Physica A., 527 (2019), 121337. doi: 10.1016/j.physa.2019.121337.

[20]

B. G. Pachpatte, A Note on Gronwall-Bellman Inequality, J. Math Anal. Appl., 44 (1973), 758-762.  doi: 10.1016/0022-247X(73)90014-0.

[21]

Pollution and Health Metrics: Global, Regional, and Country, Analysis December 2019. Available from: https://gahp.net/wp-content/uploads/2019/12/PollutionandHealthMetrics-final-12_18_2019.pdf

[22]

Y. Qian, D. Gong, J. Fan, L. R. Leung, R. Bennartz, D. Chen and W. Wang, Heavy pollution suppresses light rain in China: Observations and Modeling, Journal of Geophysical Research, 114 (2009), D00K02. doi: 10.1029/2008JD011575.

[23]

D. Rosenfeld, Suppression of rain and snow by urban and Industrial air pollution, Science, 287 (2000), 1793-1796. 

[24]

D. Rosenfeld and W. Woodley, Pollution and Clouds, 14 (2001), 33., doi: 10.1088/2058-7058/14/2/30.

[25]

D. RosenfeldU. LohmannG. B. RagaC. D. O. DowdM. KulmalaS. FuzziA. Reissell and M. O. Andreae, Flood or drought: How do aerosols affect precipitation?, Science, 321 (2008), 1309-1313. 

[26]

J. B. ShuklaM. Verma and A. K. Misra, Effect of global warming on sea level rise: A modeling study, Ecol. Complex., 32 (2017), 99-110. 

[27]

J. B. ShuklaA. K. MisraR. Naresh and P. Chandra, How artificial rain can be produced? A mathematical model, Nonlinear Anal. Real World Appl., 11 (2010), 2659-2668. 

[28]

J. B. ShuklaS. SundarA. K. Misra and R. Naresh, Modeling the effects of aerosols to increase rainfall in regions with shortage, Meteorol .Atmos. Phys., 120 (2013), 157-163. 

[29]

S. Sundar and R. K. Sharma, The role of aerosols to increase rainfall in the regions with less intensity rain: A modeling study, Comput. Ecol. Softw., 3 (2013), 1-8. 

[30]

S. SundarR. NareshA. K. Misra and J. B. Shukla, A nonlinear mathematical model to study the interactions of hot gases with cloud droplets and raindrops, Appl Math Model., 33 (2009), 3015-3024.  doi: 10.1016/j.apm.2008.10.032.

[31]

R. K. UpadhyayR. D. ParshadK. Antwi-FordjourE. Quansah and S. Kumari, Global dynamics of stochastic predator-prey model with mutual interference and prey defense, J. Appl. Math. Comput., 60 (2019), 169-190.  doi: 10.1007/s12190-018-1207-7.

[32]

Y. WangM. WangR. ZhangS. J. GhanY. LinJ. HuB. PanM. LevyJ. H. Jiang and M. J. Molina, Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model, Proc. Natl. Acad. Sci. USA., 111 (2014), 6894-6899. 

[33]

B. P. Yadav, A. K. Das, K. V. Singh and S. K. Manik, Rainfall Statistics of India - $(2017)$. http://www.imd.gov.in.,

[34]

C. Zhao, X. Tie and Y. Lin, A possible positive feedback of reduction of precipitation and increase in aerosols over eastern central China, Geophysical Research Letters, 33 (2006), L11814. doi: 10.1029/2006GL025959.

Figure 1.  Plot of isoclines (12) in blue color and (13) in red color
Figure 2.  Global stability of $ (N^*, C_r^*, P^*) $ and $ (N^*, C_d^*, C_r^*) $ in $ N-C_r-P $ and $ N-C_d-C_r $ spaces, respectively
Figure 3.  Variation of $ C_r(t) $ with time for different values of $ \eta $ (a) for $ \pi_1 = 0.09 $ and (b) for $ \pi_1 = 0.9. $
Figure 4.  Path of $ N(t), C_d(t), C_r(t) $ and $ P(t) $ for stochastic model (17) with $ \sigma_1 = 0.0001, \sigma_2 = 0.006, \sigma_3 = 0.004, \sigma_4 = 0.008 $ as well as deterministic model (1)
Figure 5.  Path of $ N(t), C_d(t), C_r(t) $ and $ P(t) $ for stochastic model (17) with $ \sigma_1 = 0.08, \sigma_2 = 0.2, \sigma_3 = 0.09, \sigma_4 = 0.1 $ as well as deterministic model (1)
Figure 6.  The stationary distribution of $ N(t), C_d(t), C_r(t) $ and $ P(t) $ obtained at $ t = 100 $ from $ 10,000 $ simulation run for the stochastic model (17), for $ \sigma_1 = 0.0001, \sigma_2 = 0.006, \sigma_3 = 0.004, \sigma_4 = 0.008. $
Figure 7.  The stationary distribution of N(t), Cd(t), Cr(t) and P(t) obtained at t = 100 from 10, 000 simulation run for the stochastic model (17), for σ1 = 0.08, σ2 = 0.2, σ3 = 0.09, σ4 = 0.1.
Figure 8.  The stationary distribution of N(t), Cd(t), Cr(t) and P(t) obtained at t = 100 from 10, 000 simulation run for the stochastic model (17), for σ1 = 0.09, σ2 = 0.3, σ3 = 0.1, σ4 = 0.2.
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