Causal effects of population growth on energy utilization and environmental pollution: A system dynamics approach

Document Type : Research Paper


1 Department of Agricultural Economic, Marvdasht branch, Islamic Azad University, Marvdasht, Iran

2 Agricultural Economics, Fars Agricultural and Natural Resources Research and Training Center, Fars, Iran


Population growth will change the demand for food and energy resources and environmental pollution. Although early energy resources modeling has made vital efforts to model the energy system in the world, because of increasing complexity and integration of environmental, social, and economic functions, these models still need to be developed to show a system close to the real world to enhance sustainable management of natural resources. Hence, the main objective of this study is to design a system dynamics model for the food production system and energy demand in Iran in order to evaluate the effects of different population scenarios on key variables. In this regard, an integrated system dynamics simulation model was developed in Iran where managing energy resources is seriously challenging due to population growth and increasing food demand. The results of the behavioral test showed that the designed model can be used to investigate and simulate the effects of different population growth rate scenarios. Findings illustrated that by increasing population, if no further energy demand management policies were implemented, the total food demand and energy use increase by more than 1.35% and 3.31% respectively. Also, the annual air pollution change during 2014-2030 is expected to be around 4.41%. By changing the population growth rate in the form of population scenarios, the average annual energy demand in the first population scenario will be 20,277 barrels of crude oil and in the second population scenario will be 20049 barrels of crude oil. It seems that the change in the population growth rate will lead to an increase of 3.23% and 2.16% in average annual energy demand, respectively. The results showed that in the first population scenario, with a further increase in population variables, food demand and energy demand, the average change in pollution emission is 4.79%, which is at a higher level than the baseline conditions. In the second population scenario, changes in environmental pollution will be reduced to 4.31%. Therefore, given the effectiveness of population growth on the behavior of the energy system and pollution, the adoption of energy management policies should be considered by policy makers.


Alam, MJ, Begum, IA, Buysse, J & Van Huylenbroeck, G 2012, Energy consumption, carbon emissions and economic growth nexus in Bangladesh: Cointegration and dynamic causality analysis. Energy policy, 45: 217-225.
Alvarez-Herranz, A, Balsalobre-Lorente, D, Shahbaz, M & Cantos, JM 2017, Energy innovation and renewable energy consumption in the correction of air pollution levels. Energy Policy, 105: 386-397.
Ang, JB 2007, Co2 emissions, energy consumption, and output in France. Energy Policy, 35: 4772-4778
Ansari, N, Seifi, A 2012, A system dynamics analysis of energy consumption and corrective policies in Iranian iron and steel industry. Energy, 43: 334-343.
Asayesh, K 2021, Assessing the level of CO2 emission in Iran via the econometric approach. Caspian Journal of Environmental Sciences, 19: 173-181.
Assaraf, OBZ & Orion, N 2005, Development of system thinking skills in the context of earth system education. Journal of Research in Science Teaching, 42: 518-560.
Bahill, AT & Gissing, B 1998, Re-evaluating systems engineering concepts using systems thinking. Systems, Man, and Cybernetics, Part C: Applications and Reviews. IEEE Transactions, 28: 516-527.
 Buzby, JC, Farah-Wells, H & Hyman, J 2014, The estimated amount, value, and calories of postharvest food losses at the retail and consumer levels in the United States. USDA-ERS Economic Information Bulletin Number 121.
Cole, MA, Elliott, RJR & Shimamoto, K 2005, Industrial characteristics, environmental regulations and air pollution: An analysis of the UK manufacturing sector. Journal of Environmental Economics and Management, 50: 121-143.
Costantini, V & Martini, C 2010, A modified environmental Kuznets curve for sustainable development assessment using panel data. International Journal of Global Environmental Issues, 10: 84-122.
Dogan, E & Seker, F 2016, Determinants of CO2 emissions in the European Union: the role of renewable and non-renewable energy. Renewable Energy, 94: 429-439.
Dooley, JJ 1998, Unintended consequences: Energy R & D in a deregulated market. Energy Policy 26: 547-555.
Elif, AS, Turut,A & Ipek, T 2009, The relationship between income and environment in Turkey: Is there an environmental Kuznets Curve? Energy policy, 37: 861-867
Esfandiari, S, Sepahvand, A & Mehrabi BasharAbadi, H 2016, Investigating the effect of agricultural mechanization on the food security of rural households in Iran. Research in Iranian Economics and Agricultural Development, 2-47: 609-618.
Falahi, F & Hekmati Farid, S 2013, Determinants of CO2 emissions in the Iranian provinces (Panel data approach). Iranian Energy Economics, 2: 129-150.
Farajzadeh, Z & Bakhshoodeh, M 2015, Economic and environmental analyses of Iranian energy subsidy reform using Computable General Equilibrium (CGE) model. Energy for Sustainable Development, 27: 147-154.
Feng, YY, Chen, SQ & Zhang, LX 2013, System dynamics modeling for urban energy consumption and CO2 emissions: A case study of Beijing, China. Ecological Modelling, pp. 252-452.
Ford, A 1997, System dynamics and the electric power industry. System Dynamics Review, 13: 57-85.
Ford, FA 1999, Modeling the environment: an introduction to system dynamics models of environmental systems. Island Press.
Forrester, JW 1994, System dynamics, systems thinking, and soft OR. System Dynamics Review, 10: 245-256.
Franco, C, Dyner, I et al. 2000, Microworld for training traders in the Colombian electricity market. Proceedings of the 2000 International Conference of System Dynamics Conference Society, Bergen, Norway.
Franco, S, Mandla, VR & Rao, KRM 2017, Urbanization, energy consumption and emissions in the Indian context A review. Renewable and Sustainable Energy Reviews, 71: 898-907.
Frank, M 2000, Engineering systems thinking and systems thinking. Systems Engineering, 3: 163-168.
Girard, C, Rinaudo, JD, Pulido-Velazquez, M & Caballero, Y 2015, An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario. Environmental Modelling & Software, 69: 42-54.
Hassanzadeh, E, Elshorbagy, A, Wheater, H & Gober, P 2014, Managing water in complex systems: An integrated water resources model for Saskatchewan, Canada. Environmental Modelling & Software, 58: 12-26.
Jacobson, MZ 2009, Review of solutions to global warming, air pollution, and energy security. Energy & Environmental Science, 2: 148-173.
Jacobson, MZ & Delucchi, MA 2011, Providing all global energy with wind, water, and solar power, Part I: Technologies, energy resources, quantities and areas of infrastructure, and materials. Energy Policy, 39: 1170-1190.
Javied, T, Rackow, T & Franke, J 2015, Implementing energy management system to increase energy efficiency in manufacturing companies. Procedia CIRP, 26: 156-161.
Kargar Dehbidi, N, Esmaeili, A & Zibaeei, M 2018, The effect of environmental quality and economic growth on the health expenditure in the MENA region. Environmental Researches, 8: 75-86.
Kiani, B, Mirzamohammadi, S et al. 2010, A survey on the role of system dynamics methodology on fossil fuel resources analysis. International Business Research, 3: 84-93.
Kotir, JH, Smith, C, Brown, G, Marshall, N & Johnstone, R 2016, A system dynamics simulation model for sustainable water resources management and agricultural development in the Volta River Basin, Ghana. Science of the Total Environment, 573: 444-457.
Masoudi, N, Dahmardeh Ghaleno, N, Esfandiari, M 2020, Investigating the impacts of technological innovation and renewable energy on environmental pollution in countries selected by the International Renewable Energy Agency: A quantile regression approach. Caspian Journal of Environmental Sciences, 18: 97-107.
Meidani, AAN & Zabihi, M 2014, Energy consumption and real GDP in Iran. International Journal of Energy Economics and Policy, 4: 15.
Mendiluce, M, Pérez-Arriaga, I & Ocaña, C 2010, Comparison of the evolution of energy intensity in Spain and in the EU15. Why Spain Differ? Energy Policy 38: 639-645.
Menyah, K & Wolde-Rufael, Y 2010, Energy consumption, pollutant emissions and economic growth in South Africa. Energy economics, 32: 1374-1382.
Mirchi, A 2013, System dynamics modeling as a quantitative-qualitative framework for sustainable water resources management: insights for water quality policy in the Great Lakes Region. Doctoral Dissertation, Michigan Technological University, 207 p.
Mirzaei, M & Bekri, M 2017, Energy consumption and CO2 emissions in Iran, 2025. Environmental Research, 154: 345-351.
Mutingi, M, Mbohwa, C & Kommula, VP 2017, System dynamics approaches to energy policy modelling and simulation. Energy Procedia, 141: 532-539.
Pasqualino, R, Monasterolo, I & Jones, A 2019, An Integrated global food and energy security system dynamics model for addressing systemic risk. Sustainability, 11: 3995.
Ranjbarpour, R, Haghighat, J, Karimi Takanel, Z & Mardi Biveh Rah, R 2014, Investigating the effect of investment in the agricultural sector on food prices in Iran. Journal of Agricultural Economics Research, 6: 71-91.
Shabanzadeh, M, Mahmoudi, A & Esfnjari kenari, R 2014, Investigating the effect of transferring global prices to domestic markets for specific products of Iran's agricultural sector. Journal of Agricultural Economics and Development, 29: 55-67.
Simonovic, SP 2012, Managing water resources: methods and tools for a systems approach. Routledge.
Stave, KA 2002, A system dynamics model to facilitate public understanding of water management options in Las Vegas, Nevada. Journal of Environmental Management, 67: 303-313.
Sterman, JD 2000, Business dynamics, systems thinking and modeling for a complex world (No. HD30. 2 S7835), Boston, Corpus ID: 18871550.
Suh, D 2015, Declining energy intensity in the U.S. agricultural sector: Implications for factor substitution and technological change. Sustainability, 7: 13192-13205.
Wang, J, Rothausen, SGSA et al. 2015, China’s water–energy nexus: Greenhouse-gas emissions from groundwater use for agriculture. Environmental Research Letters, 7: 14-35.
Xu, Y & Szmerekovsky, J 2017, System dynamic modeling of energy savings in the US food industry. Journal of Cleaner Production, 165: 13-26.
Yuan, XL & Zuo J 2011, Transition to low carbon energy policies in China—From the Five-Year Plan perspective. Energy Policy, 39: 3855-3859.
Zamani, M 2007, Energy consumption and economic activities in Iran. Energy economics, 29: 1135-1140.
Zarghami, M & Akbariyeh, S 2012, System dynamics modeling for complex urban water systems: Application to Tabriz, Iran. Resources, Conservation and Recycling, 60: 99-106.
Zeinali Ghasemi, Z, Mousavi, SN, Najafi, B 2020, Effects of Implementation of Green Tax on environmental Pollutants’ Dispersion on Macroeconomic Variables: Application of Multi-Regional General Equilibrium Model. Caspian Journal of Environmental Sciences, 18:181-192
Zhang, DS, Aunan, K, Seip, HM et al. 2010, The assessment of health damage caused by air pollution and its implication for policy making in Taiyuan, Shanxi, China. Energy Policy, 38: 491-502.