Research article

Drivers of changes in natural resources consumption of Central African countries

  • Received: 13 December 2021 Revised: 14 March 2022 Accepted: 24 March 2022 Published: 29 April 2022
  • Consumption of nine different natural resources has kept an increasing trend in Central African countries from 1970 to 2018. This study therefore, investigates the changes and major determinants that have driven the patterns of resource use in six Central African countries over almost fifty years. We used the logarithmic mean Divisia index (LMDI) method to quantitatively analyze different effects of technology, affluence and population associated with domestic material consumption (DMC) of Cameroon, Chad, Central African Republic, Equatorial Guinea, Democratic Republic of the Congo and Gabon from 1970 to 2018. We further subdivided the affluence effect into energy productivity (GDP/energy) and per capita energy use (energy/cap) and conducted a four-factor LMDI analysis of Cameroon as a case study. The results highlight that decreased affluence during certain periods has slowed down DMC growth in four of six Central African countries except for Cameroon and Equatorial Guinea, while significant technology offset in Equatorial Guinea reduces DMC growth by 28%. Population remains the main positive driving factor of DMC growth, with the highest share in the Democratic Republic of the Congo. The case of Cameroon shows that technological intensity and energy intensity play different roles in changing DMC. This study confirms that the rising population and economic growth, combined with a gradual improvement in technology in the region are insufficient to reduce natural resource use. A stringent management plan of natural resources for Central African countries should focus on technological improvement while remaining balanced with the future demand for socioeconomic development in the coming decades.

    Citation: Yvette Baninla, Qian Zhang, Xiaoqi Zheng, Yonglong Lu. Drivers of changes in natural resources consumption of Central African countries[J]. Clean Technologies and Recycling, 2022, 2(2): 80-102. doi: 10.3934/ctr.2022005

    Related Papers:

  • Consumption of nine different natural resources has kept an increasing trend in Central African countries from 1970 to 2018. This study therefore, investigates the changes and major determinants that have driven the patterns of resource use in six Central African countries over almost fifty years. We used the logarithmic mean Divisia index (LMDI) method to quantitatively analyze different effects of technology, affluence and population associated with domestic material consumption (DMC) of Cameroon, Chad, Central African Republic, Equatorial Guinea, Democratic Republic of the Congo and Gabon from 1970 to 2018. We further subdivided the affluence effect into energy productivity (GDP/energy) and per capita energy use (energy/cap) and conducted a four-factor LMDI analysis of Cameroon as a case study. The results highlight that decreased affluence during certain periods has slowed down DMC growth in four of six Central African countries except for Cameroon and Equatorial Guinea, while significant technology offset in Equatorial Guinea reduces DMC growth by 28%. Population remains the main positive driving factor of DMC growth, with the highest share in the Democratic Republic of the Congo. The case of Cameroon shows that technological intensity and energy intensity play different roles in changing DMC. This study confirms that the rising population and economic growth, combined with a gradual improvement in technology in the region are insufficient to reduce natural resource use. A stringent management plan of natural resources for Central African countries should focus on technological improvement while remaining balanced with the future demand for socioeconomic development in the coming decades.



    加载中


    [1] UNEP, Decoupling natural resource use and environmental impacts from economic growth. United Nations Environment Program, 2011. Available from: https://www.resourcepanel.org/reports/decoupling-natural-resource-use-and-environmental-impacts-economic-growth.
    [2] Nilsson M, Griggs D, Visbeck M (2016) Policy: map the interactions between Sustainable Development Goals. Nature 534: 320–322. https://doi.org/10.1038/534320a doi: 10.1038/534320a
    [3] Van Soest HL, Van Vuuren DP, Hilaire J, et al. (2019) Analysing interactions among sustainable development goals with integrated assessment models. Glob Transit 1: 210–225. https://doi.org/10.1016/j.glt.2019.10.004 doi: 10.1016/j.glt.2019.10.004
    [4] Zhang Q, Liu S, Wang T, et al. (2019) Urbanization impacts on greenhouse gas (GHG) emissions of the water infrastructure in China: Trade-offs among sustainable development goals (SDGs). J Cleaner Prod 232: 474–486. https://doi.org/10.1016/j.jclepro.2019.05.333 doi: 10.1016/j.jclepro.2019.05.333
    [5] Wallace KJ, Kim MK, Rogers A, et al. (2020) Classifying human wellbeing values for planning the conservation and use of natural resources. J Environ Manage 256: 109955. https://doi.org/10.1016/j.jenvman.2019.109955 doi: 10.1016/j.jenvman.2019.109955
    [6] International Resource Panel (2011) Decoupling Natural Resource Use and Environmental Impacts from Economic Growth, UNEP/Earthprint.
    [7] Simonis UE (2013) Decoupling natural resource use and environmental impacts from economic growth. Int J Soc Econ 40: 385–386. https://doi.org/10.1108/03068291311305044 doi: 10.1108/03068291311305044
    [8] Haberl H, Fischer‐Kowalski M, Krausmann F, et al. (2011) A socio‐metabolic transition towards sustainability? Challenges for another Great Transformation. Sustain Dev 19: 1–14. https://doi.org/10.1002/sd.410 doi: 10.1002/sd.410
    [9] Moutinho V, Madaleno M, Inglesi-Lotz R, et al. (2018) Factors affecting CO2 emissions in top countries on renewable energies: a LMDI decomposition application. Renewable Sustainable Energy Rev 90: 605–622. https://doi.org/10.1016/j.rser.2018.02.009 doi: 10.1016/j.rser.2018.02.009
    [10] Lin B, Agyeman SD (2019) Assessing Ghana's carbon dioxide emissions through energy consumption structure towards a sustainable development path. J Cleaner Prod 238: 117941. https://doi.org/10.1016/j.jclepro.2019.117941 doi: 10.1016/j.jclepro.2019.117941
    [11] Ang BW, Zhang FQ (2000) A survey of index decomposition analysis in energy and environmental studies. Energy 25 1149–1176. https://doi.org/10.1016/S0360-5442(00)00039-6 doi: 10.1016/S0360-5442(00)00039-6
    [12] Su B, Ang BW (2012) Structural decomposition analysis applied to energy and emissions: some methodological developments. Energy Econ 34: 177–188. https://doi.org/10.1016/j.eneco.2011.10.009 doi: 10.1016/j.eneco.2011.10.009
    [13] Ang BW, Liu FL (2001) A new energy decomposition method: perfect in decomposition and consistent in aggregation. Energy 26: 537–548. https://doi.org/10.1016/S0360-5442(01)00022-6 doi: 10.1016/S0360-5442(01)00022-6
    [14] Yang J, Cai W, Ma M, et al. (2020) Driving forces of China's CO2 emissions from energy consumption based on Kaya-LMDI methods. Sci Total Environ 711: 134569. https://doi.org/10.1016/j.scitotenv.2019.134569 doi: 10.1016/j.scitotenv.2019.134569
    [15] Wang L, Wang Y, He H, et al. (2020) Driving force analysis of the nitrogen oxides intensity related to electricity sector in China based on the LMDI method. J Cleaner Prod 242: 118364. https://doi.org/10.1016/j.jclepro.2019.118364 doi: 10.1016/j.jclepro.2019.118364
    [16] Steckel JC, Hilaire J, Jakob M, et al. (2019) Coal and carbonization in sub-Saharan Africa. Nat Clim Change 10: 83–88. https://doi.org/10.1038/s41558-019-0649-8 doi: 10.1038/s41558-019-0649-8
    [17] Pothen F, Schymura M (2015). Bigger cakes with fewer ingredients? A comparison of material use of the world economy. Ecol Econ 109: 109–121. https://doi.org/10.1016/j.ecolecon.2014.10.009 doi: 10.1016/j.ecolecon.2014.10.009
    [18] Steinberger JK, Krausmann F, Getzner M et al. (2013) Development and dematerialization: an international study. PLoS One 8: e70385. https://doi.org/10.1371/journal.pone.0070385 doi: 10.1371/journal.pone.0070385
    [19] Wiedmann TO, Schandl H, Lenzen M, et al. (2015) The material footprint of nations. P Natl Acad Sci USA 112: 6271–6276. https://doi.org/10.1073/pnas.1220362110 doi: 10.1073/pnas.1220362110
    [20] Weinzettel J, Kovanda J (2011) Structural decomposition analysis of raw material consumption: the case of the Czech Republic. J Ind Ecol 15: 893–907. https://doi.org/10.1111/j.1530-9290.2011.00378.x doi: 10.1111/j.1530-9290.2011.00378.x
    [21] Azami S, Hajiloui MM (2022) How does the decomposition approach explain changes in Iran's energy consumption? What are the driving factors? Clean Responsible Consum 4: 100054. https://doi.org/10.1016/j.clrc.2022.100054 doi: 10.1016/j.clrc.2022.100054
    [22] Zhang J, Wang H, Ma L, et al. (2021) Structural path decomposition analysis of resource utilization in China, 1997–2017. J Cleaner Prod 322: 129006. https://doi.org/10.1016/j.jclepro.2021.129006 doi: 10.1016/j.jclepro.2021.129006
    [23] Krausmann F, Wiedenhofer D, Haberl H (2020) Growing stocks of buildings, infrastructures and machinery as key challenge for compliance with climate targets. Global Environ Chang 61: 102034. https://doi.org/10.1016/j.gloenvcha.2020.102034 doi: 10.1016/j.gloenvcha.2020.102034
    [24] Eyre N, Killip G (2019) Shifting the Focus: Energy Demand in a Net-Zero Carbon UK, 1 Ed., Oxford: Centre for Research into Energy Demand Solutions.
    [25] Gonzalez Hernandez A (2018) Site-level resource efficiency analysis[PhD's thesis]. University of Cambridge, United Kingdom.
    [26] Baninla Y, Lu Y, Zhang Q, et al. (2020) Material use and resource efficiency of African sub-regions. J Cleaner Prod 247: 119092. https://doi.org/10.1016/j.jclepro.2019.119092 doi: 10.1016/j.jclepro.2019.119092
    [27] OECD Statistics Database, OECD Statistics Database Domestic Material Consumption and Material Footprint. OECD, 2020. Available from: https://stats.oecd.org/Index.aspx?DataSetCode=MATERIAL_RESOURCES.
    [28] Ward JD, Sutton PC, Werner AD, et al. (2016) Is decoupling GDP growth from environmental impact possible? PLoS One 11: e0164733. https://doi.org/10.1371/journal.pone.0164733 doi: 10.1371/journal.pone.0164733
    [29] Bithas K, Kalimeris P (2018) Unmasking decoupling: redefining the resource intensity of the economy. Sci Total Environ 619: 338–351. https://doi.org/10.1016/j.scitotenv.2017.11.061 doi: 10.1016/j.scitotenv.2017.11.061
    [30] Pao HT, Chen CC (2019) Decoupling strategies: CO2 emissions, energy resources, and economic growth in the Group of Twenty. J Cleaner Prod 206: 907–919. https://doi.org/10.1016/j.jclepro.2018.09.190 doi: 10.1016/j.jclepro.2018.09.190
    [31] Sanyé-Mengual E, Secchi M, Corrado S, et al. (2019) Assessing the decoupling of economic growth from environmental impacts in the European Union: A consumption-based approach. J Cleaner Prod 236: 117535. https://doi.org/10.1016/j.jclepro.2019.07.010 doi: 10.1016/j.jclepro.2019.07.010
    [32] Liu Z, Xin L (2019) Dynamic analysis of spatial convergence of green total factor productivity in China's primary provinces along its Belt and Road Initiative. Chin J Popul Resour Environ 17: 101–112. https://doi.org/10.1080/10042857.2019.1611342 doi: 10.1080/10042857.2019.1611342
    [33] Ang BW (2005) The LMDI approach to decomposition analysis: a practical guide. Energ Policy 33: 867–871. https://doi.org/10.1016/j.enpol.2003.10.010 doi: 10.1016/j.enpol.2003.10.010
    [34] Wang W, Li M, Zhang M (2017) Study on the changes of the decoupling indicator between energy-related CO2 emission and GDP in China. Energy 128: 11–18. https://doi.org/10.1016/j.energy.2017.04.004 doi: 10.1016/j.energy.2017.04.004
    [35] Chen J, Wang P, Cui L (2018) Decomposition and decoupling analysis of CO2 emissions in OECD. Appl Energy 231: 937–950. https://doi.org/10.1016/j.apenergy.2018.09.179 doi: 10.1016/j.apenergy.2018.09.179
    [36] Du G, Sun C, Ouyang X, et al. (2018) A decomposition analysis of energy-related CO2 emissions in Chinese six high-energy intensive industries. J Clean Prod 184: 1102–1112. https://doi.org/10.1016/j.jclepro.2018.02.304 doi: 10.1016/j.jclepro.2018.02.304
    [37] Zheng X, Lu Y, Yuan J, et al. (2020) Drivers of change in China's energy-related CO2 emissions. P Natl Acad Sci USA 117: 29–36. https://doi.org/10.1073/pnas.1908513117 doi: 10.1073/pnas.1908513117
    [38] Shao S, Yang L, Gan C, et al. (2016) Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China). Renewable Sustainable Energy Rev 55: 516–536. https://doi.org/10.1016/j.rser.2015.10.081 doi: 10.1016/j.rser.2015.10.081
    [39] Li H, Zhao Y, Qiao X, et al. (2017) Identifying the driving forces of national and regional CO2 emissions in China: based on temporal and spatial decomposition analysis models. Energy Econ 68: 522–538. https://doi.org/10.1016/j.eneco.2017.10.024 doi: 10.1016/j.eneco.2017.10.024
    [40] Guan D, Meng J, Reiner DM, et al. (2018) Structural decline in China's CO2 emissions through transitions in industry and energy systems. Nat Geosci 11: 551–555. https://doi.org/10.1038/s41561-018-0161-1 doi: 10.1038/s41561-018-0161-1
    [41] Wu Y, Tam VW, Shuai C, et al. (2019) Decoupling China's economic growth from carbon emissions: Empirical studies from 30 Chinese provinces (2001–2015). Sci Total Environ 656: 576–588. https://doi.org/10.1016/j.scitotenv.2018.11.384 doi: 10.1016/j.scitotenv.2018.11.384
    [42] Bekun FV, Alola AA, Gyamfi BA, et al. (2021) The environmental aspects of conventional and clean energy policy in sub-Saharan Africa: is N-shaped hypothesis valid? Environ Sci Pollut R 28: 66695–66708. https://doi.org/10.1007/s11356-021-14758-w doi: 10.1007/s11356-021-14758-w
    [43] Adedoyin FF, Nwulu N, Bekun FV (2021) Environmental degradation, energy consumption and sustainable development: accounting for the role of economic complexities with evidence from World Bank income clusters. Bus Strategy Environ 30: 2727–2740. https://doi.org/10.1002/bse.2774 doi: 10.1002/bse.2774
    [44] Kwakwa PA, Alhassan H, Aboagye S (2018) Environmental Kuznets curve hypothesis in a financial development and natural resource extraction context: evidence from Tunisia. Quant Finance Econ 2: 981–1000. https://doi.org/10.3934/QFE.2018.4.981 doi: 10.3934/QFE.2018.4.981
    [45] Gyamfi BA (2022) Consumption-based carbon emission and foreign direct investment in oil-producing Sub-Sahara African countries: the role of natural resources and urbanization. Environ Sci Pollut R 29: 13154–13166. https://doi.org/10.1007/s11356-021-16509-3 doi: 10.1007/s11356-021-16509-3
    [46] Kwakwa PA, Alhassan H, Adu G (2020) Effect of natural resources extraction on energy consumption and carbon dioxide emission in Ghana. Int J Energy Sect Manag 14: 20–39. https://doi.org/10.1108/IJESM-09-2018-0003 doi: 10.1108/IJESM-09-2018-0003
    [47] Wiedenhofer D, Fishman T, Plank B, et al. (2021) Prospects for a saturation of humanity's resource use? An analysis of material stocks and flows in nine world regions from 1900 to 2035. Global Environ Chang 71: 102410. https://doi.org/10.1016/j.gloenvcha.2021.102410 doi: 10.1016/j.gloenvcha.2021.102410
    [48] Haberl H, Wiedenhofer D, Virág D, et al. (2020) A systematic review of the evidence on decoupling of GDP, resource use and GHG emissions, part Ⅱ: synthesizing the insights. Environ Res Lett 15: 065003. https://doi.org/10.1088/1748-9326/ab842a doi: 10.1088/1748-9326/ab842a
    [49] Bolt J, Inklaar R, de Jong H, et al. (2018) Rebasing 'Maddison': new income comparisons and the shape of long-run economic development. Maddison Project Database, version 2018. Maddison Project Working Paper 10. Available from: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2018.
    [50] Johansen S, Juselius K (1990) Some structural hypotheses in a multivariate cointegration analysis of the purchasing power parity and the uncovered interest parity for UK. Discussion Papers 90-05, University of Copenhagen.
    [51] Omay T, Emirmahmutoglu F, Denaux ZS (2017) Nonlinear error correction based cointegration test in panel data. Econ Lett 157: 1–4. https://doi.org/10.1016/j.econlet.2017.05.017 doi: 10.1016/j.econlet.2017.05.017
    [52] Odaki M (2015) Cointegration rank tests based on vector autoregressive approximations under alternative hypotheses. Econ Lett 136: 187–189. https://doi.org/10.1016/j.econlet.2015.09.028 doi: 10.1016/j.econlet.2015.09.028
    [53] Aslan A, Kula F, Kalyoncu H (2010) Additional evidence of long-run purchasing power parity with black and official exchange rates. Appl Econ Lett 17: 1379–1382. https://doi.org/10.1080/13504850902967522 doi: 10.1080/13504850902967522
    [54] Kaya Y (1989) Impact of carbon dioxide emission control on GNP growth: interpretation of proposed scenarios. Intergovernmental Panel on Climate Change/Response Strategies Working Group.
    [55] Ang BW, Liu FL, Chew EP (2003) Perfect decomposition techniques in energy and environmental analysis. Energ Policy 31: 1561–1566. https://doi.org/10.1016/S0301-4215(02)00206-9 doi: 10.1016/S0301-4215(02)00206-9
    [56] Bianchi M, del Valle I, Tapia C (2021) Material productivity, socioeconomic drivers and economic structures: A panel study for European regions. Ecol Econ 183: 106948. https://doi.org/10.1016/j.ecolecon.2021.106948 doi: 10.1016/j.ecolecon.2021.106948
    [57] Weisz H, Krausmann F, Amann C, et al. (2006) The physical economy of the European Union: Cross-country comparison and determinants of material consumption. Ecol Econ 58: 676–698. https://doi.org/10.1016/j.ecolecon.2005.08.016 doi: 10.1016/j.ecolecon.2005.08.016
    [58] Kassouri Y, Alola AA, Savaş S (2021) The dynamics of material consumption in phases of the economic cycle for selected emerging countries. Resour Policy 70: 101918. https://doi.org/10.1016/j.resourpol.2020.101918 doi: 10.1016/j.resourpol.2020.101918
    [59] Karakaya E, Sarı E, Alataş S (2021) What drives material use in the EU? Evidence from club convergence and decomposition analysis on domestic material consumption and material footprint. Resour Policy 70: 101904. https://doi.org/10.1016/j.resourpol.2020.101904 doi: 10.1016/j.resourpol.2020.101904
    [60] Jia H, Li T, Wang A, et al. (2021) Decoupling analysis of economic growth and mineral resources consumption in China from 1992 to 2017: A comparison between tonnage and exergy perspective. Resour Policy 74: 102448. https://doi.org/10.1016/j.resourpol.2021.102448 doi: 10.1016/j.resourpol.2021.102448
    [61] Khan I, Zakari A, Ahmad M, et al. (2022) Linking energy transitions, energy consumption, and environmental sustainability in OECD countries. Gondwana Res 103: 445–457. https://doi.org/10.1016/j.gr.2021.10.026 doi: 10.1016/j.gr.2021.10.026
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(11257) PDF downloads(81) Cited by(0)

Article outline

Figures and Tables

Figures(11)  /  Tables(1)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog