Abstract
Energy consumption and CO2 emissions are agreed as the main causes of global warming and climate change, which are causing several extreme weather events in recent decades. However, there is little understanding how humans adjust their behaviours in energy consumption and emissions in responding to these natural threats. This study aims to examine the influences of exposure, susceptibility, and vulnerability to five natural hazards on CO2 emissions, energy intensity, renewable energy, and electricity consumption. The feasible generalized least squares model and several panel estimates are applied for a global sample of 161 countries from 2011 to 2018. The empirical results provide interesting findings. First, exposure, susceptibility, and vulnerability appear to reduce electricity usage, renewable energy consumption, energy intensity, and CO2 emissions in the global sample. Second, the negative effects of exposure, susceptibility, and vulnerability are consistent across four income groups (high-income; upper-middle-income; lower-middle-income; and low-income) except for some interesting differences. Exposure appears to increase renewable energy consumption significantly in upper-middle and high-income, while susceptibility has a significant positive influence on renewable energy consumption in low-, upper-middle, and high-income. Third, the negative impact is also documented in seven regions, with the exception of some interesting findings: threats from nature appear to increase CO2 emissions and energy intensity in the Middle East and North Africa, South Asia, and Europe and Central Asia, while they stimulate the use of renewable energy in Latin America and Caribbean. Interestingly, exposure and susceptibility appear to induce renewable energy transformation in Europe and Central Asia.
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Source: US International Energy Administration
Source: US International Energy Administration
Source: US International Energy Administration
Source: The WorldRiskIndex
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Notes
Due to data the availability from the US International Energy Administration. Further detail is explained in the data section.
Susceptibility to natural hazards is the likelihood of suffering harm. Vulnerability to natural hazards means susceptibility, lacking capabilities to reduce the negative consequences of natural hazards, and lacking capabilities for long-term strategies for societal change (World Risk Index report, 2020).
In other words, economic development and environmental quality have a U-shaped relationship.
Most studies use CO2 emissions per capita to exclude the population from assessing impact. It is also important to evaluate the intensity of CO2 emissions (in per capita form).
We are thankful to a helpful comment from an anonymous reviewer on this point.
It is worthy to notice that natural threats might affect on economic development, which then impacts on energy consumption and CO2 emissions. This implies that there may be multicollinearity between natural threats with income variable in our model. We have checked the multicollinearity by variance inflation factors (VIFs) for each proxy of natural threats before main estimates. The results show less probability of multicollinearity among variables. We are thankful to the comment and helpful suggestion for an anonymous reviewer.
All results are consistent. To save space of the manuscript, we do not report here. The results can be provided upon request.
References
Ali MU, Gong Z, Ali MU, Wu X, Yao C (2021) Fossil energy consumption, economic development, inward FDI impact on CO2 emissions in Pakistan: testing EKC hypothesis through ARDL model. Int J Financ Econ 26(3):3210–3221. https://doi.org/10.1002/ijfe.1958
Azam M, Khan AQ, Zaman K, Ahmad M (2015) Factors determining energy consumption: evidence from Indonesia, Malaysia and Thailand. Renew Sustain Energy Rev 42:1123–1131. https://doi.org/10.1016/j.rser.2014.10.061
Bailey D, Katz JN (2011) Implementing panel corrected standard errors in R: the pcse package. J Stat Softw 42(CS1):1–11
Bernardini O, Galli R (1993) Dematerialization: long-term trends in the intensity of use of materials and energy. Futures 25(4):431–448. https://doi.org/10.1016/0016-3287(93)90005-E
Biardeau LT, Davis LW, Gertler P, Wolfram C (2020) Heat exposure and global air conditioning. Nat Sustain 3(1):25–28. https://doi.org/10.1038/s41893-019-0441-9
Burger J, Gochfeld M (1998) The tragedy of the commons 30 years later. Environment: Science and Policy for Sustainable Development, 40(10), 4–13, https://doi.org/10.1080/00139159809605104.
Canh NP, Binh NT, Thanh SD, Schinckus C (2020a) Determinants of foreign direct investment inflows: the role of economic policy uncertainty. Int Econ 161:159–172. https://doi.org/10.1016/j.inteco.2019.11.012
Canh NP, Thanh SD, Nasir MA (2020b) Nexus between financial development & energy intensity: two sides of a coin? J Environ Manage 270:110902. https://doi.org/10.1016/j.jenvman.2020.110902
Canh NP, Schinckus C, Thanh SD, Chong FHL (2021) The determinants of the energy consumption: a shadow economy-based perspective. Energy 225:120210. https://doi.org/10.1016/j.energy.2021.120210
Cappelli F, Costantini V, Consoli D (2021) The trap of climate change-induced “natural” disasters and inequality. Glob Environ Chang 70:102329. https://doi.org/10.1016/j.gloenvcha.2021.102329
Danish, Zhang B, Wang B, Wang Z (2017) Role of renewable energy and non-renewable energy consumption on EKC: Evidence from Pakistan. J Clean Prod, 156, 855-864. https://doi.org/10.1016/j.jclepro.2017.03.203
Dogan E, Turkekul B (2016) CO2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the EKC hypothesis for the USA. Environ Sci Pollut Res 23(2):1203–1213. https://doi.org/10.1007/s11356-015-5323-8
Doytch N, Klein YL (2018) The impact of natural disasters on energy consumption: an analysis of renewable and nonrenewable energy demand in the residential and industrial sectors. Environ Prog Sustainable Energy 37(1):37–45. https://doi.org/10.1002/ep.12640
Ehrlich PR, Holdren JP (1971) Impact of population growth. Science, 171(3977), 1212–1217. https://www.jstor.org/stable/1731166. Accessed 02 Dec 2021
Elks S (2021) Exploring the relationship between climate change and extreme weather. https://www.weforum.org/agenda/2021/08/can-we-really-blame-extreme-weather-events-on-climate-change/?fbclid=IwAR2phIvQCB6tltNUe_ntUaHlbuNuVXfx5h7zFbGMl74Tqu-EvVHT5zJUS54. Accessed Sep 03 2021.
Grothmann T, Reusswig F (2006) People at risk of flooding: why some residents take precautionary action while others do not. Nat Hazards 38(1):101–120. https://doi.org/10.1007/s11069-005-8604-6
Hansen CB (2007) Generalized least squares inference in panel and multilevel models with serial correlation and fixed effects. J Econom 140(2):670–694
Hardin G (2009) The tragedy of the commons. J Nat Resour Policy Res 1(3):243–253. https://doi.org/10.1080/19390450903037302
Hilft BE (2020) WorldRiskReport 2020. WorldRiskReport. Berlin, Germany: Bündnis Entwicklung Hilft
IPCC (2018) Summary for policymakers. Intergovernmental Panel on Climate Change (IPCC). https://www.ipcc.ch/site/assets/uploads/2018/10/SR15_SPM_version_stand_alone_LR.pdf. Accessed Aug 14 2021.
IPCC (2021) Climate change widespread, rapid, and intensifying. Intergovernmental Panel on Climate Change (IPCC). https://www.ipcc.ch/2021/08/09/ar6-wg1-20210809-pr/. Accessed Aug 14 2021.
IRENA (2021) Renewable Capacity Statistics 2021. https://www.irena.org/publications/2021/March/Renewable-Capacity-Statistics-2021. Accessed Sep 03 2021.
Işık C, Ongan S, Özdemir D (2019) Testing the EKC hypothesis for ten US states: an application of heterogeneous panel estimation method. Environ Sci Pollut Res 26(11):10846–10853. https://doi.org/10.1007/s11356-019-04514-6
Kariya T, Kurata H (2004) Generalized least squares: John Wiley & Sons
Kates RW (1971) Natural hazard in human ecological perspective: hypotheses and models. Econ Geogr 47(3):438–451. https://doi.org/10.2307/142820
Koondhar MA, Shahbaz M, Memon KA, Ozturk I, Kong R (2021) A visualization review analysis of the last two decades for environmental Kuznets curve “EKC” based on co-citation analysis theory and pathfinder network scaling algorithms. Environ Sci Pollut Res 28(13):16690–16706. https://doi.org/10.1007/s11356-020-12199-5
Krey V, O’Neill BC, van Ruijven B, Chaturvedi V, Daioglou V, Eom J et al (2012) Urban and rural energy use and carbon dioxide emissions in Asia. Energy Econ 34:S272–S283. https://doi.org/10.1016/j.eneco.2012.04.013
Le T-H, Nguyen CP (2021) The impact of tourism on carbon dioxide emissions: insights from 95 countries. Appl Econ 53(2):235–261. https://doi.org/10.1080/00036846.2020.1804051
Mahmood H, Alkhateeb TTY, Furqan M (2020) Industrialization, urbanization and CO2 emissions in Saudi Arabia: Asymmetry analysis. Energy Rep 6:1553–1560. https://doi.org/10.1016/j.egyr.2020.06.004
Malenbaum W (1978) World demand for raw materials in 1985 and 2000: McGraw-Hill E/Mj Mining Informational Services
Mardani A, Streimikiene D, Cavallaro F, Loganathan N, Khoshnoudi M (2019) Carbon dioxide (CO2) emissions and economic growth: a systematic review of two decades of research from 1995 to 2017. Sci Total Environ 649:31–49. https://doi.org/10.1016/j.scitotenv.2018.08.229
Masterson V (2021) Renewables were the world’s cheapest source of energy in 2020, new report shows. https://www.weforum.org/agenda/2021/07/renewables-cheapest-energy-source/. Accessed 24 Jan 2022.
Nguyen CP, Le T-H, Schinckus C, Su TD (2021) Determinants of agricultural emissions: panel data evidence from a global sample. Environ Dev Econ 26(2):109–130. https://doi.org/10.1017/S1355770X20000315
Nguyen CP, Thanh SD, Nguyen B (2020) Economic uncertainty and tourism consumption. Tour Econ, 1354816620981519. https://doi.org/10.1177/1354816620981519
Panja P (2021) Deforestation, Carbon dioxide increase in the atmosphere and global warming: A modelling study. Int J Model Simul 41(3):209–219. https://doi.org/10.1080/02286203.2019.1707501
Pata UK, Aydin M (2020) Testing the EKC hypothesis for the top six hydropower energy-consuming countries: evidence from Fourier Bootstrap ARDL procedure. J Clean Prod 264:121699. https://doi.org/10.1016/j.jclepro.2020.121699
Pata UK, Caglar AE (2021) Investigating the EKC hypothesis with renewable energy consumption, human capital, globalization and trade openness for China: Evidence from augmented ARDL approach with a structural break. Energy 216:119220. https://doi.org/10.1016/j.energy.2020.119220
Pauleit S, Ambrose-Oji B, Andersson E, Anton B, Buijs A, Haase D et al (2019) Advancing urban green infrastructure in Europe: Outcomes and reflections from the GREEN SURGE project. Urban For Urban Green 40:4–16. https://doi.org/10.1016/j.ufug.2018.10.006
Phuc Nguyen C, Schinckus C, Dinh Su T (2020) Economic integration and CO2 emissions: evidence from emerging economies. Clim Dev, 12(4), 369-384. https://doi.org/10.1080/17565529.2019.1630350
Popp DC (2001) The effect of new technology on energy consumption. Resour Energy Econ 23(3):215–239. https://doi.org/10.1016/S0928-7655(00)00045-2
Richard Eiser J, Bostrom A, Burton I, Johnston DM, McClure J, Paton D et al (2012) Risk interpretation and action: a conceptual framework for responses to natural hazards. Int J Disaster Risk Reduct 1:5–16. https://doi.org/10.1016/j.ijdrr.2012.05.002
Richmond AK, Kaufmann RK (2006) Is there a turning point in the relationship between income and energy use and/or carbon emissions? Ecol Econ 56(2):176–189. https://doi.org/10.1016/j.ecolecon.2005.01.011
Rubio MdM, Tafunell X (2014) Latin American hydropower: a century of uneven evolution. Renew Sust Energ Rev, 38, 323-334. https://doi.org/10.1016/j.rser.2014.05.068
Sadorsky P (2013) Do urbanization and industrialization affect energy intensity in developing countries? Energy Econ 37:52–59. https://doi.org/10.1016/j.eneco.2013.01.009
Sarkodie SA, Strezov V (2019) A review on Environmental Kuznets curve hypothesis using bibliometric and meta-analysis. Sci Total Environ 649:128–145. https://doi.org/10.1016/j.scitotenv.2018.08.276
Shahzad U, Fareed Z, Shahzad F, Shahzad K (2021) Investigating the nexus between economic complexity, energy consumption and ecological footprint for the United States: New insights from quantile methods. J Clean Prod 279:123806. https://doi.org/10.1016/j.jclepro.2020.123806
Shaktawat A, Vadhera S (2021) Risk management of hydropower projects for sustainable development: a review. Environ Dev Sustain 23(1):45–76. https://doi.org/10.1007/s10668-020-00607-2
Sharma R, Sinha A, Kautish P (2021) Does renewable energy consumption reduce ecological footprint? Evidence from eight developing countries of Asia. J Clean Prod 285:124867. https://doi.org/10.1016/j.jclepro.2020.124867
Sun J (1999) The nature of CO2 emission Kuznets curve. Energy Policy 27(12):691–694. https://doi.org/10.1016/S0301-4215(99)00056-7
Sun L, Zhang T, Liu S, Wang K, Rogers T, Yao L et al (2021) Reducing energy consumption and pollution in the urban transportation sector: a review of policies and regulations in Beijing. J Clean Prod 285:125339. https://doi.org/10.1016/j.jclepro.2020.125339
UNEP (2019) Emissions Gap Report 2019. https://wedocs.unep.org/bitstream/handle/20.500.11822/30797/EGR2019.pdf. Accessed Aug 14 2021.
Usman O, Iorember PT, Olanipekun IO (2019) Revisiting the environmental Kuznets curve (EKC) hypothesis in India: the effects of energy consumption and democracy. Environ Sci Pollut Res 26(13):13390–13400. https://doi.org/10.1007/s11356-019-04696-z
Verschuur J, Koks EE, Haque A, Hall JW (2020) Prioritising resilience policies to reduce welfare losses from natural disasters: a case study for coastal Bangladesh. Glob Environ Chang 65:102179. https://doi.org/10.1016/j.gloenvcha.2020.102179
Wachinger G, Renn O, Begg C, Kuhlicke C (2013) The risk perception paradox—implications for governance and communication of natural hazards. Risk Anal 33(6):1049–1065. https://doi.org/10.1111/j.1539-6924.2012.01942.x
Wang Q, Yang X (2019) Urbanization impact on residential energy consumption in China: the roles of income, urbanization level, and urban density. Environ Sci Pollut Res 26(4):3542–3555. https://doi.org/10.1007/s11356-018-3863-4
Zheng W, Walsh PP (2019) Economic growth, urbanization and energy consumption — a provincial level analysis of China. Energy Economics 80:153–162. https://doi.org/10.1016/j.eneco.2019.01.004
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The study is funded by the University of Economics Ho Chi Minh City, Vietnam.
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Nguyen, C.P. The “karma” of impact on the Earth: will humans take responsibility? Evidence of energy consumption and CO2 emissions. Environ Sci Pollut Res 29, 50686–50703 (2022). https://doi.org/10.1007/s11356-022-19461-y
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DOI: https://doi.org/10.1007/s11356-022-19461-y