3,027
Views
23
CrossRef citations to date
0
Altmetric
Articles

The sustainable potential of efficient air-transportation industry and green innovation in realising environmental sustainability in G7 countries

, , &
Pages 3814-3835 | Received 26 Sep 2021, Accepted 03 Nov 2021, Published online: 22 Nov 2021

References

  • Adedoyin, F. F., Bekun, F. V., Driha, O. M., & Balsalobre-Lorente, D. (2020). The effects of air transportation, energy, ICT and FDI on economic growth in the industry 4.0 era: Evidence from the United States. Technological Forecasting and Social Change, 160, 120297.
  • Afrifa, G. A., Tingbani, I., Yamoah, F., & Appiah, G. (2020). Innovation input, governance and climate change: Evidence from emerging countries. Technological Forecasting and Social Change, 161, 120256. https://doi.org/10.1016/j.techfore.2020.120256
  • Ali, S. S., Kaur, R., Persis, D. J., Saha, R., Pattusamy, M., & Sreedharan, V. R. (2020). Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment. Annals of Operations Research, 1–33. https://doi.org/10.1007/s10479-020-03877-1
  • An, H., Razzaq, A., Haseeb, M., & Mihardjo, L. W. (2021). The role of technology innovation and people's connectivity in testing environmental Kuznets curve and pollution heaven hypotheses across the Belt and Road host countries: New evidence from Method of Moments Quantile Regression. Environmental Science and Pollution Research International, 28(5), 5254–5270. https://doi.org/10.1007/s11356-020-10775-3
  • An, H., Razzaq, A., Nawaz, A., Noman, S. M., & Khan, S. A. R. (2021). Nexus between green logistic operations and triple bottom line: Evidence from infrastructure-led Chinese outward foreign direct investment in Belt and Road host countries. Environmental Science and Pollution Research, 28(37), 1–24. https://doi.org/10.1007/s11356-021-12470-3
  • Arter, C. A., & Arunachalam, S. (2021). Assessing the importance of nonlinearity for aircraft emissions' impact on O3 and PM2.5. Science of the Total Environment, 777, 146121. https://doi.org/10.1016/j.scitotenv.2021.146121
  • ATAG. (2020). Facts & figures. Retrieved March 8, 2021, from https://www.atag.org/facts-figures.html
  • Bai, J., & Carrion-I-Silvestre, J. L. (2009). Structural changes, common stochastic trends, and unit roots in panel data. Review of Economic Studies, 76(2), 471–501. https://doi.org/10.1111/j.1467-937X.2008.00530.x
  • Balkanski, Y., Myhre, G., Gauss, M., Rädel, G., Highwood, E. J., & Shine, K. P. (2010). Direct radiative effect of aerosols emitted by transport: From road, shipping and aviation. Atmospheric Chemistry and Physics, 10(10), 4477–4489. https://doi.org/10.5194/acp-10-4477-2010
  • Balsalobre-Lorente, D., Driha, O. M., Bekun, F. V., & Adedoyin, F. F. (2021). The asymmetric impact of air transport on economic growth in Spain: Fresh evidence from the tourism-led growth hypothesis. Current Issues in Tourism, 24(4), 503–519. https://doi.org/10.1080/13683500.2020.1720624
  • Banerjee, A., & Carrion‐i-Silvestre, J. L. (2017). Testing for panel cointegration using common correlated effects estimators. Journal of Time Series Analysis, 38(4), 610–636. https://doi.org/10.1111/jtsa.12234
  • Baumeister, S. (2017). ‘Each flight is different’: Carbon emissions of selected flights in three geographical markets. Transportation Research Part D: Transport and Environment, 57, 1–9. https://doi.org/10.1016/j.trd.2017.08.020
  • Bo, X., Xue, X., Xu, J., Du, X., Zhou, B., & Tang, L. (2019). Aviation's emissions and contribution to the air quality in China. Atmospheric Environment, 201, 121–131. https://doi.org/10.1016/j.atmosenv.2019.01.005
  • Chien, F., Sadiq, M., Nawaz, M. A., Hussain, M. S., Tran, T. D., & Le Thanh, T. (2021). A step toward reducing air pollution in top Asian economies: The role of green energy, eco-innovation, and environmental taxes. Journal of Environmental Management, 297, 113420.
  • Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20(2), 249–272. https://doi.org/10.1016/S0261-5606(00)00048-6
  • Churchill, S. A., Inekwe, J., Smyth, R., & Zhang, X. (2019). R&D intensity and carbon emissions in the G7: 1870–2014. Energy Economics, 80, 30–37. https://doi.org/10.1016/j.eneco.2018.12.020
  • Chudik, A., & Pesaran, M. H. (2015). Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188(2), 393–420.
  • Çoban, S., & Topcu, M. (2013). The nexus between financial development and energy consumption in the EU: A dynamic panel data analysis. Energy Economics, 39, 81–88.
  • Corporan, E., Roquemore, M., Harrison, W., Jacobson, A., & Phelps, D. (2002). Air Force programs to reduce particulate matter emissions from aircraft. In 38th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit (p. 3722).
  • Destek, M. A., & Sarkodie, S. A. (2019). Investigation of environmental Kuznets curve for ecological footprint: The role of energy and financial development. The Science of the Total Environment, 650(Pt 2), 2483–2489.
  • Eberhardt, M., & Teal, F. (2011). Aggregation versus heterogeneity in cross-country growth empirics (No. 11/08). CREDIT Research Paper.
  • Erdogan, S., Adedoyin, F. F., Bekun, F. V., & Sarkodie, S. A. (2020). Testing the transport-induced environmental Kuznets curve hypothesis: The role of air and railway transport. Journal of Air Transport Management, 89, 101935. https://doi.org/10.1016/j.jairtraman.2020.101935
  • Habre, R., Zhou, H., Eckel, S. P., Enebish, T., Fruin, S., Bastain, T., Rappaport, E., & Gilliland, F. (2018). Short-term effects of airport-associated ultrafine particle exposure on lung function and inflammation in adults with asthma. Environment International, 118, 48–59. https://doi.org/10.1016/j.envint.2018.05.031
  • Harris, R. D., & Tzavalis, E. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics, 91(2), 201–226. https://doi.org/10.1016/S0304-4076(98)00076-1
  • Harrison, R. M., Masiol, M., & Vardoulakis, S. (2015). Civil aviation, air pollution and human health. Environmental Research Letters, 10(4), 041001. https://doi.org/10.1088/1748-9326/10/4/041001
  • Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7
  • Khan, Z., Ali, M., Jinyu, L., Shahbaz, M., & Siqun, Y. (2020). Consumption-based carbon emissions and trade nexus: Evidence from nine oil exporting countries. Energy Economics, 89, 104806. https://doi.org/10.1016/j.eneco.2020.104806
  • Khan, Z., Ali, S., Umar, M., Kirikkaleli, D., & Jiao, Z. (2020). Consumption-based carbon emissions and international trade in G7 countries: The role of environmental innovation and renewable energy. Science of the Total Environment, 730, 138945. https://doi.org/10.1016/j.scitotenv.2020.138945
  • Kito, M., Nagashima, F., Kagawa, S., & Nansai, K. (2020). Drivers of CO2 emissions in international aviation: The case of Japan. Environmental Research Letters, 15(10), 104036. https://doi.org/10.1088/1748-9326/ab9e9b
  • Kommenda, N. (2019). How your flight emits as much CO2 as many people do in a year. The Guardian. https://www.theguardian.com/environment/nginteractive/2019/jul/19/carbon-calculator-how-taking-one-flight-emits-as-much-asmany-people-do-in-a-year
  • Lee, B. L., Wilson, C., Pasurka, C. A., Fujii, H., & Managi, S. (2017). Sources of airline productivity from carbon emissions: An analysis of operational performance under good and bad outputs. Journal of Productivity Analysis, 47(3), 223–246. https://doi.org/10.1007/s11123-016-0480-4
  • Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24. https://doi.org/10.1016/S0304-4076(01)00098-7
  • Li, X., Wang, J., Zhang, M., Ouyang, J., & Shi, W. (2020). Regional differences in carbon emission of China’s industries and its decomposition effects. Journal of Cleaner Production, 270, 122528. https://doi.org/10.1016/j.jclepro.2020.122528
  • Lin, W., He, Q., & Yu, H. (2021). The convergence of PM2.5 concentration in Chinese cities: A distribution dynamic approach. Economic Research-Ekonomska Istraživanja, 1–19. https://doi.org/10.1080/1331677X.2021.1967772
  • Ling, G., Razzaq, A., Guo, Y., Fatima, T., & Shahzad, F. (2021). Asymmetric and time-varying linkages between carbon emissions, globalization, natural resources and financial development in China. Environment, Development and Sustainability, 1–29. https://doi.org/10.1007/s10668-021-01724-2
  • Lingyan, M., Zhao, Z., Malik, H. A., Razzaq, A., An, H., & Hassan, M. (2021). Asymmetric impact of fiscal decentralization and environmental innovation on carbon emissions: Evidence from highly decentralized countries. Energy & Environment, 0958305X2110184. https://doi.org/10.1177/0958305X211018453
  • Liu, X., Zhou, D., Zhou, P., & Wang, Q. (2017). Dynamic carbon emission performance of Chinese airlines: A global Malmquist index analysis. Journal of Air Transport Management, 65, 99–109. https://doi.org/10.1016/j.jairtraman.2017.09.009
  • Lluís Carrion‐i‐Silvestre, J., Del Barrio-Castro, T., & López-Bazo, E. (2005). Breaking the panels: An application to the GDP per capita. The Econometrics Journal, 8(2), 159–175.
  • Lo, P. L., Martini, G., Porta, F., & Scotti, D. (2020). The determinants of CO2 emissions of air transport passenger traffic: An analysis of Lombardy (Italy). Transport Policy, 91, 108–119. https://doi.org/10.1016/j.tranpol.2018.11.010
  • Lu, Y., Shao, M., Zheng, C., Ji, H., Gao, X., & Wang, Q. G. (2020). Air pollutant emissions from fossil fuel consumption in China: Current status and future predictions. Atmospheric Environment, 231, 117536. https://doi.org/10.1016/j.atmosenv.2020.117536
  • Malhotra, A., & Schmidt, T. S. (2020). Accelerating low-carbon innovation. Joule, 4(11), 2259–2267. https://doi.org/10.1016/j.joule.2020.09.004
  • Mavi, R. K., Fathi, A., Saen, R. F., & Mavi, N. K. (2019). Eco-innovation in transportation industry: A double frontier common weights analysis with ideal point method for Malmquist productivity index. Resources, Conservation and Recycling, 147, 39–48. https://doi.org/10.1016/j.resconrec.2019.04.017
  • Moniruzzaman, C. G., Bowden, J., & Arunachalam, S. (2020). Aircraft landing and takeoff emission impacts on surface O3 and PM2.5 through aerosol direct feedback effects estimated by the coupled WRF-CMAQ model. Atmospheric Environment, 243, 117859. https://doi.org/10.1016/j.atmosenv.2020.117859
  • Moon, H. R., & Perron, B. (2012). Beyond panel unit root tests: Using multiple testing to determine the nonstationarity properties of individual series in a panel. Journal of Econometrics, 169(1), 29–33. https://doi.org/10.1016/j.jeconom.2012.01.008
  • Mukherjee, A., & Agrawal, M. (2017). A global perspective of fine particulate matter pollution and its health effects. Reviews of Environmental Contamination and Toxicology, 244, 5–51.
  • Naghawi, H. (2019). Econometric modeling for international passenger air travel demand in Jordan. Jordan Journal of Civil Engineering, 13(3), 377–385.
  • Nasreen, S., Saidi, S., & Ozturk, I. (2018). Assessing links between energy consumption, freight transport, and economic growth: Evidence from dynamic simultaneous equation models. Environmental Science and Pollution Research International, 25(17), 16825–16841.
  • Orji, I. J., Kusi-Sarpong, S., Gupta, H., & Okwu, M. (2019). Evaluating challenges to implementing eco-innovation for freight logistics sustainability in Nigeria. Transportation Research Part A: Policy and Practice, 129, 288–305.
  • Ozturk, I., & Acaravci, A. (2013). The long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in Turkey. Energy Economics, 36, 262–267. https://doi.org/10.1016/j.eneco.2012.08.025
  • Öztürk, İ., Sharif, A., Tuzemenc, O. B., Uzuner, G., & Sinha, A. (2020). Revisiting the role of renewable and non-renewable energy consumption on Turkey’s ecological footprint: Evidence from Quantile ARDL approach. Sustainable Cities and Society, 57, 102138.
  • Penn, S. L., Boone, S. T., Harvey, B. C., Heiger-Bernays, W., Tripodis, Y., Arunachalam, S., & Levy, J. I. (2017). Modeling variability in air pollution-related health damages from individual airport emissions. Environmental Research, 156, 791–800.
  • Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967–1012. https://doi.org/10.1111/j.1468-0262.2006.00692.x
  • Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of Applied Econometrics, 22(2), 265–312. https://doi.org/10.1002/jae.951
  • Pesaran, M. H. (2015). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6–10), 1089–1117. https://doi.org/10.1080/07474938.2014.956623
  • Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of econometrics, 142(1), 50–93.
  • Pope, C. A., III, Coleman, N., Pond, Z. A., & Burnett, R. T. (2020). Fine particulate air pollution and human mortality: 25+ years of cohort studies. Environmental Research, 183, 108924. https://doi.org/10.1016/j.envres.2019.108924
  • Razzaq, A., Ajaz, T., Li, J. C., Irfan, M., & Suksatan, W. (2021). Investigating the asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint: Novel empirical estimations from highly resource-consuming economies. Resources Policy, 74, 102302. https://doi.org/10.1016/j.resourpol.2021.102302
  • Razzaq, A., Sharif, A., Ahmad, P., & Jermsittiparsert, K. (2021). Asymmetric role of tourism development and technology innovation on carbon dioxide emission reduction in the Chinese economy: Fresh insights from QARDL approach. Sustainable Development, 29(1), 176–193. https://doi.org/10.1002/sd.2139
  • Razzaq, A., Sharif, A., Aziz, N., Irfan, M., & Jermsittiparsert, K. (2020). Asymmetric link between environmental pollution and COVID-19 in the top ten affected states of US: A novel estimations from quantile-on-quantile approach. Environmental Research, 191, 110189. https://doi.org/10.1016/j.envres.2020.110189
  • Razzaq, A., Sharif, A., Najmi, A., Tseng, M. L., & Lim, M. K. (2021). Dynamic and causality interrelationships from municipal solid waste recycling to economic growth, carbon emissions and energy efficiency using a novel bootstrapping autoregressive distributed lag. Resources, Conservation and Recycling, 166, 105372. https://doi.org/10.1016/j.resconrec.2020.105372
  • Razzaq, A., Wang, Y., Chupradit, S., Suksatan, W., & Shahzad, F. (2021). Asymmetric inter-linkages between green technology innovation and consumption-based carbon emissions in BRICS countries using quantile-on-quantile framework. Technology in Society, 66, 101656. https://doi.org/10.1016/j.techsoc.2021.101656
  • Rutherford, D., Mao, X., Osipova, L., & Comer, B. (2020). Limiting engine power to reduce CO [Working Paper 2020-01]. International Council on Clean Transportation, 1–16.
  • Saether, E. A., Eide, A. E., & Bjørgum, Ø. (2021). Sustainability among Norwegian maritime firms: Green strategy and innovation as mediators of long‐term orientation and emission reduction. Business Strategy and the Environment, 30(5), 2382–2395. https://doi.org/10.1002/bse.2752
  • Salim, R., Yao, Y., & Chen, G. S. (2017). Does human capital matter for energy consumption in China? Energy Economics, 67, 49–59. https://doi.org/10.1016/j.eneco.2017.05.016
  • Sharif, A., Baris-Tuzemen, O., Uzuner, G., Ozturk, I., & Sinha, A. (2020). Revisiting the role of renewable and non-renewable energy consumption on Turkey’s ecological footprint: Evidence from Quantile ARDL approach. Sustainable Cities and Society, 57, 102138. https://doi.org/10.1016/j.scs.2020.102138
  • Sharif, A., Raza, S. A., Ozturk, I., & Afshan, S. (2019). The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: A global study with the application of heterogeneous panel estimations. Renewable Energy, 133, 685–691. https://doi.org/10.1016/j.renene.2018.10.052
  • Staples, M. D., Malina, R., Suresh, P., Hileman, J. I., & Barrett, S. R. (2018). Aviation CO2 emissions reductions from the use of alternative jet fuels. Energy Policy, 114, 342–354. https://doi.org/10.1016/j.enpol.2017.12.007
  • Sun, Y., Duru, O. A., Razzaq, A., & Dinca, M. S. (2021). The asymmetric effect eco-innovation and tourism towards carbon neutrality target in Turkey. Journal of Environmental Management, 299, 113653.
  • Suwarni, Akhmetshin, E. M., Okagbue, H. I., Lydia, E. L., & Shankar, K. (2020). Digital economic challenges and economic growth in environmental revolution 4.0. Journal of Environmental Treatment Techniques, 8(1), 546–550.
  • Tao, R., Umar, M., Naseer, A., & Razi, U. (2021). The dynamic effect of eco-innovation and environmental taxes on carbon neutrality target in emerging seven (E7) economies. Journal of Environmental Management, 299, 113525.
  • U.S. Environmental Protection Agency (EPA). (2019). Integrated Science Assessment (ISA) for particulate matter (Final Report, 2019). U.S. Environmental Protection Agency, EPA/600/R-19/188. Retrieved May 10, 2021, from https://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=347534
  • Van Song, N., Tiep, N. C., van Tien, D., Van Ha, T., Phuong, N. T. M., & Mai, T. T. H. (2021). The role of public-private partnership investment and eco-innovation in environmental abatement in USA: Evidence from quantile ARDL approach. Environmental Science and Pollution Research, 1–12. https://doi.org/10.1007/s11356-021-16520-8
  • Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69(6), 709–748. https://doi.org/10.1111/j.1468-0084.2007.00477.x
  • Westerlund, J., & Edgerton, D. L. (2008). A simple test for cointegration in dependent panels with structural breaks. Oxford Bulletin of Economics and Statistics, 70(5), 665–704. https://doi.org/10.1111/j.1468-0084.2008.00513.x
  • Wise, M., Muratori, M., & Kyle, P. (2017). Biojet fuels and emissions mitigation in aviation: An integrated assessment modeling analysis. Transportation Research Part D: Transport and Environment, 52, 244–253. https://doi.org/10.1016/j.trd.2017.03.006
  • Woody, M. C., Wong, H. W., West, J. J., & Arunachalam, S. (2016). Multiscale predictions of aviation-attributable PM2.5 for US airports modeled using CMAQ with plume-in-grid and an aircraft-specific 1-D emission model. Atmospheric Environment, 147, 384–394. https://doi.org/10.1016/j.atmosenv.2016.10.016
  • World Bank. (2020). Patent applications. RESD. Retrieved May 28, 2020, from https://data.worldbank.org/indicator/IP.PAT
  • Yao, Y., Ivanovski, K., Inekwe, J., & Smyth, R. (2019). Human capital and energy consumption: Evidence from OECD countries. Energy Economics, 84, 104534. https://doi.org/10.1016/j.eneco.2019.104534
  • Yu, J., Shao, C., Xue, C., & Hu, H. (2020). China's aircraft-related CO2 emissions: Decomposition analysis, decoupling status, and future trends. Energy Policy, 138, 111215. https://doi.org/10.1016/j.enpol.2019.111215
  • Yu, W. D., Cheng, S. T., Miao, C. M., & Perng, G. Y. (2017). Green innovation of green roof technology – A case study: Umweltverträgliche Dachtechnologie‐eine Fallstudie. Materialwissenschaft und Werkstofftechnik, 48(5), 420–429. https://doi.org/10.1002/mawe.201700015
  • Yurdakul, M., & Kazan, H. (2020). Effects of eco-innovation on economic and environmental performance: Evidence from Turkey’s manufacturing companies. Sustainability, 12(8), 3167. https://doi.org/10.3390/su12083167
  • Zeng, W., Liu, J., Yu, L., Ma, H., & Zheng, W. (2019). Reaction kinetic simulation of the combustion and emission characteristics of a dual-fuel aero-engine. Fuel, 237, 352–360. https://doi.org/10.1016/j.fuel.2018.09.122
  • Zhang, X., Karl, M., Zhang, L., & Wang, J. (2020). Influence of aviation emission on the particle number concentration near Zurich airport. Environmental Science & Technology, 54(22), 14161–14171. https://doi.org/10.1021/acs.est.0c02249
  • Zhang, X., Zheng, Y., & Wang, S. (2019). A demand forecasting method based on stochastic frontier analysis and model average: An application in air travel demand forecasting. Journal of Systems Science and Complexity, 32(2), 615–633. https://doi.org/10.1007/s11424-018-7093-0
  • Zhang, Y. J., Peng, Y. L., Ma, C. Q., & Shen, B. (2017). Can environmental innovation facilitate carbon emissions reduction? Evidence from China. Energy Policy, 100, 18–28. https://doi.org/10.1016/j.enpol.2016.10.005
  • Zheng, X. S., Graver, B., & Rutherford, D. (2019). US domestic airline fuel efficiency ranking, 2017-2018. The International Council of Clean Transportation. https://theicct.org/sites/default/files/publications/CO2-commercial-aviation-oct2020.pdf