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Introduction of hydrogen fuel cell vehicles: prospects and challenges for Malaysia’s transition to a low-carbon economy

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Abstract

Alternative energy policies targeting the adoption of hydrogen fuel cell vehicles (HFCVs) could have significant positive impacts on Malaysia’s ability to meet both its carbon reduction goal and its energy security needs. The transport sector generally contributes heavily to carbon emissions, and is also difficult to decarbonize because of the costs associated with many greener options. This study explores the possibility of decarbonizing the Malaysian transport sector by promoting the use of hydrogen vehicles, and analyzes the adoption challenges and economic obstacles (especially public acceptance) associated with introducing HFCVs. This study contends that the adoption challenges of this new technology can be overcome through the use of development strategies outlined. This study also addresses the regulatory framework that Malaysia (and other countries) might use to overcome common policy adoption challenges of HFCVs.

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Notes

  1. The United Nations Conference on Climate Change (COP) in 2015 held since 1995 under the framework of the United Nations Framework Convention on Climate Change (UNFCCC).

  2. The obligations included the Paris Agreement’s agenda on global response to climate change beyond 2020 and pre-2020 commitments and actions, differentiated responsibilities and Parties’ (e.g. nations signed to the Agreement) efforts to cover adaptation, mitigation, and means of implementation addressing new technology framework, including its guidance to the technology mechanism in enhancing global actions.

  3. Intended Nationally Determined Contributions (INDCs) is a commitment by counties who signed Paris Agreement 2015, under UNFCCC for reductions in greenhouse gas emissions to a certain level over time.

  4. A conventional vehicle is that which uses an internal combustion engine in which combustion of fuel (usually petrol and diesel) generates by-products including greenhouse gases (GHG). Unlike conventional vehicles, hydrogen fuel cell vehicles (HFCV) technology combines oxygen and hydrogen to generate electricity to power an electric motor, with water as a combustion byproduct. HFCVs run like electric vehicles (“EVs”) but there are several technological differences in fuel, fueling procedures, and conversion processes (e.g., like natural gas station: NGV) which need to be developed by the introducing country.

  5. Obstacle/issue is that a development which connects with technology and societal needs, unsure that market-driven forces (e.g., prices) may not be achieved for the society within the existing technologies and developments unless further technological interventions taken place.

  6. Benefit intention on the awareness of the environment may influence consumer purchase intentions, and once large numbers of people understand the benefit of HFCV for the environment, then the purchase intentions of large numbers of consumer may influence societal desires to embrace HFCV (Chen et al. 2016; Albayrak et al. 2013).

  7. We used discrete categorical random and purposive sampling on the basis of some qualitative properties where all ranges of existing sample vehicle owners, e.g., professional, business people, taxi company owners, student, worker, and driver, have been considered.

  8. The coefficient (r) measures the direction and strength of a linear relationship between two variables (Y = ax+b) within the valued range of between + 1 and − 1.

  9. Demand side policies aim to increase aggregate demand (AD) in the economy through either contractionary or expansionary policies. Those polices are related to aggregate spending in the overall economy based on the economic situation.

  10. Supply side policies aim to increasing aggregate supply (AS) in the economy through productive capacities by improving the factor of production.

Abbreviations

AWAR :

Awareness

BEHAV :

Behavior

COP :

Conference on Climate Change

EIA :

Energy Information Administration (United States)

EV :

Electric vehicles

GHG :

Greenhouse gases

HFCV :

Hydrogen fuel cell vehicles

INDCs :

Intended Nationally Determined Contributions

KNW :

Knowledge

OECD :

Organization for Economic Co-operation and Development

PB :

Purchase behavior

PI :

Purchase intention

R&D :

Research and development

SEM :

Structural equation modelling

SN :

Subjective norms

TPB :

Theory of planned behavior

UNFCCC :

United Nations Framework Convention on Climate Change

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Authors and Affiliations

  1. Department of Urban Studies & Planning, Massachusetts Institute of Technology, Boston, USA

    Abul Quasem Al-Amin

  2. Institute of Energy Policy and Research (IEPRe), Universiti Tenaga Nasional, Kajang, Malaysia

    Abul Quasem Al-Amin

  3. Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada

    Abul Quasem Al-Amin & Brent Doberstein

  4. Institut Sultan Iskandar, Universiti Teknologi Malaysia, Johor Bahru, Skudai, Malaysia

    Abul Quasem Al-Amin

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  1. Abul Quasem Al-Amin
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Appendix

Appendix

  1. A.

    Validation of measurement model

As addressed in other studies, validation of model appropriateness is important for accurate study outcomes, as some hidden variables can affect findings (Kline 2010; Hair et al. 2011). Thus, some measurements such as Absolute Fit Index (e.g., RMR and GFI), Incremental Fit Index (e.g., CFI and NFI), and Parsimony Fit Index (e.g., χ2/df) have been tested. The fit indices show that the model fits the data. The normed chi-square χ2/df = 1.00 which is below the recommended cut-off point of 5 to reflect good model fit. Also, CFI of 0.873 and RMR 0.038 indicated that the data fit the model well (Fenn and Byrne 2013; Hair et al. 2010). The model fit indices for the model were statistically significant at the .001% level and the relative recommended thresholds presented well. The values of GFI (0.901) and NFI (0.892) were very close to threshold value. The model fit indices’ results are summarized in Table 5. The model summary as indicated in Table 4 shows a presence of absolute, incremental and parsimony fit. The results supported by the related studies indicated by Hair et al. (2010) and Chinna (2009).

Table 5 Fitness of research model
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Al-Amin, A.Q., Doberstein, B. Introduction of hydrogen fuel cell vehicles: prospects and challenges for Malaysia’s transition to a low-carbon economy. Environ Sci Pollut Res 26, 31062–31076 (2019). https://doi.org/10.1007/s11356-019-06128-4

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