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Research Article

A systematic bibliometric review of clean energy transition: Implications for low-carbon development

Roles Writing – original draft, Writing – review & editing

Affiliation School of Statistics, Shandong University of Finance and Economics, Jinan, China

Roles Data curation, Software

Roles Conceptualization, Writing – review & editing

* E-mail: [email protected]

Affiliation Centre for Corporate Sustainability and Environmental Finance, Department of Applied Finance, Macquarie Business School, Macquarie University, Sydney, Australia

Roles Methodology, Validation

Affiliation School of Humanities and Foreign Languages, Qingdao University of Technology, Qingdao, China

Roles Software, Visualization

• Wei Zhang, 
• Binshuai Li, 
• Rui Xue, 
• Chengcheng Wang, 

• Published: December 3, 2021
• https://doi.org/10.1371/journal.pone.0261091
• Reader Comments

More voices are calling for a quicker transition towards clean energy. The exploration and exploitation of clean energy such as wind energy and solar energy are effective means to optimise energy structure and improve energy efficiency. To provide in-depth understanding of clean energy transition, this paper utilises a combination of multiple bibliometric mapping techniques, including HistCite, CiteSpace and R Bibliometrix, to conduct a systematic review on 2,191 clean energy related articles obtained from Web of Science (WoS). We identify five current main research streams in the clean energy field, including Energy Transition, Clean Energy and Carbon Emission Policy, Impact of Oil Price on Alternative Energy Stocks, Clean Energy and Economics, and Venture Capital Investments in Clean Energy. Clearly, the effectiveness of policy-driven and market-driven energy transition is an important ongoing debate. Emerging research topics are also discussed and classified into six areas: Clean Energy Conversion Technology and Biomass Energy Utilisation, Optimisation of Energy Generation Technology, Policy-Making in Clean Energy Transition, Impact of Clean Energy Use and Economic Development on Carbon Emissions, Household Use of Clean Energy, and Clean Energy Stock Markets. Accordingly, more and more research attention has been paid to how to improve energy efficiency through advanced clean energy technology, and how to make targeted policies for clean energy transition and energy market development. This article moves beyond the traditional literature review methods and delineates a systematic research agenda for clean energy research, providing research directions for achieving low-carbon development through the clean energy transition.

Citation: Zhang W, Li B, Xue R, Wang C, Cao W (2021) A systematic bibliometric review of clean energy transition: Implications for low-carbon development. PLoS ONE 16(12): e0261091. https://doi.org/10.1371/journal.pone.0261091

Editor: Ghaffar Ali, Shenzhen University, CHINA

Received: July 29, 2021; Accepted: November 23, 2021; Published: December 3, 2021

Copyright: © 2021 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data underlying the results presented in the study are available from: Zhang, Wei; Li, Binshuai; Xue, Rui; Wang, Chengcheng; Cao, Wei (2021), “Clean Energy Related Literature Data”, Mendeley Data, V1, doi: 10.17632/h9n69648d9.1 .

Funding: This research was supported by the National Social Science Foundation of China (Grant Number: 20BTJ030), the Social Science Planning Foundation of Shandong Province (16CTJJ01) and Youth Innovation Program of Shandong Province (2019REW021). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

1 Introduction

Currently, many countries worldwide have proposed and implemented their green recovery plans [ 1 – 3 ]. Public voices for transitioning to clean energy are increasingly high, shifting investors’ attention from traditional energy markets to clean energy markets. Therefore, it is important and urgent to systematically understand how to transition to a “clean” world.

Considering this context, the key research question of this study is to provide a comprehensive understanding of the current progress of the clean energy transition and illustrate a research agenda for emerging areas that await more academic and practical attention. To address the research question, this study provides a systematic literature review of 2,191 articles on clean energy related areas obtained from the Web of Science (WoS) Core Collection database over the period from 1950 to 2020. Using a combination of multiple bibliometric mapping techniques, we identify the main streams of current research and propose important topics for future research, providing comprehensive insights for the developments in clean energy transitions and a theoretical basis for more effective ways to achieve carbon neutrality.

Current main streams of clean energy research identified by bibliometric analysis include Energy Transition, Clean Energy and Carbon Emission Policy, Impact of Oil Price on Alternative Energy Stocks, Clean Energy and Economics, and Venture Capital Investments in Clean Energy.

Specifically, the Energy Transition research stream focuses on the barriers to energy transition at the national and household level [ 4 ]. Given the governments’ dominant role in promoting the clean energy transition [ 5 ], the Clean Energy and Carbon Emission Policy stream concentrates on assessing governments’ related policies and their impacts on carbon emissions. The Impact of Oil Price on Alternative Energy Stocks stream centres around the influencing factors on clean energy stock prices; existing studies show that oil prices, technology stock prices, and interest rates are prominent factors affecting clean energy stock prices [ 6 ]. The Clean Energy and Economics stream tends to apply econometric models to test the causal relationship between clean energy consumption and socio-economic variables such as economic growth [ 7 ] and foreign direct investment (FDI) [ 8 ]. As the soaring demand for clean energy attracts a significant amount of venture capital inflows, especially the private ones [ 9 ], the identification and minimisation of investment risk for investors remains the major topic for current research in Venture Capital Investments in Clean Energy.

We further employ the cluster analysis of articles published in recent five years (2015–2020) to propose the emerging trends and future directions in clean energy research. Clean Energy Conversion Technology and Biomass Energy Utilisation, Optimisation of Energy Generation Technology, Policy-Making in Clean Energy Transition, Impact of Clean Energy Use and Economic Development on Carbon Emissions, Household Use of Clean Energy, and Clean Energy Stock Markets are trending topics in the clean energy transition.

Specifically, a growing trend in Clean Energy Conversion Technology and Biomass Energy Utilisation aims to enhance the efficiency and reliability of the biomass gasification system [ 10 , 11 ]. Research in Optimisation of Energy Generation Technology has been paying more attention to explore ways to effectively integrate new energy resources with traditional ones, construct an efficient hybrid energy system, and resolve the environmental problems incurred from the use of clean energy [ 12 , 13 ]. Because of the significant discrepancies in the influences of local governments’ clean energy policies [ 14 , 15 ], the Policy-Making in Clean Energy Transition research continues to explore how local governments should formulate policies conducive to the development of clean energy. The Impact of Clean Energy Use and Economic Development on Carbon Emissions stream provides policymakers with emission reduction recommendations. It starts to investigate the implications of clean energy use and various economic factors, particularly on carbon productivity and carbon transfer [ 16 ]. The vital issue of Household Use of Clean Energy research is to increase the the heating system’s energy efficiency and to accelerate the energy transfer of clean cooking [ 17 ]. Finally, studies on Clean Energy Stock Markets examine the correlation between clean energy stock prices and the overall stock market, green bond market, electricity market, and coal market [ 18 , 19 ].

Through systematic reviews of current and trending topics in clean energy research, we aim to delineate a critical research agenda for clean energy transition as an effective way to achieve a low-carbon development and carbon neutrality. The article proceeds as follows. Section 2 introduces the literature retrieval process, the bibliometric techniques used and the descriptive information of existing literature on clean energy. Section 3 illustrates the citation map to identify current main streams in clean energy research and provides a critical review of every stream. Section 4 proposes emerging areas and trending topics. Section 5 concludes the article and provides an agenda for future research in the clean energy transition.

2 Research methods

2.1 literature retrieval process.

The method of literature retrieval and bibliometric analysis used in this study is illustrated in Fig 1 . Specifically, we collect basic information and cited references of clean energy articles from Web of Science (WoS) over the period of 1950 to June 2020, with themes limited to “clean energy” and journal sources limited to “SSCI, SCIE, A&HCI.” A total of 2,652 initial articles is retrieved. For validation purposes, we have implemented manual checks to select relevant articles, resulting in 471 irrelevant articles removed. Following Linnenluecke et al. (2017) [ 20 ], we then add another ten most cited clean energy articles into our database. Therefore, we obtain 2,191 articles in our final dataset.

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https://doi.org/10.1371/journal.pone.0261091.g001

Table 1 shows the basic information of sample articles. The next section will introduce the bibliometric techniques used, i.e., R Bibliometrix, HistCite and CiteSpace, to analyse these clean energy articles.

https://doi.org/10.1371/journal.pone.0261091.t001

2.2 Bibliometric techniques

2.2.1 r bibliometrix..

Bibliometrix is a widely-used R-package developed by Massimo and Corrado (2017) [ 21 ]. It provides access to a wide range of bibliometric functions and excellent visualisation tools. This article uses Bibliometrix to carry out descriptive statistical analysis to illustrate the diagrams for the number of publications over time and the author-keyword-journal connections (Sankey diagram).

2.2.2 HistCite.

HistCite is a citation software developed by Eugene (2004) [ 22 ]. The citation map generated by HistCite is highly useful for mapping out the relationships among highly cited publications [ 23 ]. It is a popular tool for researchers to explore research hotspots and how research themes develop over time. It is an essential tool for bibliometric analysis. This paper utilises HistCite to generate the citation map of 50 highly cited articles as guidance to identify key streams of clean energy research.

2.2.3 CiteSpace.

CiteSpace is a Java visualization application developed by Chen (2017) [ 24 ]. It has powerful bibliometric and visualization functions and is extremely popular in research. It generates a spectrum of colors to depict the literature network’s temporal orders and uses algorithms such as LLR for cluster labeling extraction. This article uses this application to cluster keywords of relevant literature from 2015 to 2020 to identify future research hotspots.

2.3 Descriptive information

2.3.1 publications over time..

Fig 2 illustrates the number of publications from 2000 to 2019. The sample ends at June 2020 and the total number of publications from January 2020 to June 2020 is 274; so to make the diagram more illustrative, we do not include the publication number of 2020. Fig 2 indicates a three-stage development of clean energy research. The first stage (from 2000 to 2010) is the initial stage, with an average of 17.5 articles published per year. The period of 2011–2015 is the developing stage, with an average of 97.4 articles published per year. The publications in the clean energy areas experience a significant increase from 2016, with an average number of 291.5 publications per year (2016–2019). It signals a robust momentum in clean energy research. The clean energy transition is crucially important to mitigate climate change issues and achieve carbon neutrality. Therefore, it is expected to continue to (exponentially) grow in the next few decades.

https://doi.org/10.1371/journal.pone.0261091.g002

2.3.2 Author-Keyword-Journal (AKJ) analysis.

Fig 3 displays the Sankey diagram, i.e., the author-keyword-journal diagram. The three columns in Fig 3 are the top 20 authors, keywords, and source journals in clean energy research, respectively. The Sankey diagram gives a graphical overview of influential clean energy research. The keywords broadly fall into the following categories: Clean Energy Stock Performance, Clean Energy and Economy Growth, Energy Consumption and Carbon Emissions, Clean Energy Power Generation, and Clean Energy Policy. The major publishing journals in the clean energy area include Renewable Energy , Journal of Cleaner Production , Energy Policy , Energy Economics , Applied Energy , etc.

https://doi.org/10.1371/journal.pone.0261091.g003

3 Developments in clean energy transition research

3.1 identification of current research streams.

In this section, we utilise HistCite to generate a citation network map for the top 50 cited articles in clean energy transition research. We then apply the triangulation process [ 23 ] to assign titles for each research stream, laying the foundation for the systematic review of these research themes. Table 2 summarises the citation information of top-cited literature, and Fig 4 illustrates the corresponding citation network map.

https://doi.org/10.1371/journal.pone.0261091.g004

https://doi.org/10.1371/journal.pone.0261091.t002

In Fig 4 , each article is displayed as a node, with a larger-sized node denoting a higher number of citations. The arrows illustrate the citation connections among articles, with arrowheads pointed to the cited ones. Through the triangulation process, we categorise the current clean energy research into the following streams: Energy Transition, Clean Energy and Carbon Emission Policy, Impact of Oil Price on Alternative Energy Stocks, Clean Energy and Economics, and Venture Capital Investments in Clean Energy. In the next section, we provide a comprehensive review of each of these five research streams.

3.2 Review of main research streams

3.2.1 energy transition..

The transition from traditional energy towards clean energy remains the major challenge for the first half of the 21st century [ 4 ]. We discuss the Energy Transition stream from two perspectives: obstacles in clean energy transition and influencing factors on household energy transition.

3 . 2 . 1 . 1 Obstacles in the clean energy transition . Current major challenges to clean energy transition include subsidies to traditional energy, high initial capital cost, high transaction cost, high financing risk, lack of price risk assessment, lack of clean technology, low market acceptance rate, and immature regulatory systems [ 25 – 28 ]. Luthra et al. (2015) [ 29 ] categorised 28 obstacles to the clean energy transition into seven dimensions: economy and finance, market, awareness and information, technology, ecology and geography, culture and behavior, political and government issues. For an in-depth look, the more challenging obstacles are ecological problems, consumers’ lack of awareness of clean technology, inability to obtain solar radiation data, technical complexity, rehabilitation disputes and lack of political commitment.

3 . 2 . 1 . 2 Influencing factors on household energy transition . Household energy use is a substantial part of energy consumption. Investigating the driving factors affecting household energy transition is an effective way to promote clean energy transition. Researchers conduct surveys on households in urban and rural areas in China, India, Brazil, Ethiopia, Guatemala, and other countries. Their results show that 1) household income and fuel prices are the dominant factors affecting household energy transition, 2) household size, household members’ occupations, and education levels are also important factors, and 3) the availability and cost of clean energy alternatives have a significant impact on rural household energy transition [ 30 – 42 ].

3.2.2 Clean energy and carbon emission policy.

The high carbon energy represented by raw coal was still the main factor in promoting the growth of energy-related CO2 emissions [ 43 ]. Appropriate and effective policies are needed to accelerate the clean energy transition. The majority of countries worldwide have set goals to increase the share of clean energy consumption and reduce greenhouse gas (GHG) emissions, resulting in various supportive policies [ 44 ]. Existing policies concentrate around quantity-driven policies. For instance, levying a carbon tax is a typical quantity-driven policy. Guo et al. (2014) [ 5 ] argues that a moderate carbon tax significantly reduces carbon emissions and fossil fuel consumption, with a minimal impact on economic growth. But a more recent study claims that carbon taxes are not always good for the environment [ 45 ]. Another example is feed-in tariffs (FIT), a quantity-driven policy targeted at specific technology [ 46 ]. It is generally regarded as an effective policy for clean energy transition due to its advantages of low costs, low risks, and high innovation incentives [ 47 – 51 ].

3.2.3 Impact of oil price on alternative energy stocks.

The way how oil prices affect stock prices works as follows. On the one hand, rising oil prices increase production and service costs and decrease cash flow turnover, leading to a stock price drop. On the other hand, rising oil prices also indicate the mounting inflation pressure and discount rate, resulting in stock price drop [ 52 ]. As a critical component of the stock market, energy stocks are also highly correlated with oil prices [ 52 – 55 ]. Nevertheless, the negative impact of oil prices may only be a short-term effect for clean energy stocks [ 6 ].

3.2.4 Clean energy and economics.

The clean energy transition is closely related to economic development [ 7 ]. In Fig 4 , the theme of Clean Energy and Economy contains comparatively more nodes (articles), the majority of which use different econometric models to examine the relationship between clean energy consumption and socio-economic variables such as economic growth and FDI. In the short term, there exists a positive correlation and bidirectional causal relationship between clean energy consumption and economic development. In the long run, clean energy consumption will positively affect on economic growth [ 8 , 56 – 60 ]. The empirical results of Paramati et al.(2016) [ 8 ] indicate that there is a unidirectional causality running from FDI to clean energy consumption, with inflows of FDI having a positive impact on the latter. Moreover, the results of Paramati et al.(2016) [ 8 ] also show that the development of the stock market has brought more investment in the clean energy industry and plays a significant role in promoting clean energy transition.

3.2.5 Venture capital investments in clean energy.

Venture capital (VC) is one of the main drivers of technology advancement, especially in new and innovative fields such as clean energy. As the demand for clean energy increases, there has been a surge of venture capital inflows, especially private VCs, into clean energy companies [ 9 , 61 , 62 ]. Currently, clean energy has become the third-largest venture investment field [ 63 ]. In addition, there are also risks embedded in clean energy investments, including market risks, technology risks, human resource risks, and more importantly, regulatory risks [ 64 ]. However, it is feasible to reduce market risks through appropriate business models, reduce technology risks through publicly funded R&D projects, reduce human resource risks through market liberalisation, and reduce regulatory risks through effective government policies [ 64 , 65 ].

4 Emerging research areas

To illustrate the emerging topics in clean energy transition research, we utilise CiteSpace to conduct cluster analysis on sample articles published in recent five years, from 2015 to 2020. The following two sections provide basic information on identified emerging topics and provide a detailed analysis of the relevant literature.

4.1 Identifications of emerging research areas

Fig 5 demonstrates the keyword co-occurrence network map of recent five years’ publications in clean energy transition areas, with a larger circle (keyword) representing more frequent occurrence, and darker colour representing earlier occurrence (publication time). The lines connecting circles (keywords) refer to co-occurrence.

https://doi.org/10.1371/journal.pone.0261091.g005

Using cluster analysis, CiteSpace classifies recent five years’ publications into seven clusters, reflecting seven emerging research topics in clean energy research. The clustered emerging topics include Surface Properties, Fuel Cell, Energy Transition, CO 2 Emission, Household Fuel Use, Oil Price, and Wind Farm. Once again, we apply the triangulation process to define the title of each cluster (area) and provide more details in Table 3 .

https://doi.org/10.1371/journal.pone.0261091.t003

4.2 Analyses of emerging research areas

4.2.1 clean energy conversion technology and biomass energy utilization..

Converting industrial waste and household garbage into clean energy can help deal with the current shortage of clean energy and protect the environment through the recycling process. Studies show that kitchen waste, animal waste, agricultural waste, forestry waste, waste plastics and waste tyres can be converted into clean energy through advanced technologies such as thermochemical conversion or hydrothermal carbonisation [ 10 , 66 – 70 ]. Research on improving these conversion technologies is a trending research hotspot. For example, biomass gasification is a feasible and practical clean energy conversion technology, but it faces crucial challenges to effectively eliminate the tar generated during the gasification process [ 11 , 71 , 72 ]. Another trending research topic in this area is to enhance the efficiency and reliability of biomass gasification. In addition, with the continuous advancement of clean energy conversion technology, how to formulate policies to implement more effective classifications of waste and refuse continues to be an urgent issue to be further explored.

4.2.2 Optimisation of Energy Generation Technology.

Comprehensive utilisation of various energy resources is an ideal approach to alleviate the energy crisis [ 73 ]. Many scholars have investigated how to integrate various new and traditional energy resources, including photovoltaics, batteries, diesel, wind energy, and solar energy, to build a highly effective hybrid energy system [ 12 , 13 , 74 ]. Research on the development of clean energy battery systems, the optimisation of power station scale, and generator systems also receives extensive academic attention [ 75 , 76 ].

Electricity generation from clean energy, such as wind and solar, plays a key role in the clean technology optimisation research [ 77 , 78 ]; however, a series of problems are setting obstacles for it. For instance, wind power generation has a high level of uncertainty, and there are potential exposure risks to the operation of a power grid [ 79 , 80 ]. Therefore, research on wind power generation in recent years tends to focus on wind flow models with the expectation to achieve a more accurate prediction of wind power generation [ 79 , 81 ]. Besides, considering the negative impact of the wind power plant on the environment, researchers have made significant explorations on the environmental effects of wind farms and on the selection of wind farm locations for harnessing wind energy [ 82 – 87 ]. Resolving the problems arising from the use of clean energy is an important topic to be further examined.

4.2.3 Policy-making in clean energy transition.

Regulations and legislations guarantee the secure transition towards clean energy. The government thus plays an essential role in addressing the potential risks incurred by the clean energy transition process. Relevant policies involve electricity price standards, emission trading system, clean energy investment policies, and the use of innovative finance tools in clean energy support [ 14 , 15 , 88 , 89 ]. Tingey and Webb (2020) [ 90 ], Bayulgen (2020) [ 91 ] and Proedrou (2019) [ 92 ] evaluate the practices of local government in the UK, US, and EU in terms of the clean energy transition. Their results indicate that although most local governments have adopted clean energy policies, the effectiveness of these policies varies substantially. To improve the effectiveness of energy policies, the views of different local energy users should be taken into account [ 93 ]. Therefore, what policies local governments should formulate to accelerate clean energy development will continue to be one of the research hotspots in clean energy transition research.

4.2.4 Impact of clean energy use and economic development on carbon emissions.

A large body of literature concentrates on how clean energy, economic growth, land resource use, industrial restructuring, financial market development, the application of new technology and R&D activities affect carbon emissions in recent clean energy areas [ 16 , 94 – 100 ]. And it is likely to be a hot issue worth studying in the future. With the improvement of carbon emission measurement methods, research on the impact of the aforementioned factors on carbon productivity and carbon transfer is attracting increasing scholarly attention [ 101 – 103 ]. Moreover, from a micro point of view, the role of enterprises, as an essential component of the national economy, in environmental governance will become another trending research direction [ 104 ].

4.2.5 Household use of clean energy.

Given that household energy use for heating and cooking is an essential part of energy use, recent studies have made substantial progress on enhancing the heating system’s energy efficiency and advancing the clean energy transition for cooking [ 17 , 105 – 108 ]. Moreover, in terms of the driving factors on the household clean energy transition, more recent literature indicates that household income and energy prices are found to have significant effects on household energy use decisions. Therefore, energy poverty is also an issue worth future research attention [ 109 – 111 ].

4.2.6 Clean energy stock markets.

Without support from the financial markets, the clean energy industry alone cannot secure the desired level of clean energy development. In effect, clean energy stocks have recently become a popular investment asset for investors, especially for those with strong considerations for environmental protection [ 18 , 112 ]. In addition to the follow-up research on the impact of oil price on clean energy stock prices [ 19 , 113 , 114 ], increasingly great attention has been focused on the relationship between clean energy stock investment and its driving factors, including the overall stock market, bond market, electricity market, coal market, gold market, silver market and many more [ 18 , 112 , 115 – 118 ]. Therefore, we reckon that the relationship between clean energy stocks and the financial markets, especially the green bond market [ 119 ] and the carbon market [ 53 ], has great potential to be explored in future clean energy research.

5 Conclusions

Clean energy transition plays a crucial role in post-pandemic green recoveries and carbon neutrality. To advance understanding of clean energy transition, this paper provides a systematic review of existing clean energy literature through a combination of bibliometric analysis techniques. Overall, there has been a surging trend of clean energy research since 2000, especially after 2016, clean energy research has experienced exponential growth.

We collect clean energy literature from the Web of Science (WoS) Core Collection database over the period from 1950 to 2020. Using bibliometric analysis, we identify and provide a comprehensive review of five current main research streams in the clean energy area, including Energy Transition, Clean Energy and Carbon Emission Policy, Impact of Oil Price on Alternative Energy Stocks, Clean Energy and Economics, and Venture Capital Investments in Clean Energy. Main challenges and opportunities facing the current clean energy transition with respect to each research stream are investigated.

To illustrate emerging research topics that attract more recent academic attention, we apply bibliometric cluster analysis to clean energy literature published in recent five years (from 2015 to 2020). Six trending research areas in the clean energy field are proposed and analysed, including Clean Energy Conversion Technology and Biomass Energy Utilisation, Optimisation of Energy Generation Technology, Policy-Making in Clean Energy Transition, Impact of Clean Energy Use and Economic Development on Carbon Emissions, Household Use of Clean Energy, and Clean Energy Stock Markets.

Future research agenda of clean energy awaits theoretical and practical exploration. We propose that the advancement of clean technology is at the heart of clean energy transition and post-pandemic green recovery. Funding for clean energy transition is a critical challenge that needs innovative financial instruments and policy support. Thus green bond markets, carbon taxes and emission trading system (ETS) need in-depth investigation. With more disruptive financing tools available such as crowdfunding, efforts from enterprises and individuals also deserve more attention. In addition, international collaborations on clean energy transition projects are highly recommended. Intensive international collaborations and cooperations are of high importance to achieve the low-carbon development. The completion of the global warming goal needs collective contributions from all countries over the world. A community of common destiny for all of humankind cannot be successfully built with efforts from only a small number of highly engaged countries. The current collaboration in clean energy research lacks worldwide collaborations in climate change actions. Therefore, it is highly recommended that all countries shall shoulder their responsibilities in climate change mitigation and adaptation, with steady growth of environmental investments and frequent collaborations with leading countries in climate change actions.

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Article Contents

Introduction, 1 overview of green hydrogen production, 2 energy transition with green hydrogen, 3 the perspective of green hydrogen energy, 4 conclusions, acknowledgements, conflict of interest statement, data availability, green hydrogen energy production: current status and potential.

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• Supplementary Data

Ali O M Maka, Mubbashar Mehmood, Green hydrogen energy production: current status and potential, Clean Energy , Volume 8, Issue 2, April 2024, Pages 1–7, https://doi.org/10.1093/ce/zkae012

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The technique of producing hydrogen by utilizing green and renewable energy sources is called green hydrogen production. Therefore, by implementing this technique, hydrogen will become a sustainable and clean energy source by lowering greenhouse gas emissions and reducing our reliance on fossil fuels. The key benefit of producing green hydrogen by utilizing green energy is that no harmful pollutants or greenhouse gases are directly released throughout the process. Hence, to guarantee all of the environmental advantages, it is crucial to consider the entire hydrogen supply chain, involving storage, transportation and end users. Hydrogen is a promising clean energy source and targets plan pathways towards decarbonization and net-zero emissions by 2050. This paper has highlighted the techniques for generating green hydrogen that are needed for a clean environment and sustainable energy solutions. Moreover, it summarizes an overview, outlook and energy transient of green hydrogen production. Consequently, its perspective provides new insights and research directions in order to accelerate the development and identify the potential of green hydrogen production.

Nowadays, the technology of renewable-energy-powered green hydrogen production is one method that is increasingly being regarded as an approach to lower emissions of greenhouse gases (GHGs) and environmental pollution in the transition towards worldwide decarbonization [ 1 , 2 ]. However, there is a societal realization that fossil fuels are not zero-carbon, which leads to significant thinking about alternative solutions.

The global energy system ought to drastically change from one mostly reliant on fossil fuels to one that is effective and sustainable with low carbon emissions to meet the goals of the Paris Agreement. Accordingly, >90% is the required global CO 2 emission decrease and the projected direct contribution of renewable energy to the necessary emission decrease is 41% [ 3 , 4 ]. Hydrogen (H 2 ) is a cost-effective, environmentally friendly alternative for energy consumption/storage [ 5 , 6 ]. In addition, it can contribute to making a low-carbon society a reality and largely boost the share of hydrogen [ 7 ].

Hydrogen technologies have been considered an approach to strengthening various economic sectors since the COVID-19 pandemic. The potential of hydrogen is currently the subject of an important consensus, partly due to an increased ambitious climate policy [ 8 , 9 ]. In addition, hydrogen can be used in fuel cell technology in the power generation sector and many other sectors, such as industry, transport and residential applications, which reflects its potential for decarbonization [ 10–12 ].

Several initiatives and projects worldwide are rapidly rising, reflecting the outstanding political and commercial momentum that the development of hydrogen as a zero-carbon fuel is undergoing. The growing boost is caused by the decreasing cost of hydrogen produced by renewable energy sources, or ‘green hydrogen’, and the urgent need to reduce GHG emissions [ 3 , 13 ]. However, green hydrogen is expected to increase in prominence over the next few decades and attain high commercial viability [ 13 , 14 ]. Producing hydrogen can be done using coal, methane, bioenergy and even solar energy; however, green hydrogen production is one of the pathways [ 15 , 16 ].

Numerous countries consider hydrogen the next-generation energy management response, and they increasingly support adopting hydrogen technology intended to create a decarbonized economy. Therefore, many strategies and plans for developing and implementing hydrogen have been made [ 17 ].

By 2050, according to Anouti et al. [ 18 ], there could be 530 million tonnes (Mt) of demand globally for green hydrogen, or hydrogen produced with fewer carbon dioxide emissions. Consequently, it would displace ~10.4 billion barrels of oil, which is equivalent to ~37% of the pre-pandemic world oil production [ 18 , 19 ]. Based on its forecast, the worldwide market for green hydrogen exports may be worth $300 billion annually by 2050, creating ~400 000 jobs in the hydrogen and renewable-energy industries [ 18 ].

Based on the technique used to produce hydrogen, the energy source used and its effects on the environment, hydrogen is categorized into various colour shades, including blue, grey, brown, black and green [ 20 ]. Using the steam-reforming/auto-thermal reforming method, grey hydrogen is extracted from natural gas but CO 2 is emitted into the atmosphere as a by-product. When the steam-reforming method converts natural gas into hydrogen and the CO 2 emissions from the process are captured, this is known as blue hydrogen. The most prevalent type of hydrogen used today is brown hydrogen, mainly produced via the gasification of hydrocarbon-rich fuel, in which CO 2 is released into the atmosphere as a by-product. However, green hydrogen is produced by water electrolysis, which is powered by renewable energy resources [ 18 , 21 , 22 ].

Green hydrogen is already competitive in regions with all the appropriate conditions [ 15 ] and will play a significant role in achieving sustainable development goals (SDGs) for the UN 2030, based on the agenda for sustainable development adopted wholly by UN Member States. The specified section of SDG 7 depends on ‘Affordable and Clean Energy’ [ 23 , 24 ]. For this reason, many efforts have been made to attain this goal globally in recent years.

Therefore, continuing on from those issues mentioned above in the introduction, in this paper, we analyse green hydrogen production technologies and investigate several aspects of the significance of the growth of the green hydrogen economy (GEE). The key objective of this study is to highlight the potential and progress of green hydrogen production and its significance in meeting energy needs. The paper is organized as follows. Section 1 summarizes the introduction, Section 2 presents an analysis of the energy transition with green hydrogen, Section 3 details a general overview of green hydrogen production, Section 4 specifics the perspective of green hydrogen energy production and Section 5 summarizes the conclusions and recommendations for future work.

There are several uses for hydrogen, including energy storage, power generation, industrial production and fuel for fuel cell vehicles. Hence, hydrogen production from green energy sources is essential to meet sustainable energy targets (SETs) as the globe attempts to move to a low-carbon economy.

Green hydrogen production requires large amounts of renewable energy and water resources. Thus, areas with an abundance of renewable energy resources, as well as accessibility to water sources, have been determined to be optimal for producing huge amounts of green hydrogen. However, to allow green hydrogen to be more economically viable than fossil fuels, advances in technology and cost reductions must be made.

In order to achieve the target for the expansion of green hydrogen production and utilization, details ought to be established at the level of the authorities. They can facilitate adoption, on the one hand, by increasing manufacturing capacity and guaranteeing an ongoing renewable energy source and, on the other, by increasing the need for green hydrogen alongside its derivatives and developing a system for storing and transporting hydrogen [ 25 ].

This paper performed a literature review to screen >100 papers related to Google Scholar/Web of Science to consider precisely green energy production by filtering the information in a large number of literature papers in science databases. Figs 1 and 2 illustrate the visualized literature network diagrams; hence, searching for keywords in science databases maps the intensity of relations/strengths among items. The analysis, which determined the research relationships of networks for visualization and exploration, utilized the VOSviewer. The categorical evaluation relies on the occurrence and frequency of keywords in related publications. The red cluster (lower left) represents initial development words trend links, the blue cluster (upper center) represents the second stage of development and the green cluster (lower right) links the green hydrogen words. Fig. 1 displays and signifies the mapping of the intensity of relations among words. In recent years, more research has focused on developing green hydrogen production from 2016 to 2023. Fig. 2 elucidates the keywords of scientific mapping and field trends. The blue cluster (lower left) represents the trend of research development from 2016 to 2019 and the bright maroon cluster (upper right) represents the trend of research development from 2020 to 2023.

Characterizes scientific mapping and relations between words

Characterizes keywords of scientific mapping and developing field trends from 2016 to 2023

The technology of green hydrogen can play a vital role in energy storage. Electrolysis can be utilized for producing hydrogen by using a surplus of renewable energy produced when demand is low. Whenever required, hydrogen can be used directly in various applications or stored and subsequently turned back into power using fuel cells. Hydrogen can be stored in different ways, either in the form of liquid, gaseous fuel or solid state; thus, the storage method is determined based on the consumption approach or export. In addition to resources such as solar and wind, this makes it possible to integrate renewable energy into the grid. This may lower the overall cost of the hydrogen yield.

Long-haul transportation, chemicals, and iron and steel are only a few industries that can benefit from the decarbonization of clean hydrogen produced using renewables, fossil fuels, nuclear energy or carbon capture. These industries have had difficulty in reducing their emissions. Vehicles fuelled by hydrogen would enhance the security of energy and the quality of air. Although it is one of the few alternative energy sources that can store energy for days, weeks or months, hydrogen can facilitate the incorporation of various renewable energies into the electrical grid.

Hydrogen storage technology, either underground or surface storage, gives more effectiveness and is more reliable to utilize; also, storage on a large scale has advantages in terms of energy demand and flexibility of the energy system [ 26 ]. The important consideration of storing hydrogen efficiently and safely is vital for many applications, such as industrial processes and transportation.

The transition towards green hydrogen will create new job opportunities in several sectors, including manufacturing, fuel cells, infrastructure, and operation and maintenance of electrolysers. Moreover, the development of the green hydrogen sector has the potential to promote economic growth, produce income through exports, bring in investments and drive scientific breakthroughs in the field.

Green hydrogen technological progress is the focus of ongoing studies and developments. Hence, this encompasses enhancing the effectiveness of electrolysis procedures, making affordable fuel cells, investigating cutting-edge materials for hydrogen storage and raising the overall efficacy of hydrogen systems. The range of applications for green hydrogen will grow due to technological improvements that will lower costs, boost effectiveness and expand their usage. State-of-the-art electrolyser devices and their development are based on decreasing the cost of manufacturing, enhancing efficiency and increasing the role played by electrolysis in the global hydrogen economy.

However, before worldwide commerce in hydrogen becomes a feasible, affordable option on a large scale, numerous milestones must be accomplished. The key is a techno–economic analysis used to investigate the circumstances required for such a trade to be profitable. The scenarios are for predicting the hydrogen trade outlook towards 2050 in which hydrogen production and costs of transportation are accessible. The trade of hydrogen is expected to develop in local markets to a great extent.

Based on a global plan through a ‘pathway toward decarbonization and net-zero emissions via 2050’ in the 1.5°C scenario, ~55% of the hydrogen traded globally by 2050 will be transported through a pipeline. The vast majority of the hydrogen network would rely on already-built natural gas pipelines that can be converted to transport pure hydrogen, greatly lowering the cost of transportation [ 27 , 28 ]. Hence, if we examine the economic and technological production capability of green hydrogen globally over various scenarios, we can evaluate the prognosis for the global hydrogen trade in 2030 and 2050 [ 27 ].

Progress and optimization of the hydrogen supply chain are important for comprehending the potential of hydrogen as a sustainable and clean energy carrier. Moreover, socio-economic aspects through providing a labour market can extend to the supply chain by deploying/installing renewable-energy devices. Thus, as technology and infrastructure continue to develop, the hydrogen supply chain is anticipated to play a substantial role in the shift to a low-carbon energy system.

Further outlook of green hydrogen to extend knowledge to include outreach approaches incorporating hydrogen-related topics into the curriculum might include online sources, community workshops and collaborations with educational institutions.

Accordingly, many factors have led numerous countries to endorse adopting green hydrogen technology projects. These aim to create a decarbonized economy and reduce GHG emissions, considering hydrogen as an alternative for sustainable energy management. Table 1 summarizes the breakdown of recently announced ongoing investment projects in green hydrogen production.

List of large green hydrogen planned/ongoing projects

Achieving the 1.5°C scenario includes a commercially viable form of large-scale production of hydrogen and commerce. The electricity needed for the production of hydrogen should be adequate and not take away from the electricity needed for other vital and more productive purposes. Thus, this leads to increased scale and acceleration of renewable-energy development at the core of the transition to green hydrogen.

Green hydrogen has the potential to play a crucial role in the development of a cleaner and more sustainable energy future as costs decrease, technology improves and supportive policies are put in place [ 34 ]. Fig. 3 depicts a potential pathway for producing hydrogen from green energy resources. An environmentally friendly renewable-energy supply, so-called biogas, is produced whenever organic matter, including food scraps and animal waste, breaks down. The biomass gasification of organic materials or agricultural waste can be gasified in a controlled environment to harvest a mixture of hydrogen. The biogas produced may be used to generate energy, heat houses and fuel motor vehicles.

Potential pathway for producing hydrogen from green energy

Electrolysis is a procedure that uses electrolysers to separate water into hydrogen and oxygen, utilizing electricity produced by renewable sources such as solar technology, including photovoltaic (PV) and concentrating solar power (CSP), wind or hydropower. The hydrogen produced can then be used for numerous purposes, such as fuel cells or industrial processes, or it can be stored. The basic production of hydrogen via electrolysis using electricity to split molecules in water into hydrogen and oxygen is given by:

It is important to mention that another method—the so-called photoelectrochemical (PEC) hydrogen production technique—depends on the use of solar radiation to drive the water-splitting process directly; PEC cells transform solar energy into hydrogen [ 35 , 36 ]. Although this technology is still in its infancy, it indicates promise for producing hydrogen sustainably and effectively [ 35 ].

Owing to their capability for photosynthetic oxygen production, algae have been recommended as a potential resource for the production of green hydrogen. Some types of algae can also produce ‘hydrogen gas as a by-product of their metabolism’ under certain conditions. Green hydrogen production from algae is based on the biohydrogen production technique, which is a subject of interest and ongoing study [ 37 , 38 ]; however, it is not commonly used in industrial practice yet [ 39–41 ].

Electrolysers ought to function at a higher usage rate to reduce the expenses of producing hydrogen, although this is incompatible with the curtailed supply of restricted energy [ 42 ]. Several research publications suggested the idea of using direct seawater electrolysis to produce hydrogen and oxygen [ 43–45 ].

The shift towards clean energy using green hydrogen necessitates collaboration among industries, governments, communities and research institutions. It offers a chance to increase sustainable growth, diversify sources of energy and decrease emissions of GHGs [ 14 ]. Table 2 details the world’s green hydrogen production capacity (in EJ) and potential by region distributed on continents. The top high potential was in sub-Saharan Africa, at ~28.6%, followed by the Middle East and North Africa, at ~21.3%. Then, the following other regions across the continent are listed.

Breakdown of the potential of global green hydrogen production by region [ 46 ]

Green hydrogen, from an economic perspective, represents a large economic opportunity. It includes the potential to promote the growth of new industries, the creation of employment opportunities and economic expansion. Thus, countries with abundant renewable energy resources can use green hydrogen generation to export energy, diversify their economy and lower their dependency on fossil fuels.

The production of hydrogen can assist in reducing curtailed systems that use a significant amount of variable energy from renewable sources [ 42 ]. Herein, green hydrogen is considered a technological development catalyst from a technical development perspective. Technology advances in the field are anticipated to result from research and development initiatives to increase electrolysis efficiency, lower costs and create improved materials and methods. This perspective highlights the innovative potential and development of green hydrogen technology.

Moreover, green hydrogen is considered an essential catalyst of the energy shift from the perspective of that transition. Subsequently, clean energy sources such as wind and solar power provide a method of integrating and balancing energy from renewable sources. Green hydrogen may increase the shares of clean energy sources in the energy system by offering grid flexibility and long-term energy storage.

It is clear that the movement towards the global transition is accelerating based on the energy transition policies and carbon-neutrality targets of different nations [ 47 ]. The investments in green hydrogen projects are progressing and taking place globally, including the USA, Germany, Austria, Saudi Arabia and China, to name a few. These countries have taken a step forward towards implementing large-scale projects of green hydrogen [ 15 , 42 ].

Energy from hydrogen can be utilized in numerous fields encompassing industry, electricity, construction, transportation, etc. [ 47 ]. Fig. 4 elucidates the schematic flow of perspectives on green hydrogen production. The demand for green hydrogen has recently evolved since more recent sources have become the latest insights on its current status and projections. The need for green hydrogen is anticipated to increase over the coming years as green technologies develop and the urgency to battle climate change grows. The demand is also needed for environmental aspects of climate change mitigation, decarbonization, technological developments and policy support.

Green hydrogen production perspectives

A study reported that hydrogen has a significant potential role in supporting the globe in meeting decarbonization goals/net-zero emissions by 2050 and limiting the global warming phenomenon to 1.5°C because it can reduce ~80 GT (gigatonnes) of CO 2 emissions by 2050 [ 48 ].

The potential of green hydrogen relies on geographic location and abundant natural resources. Hence, water, solar energy, wind and hydro-energy and organic materials are available. The development in infrastructure enables the widespread implementation of green hydrogen and important infrastructure progress is required. It comprises establishing hydrogen refuelling and building electrolysis plants, storage systems, etc.

Furthermore, investment projects would be viable in desert areas, where large projects might be constructed using solar PV and CSP to generate electricity. Subsequently, electricity can be used to produce enough hydrogen for the local market and export the surplus. Hence, these will help economic development in countries with great potential for solar radiation intensity over the years.

The economies of scale enabled via a developing global market for clean energy sources and green hydrogen will continue to drive down overall expenses [ 29 ]. However, the most economical way to use green financing will be to focus on helping the initial phases of the expansion of green hydrogen generation during a period when the investment takes place [ 49 ]. The investment cost is the main aspect to be considered while designing a hydrogen plant. Therefore, a core desired feature is low-levelized energy costs from renewable energy resources and electrolysers. These will make the project more feasible, efficient and cheap for the production of green hydrogen. The environmental impact of green hydrogen production is a key tool for attaining global climate goals—the potential to guarantee a more sustainable and environmentally friendly future for our planet.

This paper summarizes the outline of green hydrogen, its contribution and its potential towards net-zero emissions. Hence, its viewpoint provides new insights to accelerate the expansion of green hydrogen production projects. In order to accelerate the implementation of green hydrogen, scholars, industries and governments worldwide will contribute to the research and development of the technology. It is considered a feasible option for lowering emissions of GHGs, encouraging energy independence and helping in shifting to a low-carbon, environmentally friendly energy system.

There has been development of hydrogen technology that has significantly progressed to meet energy needs. Therefore, green hydrogen yield, which depends on renewable energy resources, has recently become a more attractive option due to decreased expenditure. Thus, it has the potential to mitigate environmental issues, promote economic expansion and contribute to the transition of the entire world to sustainable and clean energy systems. To adequately realize the potential of green hydrogen, challenges, including lower expenses, development of infrastructure and industrial scale, remain important factors.

A worldwide market for green hydrogen could emerge, enabling assignees with abundant renewable resources to export surplus electricity in the form of hydrogen. Therefore, this could assist countries in switching to a more sustainable energy mix and decrease their dependence on fossil fuel imports. Future work includes developing/deep analysis of a cost-effective, high-efficiency electrolyser device that will decrease the overall cost of green hydrogen yield.

Many grateful thanks go to the Libyan Authority for Research Science and Technology, and many thanks go to the staff in the Libyan Centre for Research and Development of Saharian Communities. Also, thanks to the anonymous reviewers for their constructive comments in improving this paper.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data sharing does not apply to this perspective paper, as no new data sets were created during this research.

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Accessibility, affordability, and efficiency of clean energy: a review and research agenda

Affiliations.

• 1 University School of Business, Chandigarh University, Gharuan, Mohali, India. [email protected].
• 2 University Centre of Research & Development, Chandigarh University, Gharuan, Mohali, India. [email protected].
• 3 University School of Business, Chandigarh University, Gharuan, Mohali, India.
• PMID: 35013970
• DOI: 10.1007/s11356-022-18565-9

Clean, affordable, and efficient energy sources are inevitable for a sustainable world. Energy crisis, especially the poor access and affordability, demand-supply mismatches, energy inequality, and high dependence on non-renewable energy sources, are the challenges before the attainment of clean energy goals for sustainable development. The 5-year review from the adoption of sustainable development goals (SDGs) by using bibliometric and thematic analysis was conducted in this review. This review is a synthesis of 175 scientific papers on SDG 7. Policy reforms and better funding; technology innovation and inclusion; and economic growth, rapid promotion of renewable, and alternative fuels are the recommendations for the achievement of the energy goals. Future research on energy-related goals should focus on energy justice, policy reforms, energy poverty, poor affordability, off-grid transmissions, renewable energy sources, alternative fuels, reforms in the energy supply chain, and international cooperation for better implementation of projects and for attracting foreign capital and private funds. This paper invites the attention of practitioners, academicians, funding agencies, and international agencies to collaborate in the initiatives for a clean, green, and energized world.

Keywords: Cooking fuels; Electricity; Energy; Renewable energy; Sustainable development goals.

© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Policy and practice reviews article, clean energy technology pathways from research to commercialization: policy and practice case studies.

• 1 Joint Institute for Strategic Energy Analysis, National Renewable Energy Laboratory, Golden Colorado, CO, United States
• 2 U S Department of Energy, Washington, DC, United States
• 3 Renewable Energy Consulting Services, Inc, Palo Alto, CA, United States

Clean energy research and development (R and D) leading to commercial technologies is vital to economic development, technology competitiveness, and reduced environmental impact. Over the past 30 years, such efforts have advanced technology performance and reduced cost by leveraging network effects and economies of scale. After demonstrating promise in applied R and D, successful clean energy and energy efficiency technologies are incorporated into an initial product sold by the private sector. Despite its importance, processes by which first commercialization occurs are difficult to generalize while capturing specific insights from practitioners in markets and technologies. This paper presents a policy-focused qualitative assessment of the first commercialization of four diverse energy technologies: thin film photovoltaics, wind turbine blades, dual-stage refrigeration evaporators, and fuel cells for material handling equipment. Each technology presents distinct value propositions, markets, and regulatory drivers. The case studies indicate three common characteristics of successful first commercialization for new energy technologies: 1) good fit between the technology, R&D infrastructure, and public-private partnership models; 2) high degree of alignment of government regulations and R&D priorities with market forces; and 3) compatibility between time scales required for R&D, product development, and opportunities. These findings may inform energy investment decision-making, maximize benefits from R&D, and advance the transition to a low-emission future.

Introduction

Innovations in energy technologies are needed to mitigate the worst effects of climate change, improve resilience ( DOE, 2020 ), and confer other benefits ( Fuss et al., 2014 ; Hao, 2022 ). In energy, similar to all business sectors, market forces drive innovation ( Perez, 2002 ; Holmqvist, 2004 ; Markman et al., 2009 ), with governments mitigating risk for initial investments and addressing problems that markets cannot address themselves ( Janeway, 2012 ). Private sector commercializing of innovations, i.e., achieving financial benefits by selling useful and new developments, often depends on success in niche segments before expanding ( Porter, 2002 ). This pattern is particularly true for technologies that improve sustainability, for which robust sociotechnical models and research exists ( Geels, 2010 ; Smith et al., 2010 ; Jørgensen, 2012 ; Geels, 2018 ; Geels, 2019 ; Geddes and Schmidt, 2020 ). However, there are limits to these general theories, and specific, practical case studies are important complements to assess such transitions ( Kanger, 2021 ).

The specific barriers to commercializing new renewable power, sustainable transportation, and energy efficiency technologies present unique challenges. Such technologies often compete with mature incumbents ( Bonvillian and Weiss, 2015 ), including hydrocarbon, nuclear, and earlier-generation clean technologies ( Sivaram, 2017 ) in fragmented, regulated markets ( Energy Gov, 2020a ). Moreover, clean and efficient energy technologies are at varying stages of development Wind and solar are fully mature and commercialized ( Balachandra et al., 2010 ) while carbon capture and utilization ( Sanchez and Kammen, 2016 ) is neither. Investment needs for technologies at different stages and shortfalls described as “valley(s) of death” are well described ( Clyde et al., 1996 ; Brown et al., 2007 ); yet, relative to many externally funded businesses, clean energy companies have considerable time ( Balachandra et al., 2010 ) and capital requirements, which limit their growth rates and/or profit margins ( Powell et al., 2015 ) and make for poor fits with most venture capital ( Gaddy et al., 2017 ).

To lower barriers to clean and efficient energy technology development and commercialization, governments have had roles in energy innovation as sponsors, partners, regulators, customers, or some combination ( Fuchs, 2010 ; Bonvillian, 2018 ; Kattel and Mazzucato, 2018 ). Governments have directly influenced technology commercialization ( Zahra and Nielsen, 2002 ) via policy, including regulations, tariffs, taxes, rebates ( Bronzini and Piselli, 2016 ); legal fines and court rulings; research funding ( Azoulay et al., 2018 ; Goldstein et al., 2020 ); and by being a critical first customer for a new technology. Studies spanning many countries have explored the impact of government on technology commercialization extensively ( de Almeida, 1998 ; Foxon et al., 2005 ; Yeh, 2007 ; Mazzucato, 2013 ; Tse and Oluwatola, 2015 ; Lewis et al., 2017 ) including comparative studies of impact ( Popp, 2016 ; Goldstein et al., 2020 ; Popp et al., 2020 ). The public sector has also stimulated commercialization indirectly by supporting an “innovation ecosystem,” or R&D infrastructure that promotes cooperation and open shared resources between public ( Anadon et al., 2016 ) and private ( Oh et al., 2016 ; Pinto, 2020 ) organizations. In some situations, researchers have argued the impact of government policy on technology development has been equal to or greater than prices and market forces ( Wiser, 2000 ; Jacobsson and Lauber, 2006 ).

The rate of technology development and diffusion also depends on business factors, including the stage of commercialization for investment ( Nevens et al., 1990 ; Murphy et al., 2003 ), corporate culture ( Nevens et al., 1990 ; Treacy and Wiersema, 2007 ), and management focus ( Buckley-Golder et al., 1984 ; Christensen, 2015 ). For clean and efficient energy technologies, increased attention to environmental and social impacts has helped attract capital, though such impacts have been insufficient to entirely realign investor priorities ( Balachandra et al., 2010 ) or customers’ tolerance for cost or technology risk ( Gompers and Lerner, 2001 ; Brown et al., 2007 ; Verbruggen et al., 2010 ; Gross et al., 2018 ). In practice, adoption of new technology occurs only if it presents value that is unavailable elsewhere ( von Hippel, 1988 ).

Considering the intense and diverse risks entailed by any business operation ( Hall and Woodward, 2010 ) and especially new ventures ( Linton and Walsh, 2003 ; Popp et al., 2020 ), the barrier to technology diffusion decreases once a successful product exists. This fact highlights the importance of the initial private sector commercialization of clean and efficient energy technologies, and the paths these technologies take to their respective first markets may therefore contain insights for clean tech commercialization.

The purpose of this policy and practice review paper is to evaluate the conditions and identify generalizable approaches for successful first commercialization of clean energy technologies, a rarely studied phase of research and demonstration and a technology sector of considerably less focus in the literature compared to consumer products. The paper seeks to inform research investment by government program managers and industry decision-makers for technology commercialization in order to advance the transition to a low-emission future. To that end, this work presents four case studies detailing public-private partnerships that resulted in clean energy and energy efficient technology commercialization. While case study papers typically focus on a single technology or technology type, this paper uses diverse case studies to identify key details of the technologies’ transition from lab to first market with emphasis on the enabling factors of the innovation and the market landscape that led to initial success.

The paper does not cover later developments of these technologies toward full market acceptance, nor does it address current early or pre-commercial technologies; instead, the case studies focus on the critical period between advanced research demonstrations and first commercial market success. Common features relevant to broader decision-making in R&D and commercialization processes were identified across the case studies, drawing on primary sources and interviews with government program managers and industry partners that were involved in the adoption of these technologies. The conclusions present specific approaches for key stakeholders involved in energy technology commercialization—government research program managers, technology developers, and business decision makers—to further energy technology development and commercialization initiatives.

Methodology

The data and arguments put forth in this analysis came from primary sources based on a case study approach. These sources include one-on-one and panel interviews from subject matter experts who hold or have held critical leadership roles and contributed to the development of their respective technologies, and four workshops (one on each technology) conducted with government research sponsors. Over 50 experts contributed input over 6 months in mid-2020, including key individuals from the companies involved, their research partners from national laboratories, and the government program managers for each technology (see list of names in the Acknowledgements). The government subject matter experts included the U.S.-based program managers responsible for establishing targets and overseeing technology research programs in these specific areas. Industry partners and research collaborators interviewed were involved in the technology development and the relevant public-private partnerships. All participants were from the United States with one exception from Europe.

The case studies selected originated from the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy’s (EERE) portfolio of investments. The following criteria were used to select the cases for this paper:

Diversity of technology type within the broad category of clean energy and energy efficiency. Selected technologies covered renewable energy generation, energy efficiency, and transportation-related equipment that are implemented by power developers and manufacturers with the end users being power companies, industrial operators, and general consumers. This diversity enabled exploration of various drivers of first commercialization of dissimilar technologies and applications.

Diversity of commercialization approaches and strategies. Selected technologies were commercialized by both start-ups and established companies as completely new technologies to the market, major changes to an existing technology, and efficiency enhancements largely invisible to the consumer. This diversity enabled exploration of approaches to first commercialization by different types of organizations based on a variety of policy and market drivers.

Fully commercialized technology. Technologies that had achieved market success enabled identification of the pathways and elements around first commercialization, rather than selecting technologies that were still in development and had not completed their early commercial stage. This was a relatively small subset of technologies with a few caveats, as elaborated below.

Data for these case studies came from internal program metrics, contracts with industry, patent portfolios, published research papers, and government documents that recorded industry interviews and collaborations (and the terms and conditions that are associated with these interactions). Targeted interviews with questionnaires prepared for each technology were conducted with program managers, industry management, and researchers who were participants in the technology development at the time. Generalized energy technology development approaches were derived from these primary data collection sources through careful evaluation by case study participants and the authors. Specific source materials and interviews are referenced within each of the case studies presented in section 3.

Note that there are several areas of constraint within this study. First, the technologies selected for the case studies all reached some level of commercial success, although limited in some cases, since the focus is on first successful commercialization. As with any program directed toward high-risk innovation, many clean energy and energy efficiency technologies supported by government programs never move beyond the lab or demonstration stage or are partially commercialized before failure to fully reach the market ( Mufson, 2011 ; Kao, 2013 ). This paper focuses on success factors, whereas limits to success represent an area for future evaluation. Second, there is no counterfactual data on the development of these specific technologies without the involvement of DOE. So, the findings may be relevant to specific circumstances for U.S. government R&D programs and not universal strategies as every technology’s path to commercialization differs. Third, the study’s data and information were largely historically collected, not on-going real-time data collection during the development of a portfolio of technologies. This also represents a future area of study for new research and commercialization investments that is briefly discussed in the Conclusions.

Research and commercialization case studies

This section presents summaries and key findings pertinent to the development of four technologies—thin film photovoltaic solar panels, highly efficient wind turbine blades, dual-stage refrigeration evaporators, and fuel cells for material handling equipment—with generalized findings in section 4.

Thin film solar photovoltaics

Thin film cadmium telluride (CdTe) photovoltaic (PV) modules became a commercial product after nearly 30 years of R&D and collaboration among national labs, universities, and private companies ( Cheese et al., 2016 ). This case study focuses on the commercialization success of the company First Solar, which benefited from U.S. DOE solar research, directly received DOE funding in research partnerships in the 1980s–2000s, and subsequently led cost reductions for PV module commercialization ( Hegedus and Luque, 2005 ; Scheer and Schock, 2011 ; Cheese et al., 2016 ). This case study argues that addressing regulatory needs within this thin film PV technology’s first major market and establishing a proven product at a price and time for a market that was ready for it, led to its early success.

DOE collaboration generated an innovation ecosystem of thin film PV research that made key advances in CdTe PV technology by funding universities and industrial partnerships from the late 1980s to early 2000s, primarily through programs at the DOE’s National Renewable Energy Laboratory (NREL). An early notable advance during this period was the demonstration of 15.8% cell efficiency (a record at the time) ( Britt and Ferekides, 1993 ) using a cadmium chloride (CdCl 2 ) heat treating process (US Patent 4873198). First Solar co-developed a high-rate vapor transport deposition manufacturing technique (US 5945163) to produce CdTe-based panels at a larger scale—an alternative to the slower, costlier close space sublimation manufacturing process. With suitable device efficiency and scalable manufacturing procedures in place, R&D focus shifted to testing and validation of product reliability. First Solar used testing standards, product quality certifications, and outdoor testing facilities funded by DOE and led by Arizona State University and NREL to prove by 2003 that its modules were ready to enter the solar market. Figure 1 shows a 0.6-kW CdTe test array at NREL’s outdoor testing facility, as well as the structure of a CdTe solar cell.

FIGURE 1 . A 0.6 kW First Solar CdTe PV test array installed June 1995 at NREL’s Outdoor Test Facility (A) and CdTe PV cell structure (B) .

First Solar entered Germany’s major solar market in the 2000s. To do this, First Solar’s modules needed to meet energy performance and regulatory requirements, which included electronic waste regulation and restrictions on the use of certain toxic substances like cadmium (Directive 2002/96/ EC, 2003 ). In 2004, the European Union (EU) Commission evaluated these policies through a workshop on life-cycle analysis and recycling and disseminated DOE-funded research on CdTe from the DOE’s PV Environmental Health and Safety Assessment and Assistance Center at Brookhaven National Laboratory. This effort helped resolve concerns about emissions and recyclability of CdTe PV modules with independent, peer-reviewed studies. Later in 2004, First Solar secured its first contract for its compound thin semiconductor modules in the German PV market—a commercial turning point for CdTe p V. In 2005, First Solar announced a module takeback and recycling program to respond to evolving EU policy directives. These efforts helped communicate First Solar’s responsiveness to regulatory issues, and they addressed public perception of risk sufficiently to access key markets.

CdTe modules are less efficient than silicon-based panels, but owing to their reduced manufacturing costs, they led the lowest price per watt from the mid-2000s until the mid-2010s ( Figure 2 ) ( First Solar Inc, 2020 ; Fraunhofer Institute of Solar Energy Systems, 2020 ; Mints, 2020 ). Significant demand for photovoltaics in the European market during this time coincided with insufficient residual wafers from integrated circuit silicon, as well as a temporary shortage in polysilicon, which were used to make silicon solar photovoltaics ( Photon Energy Group, 2020 ).

FIGURE 2 . First Solar’s production, capacity, and manufacturing cost enabled a decrease in module prices to levels lower than silicon module costs during an increase in polysilicon spot prices (which signaled underlying polysilicon market trends), producing a serendipitous window for CdTe module market entry. Cost per watt adjusted to be real values for 2019. Data sources: ( Bernreuter Research, 2020 ; First Solar Inc, 2020 ; Photon Energy Group, 2020 ).

Key Findings : The thin film solar PV case study identified the successful use of three key commercialization strategies: development of technology with many commercially relevant inputs through public/private partnerships, alignment of set technology cost goals and product development that achieved them, and timing compatibility of technology readiness and market opportunity. In this case, government funding over decades enabled foundational materials research and consistent testing standards, that could be taken up by industry as the technology neared commercial readiness. Chance also favored a prepared company with the right product at the right time: CdTe photovoltaics of proven reliability were a lower-cost replacement in a clean energy market with an open window of opportunity, allowing the early commercialization success of this solar technology.

Wind blade improvements

Between 1995 and 2008, a funded ecosystem of universities, national labs, and private companies pursued advances in wind turbine blade design agnostic to a specific approach or design solution. This initiative was conceived and managed by Sandia National Laboratories, in partnership with NREL, and culminated in innovations that substantially increased adoption of wind energy and decreased the levelized cost of electricity (LCOE) for wind ( Larwood et al., 2014 ). From 2009 through 2018, wind energy prices, as indicated by executed power purchase agreements, decreased by over 60% (R. Wiser et al., 2021 ), holding steady from 2018 to 2021. Although several factors contributed, wind subject matter experts identify improved blade designs as one of the largest innovation factors contributing to wind energy technology cost reductions during this period. This case considers blade design advances and the enabling R&D environment that ultimately led to LCOE improvements, and thus to early market success.

Historically, blade lengths have increased over time to capture more energy. With traditional blade designs, the corresponding increase in the blade mass incurred costs not justified by the associated increase in energy capture. The longer, heavier blades resulted in higher loads and increased cost throughout the turbine system. The exploration in the early 2000s of blade design advances for wind turbine system optimization led to the development of turbine blades with flat backs and bend-twist coupling geometries. These two separate innovations, developed in parallel, allowed for significantly longer blades and thus more energy delivered by each turbine without compromising reliability.

The bend-twist innovation is an inherent structural design for blades to twist as they experienced a wind gust, thus passively reducing the pitch of the blade and lowering the load ( Figure 3 ). This technology was much simpler in concept and operation than contemporary suggestions to change blade pitch with active aerodynamic control devices requiring multiple actuators and moving parts. The flat-back design creates a structurally enhanced portion of the blade closest to the connection to the hub by flattening the trailing edge while the outboard portion remains shaped like a traditional airfoil. Flat-back blades balance ease of manufacturing, aerodynamic performance, and structural strength while reducing weight and enabling a longer, more reliable blade ( Miller et al., 2018 ).

FIGURE 3 . Digital rendering of a modern bend-twist flat backed wind turbine blade. Cross sectional view of the flat back is seen in the upper left corner.

The combination of bend-twist and flat-back design enabled longer blades with less mass ( Paquette and Veers, 2009 ). Figure 4 illustrates industry trends in rotor mass and diameter before and after the bend-twist and flat-back innovations ( Thewindpower, 2020 ).

FIGURE 4 . Rotor mass in tons vs rotor diameter in meters for Siemens wind turbine products with trend lines fit before (blue triangles) and after (green circles) the adoption of bend-twist coupling and flatback airfoils (2008). Significant reduction in scaling trends enables larger rotors and lower levelized cost of energy. Data source: ( Thewindpower, 2020 ).

The genesis of these design concepts was in the aerospace industry, and academic papers and presentations in open fora documented their innovative extension to wind turbine blades. As the flat-back and bend-twist designs proved out in the R&D ecosystem, private companies adapted the innovations to their own proprietary blades and analysis tools. There were no patents protecting the fundamental applications to wind blades. There were, however, demanding engineering and manufacturing requirements, especially for bend-twist blades, which deterred smaller and less engineering-focused firms. The twin considerations of intellectual property and engineering complexities have shifted focus in the wind turbine industry away from patents toward trade secrets and the development of proprietary internal computational design and analysis tools. Ultimately, industry responsiveness to flat-back and bend-twist coupled blade designs led to innovations that were commercially successful in first markets and, combined with related supporting design tools, drove diversity in blades across the industry, serving as differentiators across companies.

Key Findings: Public-private partnerships that connect universities and private companies with national lab research infrastructure, along with a selectively open approach to intellectual property, spurred the development of advanced wind blade designs. In this case, government played a convening role for innovation in a nascent industry and funded shared research user facilities. In turn, the wind turbine industry successfully commercialized the resulting advanced engineering designs that overcome the tradeoff between rotor diameter and mass inherent to incumbent technologies. The resulting decrease in LCOE, which wind technologists estimate to be nearly 33%, enabled significant wind power expansion post-2008 and led to a worldwide market over $100 billion per year ( Global Wind Energy Council, 2019 ). Given that most major commercial turbines now use elements of flat-back and/or bend twist innovation in their turbine designs, these innovations had a substantial impact on wind deployment and the global economy.

Efficiency in refrigerators

Refrigerators and freezers account for ∼7% of the total electricity usage in U.S. homes, or 105 billion kilowatt-hours and 74 million metric tons of CO 2 annually ( EIA, 2020 ; Energy Star Portfolio Manager, 2020 ). Historically, the bulk of this electricity demand has driven vapor compression to achieve cooling with a single compressor, evaporator, and condenser. This design unavoidably mixes air between the fresh food and freezer compartments, causing fresh food to lose moisture that forms frost on the evaporator coil. Inadequate or over-cooling degrades food preservation quality and is difficult to prevent with a single evaporator, which cannot simultaneously accommodate the different cooling requirements for the two separate compartments. Two evaporators with a post-condenser valve system allows each evaporator and heat exchanger to receive the correct amount of flow for the cooling load, while increasing energy efficiency (see Figure 5 ). However, dual-evaporator systems driven by two compressors (i.e., two separate vapor compression systems) require extra components, driving up production costs.

FIGURE 5 . Dual evaporator flow and component diagram (Adapted from US Patent 9285161B2).

Higher costs may be unacceptable to manufacturers, who already have low margins from most refrigerator sales. Consumers are especially price sensitive when purchasing a refrigerator and may be unwilling to pay a premium for increased energy efficiency, opting instead to pay more for such design features as extra compartments or embedded touchscreens. These market forces incentivize manufacturers to invest enough into efficiency R&D to meet minimum efficiency standards, but little more. In this way, efficiency innovations may be driven more by minimum standards requirements than direct consumer demand. Figure 6 shows the annual energy use over time for units sold in a given year and highlights the step-like nature corresponding with new minimum efficiency standards.

FIGURE 6 . Average annual electricity use of new refrigerator-freezers and freezers. Data sources: ( Rosenfeld, 1999 ; Energy Conservation Standards for Residential Refrigerators, Refrigerator-Freezers, and Freezers, 2010 ; AHAM, 2018 ).

Whirlpool Corporation and DOE began work on a single-compressor, dual-evaporator system in 2014 as part of a DOE initiative to increase appliance efficiency. Funded by the American Recovery and Reinvestment Act (ARRA), Oak Ridge National Lab (ORNL) provided R&D resources and staffing in collaboration with Whirlpool. A cooperative R&D agreement allowed Whirlpool access to ORNL modeling tools and advanced experimental facilities to assist in the design, validation, and prototyping of this new technology while retaining ownership of the intellectual property. The team was able to demonstrate an advanced refrigerator design with more than 50% energy reduction per unit volume (as compared to the 2001 federal minimum efficiency standard), with a cost increase of less than $100. The innovation led to a family of 14 patents for Whirlpool and enabled the company to meet new minimum efficiency standards ( Energy Gov, 2020b ).

Key Findings: The refrigerator efficiency case study typifies a successful commercialization pathway driven by alignment between regulatory constraints and R&D priorities. In this case, the government collaborated with an established company through cooperative research agreements utilizing government research models and facilities. The progress in refrigerator efficiency mandated by standards and achieved by Whirlpool’s dual-evaporator technology spurred other companies to develop similar systems to meet the minimum efficiency requirements, until more R&D could be done on other components such as compressors and insulation materials. As those components achieved cost-competitiveness with the dual-evaporator system, a diversity of solutions to comply with standards emerged. Dual evaporator systems are still present on modern day refrigerators, primarily on higher-end units where cost is already at a premium level; lower-end models are simply equipped with higher efficiency and less complex components with advanced adaptive compressors emerging as a technology for highly efficient temperature control. The dual-stage evaporator thus served to satisfy the needs of the first-market conditions set by regulatory policy, and in turn compelled additional R&D of components that met similar needs with reduced complexity and cost.

Fuel cells for material handling equipment

Fuel cells can provide electricity via redox chemistry for stationary, transportation, and portable power applications. DOE has invested in hydrogen fuel cell research since the early 1990s, when successful fuel cell applications (such as in spacecraft and satellites) were too costly for commercial products. Today, large-scale follow-on investment occurs worldwide ( Hydrogen Society of Australia, 2020 ). This case study focuses on fuel cells deployed in forklift and other material handling equipment (MHE) and consider the unique compatibility of this niche market for the technology.

The “captive” nature of MHE fleets made them a practical fit as a first-commercialization target for fuel cells in transportation applications. Integrators forgo the need for a large network of hydrogen refueling stations across the country, opting instead for one location within a warehouse facility. Historically, gasoline-, propane-, or diesel-fueled engines powered MHE for outdoor operations while lead acid batteries powered indoor applications where emissions must be controlled. Lead acid battery-powered MHE exhibit performance issues at low charge, requires long charging and cool down times that can disrupt warehouse throughput, and have limitations in cold environments like refrigerated warehouses. Fuel-cell-powered MHE resolves these issues, as fuel cells do not emit harmful air pollutants or carbon dioxide at the point of operation, and they work in cold environments without degradation of performance ( Figure 7 ). These attributes can lead to reduction of labor costs associated with changing and recharging batteries by as much as 80% while also eliminating the need for battery rooms, shrinking the infrastructure footprint by 75% ( Ramsden, 2013 ).

FIGURE 7 . Fuel-cell-powered forklifts in a Sysco warehouse in Houston, where they operated in part in a refrigerated environment.

As potential entrants to this niche market in the late 2000s, fuel cell MHEs made a strong case for displacing lead acid battery-powered MHEs. Other emerging power technologies such as lithium-ion batteries were not yet price competitive. At the time, hybrid electric vehicle lithium-ion batteries needed a 3–5x cost decrease to achieve wide commercialization ( FY, 2009 ; Annual Progress Report for Energy Storage R&D, 2009). In 2009, funding from ARRA enabled a large-scale fuel cell MHE demonstration. Through competitive awards with industry, DOE deployed hundreds of hydrogen fuel-cell-powered lift trucks along with supporting systems (fueling infrastructure, data collection and analysis, and operator training). The U.S. Department of Defense also deployed 100 fuel-cell-powered lift trucks at three centers and an army base. A detailed analysis conducted by NREL documented the techno-economics of fuel cell MHE, summarizing the conditions where the technology was cost competitive ( Ramsden, 2013 ).

Throughout the 2010s, guidance and education originating from ARRA deployment and follow-on work led to the integration of 40,000 MH E units within the industry ( John, 2021 ). At the same time, technology competitors surged and the cost of lithium-ion batteries decreased beyond projections (89% since 2010) ( BloombergNEF, 2021 ). Additionally, these batteries’ recharge speed increased, and they gained acceptance in a variety of markets. Comparisons continued to show fuel cells’ utility for refueling in high throughput applications compared to similar fast charging batteries such as lithium-ion ( Cano et al., 2018 ). In the last year, some MHE manufacturers that had announced production manufacturing of fuel cell forklifts have pivoted to advertising forklifts that work with lithium-ion battery technology for similar use cases. The opening of the MHE market to new innovations created by fuel cell forklifts helped spawn further electrification of MHEs and interest from industry in converting to cleaner technologies ( Nuvera, 2021 ).

Key Findings: The fuel cell MHE case study demonstrates all three approaches for commercialization success, including collaboration between private industry and publicly funded research testing opportunities (e.g., ARRA DoD demonstration), R&D advancing technology performance that could meet market requirements, and technology that had performance advantages in time for addressable opportunities. In this case, the government support for research continued through full-scale demonstration funding and direct procurement of early commercial technologies for private and government facilities. Ultimately, MHEs powered by fuel cell technology achieved an overlap of technology readiness and market opportunity, demonstrating energy density, fast refueling, and fuel storage capacities that exceeded performances by competitive contemporary alternative technologies.

Generalized commercialization approaches for energy decisionmakers

Although the four case studies have distinct technologies and stakeholders, they also have common approaches that influenced the technologies’ commercial successes, described below, and summarized in Figure 8 . These approaches are relevant for all stakeholders interested in future innovation related to energy. In particular, success depended on a combination of three approaches, and while these have been mentioned in the literature, their application to energy technology R&D has not been made explicit until now. Also noted are key distinctions between market contexts for the four technologies.

FIGURE 8 . Graphical summary of common approaches and key distinctions across four case studies of first commercialization.

First, technology development and commercialization depend on technology fit with research infrastructure and public-private partnership models. Each case study featured collaboration between the private sector and a research institution with critical shared infrastructure supported by an innovation ecosystem. Private sector technology developers leveraged government funding in research capabilities, including testing facilities, standards, and independent analysts. Large energy test facilities are beyond the resources of many companies, especially those in a nascent industry (e.g., PV and wind in the late 1990s). Likewise, field validation and consensus standards often emerge from efforts no company can pursue on its own. In these cases, government often has an important role as a steward of shared resources—physical and informational—that are required for progress. Our findings indicate that at this stage, open access to intellectual property may benefit a nascent industry most broadly. For pre-commercial energy technologies, the long time horizons and competitive challenges mean that it is often necessary to identify and develop shared-use facilities and standards to meet needs through many unexpected technology and market developments. Because public agencies can take risks that private entities cannot, the government is often the first investor in any innovative area; these investments both de-risk and leverage private capital aimed at commercialization. Industry leaders who successfully engage government often begin collaborating on pre-commercial technology, followed by independent innovation that differentiates their companies’ products. Such strategies require significant knowledge of government programs, flexibility in contracting, and strong relationships among individual researchers. For example, with wind blade improvements, technologists collaborated across multiple institutions and companies within an open innovation ecosystem to share or discard ideas, stimulating rapid iteration to overcome technical hurdles. In other cases, individual companies collaborated more independently with government resources, as with the development of dual-evaporator systems for refrigerators.

The second area of commonality among the case studies was a high degree of alignment between government regulations, R&D priorities, and market forces. With extensive stakeholder input, government leaders and program managers publish strategic objectives (e.g., increase energy efficiency) and technical targets aimed at specific priorities to incent innovation. Given higher tolerance for technology risk in government than the private sector, program managers can follow a correspondingly longer path for commercialization. These paths may have a commercialization endpoint identified (e.g., PV panel cost per watt target) or related technology performance targets (e.g., seeking materials with fuel cell properties before reduction to practice), and often require revision in response to technological and external developments. In areas where there is a national objective (e.g., efficiency of refrigerators) but insufficient consumer demand to drive change, government programs may support meeting regulations and standards and enabling industry innovation through access to research and testing capabilities. Each case study technology catered to a specific target market that was in turn responsive to policy, regulation, economics, environment, and manufacturer needs. Fit between product and market is a well-established success factor, and clean energy and energy efficient technologies are no exception. However, unlike most consumer products where the market fit is to consumer demand, clean and efficient energy technologies must also meet specific economic and regulatory requirements, often while contributing toward government or societal objectives noted above.

Finally, each case study found compatibility between time scales required for R&D, product development, and addressable opportunities, including a degree of serendipity. Building on years of fundamental research, funding for later-stage technologies focused on demonstration and commercialization based on market requirements for success. Early development decisions addressed constraints such as environmental health, manufacturability, customer price sensitivity, and demand for drop-in solutions. The case studies profiled various timing compatibilities based on the stage of technology acceptance and market readiness. Highly efficient turbine blades and thin film solar PV advanced fundamentally new technologies, timed with increasing demand for low-emission energy sources—a high-risk market approach rewarded with rapidly increasing sales of renewable energy technologies. While less conspicuous, fuel cells and dual evaporators had performance advantages versus incumbents (e.g., reduced fueling time for MHE and increased efficiency across multiple cooling loads for refrigeration). These advantages led to inclusion in established products that have been viable first markets, and, as with any technology, further growth depends on overcoming increasing competition.

The diverse cases revealed a key distinction between new power generation technologies versus those that create incremental efficiency or energy source changes. Electricity suppliers have widely adopted the core energy generation technologies (thin film photovoltaic cells and efficient wind turbine blades), and these technologies continue to find success in the market. The dual-stage refrigeration evaporators and fuel cells for MHEs achieved lower market penetration as individual technologies. Instead, their development instigated an opening of the market to a multitude of options for cleaner or more efficient energy within their target technology. There are multiple explanations for this difference. First, there are national incentives and sub-national mandates for adoption of renewable power generation that do not exist for other technologies. Moreover, first commercialization of end-use technologies often introduces consumer-focused features (such as better food preservation or reduced equipment downtime) with efficiency improvements receiving lower priority.

Conclusions and policy implications

Commercialization pathways of energy technologies are as diverse as research fields and markets themselves. Each case involved an appropriate set of research policy tools for the stage of the technology development and the partners. Thin-film solar developed through decades of research funding and was enabled through standardized testing protocols. Wind blades improved through a government-convened innovation network and shared research facilities. Advances in refrigeration efficiency emerged from collaboration between government researchers and a motivated established company. Fuel cell equipment launched through direct procurement support after years of government funded technology research. While the specific approaches varied, these diverse case studies did allow generalizable conclusions for both the private and government sector.

Successful private sector decision makers have a deep knowledge of the technology as well as the market and relevant policies, and their strategies account for all these arenas. Leaders at successful companies take advantage of available research infrastructure, including opportunities for cost share and access to shared knowledge or other assets. The timing of such opportunities lends an element of serendipity to commercialization that favors technologies and organizations that are well-prepared, for example through familiarity with resources and priorities of research agencies, government regulators, and other stakeholders.

Government research program managers and policy makers have an array of policy tools to support first commercialization of technologies, although they should be applied differently based on the technology and opportunity. Research funding, shared-use facilities, technology targets, open innovation, and deployment incentives can create the success factors for new energy generating technologies. Regulations, standards, testing, and demonstrations enable advancement in efficiency and powering existing technologies. Every case relied on mission-driven, personalized engagement between government and other stakeholders—in industry, academia, standards-development organizations, and others—that informed ambitious but realistic strategic targets and forged partnerships around them. Together, these elements were essential to creating the first commercialization at the right time. They also establish a self-reinforcing cycle, where successful projects lead both to technology and market impact, and also encourage further engagement between stakeholders and government. R&D agencies have encouraged such cycles for solid-state lighting ( National Academies of Sciences, 2017 ; National Research Council (2013) , geothermal energy ( Burr, 2000 ), and in other cases.

This policy and practice review paper and similar business case studies highlight the need for a new approach to understanding success factors for commercialization. Commercialization and related industrial policy case studies are largely historical, retrospectively collecting data and conducting interviews to extract findings. A future approach for government and industry research program managers would be a proactive longitudinal study that would start with defining a set of measurable inputs and success metrics to be applied during research on a diverse portfolio of energy technologies. These data would be collected periodically and interviews with researchers and various stakeholders would be recorded in real-time, indexed, and archived. Over a decade or more of the technologies’ development through either failure, stagnation, or first commercialization, a set of analyzable information would become available to quantitatively model and statistically assess for common definable conditions for success. Ideally, the information might also be used to identify the preparedness needed to take advantage of serendipity to make the leap from research to successful energy product.

The case studies presented here demonstrate that productive interactions between innovative businesses and government have led repeatedly to successful first commercialization of clean energy and energy efficiency technologies. Together, they reveal generalized approaches to new research and interaction with industries comprising the clean energy economy. Future longitudinal and structured cross-cutting studies of energy technology research programs could further enable successful investment and commercialization of advanced energy technologies.

Author contributions

All authors contributed to the initial writing. Additionally, JE, WM, MM, BM, and BW contributed to the conceptualization, methodology, and revisions. BW also supported with funding.

This work was authored in part by the Joint Institute for Strategic Energy Analysis (JISEA) and the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by U.S. DOE Office of Energy Efficiency and Renewable Energy Building Technologies Office. The views expressed herein do not necessarily represent the views of the DOE, the U.S. Government, or sponsors.

Acknowledgments

Special thanks for photos and graphic design to Dennis Schroeder ( Figure 1A ), Alfred Hicks ( Figure 1B ), Besiki Kazaishvili ( Figure 3 ), Jennifer Kurtz ( Figure 7 ), and Nicole Leon ( Figure 8 ). The authors would also like to thank the many experts we interviewed, who reviewed drafts, or otherwise contributed to this paper, including: Andenet Alemu, Jeff Alexander, Sam Baldwin, Garrett Barter, Erin Beaumont, Markus Beck, Jen Bristol, Steve Capanna, Tom Catania, Al Compaan, Fernando Corral, Tim Cortes, Andrea Crooms, Peter Devlin, David Feldman, David Eaglesham, Chris Ferekides, Steve Freilich, Christina Freyman, Vasilis Fthenakis, Nancy Garland, Sarah Garman, Jennifer Garson, Charlie Gay, Markus Gloeckler, Alberto Gomes, Marcos Gonzales-Harsha, Bill Hadley, Michael Heben, Mark Johnson, Stephanie Johnson, Becca Jones-Albertus, Richard King, Jennifer Kurtz, Jeff Logan, Sumanth Lokanath, Robert Margolis, Wyatt Metzger, Anne Miller, Steve Ringel, Doug Rose, Karma Sawyer, Jared S. Silvia, Jim Sites, Henrik Stiesdal, Martha Symko-Davies, Govindasamy Tamizhmani, Lenny Tinker, Christopher Tully, Paul Veers, Alan Ward, Johanna Wolfson, Jetta Wong, Leah Zibulsky and Ken Zweibel. We also thank our journal reviewers for their insightful comments.

Conflict of interest

Author ED is employed by Renewable Energy Consulting Services, Inc.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: renewable energy, energy policy, technology commercialization, photovoltaics, wind turbines, refrigeration, fuel cells

Citation: Engel-Cox JA, Merrill WG, Mapes MK, McKenney BC, Bouza AM, DeMeo E, Hubbard M, Miller EL, Tusing R and Walker BJ (2022) Clean energy technology pathways from research to commercialization: Policy and practice case studies. Front. Energy Res. 10:1011990. doi: 10.3389/fenrg.2022.1011990

Received: 04 August 2022; Accepted: 25 October 2022; Published: 09 November 2022.

Reviewed by:

Copyright © 2022 Engel-Cox, Merrill, Mapes, McKenney, Bouza, DeMeo, Hubbard, Miller, Tusing and Walker. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jill A. Engel-Cox, [email protected]

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Household clean energy consumption and health: Theoretical and empirical analysis

1 College of Economics, Sichuan Agricultural University, Chengdu, China

2 School of Business and Tourism, Sichuan Agricultural University, Chengdu, China

Abbas Ali Chandio

Dungang zang, yinying duan, associated data.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The impact of energy consumption on health has become a widely debated topic around the world. However, much of the current research on this topic lacks a theoretical basis. As a result, this paper employs both theoretical and empirical analysis to investigate the impact of household clean energy consumption on residents' health. First, based on the theories of health economics and energy economics, this paper believes that the usage of clean energy can improve the health of residents. Then, the sample for this study is comprised of data from the 2018 China Health and Retirement Longitudinal Study, and the Order Probit Model is applied for the empirical analysis. The outcomes of basic regression, robustness testing, and the treatment of endogenous factors reveal that the usage of clean energy has greatly benefited the health of residents. Furthermore, the heterogeneity analysis shows that long-term use of clean energy greatly improved the health of non-religious people and had a more pronounced impact on the health of women and low-income residents. In addition, the mechanistic analysis indicates that subjective happiness and air quality played a partial mediating role in the impact of cleaner energy consumption on health. Finally, cleaner household energy reduced the prevalence of hypertension, hyperlipidemia, lung disease, asthma, and depression. The conclusion of this paper supports the view of some existing literature, and several policy recommendations are made based on the research findings.

Introduction

The health crisis is an obstacle to the sustainable development of individuals, families, nations, and the world ( 1 , 2 ). From 2000 to 2020, the global mortality rate due to several diseases showed a continuous increasing trend (excluding deaths due to SARS and COVID-19) ( 3 ). All inhabitants of the world are threatened by various diseases, but health problems are more serious in developing countries. In the past 10 years, the number of deaths in China has increased by about 10 million each year (excluding deaths from COVID-19) ( 4 ). Many studies discussed the influencing factors of health from different perspectives, and some studies investigated the impact of household clean energy consumption on individual health.

Twumasi et al. ( 5 ) used the Order Probit Model to analyze research data from Ghana, and the results showed that the use of clean cooking fuels increased the proportion of healthy household members by 19.11%. Cleaner household energy improves indoor air quality ( 6 ) and reduces the probability of residents being diagnosed with respiratory diseases such as asthma, bronchitis, tuberculosis, and lung cancer ( 7 , 8 ). At the same time, long-term household use of clean energy mitigates the risk of climate extremes, improves outdoor living conditions and reduces the production and spread of disease ( 9 ). The use of clean energy increases the efficiency of tasks such as cooking and heating ( 10 ), saves time for residents to engage in productive activities, increases household income, and enhances disease prevention and treatment ( 11 ). The long-term use of clean energy in households significantly increases residents' life satisfaction and wellbeing ( 12 , 13 ), thereby improving their mental health ( 14 ). The health effects of household clean energy consumption were more pronounced for women ( 15 ), particularly in terms of lower rates of maternal morbidity and mortality ( 16 ). In addition, the positive health effects of cleaner energy use are more pronounced in developing countries, with households using clean energy sources for instance LPG having higher levels of health than those using non-clean energy sources like as coal in Pakistan ( 17 ). In the case of China, Liu et al. ( 18 ) found that using clean energy reduced the odds of residents being diagnosed with chronic lung disease and heart disease in China's families. Likewise, Zhang et al. ( 19 ) analysis research data from China, and the findings revealed that household energy cleanliness improved the physical health of rural residents and improved the mental health of urban residents.

According to the current literature, long-term household use of clean energy is beneficial to residents' health. The macro-statistics of China support this viewpoint. This paper compiled and plotted data from China's National Statistical Yearbook on per capita energy consumption and resident mortality (respiratory disease mortality + mental disease mortality) from 2009 to 2019 (see Figure 1 ). As shown in Figure 1 , per capita consumption of clean energy (electricity + LPG + natural gas) has been increasing, while consumption of non-clean energy (coal + coal gas) has been decreasing, indicating that China's household energy consumption is shifting to a cleaner energy. At the same time, residents' mortality rates from respiratory and mental diseases were declined. The choice of respiratory and mental disease mortality is based on existing research that suggests these two diseases are linked to household energy consumption ( 8 , 20 ). As a result of Figure 1 , it can be concluded that household clean energy consumption benefits residents' health. However, macro-statistics have limitations, which lack of information on household fuel use such as firewood, hay, cow dung, biogas, and solar energy. This problem can be addressed more effectively using micro-survey data. As a result, this paper examines the impact of household clean energy consumption on health using data from the 2018 China Health and Retirement Longitudinal Study (CHARLS).

Per capita energy consumption and resident mortality from respiratory and mental diseases of China. Data source: China National Statistical Yearbook (2010–2020). In this paper, the units of different energy sources are uniformly converted into kilograms of standard coal according to the energy calorie conversion formula.

A relatively consistent conclusion in the existing literature is that long-term use of clean energy can improve residents' health. But most studies have only reached this conclusion based on data analysis ( 5 , 8 ), and few literature explored the internal mechanism of the impact of clean energy consumption on health based on theory ( 21 ). Meanwhile, some studies have used the Order Probit Model to analyze the relationship between energy consumption and health in empirical analysis, but few studies have dealt with potential endogenous problems ( 20 ). Furthermore, the current literature only discusses the impact of clean energy consumption on total health ( 9 , 14 ), and does not analyze whether or how clean energy consumption impacts common diseases.

In summary, this paper makes five marginal contributions to the literature. First, the 2018 CHARLS data is used as a sample in this paper to provide new micro-evidence for the study of clean energy consumption and health. CHARLS focuses on collecting health data from Chinese residents, and using this data as a sample to study the health problems of micro-subjects would be more reliable ( 22 ). Second, this paper introduces a new theoretical analysis concept, and health and energy economics theory can fully reveal the impact of clean energy consumption on health. Third, to address the existing endogeneity problem, this paper employs the instrumental variable method and the conditional mixed process estimation method, which increases the credibility of this paper. Fourth, this paper discusses the heterogeneity of the health effects of clean energy consumption across genders, household economic conditions, and religious beliefs, adding to the findings of previous research. Fifth, this paper examines the impact of clean energy consumption on eight different common diseases, offering a fresh perspective for future research on the subject.

The remaining sections include, Theoretical analysis (Section 2); Data and method (Section 3); Empirical analysis (Section 4); Mechanism analysis (Section 5); Further research (Section 6); Conclusion and policy recommendations (Section 7).

Theoretical analysis

Mushkin ( 23 ) identified health as a component of human capital and previously examined health issues from an economic standpoint. The classic paper by Arrow ( 24 ), “Uncertainty and Welfare Economics,” marked the establishment of health economics. Human capital theory and welfare economic theory have both become important theoretical foundations of health economics ( 25 ). Furthermore, Groosman ( 26 ) put forward the concept of health demand, believed that health can be regarded as an investment activity of people, and first proposed the health production function:

The H represents health; M indicates healthcare; LS shows lifestyle; E stands for environment; S signifies schooling; and X shows other factors that affect health.

Some research enhanced the HPF and examined the dynamic interactions between various factors and health, with household economic condition, human capital (schooling), environment, society, and lifestyle serving as common HPF vectors ( 27 , 28 ). Despite the fact that there have been few studies that incorporate energy (fuel) as a vector in the HPF, earlier research has demonstrated that household energy use is an important factor in health ( 29 ). Consequently, this study establishes the Household Health Production Function (HHPF) with energy consumption:

The H indicates health; EC shows household energy consumption; W represent welfare; HC stands for human capital; ES signifies the household economic status; EN represents environment; SC is social contact; and X shows other important factors (i.e., age, gender, and etc.).

Energy is a basic requirement for household production and daily life. Household energy consumption, according to energy economics theory, is a decision process that seeks to maximize utility ( 30 ). To meet their utility needs, most households use multiple types of energy at the same time ( 21 ). In general, households use four types of energy: first, all clean energy, second, all non-clean energy, third, a mixture of clean and non-clean energy with a greater proportion of clean energy than non-clean energy, and fourth a mixture of clean and non-clean energy with a smaller proportion of clean energy than non-clean energy. To achieve Pareto dynamic optimization of energy consumption, households dynamically adjust their energy mix in response to changes in utility pursuits.

It is assumed that households choose the first energy consumption mix, using clean energy sources in various activities such as cooking and heating. Then clean energy does not produce harmful substances during the combustion process and does not pollute the indoor air, thus not harming health. At the same time, clean energy is more efficient than non-clean energy, saving time for productive, social contact, and educational activities for households, potentially leading to higher household income, increased economic wellbeing, and the accumulation of social and human capital, which in turn contributes to better health. Further, it is assumed that the household chooses the second energy consumption mix. Substances such as carbon monoxide generated during the combustion of non-clean energy will directly damage human health through the respiratory system. Meanwhile, the use of non-clean energy will also cause problems such as air pollution and environmental damage, which indirectly affect health.

In addition, it is assumed that household A chooses the third energy consumption mix and household B chooses the fourth energy consumption mix. Non-clean energy sources will then have a negative impact on the health of both families. However, because the proportion and frequency with which household A uses clean energy is greater than that of household B , household A's health level will be greater than that of household B . In summary, household energy use is included as a vector in the health production function in this paper. The analysis revealed that if households rely on non-clean energy excessively, they not only have a direct negative impact on health but also damage it indirectly through other pathways (e.g., air pollution, decreased wellbeing, etc.), whereas household clean energy consumption benefits residents' health.

Figure 2 shows the theoretical analysis process of the impact of household clean energy consumption on health.

The theoretical mechanism of household clean energy consumption affecting health. Source: The author draws according to the content.

Data and method

The sample for this study is the 2018 China Health and Retirement Longitudinal Study (CHARLS) data, which is published in September 2020. CHARLS is a longitudinal study that began in 2011 and provides definitive information on the health and aging of Chinese families ( 31 ). The 2018 questionnaire covers: demographic backgrounds; family information; health status and function; cognition and depression; informant information; health care and insurance; work and retirement; pension; income, expenditure, and assets; house property, and housing characteristics. The CHARLS covered 28 provinces of China, 150 countries/districts, and 450 villages/urban communities, which are representative at a national level. This paper first matches the data of each module according to the respondent ID; Then extract the data for variables related to this study from the data set; Next, the missing values of variables are processed by means of mean filling, median filling, and deletion, and the data is standardized by the Z-score method; Finally, 11,635 sample data were obtained for empirical analysis.

Explained variable

Health. In the current literature on health issues from the perspective of microeconomics, “health self-assessment” is often used as a proxy variable for “health” ( 32 ). Because “health self-assessment” can reflect both the physical and mental health of micro-subjects to a certain extent ( 20 ). Therefore, we use residents' subjective health evaluation perceptions as a proxy variable for health, and the data of the survey question “What do you think about your health?” was chosen to measure resident's health.

Explanatory variable

Clean Energy Consumption (CEC). “Whether to use clean energy,” “the percentage of clean energy usage,” and “the frequency of clean energy usage” are three commonly used indicators to measure clean energy consumption ( 33 ). However, we cannot obtain data from CHARLS to calculate “the percentage of clean energy usage” and “the frequency of clean energy usage.” Therefore, according to the options in the questionnaire “what is the main source of cooking fuel?” this paper set to CEC = 1 if the respondent chooses clean energy (natural-gas, marsh-gas, LPG, or electricity) and CEC =0 if the respondent chooses non-clean energy (coal, crop-residue, or wood-burning).

Control variables

The individual characteristics, family economic status, and daily life situation of micro-subjects may all have an impact on their health ( 18 ). In empirical analysis, these factors are usually added to the model as control variables, so as to improve the accuracy of the regression results of the core explanatory variables and the explained variables. Therefore, this paper selects age, education level, income, and housing structure, etc. as the explained variables ( 34 ).

Table 1 presents the main variables of this paper.

Variables selection and definition.

In this paper, the mean, standard deviation, and maximum and minimum values of the main variables were calculated using Stata v15.0 software, and the calculation results are reported in Table 2 . The mean of health is 3.13, indicating that residents are in good health, but still about 24% of respondents are unhealthy. There are 7,872 (67.66%) households using clean energy, and another 1/3 of the households are still using non-clean energy. Most of the respondents were middle-aged (mean age = 50.26), with a total of 6,965 (59.86%) residents between the ages of 41 and 60. The mean of education is 2.23, indicating that most of the residents have a low level of school education, and only 2.01% of the residents have received university education. 178 (1.53%) residents were not yet married, and among the 11,457 residents who were married, 17.82% were in an abnormal state of marriage (widowed, divorced, and separated). The income of the interviewed families was greater than the expenditure, and the gap between household income and expenditure was large, but most of the families were debt free. About 4/5 of the surveyed households purchased public health insurance. 69.15% of the household housing structure is concrete, steel, bricks, and wood. 6,598 (56.71%) of the surveyed households lived in rural areas. From 2013 to 2018, 25.10% of the surveyed households were identified as poor households by the Chinese government. More than half (55.95%) of the respondents were male. Most (72.51%) respondents do not believe in religion. About 10% of respondents are dissatisfied with their current life. Air quality has been significantly improved, and 85.80% of the respondents are satisfied with the current air quality.

Descriptive statistics of the studied variables.

Econometric model

As “Health” is an ordered multi-category variable, valid estimates may not be obtained if OLS and bivariate Probit models are used. The ordered probit (O-probit) model can meet the requirements of the data structure ( 5 ), and Greene et al. ( 35 ) uses the ordered probit model to explore the question of health in Australia. Therefore, the main model in this paper is:

The H e a l t h i * is the latent variable for health; i = 1, 2, 3, 4, 5 denotes five self-evaluations of health; ω n is the intercept term, β n and φ n are regression coefficients; CEC is clean energy consumption. CV r is the control variables. μ k denotes the error term.

To examine the mediating and moderating effects of clean energy consumption and health, this paper refers to Wen et al. ( 36 ) approach and set up a mediating effects model as:

Where MV is the mediating variable, and ρ is the regression coefficient of the mediating variable. If β n ,β 1 ,β 2 and ρ are all significant, it means that MV has a mediating effect on CEC and H e a l t h i * .

Empirical analysis and discussion

Basic regression.

We consider that if there is a multi-collinearity issue among variables, it will lead to serious deviations in the regression results. Therefore, the multi-collinearity test was carried out in this study before the regression. The variance inflation factor (VIF) is a common indicator to measure multi-collinearity. The VIF of this paper is 5.63 <10, which means that there is no multi-collinearity issue between the variables selected in this paper ( 37 ).

The results from models (1) show that clean energy consumption is significantly and positively associated with health, indicating that the use of clean energy by households can improve the health of residents ( 38 ). The trend in the average marginal effect values in the results of model (2) shows that the use of clean energy can gradually improve the health of the residents.

Age is negatively correlated with health under the significance standard of 0.01. With the increase of age, the functions of human organs and the immune system decline, and they are prone to diseases ( 39 ). Furthermore, at the 0.01 level of significance, education is positively associated with health, as higher education is associated with higher returns on educational investment, better jobs, income levels, and a greater ability to prevent and treat disease ( 40 ). Likewise, this study also revealed a significant positive correlation between income and health. The greater the willingness and ability of residents to invest in health, the greater their willingness and ability ( 41 ). Expenditure is significantly and negatively correlated with health, as the more items and amounts a household spends, the less it must spend on savings and investments, the less it is able to invest in health and fight disease, and the more it is vulnerable to health risks ( 42 ). In addition, medical insurance is significantly and positively correlated with health, and medical insurance has the function of defusing and hedging health risk ( 43 ). Building structure is positively correlated with health, firstly because a safer housing structure indicates a higher level of household income and the ability to cope with disease crises ( 44 ), and secondly because households with a safe housing structure can withstand the risks to human health caused by climatic disasters and environmental degradation ( 45 ).

As shown in Table 3 , marriage is not related to health, which is different from the conclusions of some current studies ( 46 ). It is observed that the regression coefficient of marriage is 0.014 > 0, indicating that marriage will have a positive effect on health ( 47 ). Debt is not related to health, which is different from the conclusions of Clayton et al. ( 48 ) and Andelic and Feeney ( 49 ), which may be related to the sample data in this paper and the debt structure of Chinese residents.

The regression results of CEC and health.

Robust standard errors in parentheses

Robustness test

This paper uses three approaches for robustness tests, and the results of the robustness tests are reported in Table 4 . First, replace the O-probit model with an ordered logit (O-logit) model (Model 1). Second, the sample size was reduced: the life expectancy per capita in China was 77 years in 2018 ( 50 ). Because CHARLS primarily collected health data from people aged 45 and up, samples younger than 45 and older than 77 years were excluded and then regressed (Model 2). Third, the 2018 CHARLS sample set was replaced by the 2018 China Family Panel Studies (CFPS) and the 2018 Chinese General Social Survey (CGSS). CFPS is a nationwide, comprehensive social tracking survey designed to reflect social, economic, demographic, educational, and health changes in China by tracking and collecting data at the individual, household, and community levels ( 51 ). CGSS is the earliest national, comprehensive, and continuous academic survey project in China that systematically and comprehensively collects data at multiple levels of society, communities, households, and individuals ( 52 ). We extract data from CFPS and CGSS for the same metrics as in this paper; define and calculate “Health,” “CEC,” and control variables in the same way as in this paper; and use the same model (O-probit) to analyze the relationship between clean energy consumption and residents' health (Model 3 and 4).

The results of robustness test of CEC and health.

As it can be seen in Table 4 , clean energy consumption was significantly positively associated with health after robustness tests using three different approaches. The robustness test results support the findings of the basic regression, indicating that the analysis results in this paper are reliable, that is, the long-term use of clean energy in households can significantly improve the health of residents.

Endogenous discussion and treatment

We cannot add all the factors that affect residents' health as control variables to the model for regression, and there may be errors between residents' self-health evaluation and their real health status. This paper may have endogenous issues caused by “missing variables” and “self-selection bias,” resulting in errors in regression coefficients. In this paper, “respondent's residential district (District, 1 = rural, 2 = urban-rural combination, 3 = urban)” was selected as the instrumental variable (IV), and the Iv-O-probit models were used to deal with possible endogenous issues. IV must meet two basic requirements: first is correlation (IV are related to endogenous variables); and second is exclusivity (IV are not related to control variables, explained variables, and error terms). “District” meets the correlation requirements since households living in different districts have different energy consumption due to differences in energy resource endowments ( 53 , 54 ), thus “District” is related to “CEC.” Some literature believes that rural residents are healthier than urban residents, because of rural residents have a green lifestyle ( 55 ). Other studies have found that the health level of urban residents is higher than that of rural residents ( 56 ), which may be because cities have more convenient medical resources so as to get more health care. This means that there is no strict causal relationship between “District” and “Health” ( 57 ). Therefore, “District” conforms to exclusivity, and it is reasonable to use “District” as an IV in this paper.

The explained variable health in this paper is an ordered multi-category variable, and it is still technically difficult to directly use the IV in combination with O-probit. Therefore, in this paper, we refer to Roodman ( 58 ) and use a combination of instrumental variables approach and conditional mixed process (CMP) estimation to deal with the endogenous of the O-probit model. Table 5 reports the results of the Iv-O-probit model for the endogenous problem.

The results of endogenous treatment of CEC and health with CMP estimation method.

In Table 5 , the results of models (1) and (2) show that the IV (District) is significantly correlated with the explanatory variable “CEC” and not with the explanatory variable “Health,” which statistically meets the requirements of IV. The auxiliary estimation parameter atanhrho_12 is significantly different from 0 ( P = 0), indicating that there is a significant correlation between the two equations in the joint cubic equation model and that adopting the CMP estimation method is more effective than estimating them separately, also demonstrating that “CEC” is an endogenous variable. The results of model (3) indicate that “CEC” is significantly and positively associated with “Health” after instrumental variables approach with CMP estimation. Compared to the basic regression, the coefficient of 0.072 > 0.054 and the increased average marginal effect value at each cut-off point indicate that the positive health effects of clean energy consumption are underestimated in the base regression. The first stage F-statistic value of 242.4 is greater than the experiential value of 10, indicating that there is no weak instrumental variable problem.

Heterogeneity analysis

In China, women carry out more work within the home than men, and use energy more frequently than men. Twumasi et al. ( 5 ) found that the risks to women's health from using non-clean energy were more significant. The results of model (1) in Table 6 show that clean energy consumption is positively associated with men's and women's health at the 0.05 level of significance, and the regression coefficient (0.071 > 0.039) shows that household clean energy consumption has a stronger effect on improving women's health.

The results of heterogeneity analysis of CEC and health.

The economic status of the household is directly influenced by energy choices. According to the poverty theory of development economics, economically poor households are also more likely to be energy poverty and have a higher reliance on non-clean energy sources ( 33 ). The results of model (2) in Table 6 show that clean energy consumption is positively associated with health regardless of whether the household is in poverty or not, but the coefficient values show that clean energy consumption has a more obvious effect on improving the health of poor households.

Religious households regularly incur expenditure on religious activities, have less money to spend on clean energy, and are more likely to use non-clean energy. Simultaneously, some religious teachings may discourage residents from utilizing clean energy ( 59 ). The results of model (3) in Table 6 show that clean energy consumption is positively associated with the health of residents who are not religious and not associated with the health of residents who are religious.

Mechanism analysis: Mediating effect test

The use of clean energy in the home increases the life satisfaction (happiness) of residents ( 60 , 61 ). Residents with high life satisfaction are more concerned about health and less likely to suffer from mental illness. The results of models (1), (2), and (3) in Table 7 show that clean energy consumption increases resident happiness at a significance criterion of 0.01 and is thus significantly and positively associated with residents' health. The corresponding p- values of the Soble and Bootstrap tests are both <0.05, indicating that happiness plays a partial mediating role in clean energy consumption impact on health.

The results of mediating effect of CEC, happiness and AQ on health.

Household use of non-clean energy pollutes the air and reduces indoor air quality (AQ) ( 62 ). Harmful products of energy combustion enter the body through human respiration, causing harm to the health of residents. This paper uses residents' subjective evaluation of air quality as a proxy variable for air quality and conducts a mediating effects analysis. The results of models (1), (4), and (5) in Table 7 show that the long-term use of clean energy significantly enhances air quality and thus improves the health of the residents. The p -values for the corresponding Soble and Bootstrap tests were <0.05, indicating that air quality plays a partially mediating role in clean energy consumption and health.

Further research: Nexus between CEC and eight different common diseases

Chronic diseases have become a global health concern. Obesity, hypertension, hyperlipidemia, diabetes, cancer, lung disease, stroke, asthma, osteoporosis, and kidney disease are the main chronic diseases with increasing diagnosis and mortality rates in the world ( 3 ). Deaths from chronic diseases accounted for 88.5% of deaths in China in 2019, with 80.7% of deaths from cardiovascular diseases, cancer, and chronic respiratory diseases ( 50 ). Households that used non-clean energy sources were more likely to develop diseases such as cardiovascular disease and asthma ( 63 ). Therefore, this paper further discusses the impact of clean energy consumption on common chronic diseases.

It can be seen from Table 8 , the results of model (1) show that clean energy consumption significantly reduces the prevalence of hypertension; the results of model (2) illustrate that clean energy consumption is negatively associated with hyperlipidemia at the 0.01 level of significance; the results of model (5) indicate that the long-term use of clean energy significantly suppresses the prevalence of lung disease; and the results of model (7) demonstrate that clean energy use is significantly negatively associated with asthma. The result of models (3), (4), and (6) indicated that the use of clean energy was negatively associated with diabetes, cancer, and stroke, respectively.

The regression results of CEC and eight different common diseases.

In recent years, depression has become a serious health issue that has plagued society ( 64 ). Long-term use of non-clean energy can lead to psychological and mental illness ( 19 ). This paper refers to Zhang et al. ( 65 ) and select data from seven research questions and take the factor analysis method to measure the depression index as a proxy variable for depression. The seven questions including: (1) I had trouble keeping my mind on what I was doing; (2) I felt depressed; (3) I felt everything I did was an effort; (4) I felt hopeful about the future; (5) I felt fearful; (6) I was happy; (7) I felt lonely.” The answer to each question is “ 1 = rarely or none of the time, 2 = some or a little of the time, 3 = occasionally or a moderate amount of the time, 4 = most or all of the time.” In Table 8 , the results of model (8) show that the use of clean energy significantly reduces the probability of diagnosed depression among residents.

Conclusion and policy recommendations

Conclusions.

Recently, both developing and developed countries around the world have committed to using cleaner energy and addressing health issues. Based on health economics and energy economics theory, this paper first examines the impact mechanism of household energy consumption on residents' health. The data from the 2018 CHARLS is used as a sample in an econometric model to investigate whether and how clean energy consumption affects residents' health. This study discovered that long-term use of clean energy can significantly improve residents' health. Simultaneously, household clean energy consumption has a greater impact on the health of women, low-income households, and non-religious residents. Furthermore, the mechanism analysis revealed that subjective happiness and air quality play a partial role in mediating the impact of energy consumption on residents' health. Furthermore, long-term use of clean energy reduced the incidence of hypertension, hyperlipidemia, lung disease, asthma, and depression.

Using both theoretical and empirical analyses, this paper verifies the positive impact of clean energy consumption on health, similar to the findings of Twumasi et al. ( 5 ), Liao et al. ( 7 ), and Wang et al. ( 16 ), etc., The contributions of this paper include: (1) using health economics and energy economics theories to analyze the underlying mechanisms of clean energy consumption affecting health; (2) not only analyzing whether clean energy consumption affects residents' health but also discussing how it affects health using mediating effect models; (3) not only analyzing the impact of clean energy consumption on overall health but also studying the relationship between clean energy and common chronic diseases and depression. Meanwhile, there are some limitations to this paper, such as the sample data is from China and the conclusions drawn may only be applicable to China or developing countries (regions) and are not of global relevance. Therefore, this paper provides ideas for further research: (1) Health economics and energy economics theories can be used to lay the groundwork for research on the impact of energy use on health; and (2) scholars can select data from different countries/regions (e.g., China and the United States, Europe and Africa, South Asia, and Western Europe, etc.) for repeated validation and comparative analysis.

Policy recommendations

This study makes three policy recommendations in light of the conclusions.

First , the government first utilizes macro policies to modify the market pricing of clean energy and non-clean energy, reduce the household consumption expenses of clean energy, and boost the consumption demand for clean energy, thereby encouraging households to use clean energy for an extended period of time.

Second , the government provides financial incentives to households in urban areas to upgrade their fuel-energy infrastructure and to hasten the development of clean-burning stoves for those living in rural areas (especially poor households). Financial subsidies will be given to households implementing clean energy facilities to improve their clean energy consumption abilities.

Third , community and rural management organizations play the role of social education, publicize the effect of clean energy consumption, and increase residents' willingness to use clean energy. At the same time, community and rural management organizations should carry out health education activities to raise the health awareness of residents (especially female residents).

Data availability statement

Author contributions.

Material preparation, data collection, and analysis were performed by FL and YD. The first draft of the manuscript was written by FL, YD, WL, DZ, and AC. All authors commented on previous versions of the manuscript, contributed to the study conception and design, and read and approved the final manuscript.

This study was supported by the Youth Project of National Social Science Foundation of China (grant number 17CGL012) and the Key Project of Social Science Planning of Sichuan Province (grant number SC21A016).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors' thanks to the China Health and Retirement Longitudinal Study for providing us with raw data.

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Clean energy, economic development and healthy energy intensity: an empirical analysis based on China’s inter-provincial panel data

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• Published: 18 June 2022
• Volume 29 , pages 80366–80382, ( 2022 )

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• Hui Hou 1 &
• Siwei Yang   ORCID: orcid.org/0000-0001-5214-9331 1  

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The use of clean energy can promote the coordinated development of the economy and the ecological environment. However, few studies have paid attention to the changes in the health status of residents in the process of economic development and energy use. To fill this gap, this paper uses health energy intensity, which refers to the amount of energy consumed per unit of health status (composed of population mortality, maternal mortality, and perinatal mortality), to explore the impact of clean energy (expressed by the share of clean energy consumption in total energy consumption) on economic development and healthy energy intensity. By using the panel data of 30 provinces and cities in China from 2005 to 2019, this paper constructs a simultaneous equation model for empirical analysis from the perspective of the whole country and areas with different income levels. The results show that from the national perspective, in the early stage of clean energy development, the level of economic development and healthy energy intensity increased; however, with the further development of clean energy, the sample period shows that the level of economic development and the healthy energy intensity decreased. Heterogeneity analysis shows that in both high-income and moderate-income areas, clean energy has a U -shaped effect on economic development; but in low-income areas, clean energy has an inverted U -shaped effect on economic development. In high-income and low-income areas, clean energy has an inverted U -shaped effect on healthy energy intensity; but in moderate-income areas, clean energy has a U -shaped effect on healthy energy intensity. China’s clean energy market is still in its early stage, and the research conclusions of this paper provide a theoretical basis for the realization of China’s clean energy development.

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Here is a brief introduction to some indicators of these five aspects: product quality, such as the rate of superior products; service quality, such as the density of star-rated hotels; economic benefits, such as the rate of land output; social benefits, such as public transport vehicles per 10,000 people; in terms of ecological benefits, such as park green space per capita; in terms of economic performance, such as the real growth rate of GDP. For the detailed composition of the indicators, see (Nie C and Jian X 2020).

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Appendix 1. Calculation formula and steps of entropy weight method

The entropy weighting method is an objective weighting method, and its idea is to determine the index weight according to the information provided by the observed values of each index. The specific calculation methods are as follows:

Firstly, set the metrics. There are m provinces and cities, and n evaluation indicators together constitute the initial global evaluation matrix: \(X=\{{x}_{ij}{\}}_{\mathrm{mxn}}\) , where \({x}_{ij}\) represents the j index value of the i province and city.

Secondly, process the data. The entropy weight method requires that the original value of the index should be standardized before calculating the weight of the index. In order to avoid the interference of dimensions and positive and negative orientations between indicators, the method of extreme difference one is used to carry out dimensionless normalization processing on the original data. To eliminate the effects of negative numbers and zeros, data panning is performed at the same time. For negative indicators (smaller is better) use the formula:

\({y}_{ij}=\frac{{x}_{j\mathrm{ max}}-{x}_{ij}}{{x}_{j\mathrm{ max}}-{x}_{j\mathrm{ min}}}\) +0.0001 (The logarithmic operation will be performed later, and 0.0001 is added to ensure that the true number is not 0.) This formula makes the negative index positive and standardizes at the same time (in fractions, the denominator is fixed, but the smaller the numerator \({x}_{ij}\) , the larger the value of the whole fraction, which shows that the smaller \({x}_{ij}\) , the better).

Calculate the characteristic proportion or contribution degree of the i province and city under the j index.

The formula is: \({p}_{ij}=\frac{{y}_{ij}}{\sum_{i=1}^{m}{y}_{ij}}\) .

Calculate the entropy value. The formula is \({e}_{j}=-\frac{1}{\mathrm{ln}m}\sum_{i=1}^{m}{p}_{ij}\mathrm{ln}{p}_{ij}\) . In the formula, \({e}_{j}\) is the entropy value of the j index, 0 ≤  \({e}_{j}\) ≤1.

Calculate the coefficient of variance. The formula is \({g}_{j}=1-{e}_{j}\) . In the formula, \({g}_{j}\) is the difference coefficient, and the larger the value of \({g}_{j}\) , the more important the index is.

Determine weights. The formula is: \({w}_{j}=\frac{{g}_{j}}{\sum_{i=1}^{m}{g}_{j}}\) . In the formula, \({w}_{j}\) is the weight of the j indicator, 0 ≤  \({w}_{j}\) ≤1, \(\sum_{j=1}^{n}{w}_{j}=1\) .

Comprehensive index calculation. The formula is: \({s}_{i}=\sum_{j=1}^{n}{w}_{j}{y}_{ij}\) . So far, the comprehensive index value has been calculated.

Appendix 2. Multicollinearity test results

In doing the multicollinearity test, we will explore each of the three single equations separately. In the single equation of economic development, the core variable of the main research is clean energy, so we did the tests for lnurban, lntp, lnl, and lnclean; in the single equation of healthy energy intensity, the core variable of the main study is clean energy, so we did the tests for lntp, lnil, lnphe, and lnclean; in the single equation of clean energy, the core variable of the main research is economic development, so we did the tests for lntp, lnis, lnil, and lned. The test results are shown in the table below (Table 8 ).

As can be seen from the results of the above tests, all VIF values are less than 10. It can be considered that in the single equation of economic development, lnurban, lntp, lnl, and lnclean do not have serious multicollinearity; in the single equation of health energy intensity, lntp, lnil, lnphe, and lnclean do not have serious multicollinearity; in the single equation of clean energy, lntp, lnis, lnil, and lned do not have serious multicollinearity.

For each single equation, there is no serious multicollinearity between the core variable and the control variable, so the parameter estimates of the control variables will not affect the parameter estimates of the core variables. The paper wants to study these three core variables: clean energy, economic development, and healthy energy intensity. In simultaneous equation model, these three core variables are endogenous. For the endogeneity problem of the simultaneous equation model, many studies have used the 3SLS method to solve it. Therefore, the paper also uses the 3SLS method to solve the endogeneity problem between the core variables, and further empirical analysis is carried out on this basis.

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Hou, H., Yang, S. Clean energy, economic development and healthy energy intensity: an empirical analysis based on China’s inter-provincial panel data. Environ Sci Pollut Res 29 , 80366–80382 (2022). https://doi.org/10.1007/s11356-022-21322-7

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DOI : https://doi.org/10.1007/s11356-022-21322-7

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Challenges of a Clean Energy Transition and Implications for Energy Infrastructure Policy

Severin Borenstein and Ryan Kellogg

The United States faces the challenge of dramatically reducing carbon emissions while simultaneously ensuring the reliable supply of on-demand energy services that its residents have come to expect. Federal policy will be instrumental in driving investments in energy infrastructure that will be required to transition the U.S. energy supply to zero-emissions sources. This paper discusses the major barriers that policy will need to overcome in order to successfully execute this transition at a reasonable cost. A core problem is that wind and solar generation are intermittent. Provision of reliable zero-emission supply therefore requires combining wind and solar resources with investments in dispatchable zero-emission sources (such as nuclear, hydroelectric, geothermal, and fossil-fueled power plants with carbon capture and sequestration), long-distance transmission, demand flexibility, and storage technologies. But given uncertainties about technological progress, it is difficult to know which combination of investments will be most cost-effective. We argue that broad incentives – such as carbon pricing, clean energy standards, or clean energy subsidies – that do not discriminate across zero-emissions resources will be essential for directing capital toward cost-effective investments in clean energy infrastructure. We also argue, however, that such incentives on their own will be insufficient to meet the overall challenge. Policy must also address a suite of additional problems in energy markets that clean energy pricing incentives alone will not address. These problems include motivating global emissions reductions, overcoming regulatory barriers to long-distance transmission construction, addressing deficiencies in wholesale energy markets, reducing utilities’ inclusion of non-marginal costs in volumetric retail rates, eliminating inequities in the distribution of clean energy’s benefits and costs, and funding infrastructure decommissioning at the end of its useful life.

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Bringing rigour to energy innovation policy evaluation

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Clean energy innovation is pivotal for low-cost energy sector decarbonization. Substantial public research and development funding is spent on energy innovation. Generating more evidence on which support mechanisms most effectively drive clean energy innovations, and why, could improve their design moving forward. In this Perspective, we discuss five challenges that researchers often face when attempting to rigorously evaluate energy innovation policies and public subsidy programmes. We recommend solutions, such as developing new innovation outcome metrics that consider unique features of the energy sector and building databases that cover long time periods. We also suggest that researchers and funding agencies work together to implement randomized control trials or conduct quasi-experimental evaluation of existing programmes and policies wherever possible.

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Acknowledgements

We are grateful to D. Popp and J. Rhys for comments on an early version of this Perspective. The authors gratefully acknowledge the Oxford Martin Programme on Integrating Renewable Energy at the Oxford Martin School for financial support. N.F. also acknowledges funding through the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 743582.

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Pless, J., Hepburn, C. & Farrell, N. Bringing rigour to energy innovation policy evaluation. Nat Energy 5 , 284–290 (2020). https://doi.org/10.1038/s41560-020-0557-1

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The world now invests almost twice as much in clean energy as it does in fossil fuels…, global investment in clean energy and fossil fuels, 2015-2024, …but there are major imbalances in investment, and emerging market and developing economies (emde) outside china account for only around 15% of global clean energy spending, annual investment in clean energy by selected country and region, 2019 and 2024, investment in solar pv now surpasses all other generation technologies combined, global annual investment in solar pv and other generation technologies, 2021-2024, the integration of renewables and upgrades to existing infrastructure have sparked a recovery in spending on grids and storage, investment in power grids and storage by region 2017-2024, rising investments in clean energy push overall energy investment above usd 3 trillion for the first time.

Global energy investment is set to exceed USD 3 trillion for the first time in 2024, with USD 2 trillion going to clean energy technologies and infrastructure. Investment in clean energy has accelerated since 2020, and spending on renewable power, grids and storage is now higher than total spending on oil, gas, and coal.

As the era of cheap borrowing comes to an end, certain kinds of investment are being held back by higher financing costs. However, the impact on project economics has been partially offset by easing supply chain pressures and falling prices. Solar panel costs have decreased by 30% over the last two years, and prices for minerals and metals crucial for energy transitions have also sharply dropped, especially the metals required for batteries.

The annual World Energy Investment report has consistently warned of energy investment flow imbalances, particularly insufficient clean energy investments in EMDE outside China. There are tentative signs of a pick-up in these investments: in our assessment, clean energy investments are set to approach USD 320 billion in 2024, up by more 50% since 2020. This is similar to the growth seen in advanced economies (+50%), although trailing China (+75%). The gains primarily come from higher investments in renewable power, now representing half of all power sector investments in these economies. Progress in India, Brazil, parts of Southeast Asia and Africa reflects new policy initiatives, well-managed public tenders, and improved grid infrastructure. Africa’s clean energy investments in 2024, at over USD 40 billion, are nearly double those in 2020.

Yet much more needs to be done. In most cases, this growth comes from a very low base and many of the least-developed economies are being left behind (several face acute problems servicing high levels of debt). In 2024, the share of global clean energy investment in EMDE outside China is expected to remain around 15% of the total. Both in terms of volume and share, this is far below the amounts that are required to ensure full access to modern energy and to meet rising energy demand in a sustainable way.

Power sector investment in solar photovoltaic (PV) technology is projected to exceed USD 500 billion in 2024, surpassing all other generation sources combined. Though growth may moderate slightly in 2024 due to falling PV module prices, solar remains central to the power sector’s transformation. In 2023, each dollar invested in wind and solar PV yielded 2.5 times more energy output than a dollar spent on the same technologies a decade prior.

In 2015, the ratio of clean power to unabated fossil fuel power investments was roughly 2:1. In 2024, this ratio is set to reach 10:1. The rise in solar and wind deployment has driven wholesale prices down in some countries, occasionally below zero, particularly during peak periods of wind and solar generation. This lowers the potential for spot market earnings for producers and highlights the need for complementary investments in flexibility and storage capacity.

Investments in nuclear power are expected to pick up in 2024, with its share (9%) in clean power investments rising after two consecutive years of decline. Total investment in nuclear is projected to reach USD 80 billion in 2024, nearly double the 2018 level, which was the lowest point in a decade.

Grids have become a bottleneck for energy transitions, but investment is rising. After stagnating around USD 300 billion per year since 2015, spending is expected to hit USD 400 billion in 2024, driven by new policies and funding in Europe, the United States, China, and parts of Latin America. Advanced economies and China account for 80% of global grid spending. Investment in Latin America has almost doubled since 2021, notably in Colombia, Chile, and Brazil, where spending doubled in 2023 alone. However, investment remains worryingly low elsewhere.

Investments in battery storage are ramping up and are set to exceed USD 50 billion in 2024. But spending is highly concentrated. In 2023, for every dollar invested in battery storage in advanced economies and China, only one cent was invested in other EMDE.

Investment in energy efficiency and electrification in buildings and industry has been quite resilient, despite the economic headwinds. But most of the dynamism in the end-use sectors is coming from transport, where investment is set to reach new highs in 2024 (+8% compared to 2023), driven by strong electric vehicle (EV) sales.

The rise in clean energy spending is underpinned by emissions reduction goals, technological gains, energy security imperatives (particularly in the European Union), and an additional strategic element: major economies are deploying new industrial strategies to spur clean energy manufacturing and establish stronger market positions. Such policies can bring local benefits, although gaining a cost-competitive foothold in sectors with ample global capacity like solar PV can be challenging. Policy makers need to balance the costs and benefits of these programmes so that they increase the resilience of clean energy supply chains while maintaining gains from trade.

In the United States, investment in clean energy increases to an estimated more than USD 300 billion in 2024, 1.6 times the 2020 level and well ahead of the amount invested in fossil fuels. The European Union spends USD 370 billion on clean energy today, while China is set to spend almost USD 680 billion in 2024, supported by its large domestic market and rapid growth in the so-called “new three” industries: solar cells, lithium battery production and EV manufacturing.

Overall upstream oil and gas investment in 2024 is set to return to 2017 levels, but companies in the Middle East and Asia now account for a much larger share of the total

Change in upstream oil and gas investment by company type, 2017-2024, newly approved lng projects, led by the united states and qatar, bring a new wave of investment that could boost global lng export capacity by 50%, investment and cumulative capacity in lng liquefaction, 2015-2028, investment in fuel supply remains largely dominated by fossil fuels, although interest in low-emissions fuels is growing fast from a low base.

Upstream oil and gas investment is expected to increase by 7% in 2024 to reach USD 570 billion, following a 9% rise in 2023. This is being led by Middle East and Asian NOCs, which have increased their investments in oil and gas by over 50% since 2017, and which account for almost the entire rise in spending for 2023-2024.

Lower cost inflation means that the headline rise in spending results in an even larger rise in activity, by approximately 25% compared with 2022. Existing fields account for around 40% total oil and gas upstream investment, while another 33% goes to new fields and exploration. The remainder goes to tight oil and shale gas.

Most of the huge influx of cashflows to the oil and gas industry in 2022-2023 was either returned to shareholders, used to buy back shares or to pay down debt; these uses exceeded capital expenditure again in 2023. A surge in profits has also spurred a wave of mergers and acquisitions (M&A), especially among US shale companies, which represented 75% of M&A activity in 2023. Clean energy spending by oil and gas companies grew to around USD 30 billion in 2023 (of which just USD 1.5 billion was by NOCs), but this represents less than 4% of global capital investment on clean energy.

A significant wave of new investment is expected in LNG in the coming years as new liquefaction plants are built, primarily in the United States and Qatar. The concentration of projects looking to start operation in the second half of this decade could increase competition and raise costs for the limited number of specialised contractors in this area. For the moment, the prospect of ample gas supplies has not triggered a major reaction further down the value chain. The amount of new gas-fired power capacity being approved and coming online remains stable at around 50-60 GW per year.

Investment in coal has been rising steadily in recent years, and more than 50 GW of unabated coal-fired power generation was approved in 2023, the most since 2015, and almost all of this was in China.

Investment in low-emissions fuels is only 1.4% of the amount spent on fossil fuels (compared to about 0.5% a decade ago). There are some fast-growing areas. Investments in hydrogen electrolysers have risen to around USD 3 billion per year, although they remain constrained by uncertainty about demand and a lack of reliable offtakers. Investments in sustainable aviation fuels have reached USD 1 billion, while USD 800 million is going to direct air capture projects (a 140% increase from 2023). Some 20 commercial-scale carbon capture utilisation and storage (CCUS) projects in seven countries reached final investment decision (FID) in 2023; according to company announcements, another 110 capture facilities, transport and storage projects could do the same in 2024.

Energy investment decisions are primarily driven and financed by the private sector, but governments have essential direct and indirect roles in shaping capital flows

Sources of investment in the energy sector, average 2018-2023, sources of finance in the energy sector, average 2018-2023, households are emerging as important actors for consumer-facing clean energy investments, highlighting the importance of affordability and access to capital, change in energy investment volume by region and fuel category, 2016 versus 2023, market sentiment around sustainable finance is down from the high point in 2021, with lower levels of sustainable debt issuances and inflows into sustainable funds, sustainable debt issuances, 2020-2023, sustainable fund launches, 2020-2023, energy transitions are reshaping how energy investment decisions are made, and by whom.

This year’s World Energy Investment report contains new analysis on sources of investments and sources of finance, making a clear distinction between those making investment decisions (governments, often via state-owned enterprises (SOEs), private firms and households) and the institutions providing the capital (the public sector, commercial lenders, and development finance institutions) to finance these investments.

Overall, most investments in the energy sector are made by corporates, with firms accounting for the largest share of investments in both the fossil fuel and clean energy sectors. However, there are significant country-by-country variations: half of all energy investments in EMDE are made by governments or SOEs, compared with just 15% in advanced economies. Investments by state-owned enterprises come mainly from national oil companies, notably in the Middle East and Asia where they have risen substantially in recent years, and among some state-owned utilities. The financial sustainability, investment strategies and the ability for SOEs to attract private capital therefore become a central issue for secure and affordable transitions.

The share of total energy investments made or decided by private households (if not necessarily financed by them directly) has doubled from 9% in 2015 to 18% today, thanks to the combined growth in rooftop solar installations, investments in buildings efficiency and electric vehicle purchases. For the moment, these investments are mainly made by wealthier households – and well-designed policies are essential to making clean energy technologies more accessible to all . A comparison shows that households have contributed to more than 40% of the increase in investment in clean energy spending since 2016 – by far the largest share. It was particularly pronounced in advanced economies, where, because of strong policy support, households accounted for nearly 60% of the growth in energy investments.

Three quarters of global energy investments today are funded from private and commercial sources, and around 25% from public finance, and just 1% from national and international development finance institutions (DFIs).

Other financing options for energy transition have faced challenges and are focused on advanced economies. In 2023, sustainable debt issuances exceeded USD 1 trillion for the third consecutive year, but were still 25% below their 2021 peak, as rising coupon rates dampened issuers’ borrowing appetite. Market sentiment for sustainable finance is wavering, with flows to ESG funds decreasing in 2023, due to potential higher returns elsewhere and credibility concerns. Transition finance is emerging to mobilise capital for high-emitting sectors, but greater harmonisation and credible standards are required for these instruments to reach scale.

A secure and affordable transitioning away from fossil fuels requires a major rebalancing of investments

Investment change in 2023-2024, and additional average annual change in investment in the net zero scenario, 2023-2030, a doubling of investments to triple renewables capacity and a tripling of spending to double efficiency: a steep hill needs climbing to keep 1.5°c within reach, investments in renewables, grids and battery storage in the net zero emissions by 2050 scenario, historical versus 2030, investments in end-use sectors in the net zero emissions by 2050 scenario, historical versus 2030, meeting cop28 goals requires a doubling of clean energy investment by 2030 worldwide, and a quadrupling in emde outside china, investments in renewables, grids, batteries and end use in the net zero emissions by 2050 scenario, 2024 and 2030, mobilising additional, affordable financing is the key to a safer and more sustainable future, breakdown of dfi financing by instrument, currency, technology and region, average 2019-2022, much greater efforts are needed to get on track to meet energy & climate goals, including those agreed at cop28.

Today’s investment trends are not aligned with the levels necessary for the world to have a chance of limiting global warming to 1.5°C above pre-industrial levels and to achieve the interim goals agreed at COP28. The current momentum behind renewable power is impressive, and if the current spending trend continues, it would cover approximately two-thirds of the total investment needed to triple renewable capacity by 2030. But an extra USD 500 billion per year is required in the IEA’s Net Zero Emissions by 2050 Scenario (NZE Scenario) to fill the gap completely (including spending for grids and battery storage). This equates to a doubling of current annual spending on renewable power generation, grids, and storage in 2030, in order to triple renewable capacity.

The goal of doubling the pace of energy efficiency improvement requires an even greater additional effort. While investment in the electrification of transport is relatively strong and brings important efficiency gains, investment in other efficiency measures – notably building retrofits – is well below where it needs to be: efficiency investments in buildings fell in 2023 and are expected to decline further in 2024. A tripling in the current annual rate of spending on efficiency and electrification – to about USD 1.9 trillion in 2030 – is needed to double the rate of energy efficiency improvements.

Anticipated oil and gas investment in 2024 is broadly in line with the level of investment required in 2030 in the Stated Policies Scenario, a scenario which sees oil and natural gas demand levelling off before 2030. However, global spare oil production capacity is already close to 6 million barrels per day (excluding Iran and Russia) and there is a shift expected in the coming years towards a buyers’ market for LNG. Against this backdrop, the risk of over-investment would be strong if the world moves swiftly to meet the net zero pledges and climate goals in the Announced Pledges Scenario (APS) and the NZE Scenario.

The NZE Scenario sees a major rebalancing of investments in fuel supply, away from fossil fuels and towards low-emissions fuels, such as bioenergy and low-emissions hydrogen, as well as CCUS. Achieving net zero emissions globally by 2050 would mean annual investment in oil, gas, and coal falls by more than half, from just over USD 1 trillion in 2024 to below USD 450 billion per year in 2030, while spending on low-emissions fuels increases tenfold, to about USD 200 billion in 2030 from just under USD 20 billion today.

The required increase in clean energy investments in the NZE Scenario is particularly steep in many emerging and developing economies. The cost of capital remains one of the largest barriers to investment in clean energy projects and infrastructure in many EMDE, with financing costs at least twice as high as in advanced economies as well as China. Macroeconomic and country-specific factors are the major contributors to the high cost of capital for clean energy projects, but so, too, are risks specific to the energy sector. Alongside actions by national policy makers, enhanced support from DFIs can play a major role in lowering financing costs and bringing in much larger volumes of private capital.

Targeted concessional support is particularly important for the least-developed countries that will otherwise struggle to access adequate capital. Our analysis shows cumulative financing for energy projects by DFIs was USD 470 billion between 2013 and 2021, with China-based DFIs accounting for slightly over half of the total. There was a significant reduction in financing for fossil fuel projects over this period, largely because of reduced Chinese support. However, this was not accompanied by a surge in support for clean energy projects. DFI support was provided almost exclusively (more than 90%) as debt (not all concessional) with only about 3% reported as equity financing and about 6% as grants. This debt was provided in hard currency or in the currency of donors, with almost no local-currency financing being reported.

The lack of local-currency lending pushes up borrowing costs and in many cases is the primary reason behind the much higher cost of capital in EMDE compared to advanced economies. High hedging costs often make this financing unaffordable to many of the least-developed countries and raises questions of debt sustainability. More attention is needed from DFIs to focus interventions on project de-risking that can mobilise much higher multiples of private capital.

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