(Health)
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.
. | ||||||
---|---|---|---|---|---|---|
Health | 11,635 | 100.00% | 3.13 | 1.02 | 1 | 5 |
Health = 1 | 645 | 5.54% | ||||
Health = 2 | 2,155 | 18.52% | ||||
Health = 3 | 5,197 | 44.67% | ||||
Health = 4 | 2,319 | 19.93% | ||||
Health = 5 | 1,319 | 11.34% | ||||
CEC | 11,635 | 100.00% | 0.76 | 0.43 | 0 | 1 |
CEC = 1 | 7,872 | 67.66% | ||||
CEC = 0 | 3,763 | 32.34% | ||||
Age | 11,635 | 100.00% | 51.26 | 9.63 | 18 | 97 |
18 ≤ Age ≤ 40 | 934 | 8.03% | ||||
41 ≤ Age ≤ 60 | 6,965 | 59.86% | ||||
61 ≤ Age ≤ 97 | 3,736 | 32.11% | ||||
Education | 11,635 | 100.00% | 2.23 | 0.75 | 1 | 4 |
Education = 1 | 2,019 | 17.35% | ||||
Education = 2 | 5,178 | 44.50% | ||||
Education = 3 | 4,204 | 36.13% | ||||
Education = 4 | 234 | 2.01% | ||||
Marriage | 11,635 | 100.00% | 1.17 | 0.39 | 0 | 2 |
Marriage = 0 | 178 | 1.53% | ||||
Marriage = 1 | 9,384 | 80.65% | ||||
Marriage = 2 | 2,073 | 17.82% | ||||
Income | 11,635 | 100.00% | 9.14 | 2.38 | 0.00 | 17.48 |
Expenditure | 11,635 | 100.00% | 8.96 | 1.61 | 0.00 | 14.51 |
Debt | 11,635 | 100.00% | 1.28 | 3.45 | 0.00 | 15.43 |
Insurance | 11,635 | 100.00% | 0.79 | 0.41 | 0 | 1 |
Insurance = 1 | 9,132 | 78.49% | ||||
Insurance = 0 | 2,503 | 21.51% | ||||
BS | 11,635 | 100.00% | 5.63 | 0.8 | 1 | 6 |
BS = 1 | 206 | 1.77% | ||||
BS = 2 | 109 | 0.94% | ||||
BS = 3 | 167 | 1.44% | ||||
BS = 4 | 135 | 1.16% | ||||
BS = 5 | 2,972 | 25.54% | ||||
BS = 6 | 8,046 | 69.15% | ||||
District | 11,635 | 100.00% | 1.61 | 0.77 | 1 | 3 |
District = 1 | 6,598 | 56.71% | ||||
District = 2 | 2,964 | 25.47% | ||||
District = 3 | 2,073 | 17.82% | ||||
Gender | 11,635 | 100.00% | 0.56 | 0.5 | 0 | 1 |
Gender = 1 | 6,510 | 55.95% | ||||
Gender = 0 | 5,125 | 44.05% | ||||
Poverty | 11,635 | 100.00% | 0.25 | 0.43 | 0 | 1 |
Poverty = 1 | 2,920 | 25.10% | ||||
Poverty = 0 | 8,715 | 74.90% | ||||
Religious | 11,635 | 100.00% | 0.28 | 0.45 | 0 | 1 |
Religious = 1 | 3,198 | 27.49% | ||||
Religious = 0 | 8,437 | 72.51% | ||||
AQ | 11,635 | 100.00% | 3.29 | 0.83 | 1 | 5 |
AQ = 1 | 329 | 2.83% | ||||
AQ = 2 | 1,323 | 11.37% | ||||
AQ = 3 | 5,089 | 43.74% | ||||
AQ = 4 | 4,420 | 37.99% | ||||
AQ = 5 | 474 | 4.07% | ||||
Happiness | 11,635 | 100.00% | 3.36 | 0.80 | 1 | 5 |
Happiness = 1 | 327 | 2.81% | ||||
Happiness = 2 | 857 | 7.37% | ||||
Happiness = 3 | 5,258 | 45.19% | ||||
Happiness = 4 | 4,689 | 40.30% | ||||
Happiness = 5 | 504 | 4.33% |
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 * .
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.
CEC | 0.054 (0.025) | −0.006 (0.003) | −0.011 (0.005) | −0.002 (0.001) | 0.009 (0.004) | 0.010 (0.005) |
Age | −0.004 (0.001) | |||||
Education | 0.016 (0.004) | |||||
Marriage | 0.014 (0.027) | |||||
Income | 0.034 (0.004) | |||||
Expenditure | −0.014 (0.006) | |||||
Debt | 0.003 (0.002) | |||||
Insurance | 0.056 (0.027) | |||||
BS | 0.020 (0.010) | |||||
Observations | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 |
Robust standard errors in parentheses
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.
CEC | 0.090 (0.043) | 0.062 (0.030) | 0.072 (0.018) | 0.146 (0.019) |
CV | Control | Control | Control | Control |
Observations | 11,635 | 10,666 | 13,502 | 12,781 |
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.
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.
| ||||||||
---|---|---|---|---|---|---|---|---|
CEC | 0.054 (0.025) | 0.072 (0.033) | −0.005 (0.002) | −0.010 (0.004) | −0.002 (0.001) | 0.009 (0.004) | 0.019 (0.009) | |
District | 0.012 (0.010) | 0.096 (0.026) | ||||||
atanhrho_12(P) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
F statistics | 242.4 | |||||||
CV | Control | Control | Control | Control | Control | Control | Control | Control |
Observations | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 |
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.
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.
CEC | 0.039 (0.017) | 0.071 (0.034) | 0.137 (0.058) | 0.058 (0.025) | 0.015 (0.067) | 0.074 (0.025) |
CV | Control | Control | Control | Control | Control | Control |
Observations | 6,510 | 5,125 | 2,920 | 8,715 | 3,198 | 8,437 |
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.
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.
CEC | 0.054 (0.025) | 0.082 (0.024) | 0.075 (0.023) | 0.085 (0.023) | 0.075 (0.023) |
Happiness | 0.0274 (0.0123) | ||||
AQ | 0.030 (0.012) | ||||
Soble test ( ) | 0.046 < 0.05 | 0.036 < 0.05 | |||
Bootstrap (500) | Direct effect ( = 0.058 < 0.10) | Direct effect ( = 0.025 < 0.05) | |||
Indirect effect ( = 0.001 < 0.01) | Indirect effect ( = 0.001 < 0.01) | ||||
CV | Control | Control | Control | Control | Control |
Observations | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 |
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.
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.
CEC | −0.092 (0.028) | −0.038 (0.003) | −0.046 (0.040) | −0.072 (0.076) | −0.134 (0.032) | −0.052 (0.038) | −0.088 (0.030) | −0.025 (0.008) |
CV | Control | Control | Control | Control | Control | Control | Control | Control |
Constant | −0.292 (0.024) | −0.747 (0.026) | −1.638 (0.040) | −2.241 (0.065) | −1.014 (0.029) | −1.415 (0.035) | −1.524 (0.037) | 0.606 (0.007) |
Observations | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 | 11,635 |
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.
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.
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).
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).
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.
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.
The authors' thanks to the China Health and Retirement Longitudinal Study for providing us with raw data.
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.
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
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
No. . | Name of project . | Country . | Estimated cost . | Estimated capacity of green hydrogen harvesting . | References . |
---|---|---|---|---|---|
1 | NEOM | Saudi Arabia | $8.5 billion | 1.2 M tonnes per year | [ , ] |
2 | Asian Renewable Energy hub | Australia | – | 1.75 M tonnes per year | [ ] |
3 | Green Energy Oman | Oman | $10 billion | 3.75 M tonnes per year | [ ] |
4 | Reckaz | Kazakhstan | $40–50 billion | 3 M tons per year | [ ] |
5 | HyDeal Ambition | Spain | – | 3.6 M tonnes per year | [ ] |
6 | Western Green Energy Hub | Australia | $70 billion | 20 M tonnes per year | [ ] |
7 | Hy deal Ambition | West Europe | – | 3.6 M tonnes per year | [ ] |
8 | Sinopec | China | ¥2.6 billion | 3.5 M tonnes per year | [ ] |
9 | – | India | $4.29 billion | 5 M tonnes per year | [ ] |
No. . | Name of project . | Country . | Estimated cost . | Estimated capacity of green hydrogen harvesting . | References . |
---|---|---|---|---|---|
1 | NEOM | Saudi Arabia | $8.5 billion | 1.2 M tonnes per year | [ , ] |
2 | Asian Renewable Energy hub | Australia | – | 1.75 M tonnes per year | [ ] |
3 | Green Energy Oman | Oman | $10 billion | 3.75 M tonnes per year | [ ] |
4 | Reckaz | Kazakhstan | $40–50 billion | 3 M tons per year | [ ] |
5 | HyDeal Ambition | Spain | – | 3.6 M tonnes per year | [ ] |
6 | Western Green Energy Hub | Australia | $70 billion | 20 M tonnes per year | [ ] |
7 | Hy deal Ambition | West Europe | – | 3.6 M tonnes per year | [ ] |
8 | Sinopec | China | ¥2.6 billion | 3.5 M tonnes per year | [ ] |
9 | – | India | $4.29 billion | 5 M tonnes per year | [ ] |
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 ]
No. . | Region . | Estimated energy capacity, Exajoule (EJ) . | Percentage value . |
---|---|---|---|
1 | Sub-Saharan Africa | 2715 | 28.6 |
2 | Middle East and North Africa | 2023 | 21.3 |
3 | North America | 1314 | 13.8 |
4 | Oceania (Australia) | 1272 | 13.4 |
5 | South America | 1114 | 11.7 |
6 | Rest of Asia | 684 | 7.2 |
7 | Northeast Asia | 212 | 2.23 |
9 | Europe | 88 | 0.92 |
10 | Southeast Asia | 64 | 0.67 |
No. . | Region . | Estimated energy capacity, Exajoule (EJ) . | Percentage value . |
---|---|---|---|
1 | Sub-Saharan Africa | 2715 | 28.6 |
2 | Middle East and North Africa | 2023 | 21.3 |
3 | North America | 1314 | 13.8 |
4 | Oceania (Australia) | 1272 | 13.4 |
5 | South America | 1114 | 11.7 |
6 | Rest of Asia | 684 | 7.2 |
7 | Northeast Asia | 212 | 2.23 |
9 | Europe | 88 | 0.92 |
10 | Southeast Asia | 64 | 0.67 |
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.
Burton N , Padilla R , Rose A , et al. . Increasing the efficiency of hydrogen production from solar powered water electrolysis . Renew Sustain Energy Rev , 2021 , 135 : 110255 .
Google Scholar
Yue M , Lambert H , Pahon E , et al. . Hydrogen energy systems: a critical review of technologies, applications, trends and challenges . Renew Sustain Energy Rev , 2021 , 146 : 111180 .
IRENA . Hydrogen from Renewable Power Technology Outlook for the Energy Transition . Abu Dhabi, UAE : International Renewable Energy Agency , 2018 .
Google Preview
Gielen D , Gorini R , Wagner N , et al. . Global Energy Transformation: A Roadmap to 2050 . Abu Dhabi, UAE : International Renewable Energy Agency , 2019 .
IRENA . Geopolitics of the Energy Transformation: the Hydrogen Factor . Abu Dhabi, UAE : International Renewable Energy Agency , 2022 . https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2022/Jan/IRENA_Geopolitics_Hydrogen_2022.pdf (8 February 2024, date last accessed) .
Zun MT , McLellan BC. Cost projection of global green hydrogen production scenarios . Hydrogen , 2023 , 4 : 932 – 960 .
Iida S , Sakata K. Hydrogen technologies and developments in Japan . Clean Energy , 2019 , 3 : 105 – 113 .
Ejike C. The advancement of green hydrogen and prospects for the future: a brief overview . In: SPE Nigeria Annual International Conference and Exhibition, Lagos, Nigeria, 1–3 August 2022 . https://doi.org/10.2118/211901-MS
IRENA . Hydrogen: A Renewable Energy Perspective. Report prepared for the 2nd Hydrogen Energy Ministerial Meeting in Tokyo, Japan . Abu Dhabi, UAE : International Renewable Energy Agency , 2019 .
Muhammed NS , Gbadamosi AO , Epelle EI , et al. . Hydrogen production, transportation, utilization, and storage: recent advances towards sustainable energy . J Storage Mater , 2023 , 73 : 109207 .
Mahmood MA , Chaudhary TN , Farooq M , et al. . Sensitivity analysis of performance and thermal impacts of a single hydrogen fueled solid oxide fuel cell to optimize the operational and design parameters . Sustain Energy Technol Assess , 2023 , 57 : 103241 .
Chaudhary TN , Akbar A , Usman M , et al. . Parametric sensitivity analysis to investigate the effects of operating and design parameters on single direct methane steam reforming solid oxide fuel cell performance and thermal impacts generation . Energy Convers Manag X , 2023 , 18 : 100374 .
Li Y , Shi X , Phoumin H. A strategic roadmap for large-scale green hydrogen demonstration and commercialisation in China: a review and survey analysis . Int J Hydrog Energy , 2022 , 47 : 24592 – 24609 .
IEA . The Future of Hydrogen for G20 . Paris, France : International Energy Agency , 2019 . https://www.iea.org/reports/the-future-of-hydrogen ( 15 November 2023 , date last accessed).
IRENA . Green Hydrogen Cost Reduction: Scaling Up Electrolysers to Meet the 1.5°C Climate Goal . Abu Dhabi, UAE : International Renewable Energy Agency , 2020 .
Kothari R , Buddhi D , Sawhney RL. Sources and technology for hydrogen production: a review . Int J Glob Energy Issues , 2004 , 21 : 154 – 178 .
Kovač A , Paranos M , Marciuš D. Hydrogen in energy transition: a review . Int J Hydrog Energy , 2021 , 46 : 10016 – 10035 .
Anouti Y , Elborai S , Kombargi R , Hage R. The Dawn of Green Hydrogen: Maintaining the GCC’s Edge in a Decarbonized World . 2020 . https://www.strategyand.pwc.com/m1/en/reports/2020/the-dawn-of-green-hydrogen/the-dawn-of-green-hydrogen.pdf ( 25 September 2023 , date last accessed).
Khan MI , Al-Ghamdi SG. Hydrogen economy for sustainable development in GCC countries: a SWOT analysis considering current situation, challenges, and prospects . Int J Hydrog Energy , 2023 , 48 : 10315 – 10344 .
Noussan M , Raimondi PP , Scita R , et al. . The role of green and blue hydrogen in the energy transition: a technological and geopolitical perspective . Sustainability , 2020 , 13 : 298 .
Kumar SS , Lim H. An overview of water electrolysis technologies for green hydrogen production . Energy Rep , 2022 , 8 : 13793 – 13813 .
Catumba BD , Sales MB , Borges PT , et al. . Sustainability and challenges in hydrogen production: an advanced bibliometric analysis . Int J Hydrog Energy , 2023 , 48 : 7975 – 7992 .
Olabi A , Abdelkareem MA , Mahmoud MS , et al. . Green hydrogen: pathways, roadmap, and role in achieving sustainable development goals . Process Saf Environ Prot , 2023 , 177 : 664 – 687 .
Trinh V , Chung C. Renewable energy for SDG-7 and sustainable electrical production, integration, industrial application, and globalization . Clean Eng Technol , 2023 , 15 : 100657 .
IRENA . Green Hydrogen Supply: A Guide to Policy Making . Abu Dhabi, UAE : International Renewable Energy Agency , 2021 .
Abe JO , Popoola A , Ajenifuja E , et al. . Hydrogen energy, economy and storage: review and recommendation . Int J Hydrog Energy , 2019 , 44 : 15072 – 15086 .
IRENA . Global Hydrogen Trade to Meet the 1.5°C Climate Goal: Part I—Trade Outlook for 2050 and Way Forward . Abu Dhabi, UAE : International Renewable Energy Agency , 2022 .
IRENA . Global Hydrogen Trade to Meet the 1.5°C Climate Goal: Part II—Technology Review of Hydrogen Carriers . Abu Dhabi, UAE : International Renewable Energy Agency , 2022 .
Sadiq M , Alshehhi RJ , Urs RR , et al. . Techno-economic analysis of Green-H2@ Scale production . Renew Energy , 2023 , 219 : 119362 .
Balabel A , Alrehaili MS , Alharbi AO , et al. . Potential of solar hydrogen production by water electrolysis in the NEOM green city of Saudi Arabia . World J Adv Eng Eng Technol Sci , 2023 , 8 : 29 – 52 .
NLGHP . Nine of the Largest Green Hydrogen Projects 2022 . https://fuelcellsworks.com/news/nine-of-the-largest-green-hydrogen-projects-2022/ ( 1 November 2023 , date last accessed).
Sinopec . China’s Sinopec Targets of Green Hydrogen Capacity by 2025 . 2021 . https://www.world-energy.org/article/18010.html#:~:text=Company%20vice%20president%20Ling%20Yiqun%20told%20a%20hydrogen,dioxide%20emissions%20by%20more%20than%2010%20million%20tonnes ( 3 November 2023 , date last accessed).
Varadhan S. India plans to produce 5 mln tonnes of green hydrogen by 2030: India sets a target of 5 MMT annual green hydrogen production by 2030 | IBEF . https://www.ibef.org/news/india-sets-a-target-of-5-mmt-annual-green-hydrogen-production-by-2030 ( 2 November 2023 . date last accessed).
Zhang B , Zhang S-X , Yao R , et al. . Progress and prospects of hydrogen production: opportunities and challenges . J Electron Sci Technol , 2021 , 19 : 100080 .
Van de Krol R , Grätzel M. Photoelectrochemical Hydrogen Production . Vol. 90 . New York : Springer , 2012 .
Chiu Y-H , Lai T-H , Kuo M-Y , et al. . Photoelectrochemical cells for solar hydrogen production: challenges and opportunities . APL Mater , 2019 , 7 : 8 .
Melis A , Happe T. Hydrogen production: green algae as a source of energy . Plant Physiol , 2001 , 127 : 740 – 748 .
Timmins M , Thomas-Hall SR , Darling A , et al. . Phylogenetic and molecular analysis of hydrogen-producing green algae . J Exp Bot , 2009 , 60 : 1691 – 1702 .
Melis A. Green alga hydrogen production: progress, challenges and prospects . Int J Hydrog Energy , 2002 , 27 : 1217 – 1228 .
Badawi EY , Elkharsa RA , Abdelfattah EA. Value proposition of bio-hydrogen production from different biomass sources . Energy Nexus , 2023 , 10 : 100194 .
Saifuddin N , Priatharsini P. Developments in bio-hydrogen production from algae: a review . Res J Appl Sci Eng Technol , 2016 , 12 : 968 – 982 .
IRENA . A Renewable Energy Perspective: Report Prepared for the 2nd Hydrogen Energy Ministerial Meeting in Tokyo, Japan . Abu Dhabi, UAE : International Renewable Energy Agency , 2019 .
Mohammed-Ibrahim J , Moussab H. Recent advances on hydrogen production through seawater electrolysis . Mater Sci Energy Technol , 2020 , 3 : 780 – 807 .
Khan MA , Al-Attas T , Roy S , et al. . Seawater electrolysis for hydrogen production: a solution looking for a problem ? Energy Environ Sci , 2021 , 14 : 4831 – 4839 .
Squadrito G , Maggio G , Nicita A. The green hydrogen revolution . Renew Energy , 2023 , 216 : 119041 .
Zainal BS , Ker PJ , Mohamed H , et al. . Recent advancement and assessment of green hydrogen production technologies . Renew Sustain Energy Rev , 2024 , 189 : 113941 .
Zhou Y , Li R , Lv Z , et al. . Green hydrogen: a promising way to the carbon-free society . Chin J Chem Eng , 2022 , 43 : 2 – 13 .
Pathak PK , Yadav AK , Padmanaban S. Transition toward emission-free energy systems by 2050: potential role of hydrogen . Int J Hydrog Energy , 2023 , 48 : 9921 – 9927 .
Webb J , Longden T , Boulaire F , et al. . The application of green finance to the production of blue and green hydrogen: a comparative study . Renew Energy , 2023 , 219 : 119236 .
Month: | Total Views: |
---|---|
March 2024 | 1,102 |
April 2024 | 1,291 |
May 2024 | 1,609 |
June 2024 | 1,336 |
Citing articles via.
Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide
Sign In or Create an Account
This PDF is available to Subscribers Only
For full access to this pdf, sign in to an existing account, or purchase an annual subscription.
Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.
Nature Energy volume 5 , pages 284–290 ( 2020 ) Cite this article
2932 Accesses
29 Citations
80 Altmetric
Metrics details
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.
This is a preview of subscription content, access via your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
24,99 € / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
111,21 € per year
only 9,27 € per issue
Buy this article
Prices may be subject to local taxes which are calculated during checkout
Data availability.
Please see the Supplementary Information file for the data used to create Fig. 1 .
Cunliff, C. Omission Innovation 2.0: Diagnosing the Global Clean Energy Innovation System (Information Technology & Innovation Foundation, 2019); https://itif.org/publications/2019/09/23/omission-innovation-20-diagnosing-global-clean-energy-innovation-system
Innovation: Grants, Loans and Subsidies (What Works Centre for Local Economic Growth, 2015); http://www.whatworksgrowth.org/public/files/Policy_Reviews/15-10-20-Innovation-Grants-Loans-Subsidies-Report.pdf .
Gallagher, K. S., Anadón, L. D., Kempener, R. & Wilson, C. Trends in global energy technology innovation. Wiley Interdiscip. Rev. Clim. Change 2 , 373–396 (2011).
Google Scholar
Grubler, A., Wilson, C. & Nemet, G. F. Apples, oranges, and consistent comparisons of the temporal dynamics of energy transitions. Energy Res. Soc. Sci. 22 , 18–25 (2016).
Grubler, A. & Wilson, C. (eds) Energy Technology Innovation: Learning from Historical Successes and Failures (Cambridge Univ. Press, 2014).
Tracking Clean Energy Progress 2017 (International Energy Agency (IEA), 2017); https://www.iea.org/reports/tracking-clean-energy-progress-2017
Anadón, L. D., Gallagher, K. S. & Holdren, J. P. Rescue US energy innovation. Nat. Energy 2 , 760–763 (2017).
An Assessment of ARPA-E (The National Academies Press, 2017); https://doi.org/10.17226/24778
ARPA-E impacts: a sampling of project outcomes, volume II . (US Department of Energy, 2017); https://arpa-e.energy.gov/sites/default/files/documents/files/Volume%202_ARPA-E_ImpactSheetCompilation_FINAL.pdf .
Jaffe, A. B., Newell, R. G. & Stavins, R. N. A tale of two market failures: technology and environmental policy. Ecol. Econ. 54 , 164–174 (2005).
Dechezleprêtre, A., Martin, R. & Mohnen, M. Knowledge Spillovers From Clean and Dirty Technologies Working Paper 135 (Grantham Research Institute on Climate Change and the Environment, 2017).
Gaddy, B., Sivaram, V. & O’Sullivan, F. Venture Capital and Cleantech: The Wrong Model For Clean Energy Innovation Working Paper MITEI-WP-2016–06 (MIT Energy Initiative, 2016).
Sivaram, V. Unlocking clean energy. Issues in Science and Technology https://issues.org/unlocking-clean-energy/ (2017).
Nelson, R. R. The simple economics of basic scientific research. J. Polit. Econ. 67 , 297–306 (1959).
Arrow, K. J. The economic implications of learning by doing. Rev. Econ. Stud. 29 , 155–173 (1962).
Goulder, L. H. & Schneider, S. H. Induced technological change and the attractiveness of CO 2 abatement policies. Resour. Energy Econ. 21 , 211–52 (1999).
Heckman, J. H., Ichimura, H., Smith, J. & Todd, P. Characterizing selection bias using experimental data. Econometrica 66 , 1017–98 (1998).
MathSciNet MATH Google Scholar
Jaffe, A. Building programme evaluation into the design of public research-support programmes. Oxford Rev. Econ. Policy 18 , 22–34 (2002).
Duflo, E., Glennerster, R. & Kremer, M. Using Randomization in Development Economics Research: A Toolkit (National Bureau of Economic Research, 2016).
Athey, S. & Imbens, G. W. in Handbook of Economic Field Experiments (eds Banerjee, A. V. & Duflo, E.) Ch. 3 (ScienceDirect, 2017).
Lee, D. S. & Lemieux, T. Regression discontinuity designs in economics. J. Econ. Lit. 48 , 281–355 (2010).
Howell, S. Financing innovation: evidence from R&D grants. Am. Econ. Rev. 107 , 1136–1164 (2017).
Bronzini, R. & Iachini, E. Are incentives for R&D effective? Evidence from a regression discontinuity approach. Am. Econ. J. Econ. Policy 6 , 100–134 (2014).
Agrawal A., Rosell C. & Simcoe, T. S. Tax credits and small firm R&D spending. Am. Econ. J. Econ. Policy (in the press).
Bronzini, R. & Piselli, P. The impact of R&D subsidies on firm innovation. Res. Policy 45 , 442–457 (2016).
Dechezleprêtre A., Einiö E., Martin R., Nguyen K.-T. & Van Reenen J. Do Tax Incentives for Research Increase Firm Innovation? An RD Design For R&D CEP Discussion Paper No 1413 (Centre for Economic Performance, 2016).
Ganguli, I. Saving soviet science: the impact of grants when government R&D funding disappears. Am. Econ. J. Appl. Econ. 9 , 165–201 (2017).
Wallsten, S. The effects of government-industry R&D programs on private R&D: the case of the Small Business Innovation Research Program. Rand J. Econ. 21 , 82–100 (2000).
Bloom, N., Griffith, R. & van Reenen, J. Do R&D tax credits work? Evidence from a panel of countries 1979–1997. J. Public. Econ. 85 , 1–31 (2002).
Rao, N. Do tax credits stimulate R&D spending? The effect of the R&D tax credit in its first decade. J. Public. Econ. 140 , 1–12 (2016).
Lane, J. Assessing the impact of science funding. Science 324 , 1273–1275 (2009).
Bonvillian, W. B. & Weiss, C. Technological Innovation in Legacy Sectors (Oxford University Press, 2015).
Popp, D. Economic analysis of scientific publications and implications for energy research and development. Nat. Energy 1 , 16020 (2016).
Popp, D. The effect of new technology on energy consumption. Resour. Energy Econ. 23 , 215–239 (2001).
Popp, D. Induced innovation and energy prices. Am. Econ. Rev. 92 , 160–180 (2002).
Popp, D. They don’t invent them like they used to: an examination of energy patent citations over time. Econ. Innov. New Technol. 15 , 753–776 (2006).
Johnstone, N., Haščič, I. & Popp, D. Renewable energy policies and technological innovation: evidence based on patent counts. Environ. Resour. Econ. (Dordr) 45 , 133–155 (2010).
Verdolini, E. & Gaelotti, M. At home and abroad: an empirical analysis of innovation and diffusion in energy technologies. J. Environ. Econ. Manage. 61 , 119–134 (2011).
Einiö, E. R&D subsidies and company performance: evidence from geographic variation in government funding based on the ERDF population-density rule. Rev. Econ. Stat. 96 , 710–728 (2014).
Czarnitzki, D., Hanel, P. & Rosa, J. M. Evaluating the impact of R&D tax credits on innovation: a microeconometric study on Canadian firms. Res. Policy 40 , 217–229 (2011).
Colombo, M. G., Grilli, L. & Murtinu, S. R&D subsidies and the performance of high-tech start-ups. Economics Letters 112 , 97–99 (2011).
Acemoglu, D., Aghion, P., Bursztyn, L. & Hemous, D. The environment and directed technical change. American Economic Review 102 , 131–166 (2012).
Acemoglu, D., Akcigit, U., Hanley, D. & Kerr, W. Transition to clean technology. J. Polit. Econ. 124 , 52–104 (2016).
Kattel, R. & Mazzucato, M. Mission-oriented innovation policy and dynamic capabilities in the public sector. Ind. Corp. Change 27 , 787–801 (2018).
Aghion, P., Dechezlepretre, A., Hemous, D., Martin, R. & van Reenen, J. Carbon taxes, path dependency, and directed technical change: evidence from the auto industry. J. Polit. Econ. 124 , 1–51 (2016).
Goulder, L. H. & Parry, I. Instrument choice in environmental policy. Rev. Environ. Econ. Policy 2 , 152–74 (2008).
Fischer, C. & Newell, R. G. Environmental and technology policies for climate mitigation. J. Environ. Econ. Manage. 55 , 142–62 (2008).
MATH Google Scholar
Fischer, C., Preonas, L. & Newell, R. Environmental and technology policy options in the electricity sector: are we deploying too many? J. Assoc. Environ. Resour. Econ. 4 , 959–984 (2017).
Adam, D. Science funders gamble on grant lotteries. Nature 575 , 574–575 (2019).
IGL Trials Database (Innovation Growth Lab, 2019); https://www.innovationgrowthlab.org/igl-database
Afcha, S. Analyzing the interaction between R&D subsidies and firm’s innovation strategy. Journal of Technol. Manag. Innov. 7 , 57–70 (2012).
Antonioli, D., Marzucchi, A. & Montresor, S. Regional innovation policy and innovative behaviour: Looking for Additional Effects. Eur. Plan. Stud. 22 , 64–83 (2014).
Branstetter, L. & Sakakibara, M. Japanese research consortia: a microeconometric analysis of industrial policy. J. Ind. Econ. 46 , 207–233 (2003).
Coupé, T. Science is golden: academic R&D and university patents. J. Technol. Transf. 28 , 31–46 (2003).
Czarnitzki, D., Ebersberger, B. & Fier, A. The relationship between R&D collaboration, subsidies and R&D performance: empirical evidence from Finland and Germany. J. Appl. Econ. 22 , 1347–1366 (2007).
MathSciNet Google Scholar
Kaiser, U. & Kuh, J. Long-Run Effects of Public-Private Research Joint Ventures: the Case of The Danish Innovation Consortia Support Scheme IZA Discussion Paper 5986 (IZA Institute for Labor Economics, 2011).
Nishimura, J. & Okamuro, H. Subsidy and networking: the effects of direct and indirect support programs of the cluster policy. Res. Policy 40 , 714–727 (2011).
Teirlinck, P. & Spithoven, A. Fostering industry-science cooperation through public funding: differences between universities and public research centres. J. Technol. Transf. 37 , 676–695 (2013).
Lechevalier, S., Ikeda, Y. & Nishimura, J. The effect of participation in government consortia on the R&D productivity of firms: a case study of robot technology in Japan. Discussion Paper Series A 500 (2008).
Aguiar, L. & Gagnepain, P. European Cooperative R&D and Firm Performance: Evidence Based on Funding Differences in Key Actions CEPR Discussion Paper DP9426 (Paris School of Economics, 2013).
Aerts, K. & Schmidt, T. Two For the Price of One? On Additionality Effects Of R&D Subsidies: A Comparison Between Flanders And Germany ZEW Discussion Paper no. 06-063 (ZEW - Centre for European Economic Research Discussion, 2006).
Bayona-Sáez, C. & García-Marco, T. Assessing the effectiveness of the Eureka program. Res. Policy 39 , 1375–1386 (2010).
Benavente, J. M., Crespi, G. & Maffioli, A. Public Support to Firm-Level Innovation: An Evaluation of the FONTEC Program OVE Working Paper 05 07 (Office of Evaluation and Oversight, 2007).
Benavente, J. M., Crespi, G., Garone, L. F. & Maffioli, A. The impact of national research funds: a regression discontinuity approach to the chilean FONDECYT. Res. Policy 41 , 1467–1475 (2012).
Callejon, M. & Garcia-Quevedo, J. Public subsidies to business R&D: do they stimulate private expenditures? Environ. Plann. C Gov. Policy 23 , 279–293 (2005).
Cannone, G. & Ughetto, E. Funding innovation at regional level: an analysis of a public policy intervention in the Piedmont region. Reg. Stud. 48 , 270–283 (2012).
Economic Impact of International Research and Innovation Cooperation - Analysis of 25 years of Danish participation in EUREKA (Danish Agency for Science Technology and Innovation, 2011).
Duch, N., Montolio, D. & Mediavilla, M. Evaluating the impact of public subsidies on a firm’s performance: A two-stage quasi-experimental approach. Investigaciones Regionales 16 , 143–165 (2009).
Dumont, M. The Impact of Subsidies and Fiscal Incentives on Corporate R&D Expenditures in Belgium (2001–2009) Federal Planning Bureau Working Paper 1–13 (De Boeck Université, 2013).
Foreman-Peck, J. Effectiveness and Efficiency of SME Innovation Policy Cardiff Economics Working Papers E2012/4 (Cardiff Business School, 2012).
Fornahl, D., Broekel, T. & Boschma, R. What drives patent performance of German biotech firms? the impact of R&D subsidies, knowledge networks and their location. Reg. Sci. 90 , 395–419 (2011).
Gonzalez, X. & Pazo, C. Do public subsidies stimulate private R&D spending? Res. Policy 37 , 371–389 (2008).
Görg, H. & Strobl, E. The Effect of R&D Subsidies on Private R&D Globalisation, Productivity and Technology Research Paper 2005/38 (University of Nottingham, 2005).
Grilli, L. & Murtinu, S. Do public subsidies affect the performance of new technology-based firms? The importance of evaluation schemes and agency goals. Prometheus: Crit. Stud. Innovation 30 , 97–111 (2012).
Hewitt-Dundas, N. & Roper, S. Output Addtionality of Public Support for Innovation: Evidence for Irish Manufacturing Plants Working Paper No. 103 (Warwick Business School’s Small and Medium Sized Enterprise Centre, 2009).
Hujer, R. & Dubravko, R. Evaluating the Impacts of Subsidies on Innovation Activities in Germany ZEW Discussion Paper 05–43 (ZEW, 2005).
Kolympiris, C., Kalaitzandonakes, N. & Miller, D. Public funds and local biotechnology firm creation. Res. Policy 43 , 121–137 (2014). (2014).
Lach, S. Do R&D subsidies stimulate or displace private R&D? Evidence from Israel. J. Ind. Econ. 50 , 369–390 (2002).
Merito, M., Giannangeli, S. & Bonaccorsi, A. Do incentives to industrial R&D enhance research productivity and firm growth? Evidence from the Italian Case. L’industria 2 , 221–242 (2007).
Moretti, E. & Wilson, D. J. State incentives for innovation, star scientists and jobs: evidence from biotech. J. Urban Econ. 79 , 20–38 (2014).
Morris, M. & Herrmann, O. J. Beyond surveys: the research frontier moves to the use of administrative data to evaluate R&D Grants. Res. Eval. 22 , 298–306 (2013).
Sissoko, A. R&D Subsidies and Firm-Level Productivity: Evidence From France Institut de Recherches Economiques et Sociales Discussion Paper 2011–2 (IRES, 2013).
Wu, Y. NSF’s experimental program to stimulate competitive research (epscor): subsidizing academic research or state budgets? J. Policy Anal. Manage. 28 , 479–495 (2009).
Fantino, D. & Cannone, G. Evaluating the Efficacy of European Regional Funds for R&D Working Paper no. 902 (Bank of Italy, 2013).
Romero-Jordan, D., Delgrado-Rodriguez, M., Alvaerz-Ayuso, I. & de Lucas-Santos, S. Assessment of the Public Tools Used to Promote R&D Investment in Spanish SMEs. Small Bus. Econ. 43 , 959–976 (2014).
Broekel, T., Brachert, M., Duschl, M. & Brenner, T. Joint R&D subsidies, related variety, and regional innovation. Int. Regional Sci. Rev . https://doi.org/10.1177/0160017615589007 (2015).
Henningsen, M., Hægeland, T. & Møen, J. Estimating the additionality of R&D subsidies using proposal evaluation data to control for research intentions. J. Technol. Transfer 40 , 227–251 (2015).
Azoulay, P., Graff Zivin, J., Li, D. & Sampat, B. Public R&D investments and private-sector patenting: evidence from NIH funding rules. Rev. Econ. Stud. 86 , 117–152 (2019).
Le, T. & Jaffe, A. B. The impact of R&D subsidy on innovation: evidence from New Zealand firms. Econ. Innov. New Technol. 26 , 429–452 (2017).
Download references
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.
Authors and affiliations.
MIT Sloan School of Management, Cambridge, MA, USA
Jacquelyn Pless
Smith School of Enterprise and the Environment, University of Oxford, Oxford, UK
Jacquelyn Pless & Cameron Hepburn
Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, Oxford, UK
Cameron Hepburn
Grantham Research Institute, London School of Economics and Political Science, London, UK
Queen’s Management School, Queen’s University Belfast, Belfast, UK
Niall Farrell
Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
You can also search for this author in PubMed Google Scholar
All three authors contributed to the writing of this paper.
Correspondence to Jacquelyn Pless .
Competing interests.
C.H. is the director of Aurora Energy Research Limited, an energy analytics firm, Vivid Economics Limited, an economics consultancy firm, has several clients in the energy sector and has had academic funding from Shell.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Source data fig. 1.
Data points for all the papers in Fig. 1.
Reprints and permissions
Cite this article.
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
Download citation
Received : 11 June 2018
Accepted : 10 January 2020
Published : 17 February 2020
Issue Date : April 2020
DOI : https://doi.org/10.1038/s41560-020-0557-1
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative
Startups supported by arpa-e were more innovative than others but an investment gap may remain.
Nature Energy (2020)
Patenting and business outcomes for cleantech startups funded by the advanced research projects agency-energy, quick links.
Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.
New citation alert added.
This alert has been successfully added and will be sent to:
You will be notified whenever a record that you have chosen has been cited.
To manage your alert preferences, click on the button below.
Please log in to your account
Bibliometrics & citations, view options, recommendations, hydrogen energy as a key player in poland's energy policy 2040: a roadmap for system transformation.
Transformation of the energy system using hydrogen energy is one of the key challenges facing the world today. The problem primarily concerns the need to reduce greenhouse gas emissions, which is necessary to stop climate change. The current ...
The gas turbine and steam turbine combined cycle fueled with hydrogen have an overall high efficiency. The virtues of the supercritical steam turbine, the high temperature gas turbine and the low pressure steam turbine are fully expressed in this ...
The main objective of this study is to presents the overview ideas on the infrastructure planning of hydrogen energy in Malaysia as potential future use of hydrogen as an energy carrier in the transportation sector. Finally the results will give the ...
Published in.
Elsevier Science Ltd.
United Kingdom
Author tags.
Other metrics, bibliometrics, article metrics.
Login options.
Check if you have access through your login credentials or your institution to get full access on this article.
Share this publication link.
Copying failed.
Affiliations, export citations.
We are preparing your search results for download ...
We will inform you here when the file is ready.
Your file of search results citations is now ready.
Your search export query has expired. Please try again.
Support for renewable energy and evs has dropped since president joe biden was elected, a new survey finds..
By Justine Calma , a senior science reporter covering energy and the environment with more than a decade of experience. She is also the host of Hell or High Water: When Disaster Hits Home , a podcast from Vox Media and Audible Originals.
While the majority of Americans would like to see more clean energy from solar and wind farms — support for new renewable energy projects has started to wane, according to a recent Pew Research Center survey . It also found a drop in interest in electric vehicles following Biden administration policies to slash greenhouse gas emissions and Republican backlash.
The share of people who favor more solar power has dropped from 90 to 78 percent since 2020, the survey found. Support for wind power among survey participants similarly dropped more than 10 percentage points to 72 percent over the past four years. And just 29 percent of adults said they’d consider an EV as their next car purchase, compared to 38 percent last year.
A widening partisan divide on clean energy technologies seems to be driving those changes. The biggest drop in support has been among Republicans in recent years, even though there are differences between how older and younger generations of the GOP view climate change and renewable energy.
The Pew Research Center surveyed 8,638 adults in the US in May of this year. It tries to include participants representative of the US population when it comes to race, ethnicity, gender, education, political affiliation, and more.
The biggest drop in support has been among Republicans in recent years
Back in 2020, 84 percent of Republican survey participants said they’d like to see more solar farms, and 75 percent said they’d favor more wind farms in the US. That support has fallen to 64 and 56 percent, respectively, for solar and wind farms this year. More than 80 percent of Republicans surveyed, compared to 35 percent of Democrats, oppose the Environmental Protection Agency’s new standards for greenhouse gas emissions from tailpipes expected to make more than half of car sales EVs by 2032.
Those shifts in opinion coincide with the Biden administration’s push to incentivize new renewable energy projects since he was elected in 2020. President Biden signed the nation’s biggest investment in climate action and clean energy into law in 2022, the $369 billion Inflation Reduction Act (IRA) . Republican lawmakers, meanwhile, have tried to slow EV adoption by attempting to roll back tax credits for EVs and block the tailpipe pollution rule.
While many Republican lawmakers have lambasted the IRA investments in EVs and renewables, a lot of the funding it created for clean tech manufacturing is actually flowing into their districts. Of $206 billion in investments so far, $161 billion is slated for projects in Republican districts, according to a recent Bloomberg analysis . Most of that money supports EV and battery manufacturing. A separate analysis by CNN similarly found that nearly 78 percent of IRA investments go to congressional Republican districts.
We’ll have to wait and see if that infusion of cash happens to shift Republicans’ views on renewables. But the tides could also turn again with younger Republicans, who are far more optimistic about solar and wind energy than their older counterparts. Only 22 percent of Republicans aged 65 or older in the survey said that expanding renewable energy production should be a priority. In contrast, 67 percent of Republicans between the ages of 18 and 29 said renewable energy ought to be the priority over coal, oil, and gas production. In general, young adults are more likely to think climate change will cause more harm in the US in their lifetime, according to another Pew survey published in October.
This is big tech’s playbook for swallowing the ai industry, uber and lyft now required to pay massachusetts rideshare drivers $32 an hour, netflix is starting to phase out its cheapest ad-free plan, tap-to-pay could get more capable and more complicated.
Energy legislation amendment (clean energy future) bill 2024.
IMAGES
COMMENTS
Clean Energy, with the support of the China Energy Group, is pleased to announce the Clean Energy Best Paper Prize for 2022. ... Discover a more complete picture of how readers engage with research in Clean Energy through Altmetric data. Now available on article pages. Publication Ethics.
More energy efficiency means less pollution, and energy efficiency has increased by around 2% annually in the past few years. But meeting the target for 2030 — to double the rate of the 1990 ...
The transition to renewable energy has been recognized as a crucial step in addressing climate change and achieving greenhouse gas reduction targets, but it can also cause energy sprawl if not planned properly. Clean renewable energy communities (CREC) are emerging globally as an approach for decentralized energy systems and an alternative to traditional centralized energy systems.
The aim of the paper is to ascertain if renewable energy sources are sustainable and examine how a shift from fossil fuel-based energy sources to renewable energy sources would help reduce climate change and its impact. ... energy efficiency, clean energy technology and research and energy infrastructure investment will reduce the cost of ...
Research on clean energy production is essential and beneficial, and the scientific community has made significant advances in various aspects of this field. ... have higher reputations with more high-qualified peer-reviewed papers in clean energy production [62, 63]. Therefore, the research literature in these two editions of WoS can well ...
Seawater electrolysis shows promising potential toward sustainable energy generation, but large-scale in-situ demonstrations are still lacking. Here, authors report a floating platform integrating ...
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.
The energy transition must reduce emissions substantially, while ensuring that sufficient energy is available for economic growth. The analysis shows that the CO 2 emissions intensity of global economic activity needs to be reduced by 85% between 2015 and 2050, and CO 2 emissions need to decline by more than 70% compared to the Reference Case in 2050. . The result is an annual decline of ...
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 ...
Abstract. Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances — at the materials, devices and systems levels — for the efficient ...
This paper highlights solar energy applications and their role in sustainable development and considers renewable energy's overall employment potential. ... based on the information mentioned above, the advantages of solar energy technology are a renewable and clean energy source that is plentiful, cheaper costs, less maintenance and ...
Based on these facts nuclear power plant is a strategic choice to develop a clean energy. This paper is an outcome of the review - Nuclear power as foundation of a clean energy future. ... B. Lacarrièrec, O. Le Correc aIN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 ...
About the Journal. Clean Energy is an open access, peer-reviewed international journal and serves as an important medium to present the latest research developments and knowledge on topics related to clean energy.. Energy is crucial for prosperity and development as well as playing a key role in driving innovation. The transition of the world fuel energy mix from fossil fuels towards renewable ...
The primary objective for deploying renewable energy in India is to advance economic development, improve energy security, improve access to energy, and mitigate climate change. Sustainable development is possible by use of sustainable energy and by ensuring access to affordable, reliable, sustainable, and modern energy for citizens. Strong government support and the increasingly opportune ...
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.
Abstract The global prospects for the transition to green energy generation in Saratov oblast are discussed. The literature data on the current situation in the alternative energy sector (wind energy, solar energy, and bioenergy) in Saratov oblast have been studied and systematized. The data were obtained from the most relevant and cited publications in the world databases: Scopus, Google ...
The aim of this review paper is to understand and study further the current RE technologies such as solar energy, hydro energy, wind energy, bioenergy, geothermal energy, and hydrogen energy. ... Hydrogen energy is known as a non-toxic and clean energy carrier that contains high specific energy on mass basis. For instance, ...
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. ... 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 ...
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 ...
energy sources in the regional energy balance will reach 6% by 2035 and about 13% in 2050. We believe that the global prospects for green energy transitions in the Russian Federation, including Saratov oblast, consist in a partial transition to alternative energy (solar and wind energy) using bioenergy and highly efficient tech-
Nature Energy (2020) Clean energy innovation is pivotal for low-cost energy sector decarbonization. Substantial public research and development funding is spent on energy innovation. Generating ...
Highlights •This paper is oriented to the context of carbon-free port.•This paper studies a shore hydrogen deployment problem.•A mixed integer linear programming model is formulated.•A tailored bra... AbstractIn the context of carbon neutrality and peak carbon, research on emerging technologies for the clean, efficient, safe, and ...
A Pew Research Center poll of over 8,000 people in the US shows drops in support for more solar energy, and fewer people say they'll buy an EV as their next car. ... Clean energy has become an ...
In some developed countries, the positive employment effect of the green economy appears. In America, the clean energy policy on employment is significantly positive, and net job gains rose to about 660,000 jobs in 2010 (Barrett, James P, et al. 2002). The American Recovery and Reinvestment Act and American Clean Energy and Security Act show ...
Energy Legislation Amendment (Clean Energy Future) Bill 2024. Type: Government: Status: Assented on Mon 24 Jun 2024 - Act No 41 of 2024: Bill Remarks: Bill declared urgent 18/06/2024: Origin: ... Research Papers. About Parliament. Watch 'The People's Parliament' video; How Parliament Works; History of democracy; The Departments;
The aim of this paper is that of contributing to existing literature on the relationship between environmental innovation and productivity. Generally, environmental innovation (clean) has a lower return than non-environmental one (dirty) in the short run, because of higher compliance costs for regulations.However, the positive effects of policy-induced clean innovations on productivity will be ...
The biodiversity structure and habitat requirements of longhorn beetles (Cerambycidae) in floodplain forests of the western part of Saratov oblast were studied from 2011 to 2014. A total of 51 species of longhorn beetles has been identified. The largest subfamilies are Cerambycinae (19 species), Lepturinae (17 species), and Lamiinae (13 species). The specific communities include 34, 14, 11, 9 ...