Adoption Of Clean Energy Research Articles

Flexible rechargeable photo-assisted zinc-air batteries based on photo-active pTTh bifunctional oxygen electrocatalyst

Photo-assisted zinc-air batteries have gained attention for incorporating solar energy, reducing reliance on non-renewable sources, and promoting clean energy adoption. However, currently, the efficiency of the photo-assisted cathode for oxygen reduction/evolution reactions (ORR/OER) remains low, and its application is limited to aqueous zinc-air batteries. Therefore, it is highly necessary to develop bifunctional cathodes with high photo-assisted ORR/OER efficiency and to expand the application of aqueous zinc-air batteries to flexible zinc-air batteries, providing efficient, flexible, and portable power solutions. In this study, we employed pTTh as a bifunctional catalyst in rechargeable zinc-air batteries (RZABs) and utilized solar energy to address the issues of high polarization and low round-trip efficiencies. For photo-assisted pTTh cathode, the Eonset is 0.910 V vs. RHE, E1/2 is 0.831 V vs. RHE, and E10 is 1.99 V vs. RHE. The power density of pTTh cathode-based ZABs is enhanced 56.25 % under illumination. Furthermore, we have pioneered the application of photo-assisted strategy in flexible zinc-air batteries. This photo-assisted pTTh cathode based flexible zinc-air batteries showing the discharge potential of ca. 1.2 V, and the charge potential of ca. 1.8 V at 0.1 mA cm−2 under illumination. Further, under illumination a single photo-assisted flexible zinc-air battery can light up a diode and propel a toy car, and four photo-assisted rechargeable flexible Zn-air pouch batteries (FZAPBs) in series can charge a smartphone.

Labor mobility and clean energy use: Evidence from rural households in China

One of the critical challenges facing China is environmental pollution caused by insufficient use of clean energy. This paper empirically investigates the impact of rural labor mobility on household clean energy use using data from the China Family Panel Studies (CFPS). The results indicate that labor mobility significantly promotes the adoption of clean energy by rural households, with income effects and information channel effects serving as the underlying mechanisms. The study also finds that health risks, as an important consideration for household energy use choices, enhance this positive effect. Furthermore, heterogeneity analysis reveals that labor mobility has a greater impact on households with lower levels of education, lack of social security, and those located in central and western regions. Therefore, the government should take measures to increase the income of the rural migrant population and continuously widen the information channels for rural households to promote clean energy use. The findings of this study provide a new perspective and evidence for understanding household energy use behavior in China, offering valuable insights for policymakers aiming to expand the use of clean energy.

The Impact of Family Life Cycle on Farmers’ Living Clean Energy Adoption Behavior—Based on 1382 Farmer Survey Data in Jiangxi Province

Encouraging farmers to adopt greener and cleaner energy is crucial for reducing energy pollution and achieving carbon neutrality goals. In rural China, the decision making of farmers is often closely related to the whole family. At different stages of the family life cycle, the family has different characteristics, which leads to heterogeneity in the focus and final decision of farmers in adopting living clean energy. Therefore, this paper studies the farmers’ living clean energy adoption behavior from the perspective of the family life cycle. It is helpful to identify the different policy needs and the evolution of farmers in different stages in order to provide a reference and inspiration for encouraging the adoption of living clean energy by farmers and for promoting the development of clean energy in rural areas. Based on the survey data of 1382 farmers in Jiangxi Province, this paper uses a multiple linear regression model to explore the impact of the family life cycle on farmers’ clean energy adoption behavior. The results show the following: (1) The family life cycle has a significant impact on farmers’ living clean energy adoption behavior, which is reflected in four aspects: energy demand, livelihood strategy, health demand and support burden; (2) Awareness of environmental ecology and frequency of government promotion have significant positive effects on farmers’ living clean energy adoption behavior, while gender has significant negative effects on farmers’ clean energy adoption behavior; (3) There are also differences in the influencing factors of farmers’ living clean energy adoption behavior at different stages of the family life cycle. Therefore, when promoting clean energy in rural areas, a precise clean energy incentive mechanism should be adopted to treat families in different family life cycle stages differently.

Sustainable Integration of Solar Energy, Behavior Change, and Recycling Practices in Educational Institutions: A Holistic Framework for Environmental Conservation and Quality Education

Environmental sustainability in educational institutions is a critical concern for addressing global challenges. This research presents a comprehensive framework for sustainable energy conservation, behavior change, and recycling practices in schools, with the aim of fostering environmental consciousness among students and enhancing overall educational quality. The framework integrates solar photovoltaic (PV) systems, encouraging students’ participation in their maintenance while repurposing collected water for plant irrigation and using organic waste as a natural fertilizer. By creating a micro-ecosystem within schools, the approach cultivates a generation of environmentally aware individuals who actively contribute to environmental stewardship. The framework aligns with Saudi Arabia’s 2030 vision of improving quality of life and increasing green surfaces. It promotes environmental awareness, facilitates clean energy adoption, and reduces operational costs. The role of municipalities and recycling bodies is crucial for its successful execution, involving waste management support, educational programs, and regulatory compliance. Through collaboration between schools, municipalities, and recycling bodies, the framework aims to create a culture of sustainability. It envisions students as advocates, gaining experiential knowledge in renewable energy technologies and waste management. This research offers a roadmap for schools to integrate solar energy, behavior change, and recycling practices, positioning them as leaders in environmental stewardship. The framework underscores the importance of collaborative efforts, financial support, and awareness campaigns. By embracing this comprehensive approach, schools can play a pivotal role in mitigating climate change, promoting sustainable living, and inspiring a brighter future for generations to come.

The relationship between dynamic monitoring network plans and eco-efficiency – New evidence from atmospheric quality monitoring policy in China

China’s rapid economic development in recent decades has come at a considerable environmental cost. This paper explores whether atmospheric quality monitoring policy (AQMP) improves eco-efficiency by using AQMP as a natural experimental group. We assessed the eco-efficiency of 285 cities in China from 2009 to 2019 using the super-efficient SBM model and estimated the impact of AQMP using the propensity score method Difference-in-Difference (PSM-DID) model. The key findings of this paper are as follows: First, AQMP can enhance eco-efficiency, promoting sustainable urban development. Second, governmental and non-governmental organizations play contrasting roles in either fostering or reversing the positive effects of AQMP. Factors like innovation, clean energy adoption, and industrial structure have a positive mediating influence. Finally, the impact of AQMP on eco-efficiency varies across cities, displaying heterogeneity. Specifically, AQMP has a positive effect on eco-efficiency in resource-rich cities, small and medium-sized urban centers, smart cities, and coastal areas. These findings carry significant implications for the establishment of dynamic monitoring networks and the advancement of eco-efficiency in emerging countries, including China.

The deviation between the behavior and willingness of rural residents to use clean energy and its influencing factors in China

Rural residents who really accept and adopt clean energy make significant sense for long-term sustainability. The purpose of this study was to resolve the limitations of existing studies that only discuss whether there is a deviation between behavior and willingness, and deeply measures the deviation level between behavior and willingness to use clean energy for heating, cooking, and producing hot water, and to identify the factors influencing contrasting levels of deviation for different energy-consumption activities. A survey of 854 rural residents from 62 villages was conducted in the Loess Plateau region of China, and the multinomial logit model was used to investigate the influencing factors. The results showed that the proportion of high-level deviation for heating and low-level deviation for cooking was the highest. Policy cognition and usefulness perception had significant negative impacts on the deviation for heating, cooking, and producing hot water. Herd mentality had a significant positive impact on low-level deviation in hot water production. Males were more likely to have a high-level deviation for cooking. The results of this study provide a basis for scientific policy formulation and guide the transition from the willingness to the actual clean energy adoption behavior of rural residents.

The impact of household fuel usage on adverse pregnancy outcomes in rural Ma'anshan City, Anhui Province: a birth cohort study.

The combustion of cooking fuels generates detrimental gases significantly impacting human health, particularly for vulnerable populations like expectant mothers. Prenatal exposure of such hazardous emissions raises the probability of adverse pregnancy outcomes, including preterm birth (PTB) and low birth weight (LBW). Our research aims to explore the association between cooking fuel utilization and adverse birth outcomes in rural Ma'anshan, Anhui Province. A prospective cohort study was executed, employing the Maternal and Infant Health Assessment questionnaire to classify fuels into clean (natural gas, electricity) and polluting energy sources (coal, coal gas, firewood). Multivariate logistic regression models were conducted to evaluate the association between fuel consumption and postpartum maternal and infant outcomes. Among the 442 surveyed pregnant women, 38.2% (N=169) utilized polluting fuels. After adjusting for covariates such as age and BMI, the relative risks of preterm birth, low birth weight, and postpartum hemorrhage in the polluting fuel group compared to the clean fuel group were OR: 3.27, 95% CI: 1.34, 8.00; OR: 3.50, 95% CI: 1.12, 10.90; and OR: 3.18, 95% CI: 1.06, 9.46, respectively. These results indicate that the usage of polluting fuels during pregnancy may heighten the risk of adverse birth outcomes. Consequently, additional research is advised to mitigate the harmful emissions generated by cooking fuels and advocate for clean energy adoption, enhancing maternal and infant well-being.

Present and future emission characteristics of air pollutants and CO2 from the Beijing transport sector and their synergistic emission reduction benefits

Coordinated control of both carbon dioxide (CO2) and air pollutants from the urban transport sector will deliver the greatest benefit to climate and health. To calculate and assess the synergistic control effect on CO2 and air pollutants from various transport types in Beijing from 2021 to 2050, we built a quantitative analysis model based on the Long-range Energy Alternatives Planning framework. Results showed that passenger transport was the dominant contributor to CO2 and major air pollutants (fine particles, carbon monoxide, volatile organic compounds) emitted from the transport sector in 2021 in Beijing. An exception is for nitric oxide which was mostly from freight transport. Clean energy alternatives for road vehicles and aviation, and electrification of railways offer the best synergistic emission reduction potential for both CO2 and air pollutants, and are also the most important measure to realize carbon neutrality in transportation. A change in transport mode (e.g. from road to rail) and the early elimination of aging vehicles would lead to a greater synergistic effect than that achieved by improving fuel economy in the short-term, except for co-benefits for fine particles and CO2 for which the fine particle emission reduction was much lower than that of CO2. In general, the adoption of clean energy for motor vehicles and aviation (e.g., electric vehicles, hydrogen fuel cell vehicles, and bio-fuels), is the best way for Beijing to quickly pass the carbon peak and achieve neutrality in the transport sector and improve air quality in the future.

Solving barrier ranking in clean energy adoption: An MCDM approach with q-rung orthopair fuzzy preferences

With a growing focus from the United Nations to eradicate the ill effects of climate change, countries around the world are transforming to green and sustainable habits/practices. Adoption of clean energy for demand satisfaction is a prime focus of many countries as it reduces carbon trace and promotes global development. In developing countries like India, there is an urge for sustainable global development. Literature shows that direct and complete adoption of clean energy incurs some barriers, which impede the sustainable development of the nation. Grading such barriers supports policymakers to effectively plan strategies, which motivates authors to put forward a novel decision model with integrated approaches. First, qualitative rating data on barriers and circular economy (CE) factors are collected from experts via questionnaires, which are transformed into q-rung orthopair fuzzy information (qRFI). Second, the weights of experts and CE factors are determined by the proposed variance measure and CRITIC. Third, barriers are graded by the proposed ranking algorithm that considers modified WAPAS formulation. Finally, these approaches are integrated into a model that is testified for practicality by using a case example from India. Sensitivity and comparative analyses are performed to realize the merits and limitations of the model for extant works.

RENEWABLE ENERGY SOURCES - BENEFITS AND DRAWBACKS FROM THE PERSPECTIVE OF THE EXPERIENCES OF CHINA, BRAZIL, CANADA AND THE UNITED STATES

The aim of the article was to identify actions, based on the experiences of China, Brazil, Canada, and the United States, that countries can implement to increase the share of hydro, solar, and wind energy in their economies. The analysis relied on a literature review and data obtained from the Our World In Data database. The findings indicate that there are effective strategies for clean energy adoption that can be applied worldwide. Key considerations include investing in appropriate infrastructure, developing new energy storage technologies, and implementing environmentally friendly methods for disposing of photovoltaic panels. It is essential to provide financial support for scientific research, particularly in assessing the long-term potential of renewable energy, considering geographic distribution, and evaluating public acceptance. Regulatory frameworks should strike a balance between promoting renewable energy expansion and avoiding excessive growth.

Shaping a sustainable future: The impact of board gender diversity on clean energy use and the moderating role of environmental, social and governance controversies

AbstractThis study investigates how gender‐diverse boards are related to the adoption of clean energy and examines whether environmental, social, and governance (ESG) controversies have an impact on this link. The study analyzes 2395 firm‐year observations from 13 European countries from 2006 to 2021. Drawing on the gender socialization theory and diversity theory, the research reveals a favorable effect of board gender diversity on a company's utilization of clean energy. It also demonstrates that ESG controversies play a significant role in moderating this relationship. Furthermore, the study affirms the critical mass theory by indicating that companies with at least three female board members exhibit a greater use of clean energy. The findings are robust to various methods, such as controlling for endogeneity problems, propensity score matching, sub‐sample analysis, and alternative econometric models. This study's implications are important for stakeholders, policymakers, and managers. It suggests that having a gender‐diverse board can increase the adoption of clean energy, benefiting a company's reputation and attractiveness to stakeholders. Policymakers can use these findings to design policies that encourage gender diversity on boards and achieve environmental goals, while managers can make informed decisions about board composition and clean energy adoption.

Household fuel choices and consumption intensity in Pakistan: evidence from HIES data 2001-2019.

The adoption of clean energy (electricity and gas) for domestic purposes has increased over the decades, yet the share of clean energy in total energy consumption remains low. Therefore, this study analyses seven rounds of HIES surveys in Pakistan collected between 2001 to 2019 to understand the energy use patterns and why clean fuel consumption is low among households that have already adopted clean energy. To this end, the present study applied the Probit and Tobit models to examine the determinants of using different fuel types and their consumption intensity. The results show that female-headed households are more likely to adopt and consume more clean fuels such as electricity and gas. Moreover, education, wealth, and urban location have a positive association with clean fuel adoption and consumption. The study also finds that age and household size have a non-linear impact on clean fuel consumption intensity. The study recommends policies to achieve SDG 7 by improving accessibility and affordability by increasing income and the supply of clean fuel. Further, it emphasizes enhancing the knowledge about the benefit of using clean energy through education programs.

Energy structure transformation in the context of carbon neutralization: Evolutionary game analysis based on inclusive development of coal and clean energy

Efficient utilization of the clean coal and adoption of clean energy are key points to promote energy structure transformation in the context of carbon neutrality. Considering the influence of decision makers' subjective preferences on energy structure transformation, we introduce prospect theory and psychological account theory into the evolutionary game analysis, construct an evolutionary game model with the participation of government regulators and energy consumers, and analyze the dynamic evolution of each game subject. The results of the study show that the share of coal and clean energy in energy consumption significantly affects the strategy choice of energy consumers and government regulators. The impact of the intensity of subsidies on coal and clean energy and the resulting positive externalities on the inclusive development of coal and clean energy is nonlinear. More interestingly, the strategy combination of green regulation by government regulators and integrated energy use by energy consumers is not optimal in practice due to subjective factors such as reference effects, risk preferences, and loss aversion. This study provides a new perspective on the energy mix transition based on the current situation in China.

A regional appraisal of electricity accessibility determinants: the relevance of international remittances, clean energy, income inequality, and institutional quality.

The majority of developing nations worldwide face severechallenges in ensuring universal electricity access for their respective populations. Hence, this study focuses on assessing the factors stimulating and inhibiting national electricity accessrates in 61 developing nations from six global regions during the 2000-2020 period. For analytical purposes, both parametric and non-parametric estimation techniques that are efficient in handling major panel data-related problems are used. Overall, the results reveal that a higher influx of remittances sent by the expatriates does not directlyinfluence electricity accessibility. However, adoption of clean energy and improvement in institutional quality promote electricity accessibility while higher income inequality undermines it. More importantly, good institutional quality mediates between international remittance receipts and electricity accessibility as results endorse that international remittance receipts and institutional quality improvement jointly exert electricity accessibility-promoting impacts. Moreover, these findings depict regional heterogeneity while the quantile-based analysis highlights contrasting impacts of international remittance receipts, clean energy use, and institutional quality across different quantiles of electricity accessibility. Contrarily, worsening incidences of income inequality are evidenced to undermine electricity accessibility across all quantiles. Therefore, considering these key findings, several electricity accessibility-boosting policies are suggested.

Use of Clean Energy Product - A Path Towards Attainment of Quality of Life

Improving the economy and safeguarding sustainability are major challenges of the present day. Clean energy offers the solution to both. Adoption of clean energy is important for human development, economic progress of the region, societal growth and improved quality of life. Adoption of clean energy has no negative externalities. Sun, wind, hydro, tidal, etc. are some of the examples of clean energy sources. This paper consists of two sections. First section focuses on design and development of a hybrid type of solar dryer by using a solar flat plate collector and the second section emphasises on a case related to adoption of solar operated lights in rural areas of Odisha followed by status of adoption of solar operated lights both in rural and urban context in the state of Odisha, Eastern India.

Implications of Non-Farm Work for Clean Energy Adoption: Evidence from Rural China

Due to China’s socioeconomic development, labor force transfer from rural areas has become more common, the income of rural households has increased, and the structure of rural household clean living energy consumption has changed. However, few studies have explored the correlation between non-farm employment and clean energy adoption in rural households. Using survey data from 1175 farmers in 106 villages from a 2018 Survey in Liaoning Province, this study uses a Probit model to analyze the effect of non-farm work on clean energy adoption, as well as an effect decomposition model to examine the specific mechanism of their interaction. Robustness tests were performed using extended regression models (ERMs), propensity score matching (PSM), and variation of the core explanatory variable measures. The results found that: (1) Rural residents’ non-farm work has a significant positive effect on their household clean energy adoption. (2) Increasing rural residents’ household income and promoting the growth of their health knowledge are the main channels through which non-farm work influences their clean energy adoption. (3) Non-farm work has a more positive impact on household clean energy adoption for young or male farmers, those who had a junior high school education or above, and those who had a village head in the family. This study provides an understanding of rural non-farm work and clean energy adoption decisions and provides references for the effective allocation of rural labor resources and the formulation of policies related to rural energy adoption.

Using machine learning to predict clean energy stock prices: How important are market volatility and economic policy uncertainty?

The disruptive impacts of climate change have created an urgent need to transition to a low carbon economy and an important part of this transition is an increase in the usage of clean energy. The greater adoption of clean energy is creating new opportunities for clean energy equity investing. The existing literature mostly focuses on the dynamic relationship between clean energy equities, oil prices, technology stock prices, and other important macroeconomic variables like market volatility and economic policy uncertainty. However, there is a shortage of literature on forecasting clean energy stock prices. Forecasting clean energy equity prices is important for making investment decisions. This paper uses machine learning methods to predict the direction of clean energy stock prices. The analysis reveals that random forests, extremely randomized trees, stochastic gradient boosting, and support vector machine have higher prediction accuracy than Lasso or Naïve Bayes. For forecasts in the 10-day to 20-day range, random forests, extremely randomized trees, stochastic gradient boosting, and support vector machine achieve prediction accuracies greater than 85 %. In some cases, prediction accuracy reaches 90%. Lasso prediction accuracy is higher than Naïve Bayes but never greater than 65 %. The MA200, MA50, and WAD technical indicators are, on average, the features most important for predicting clean energy stock price direction. Of the non-technical indicators, VIX and OVX are consistently ranked high in importance. In most cases, EPU is not one of the most important features, Of the forecasting methods considered, extremely randomized trees are very impressive due to high accuracy and short computational time.

Can clean energy adoption and international trade contribute to the achievement of India’s 2070 carbon neutrality agenda? Evidence using quantile ARDL measures

ABSTRACT India is a major developing world economy that has predominantly been highly energy-intensive and fossil fuel dependent. Consequently, this South Asian nation has not been able to safeguard its environment from persistent degradation through the discharge of greenhouse gases. Accordingly, this study tries to reveal the relationships between Carbon Dioxide (CO2) emissions, renewable energy consumption, international trade, and economic growth in India in order to recommend policies that can help the nation attain carbon neutrality. Both the conventional Autoregressive Distributed Lag (ARDL) and the newly developed Quantile ARDL (QARDL) models are used in this study. The ARDL results unveil that 1% increase in renewable energy consumption contributes to 0.8% reduction in CO2 emissions, while economic growth boosts CO2 emissions in the long run. Besides, international trade deteriorates the environment by amplifying emissions only in the short run. The QARDL results reveal that economic growth positively and renewable energy consumption negatively affect CO2 emissions across all quantiles of CO2 emissions. In contrast, international trade is not found to exert any statistically significant effect on CO2 emissions. Lastly, the quantile-based causality analysis somewhat supports the regression findings by verifying causal associations between the variables of concern in India’s context. Thus, in light of these findings, several carbon neutrality-related policy insights are put forward.

A novel design approach to prefabricated BIPV walls for multi-storey buildings

Building-integrated photovoltaics (BIPV) allow the adoption of clean energy on site and promote low-energy buildings. In highly urbanised cities, BIPV applications on building façades are preferable to rooftop solar systems, especially on tall buildings with limited roof space. However, the lack of “plug-and-play” BIPV on the market has hindered their deployment. To facilitate BIPV adoption in buildings, this study investigates the design method of a prefabricated unitised BIPV wall system based on the prefabrication technology of light gauge steel structure. The new BIPV wall system is characterised by an “all-in-one” design with multiple functional layers that allows the independent operation of each unit and an interlocking joint design that enables fast installation and guarantees air and water tightness requirements. The investigated novel and systematic design approach includes two-dimensional cross-sectional design, PV mounting design, three-dimensional modelling and system mock-up. The outcome of the design approach has been constructed and demonstrated at full-scale in Singapore. Three workers without electrical experience can handle the on-site installation manually from indoors in the building without the use of scaffolding, because each unit is preassembled and pre-wired at the off-site factory. The findings reveal practical implications and the potential of the prefabricated BIPV system, as well as several limitations in the current study and future research directions for further development.

Climate change disclosure and sustainable development goals (SDGs) of the 2030 agenda: the moderating role of corporate governance

PurposeThis study is justified by the economic importance of information on greenhouse gases, as well as the interest in the question of governance structure after the adoption of the objectives of the 2030 Agenda. The problem is also explained by the lack of research that has investigated the relationship between the best governance structure that contributes to achieving sustainability goals, including climate actions (SDG13) and clean energy adoption (SDG7) as part of the 2030 Agenda.Design/methodology/approachThe level of disclosure is measured on the basis of the carbon disclosure score calculated by the carbon disclosure project (CDP). The study sample consists of 387 US companies that voluntarily participated in the CDP survey from 2011 to 2018. The authors use panel data analysis based on multiple regression models.FindingsThe results confirm the influential role of board size, director independence, the presence of women on the board and the presence of an environmental committee on carbon disclosure. In terms of carbon disclosure, the results suggest that a better governance structure is likely to reduce carbon emissions and improve carbon performance practices. Similarly, the analyses show a different representation of the role of corporate governance in high-carbon sectors compared to low-carbon sectors.Research limitations/implicationsThis study has some limitations. First, the sample is only interested in US companies that responded to the CDP questionnaire during the period 2011–2018. Thus, the results cannot be generalized to countries with different governance structures. Second, the data from this study on carbon disclosure, specifically focuses on CDP reporting to determine the carbon disclosure score. In this sense, the findings on information disclosed do not necessarily address disclosures through other media, such as a company’s website or a press release.Originality/valueSustainability and commitment to the sustainable development goals (SDGs) are more likely to exist in companies that have good governance and, in particular, a better board. The research is inspired by the SDGs. The study aims to examine the relationship between carbon disclosure and corporate governance in the context of SDGs. Indeed, this research work contributes to achieving sustainability goals, including climate actions (SDG13) and clean energy adoption (SDG7).