This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased.
Economic growth is a global requirement that requires extensive energy consumption, and this phenomenon needs researchers' attention and regulators' focus. Thereby, the paper scrutinizes the determinants of energy consumption such as fossil fuel energy consumption (FFEC), energy use, nuclear energy consumption (NEC), energy import, and renewable energy consumption (REC) and sustainability-oriented eco-innovation and their effectiveness on the economic growth of Saudi Arabia. The study extracted data from the World Bank from 1989 to 2020. Stationarity was examined using augmented Dickey-Fuller (ADF) tests, and the associations among constructs were analyzed through QARDL model. The findings revealed that FFEC, EU, NEC, EI, REC, and sustainability-oriented eco-innovation are significantly correlated with the EG of Saudi Arabia. The study also provides insights to new researchers who will investigate this area in the future and guides regulators in developing regulations related to economic growth using an appropriate level of energy and adoption of sustainability-oriented eco-innovation.
Since the inception of the twenty-first century, there has been a profound upsurge in economic policy uncertainty (EPU) with several economic and environmental impacts. Although there exists a growing body of literature that probes the economic effects of EPU, the EPU-energy nexus yet remains understudied. To fill this gap, the current study probes the impact of disaggregated EPU (i.e., monetary, fiscal, and trade policy uncertainty) on energy consumption (EC) in the USA covering the period 1990M1-2020M12. In particular, we use sectoral EC (i.e., energy consumed by the residential sector, the industrial sector, the transport sector, the electric power sector, and the commercial sector) in consort with total EC. The findings from the bootstrap ARDL approach document that monetary policy uncertainty (MP) plunges EC, whereas trade (TP) and fiscal policy uncertainty (FP) escalate EC in the long run. On the contrary, there is a heterogeneous impact of FP and MP across sectors in the short run, while TP does not affect EC. Keeping in view the findings, we propose policy recommendations to achieve numerous Sustainable Development Goals.
The BRICS nations-Brazil, Russia, India, China, and South Africa-have grown significantly in importance over the past few decades, playing a vital role in the development and growth of the global economy. This expansion has not been without cost, either, since these countries' concern over environmental deterioration has risen sharply. Both researchers and decision-makers have focused a lot of attention on the connection between economic growth and ecological sustainability. By using nonlinear autoregressive distributed lag (NARDL) approach, the complex relationships were analyzed between important economic indicators-such as gross domestic product (GDP), ecological innovations (EI), energy consumption (ENC), institutional performance (IP), and trade openness (TOP)-and their effect on carbon emissions and nitrous oxide emissions in the BRICS countries from 1990 to 2021, this study seeks to contribute to this important dialog. Principal component analysis is formed for technological innovations and institutional performance using six (ICT service exports as a percentage of service exports, computer communications as a percentage of commercial service exports, fixed telephone subscriptions per 100 people, internet users as a percentage of the population, number of patent applications, and R&D expenditures as a percentage of GDP) and twelve (government stability, investment profile, socioeconomic conditions, internal conflict, external conflict, military in politics, control of corruption, religious tensions, ethnic tensions, law and order, bureaucracy quality, and democratic accountability) distinct indicators, respectively. The results of nonlinear autoregressive distributed lag estimation show that increase in economic growth would increase carbon dioxide and nitrous oxide emissions. The positive and negative shocks in trade openness have positive and significant impact on carbon dioxide and nitrous oxide emissions in BRICS countries. Furthermore, the positive shock energy consumptions have positive and significant effect on Brazil and India when carbon dioxide and nitrous oxide emissions are used. However, EKC exists in BRICS countries when carbon dioxide and nitrous oxide emissions are used. According to long-term estimation, energy consumption and technological innovations in the BRICS countries show a strong and adverse link with nitrous oxide and a favorable relationship with carbon dioxide emissions. In the long run, environmental indicators are seen to have a major and unfavorable impact in BRICS nations. Finally, it is proposed that BRICS nations can assure environmental sustainability if they support creative activities, enhance their institutions, and support free trade policies.
Global warming remains the most devastating environmental issue embattling the global economies, with significant contributions emanating from CO2 emissions. The continued rise in the level of greenhouse gas (GHG) emissions serves as a compelling force which constitutes the core of discussion at the recent COP26 prompting nations to commit to the net-zero emission target. The current research presents the first empirical investigation on the roles of technological advancement, demographic mobility, and energy transition in G7 pathways to environmental sustainability captured by CO2 emissions per capita (PCCO2) from 2000 to 2019. The study considers the additional impacts of structural change and resource abundance. The empirical backings are subjected to pre-estimation tests consisting of cross-sectional dependence, second-generation stationarity, and panel cointegration tests. The model estimation is based on cross-sectional augmented autoregressive distributed lag, dynamic common correlated effects mean group, and augmented mean group for the main analysis and robustness checks. The findings reveal the existence of EKC based on the direct and indirect effects of the components of economic growth. The indicators of demographic mobility differ in the direction of influence on PCCO2. For instance, while rural population growth negatively influences PCCO2 in the short-run alone, urban population growth increases PCCO2 in the short-run and long-run periods. Nonrenewable energy, information computer technology (ICT) imports, and mobile cellular subscriptions serve as positive predictors of PCCO2, while ICT exports and renewable energy moderate the surge in PCCO2. Policy implications that enhance environmental sustainability are suggested following the empirical verifications.
Global warming and the dreadful climate condition in China demands the sustainable energy transition and production that must be far away from coal-based energy production. The present article, thereby, intends to assess the effectiveness of environmental knowledge and green supply chain practices on sustainable energy production. The study also introduces green behavior and green leadership as a moderator to evaluate the proposed relationship. Primary data has been collected and assessed by PLS-SEM. The findings reveal that environmental knowledge, green purchases, and internal environmental management (IEM) have a positive association with sustainable energy production (SEP) in China. The outcomes also indicate that green behavior significantly moderates among environmental knowledge, green purchases, and SEP, and green leadership significantly moderates among IEM and SEP in China. The research guides the policymakers in establishing policies related to SEP using green behavior, GSC practices, and environmental knowledge.
Wind is a renewable energy source. Overall, using wind to produce energy has fewer effects on the environment than many other energy sources. Wind and solar energy provide public health and environmental benefits to the social. Wind turbines may also reduce the amount of electricity generation from fossil fuels, which results in lower total air pollution and carbon dioxide emissions. In order to better optimize the effect of social energy economic management and facilitate the multiobjective decision making of coordinated development of energy and socioeconomic environment, a modeling and analysis method of economic benefits of wind power generation based on deep learning is proposed. In this paper, based on the principle of deep learning, the evaluation indicators of wind power economic benefits are excavated, a scientific and reasonable economic benefit evaluation system is constructed, a wind power economic benefit analysis model supported by public management is constructed, and the steps of wind power economic benefit analysis are simplified. It is concluded that the modeling and analysis method of wind power economic benefits based on deep learning has high practicability in the actual application process, which is convenient for the prediction and analysis of energy demand for social and economic development.
The connection between ecological footprint and economic complexity has significant implications for environmental sustainability regarding the policy. Additionally, institutional quality is crucial in ensuring environmental sustainability and moderating the link between economic complexity and ecological footprint. The task of achieving sustainable environmental development and preventing further degradation of the environment poses a formidable challenge to policymakers. This study delves into the significance of technology innovation and renewable energy in creating a more sustainable environment. Recognizing the need for a more critical review, this research establishes the dynamic linkage between ecological footprint, renewable energy consumption, and technological innovation, especially in conjunction with a moderating component, particularly institutional quality, in G20 countries from 1990 to 2021. We employ advanced panel approaches to address panel data analysis concerns, such as cross-sectional dependence, slope heterogeneity, unit root, cointegration test and CS-ARDL. The long-term estimator indicates that renewable energy and technological innovation negatively but significantly impact the ecological footprint. Whilst economic growth, FDI, and urbanization have shown a positive and significant impact on ecological footprint; institutional quality negatively moderates the relationship between ecological footprint, renewable energy, and technological innovation in the G20 countries. Further evidence from the Dumitrescu-Hurlin Granger causality test shows that efforts to expand access to renewable energy, technological advancements, and economic growth will significantly affect environmental impacts. Based on our results, it is imperative to introduce more favorable legislation and encourage technological advancements in the field of renewable energy if we want to achieve our sustainable development objectives.
With the growing nature of the ecological footprint, research studies focus on exploring new determinants of environmental degradation. Moreover, the role of natural resources and energy consumption in environmental quality has gained much attention in the literature. However, tourism raises the demand for energy consumption and extraction of natural resources. This research study investigates the influence of natural resources, tourism, and renewable energy in MINT countries, using novel Cross-Sectional Auto Regressive Distributive Lag (CS-ARDL) methodological techniques and employing yearly data from 1995 to 2018. The study also applied recently developed Kónya (Econ Model 23:978-992, 2006) causality to identify the causal relationship between the variables of the heterogenous panel. The result shows that tourism, natural resources, and economic growth are positively associated with the ecological footprint in the long-run. However, renewable energy consumption negatively impacts ecological footprint in both in short-run and the long-run. Further, the study explored a bidirectional causality between economic growth and ecological footprint in MINT countries. Finally, based on the empirical results, the study recommends that the authorities in MINT countries revisit their tourism, natural resources, and economic activities policies to enhance the environmental quality and reduce the ecological footprint.
The lack of control in voltage overshoot, transient response, and steady state error are major issues that are frequently encountered in a grid-connected photovoltaic (PV) system, resulting in poor power quality performance and damages to the overall power system. This paper presents the performance of a control strategy for an inverter in a three-phase grid-connected PV system. The system consists of a PV panel, a boost converter, a DC link, an inverter, and a resistor-inductor (RL) filter and is connected to the utility grid through a voltage source inverter. The main objective of the proposed strategy is to improve the power quality performance of the three-phase grid-connected inverter system by optimising the proportional-integral (PI) controller. Such a strategy aims to reduce the DC link input voltage fluctuation, decrease the harmonics, and stabilise the output current, voltage, frequency, and power flow. The particle swarm optimisation (PSO) technique was implemented to tune the PI controller parameters by minimising the error of the voltage regulator and current controller schemes in the inverter system. The system model and control strategies were implemented using MATLAB/Simulink environment (Version 2020A) Simscape-Power system toolbox. Results show that the proposed strategy outperformed other reported research works with total harmonic distortion (THD) at a grid voltage and current of 0.29% and 2.72%, respectively, and a transient response time of 0.1853s. Compared to conventional systems, the PI controller with PSO-based optimization provides less voltage overshoot by 11.1% while reducing the time to reach equilibrium state by 32.6%. The consideration of additional input parameters and the optimization of input parameters were identified to be the two main factors that contribute to the significant improvements in power quality control. Therefore, the proposed strategy effectively enhances the power quality of the utility grid, and such an enhancement contributes to the efficient and smooth integration of the PV system.
This study utilized panel data from 132 countries spanning from 1996 to 2019 to examine the effect of government efficiency on carbon emission intensity. Using a fixed effect model, the study found that stronger government efficiency is associated with a significant decrease in carbon emission intensity. Robustness tests were performed, the results of which consistently supported the main findings. Additionally, the study investigated the mechanisms underlying the linkage between government efficiency and carbon emission intensity, revealing that improved government efficiency can inhibit carbon emission intensity by fostering environmental innovation and promoting renewable energy consumption. Finally, the study examined the moderating effects of national income level, economic freedom, democracy, and ruling party ideology on the nexus of government efficiency and carbon emission intensity, and found empirical evidence supporting these moderating effects. These results provide new insights for governments seeking to reduce carbon emission intensity.
Policy adjustments can help strike a balance between economic growth and environmental sustainability, which has increasingly been the heart to nations and regions throughout the World. This paper examines how public investment affects economic growth, energy consumption, and CO2 emissions in eight ASEAN countries: Cambodia, Myanmar, Malaysia, Indonesia, the Philippines, Singapore, Thailand, and Vietnam. Extension of a Cobb-Douglas production function and application of panel cointegration techniques reveal bidirectional Granger causation between public investment and both private development and CO2 emissions from 1980 to 2019. Public investment Granger causes energy usage, the opposite does not hold statistically. More findings from pooled mean group estimations show a mean-reversion dynamic that corrects disequilibria by 14% yearly. State investment crowds in private sector growth, energy use, and carbon footprint. It also finds an inverted U-shaped relationship between public investment and energy consumption, and a U-shaped relationship between public investment and CO2 emissions, indicating complex regional interactions. It is suggested the implementation of public investment policies that enrich green infrastructure projects to foster growth while minimizing environmental impacts, and encourage a strategic approach to public investment for prioritizing environmental sustainability and thus, achieving Sustainable Development Goals 7 to 9 and 11 to 13 in this region.
In terms of achieving sustainable development goals (SDGs), the developing economies are facing many issues, and one of the key issues is environmental degradation. Being a developing economy, Pakistan is also experiencing thought-provoking impacts of global warming and still far away from the ideal track of sustainable development. For addressing environment-related issue and achieving the targets of SDGs, a policy-level reorientation might be necessary. In this view, this study investigates the impact of economic growth, transport infrastructure, urbanization, financial development, and renewable energy consumption on CO2 emissions by using the data of Pakistan during 1990-2020. For this purpose, we use novel wavelet quantile correlation approach. The empirical results of wavelet quantile correlation approach demonstrate that economic growth, transport infrastructure, urbanization, and financial development are responsible for environmental pollution. Whereas, result also claims that renewable energy consumption is a useful tool for reducing environmental pollution in Pakistan. Moreover, the results of FMOLS approach show that 1% increase in economic growth, transportation infrastructure, urbanization, and financial development increases CO2 emissions by 0.240, 0.010, 0.478, and 0.102%, respectively. However, 1% increase in renewable energy usage reduces CO2 emission by 1.083%. Based on the empirical outcomes, this study proposes comprehensive policy framework for achieving the targets of SDG 7 (clean energy), SDG 8 (economic growth), SDG 11 (sustainable cities and communities), and SDG 13 (climate action).
A country's financing system is essential in addressing sustainable development requirements. National sources and international financial flows contribute to economic growth and environmental quality in many ways, and their impact can be critical. This paper applied panel data analysis using a comparative approach of Pooled Mean Group Auto Regressive Distribute Lags (PMG-ARDL) and Cross Sectionally ARDL (CS-ARDL) to estimate the effects of FDI, renewable energy, and remittance on environmental quality in the top remittance-receiving countries, during 2000-2021. The study emphasized the positive relationship between FDI and carbon emissions. Moreover, renewable energy and remittances revealed an inverted U-shaped relationship with carbon emissions. In the case of developing countries from the panel, remittance improves environmental quality after reaching the threshold. Moreover, for some of the developing countries included in the panel, we found that they do not achieve the desired carbon mitigation effect in their early stages of renewable energy implementation. However, renewable energy becomes a key factor for tackling environmental pollution after a certain threshold. The mixed results determined diverse policy recommendations for various stakeholders.
The rapid rise in climate and ecological challenges have allowed policymakers to introduce stringent environmental policies. In addition, financial limitations may pose challenges for countries looking to green energy investments as energy transition is associated with geopolitical risks that could create uncertainty and dissuade green energy investments. The current study uses PTR and PSTR as econometric strategy to investigate how geopolitical risks and financial development indicators influence energy transition in selected industrial economies. Our findings indicate a non-linear DCPB-RE relationship with a threshold equal to 39.361 in PTR model and 35.605 and 122.35 in PSTR model. Additionally, when the threshold was estimated above, financial development indicators and geopolitical risk positively impacts renewable energy. This confirms that these economies operate within a geopolitical context, with the objective of investing more in clean energy. We report novel policy suggestion to encourage policymakers promoting energy transition and advance the sustainable financing development and ecological sustainability.
Anthropogenic activities are largely responsible for the vast amounts of pollutants such as polycyclic aromatic hydrocarbons, cyanides, phenols, metal derivatives, sulphides, and other chemicals in wastewater. The excess benzene, toluene and xylene (BTX) can cause severe toxicity to living organisms in wastewater. A novel approach to mitigate this problem is the benthic microbial fuel cell (BMFC) setup to produce renewable energy and bio-remediate wastewater aromatic hydrocarbons. Several mechanisms of electrogens have been utilized for the bioremediation of BTX through BMFCs. In the future, BMFCs may be significant for chemical and petrochemical industry wastewater treatment. The distinct factors are considered to evaluate the performance of BMFCs, such as pollutant removal efficiency, power density, and current density, which are discussed by using operating parameters such as, pH, temperature and internal resistance. To further upgrade the BMFC technology, this review summarizes prototype electrode materials, the bioremediation of BTX, and their applications.
The purpose of this study is to explore the effect of financial development on CO2 emission in 129 countries classified by the income level. A panel CO2 emission model using urbanisation, GDP growth, trade openness, petroleum consumption and financial development variables that are major determinants of CO2 emission was constructed for the 1980-2011 period. The results revealed that the variables are cointegrated based on the Pedroni cointegration test. The dynamic ordinary least squares (OLS) and the Granger causality test results also show that financial development can improve environmental quality in the short run and long run due to its negative effect on CO2 emission. The rest of the determinants, especially petroleum consumption, are determined to be the major source of environmental damage in most of the income group countries. Based on the results obtained, the investigated countries should provide banking loans to projects and investments that can promote energy savings, energy efficiency and renewable energy to help these countries reduce environmental damage in both the short and long run.
Food waste and food processing wastes which are abundant in nature and rich in carbon content can be attractive renewable substrates for sustainable biohydrogen production due to wide economic prospects in industries. Many studies utilizing common food wastes such as dining hall or restaurant waste and wastes generated from food processing industries have shown good percentages of hydrogen in gas composition, production yield and rate. The carbon composition in food waste also plays a crucial role in determining high biohydrogen yield. Physicochemical factors such as pre-treatment to seed culture, pH, temperature (mesophilic/thermophilic) and etc. are also important to ensure the dominance of hydrogen-producing bacteria in dark fermentation. This review demonstrates the potential of food waste and food processing waste for biohydrogen production and provides a brief overview of several physicochemical factors that affect biohydrogen production in dark fermentation. The economic viability of biohydrogen production from food waste is also discussed.
Current human activities are seriously eroding the ability of natural and social systems to cope. Clearly we cannot continue along our current path without seriously damaging our own ability to survive as a species. This problem is usually framed as one of sustainability. As concerned professionals, citizens, and humans there is a strong collective will to address what we see as a failure to protect the natural and social environments that supports us. While acknowledging that we cannot do this alone, human factors and ergonomics needs to apply its relevant skills and knowledge to assist where it can in addressing the commonly identified problem areas. These problems include pollution, climate change, renewable energy, land transformation, and social unrest amongst numerous other emerging global problems. The issue of sustainability raises two fundamental questions for human factors and ergonomics: which system requires sustaining and what length of time is considered sustainable? In this paper we apply Wilson (2014) parent-sibling-child model to understanding what is required of an HFE sustainability response. This model is used to frame the papers that appear in this Special Issue.
The data consists of actual generation-side auditing including the distribution of loads, seasonal load profiles, and types of loads as well as an analysis of local development planning of a resort island in the South China Sea. The data has been used to propose an optimal combination of hybrid renewable energy systems that able to mitigate the diesel fuel dependency on the island. The resort island selected is Tioman, as it represents the typical energy requirements of many resort islands in the South China Sea. The data presented are related to the research article "Optimal Combination of Solar, Wind, Micro-Hydro and Diesel Systems based on Actual Seasonal Load Profiles for a Resort Island in the South China Sea" [1].