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This study's objective is to analyze ecological footprints that exist among China's economic growth, energy consumption, carbon dioxide emissions, and the revenue that is generated from tourism in other countries. The years 1995 through 2020 are the focus of this particular research endeavor. The relationship between tourism and carbon emissions has been discovered by a large number of researchers; nevertheless, the findings have been inconsistent and do not give a clear picture of the situation. We can only hope that the results of the study will improve the existing body of knowledge on tourism and the quality of the surrounding environment. Throughout the whole of this investigation, the autoregressive distributed lagged (ARDL) model was used to explore both long-run and short-run estimations. A dynamic ordinary least squares (DOLS) model was used in the study to arrive at long-term estimations that could be relied upon. Even though money from tourism does not have a substantial influence on the quality of the environment in China, growth and increasing energy usage are primary donors to carbon emissions in the nation. ARDL model's long-term projections were shown to be correct by the DOLS approach, which offered this validation. The results of the research provide fresh insights into the body of knowledge that has been accumulated on the subject of the linkage between tourism and the natural environment. Because the receipts from tourism do not have any significant negative exteriority toward the environment, energy usage is an important element of environmental degradation and policymakers should prioritize the development of the tourism sector over energy-focused manufacturing activities to maintain the growth of the nation in the upper quartiles. This is because tourism does not have any significant negative externalities on the environment. Sustainable tourism minimizes environmental and cultural damage while boosting profits. Developing the appropriate technology, physical infrastructure, and human capital requires money, time, and effort. [ABSTRACT FROM AUTHOR]

The current paper explores the influence of disintegrated energy and economic complexity on CO2 emissions (CO2) in the top economic complexity economies. The model also incorporates other drivers of CO2, such as technological innovation and economic growth. The current research utilizes data stretching from 1993 to 2018. The research employed Westerlund cointegration, fully modified OLS (FMOLS), dynamic OLS (DOLS), and method of moments quantile regression (MMQR) to evaluate these interconnections. The outcomes of the slope heterogeneity and cross-sectional dependence affirmed the use of second-generation techniques. The study confirmed the long-run association between CO2 and the regressors. The results of the MMQR disclosed that in each quantile (0.1–0.90), renewable energy enhances the quality of the environment, while economic complexity and nonrenewable energy intensify CO2. In addition, technological innovation enhances the quality of the environment from 0.1–0.70 quantiles, while from 0.80–90 quantiles, technological innovation intensifies CO2. The EKC is also validated in each quantile (0.1–0.90). The DOLS, FE-OLS, and FMOLS outcomes also affirm the MMQR outcomes. These outcomes encourage policymakers to implement holistic economic and environmental policies that prioritize greener production processes for environmental reasons and meet the United Nations SDGs 7, 8, 13, and 17.

Despite the growing knowledge and commitment to climate change, carbon dioxide (CO2) emissions continue to rise dramatically throughout the planet. In recent years, the consequences of climate change have become more catastrophic and have attracted widespread attention globally. CO2emissions from the energy industry have lately been highlighted as one of the world’s most pressing concerns for all countries. This paper examines the relationships between CO2emissions, electrical energy consumption, and gross domestic product (GDP) in Bangladesh from 1972 to 2019 in the first section. In this purpose, we applied the fully modified ordinary least squares (FMOLS) approach. The findings indicate that CO2emissions, electrical energy consumption, and GDP have a statistically significant long-term cointegrating relationship. Developing an accurate CO2emissions forecasting model is crucial for tackling it safely. This leads to the second step, which involves formulating the multivariate time series CO2emissions forecasting challenges considering its influential factors. Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). The root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) are used to analyze and compare the performances of the predictive models. The prediction errors in MAPE of the CNN, CNN–LSTM, LSTM, and DNN are 15.043, 5.065, 5.377, and 3.678, respectively. After evaluating those deep learning models, a multivariate polynomial regression has also been employed to forecast CO2emissions. It seems to have nearly similar accuracy as the LSTM model, having a MAPE of 5.541.

Undoubtedly, global warming is one of the main debatable topics among politicians, scholars, academicians, being discussedeverywhere and by everyone. Having into consideration that one of the main factors of the global warming are the greenhouse gas emissions, where carbon dioxide represents 76% of these emissions, the main aim of this paper is to analyse the effects of the CO2 emissions as well as other greenhouse gas emissions on the economy and society. In addition, a panel analysis has been conducted, where OLS, Fixed and Random effects models are used in order to check the impact of the CO2 emissions on the GDP per capita of developing countries of Western Balkans region, for the last three decades. Finally, the main conclusions and consequences from the negative impact of the CO2 emissions on the society, economy and growth of the developing countries have been highlighted as well as several important suggestions have been stated for emphasising and addressing the problems that we will be facing soonbecause of the global warming. [ABSTRACT FROM AUTHOR]

Angela Merkel's energy policy in Germany beginning in the 2010s has been marked by the accelerated implementation of the energy transition plan known as "Energiewende". The plan, which has involved as its central component aggressive denuclearization in the wake of the 2011 Fukushima crisis, has resulted in a revolution in the country's energy sector, especially with regard to the country's extensive use of nuclear energy. This has left Germany in the position of replacing a relatively clean energy source with more polluting ones, such as lignite and natural gas, resulting in a paradox given the 'green' nature of the plan. This article analyzes private economic impacts of the plan as well as changes in energy sources and carbon emissions resulting from the Energiewende from 2010 to 2020. [ABSTRACT FROM AUTHOR]

The effects of climate change and greenhouse gases (GHG) emissions are one of the deep concerns today. The energy generation sector contributes significantly to these emissions, potentiating the climate change and the vulnerability of society and the environment. To attain the Paris Agreement goals, the decarbonization of energy sector at global scale may be a solution, which includes the insertion of more renewable sources in the energy mix. In this sense, the increase on generation by wind energy is a feasible option to achieve these targets. Although the wind energy is considered a “cleaner” source and “free of CO2emissions”, when its entire life cycle is considered, it is possible to verify that certain stages, namely the equipment manufacturing and decommissioning, have different and significant contributions in terms of inputs and energy consumption, but also gases emissions and environmental impacts.Thereby, the aim of this research is to present a systematic literature review of wind farms life cycle assessments, the relevant aspects related to CO2 emissions and resource consumption are highlighted, and improvements in process and advantages of equipment reusing in end of service for diminishing the effects of climate change are discussed.

The public understanding of climate change, methods, mitigation, adaptation and the reason behind it have been investigated in developed countries. The current knowledge levels in the Global South remains limited, this while countries forming part of the Global South are more vulnerable to resultant effects of global warming. This requires the urgent attention by both citizens, who lack relevant information as well as decision makers lacking environmental literacy to establish long-term sustainable strategies.With just 9 years left, the probability of achieving the Sustainable Development Goals (SDGs) , is unlikely and will require the complete redevelopment of the building sector. Focusing on the built environment, this paper uses contemporary definitions of the Global South to establish the contribution, significance and lack of energy efficiency mechanisms in the face of climate change. A combination of literature, desk research and data gathering from various sources are employed to establish the contribution of the Global South built environment to climate change. Using Carbon Dioxide (CO₂)emissions, 2050 urban population figures and distinctive climatic regions as basis, this study selected the largest role players to establish the status, extent and efficacy of building energy codes. The review point towards a built environment lacking the necessary building energy codes, with approximately 47% of selected Global South countries not implementing any form of building energy efficiency regulations or related policies. As part of the recommendations, Global South countries lacking the necessary regulations are encouraged to revise, update or adopt possible best practice standards from relevant countries that implement mandatory building energy codes. This study aims to address the gap in knowledge, establish a way forward and facilitate a larger implementation of building energy codes and strategies in the Global South.

In recentyears, regarding theinfluence of the production processes and vehicles on the environment, new technical solutions for reducing air pollutions have been studied and developed. One of the new constructionsis fuel cell electric vehicle (FCEV). The production and running conditions of the vehicles are specific in different countries. Hence, a study of theseconditions and fuel production process is needed. In this paper,a study of the FCEV efficiency,at different producing technologies of hydrogen (H2),is carried out. Life cycle assessment (LCA) method is used. A comparison, concerning fuel consumption and emissions as CO2equivalent for the whole life cycle,is done for FCEV and conventional gasoline vehicle (GV). The influence of the energy mix and technology of production of hydrogen on spent energy and air pollution is analyzed. As the results show, in countries with CO2 emissions over 447 g per 1 kWh electricity, the technology of hydrogen production from natural gas is most effective.Now and in the near future, the ecological and financial advantages, connected to renovation of existing vehicle fleet with FCEV,are not absolutely verified.

Basalts have shown greater potential for faster and permanent sequestration of anthropogenic CO2 than sedimentary formations. Sequestration occurs through mineral carbonation due to the abundance in divalent minerals making them efficient geological hosts where they occur. Rapid population and industrial growth in developing countries leads to an exponential increase in their CO2 emissions, from stationary sources hence there is an imminent need for solutions to limit the amount of CO2 released into the atmosphere. Carbon Capture and storage (CCS) projects globally are at various stages of development majority are located in America and Europe. However, the suitability of continental basalts occurring in the East African Rift for CCS has not been assessed. Their characteristics and occurrence close to stationary CO2 sources thus limiting the high cost of transportation to far-flung locations make them ideal. Our review identified about 19 basalt groups of Miocene to Recent age (23.02 to 0.01 Ma) with thickness ranging from a few meters to 1500 m in the Kenya rift. We assessed four key parameters to determine potential CO2 sequestration sites: water availability; subsurface temperature; permeability and porosity of target formation; and accessibility to geothermal systems. Minerals such as calcic plagioclase, iron oxides and clinopyroxenes in the basalts offer the divalent elements required for carbonation. The basalts have varying porosity values ranging between 1-30%. We assessed the viability and ranked the suitability of the regions in the Kenyan rift as central Kenya rift >northern Kenya rift > southern Kenya rift. The environmental and financial challenges and their mitigation options of CO2 sequestration in the Kenya rift basalts have also been discussed. The challenges that CCS projects in the Kenya rift have to deal with include the impact of toxic and corrosive gases from geothermal systems, leakages through faults and fractures, induced seismicity, and economic costs. This knowledge is required for identifying areas where more site-specific assessment and modelling can be done for CCS projects in identifying carbon sequestration areas that can help slow down climate change.

• We examine the effects of Environmental Innovations on CO 2 Emissions for 15 UE countries. • We use an ARDL model based on data covering the period 1991–2014. • Our results highlight that in the long-term environmental innovations tend to lower CO 2 emissions. • In the short-term the observed effect is the opposite, suggesting the existence of a rebound effect. • Several orientations in terms of public policies can be drawn up in the light of these results. Environmental innovations are key enablers of transition towards greener economies. Despite their importance, empirical studies examining the effect of green technologies on CO 2 emissions are still limited. Using an autoregressive distributed-lag model (ARDL), we analyze the impact of environmental innovations, the consumption of renewable energies, GDP per capita, and degree of economic openness on CO 2 emissions for 15 European countries over 23 years. Our results indicate that, in the long-term, environmental innovations tend to lower CO 2 emissions, whereas in the short-term the observed effect is the opposite, suggesting the existence of a rebound effect. This study recommends introducing new policies that combine tools of environmental economics with those of ecological economy to integrate economic incentives with regulatory changes and encourage individuals to consume differently by favouring products and/or services with a less negative impact on the environment. [ABSTRACT FROM AUTHOR]

The sustainable power solutions provided tonon-interconnected zonesshould bebased on the renewable energy resources available in each area. Thispresents a challenge for the techno-economic feasibility of alternativesolutionsthrough micro grids. Theobjective of this work is to analyze, using HOMER software,the techno-economic impact ofintroducingfuel cells on cost reduction during the lifetime of micro grids in non-interconnected zones. Such impact is evaluated in the technical design of the micro grid as Present Value and Levelized Cost of Electricity($/kWh). The analysis considers the calculation of the demand of a generic village, the size and cost of the technologies that constitute the micro grid to satisfythe demand,and the availability of solar and wind power in two areas located at different latitudes inColombia. In addition, the effect of introducingfuel cells intothe energy mix was examined.Finally, the advantages were highlighted by comparing each case with traditional generation alternatives based on diesel consumption.

The well-established emissions-growth debate relies on the symmetric nexus between CO2 emissions and economic growth, thereby ignoring a fundamental component of macro economy in the form of asymmetric relation. This paper considers how CO2 emissions respond asymmetrically to changes in economic growth. While utilizing both linear and nonlinear time series approaches for an environmentally exposed country, Pakistan over the period 1971–2018, we find convincing evidence that CO2 emissions rise more rapidly during negative shocks to economic growth than increase during economic expansions. Thus, contrary to what has previously been reported, the effect is strong as holds both at short run and long run. This is partly due to the increase in informal sector as GDP declines. Our estimated results show that accounting for the shadow economy results a higher magnitude of CO2 emissions due to decrease in economic growth, thus question the traditional symmetric decoupling of economic growth and CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and dynamic OLS (DOLS). Thus, the findings of this study call for a re-thinking on climate policy design that rarely pays attention to the aforementioned outcomes due to fall in economic growth. [ABSTRACT FROM AUTHOR]

• Analyzed nexus between Governance and CO 2 emissions in BRICS countries. • Robust panel data estimation methods are applied. • Governance lower CO 2 emissions and improve quality of the environment. • Governance help to form the Environmental Kuznets Curve hypothesis. The linkage between economic growth and carbon dioxide (CO 2) emissions has been quantified from both a theoretical perspective and an empirical perspective. However, these studies did not address the role of governance in environmental quality explicitly. Therefore, the current study examines the behavior of governance in CO 2 emissions within the framework of the Environmental Kuznets Curve hypothesis for panel data from 1996 to 2017 for BRICS countries. The study employs Westerlund panel cointegration for investigation of cointegration among study's variables. The long-run panel data estimation methods those eliminate dependencies across countries, heteroscedasticity, and spatial and serial dependency issues are used. To summarize the finding, governance has negative and statistically significant effects on CO 2 emissions, help to form the Environmental Kuznets Curve hypothesis and reduces CO 2 emissions in the BRICS countries. The newly developed results recommend the importance of governance in the clean environment and suggestions are directed accordingly [ABSTRACT FROM AUTHOR]

• Desalination brine can be used for CO 2 mineralization aimed at emission reduction. • Sequential mineralization of Ca and Mg raised the conversion ratio from 12% to 57%. • This approach is commercially viable and environmentally friendly. Desalination brine is a potential source for CO 2 mineralization aimed at reducing CO 2 emissions, because the concentration of Ca and Mg in brine is almost twice that of ordinary seawater. However, the previously achieved conversion ratio of CO 2 to carbonate minerals is too low for commercial application, as Ca and Mg compete and interfere with each other during precipitation. In this study, we tested the separate and sequential mineralization of Ca and Mg in brine, enhancing the CO 2 conversion ratio to 57% from 12%. We also tested the use of 15% CO 2 gas (the typical concentration of actual combustion gas), and it was observed that 69% of injected CO 2 was precipitated as Ca and Mg carbonate minerals and 99% of Ca and 69% of Mg in the initial brine were precipitated. In addition, the volume of NaOH solution required was reduced by 76%. This revised method is more material- and reagent-efficient which would likely have lower operation costs; moreover, as no further additives are required, environmental impact of brine release is also likely to be reduced. The findings of this study can help address environmental problems caused by large seawater desalination plants and thermal power plants. [ABSTRACT FROM AUTHOR]

China has become the world's largest carbon emitter, and coal consumption in the Yangtze River Economic Zone takes over more than one third of the total number in the country. Investigating the main influencing factors of the Yangtze River Economic Zone's CO2 emissions is of vital importance to develop effective environmental policies. The vector autoregression model was applied in the present paper to analyze the driving forces in this area based on the pertinent data from 1985 to 2014. Results show that energy efficiency is the primary influencing factor of the region's carbon emissions, which plays a leading role in mitigating CO2 emissions. Energy structure has an obviously positive impact on the zone's CO2 emissions. Urbanization has continuously promoted coal consumption in this area. These findings are extremely helpful for related departments in the Yangtze River Economic Zone to develop appropriate policies pertaining to energy savings and emissions reduction. [ABSTRACT FROM AUTHOR]

Highlights • The effects of structural change on CO 2 emissions are explored. • An econometric analysis framework is used, taking the period 1980–2015. • Unidirectional causality is found running from energy consumption structure to CO 2 emissions. • Unidirectional causality is found running from export and import structure to CO2 emissions. • Energy consumption structure and investment structure do significantly affect CO 2 emissions in the long run. Abstract This paper empirically explores the interactions between socioeconomic structures (i.e., energy consumption structure, economic structure, export and import structure, investment structure, and urban-rural structure) and CO 2 emissions in China, using time series data for the period 1980–2015, and employing an econometric analysis framework. Using the Augmented Dickey Fuller (ADF) unit root test, we surveyed the stationarity of the selected variables, all of which were found to be stationary at the first difference. Based on Vector Error-Correction Model (VECM) model, Granger causality test was further employed in order to detect the causal relationship among the competing variables. The results show the presence of unidirectional causality running from energy consumption structure, and from export and import structure, to CO 2 emissions. No causal link was found to exist in relation to the other two variables. An impulse response analysis and a variance decomposition analysis were subsequently utilized, the results of which demonstrated that the energy consumption structure and the investment structure do significantly affect CO 2 emissions in the long run and that the energy consumption structure is the most significant variable. This paper contributes existing scholarly research into the relationship between socioeconomic structure and CO 2 emissions, and our findings have significant implications for the government in the task of implementing policy measures in order to mitigate the growth of CO 2 emissions. [ABSTRACT FROM AUTHOR]

Highlights • An inter-provincial R&D spillover network based on geographic economic distance matrix is established to examine the centrality index of each province in China. • The inter-provincial R&D direct technology spillovers effect (DS) has a significant inhibitory effect on CO 2 emissions in nationwide, eastern and central regions, except in western region. • The inter-provincial R&D indirect technology spillovers effect (IS) has a significant inhibitory effect on CO 2 emissions in central region, IS measured by closeness and betweenness is significantly positively correlated with CO 2 emissions in western region, while IS has no significant effect on CO 2 emissions in eastern region. Abstract The increase of carbon dioxide (CO 2) emissions is the main reason of global warming, and the effect of technology progress on CO 2 emissions reduction has attracted more and more attention. This paper constructs an inter-provincial R&D spillover network based on geographic economic distance matrix, and measures the centrality index of each province using the social network analysis method. Regarding inter-provincial R&D direct technology spillovers effect (DS) and indirect technology spillovers effect (IS) as the proxy variables of technology progress, DS and IS are introduced into a panel econometric model for CO 2 emissions factor analysis. The panel data of 29 provinces in China from 2000 to 2013 are used for empirical analysis. The results show that DS has a significant inhibitory effect on CO 2 emissions in nationwide, eastern and central regions, except in western region. The role of IS on CO 2 emissions varies widely in sub-regions. Specifically, IS has a significant inhibitory effect on CO 2 emissions in central region, IS measured by closeness and betweenness is significantly positively correlated with CO 2 emissions in western region, while IS has no significant effect on CO 2 emissions in eastern region. [ABSTRACT FROM AUTHOR]

Pulp and paper production is a highly energy intensive process and improvement of energy efficiency in this process is considered as promising measures for reducing industrial greenhouse gases emissions (GHG). This study focuses the Pakistan's pulp and paper industry which consumes around 7% of the country's industrial energy and contributes to over 317,269 tonnes of CO2 emissions. With rising demands for fuels and consequently as harp increase in CO2 emissions due to the growth of the paper sector in Pakistan, this article aims to analyse the energy efficiency and carbon dioxide emissions reductions potential through the incorporation of cogeneration technologies. The cogeneration technologies studied are agas turbine, steam turbine and combined cycle and are evaluated from the energetic and economic point of view to propose a best suitable technology for each paper mill. The proposed cogeneration technologies are selected on the basis of high energy utilisation factor, as implepayback period of five years or less with least Annualised life cycle cost. The result shows that a theoretical energy saving potential equivalent to 16.9% of the actual thermal energy requirement of mills can be achieved through cogeneration which will lead to 14.3% reduction of the present carbon emissions levels in Pakistan's paper sector. [ABSTRACT FROM AUTHOR]

• Three exergoeconomic and environmental optimization models have been developed. • For the exergy performance model, photovoltaics dominated in power production. • The resource distribution is mainly based on wind technologies for the cost model. • The major part is for solar technologies when applying the CO 2 emission model. • The optimum cost model is the most suitable for the resource strategy in Tunisia. Recent attention to global warming has increased interest in sustainable technology. The current issues are the reduction of emissions and cost. Innovative hybrid systems that combine fossil fuel and renewable energy sources need to be developed. The optimization of these systems is essential to ensure the continuity of load supply and to decrease the cost of energy production. This work presented a novel optimisation method for exergy resource distribution within hybrid power systems based on exergoeconomic and environmental performance. Three optimization models were proposed: the first one focuses on minimizing exergy input, the second one considers the minimization of the production cost and the last model aims to minimize the CO 2 emissions. Tunisia was selected as a case study. The findings demonstrate that using model 1 results in gains in natural gas consumption, production costs, and CO 2 emissions of 75 kWh ex /kWh ex , 0.015 €/kWh ex , and 0.12 kg CO 2 /kWh ex , respectively. Furthermore, when model 2 is used, these gains amount to 49 kWh ex /kWh ex , 0.035 €/kWh ex , and 0.159 kg CO 2 /kWh ex. And finally, when model 3 is used, there will be 2.49 kWh ex /kWh ex , 0.015 €/kWh ex , and 0.168 kg CO 2 /kWh ex. It is concluded that the second model is more suitable for the resources strategy in Tunisia; it affords a minimum cost with a moderated exergy input and CO 2 emissions. [ABSTRACT FROM AUTHOR]

The operating ship, and especially those ones older than 10 years, is the most affected by the IMO enforced standards, because of the deficiency and insufficient applicable instruments as existing in the international practice, due to the technique misalignments and the implementation costs impact against the freight rate levels. Once the structure of the world fleet counts 32% share of the old ships as reported for 2015, the conception of new improvement methods becomes very important and most of the specialized companies and seeking for practical solutions in respect of energy efficiency. Overcoming these needs, the approached research as presented in the paperwork is proposing a new algorithm for cost-benefit analysis, conceived by the authors as a pragmatic solution for optimizing the energy efficiency onboard the old operating ships, exceeding 10 years in service. [ABSTRACT FROM AUTHOR]

Biomass transport represents a significant share of the final price of biomass for energy, and transport itself requires fuel, whose combustion adds to greenhouse gas emissions. We conducted a techno-economic analysis of biomass transport for the main forest wood products in Switzerland (firewood and woodchips), as well as for solid and liquid manure. First, we identified the most common transport chains from the supplier to the final consumer in Switzerland, by conducting expert interviews that followed a mental models approach. Then, we quantified the cost, energy and environmental performance of 12 identified transport chains for these types of biomass, using performance ratios. The results show that transport of forest wood is more performant than transport of manure, except when underground pipes are used for liquid manure. In the case of Switzerland, the main barrier to biomass transport is cost rather than energy or emissions performance. Energy required to deliver biomass to final consumers represents between 0.4% and 1.8% of the primary energy contained in the forest wood, and less than 5% in the case of manure. Some forest wood chains attain the maximum break-even transport distances after 36 km only, whereas others could reach over 400 km. Using agricultural transport for slurry should not exceed 3 km from the viewpoint of cost, but could be extended to over 145 km in the case of energy or CO 2 emissions. [Display omitted] • Mental models interviews are used to identify forest wood and manure transport chains. • Costs, energy requirements and CO 2 emissions are calculated for each transport chain. • Economic, energy and environmental performance differences can occur regionally. • The main barrier to biomass transport is its costs, not energy or CO 2 performances. [ABSTRACT FROM AUTHOR]