How to bend down the environmental Kuznets curve: the significance of biomass energy

Sources of renewable energy have received wide attention in the literature because of serious threats to the environment. However, some renewable resources, including biomass energy role is debatable in the energy economics literature. This empirical work focuses to analyze the role of biomass energy in carbon dioxide (CO₂) emissions using the framework of the environmental Kuznets curve (EKC) in Pakistan over the period from 1980 to 2015. The bound testing approach suggests there is cointegration among study variables. The study uses an auto-regressive distributed lag model (ARDL) with a structural break in the series. To summarize the findings of the study, it can be inferred that biomass energy increase CO₂ emissions. In addition, biomass energy helps to form a U-shaped relationship between income and CO₂ emissions that support the EKC hypothesis. Also, the feedback hypothesis is found between biomass energy and CO₂ emissions. The findings would guide policymaker with practical guidelines to formulate policies to utilize a high amount of biomass energy in a sustainable manner.

     

The role of innovations and renewable energy consumption in reducing environmental degradation in OECD countries: an investigation for Innovation Claudia Curve

Rising economic growth in recent ages is the primary concern of most of the countries to enhance the living standard, but the ever-increasing production of economic activities consumes a lot of energy, which leads to a sharp increase in carbon dioxide emissions. Innovation may be a remedy that can help improve energy efficiency, obtain renewable energy, and promote economic growth, thereby protecting the quality of the environment. Therefore, this paper examines the role of innovation and renewable energy consumption in CO2 reduction in OECD countries from 2004 to 2019. By using the two-step system generalized of moment estimator, the results show that economic growth and innovation significantly increase carbon emissions, however the innovation Claudia Curve (ICC) is verified, and the environmental Kuznets curve does not exist. Foreign direct investment has a negative impact on carbon emissions, thus verifying the Pollution Hao hypothesis, whereas renewable energy also improves environmental quality, but the interaction between innovation and renewable energy consumption still increases carbon emissions. Financial development, industrialization, trade, and energy consumption have also been found to be harmful factors of environmental quality. Our findings have considerable policy implications for OECD countries on the improvement of innovation indicators and investment in renewable energy sources to rise environmental quality.

     

Influencing factors of carbon emissions and their trends in China and India: a machine learning method

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO₂) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO₂ emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO₂ emissions; correspondingly, this study builds a model for CO₂ emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO₂ emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO₂ emissions. Finally, this study forecasted a CO₂ emission trend, with a slowdown predicted in China by 2022; however, CO₂ emission’s reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO₂ emissions without harming economic development.

     

Closing the carbon cycle through rational use of carbon-based fuels

In this paper, a brief overview is presented of natural gas as a fuel resource with subsequent carbon capture and re-use as a means to facilitate reduction and eventual elimination of man-made carbon emissions. A particular focus is shale gas and, to a lesser extent, methane hydrates, with the former believed to provide the most reasonable alternative as a transitional fuel toward a low-carbon future. An emphasis is placed on the gradual elimination of fossil resource usage as a fuel over the coming 35 to 85 years and its eventual replacement with renewable resources and nuclear power. Furthermore, it is proposed that synthesis of chemical feedstocks from recycled carbon dioxide and hydrogen-rich materials should be undertaken for specific applications in the transport sector which require access to high energy density fuels. To achieve the latter, carbon dioxide capture is imperative and possible synthetic routes for chemical feedstock production are briefly reviewed.     

Economic complexity,ICT, biomass energy consumption,and environmental degradation: evidence from Iran

Economic complexity, biomass energy consumption, and information communication technology (ICT) have diverse impacts on energy consumption and carbon dioxide (CO₂) emissions. Nevertheless, analysis of these variable effects is not addressed in the previous literature; the antiqueness of this article is stuffing this gap. This study assessed the relationship between gross domestic product (GDP) per capita, biomass consumption, economic complexity index (ECI), ICT, and CO₂ emissions in Iran in 1994–2018. The autoregressive distributed lag (ARDL) model and the quantile regression (QR) econometric technique were used to investigate the factors affecting CO₂ emissions in the tails of the conditional distribution. The share of each influential factor was predicted through the variance decomposition analysis (VD) for the next 10 years. The empirical results showed a long-run relationship between the variables. So, the variables of biomass consumption, ECI, and ICT improve the quality of the environment in Iran by reducing CO₂ emissions, and the per capita GDP variable increases CO₂ emissions. Results suggest no evidence indicating the presence of environmental Kuznets curve (EKC); however, QR demonstrated the existence of EKCs in the lower quantiles of the conditional distribution. The ECI will have the most share to change the CO₂ emissions in the future. The income threshold should be determined at the turning point of the EKC to increase economic development. Moreover, investing in increasing biomass consumption is vital. Policymakers also need to consider strict added value for the export of products.

     

Energy use and emissions from marine vessels: a total fuel life cycle approach

Regional and global air pollution from marine transportation is a growing concern. In discerning the sources of such pollution, researchers have become interested in tracking where along the total fuel life cycle these emissions occur. In addition, new efforts to introduce alternative fuels in marine vessels have raised questions about the energy use and environmental impacts of such fuels. To address these issues, this paper presents the Total Energy and Emissions Analysis for Marine Systems (TEAMS) model. TEAMS can be used to analyze total fuel life cycle emissions and energy use from marine vessels. TEAMS captures "well-to-hull" emissions, that is, emissions along the entire fuel pathway, including extraction, processing, distribution, and use in vessels. TEAMS conducts analyses for six fuel pathways: (1) petroleum to residual oil, (2) petroleum to conventional diesel, (3) petroleum to low-sulfur diesel, (4) natural gas to compressed natural gas, (5) natural gas to Fischer-Tropsch diesel, and (6) soybeans to biodiesel. TEAMS calculates total fuel-cycle emissions of three greenhouse gases (carbon dioxide, nitrous oxide, and methane) and five criteria pollutants (volatile organic compounds, carbon monoxide, nitrogen oxides, particulate matter with aerodynamic diameters of 10 microm or less, and sulfur oxides). TEAMS also calculates total energy consumption, fossil fuel consumption, and petroleum consumption associated with each of its six fuel cycles. TEAMS can be used to study emissions from a variety of user-defined vessels. This paper presents TEAMS and provides example modeling results for three case studies using alternative fuels: a passenger ferry, a tanker vessel, and a container ship.     

Are renewable energy policies upsetting carbon dioxide emissions? The case of Latin America countries

Environmental Science and Pollution Research - The impact of renewable energy policies in carbon dioxide emissions was analysed for a panel of ten Latin American countries, for the period from 1991...     

Effects of land urbanization and internet penetration on environmental sustainability: a cross-regional study of China

Environmental Science and Pollution Research - China has pledged to peak its carbon dioxide emissions (CEM) before 2030 and achieve carbon neutrality before 2060. The energy consumption related to...     

Developments in greenhouse gas emissions and net energy use in Danish agriculture - how to achieve substantial CO(2) reductions?

Greenhouse gas (GHG) emissions from agriculture are a significant contributor to total Danish emissions. Consequently, much effort is currently given to the exploration of potential strategies to reduce agricultural emissions. This paper presents results from a study estimating agricultural GHG emissions in the form of methane, nitrous oxide and carbon dioxide (including carbon sources and sinks, and the impact of energy consumption/bioenergy production) from Danish agriculture in the years 1990–2010. An analysis of possible measures to reduce the GHG emissions indicated that a 50–70% reduction of agricultural emissions by 2050 relative to 1990 is achievable, including mitigation measures in relation to the handling of manure and fertilisers, optimization of animal feeding, cropping practices, and land use changes with more organic farming, afforestation and energy crops. In addition, the bioenergy production may be increased significantly without reducing the food production, whereby Danish agriculture could achieve a positive energy balance.     

Optimization for municipal solid waste treatment based on energy consumption and contaminant emission

This paper analyzes the characterization of energy consumption and contaminant emissions from a municipal solid waste (MSW) treatment system that comprises transfer station, landfill site, combustion plant, composting plant, dejecta treatment station, and an integrated MSW treatment plant. The consumed energy and energy medium materials were integrated under comprehensive energy consumption (CEC) for comparison. Among typical MSW disposal methods such as combustion, composting, and landfilling, landfilling has the minimum CEC value. Installing an integrated treatment plant is the recommended MSW management method because of its lower CEC. Furthermore, this method is used to ensure process centralization. In landfill sites, a positive linear correlation was observed between the CEC and contaminant removal ratios when emitted pollutants have a certain weight coefficient. The process should utilize the minimum CEC value of 5.3702 kgce/t MSW and consider energy consumption, energy recovery, MSW components, and the equivalent of carbon dioxide emissions.     

An assessment of operations of oil-exporting countries in terms of energy consumption and carbon dioxide emissions

Energy consumption and carbon dioxide emissions from 16 oil-exporting countries are studied using Data Envelopment Analysis using indicators representing economic growth, energy consumption and emissions. The analysis for 1996 shows that Norway, Gabon and Nigeria are efficient and that Russia is inefficient. Malmquist Productivity Index analysis shows that there is progress in achieving higher values of GDP and non-fossil fuel consumption and in achieving lower values of fossil fuel consumption and carbon emissions in the year 1996 when compared with 1992 for Norway, Russia, Mexico, Algeria, Libya, Gabon and Oman.     

Carbon dioxide emissions,output, and energy consumption categories in Algeria

This study examines the relation between CO₂ emissions, income, non-renewable, and renewable energy consumption in Algeria during the period extending from 1980 to 2011. Our work gives particular attention to the validity of environmental Kuznets curve (EKC) hypothesis. The autoregressive distributed lag (ARDL) with break point method outcome demonstrates the positive effect of non-renewable type of energy on CO₂ emissions consumption. On the contrary, the results reveal an insignificant effect of renewable energy on environment improvement. Moreover, the results accept the existence of EKC hypothesis but the highest gross domestic product value in logarithm scale of our data is inferior to the estimated turning point. Consequently, policy-makers in Algeria should expand the ratio of renewable energy and should decrease the quota of non-renewable energy consumption.     

Emission reductions from woody biomass waste for energy as an alternative to open burning

Woody biomass waste is generated throughout California from forest management, hazardous fuel reduction, and agricultural operations. Open pile burning in the vicinity of generation is frequently the only economic disposal option. A framework is developed to quantify air emissions reductions for projects that alternatively utilize biomass waste as fuel for energy production. A demonstration project was conducted involving the grinding and 97-km one-way transport of 6096 bone-dry metric tons (BDT) of mixed conifer forest slash in the Sierra Nevada foothills for use as fuel in a biomass power cogeneration facility. Compared with the traditional open pile burning method of disposal for the forest harvest slash, utilization of the slash for fuel reduced particulate matter (PM) emissions by 98% (6 kg PM/BDT biomass), nitrogen oxides (NOx) by 54% (1.6 kg NOx/BDT), nonmethane volatile organics (NMOCs) by 99% (4.7 kg NMOCs/BDT), carbon monoxide (CO) by 97% (58 kg CO/BDT), and carbon dioxide equivalents (CO2e) by 17% (0.38 t CO2e/BDT). Emission contributions from biomass processing and transport operations are negligible. CO2e benefits are dependent on the emission characteristics of the displaced marginal electricity supply. Monetization of emissions reductions will assist with fuel sourcing activities and the conduct of biomass energy projects.     

The impact of environment degrading factors and remittances on health expenditure: an asymmetric ARDL and dynamic simulated ARDL approach

This paper investigates the impact of CO₂ emissions, air pollution (PM2.5) exposure, foreign remittances, energy consumption, renewable energy consumption, trade openness, and gross domestic product per capita on health expenditure in a panel of the 27 highest emitting countries from 2000 to 2019. Focusing on objectives, panel ARDL, and dynamic simulated ARDL models are used to examine the short-run and long-run impact of the variables on health expenditure. An asymmetric or nonlinear ARDL model is used to test the asymmetric effect of CO₂ emissions, air pollution exposure, and foreign remittance inflows on health expenditure. The results show that environment-degrading factors, remittances, and GDP per capita significantly impact health expenditure. There is an asymmetric effect of remittances, CO₂ emissions, and air pollution (PM2.5) exposure on health expenditure. Based on the results, the study suggests policymakers should make policies regarding environment-degrading elements as these factors cause huge increases in health spending in a country. Consumption of renewable energy helps reduce health expenditure as it does not cause environmental degradation, irrespective of other forms of energy, and it is suggested that policies relating to foreign remittance inflows should be encouraged and made efficient.

     

Does energy consumption contribute to environmental pollutants? evidence from SAARC countries

The objective of the study is to examine the causal relationship between energy consumption and environmental pollutants in selected South Asian Association for Regional Cooperation (SAARC) countries, namely, Bangladesh, India, Nepal, Pakistan, and Srilanka, over the period of 1975–2011. The results indicate that energy consumption acts as an important driver to increase environmental pollutants in SAARC countries. Granger causality runs from energy consumption to environmental pollutants, but not vice versa, except carbon dioxide (CO₂) emissions in Nepal where there exists a bidirectional causality between CO₂ and energy consumption. Methane emissions in Bangladesh, Pakistan, and Srilanka and extreme temperature in India and Srilanka do not Granger cause energy consumption via both routes, which holds neutrality hypothesis. Variance decomposition analysis shows that among all the environmental indicators, CO₂ in Bangladesh and Nepal exerts the largest contribution to changes in electric power consumption. Average precipitation in India, methane emissions in Pakistan, and extreme temperature in Srilanka exert the largest contribution.     

Roadmap for climate alliance economies to vision 2030: retrospect and lessons

The United Nations Climate Conference 25, held in December 2019, reached a significant agreement against implementing the Paris agreement come 2020. Bound by the contract, 189 countries who are party to the deal agreed to constrain worldwide temperature to ascend to 1.5° Celsius. To this end, the present study attempts to investigate the readiness of selected countries in the European Union to implement the agreement, which will better the quality of the global environment. In line with this, this study appraises the connection between economic growth, renewable and non-renewable energy consumption, on emissions in 11 countries in the European Union from 1990 to 2016. The study utilises the Pooled Mean Group-Auto Regressive Distributed Lag (PMG-ARDL) model estimator and Dumitrescu and Hurlin Panel Causality analysis to analyse the long-run and short-run impact and direction of causality among these factors, respectively. The long-run study's empirical results show a U-shaped Environmental Kuznets Curve (EKC) and a negative connection between renewable energy use and emissions in the EU-11 countries. In the short-run, non-renewable energy use worsens CO₂ emissions while renewable energy use leads to a fall in emissions. Similarly, causality tests show a feedback mechanism between emissions and renewable energy use and between non-renewable energy and renewable use. Also, there is unidirectional causality from income to CO₂ emissions, non-renewable energy use to CO₂ emissions. The investigation recommends an expanded proportion of renewable energy sources in the EU countries’ energy mix to cut down on emissions.

     

Do renewable energies contribute to enhancing environmental quality in Eastern Africa?

East Africa has enormous renewable energy potential, but only a small portion of it has been exploited, and little is known on its role in improving environmental quality. Thus, this study empirically examines the impact of renewable energy on the environment using ecological footprint (EF; positive indicator) and CO₂ emissions (negative indicator) as proxy indicators for environmental quality in a panel of ten East African countries from 1990 to 2015. These indicators were chosen due to their potential impact in the environment. The work used the pooled mean group (PMG) as the main panel estimator to determine the impact while controlling non-renewable energy consumption, GDP per capita, and foreign direct investment (FDI). PMG has been used as it forces the long-run coefficients to be equal across all panel groups. The findings show that in the long run, there is a significant negative relationship between CO₂ emissions and renewable energy consumption, as well as a significant positive relationship (with a low impact) between EF and renewable energy consumption, suggesting that renewable energy use enhances the area’s environmental quality. Also, results indicate that non-renewable energy use degrades environmental quality in both metrics, whereas GDP degrades environmental quality through CO₂ emissions and improves environmental quality through EF. This requires East African countries to focus a higher emphasis on accessible renewable energy sources to achieve quick and sustainable economic growth and minimize environmental effects. To accomplish this, strategic policies and legislation, as well as the promotion of green technology, are required.

     

Assessing energy, environmental, and economic tradeoffs in intermodal freight transportation

This paper presents an energy and environmental network analysis model to explore tradeoffs associated with freight transport. The geospatial model uses an intermodal network built by the authors to connect various modes (rail, road, water) via intermodal terminals. Routes along the network are characterized not only by temporal and distance attributes, but also by cost, energy, and emissions attributes (including emissions of carbon dioxide, particulate matter, sulfur oxides, volatile organic compounds, and oxides of nitrogen). Decision-makers can use the model to explore tradeoffs among alternative route selection across different modal combinations, and to identify optimal routes for objectives that feature energy and environmental parameters (e.g., minimize carbon dioxide emissions). The model is demonstrated with three case studies of freight transport along the U.S. eastern seaboard.     

The relationship between renewable energy consumption,carbon emissions,output, and export in industrial and agricultural sectors: evidence from China

Environmental Science and Pollution Research - This paper examines the long-term and short-term relationships between renewable energy consumption, output and export, and CO2 emissions in China...     

Development of a local carbon dioxide emissions inventory based on energy demand and waste production

This paper describes the study that led to the development of a carbon dioxide emissions matrix for the Oeiras municipality, one of the largest Portuguese municipalities, located in the metropolitan area of Lisbon. This matrix takes into account the greenhouse gas (GHG) emissions due to an increase of electricity demand in buildings as well as solid and liquid wastes treatment from the domestic and services sectors. Using emission factors that were calculated from the relationship between the electricity produced and amount of treated wastes, the GHC emissions in the Oeiras municipality were estimated for a time series of 6 yr (1998-2003). The obtained results showed that the electricity sector accounts for approximately 75% of the municipal emissions in 2003. This study was developed to obtain tools to base options and actions to be undertaken by local authorities such as energy planning and also public information.