Cut Carbon Emissions Research Articles

For better or for worse? On the economic and ecologic value of industrial demand side management in constrained electricity grids

Electricity systems are in dire need to scale up volatile decentralized renewable electricity supply (RES), reducing the dependency on fossil fuels and drastically cutting carbon emissions. Industrial demand side management (DSM) is a key enabler of the energy transition, as it allows to align large shares of electricity consumption with (renewable) supply. We present a short-term market model to evaluate the economic value (i.e., reduced system costs) and ecologic value (i.e., reduced carbon emissions) of industrial DSM within a constrained electricity grid, incorporating conventional electricity supply (flexibility) and RES. A model evaluation yields four key findings: (1) Grid-capacity constraints determine whether and to what extent industrial DSM may contribute economic and ecologic value. (2) Both the economic and ecologic value of industrial DSM are determined by the location within a capacity-constrained electricity grid. (3) DSM might even increase carbon emissions depending on local merit-orders. (4) Carbon emission pricing may resolve a potential conflict between ecologic and economic DSM-value maximization. Based on these findings, energy policy should (i) establish an electricity market design that provides sufficient local price signals for industrial DSM and (ii) ensure that local merit-orders incentivize industrial DSM to contribute both economic and ecologic value based on appropriate carbon prices.

How does financial decentralization synergies carbon reduction and pollution control in China?

This study looks at how carbon reduction, pollution management, and monetary decentralization in China all work together for a win-win situation. Since China is the most significant contributor to global warming, the country must implement policies to cut carbon emissions and curb pollution. One possible answer is financial decentralization, delegating federal financial responsibilities, and decisions to state and regional governments. The study used the weighted matrix analysis technique, LM matrix analysis technique, and ARDL short-run and long-run analysis estimates. However, the degree to which it will help China reduce carbon emissions and regulate pollution is unclear. This study takes a multifaceted approach to the investigation of this problem. Determining the efficacy of financial decentralization in addressing environmental concerns and drawing policy implications for China's environmental governance framework requires investigating the drivers of this trend and the mechanisms through which it operates. We perform a comprehensive empirical analysis to examine the results of using Chinese data from 1999 to 2019. This study's results provide new information to the literature by showcasing the power of fiscal decentralization in propelling environmentally sound policies in China. Central policy takeaways from the report include decentralizing financial authority to local governments, encouraging cooperation across multiple tiers of government, and setting up effective systems for monitoring and enforcing compliance. These policy suggestions can help China decrease carbon emissions and regulate pollution more efficiently, paving the way to better environmental results and a more sustainable future.

Harnessing the power of cow dung: Exploring the environmental, energy, and economic potential of biogas production in Indonesia

In countries that produce cattle, like Indonesia, improper management of cow dung is an issue. Biogas production had previously been regarded as the most advantageous method of digesting cow dung. This study examines the energy, economic, and environmental advantages of biogas produced from cow dung if it were to replace coal-powered electricity and LPG in Indonesia. Additionally, the slurry created as a byproduct is used in place of urea as a fertilizer. Benefit calculations begin at the household level and progress to the village level and eventually the national level. According to the study's findings, installing a biogas plant can cut carbon emissions by up to 6.78 tons of CO2/village/day. Each household has an annual savings capacity of IDR 725,000, and each village has a potential annual regional income of IDR 178,000,000. Almost 44% of the urea fertilizer can be replaced by the slurry and 13.2 million households can be served by the 18,177 GWh of electricity produced annually on a country level. The annual reductionable amount of LPG is 3.84 million tonnes and the annual savings to the state budget for LPG and fertilizer subsidies are IDR 40.3 trillion. By lessening the nation's reliance on fossil fuels, the use of biogas also helps to create energy security. Replacing trucks with other equipment for transporting cow dung, utilizing absorbers to boost methane concentrations, and improving electricity generator efficiency are the best approaches to maximizing the advantages of biogas.

Is historic working machinery up to 21st century sustainability demands or are we stuck in time?

The Science and Industry Museum have embarked on an ambitious decarbonisation project to become net zero by 2030. As part of this plan, the Power Hall Gallery (historic working engines) is undergoing a redevelopment to improve and conserve the historic listed building and run the engines more efficiently, cutting carbon emissions by 60 %. The historic engines pinpoint a pivotal moment in history; the birth of the steam engine, when fossil fuel ruled. In the 21st century we are looking for ways to be more sustainable. The Science and Industry Museum have been working with external specialists and researching more efficient ways of running the historic engines. Looking at adapting and applying a different approach to running the historic engines. Will they be able to withstand the change and adapt to 21st century demands? Can the Museum balance sustainability with the care and preservation of the historic collection?

Slag and Bagasse Ash: Potential Binders for Sustainable Rigid Pavement.

The current study tries to cut carbon emissions by using various waste materials in place of cement, including sugarcane bagasse ash (SCBA), ground granulated blast furnace slag (GGBFS), and ladle furnace slag (LFS), individually and in a combined form also, which has not been studied yet. In the same context, effort was made to utilize the maximum amount of waste materials as the replacement of cement to create a sustainable environment. Besides this, another aim is checking the performance of these waste materials as binding materials with respect to compressive strength for sustainable rigid pavement construction without activating them or using any activating solution. For this purpose, the compressive strength test is done for GGBFS, LFS, and SCBA, and later on, the artificial neural network (ANN) technique is also used to check the novelty of results in a broad way. For the same purpose, M40 grade concrete was made by incorporating different selected waste materials in a varying proportion ranging from 0 to 35%. Based on the results obtained from the compressive strength test for different curing periods, i.e., 7, 14, and 28 days, it was observed that the GGBFS, LFS, and SCBA can be utilized individually up to 15%, respectively. Another observation made from the findings was that the use of LFS and SCBA in the individual form up to 20% was found to be possible as the maximum reduction in strength was found to be up to 2.63%. However, the cumulative impact of all these waste products was also examined. Based on the data, it was concluded that the best outcomes would arise from using these additives in combination to replace cement in the mix by up to 30% (i.e., without compromising the required characteristics of concrete), which will be proved as an aid to the environment and the society also. Besides this, the fluctuation in the compressive strength value of concrete mixes after integrating various waste materials was also examined in order to construct a model using the ANN approach. The model's outcomes suggest that the ANN model does a good job of forecasting the compressive strength of concrete.

Innovation city and low-carbon future: a quasinatural experiment from China.

Using the difference-in-difference model and panel data from 283 Chinese cities from 2006 to 2019, this study assesses the effect on CO2 emissions of an innovative city pilot policy and analyzes its mechanism using the mediation effect model. The findings demonstrate that the pilot policy significantly reduces urban carbon emissions overall, and this finding holds even after conducting several stability tests. Innovative pilot cities can cut carbon emissions by 11.5% compared to nonpilot cities and thus significantly impact carbon reduction. Reducing carbon emissions is possible through three mechanisms. These are the enrichment of cultural resources, the development of technological innovation levels, and the optimization of industrial structure. There is a significant lag in how the innovative city pilot policy affects this reduction. The emission reduction effects of innovative pilot policies on different pollution levels, regions, and cities of various sizes are heterogeneous. In the long run, the scope of pilot projects needs enlargement in an orderly manner, and specific policies should be implemented according to local conditions. Meanwhile, advanced technologies are required in cities of different scales to build innovative development mechanisms for carbon peaking and carbon neutrality, and environmental regulations should be strengthened to implement in urban areas the concept of green and sustainable ecological development.

Green innovation and low carbon emission in OECD economies: Sustainable energy technology role in carbon neutrality target

The rapid increase in global output has exacerbated global warming by increasing the ecological footprint through resource extraction and energy use. There has been a lot of debate about using green technologies to reduce the environmental impact of carbon footprint. Nations worldwide have vowed to cut carbon emissions through remedial measures to protect environmental quality. COP26′s target is a top priority for countries around the globe to achieve environmental sustainability. To attain economic and environmental efficiency in their production processes, many businesses employ the strategy or technique of environmental innovation in their production process that enables them to produce eco-friendly products. This study examines the effects of green innovation on CO2 emissions in the presence of renewable energies, carbon tax, and GDP. We use the quantile regression method, which simulates the relationship between several factors and the dependent variable's particular percentiles (or quantiles). The results show that eco-innovation, environmental related tax and renewable energies help abate the rising PCO2 emission of OECD countries. Policymakers and environmentalists will benefit from the findings of this study. To counteract environmental deterioration, green innovation and carbon taxation must be pursued by OECD countries.

Does the risk of oil and energy based resources extraction Hinder or Foster sustainable development?

Developed economies, particularly the United States, are rapidly developing technology and resources to cut carbon emissions to combat climate change and fulfill the COP27 target. Even though the literature addresses most environmental challenges in developed and developing nations. Nonetheless, the United States remained ignored in identifying the influence of renewables, financial risk, and natural resources on environmental quality. Therefore, it is the need of the time to empirically examine such nexus, the empirical results of which could help policymakers construct relevant and appropriate policies. This research looks at the influence of natural resources, renewable energy consumption, financial risk, and economic development on carbon emissions in the United States between 1989 and 2021. The empirical data for variables demonstrate valid cointegration but have non-linear distributional features. As a result, this study uses the unique approach of moment quantile regression to discover that economic growth is the biggest impediment to meeting the COP27 objective. On the other hand, natural resource exploitation, renewable energy use, and financial risk are all negatively related to carbon emissions. According to the data, the latter factors are the primary drivers of COP27's objective accomplishment. This report recommends sustainable resource exploitation and more investment in the renewable energy industry.

Wavelet Analysis of GPR Data for Belowground Mass Assessment of Sorghum Hybrid for Soil Carbon Sequestration

Among many agricultural practices proposed to cut carbon emissions in the next 30 years is the deposition of carbon in soils as plant matter. Adding rooting traits as part of a sequestration strategy would result in significantly increased carbon sequestration. Integrating these traits into production agriculture requires a belowground phenotyping method compatible with high-throughput breeding (i.e., rapid, inexpensive, reliable, and non-destructive). However, methods that fulfill these criteria currently do not exist. We hypothesized that ground-penetrating radar (GPR) could fill this need as a phenotypic selection tool. In this study, we employed a prototype GPR antenna array to scan and discriminate the root and rhizome mass of the perennial sorghum hybrid PSH09TX15. B-scan level time/discrete frequency analyses using continuous wavelet transform were utilized to extract features of interest that could be correlated to the biomass of the subsurface roots and rhizome. Time frequency analysis yielded strong correlations between radar features and belowground biomass (max R −0.91 for roots and −0.78 rhizomes, respectively) These results demonstrate that continued refinement of GPR data analysis workflows should yield an applicable phenotyping tool for breeding efforts in contexts where selection is otherwise impractical.

Does the synergy of the construction of high-speed railways and smart city pilot cut carbon emissions in Chinese cities?

The construction of high-speed railways and the smart city pilot (HSR-SCP) demonstrates the synergy of traditional and new infrastructure upgrades, which has a significant influence on the economic transition and green economic growth. However, little study has been conducted on the impact of HSR-SCP synergy on carbon emissions. Applying China's prefecture-level panel data, this paper, therefore, attempts to investigate the effect of HSR-SCP on carbon emissions and uncover its in-depth mechanism through the multi-period difference-in-differences model. Notably, an appropriate instrumental variable for HSR-SCP is introduced to address possible endogeneity. The main conclusions indicate that the construction of HSR-SCP plays an essential role in cutting carbon emissions, which is still valid after adopting the instrumental variable method and some robustness tests. Furthermore, green technology innovation plays a crucial intermediary role in that relationship. Finally, the carbon reduction effect of HSR-SCP is significant in Mid-Eastern China and cities with high population sizes and administrative levels, but not in other cities or regions. The research conclusions demonstrate the significant synergy of traditional and new infrastructure upgrades on carbon reduction and provide an empirical foundation for developing countries to realize low-carbon development through optimizing smart infrastructure and promoting green technology innovation.

Getting to net zero: Islington’s social housing stock

This paper describes the development of a detailed plan to get the social housing stock of the Borough of Islington in London, UK, to net zero carbon emissions. This stock is very diverse in form, age and construction, and includes houses, flats and maisonettes. A total of 4500 buildings containing some 33,300 dwellings were modelled using the 3DStock method. Six packages of measures combining fabric improvements, heat pumps and photovoltaic installations were evaluated for each dwelling individually, in terms of costs, the impacts on gas and electricity use, and predicted cuts in carbon emissions. The rollout of measures between 2020 and 2030 was modelled with a specially developed scenario tool, allowing the user to set different criteria and priorities. Fabric measures on their own were shown to achieve only a 13% cut in gas use on average. Heat pumps are the key to displacing gas use. With all measures combined and taking account of the predicted decarbonisation of the electricity supply, it is only possible to achieve an overall 70% cut in emissions by 2030. Policy relevance The development of a detailed practical plan of action is described: an applied case study with the close engagement of the local authority—not a theoretical desk exercise. Each dwelling in Islington’s housing stock was examined and measured separately. The modelling did not rely on ‘archetypes’ as in many such studies. Realistic retrofit options were analysed in each case, using current cost data from practitioners. The same approach could be applied directly to other London boroughs, and for local authorities outside the capital, although different costs and other local factors would apply. For readers outside the UK, the methodology and tools could serve as exemplars. The findings about the respective contributions of heat pumps, solar photovoltaics and fabric measures, and the effects of different priorities in the rollout of retrofits, have relevance for policymaking more generally at local and national levels.

How can a carbon tax benefit developing economies with informality? A CGE analysis for Côte d’Ivoire

ABSTRACT This study investigates how a carbon tax could reduce fiscal and economic distortions as well as cut carbon emissions in developing-country economies. A computable general equilibrium model is developed to analyze the economic impacts of a hypothetical carbon tax in Côte d’Ivoire, a country in Sub-Saharan Africa with large losses of tax revenues due to informality and leakage. The model represents informal as well as formal production activities. The analysis shows that the economic impacts of a carbon tax and the levels of CO2 reduction vary significantly among alternatives for recycling the carbon tax revenue. A carbon tax with revenues recycled to reduce the existing value-added tax would increase GDP and economic welfare. If the revenue is used to cut the existing tax on labour, the carbon tax would not only increase GDP but also induce the migration of workers from informal to formal activities. The analysis also shows that if energy producers are not excluded from carbon tax revenue recycling, the carbon emission reduction is significantly lower due to a rebound effect. A carbon tax with lump-sum transfers of revenues to households would be progressive as the revenue is equally transferred to all households, but it reduces economic output and does not help reduce informal economic activities.

Analyzing the Impact of Decarbonizing Residential Heating on the Electric Distribution Grid

Heating buildings using fossil fuels such as natural gas, propane and oil makes up a significant proportion of the aggregate carbon emissions every year. Because of this, there is a strong interest in decarbonizing residential heating systems using new technologies such as electric heat pumps. In this paper, we conduct a data-driven optimization study to analyze the potential of replacing gas heating with electric heat pumps to reduce CO 2 emission in a city-wide distribution grid. We conduct an in-depth analysis of gas consumption in the city and the resulting carbon emissions. We then present a flexible multi-objective optimization (MOO) framework that optimizes carbon emission reduction while also maximizing other aspects of the energy transition such as carbon-efficiency, and minimizing energy inefficiency in buildings. Our results show that replacing gas with electric heat pumps has the potential to cut carbon emissions by up to 81%. We also show that optimizing for other aspects such as carbon-efficiency and energy inefficiency introduces tradeoffs with carbon emission reduction that must be considered during transition. Finally, we present a detailed analysis of the implication of proposed transition strategies on the household energy consumption and utility bills, electric grid upgrades, and decarbonization policies. We compute the additional energy demand from electric heat pumps at the household as well as the transformer level and discuss how our results can inform decarbonization policies at city scale.

Green industrial transition: Leveraging environmental innovation and environmental tax to achieve carbon neutrality. Expanding on STRIPAT model

Anthropogenic global warming strategies on carbon mitigation are driven by encouraging green innovation and using carbon taxes, yet an empirical model to validate this is non-existing. Moreover, the existing stochastic effects by regression on population, wealth, and technology (STIRPAT) model has been found to lack policy tools on taxes and institutions that cut carbon emissions. This study amends the STIRPAT model with environmental technology, environmental taxes, and strong institutional frameworks to create a new model STIRPART(stochastic impacts by regression on population, affluence, regulation, and technology) to understand the factors impacting carbon pollution using the emerging 7 economies. Using data from 2000 to 2020, the Driscoll-Kraay fixed effects are employed in this analysis to conduct evidential tests of the impacts of environmental policies, eco-friendly innovations, and strong institutions. The outcomes indicate that environmental technology, environmental taxation, and institution quality decrease E7's carbon emissions by 0.170%, 0.080%, and 0.016%, respectively. It is recommended that E7 policymakers should adopt the STIRPART postulate as the theoretical basis for policies favoring environmental sustainability. The key contribution is the amendment of the STIRPAT model and the enhancement of the market-based mechanisms, such as patents, strong institutions, and carbon taxes, to enable environmental policy to be carried out sustainably and cost-effectively.

CO2 intensity of GDP, energy productivity and environmental degradation in Iceland: evidence from novel Fourier based estimators

ABSTRACT Iceland aims to achieve carbon neutrality by 2040 and to cut carbon emissions by 40% by 2030 under the Paris Agreement. Iceland’s major policy instrument for reaching its emissions reduction and carbon neutrality objectives is a Climate Action Plan, which was amended in 2020 and included 48 initiatives. Therefore, the research investigates the impact of carbon intensity, economic growth, globalization, and energy productivity on consumption-based emissions in Iceland from 1995Q1 to 2019Q4. The Fourier Autoregressive Distributed Lag Model (FARDL) is used in this study to investigate the ramifications of a long-term association. Long-run estimations demonstrate that Iceland’s environmental quality is deteriorating due to carbon intensity and economic development. It implies that increasing the carbon intensity and economic growth is environmentally damaging. Furthermore, economic expansion has a significant impact on environmental sustainability. Increased energy production also decreases consumption-based emissions, which contributes significantly to Iceland’s sustainable environment. Globalization has a positive and significant influence. A 1% rise in globalization, in particular, enhances consumption-based emissions over time. The finding is crucial for policy preferences and might be used to implement robust policy measures to address environmental challenges.

EPA seeks to dramatically cut carbon emissions from power plants

EPA seeks to dramatically cut carbon emissions from power plants

Intelligent Multi-Criteria Decision Support for Renovation Solutions for a Building Based on Emotion Recognition by Applying the COPRAS Method and BIM Integration

With accelerating climate change and the urgent need to cut carbon emissions, global focus has turned to the existing building stock and its renovation. Sustainable renovation helps to achieve better energy performance and gain wider sustainability benefits, such as increased value of a building, improved indoor and outdoor comfort, reduced carbon emissions, and the higher satisfaction and better emotional state of inhabitants. Numerous systems and tools have been developed worldwide to assist with decision making in the choice of preferred modernisation scenarios and alternatives. However, social aspects are often neglected in the existing systems, and emotions of inhabitants are rarely analysed. To close this gap, the present study proposes an innovative decision-making framework for sustainable renovation solutions, based on emotion recognition. The framework makes it possible to assess various renovation alternatives against sustainability criteria and real-time measurements of the emotional states of inhabitants. Based on the proposed framework, an intelligent multi-criteria decision support system was developed by integrating COPRAS and the facial action coding system, the method of automatic facial expression recognition, and the continuous calibration and participant methods. The system was tested in the case study of renovation solutions for a building located in Ukraine. The research results revealed that the proposed renovation solutions had a positive impact on the emotional state of inhabitants, especially when visual materials such as drawings were presented. Some case studies were analysed together with the application of decision system tools and building information modelling (BIM) subsystem integration as a multidiscipline application of various applied sciences for representation and data analysis. The authors of this research have been analysing human emotional, affective and physiological states for many years and collected over a billion of these data in Vilnius city during the H2020 ROCK, SAVAS and BIM4REN projects. Data acquired during measurements in Vilnius were used to determine correlations and trends for the case study. The proposed methodology and findings of the study can be useful for researchers who use the evaluation and analysis of human emotions when there is a need to choose appropriate renovation measures or find alternative solutions.

Review and modeling: Approach to low-carbonize the whole industry chains of integrated energy systems

Industries are undergoing low-carbon evolution with worldwide awareness of energy conservation. As the super key to processing it, integrated energy systems (IESs) are receiving more attention, in terms of cutting carbon emissions actively and passively. Until now, many well-established strategies have been proposed to low-carbonize IESs. However, issues still remain in implementing low-carbonization throughout the whole industry chain. In this context, critical technologies and available flexible resources at different levels of IESs, i.e., the transmission, distribution/district, and residential levels, are reviewed first in this paper. Then, flexible resources in the source, network, load, and storage are remodeled to minimize carbon emissions more directly. In this manner, CO2 in the whole industry chains of IESs can be marked and traced, which is named after the “all-carbon chain” here. Besides, as an original content of this paper, new technologies, i.e., CO2 flooding and Organic Rankine Cycle (ORC), get introductions for low-carbonizing IESs further. Last but not least, an actual large-scale IES is employed to verify the proposed approach from the transmission and distribution/district levels. It is concluded that the all-carbon chain is complex-less when applied in a bi-layer integration process and a weak-convex update formula also could ensure convergence (within 44 iterations). Besides, our approach helps to cut carbon emissions when compared with the traditional IES (by 50.61%) and two low-carbon IESs (by 18.37% and 12.09%). Moreover, our method makes IES enjoy a purposeful evolution for more functions of low-carbonization, source tracing, targeted evolution, and contribution quantification are covered.

Optimization of renewable energy supply for a carbon neutral society: Role of environmental regulations, sustainable finance, and financial innovation through the lens of game theory

Nations maximize green technologies and renewable energy to address climate change and reach sustainable development goals. As a result of the Paris Climate Agreement, several countries have made reducing or eliminating their carbon footprints a primary priority. Using a game theoretical perspective, this article analyses empirical data from 2011 to 2021 to determine the impact that renewable energy, environmental regulation, sustainable finance, and financial innovation will have on the ability to emerge from Asian nations in order to achieve a carbon‐neutral society. The cross‐section dependence, panel unit root, and augmented mean group tests confirmed the zero‐carbon environmental Kuznets curve hypothesis. As a result, it is observed that the availability of renewable energy, environmental regulations, sustainable finance, and financial innovation greatly cut carbon emissions and boosts national capabilities to reach the carbon neutrality target. The reduction of sectoral risks and carbon emissions, as well as achieving a sustainable and carbon‐neutral society. It would be facilitated by nations capitalizing on and reinforcing these variables and expanding investment in green recovery.

Does nuclear energy reduce carbon emissions despite using fuels and chemicals? Transition to clean energy and finance for green solutions

Green power conversion is the shift away from traditional fuels towards clean energy sources such as nuclear power plants, hydroelectric dams, wind farms, and solar panels. This research examines the impact of clean energy demand and green financing on reducing carbon emissions in 29 economies in Europe and Asia from 2007 to 2020. The study used a two-step differenced GMM estimator for the available data set spanning 2007 to 2020. The study found that rising demand for nuclear power helps to achieve a carbon-neutral agenda, but insufficient funding for renewable energy leads to higher carbon emissions. The research suggests increasing investment in nuclear energy and green financing can improve regional environmental quality. The study found a causal link between fuel imports, nuclear power and regional growth. It also determined that fuel imports, chemical use, green financing and the need for nuclear energy will likely impact regional environmental quality. The research recommends allocating more resources toward innovation to boost energy efficiency and expanding investment in renewable and nuclear energy production industries via green finance. The study also highlights the need to encourage the development of renewable energy sources to cut carbon emissions and establish a sustainable society.