Global Carbon Emissions Research Articles

Embodied carbon emissions generated by international trade of China's light industry sector based on global supply chains perspective

Accurate measurement of the embodied carbon emissions (ECE) generated by international trade is the basis for formulating fair and objective global carbon emission control strategies. This paper proposed an improved multi-regional input-output model and applied it to analyze production and consumption activities related to China's light industry sector based on its position within the global supply chain. It was found that manufacturing of light industry general equipment was the most important contributor to increased ECE, and 13 of China's 16 light industries for which data were available were a net carbon sink generated by international trade. Further, it was also revealed that China received a net transfer of carbon emissions from 12 countries, such as Indonesia, South Korea and Japan. China, as an exporter of carbon emissions, was also responsible for increasing the ECE generated by the international trade of China's light industry sector in 27 countries. Such findings provide an empirical basis for revised international trade strategies and policies to improve energy conservation and reduce carbon emissions.

Carbonic Anhydrase-Embedded Hydrogen-Bonded Organic Frameworks Coating for Facilitated Offshore CO2 Fixation.

Exhausted emission of carbon dioxide (CO2 ) from ships or offshore platforms has become one of the major contributors to global carbon emissions. Enzymes such as carbonic anhydrase (CA) have been widely used for CO2 mineralization because of their high catalytic rate. However, CA in seawater is easy to inactivate and difficult to reuse. Immobilization would be a feasible solution to address the stability issue, which, however, may cause an increase of internal diffusion resistance and reduced catalytic activity. In this regard, design of high-performance biocatalysts for acquiring high catalytic activity and stability of CA is highly desirable. Herein, a monolithic catalyst of Filler-CA@Lys-HOF-1 (FCLH) was prepared by chemical sorption of CA on the surface of the Filler followed by the coating of Lys-HOF-1. The highest catalytic activity of FCLH was obtained by regulating the amount of HOF-1 monomer added. Due to the protection of Lys-HOF-1, the FCLH showed good tolerance against acidity and salinity, which could retain about 80.2 % of the original activity after 9 h incubation in simulated seawater. The catalytic activity of FCLH could retain 85.4 % of the initial activity after 10 cycles. Hopefully, our study can provide a promising biocatalyst for CO2 mineralization, which may drive down carbon emissions when used for CO2 capture and conversion on offshore platforms.

The water, land, and carbon intensity of electricity production: The case of South Africa

Electricity production has a significant impact on the Water-Energy-Food nexus sectors as it requires substantial amounts of water and land, whilst also being a primary polluter of these resources. In addition, electricity production is a key contributor to global carbon emissions. With electricity production predicted to increase by over 50% by 2050, the impact of electricity production on water and land resources, as well as on carbon emissions, will need to be significantly reduced. This is particularly important in countries facing water, energy, and food scarcity and insecurity, such as South Africa. This paper therefore investigates the impact of electricity production on the Water-Energy-Food nexus sectors and on carbon emissions in South Africa. To do this, we conduct a lifecycle assessment of the water and land required for electricity production, as well as its carbon emissions in South Africa, by electricity source, and under key scenarios. The results from the Integrated Resource Plan 2030 scenario show that despite a 34% increase in electricity production targeted from 2018 to 2030 in South Africa, the water and land requirements, and the carbon emissions of electricity production would decrease by 29%, 9%, and 5.5%, respectively. Compared to the Business-as-Usual 2030 scenario, it was shown that the water and land requirements and carbon emissions of electricity production would be 55.5%, 42.6%, and 41.5% lower in the Integrated Resource Plan 2030 scenario, respectively. Overall, the results show that to reduce the impact of electricity production on the Water-Energy-Food nexus sectors and on carbon emissions, switching away from fossil fuels (particularly coal), and promoting the use of non-hydro and non-biomass renewables is required.

Upcycling Chips‐Bags for Passive Daytime Cooling

AbstractPlastic pollution has caused numerous environmental issues in recent decades. As one of the most commonly used packaging materials, aluminum‐plastic laminates (APL) are particularly challenging for recycling purposes due to their sophisticated materials components. This work reveals a new strategy to upcycle such post‐consumer APL packaging waste, e.g., chips‐bags, for passive daytime cooling applications. This opens an attractive route to reuse APLs while at the same time reducing global energy consumption and carbon emissions. The mirror‐like appearance of the APLs possesses a strong solar reflection, up to 86%. By coating, this reflective layer of the APL waste with a high emissive polydimethylsiloxane layer, a simple but effective passive daytime cooling foil is constructed, which shows promising passive cooling performance theoretically and practically. More importantly, the passive cooling foil based on APL waste is flexible and can be applied to any target object, protecting it from harsh sunlight. The low‐cost APL waste‐based passive cooling foil proposed in this work will significantly contribute to both energy and environmental issues that humans face today.

Demand response model by locational marginal electricity–carbon price considering wind power uncertainty and energy storage systems

With the increasing prominence of global carbon emissions, how to achieve carbon emission reduction in power systems is an urgent issue. Early research introduced carbon cost in the objective functions or constraints in an optimization model. However, the carbon cost cannot account for the time-varying carbon emissions caused by load electricity consumption. To address this challenge, this paper proposes a demand response (DR) program based on the locational marginal prices on both electricity consumption and carbon emission to reshape the load consumption pattern, which guide the load from both “electricity perspective” and “carbon perspective”. This model can reduce the carbon emissions of the power system while considering the economics of power purchase and the traditional DR to peak load shifting. Meanwhile, historical data fitting, Monte Carlo sampling and scenario reduction techniques are used to take full account of wind power uncertainties. The energy storage (ES) systems are introduced to simultaneously arbitrage from both electricity and carbon markets by appropriate charging strategies. The simulation results using PJM 5-bus system show that the locational marginal electricity–carbon price proposed in this paper can reduce the carbon emissions of the power system while ensuring an economic operation. By adding the carbon emission factor to the price, the load demand not only follows the fluctuation of electricity price, but also shows the trend of following the change of carbon emission.

A chaotic local search-based LSHADE with enhanced memory storage mechanism for wind farm layout optimization

The search for clean energy alternatives to fossil fuels has been a major effort by researchers all over the world. Wind energy is one of the most optimal choices because of its cleanliness and renewability. However, the existence of the wake effect leads to a decrease in conversion efficiency. Finding the best wind turbine layout has become an important factor in the wind power generation system. Inspired by the excellent optimization capability of meta-heuristic algorithms, they are increasingly applied to solve complex constraints and design objectives in the wind farm layout optimization problems. It is reported that LSHADE, which is an advanced variant of differential evolution, provides a more efficient configuration of wind turbines than other meta-heuristic algorithms. This motivates us to conduct research in this direction and design an effective meta-heuristic algorithm with a chaotic local search strategy and an enhanced memory storage mechanism, which contributes to the reduction of global carbon emissions. The proposed new algorithm is called CLSHADE. The validity of the proposed algorithm is verified by the simulation of different constraints and wind field distribution profiles. Compared to four state-of-the-art meta-heuristic algorithms, the average conversion rate of the proposed algorithm is 92.87%, 89.13%, and 96.86% for three wind distribution profiles, respectively. The results show that the proposed algorithm has superiorities and effectiveness in wind farm layout optimization.

Life cycle carbon emission assessment of large-span steel structures: A case study

Buildings take up a significant part of global carbon emissions and are a major contributor to the climate crisis. Large-span steel structures usually consume more materials, need more complex construction processes, and thus have a larger environmental impact. This study presents a comparative analysis of the life cycle carbon emissions of three typical large-span steel structures, i.e., a cable dome, a reticulated shell, and a suspendome, based on a design case. A tiered hybrid method using the process-based life cycle assessment for the processes with emission factors and using input–output-based life cycle assessment for the processes without emission factors is proposed to assess the life cycle carbon emissions. Comparisons on the carbon emissions of the three structures reveal that the cable dome is the best of the three, having the lowest steel consumption and the lowest carbon emissions. Although the component production phase appears to contribute most of the total emissions, the construction phase is also of considerable importance in alleviating the present emission pressure, especially for the cable dome and suspendome. Further analysis shows that carbon emissions of large-span steel structures are not simply linearly related to steel consumption and need to be considered as a separate design objective. This study provides a useful reference for life cycle carbon emission assessment and low-carbon design of large-span steel structures.

A green route for hydrogen production from alkaline thermal treatment (ATT) of biomass with carbon storage

Hydrogen, a green energy carrier, is one of the most promising energy sources. However, it is currently mainly produced from depleting fossil fuels with high carbon emissions, which has serious negative effects on the economy and environment. To address this issue, sustainable hydrogen production from bio-energy with carbon capture and storage (HyBECCS) is an ideal technology to reduce global carbon emissions while meeting energy demand. This review presents an overview of the latest progress in alkaline thermal treatment (ATT) of biomass for hydrogen production with carbon storage, especially focusing on the technical characteristics and related challenges from an industrial application perspective. Additionally, the roles of alkali and catalyst in the ATT process are critically discussed, and several aspects that have great influences on the ATT process, such as biomass types, reaction parameters, and reactors, are expounded. Finally, the potential solutions to the general challenges and obstacles to the future industrial-scale application of ATT of biomass for hydrogen production are proposed.

A biotechnological roadmap for decarbonization systems combined into bioenergy production: Prelude of environmental life-cycle assessment

Decarbonization has become a critical issue in recent years due to rising energy demands and diminishing oil resources. Decarbonization systems based on biotechnology have proven to be a cost-effective and environmentally benign technique of lowering carbon emissions. Bioenergy generation is an environmentally friendly technique for mitigating climate change in the energy industry, and it is predicted to play an important role in lowering global carbon emissions. This review essentially provides a new perspective on the unique biotechnological approaches and strategies based decarbonization pathways. Furthermore, the application of genetically engineered microbes in CO2 biomitigation and energy generation is particularly emphasized. The production of biohydrogen and biomethane via anaerobic digestion techniques has been highlighted in the perspective. In this review, role of microorganisms in bioconversion of CO2 into different types of bioproducts such as biochemical, biopolymers, biosolvents and biosurfactant was summarized. The current analysis, which includes an in-depth discussion of a biotechnology-based roadmap for the bioeconomy, provides a clear picture of sustainability, forthcoming challenges, and perspectives.

Feasibility Study of Nuclear Power Included in Carbon Trading Market: A Case Study of China's Carbon Market

As an innovative economic and clean source of energy, now nuclear power is the most worthy of large-scale development in the world. Especially in China, the development of nuclear power is not only related to China's energy security, but also of great significance to economic development and international status. Mature and stable carbon emission market is also very important for the implementation of new energy technology. Therefore whenever it comes to carbon trading, as a derivative means for countries in the world to participate in global carbon emission control, it has developed rapidly in China in recent years. Through theoretical analysis and sample data analysis, this paper studies current policies and historical sources, finds out the possible mechanism for nuclear power to enter the carbon trading market, and describes the economic benefits of the combination of nuclear power and carbon trading market. The results show that there is a correlation and causality between nuclear power and other power generation methods and carbon market, and there is a large profit space when carbon trading is included. Nuclear power has potential value for inclusion in the carbon market.

4E analysis and tri-dimensional optimization of a hybrid energy system based on biogas from the digester and high-efficiency fuel cell: An attempt to reach sustainability with decreased emission and increased efficiency

Scientists and researchers have made numerous efforts to reduce global carbon emissions. One of the greatest methods to reach this goal is using renewable energies, especially benefiting from biomass, because of their higher efficiency and lower GHG emissions. In this regard, this paper represents a fuel cell based on biogas fuel, in which the city sludge is initially treated and then fed to a digester. The gas is cleaned and put into the fuel cell for power generation and heating. The system has superiority over other biogas-fed SOFC schemes over its better installment of subsystems. The system is analyzed from technical and environmental aspects, and parametric sensitivity is carried out. Also, cooling is generated from the waste heat to minimize the effects of environmental pollution. It is exhibited that fuel utilization factor, stack temperature, and gas composition seriously affect system performance. Finally, the optimization is conducted, and the best solution point is found with an effectiveness of 56.2%, emission of 0.021 kg/kWh, and a cost of 0.05472 $/kWh.

Global Warming Research Based on GA-BP Neural Network Model

Since the industrial revolution, global carbon emissions have continued to increase, and after entering the 21st century, the trend of global warming has become more and more obvious. This paper first use the collected 10-year monthly average temperature data and divide them into two groups: 2012.3~2022.2 and 2022.3~2022.10, then conduct the Mann-Whitney U test, and find that the temperature increase in March 2022 did not increase significantly; then we three models are established to predict the future global temperature, the first model is ARIMA, the second model is BP neural network, and the third model is GA-BP neural network. Three models are used to predict the time when the future temperature will reach 20°C, ARIMA predicts the time is 2050, BP is 2046, and GA-BP is 2045. Finally, this paper use MAE, MAPE, and RMSE to evaluate the accuracy of the model, and find that GA-BP has the highest accuracy, followed by BP, and ARIMA is the worst.

The impact of the COVID-19 pandemic on global trade-embodied carbon emissions

We evaluate the response of global supply chains to carbon emissions through compiling multi-regional input-output (MRIO) models for import and export shocks in 14 countries/territories dominated by the COVID-19 crisis. Instead of traditional production-based inventories, we achieve CO2 emissions inventories based on intermediate inputs and final consumption to analyze the connected environmental impacts. In addition, we adopt the available data up to date to construct inventories of carbon emissions involved in imports and exports from different sectors. The results show that global carbon emissions could be decreased by 6.01% during the COVID-19, while export carbon emissions remained basically unchanged. As a result, imported carbon emissions fell by 5.2%, with the energy products sector most affected by the pandemic. Transport sector witnessed 18.42% carbon emission reduction. The impact of developing countries with a large proportion of resource-based industries is comparatively higher than that of developed countries with the technological advantage. International trade plays a crucial role in the choice of supply chain partners to control carbon emissions. Building a sustainable supply chain and reducing the “trade carbon deficit” between countries/regions requires the coordination of all departments of each country/region to promote the trade of energy-saving products, environmental protection services and environmental services.

Social media data shed light on air-conditioning interest of heat-vulnerable regions and sociodemographic groups

Cooling homes with air conditioners is a vital adaptation approach, but the wider adoption of air conditioners can increase hydrofluorocarbon emissions that have high global warming potential and carbon emissions as a result of more fossil energy consumption. The scale and scope of future cooling demand worldwide are, however, uncertain because the extent and drivers of air-conditioning adoption remain unclear. Here, using 2021 and 2022 Facebook and Instagram data from 113 countries, we investigate the usability of social media advertising data to address these data gaps in relation to the drivers of air-conditioning adoption. We find that social media data might represent air-conditioning purchasing trends. Globally, parents of small children and middle-aged, highly educated married or cohabiting males tend to express greater interest in air-conditioning adoption. In regions with high heat vulnerability yet little empirical data on cooling demand (e.g., the Middle East and North Africa), these sociodemographic factors play a more prominent role. These findings can strengthen our understanding of future cooling demand for more sustainable cooling management.

Role of technology learning in the decarbonization of the iron and steel sector: An energy system approach using a global-scale optimization model

The iron and steel sector, characterized by fossil fuel-driven processes is one of the most difficult to decarbonize and a significant source of greenhouse gas emissions. Various new technologies promise to change this, but their development is highly uncertain. This paper aims to analyze the prospects of key low-carbon technologies in the sector, focusing on the impact of technology learning, in the light of the uncertainty related to the learning rate. An optimization energy system model was used with an iterative learning formulation, adopting different learning assumptions. The results show that learning may have only a minor impact in the short and medium term, reducing global carbon emissions of the sector by 3% (at most) in 2050, compared to a non-learning scenario. In the long term, high learning potentials for novel processes are important, leading to a market share of up to the 80% by the end of the century. The learning potential for Carbon Capture and Storage processes, however, plays no role in the simulations. Early investments and research and development can help unlock the full potential of the technologies, while more detailed studies should be performed to better understand the retrofitting impact in the shorter term.

Low-carbon electricity technology transformation in Chinese universities

Purpose With the growing climate problem, it has become a consensus to develop low-carbon technologies to reduce emissions. Electric industry is a major carbon-emitting industry, accounting for 35% of global carbon emissions. Universities, as an important patent application sector in China, promote their patent application and transformation to enhance Chinese technological innovation capability. This study aims to analyze low-carbon electricity technology transformation in Chinese universities. Design/methodology/approach This paper uses IncoPat to collect patent data. The trend of low-carbon electricity technology patent applications in Chinese universities, the status, patent technology distribution, patent transformation status and patent transformation path of valid patent is analyzed. Findings Low-carbon electricity technology in Chinese universities has been promoted, and the number of patents has shown rapid growth. Invention patents proportion is increasing, and the transformation has become increasingly active. Low-carbon electricity technology in Chinese universities is mainly concentrated in individual cooperative patent classification (CPC) classification numbers, and innovative technologies will be an important development for electric reduction. Originality/value This paper innovatively uses valid patents to study the development of low-carbon electricity technology in Chinese universities, and defines low-carbon technology patents by CPC patent classification system. A new attempt focuses on the development status and direction in low-carbon electricity technology in Chinese universities, and highlights the contribution of valid patents to patent value.

Small island nations can achieve food security benefits through climate-adaptive blue food governance by 2050

Small island nations are highly dependent on food from aquatic environments, or blue food, and vulnerable to climate change and global food market price volatility. By 2050, rising populations will demand more food through various protein sources, including from the sea. This study identifies which small island nations can improve food self-sufficiency from the sea by implementing tailored climate-adaptive fisheries governance strategies that adapt to shifting marine resources. We combined projections of seafood demand and local catch under different future scenarios of global carbon emissions and local adaptive fisheries management to estimate potential seafood surpluses or deficits from by 2050 for 31 small island nations worldwide. We find that adapting fisheries management every 10 years could mitigate even worst-case projections of climate change impacts on locally available seafood, building a seafood surplus by 2050 in the Seychelles, Maldives, Cabo Verde, Bahamas, Antigua and Barbuda, Kiribati, PNG, Fiji, FSM, Tuvalu, and Marshall Islands. Strategic financial and capacity investments by the international community could help realize the full potential of food security from the sea for those nations. However, we project deficits in locally caught seafood by 2050 in Comoros, Sao Tome and Principe, Mauritius, Barbados, Dominican Republic, Cuba, Dominica, Jamaica, Grenada, St. Lucia, St. Vincent and the Grenadines, Trinidad and Tobago, Haiti, Palau, Samoa, Nauru, and the Solomon Islands, regardless of adapting fisheries management. For those nations, we recommend international collaboration that strengthens food security from sources other than the sea coupled with investments in locally sustainable aquaculture. Overall, we find that climate-adaptive fisheries management can benefit a range of the studied small island nations, by supporting both food security goals as well as economic goals of productive fisheries for international trade

Congestion effects of energy and capital in China's carbon emission reduction: Evidence from provincial levels

Global carbon emission control and resource conservation are important measures to realize sustainable development goals. There are few researches on carbon emissions from the perspective of congestion with the data envelopment analysis method. Congestion effects not only help us to reduce carbon emissions, but also achieve reasonable allocation of resources. This paper expands traditional congestion into undesirable congestion and desirable congestion, and both are divided into undesirable congestion of energy (capital) and desirable congestion of energy (capital) in 30 Chinese provinces with a two-stage model. So, purely technical inefficiency is separated from congestion, and energy and capital utilization can be analyzed simultaneously. The results show that: (1) China has a higher carbon emission reduction potential under natural disposability than that under managerial disposability. (2) The number of provinces with undesirable congestion of energy in the eastern region is small, while that with undesirable congestion of capital in the western region is small. (3) The number of provinces with desirable congestion increases. Desirable congestion of energy and capital is mainly concentrated in the eastern and central regions. Exploring the congestion effects of energy and capital will help China to achieve “dual carbon” targets and promote the environmental, social, and governance investment.

Assessing the Environmental Impact of Energy Efficiency and Renewable Energy: Evidence from Pakistan

Decreased environmental degradation has come to the forefront of policy debates and academic investigations. Using data from the Pakistan economy, which accounts for a substantial amount of global carbon emissions, investigate the effects of energy efficiency, human capital, renewable energy, and economic growth on the environment from 1990 to 2020. We reveal the influence of human capital by focusing on education investment to provide an understanding of the necessity of policy-making in Pakistan to prevent environmental deterioration. According to the findings, human capital expansion is substantially associated with lower CO2 emissions. Using the autoregressive distributed lag model (ARDL) estimate method, we present a complete analysis of the energy efficiency-environmental deterioration nexus. Energy efficiency, renewable energy, and human capital all are adversely associated and considerable influence on the environment. To attain a green environment, the study recommends strategies to boost energy efficiency, renewable energy, and human capital.

Spatiotemporal differentiation of carbon emission efficiency and influencing factors: From the perspective of 136 countries

The severity of the global climate issue is rising, primarily as a result of excessive carbon dioxide emissions. Climate change is a global problem. How to reduce carbon dioxide emissions while promoting social and economic development is a problem that all countries need to face. This study examines global carbon emission efficiency in order to make recommendations for comprehensively improving global low-carbon development level. We extend the research scale of carbon emission efficiency from countries, regions, economic belts and sectors to the world, which can show the differences of countries and has theoretical guiding significance for global low-carbon development. This study calculates the carbon emission efficiency for 136 countries from 2000 to 2019 using the Super-EBM model. The discussion that follows examines the temporal and spatial characteristics of carbon emissions efficiency in 136 countries from the perspective of countries, developed and developing countries, and regions. Finally, the Tobit model is used to comprehensively analyze the factors that affect carbon emission efficiency. The results show that: (1) There are great differences in carbon emission efficiency among countries and regions. Only a few countries reach the production frontier, mainly in Europe, which are Switzerland, Luxembourg, Iraq, Norway, Denmark and the United Kingdom. The carbon emission efficiency of most countries is not ideal, being mainly concentrated in Asia and Africa, and has not achieved significant improvement over time. Asia has the lowest carbon emission efficiency. Mongolia, Ukraine, Iran, Angola, Belarus and Uzbekistan are the key governance areas for global energy conservation and carbon emissions reduction. (2) Developed countries have the much higher average carbon emission efficiency than developing countries. Combined with the industrial development stages of developed and developing countries, this is in line with the environmental Kuznets curve (EKC) hypothesis. The average carbon emission efficiency gap between developing and developed countries shows a trend of “first narrowing and then widening”, which demonstrates that developing countries' reliance on energy input to boost their economies will improve carbon emission efficiency, but only temporarily. (3) Urbanization level, foreign trade and proportion of renewable energy effectively improve the carbon emission efficiency, while industrial structure and proportion of electricity users have an inhibitory effect on the carbon emission efficiency. Global low-carbon development should be hastened by strengthening international cooperation, optimizing industrial structure, promoting urbanization and foreign trade, and adjusting the energy structure.