Emission Trends Research Articles

Cycle-Life Curves Determination and Modelling of Commercially Available Electric Vehicle Batteries

In recent decades, there has been a growing concern about the trend of global emissions, and in particular those of the transport sector. In this context, the electric vehicle is a promising technology, with some barriers still to be overcome. Among these deficiencies everything related to storage technology is found. In this sense, lithium-ion batteries are one of the options to be considered, although it is necessary to continuously monitor the state of health. Cycle life vs DoD curves are very useful for characterizing profitability in any application that considers battery storage, as well as life cycle optimization studies. Cycle life refers to the number of charge-discharge cycles that a battery can provide before performance decreases to an extent that it cannot perform the required functions (e.g., 80% compared to a fresh one in electromobility applications). In this paper, a model for calculating the Cycle Life vs DoD curves is proposed, applied to a commercially available electric vehicle, the Renault Zoe. Modelling results show R squared coefficient of determinations above 0.9890.

Net-zero energy transition in ASEAN countries: The evolutionary model brings novel perspectives to the cooperative mechanism of climate governance

In an era marked by escalating climate change, the fragile ecological balance faces increasing strain. Whilst significant knowledge exists regarding the accumulation of carbon emission within the Association of Southeast Asian Nations, little is known about when and how countries could reach net-zero emission goal as agreed in Paris Agreement. For this purpose, our study examines the primary driving factors of carbon emission from 1990 to 2020 across the ten countries using the Logarithmic Mean Divisia Index model. We leverage the random forest model to explore the net-zero scenarios and the Autoregressive Integrated Moving Average approach to identify the evolutionary trajectories of carbon emission trends. Our findings underscore the imperative need for expediting decarbonization efforts, emphasizing the urgency for widespread adoption of clean technologies and substantial investment in green initiatives. Countries at similar stages of progress might establish a cooperation mechanism of clean energy base construction, energy storage allocation and policy formulation. These insights can help us better estimate future demand of clean energy, explore strategies for decarbonization, and inform historical commonalities of carbon emission growth.

Greenhouse gas emission flux (CO2, CH4, N2O) from marine shrimp (Litopenaeus vannamei) monoculture cultures in the Brazilian semi-arid region

Greenhouse gases (GHG) and their rising atmospheric concentrations have been one of the most important international subjects due to their huge impact on climate change (IPCC, 2022). Aquaculture is of crucial importance to the human food supply and nutrition since it is one of the major sectors providing animal protein, besides reducing the pressure on the fishery stocks from natural resources worldwide (Cai, Zhou, 2019; FAO, 2022). On the other hand, it represents a threat to the environment by generating waste. Thus, this research aims to evaluate the GHG flux dynamics in marine shrimp (Litopenaeus vannamei) monoculture cultures. The study was carried out in two aquaculture farms, both located in the Brazilian semi-arid region. In order to measure the production of greenhouse gases, three cultures of marine shrimp were monitored. The dynamics of the diffusive and ebullitive emission of CO2, CH4, and N2O were monitored in the three units during the daytime (6:00 AM) and nighttime (6:00 PM). The results showed the stocking density as the main regulator for ebullitive CO2 emissions. A decreasing trend in diffusive CO2 emissions was observed. Aeration played a crucial role in controlling the diffusive and ebullitive emissions of CH4 and N2O, effectively reducing their release. The diffusive CH4 emissions exceeded ebullitive emissions and the oxygen content suppressed the anoxic pathway for N2O, and the ponds acted as a sink for this gas. This research aims to evaluate the dynamics of greenhouse gas flow in marine shrimp (Litopenaeus vannamei) monoculture cultures in the Brazilian semi-arid region and to verify whether lower stocking densities emit less greenhouse gases when compared to higher densities.

Which EU Country Contributes Most to GHG Emissions in the LULUCF Sector Relative to Population and GDP?

Abstract In pursuit of climate neutrality, EU nations must collectively address the problem of greenhouse gas (GHG) emissions and air pollutants, which necessitates equitable economic strategies. However, the heterogeneous economic, social, and geographical profiles present hurdles in enacting a cohesive policy framework and realizing shared goals. Land use, land use change and forestry (LULUCF) sector play a crucial role in achieving the EU 2050 climate neutrality goal, as LULUCF is both a source and a sink for GHG emissions, it provides products like wood and biomass that help to reduce emissions in other sectors. This paper aims to compare GHG emissions of different EU countries by using targeted indicators related to per capita and to GDP per capita to enhance the analysis. The results reveal substantial differences in emissions in relation to population and GDP per capita between selected EU countries, even among countries with similar profiles, such as Estonia, Latvia, Lithuania. Notably, countries with lower GDP per capita and smaller population tend to have higher emission values, suggesting less efficiency in managing land use and forestry. The study highlights the need for multi-year data analysis to identify trends in emissions and removals within the LULUCF sector, considering the impacts of natural disasters and economic activities such as bark beetle outbreak or wood harvesting.

QUANTIFYING ROUGH FRACTURE BEHAVIORS IN GAS-BEARING COAL SEAM: A FULLY COUPLED FRACTAL ANALYSIS

In gas-bearing coal seam mining projects, the pivotal considerations encompass the assessment of gas migration, emission trends, and coal seam stability, which are crucial for ensuring both the safety and efficiency of the project. The accurate evaluation of the nonlinear evolution of the fracture network, acting as the primary conduit for gas migration and influenced by mining disturbances, coal seam stress, overlying strata pressure, and gas pressure, emerges as a key determinant in gauging coal seam stress and safety. To address the industry challenge of quantitatively assessing the complex behaviors of fracture networks during gas-bearing coal seam extraction, this study introduces a novel, interdisciplinary fractal analysis model. Drawing upon fractal theory for classical porous media, four fractal parameters capable of quantitatively characterizing the microscopic behaviors of fractures are proposed and defined as functions of permeability. Subsequently, the gas pressure in gas-bearing coal seams, coal seam deformation and stress, in-situ stress, overlying strata pressure, and adsorption–desorption effects are comprehensively coupled and applied to the classic gas-bearing coal seam at the Jianxin Coal Mine’s 4301 working face in Shaanxi, China. Upon the robust validation of the proposed model, the present computational results reveal: (1) the proposed micro-parameters adeptly characterize the number, roughness, tortuosity, and length of fractures in gas-bearing coal seams; (2) a larger fractal dimension of fractures leads to increased coal seam stress and strain, while the fractal dimensions of fracture tortuosity and roughness are inversely proportional to coal seam stress and strain; (3) these fractal parameters directly induce evolutionary changes in gas seepage behavior, leading to varying degrees of mechanical property evolution in the coal seam. When [Formula: see text] and [Formula: see text] increased from 1.2 to 1.8, the maximum change in coal seam deformation was 16.9% and 13.8%, respectively, and when [Formula: see text] increases from 0.03 to 0.12, the coal seam deformation changes by 15.1%. This represents a quantitative characterization unattainable by previously published coal seam analysis models, including mainstream fractal computation models.

Optimal Strategies for Climate Change Mitigation

This work explores methods to address climate change by applying optimization techniques in a top-down approach. A decision model is proposed to minimize temperature anomalies compared to pre-industrial levels between 2025 and 2100 by varying greenhouse gases (GHG), namely CO2 and CH4. Two objective functions are minimized. The first one considers the overall sum of the temperature anomalies by 2100, while the latter minimizes the temperature anomaly at the end of the century. Two different emission trends are assumed: a gradual (gaussian) fall in emissions or a fast (exponential) decline. The reduction of GHG emissions is constrained to a set of IPCC scenarios identified by assessing economic, social, and technological trends in the next decades. The uncertainty analysis of the decision problem solutions suggests that temperature anomalies can be limited to the range of 0.8–2°C.

Predicting the Risks of Greenhouse Gases at Raising Temperatures in Syria Using Artificial Intelligence Models

The research aimed to study the general trend of the evolution of greenhouse gas emissions in Syria during the period (1993-2022) and to predict the risks of greenhouse gas emissions to rising temperatures during the period (2023-2030). The research adopted the descriptive analytical method in estimating the equations of the general time trend of greenhouse gas emissions and calculating the annual growth rate for each of them during the studied period based on the statistics of the World Bank. The amount of gas emissions during the studied period was multi-layered to suit the nature of the data. The neural network used in prediction consisted of three layers: the input layer, the processing layer, and the output layer. The results of the research showed that there is a general trend of increasing temperatures at a rate of 0.16% annually, which is within the internationally permitted limits according to the Paris Agreement in 2015. The amount emitted of nitrous oxide gas occupied the highest relative importance in terms of the effect on temperature rise 100%, followed by the amount emitted of methane gas 94.1%. In contrast, the percentage of carbon dioxide emissions did not exceed 4.3% in the proposed model. The results of the prediction using the neural network model showed that the average temperatures during the coming period (2023-2030) will reach their maximum value in the year (2024) with an average of (14.87) degrees Celsius, with a relatively increasing annual growth rate of 0.07%.

Study on carbon emission driving factors and carbon peak forecasting in power sector of Shanxi province.

The realisation of the low-carbon transition of the energy system in resource-intensive regions, as embodied by Shanxi Province, depends on a thorough understanding of the factors impacting the power sector's carbon emissions and an accurate prediction of the peak trend. Because of this, the power industry's carbon emissions in Shanxi province are measured in this article from 1995 to 2020 using data from the Intergovernmental Panel on Climate Change (IPCC). To obtain a deeper understanding of the factors impacting carbon emissions in the power sector, factor decomposition is performed using the Logarithmic Mean Divisia Index (LMDI). Second, in order to precisely mine the relationship between variables and carbon emissions, the Sparrow Search Algorithm (SSA) aids in the optimisation of the Long Short-Term Memory (LSTM). In order to implement SSA-LSTM-based carbon peak prediction in the power industry, four development scenarios are finally built up. The findings indicate that: (1) There has been a fluctuating upward trend in Shanxi Province's total carbon emissions from the power industry between 1995 and 2020, with a cumulative growth of 372.10 percent. (2) The intensity of power consumption is the main factor restricting the rise of carbon emissions, contributing -65.19%, while the per capita secondary industry contribution factor, contributing 158.79%, is the main driver of the growth in emissions. (3) While the baseline scenario and the rapid development scenario fail to peak by 2030, the low carbon scenario and the green development scenario peak at 243,991,100 tonnes and 258,828,800 tonnes, respectively, in 2025 and 2028. (4) Based on the peak performance and the decomposition results, resource-intensive cities like Shanxi's power industry should concentrate on upgrading and strengthening the industrial structure, getting rid of obsolete production capacity, and encouraging the faster development of each factor in order to help the power sector reach peak carbon performance.

Contrasting trends of carbon emission from savanna and boreal forest fires during 1999–2022

AbstractBiomass burning (BB) as an important atmospheric carbon source has significant environmental and climatic influence. The frequent extreme BB cases in recent years have raised extensive concerns, yet the latest changes in BB emission on a global scale are not fully understood. Here, we systematically quantify the changes in BB carbon emission for 1999–2022 by fire types and on different scales based on the Global Fire Emissions Database with small fires (GFED4s) dataset. We find contrasting trends of savanna and boreal forest fires persistent over the study period, shaping the variation of global total BB carbon emission. The receding savanna fire drives a declining global BB carbon emission at −8 Tg C year−1 (−0.4% year−1) for 1999–2022, while an upturn of global carbon emission (5 Tg C year−1, 0.3% year−1) occurs in the recent decadal period (2008–2022) due to intensified boreal forest fires. The burned area decouples from carbon emission in terms of the changing tendency, as exhibited by the decreasing global burned area after 2008. Regionally, the fire carbon emission enhancement over the past 15 years (2008–2022) mainly comes from the boreal forests in northwestern North America, northeastern Siberia, and parts of the savanna area, all of which coincide with local climate change toward higher fire proneness. This study reveals a climate‐driven aggravation of the BB carbon emission, especially in high‐latitude boreal forests, and calls for attention to its potential impacts and effective fire management strategies.

Determinants of greenhouse gas emissions by Brazilian agricultural sector.

The agricultural sector is one of the most polluting economic activities, contributing significantly to greenhouse gas (GHGs) emissions. Brazil is one of the largest agricultural producers worldwide and plays a major role in reducing the environmental impact of this sector. Here, we aimed to determine the impact of the agricultural sector, with special attention to production, prices, and trade openness, on the short- and long-term GHGs emissions of Brazilian agriculture. Employing data from 1974 to 2019, we tested the cointegration of variables and compared the determinants of GHG emissions using Autoregressive Distributed Lag (ARDL) and Vector Error Correction Model (VECM) methods. Our results show a long-term equilibrium trend for Brazilian agricultural GHGs emissions, a result that correlates with emerging environmental compliance, and society demands the adoption of sustainable technologies, processes, and policies. In the short run, both cattle herds and Agricultural Added Value to GDP per capita showed an expected positive and significant contribution to GHGs emissions, while agricultural crop area demonstrated an inverse relationship. The trade openness index confirmed that foreign trade plays an important role in reducing GHGs emissions. The price index is not significant in our models. Both the private and public sectors have important roles in sustainable agriculture, especially in increasing system efficiency through the adoption of management and technologies that reduce GHG emissions levels.

Exploration of establishing a unified carbon accounting method in the field of public buildings

Under the background of low-carbon development, the construction of green public buildings is an inescapable responsibility and mission. At present, there are relatively few studies on carbon emission of public buildings in China and there is a lack of unified and standardized carbon accounting methods. Therefore, based on the domestic research status, this paper reviews the research progress and trend of carbon emission in public buildings. Sorting out the common accounting boundaries and accounting scope in the field of public buildings; By constructing the interactive accounting method framework of public buildings, the process and method of carbon accounting are sorted out. Various points for attention in the process of accounting are clarified from data acquisition，data management, accounting analysis and other aspects. This study provides a theoretical framework for carbon accounting in the field of public buildings and lays a foundation for establishing a unified carbon emission accounting method system in the field of green public buildings.

An overview on carbon emission accounting systems and method at home and abroad

Carbon emission accounting is the basic premise for accurately grasping the change trend of carbon emissions, effectively carrying out various carbon emission reduction work, and promoting the green transformation of economy. It is also an important basis for different levels of entities to implement emission reduction tasks and evaluate the completion effect. At present, China attaches great importance to the construction of carbon emission accounting system, and has achieved certain results, but the existing accounting system has been difficult to adapt to the new requirements of China's carbon emission reduction work. Therefore, this paper starts from the carbon emission accounting methods, summarizes the current domestic and foreign carbon emission accounting systems, analyzes the shortcomings of the current carbon emission accounting system construction in China, and puts forward relevant suggestions for improving China's carbon emission accounting system.

The impact of technological advancements on carbon emissions in agriculture and rural areas

Rural agriculture is an essential aspect of carbon emission reduction and sequestration and also has the potential to achieve “carbon peak” and “carbon neutrality.” A DEA-Malmquist index model is used to estimate the technical progress of agriculture using panel data from 30 provinces from 2012 to 2021. The evolution trend and spatial correlation of agricultural and rural carbon emissions are measured based on the spatial and temporal dimensions. The dynamic panel spatial lag model was also used to empirically test the mechanism of agricultural technological progress affecting agricultural rural carbon emissions. The results show that: ① There are apparent evolutionary characteristics and spatial agglomeration of agricultural and rural carbon emissions, and carbon pollution between provinces shows a weakening trend ② Agricultural technological progress can effectively drive carbon emission reduction in agriculture and rural areas, and the improvement of the farmers’ income structure can effectively regulate the carbon emission reduction efficacy of the total factor productivity, technological efficiency, and technological upgrading ③ The negative spatial spillover effect of agricultural technological progress on carbon emissions is significant; when the introduction of the farmers’ income structure as an interaction term, the negative spatial spillover effect of agricultural technological progress is significant. The negative spatial spillover effect of agricultural technological progress on carbon emissions is significant; introducing farmers’ income structure as an interaction term weakens the negative spatial spillover effect.

Towards a Sustainable Net-Zero Future: Energy and Economic Transition Amid Global Warming

As global temperatures continue to rise, there is an alarming increase in the severity and frequency of extreme climate hazards. The United Nations, responding to these dire changes, has advocated for a target of net-zero carbon emissions, a strategy aimed at pursuing efforts “to limit the temperature increase to 1.5°C above pre-industrial levels” (The Paris Agreement) and mitigating the devastating effects of global warming. This research delves into economic implications of these targets, leveraging comprehensive data that encompass carbon emissions, temperature, renewable energy, and vital economic indicators. Utilizing the RCP scenarios, we provide a nuanced projection of future climate under varying socio-economic and radiative conditions. The analysis of economic indicators can help predict the overall level and change trend of carbon emissions more reasonably, which can provide important decision-making support for the government to formulate environmental protection policies and enterprises to carry out carbon emission reduction work. At the same time, economic indicators can also help assess the changes in the carbon trading market, and play an important guiding role for enterprises and investors to conduct carbon emissions trading. Our findings underscore the intricate relationship between stringent carbon management practices and their potential economic ramifications, which include both the promise of increased market value for businesses and bolstered resilience against climate-induced threats. Bridging historical observations with future-orientated projections, this study serves as a beacon for policymakers and stakeholders alike. It emphasizes the critical need to advance sustainable development within a net-zero carbon framework, ensuring a comprehensive strategy for global warming adaptation and mitigation.

A bibliometric analysis based on hotspots and frontier trends of positron emission tomography/computed tomography utility in bone and soft tissue sarcoma.

This study aimed to analyze articles on the diagnosis and treatment of bone and soft tissue sarcoma using positron emission tomography (PET)/computed tomography (CT) published in the last 13 years. The objective was to conduct a bibliometric analysis and identify the research hotspots and emerging trends. Web of Science was used to search for articles on PET/CT diagnosis and treatment of bone and soft tissue sarcoma published from January 2010 to June 2023. CiteSpace was utilized to import data for bibliometric analysis. In total, 425 relevant publications were identified. Publications have maintained a relatively stable growth rate for the past 13 years. The USA has the highest number of published articles (139) and the highest centrality (0.35). The UDICE-French Research Universities group is the most influential institution. BYUN BH is a prominent contributor to this field. The Journal of Clinical Oncology has the highest impact factor in the field. The clinical application of PET/CT is currently a research hotspot. Upcoming areas of study concentrate on the merging of PET/CT with advanced machine learning and/or alternative imaging methods, novel imaging substances, and the fusion of diagnosis and therapy. The use of PET/CT has progressively become a crucial element in the identification and management of sarcomas. To confirm its efficacy, there is a need for extensive, multicenter, prospective studies.

Port carbon emission peaking simulation and emission reduction pathway in China

In order to achieve the goal of “carbon peak before 2030 and carbon neutrality before 2060”, all industries are fully engaged in energy conservation and carbon reduction work. Carbon emissions from the transportation sector account for nearly 10% of China's carbon emissions[1]. Port is an extremely important part of China's transportation industry, and it is also one of the key areas of energy conservation and emission reduction in the transportation industry. It is very important to carry out research on the status evaluation of port carbon emissions, predict the future trend of carbon emissions, and explore the strategy and path of port carbon peak. In this study, the carbon emission scenario prediction model based on the detailed list of port equipment was established to simulate the port carbon emissions. It is also applied to a northern port in China to study and judge the peak value and time point of carbon emission in the future, and propose the path of carbon peak in the port.

Research on Low-Carbon Energy Construction Scheme for Typical Parks in the Lancang-Mekong Region

Industrial parks serve as vital spatial carriers for economic and industrial development, exerting significant impacts on energy consumption and carbon emissions across nations. In order to promote green development in the Lancang-Mekong region, this research focuses on typical industrial parks in Laos, Thailand, and Vietnam. It analyzes the primary conditions of energy system construction, the structure of energy consumption, energy demand, and carbon emission trends in these parks. By considering local policies, development plans, and energy transition goals, the study assesses the development needs of energy consumption in the parks. It proposes differentiated schemes for constructing low-carbon energy systems in industrial parks, aiming to serve as a reference and guidance for the low-carbon energy transformation of typical industrial parks in the Lancang-Mekong region.

Efectos del crecimiento económico en las emisiones de CO2 en América del Norte

This paper examines the heterogeneity in the environmental field, specifically in the emission of the main of the greenhouse gases, CO2, within the 3 countries composing the North American region. On the one hand, the United States is a large emitter of CO2 (19% of global emissions accumulated in 1990-2020), only surpassed by China as of 2005. On the other hand, Canada and Mexico are relatively small emitters on a global scale (1.8% and 1.4% of global emissions accumulated in 1990-2020, respectively), but with large economic and technological differences. Under these conditions, the objective of this research is to find differences and similarities between the three countries regarding CO2 emissions trends and their driving structural factors: scale, technological and composition effects, based on annual data from 2001 to 2014. With a structural decomposition analysis, we found that, in general, the scale effect was polluting and dominating in the period, while the technological effect was anti-polluting, in addition to a small and ambivalent composition effect (positive in some years and negative in others). It is concluded that there is a process of convergence in the intensity of emissions per GDP value and with respect to the three mentioned effects. It is also concluded that the characteristics of the three effects in Mexico were like those of the United States, while Canada approached along the analysis period.

Greenhouse gas emissions trends and drivers insights from the domestic aviation in Thailand

Domestic aviation is a swiftly expanding contributor to global greenhouse gas (GHG) emissions. Presently, economic volatility and the Coronavirus disease (COVID-19) crisis have resulted in the decline of domestic aviation, but domestic aviation is rapidly recovering in many countries. However, from a GHG emissions viewpoint, the domestic aviation sector is largely unenforced even though the International Civil Aviation Organization's (ICAO) Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) provision for international aviation is currently in place. Accordingly, the knowledge base on emissions and their drivers from domestic aviation is weak, especially in developing countries, thus hindering an evidence-based policy debate. In this context, we have estimated and analyzed the pre-COVID-19 GHG emissions and their trends from commercial domestic aviation in Thailand; and provided insights on the role of key drivers that influence GHG emissions that are expected to be useful not only for Thailand but also for other developing countries. Emissions are estimated following Intergovernmental Panel on Climate Change (IPCC) Tier-II. Specifically, activity-based landing/take-off (LTO) cycle and cruise. This is compared to the Tier-I method, and key drivers were analyzed using an index decomposition method. The total annual average GHG emissions for all LTO cycles and cruises of commercial domestic aviation for 2015–2020 was 2254 Th. tonnes of CO2-eq. During the LTO cycle of the aircraft, GHG emissions were at an average of 983 Th. tonnes of CO2-eq. Additionally, during the cruise stage, emissions averaged 1270 Th. tonnes of CO2-eq. The choice of accounting methods (i.e., IPCC Tier II vs. Tier I) seems to have had only nominal implications. Our analysis showed that, in the 2008–2020 period, the aviation activity effect and economic growth were the key decisive factors in this sector's GHG emissions growth. It was followed by the fuel energy intensity levels and the population effect in descending order of impact. These findings have significant ramifications for present and future policies aimed at decreasing GHG emissions, aiding Thailand in achieving its climate targets by 2050, and enhancing energy efficiency as the domestic aviation market adapts.

Sustainable Driving: Zero-Emission Vehicles & Eco-Practices

Addressing vehicular emissions is crucial for safeguarding both human health and the environment. This study explores strategies to mitigate CO2 emissions from vehicles, focusing on adopting zero-emission vehicles (Electric vehicles) and promoting eco-friendly driving practices. By examining six scenarios, including measures to reduce emissions from existing Internal Combustion Engine (ICE) vehicles, the study predicts future CO2 emission trends. Moreover, the analysis incorporates the social cost of carbon (SCC) and evaluates its environmental impact and toxicological implications. The findings highlight the effectiveness of transitioning to 100% electric vehicle fleets and implementing eco-driving practices in significantly reducing future CO2 emissions. Additionally, embracing eco-driving techniques for current ICE vehicles emerges as a viable strategy for addressing current air pollution concerns while promoting a healthier environment