Level Of Carbon Emissions Research Articles

Study on the Evolution of Spatial and Temporal Patterns of Carbon Emissions from Land Use in a River Basin

Land-use change significantly contributes to carbon emission. Analyzing this relationship fosters exploration of low-carbon, efficient land-use patterns at regional levels. Using ArcGIS 10.5 and the PLUS model, this study investigated land transfer trends across six counties and one district in the Malian River Basin between 2000 and 2020. It quantified carbon emissions from land use and performed spatial distribution analysis using land-use and socio-economic data. The study demonstrates the following: (1) Between 2010 and 2020, significant land-use changes occurred in the Malian River Basin with 72,919.49 km2 of land undergoing transformation. Notably, the farmland-to-forest and grassland conversion project in Qingyang City was a major factor contributing to the shift from arable land to forest and grassland. (2) Natural factors influencing land conversion in the Loess Plateau region primarily include precipitation and elevation. Conversely, social factors such as population density, road networks, and local government establishments in districts and counties are pivotal in driving land-use changes within the Malian River Basin. (3) Carbon emissions vary significantly among different land-use types, with building land, cropland, unutilized land, watershed, grassland, and forest land showing descending emissions. The rapid expansion of building land notably increases carbon emissions in the study region, while forest land, a significant carbon sink, absorbs approximately 88% of total carbon emissions. (4) Districts and counties in the study area exhibit varying levels of carbon emissions, with Ning County, Xifeng District, Huan County, Qingcheng County, Zhengning County, Heshui County, and Huachi County listed in descending order. Regions with higher carbon emissions typically host abundant energy resources and significant energy production and consumption activities. Variations in carbon emission levels are largely influenced by resource availability and development priorities. Variations in resource levels and developmental focus are pivotal in explaining differences in carbon emission levels. Thus, it is crucial to explore the dynamic interplay between land-use carbon emission efficiency and land evolution in the Malian River Basin. This research will support ecological management and sustainable economic development in the Yellow River Basin, while also contributing to the achievement of the “double carbon” goals.

Significance of sustainable management practices and policy robustness in achieving carbon neutrality in KSA and UAE

Countries are under significant pressure from climate change due to high levels of carbon emissions, and they are working towards carbon neutrality (CN). This is particularly relevant for Saudi Arabia and the United Arab Emirates, which heavily rely on fossil fuels. Therefore, this study aims to suggest solutions for these countries. Specifically, it examines how sustainable management practices (SMP) impact CN. Additionally, it explores the moderating role of strong policies in the relationship between SMP and CN. To strengthen the study's findings, data were collected from 795 respondents across 244 firms in industries like oil, gas, iron, and copper extraction, selected based on their carbon emissions and potential for adopting sustainable practices. Using ordinary least squares regression, the study found that SMP has a significant positive effect on CN. Moreover, strong policies significantly enhance the relationship between sustainable practices and CN in both countries. Policymakers are encouraged to reinforce environmental regulations and offer incentives for adopting green technologies and practices. Effective policies can ensure the consistent use of SMP, leading to a significant reduction in carbon emissions.

Optimal Dispatch of Coal-fired Power Units with Carbon Capture Considering Peak Shaving and Ladder-type Carbon Trading

In the context of the low-carbon transformation of the power system, carbon markets, and carbon capture technologies have become important means to promote energy conservation and emission reduction. The rapid development of renewable energy poses a challenge to the regulation capability of the power system, and energy storage technology is currently an important means to enhance the regulation capability of the power grid. To reduce the carbon emission level of the power system, improve the system economy and the ability to consume renewable energy, this paper proposes a multi-energy complementary system (MECS) with carbon capture power plant (IFCCPP) considering ladder-type carbon trading (LCT) and energy storage. The optimal dispatch model was developed with the objective of minimizing the overall operating cost. The results indicated that the integration of IFCCPP and LCT has better economic and environmental benefits than separate applications. The integration of the two modes can reduce the total cost by 504.33 k$ and carbon emission by 39232.63 t, which verifies the rationality of integrating the two modes. The LCT produces more significant emission reduction effects due to its higher benefits when carbon emissions are lower. The traditional carbon trading mechanism reduces 4779.88 t of carbon emissions, and LCT reduces 38574.45 t.

The Energy Effect of Blockchain Technology Innovation in the Industry 5.0 Era--From the Perspective of Carbon Emissions

In the era of Industry 5.0, innovation in blockchain technology is expected to have a significant impact on energy efficiency and carbon emissions, especially in hybrid energy systems. This paper has obtained the innovation data on the blockchain patent of listed companies in China from 2010 to 2022 by machine learning and text analysis methodology of large language model. On this basis, the relationship between the enterprises’ blockchain technology innovation and the intensity of fossil energy consumption has been discussed. The study found that (1) the enterprises’ blockchain technology innovation is able to reduce the intensity of fossil energy consumption, and this conclusion remains valid via controlling for endogeneity and upon the completion of robustness test. (2) In terms of the mechanism, the enterprises’ blockchain technology innovation can achieve energy transition by reducing the cost of internal control, strengthening external supervision, improving the efficiency of resource allocation and strengthening the channels of supply chain management. (3) Further research has found that the energy effects as a result of blockchain technology innovation help to improve operational efficiency and lower the level of carbon emission. Our research provides scientific support for breaking the "technological energy paradox" in the field of energy economy while providing empirical evidence of "blockchain carbon reduction" for technologies such as blockchain BaaS alliance, cross-operator network spectrum, and shared base stations that will be applied on a large scale in the Industry 5.0 Era.

The impact of AI on enterprise energy management: from the perspective of carbon emissions

Given the significant impact of artificial intelligence (AI) technology on corporate energy management and the lack of research in this area, this paper employs text mining techniques to objectively assess the relative level of AI adoption among Chinese listed companies. Using econometric modelling methods, we verify these hypotheses and investigate both the direct and indirect effects of AI on corporate carbon emission intensity. our research finds that the carbon emission intensity of Chinese enterprises significantly decreased in the early stage, then stabilized, and has notably decreased again in recent years. The average level of AI among listed Chinese enterprises shows an overall upward trend, but the growth rate has slowed down. The level of AI in private enterprises is significantly higher than that in other types of enterprises, while the level of AI in state-owned enterprises is relatively lower. The level of AI in enterprises has a significant negative impact on carbon emission intensity, presenting an “S”-shaped relationship, characterized by initial emission reduction, mid-term rebound, and subsequent emission reduction. AI technology reduces the level of carbon emissions in enterprises by enhancing their green development standards and promoting technological innovation. There are significant differences in the impact of AI levels on carbon emission intensity across different types and regions of enterprises. The empirical conclusions remain robust after addressing endogeneity issues or variable substitution. This study provides important insights for corporate energy transitions and sustainable development, as well as for the formulation of government energy policies.

Do policies make a difference? Assessing the impact of China's air pollution prevention and control action plan on carbon emissions

This study aims to balance the dual objectives of improving environmental quality and achieving carbon peaking and carbon neutrality goals. Utilizing panel data from 274 Chinese cities between 2006 and 2020, this paper employs the difference-in-differences method to examine the impact of the Air Pollution Prevention and Control Action Plan (APPCAP) on urban carbon emissions. Empirical results indicate that the impact of the APPCAP on regional carbon emissions follows an inverted U-shaped curve, exhibiting a dual impact path. Although the implementation of the APPCAP increased the annual carbon emissions of the city by an average of 1.637 million tons, it showed a trend of inhibiting the growth of carbon emissions, although it was not significant. Specifically, the APPCAP is most effective in reducing carbon emissions during the "source prevention" stage, primarily by increasing industrial electricity consumption and reducing coal production and consumption. However, a rebound effect occurs at the policy period's end, with compensatory increases in crude oil and electricity consumption, thereby elevating regional carbon emission levels. The APPCAP's effect on carbon emissions is more pronounced in areas with lower population density and higher environmental regulation intensity. It notably raises carbon emission levels in non-industrial base and non-resource-based cities compared to other cities. Furthermore, the APPCAP positively impacts regional carbon emission intensity and economic growth, significantly driving the secondary industry while minimally affecting the primary industry.

The Effects of Climate Change on Kenya’s Economic Growth

Changes in the climate and natural disasters have hampered Kenya's growth in economy, as seen by periodic droughts, floods, and shifts in rainfall and temperature patterns. The research investigated the effects of climatic change on Kenya's GDP growth. Modeling was done using Autoregressive Distributed Lag (ARDL) model estimation technique while analyzing data from 1990 to 2023. Climate change was represented by annual rainfall fluctuations, carbon emissions, and forest depletion, with inflation, exchange rates, and government spending serving as the controlling factors. The regression results indicated that at 5% level of significance short run carbon emissions affect growth negatively but the long run results indicated a positive effect. Forest depletion positively impacts growth in the long run period. Government expenditure, changes in the exchange rate and economic growth had an inverse relationship. Inflation did not have potential long term impact on GDP. This study recommended that the government to balance economic growth with environmental sustainability by promoting cleaner technologies and renewable energy projects. Investments advanced irrigation and drought resistant crops are crucial. Sustainable forest management should involve controlled logging and reforestation to ensure long term health. Reducing exchange rate volatility through foreign reserves and diversified exports will stabilize the economy. Enhancing government expenditure efficiency by focusing on high return investments and minimizing waste will boost GDP stability.

Car Sales, Fuel Economy and Decarbonization in Mexico

The car market in Mexico has undergone substantial change over the last twenty years, as sales have increased dramatically and as policy measures have been introduced to improve fuel economy so that decarbonization targets can be achieved. The argument presented in this paper is that overall fuel economy is driven by vehicle sales and the fuel economy standards imposed. In addition, this picture is complicated by the purchasing preferences of buyers, and this might reduce the effectiveness of the policy measures introduced. A case study approach allows analysis of the shifts in transport policy (2003–2020) to be undertaken by linking the fuel consumption of cars (L/100 km) to the purchasing patterns of consumers, and from this estimate the levels of CO2 emissions. From the empirical analysis, it is found that, although there have been fuel economy gains every year, this is countered by (a) increasing sales of SUVs, and (b) a car market that is increasingly being dominated by larger cars. The current fuel standards are not sufficient to control the continued growth in fuel consumption, and levels of carbon emissions are continuing to increase. In conclusion, tighter emissions standards are needed, together with stronger governance structures and a range of further policy measures to improve car efficiencies and limit growth of the use of larger vehicles.

Zero-carbon tunnel: Concept, methodology and application in the built environment

Road tunnels are key components in the transportation infrastructure system, and plays a key role in the carbon emission. At present, the research on tunnel carbon emissions is still at an early stage, and its research target has not yet realized the transformation from low-carbon to zero-carbon. Therefore, this paper proposes the concept of the zero-carbon tunnel and introduces a methodology for zero-carbon tunnel design. This methodology includes defining the accounting boundaries of a zero-carbon tunnel, establishing a tunnel life-cycle carbon emissions assessment model, and verifying the zero-carbon tunnel. The methodology is applied to a road tunnel in China, to assess its carbon emission level and explore pathways to achieve zero-carbon status. Additionally, this paper discusses issues related to zero-carbon tunnels and explores future research prospects in this area. This study provides a reference for subsequent research on road tunnel carbon emissions.

Is digitalization essential for abating carbon emission growth in South Asia?

Output generation processes across South Asia are deemed unclean (highly emission-intensive) due to excessive reliance on fossil fuels. Thus, decarbonizing the growth processes within this region has critical emphasis among policymakers. However, since the South Asian countries are yet to be ready to undergo the renewable energy transition, it is unlikely that “their annual carbon discharge levels will subside” anytime soon. Under such circumstances, these countries need to limit the rate at which their carbon emission levels rise each year. Therefore, the impacts of digitalization on annual carbon emission growth rates in selected South Asian countries are assessed in this study. Overall, considering internet penetration rate as a proxy of digital technology adoption, the results confirm that policies aimed at digitalizing the concerned South Asian economies not only exert emission growth rate-reducing impacts via a direct channel, but also indirectly reduce emission growth rates by making natural resources sectors more productive, expediting the energy sector greening processes, greening the financial sectors, making corruption controlling measures within institutions more effective, and limiting urbanization-induced environmental quality-worsening effects. Therefore, it is relevant for the South Asian government to emphasize on digitalization while simultaneously ensuring that green digital technologies are adopted within the major macroeconomic sectors across this region.

Coupling geospatial suitability simulation and life cycle carbon emissions towards uncertain optimization planning for wind-photovoltaic-hydrogen multi-energy complementary system

Building clean and modern multi-energy complementary systems is a direct path to decarbonization in energy sector. The introduction of hydrogen energy with high operational flexibility enables the multi-energy complementary system to fully accommodate renewable energy. The key issues of the optimization planning of the wind-photovoltaic-hydrogen multi-energy complementary system that need to be solved are how to finely characterize the carbon reduction potential of the system, consider the uncertainty of supply and demand in the modeling process, and incorporate the energy supply business of electric vehicles into the planning. This study constructs optimization planning model with the following three progressive stages: geospatial suitability simulation based on geographic information system, uncertainty analysis based on probabilistic scene generation technology, and capacity configuration optimization. Unlike previous studies, this model measures and optimizes the carbon emissions level of the system from a lifecycle perspective. The empirical study results indicate that carbon emissions optimization from the perspective of the entire life cycle would directly affect the system configuration results. From a lifecycle perspective, the carbon emissions accounting result is about 9 times higher than that obtained only during the operation phase. Compared to the traditional distribution system, the carbon emissions of the system constructed in this study decreased by 82.75 %. In addition, considering that the system provides charging services for electric vehicles, which can reduce carbon emissions by about 93.6 % but only increase costs by about 29.4 %. The computational results justify the proposed optimization framework. This study provides optimization models for the system, and the implementation framework can support technical reference for practice.

How do water, food, and energy resources impact environmental conditions in Ghana? A novel dynamic ARDL simulation approach

Rising water, food, and energy demands pose significant resource risks and environmental threats. Despite the critical nature of this issue, there is a notable absence of empirical research linking the consumption of these resources to environmental degradation in Ghana. To fill this gap, this study investigates the short-term and long-term effects of water, food, and energy resource consumption on environmental degradation in Ghana, analyzing data from 1994 to 2020. Ghana's increasing environmental degradation accentuates the urgency of this research, its vulnerability to climate change, and the imperative to sustain human life and protect the environment. Utilizing the novel dynamic ARDL simulation method, this research offers new perspectives that diverge from previous findings. The study's findings demonstrate that water resource consumption positively impacts environmental degradation in the short and long term. However, food and energy resource consumption mitigates environmental degradation in the short and long term. Therefore, the study advocates adopting resource management strategies emphasizing efficiency and sustainability. It calls for policies that improve water efficiency, boost renewable energy uptake, and encourage sustainable farming practices. These measures are intended to lessen the negative impacts of resource exploitation and aid in environmental preservation efforts.

Climate risk and energy-saving technology innovation: Evidence from Chinese prefecture-level cities

In the face of the challenges of energy and environmental issues posed by climate risk, actively promoting energy-saving technology innovation is crucial in addressing climate risk. This study focuses on the electricity elements as the research object, and examines the impact of climate risk on energy-saving technology innovation by constructing a Spatial Durbin Model, using 2007–2021 data on temperature and electricity-saving technology patents at the prefecture-level cities in China. The findings reveal that climate risk promotes energy-saving technology innovation. Furthermore, it is discovered that climate risk exhibits significant positive spillover effects on energy-saving technology innovation through the decomposition of spatial effects, implying that the climate risk in neighboring areas has a notable positive influence on local energy-saving technology innovation. Mechanism tests indicate that climate risk directly promotes regional energy-saving technology innovation through increasing energy consumption, research and development (R&D) investment, and strengthening government environmental regulation. Particularly under the influence of climate risk, the increase in energy consumption and R&D investment more effectively drives regional energy-saving technology innovation. Moreover, variances in cities' geographical locations, carbon emission levels, electricity price levels, and electricity resource endowments result in substantial discrepancies in the effect of climate risk on energy-saving technology innovation. Based on these findings, Governments could incorporate climate risk into synergistic regional planning and enhance energy-saving technology innovation to address climate risk.

The impact assessment of low-carbon city pilot policy on urban green innovation: A batch-time heterogeneity perspective

The Chinese government is actively implementing the Low Carbon City Pilot (LCCP) policy nationwide to fulfill its commitment to carbon peaking and carbon neutrality. One of the main objectives of the LCCP policy is to enhance green innovation in cities, and many publications have assessed its effectiveness. While previous studies have considered differences in city characteristics, they have not adequately analyzed the varying effects of LCCP policy on different batches of pilot cities. To address this gap, this study utilized a cutting-edge heterogeneity causal inference approach to evaluate the heterogeneity of LCCP policy effects across different batches. The findings indicate that the LCCP policy significantly promoted urban green innovation and green substantive innovation. However, its impact on green symbolic innovation was not statistically significant. Among the different batches of pilot cities, the second batch was most strongly affected by the LCCP policy, followed by the third batch. Further analysis reveals that the initial group of pilot cities, with their varying innovation capabilities, carbon emission levels, and government intervention, along with the negative spatial competition among the cities, resulted in a less effective implementation of the LCCP policy compared to the second and third batches. This study contributes to a more accurate assessment of the effectiveness of the LCCP policy by highlighting the heterogeneity across different batches. We recommend that cities committed to low-carbon growth through green innovation customize the design and implementation of their low-carbon policies and establish broader networks of city-to-city cooperation.

Understanding the Effect of Climate Risk on Banking Business—A Panel Data Analysis of Indian Firms

The enormous phenomenon of climate change, which is affecting many organisations of different sectors today, has a special impact on the financial sector in terms of credit risk. Awareness and action on environmental, social and governance (ESG) goals and climate change impacts have been rapidly increasing worldwide. In this article, we present a firm-level panel data analysis to link ESG ratings and CO2 emissions with the default risk and solvency position of selected companies. We perform various univariate and multivariate analyses on selected top Bombay Stock Exchange (BSE) top 200 companies that have disclosures in Carbon Disclosure Project (CDP) reports over 5 years (2017–2021). We find strong empirical evidence that a firm’s risk of default is linked to its environmental performance along with the level of carbon emission. Our findings will enable banks to establish a linkage between credit risk and climate change risk. This will assist banks as well as policymakers to adjust borrower-level ratings and align their lending and investments with net zero emissions. JEL Codes: G32, G33, Q2, Q5

Spatiotemporal Differentiation of Carbon Budget and Carbon Compensation Zoning Based on the Plan for Major Function-oriented Zones：A Case Study of Counties in the Yellow River Basin

Exploring the spatiotemporal differentiation of the carbon budget and clarifying the zoning of carbon compensation based on the perspective of the main function-oriented zones is of great significance for promoting regional low-carbon development and achieving the "dual carbon" goal. This study was conducted using 550 counties in the Yellow River Basin as the basic unit, and based on the concentration index to examine the spatial distribution characteristics of carbon emissions and carbon absorptions in the main function-oriented zones of the Yellow River Basin, a four-dimensional benchmark framework for carbon compensation zoning was constructed by total scale, economic contribution, ecological carrying capacity, and land development intensity. The SOM-K-means algorithm was used to establish a differentiated carbon compensation zoning scheme. The results showed that： ① The carbon emissions and carbon absorptions and their growth trends of the main function-oriented zones in the Yellow River Basin were in line with the positioning of the main functional area, and the significant space-time distribution characteristics of the concentration level of carbon emissions and carbon absorptions were shown. ② Significant regional differences exist in the four attributes of total carbon emissions scale, economic contribution, ecological carrying capacity, and land development intensity. The overall scale of carbon emissions showed a growth trend, with obvious comparative advantages in the midstream and downstream. The overall comparative advantage of economic contribution increased first and then decreased, with the midstream and downstream being the attribute advantage areas of economic contribution. The overall ecological carrying capacity had been improved, and the upstream had obvious advantages in ecological carrying properties. The advantageous areas for land development were mainly concentrated in the midstream and downstream； in particular, the comparative advantage index in the midstream was showing a rapid upward trend. ③ Moreover, there were 287 compensated areas, 78 balanced areas, and 185 payment areas in the Yellow River Basin. Eleven types of carbon compensation zones were finally formed by combining the comparative advantage index of four types of attributes with the plan for main function-oriented zones, and corresponding low-carbon development strategies were proposed for each type of zone.

The impact of green roofs’ composition on its overall life cycle

Green roof systems have been developed to improve the environmental, economic, and social aspects of sustainability. Selecting the appropriate version of the green roof composition plays an important role in the life cycle assessment of a green roof. In this study, 10 compositions of an intensive green roof for moderate zone and 4 green roof compositions for different climatic conditions were designed and comprehensively assessed in terms of their environmental and economic impacts within the “Cradle-to-Cradle” system boundary. The assessment was carried out over a 50-year period for a moderate climate zone. The results showed that asphalt strips and concrete slab produced the highest total emissions. It was found that most greenhouse gases emissions were released in the operational energy consumption phase and in the production phase. The energy consumption phase (48.78%) for automatic irrigation and maintenance caused the highest Global Warming Potential (GWP) value (758.39 kg CO2e) in the worst variant, which also caused the highest life cycle cost (878.47€). On the contrary, in the best variant, planting more vegetation and lower maintenance and irrigation requirements led to a reduction in GWP (445.0 kg CO2e), but in terms of cost (506.6€) this composition didn't represent the best variant. The Global Warming Potential Biogenic (GWP-bio) compared to the Global Warming Potential Total (GWP-total) represents a proportion ranging from 0.8% to 78% depending on the proposed vegetation. Overall higher biogenic carbon values (up to 1525 kg CO2e) were observed for the proposed tall vegetation of Magnolia, Red Mulberry, Hawthorne, Cherry, and Crab-apple Tree. Based on the results of the multicriteria analysis, which included core environmental & economic parameters, biogenic carbon emission levels, the outcome of this paper proposed optimal green roof composition. Optimal intensive green roof composition was subjected to a sensitivity analysis to determine the impact of changing climatic conditions on CO2 emissions and life cycle costs. The results of the sensitivity analysis show that the optimal variant of the green roof can be implemented in the cold and subtropical zone with regard to CO2 emissions, but not with regard to life cycle costs.

Synergistic dance of digital economy and green finance on carbon emissions: Insights from China

China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably. This paper supports these goals and explores how the digital economy and green finance intersect and impact carbon emissions. Using panel data from 30 Chinese provinces over the period 2011–2021, this paper finds that the digital economy and green finance can together reduce carbon emissions, and conducts several robustness tests supporting this conclusion. A heterogeneity analysis shows that these synergistic effects are more important in regions with low levels of social consumption Meanwhile, in the spatial dimension, the synergistic effect of the local digital economy and green finance adversely impacts the level of carbon emissions in surrounding areas. The findings of this paper provide insights for policymakers in guiding capital flow and implementing carbon-reduction policies while fostering the growth of China’s digital economy and environmental sustainability.

Carbon footprint reporting example on WIG30 Index companies for 2021-2022

The purpose of the article is to present the results of the authors' research on the reporting of carbon footprint and carbon emission levels of 30 companies included in the WIG30 index of the Warsaw Stock Exchange for the period 2021-2022. The methodology was based on a literature review on the subject, legal acts and own research, which used non-financial reports of listed companies on information on carbon footprint and emission levels. According to the authors, the article adds value to the literature on the subject, particularly in the collection of source material and its discussion. The topics of the article can form the basis for further detailed empirical research on carbon footprint reporting.

Short- and long-term effects of carbon taxation on the prices of products shipped by sea

This study analyzes econometrically the effect of fuel carbon taxation on the prices of internationally traded goods transported by the maritime sector. Around 80% of global trade by volume is transported by sea, contributing to a nontrivial level of carbon emissions. This study is the first to analyze the effect of carbon taxation on the prices of export products transported by sea, using detailed data for the heaviest 6-digit products from 21 industries that account for 75% of the total weight of goods transported by sea. The results reveal that the closer a product is to the core competence of the exporting firm (lowest marginal production costs), the weaker the effect of the carbon tax will be on prices. This effect on export prices will be even weaker for products of certain industries that have the highest unit sales value/weight ratios. To contribute to decarbonizing the maritime sector, a carbon tax should be maintained uninterruptedly to fully internalize the awareness that improving fuel consumption competitiveness by considering the distance traveled and weight of traded products to ultimately reduce carbon tax costs.