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The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

The digital economy plays an important role in reducing the global warming process. This paper explores the spatiotemporal heterogeneity impacts of the digital economy on provincial carbon emissions and its underlying mechanisms. Initially, this paper examines the inhibitory impact of the digital economy on carbon emissions, alongside the mediating role of economic agglomeration, at a theoretical level. Subsequently, it empirically explores the quantitative associations among the digital economy, economic agglomeration, and carbon emissions by utilizing Chinese provincial panel data spanning from 2000 to 2021. This investigation employed static and dynamic spatial Durbin models as well as mediation models to analyze the interrelationships. The results firstly revealed that the digital economy notably diminishes carbon emissions, with economic agglomeration playing a significant mediating role. This conclusion remained consistent even after substituting the explanatory variables and weight matrix, modifying the sample period, and conducting other robustness tests. Secondly, the impact of the digital economy on carbon emissions exhibited spatial spillovers. Compared with the impact on the local area, the impact on neighboring provinces was found to be weaker. Thirdly, carbon emissions showed a significant "snowball" effect in the time dimension. This paper emphasizes the important role of digital technology in curbing carbon emissions, and it provides some policy insights for studying the digital economy, economic agglomeration, and carbon emissions. Furthermore, it offers valuable insight and suggestions to reduce carbon emissions and realize the goal of the "dual-carbon" strategy. [ABSTRACT FROM AUTHOR]

The land use, land-use change and forestry (LULUCF) sector, as a source and a sink of greenhouse gas (GHG) emissions, is critical for achieving carbon neutrality. Many academic journals have published papers on land use carbon emission or sink (LUCES), but LUCES reviews are relatively rare, which poses great challenges in accurately understanding the research progress and future prospects. This work analyzes the research characteristics, hotspots and future perspectives of LUCES research by using a bibliometric analysis (such as DDA, VOSviewer, CiteSpace software) and a review based on the data (6115 scientific papers) during 1991–2023 from the Web of Science (WoS) platform. We found that (1) over the past 33 years, it first presented a steady growth, then fluctuating growth, and finally a rapid growth trend in the yearly number of publications in LUCES research. The USA (17.31%), China (14.96%), and the UK (7.37%) occupy a dominant position in this research field. (2) The related LUCES research is interdisciplinary, which mainly cover science and technology, meteorology and atmospheric sciences, geology, and environmental sciences and ecology disciplines. (3) The research hotspot analysis on LUCES shows that these articles mostly covered the follow three aspects: ecosystem services, climate change, and carbon neutrality. (4) A review of the past LUCES literature suggests that it is mainly focused on exploring the forefront issues in terms of the definition and boundaries, evaluation method and influencing factors, etc. This work suggests that further research could explore the main scientific problems on quantification of land-based carbon neutrality, quantitative analysis of the impact mechanisms, as well as interdisciplinary research and collaborative governance needed for carbon neutrality. [ABSTRACT FROM AUTHOR]

Regional integration plays a pivotal role in the socio-economic advancement of various global regions and is closely linked with the expansion of construction land. This expansion is a major contributor to urban carbon emissions. Utilizing a geographical regression discontinuity design (GRDD), this paper estimates the impact of urban construction land expansion on carbon emissions and explores the underlying mechanisms within the regional integration process of the Yangtze River Delta (YRD), China. The findings reveal that urban construction land expansion significantly influences carbon emissions, displaying an inverted "U"-shaped pattern. Furthermore, this expansion affects carbon emissions through the transformation of industrial structures, shifts in consumption patterns, and enhancements in scientific and technological investments. Our findings span the performance of the Yangtze River Delta from its early development stages to a relatively mature phase. This paper also partially reveals how the Yangtze River Delta, with both megacities and large- to medium-sized cities, manages urban construction land expansion during the integration process and strives for low-carbon emissions reduction. These results can provide green growth recommendations that balance socio-economic development, low-carbon emissions, and social equity not only for other urban agglomerations in China but also for similar regions in other developing countries by altering construction land utilization patterns. [ABSTRACT FROM AUTHOR]

In order to reduce pollution caused by ship emissions, the International Maritime Organization (IMO) implemented sulfur emission control areas (SECAs). In comparison to ordinary vessels, cruise ships with dual attributes of transportation and tourism generate a greater amount of marine pollution, which poses a significant threat to the marine environment in both berthing ports and the sailing area. In light of the fierce competition of the cruise tourism market, cruise lines are looking for strategies, such as designing more attractive cruise routes, to maintain their core competencies under the emission control policy. In order to achieve this goal, this paper presents a mixed-integer non-linear programming (MINP) model with two objectives and is derived from the traditional route optimization problem. The primary objective is to optimize the route and speed of a cruise liner, while simultaneously enhancing route competitiveness and minimizing carbon emissions both within and outside the SECAs. Subsequently, the multi-objective particle swarm optimization (MOPSO) algorithm was used to reach the objective, and simulations were carried out to verify the effectiveness of the model and method. The results show that speed and sailing route optimization can affect carbon emissions. This paper has a certain application value and guiding significance for cruise line decision makers that will be beneficial for the environment. [ABSTRACT FROM AUTHOR]

The reactive power optimization of an active distribution network can effectively deal with the problem of voltage overflows at some nodes caused by the integration of a high proportion of distributed sources into the distribution network. Aiming to address the limitations in previous studies of dynamic reactive power optimization using the cluster partitioning method, a three-stage dynamic reactive power optimization decoupling strategy for active distribution networks considering carbon emissions is proposed in this paper. First, a carbon emission index is proposed based on the carbon emission intensity, and a dynamic reactive power optimization mathematical model of an active distribution network is established with the minimum active power network loss, voltage deviation, and carbon emissions as the satisfaction objective functions. Second, in order to satisfy the requirement for the all-day motion times of discrete devices, a three-stage dynamic reactive power optimization decoupling strategy based on the partitioning around a medoids clustering algorithm is proposed. Finally, taking the improved IEEE33 and PG&E69-node distribution network systems as examples, the proposed linear decreasing mutation particle swarm optimization algorithm was used to solve the mathematical model. The results show that all the indicators of the proposed strategy and algorithm throughout the day are lower than those of other methods, which verifies the effectiveness of the proposed strategy and algorithm. [ABSTRACT FROM AUTHOR]

As the world embarks on a global mission to tackle climate change, reducing carbon represents a key challenge given the escalating global warming. The U.K. is among many other nations that are determined to decarbonise all sectors and strive to achieve a net zero carbon target by 2050. While much attention has been paid to improving performance and reducing carbon emissions in electrical machines, the current research landscape focuses mainly on the thermal and electromagnetic facets. Surprisingly, carbon emissions from the production stage, especially those related to raw material consumption, remain a largely unexplored area. This paper wishes to shed light on a neglected dimension by providing a comprehensive review of carbon emissions in the manufacture of electrical machines, thus contributing significantly to the wider discourse on carbon emission reduction by comparing the carbon emission values associated with various materials commonly used for the main components of these machines. A further case study is included to assess and explore the impact of material alterations on a synchronous machine, from a carbon emission perspective. A reliable material guide will provide engineers at the design stage with the critical insight needed to make informed material selection decisions, highlighting the critical role of carbon emission values beyond conventional thermal and electromagnetic considerations, achieving sustainable and environmentally conscious electrical machine design. [ABSTRACT FROM AUTHOR]

Digital networks have brought about more frequent economic interaction. Labor misallocation influences regional green development through digital channels. Constructing a digital divide matrix among 30 Chinese provinces, a spatial Durbin model was applied in this paper to address the digital spillover of labor misallocation on carbon emission. We obtained the following research findings: (1) The digital divide in China tends to spread from east to west between 2006 and 2021. (2) Labor misallocation impacts carbon emissions through digital spillover. Specifically, labor misallocation increases local carbon emissions, as well as carbon emissions in digital adjacent regions. (3) The widening digital divide exacerbates the digital spillover effects of labor misallocation. The result's plausibility was further verified by generalized spatial two-stage least squares. (4) Labor misallocation increases carbon emissions when the digital divide exceeds a threshold. The results provide an effectual reference for digital governance in Chinese carbon emissions. [ABSTRACT FROM AUTHOR]

Low or even zero carbon dioxide emissions will be an essential requirement for energy supplies in the near future. Besides transport and electricity generation, industry is another large carbon emitter. Hydrogen produced by renewable energy provides a flexible way of utilizing that energy. Hydrogen, as an energy carrier, could be stored in a large capacity compared to electricity. In Sweden, hydrogen will be used to replace coal for steel production. This paper discusses how the need for electricity to produce hydrogen will affect the electricity supply and power flow in the Swedish power grid, and whether it will result in increased emissions in other regions. Data of the Swedish system will be used to study the feasibility of implementing the hydrogen system from the power system viewpoint, and discuss the electricity price and emission issues caused by the hydrogen production in different scenarios. This paper concludes that the Swedish power grid is feasible for accommodating the additional electricity capacity requirement of producing green hydrogen for the steel industry. The obtained results could be references for decision makers, investors, and power system operators. [ABSTRACT FROM AUTHOR]

Innovation in new energy technologies is a key driver in China's efforts to achieve its environmental goals. However, the ability of different regions to develop and utilize new energy technologies may depend on their level of economic development. Based on a two-way fixed-effects panel data model, this paper empirically analyses the industry carbon emission reduction effect of new energy technology innovation and its heterogeneous performance at different stages of economic development, using data from 30 provinces and cities in China from 2000 to 2019. The results show that new energy technology innovation generally promotes CO2 emissions in China. The specific effects are closely related to the characteristics of the industry and the stage of economic development. At the same time, the implementation of environmental regulations will inhibit this positive effect, while the adjustment of the industrial structure may promote this positive effect. This paper discovers the mechanism of heterogeneity in new energy technology innovation among different provinces with different levels of economic development. This finding helps to fully assess the carbon emission reduction capacity and potential of different provinces and facilitates the rational disaggregation and formulation of climate policy goals among regions. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality are gaining global consensus, and carbon reduction in aviation is necessary and urgent. The main objective of this research paper is to map and analyze the knowledge graph of aviation carbon emissions research from a bibliometric perspective. Publications related to aviation carbon emissions indexed by Scopus for the period 1992 to 2021 were analyzed primarily using CiteSpace software. This paper presents a bibliometric analysis of current research progress from four perspectives: (1) descriptive analysis of publications, involving annual distribution, authors, and journals; (2) analysis of co-cited authors and their countries; (3) co-citation analysis of cited references; and (4) co-occurrence analysis of keywords. A series of domain knowledge maps were constructed to visualize the core of aviation carbon emissions research and to distill the research perspectives on aviation carbon emissions in the past 20 years. The latest and most important research results in the field obtained through the combing provide certain references for the research and development of aviation carbon emissions. [ABSTRACT FROM AUTHOR]

In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction in key industries. Based on the panel data of 30 provinces. from 2011 to 2020, this paper used the fixed-effect model to analyze the emission reduction effect in key industries on the development status of technology import. The spatial econometric model was used to analyze the spatial characteristics of carbon emissions of technology import and key industries. Then, the mediating effect model was used to bring industrial technological innovations into the research category to analyze the mediating role of technology imports on the carbon emissions of key industries. Finally, a robustness test proved the reliability of the model. The findings were as follows: (1) Technology import significantly promoted carbon emission reduction in key industries; (2) In terms of the spatial relationship, technology import and carbon dioxide emissions had significant spillover effects, and there were trends of high and high aggregation and low and low aggregation, with the impact of technology import on carbon dioxide emissions having a siphon effect; (3) Industrial technological innovation played an intermediary role in this path, but it was a negative role, which was not, in general, conducive to the reduction of carbon emissions of key industries. On this basis, the paper puts forward several policy suggestions. [ABSTRACT FROM AUTHOR]

Arctic navigation research will be more urgent as it is predicted that 4.7% of the shipping trade will be deployed in the Arctic region by 2030. This paper presents a multi-objective path optimization algorithm based on the field theory to investigate Arctic shipping route design and navigation strategies that take safety, economy and environmental protection as factors. The algorithm considers the ice conditions in Arctic waters throughout the year, the energy consumption of ships with different ice classes and carbon emissions. The sea environment is initially modeled using the potential field method, incorporating the ice condition field, fuel consumption, emission field and directional field. The navigable area is defined based on the ship navigability, and path optimization is conducted using the principle of gradient descent between the departure point and destination. The experimental results show that the cost of carbon emissions and fuel consumption varies for each class of ship on the planned path in different months. Therefore, by combining different classes of ships and months, we obtain an Arctic navigation strategy with a consideration of the best cost and environmental protection for each month. The path planning and navigation strategy decision method proposed in this paper can provide a reference for an Arctic route design, navigation month and vessel selection, which is beneficial to the sustainable development of Arctic shipping. [ABSTRACT FROM AUTHOR]

Driven by energy shortages and climate concerns, the electric vehicles are popular around the world with their energy-saving and environmentally friendly advantages. As electric vehicle batteries (EVBs) mainly use lithium batteries, and the batteries' performance decreases with the increase of charging times, a large number of batteries are entering the end-of-life (EoL) stage. Recycling and reuse of EVBs are effective ways to reduce environmental pollution and promote resources utilization and is now a top priority. Building a recycling network is the foundation of battery recycling. However, there are few studies on battery recycling networks and the construction of recycling networks is expensive, which impedes the sustainable development of electric vehicles. Based on this, recycling network design is critical for EVB recycling. This paper first analyzes three strategies to deal with used batteries: remanufacturing, reuse, and recycling materials. Secondly, an EVB recycling network model is developed with the objective of minimizing the total cost and carbon emissions. The model solves the problem of siting the centers in the network and the vehicle routing in the recycling process. Finally, the model was applied to GEM (a Chinese company dedicated to circular economy) and validated using a greedy algorithm. In addition, the results show that logistics costs and operating costs account for the majority of the recycling network total expense, at 48.45% and 31%, respectively. Therefore, if companies want to further reduce the cost of EVB recycling, they should reduce logistics costs and operating costs. In summary, this paper provides a decision-making approach for EVB recycling enterprises to carry out recycling and reuse, and offers advice on how to promote the sustainable economic and environmental development of the electric vehicle battery industry. [ABSTRACT FROM AUTHOR]

In the transition to sustainable public transportation with zero-emission buses, hydrogen fuel cell electric buses have emerged as a promising alternative to traditional diesel buses. However, assessing their economic viability is crucial for widespread adoption. This study carries out a comprehensive examination, encompassing both sensitivity and probabilistic analyses, to assess the total cost of ownership (TCO) for the bus fleet and its corresponding infrastructure. It considers various hydrogen supply options, encompassing on-site electrolysis, on-site steam methane reforming, and off-site hydrogen procurement with both gaseous and liquid delivery methods. The analysis covers critical cost elements, encompassing bus acquisition costs, infrastructure capital expenses, and operational and maintenance costs for both buses and infrastructure. This paper conducted two distinct case studies: one involving a current small bus fleet of five buses and another focusing on a larger fleet set to launch in 2028. For the current small fleet, the off-site gray hydrogen purchase with a gaseous delivery option is the most cost-effective among hydrogen alternatives, but it still incurs a 26.97% higher TCO compared to diesel buses. However, in the case of the expanded 2028 fleet, the steam methane-reforming method without carbon capture emerges as the most likely option to attain the lowest TCO, with a high probability of 99.5%. Additionally, carbon emission costs were incorporated in response to the growing emphasis on environmental sustainability. The findings indicate that although diesel buses currently represent the most economical option in terms of TCO for the existing small fleet, steam methane reforming with carbon capture presents a 69.2% likelihood of being the most cost-effective solution, suggesting it is a strong candidate for cost efficiency for the expanded 2028 fleet. Notably, substantial investments are required to increase renewable energy integration in the power grid and to enhance electrolyzer efficiency. These improvements are essential to make the electrolyzer a more competitive alternative to steam methane reforming. Overall, the findings in this paper underscore the substantial impact of the hydrogen supply chain and carbon emission costs on the TCO of zero-emission buses. [ABSTRACT FROM AUTHOR]

Many nations have enacted diverse environmental control regulations to address environmental and climate concerns. Analyzing how environmental regulation affects industrial green total factor productivity can aid in creating appropriate environmental regulation laws and realizing peaceful coexistence between man and nature. Based on the panel data of various provinces in China from 2011 to 2019, this paper used the data envelopment analysis method to measure the industrial green total factor productivity and then used the system generalized method of moments model to empirically study the differential effect of heterogeneous environmental regulation on China's industrial green total factor productivity. In addition, this paper also conducted a test of internal and external mechanisms. The statistics show that environmental regulation can boost the growth of industrial green total factor productivity and pass the robustness test. Innovation ability is the external mechanism variable of environmental regulation acting on industrial green total factor productivity. Regulation can improve industrial productivity and significantly suppress industrial pollution emissions, but market-based environmental regulations do not have an effective impact on carbon emissions. Environmental regulations in economically developed regions can promote the growth of industrial green total factor productivity, but for financially backward areas, market-based environmental regulation inhibits the promotion of industrial green total factor productivity, while command-and-control environmental regulation is not helpful for industrial green total factor productivity. [ABSTRACT FROM AUTHOR]

Due to the recent abnormalities in global temperature and increasing carbon emissions, the world is working to reduce carbon emissions. In particular, the construction sector accounts for about 37% of all carbon emissions, so it is one of the areas where sustainable reduction efforts must be made. Therefore, in this paper, an optimal design process was performed by evaluating carbon emissions as the objective function, a choice which differed from the objective function of the existing research used in the optimal design of truss structures. The metaheuristics algorithm used for the process was the advanced crow search algorithm. The levels of carbon emissions generated when the material of a truss structure consisted of a customary material (steel) were compared to scenarios in which timber was used, and a construction scenario centered on the Republic of Korea was established for comparison. The structures used as examples were 10-, 17-, 22-, and 120-bar truss structures. As a result, it was confirmed that truss structures using timber had fewer carbon emissions than structures using steel. In addition, it was confirmed that, even in the same timber structures, domestic timber had fewer carbon emissions than imported timber. These results confirmed that in order to achieve carbon neutrality in the construction field, carbon emissions must be considered in advance, in the design stage. [ABSTRACT FROM AUTHOR]

This paper examines the impact of family ownership and supervisory board characteristics on carbon emission disclosure. It uses balanced panel data and a matched-pair design of 124 non-financial firms listed on the Indonesia Stock Exchange from 2017 to 2019. This study finds that family firms and larger boards improve, while female board members harm carbon emission performance. Further analyses reveal non-linear relationships between family ownership and carbon performance. When control rights are limited, family firms prioritize controlling managers and improving carbon quality. Conversely, they prioritize personal objectives over environmental concerns when there are high control rights, resulting in decreased carbon emission performance. Additionally, family board members generate more carbon information, indicating the family owners effectively utilize their position on the supervisory boards to influence the company's carbon emission performance. Finally, the study reports that more faculty member boards seem to hurt carbon emission reduction efforts. This result suggests that the diversity of their professional experiences does not affect the environmental effectiveness of supervisory boards. Our findings highlight the importance of understanding SEW principles and their connection to families in comprehending Indonesian corporate carbon emissions disclosures. The findings of this study enrich the worldwide literature by exploring the potential benefits of family business environmental performance. This study also adds to the literature on corporate governance, especially the role played by supervisory boards. Our findings align with the resource dependence theory, emphasizing the central function of supervisory boards as a monitoring tool. This study is constrained by its reliance on carbon emission data extracted from the annual reports of public firms, with a particular emphasis on pre-COVID-19 data. Future research should focus on sustainability reports and explore the time frame encompassing COVID-19 (2020–2022 datasets) to determine any differences in the findings. [ABSTRACT FROM AUTHOR]

Diverse demands have promoted the rapid development of the cold chain logistics industry. In the paper, a novel approach for calculating the comprehensive carbon emission cost was proposed and the front warehouse mode was analyzed under the background of energy conservation and emission reduction. To solve the two-echelon low-carbon location-routing problem (2E-LCLRP), a mathematical model considering operating cost, total transportation cost, fixed cost, refrigeration cost, cargo damage cost, and comprehensive carbon emission cost was proposed to determine the minimum total cost. A hybrid ant colony optimization (HACO) algorithm based on an elbow rule and an improved ant colony optimization (IACO) algorithm was proposed to solve the 2E-LCLRP. According to the elbow rule, the optimal number of front warehouses was determined and an IACO algorithm was then designed to optimize vehicle routes. An adaptive hybrid selection strategy and an optimized pheromone update mechanism were integrated into the HACO algorithm to accelerate convergence and obtain global optimal solutions. The proposed model and algorithm were verified through the case study of the 2E-LCLRP in Nanjing, China. The HACO algorithm outperformed the original ant colony optimization (ACO) algorithm in terms of convergence rate and solution quality. This study provides significant insights for enhancing heuristic algorithms as well as valuable research methods. Furthermore, the results can help cold chain logistics companies in balancing economic costs and environmental benefits and address cold chain distribution of agricultural products. [ABSTRACT FROM AUTHOR]

Predicting carbon emissions is important in various sectors, including environmental management, economic planning, and energy policy. Traditional forecasting models typically require extensive training data to achieve high accuracy. However, carbon emission data are usually available on an annual basis, which is insufficient for effectively training conventional forecasting models. To address this challenge, this paper introduces an innovative carbon emissions prediction model that integrates Fibonacci attenuation particle swarm optimization (FAPSO) with the gated recurrent unit (GRU). The FAPSO algorithm is used to optimize the hyperparameters of the GRU, thereby alleviating the decline in prediction accuracy that conventional recurrent neural networks often face when dealing with limited training data. To evaluate the effectiveness of the FAPSO-GRU model, we tested it using carbon emission data from Hainan Province. Compared to the conventional GRU model, the FAPSO-GRU model achieved a significant reduction in the mean absolute error (42.27%), root mean square error (42.38%), and mean absolute percentage error (43.06%). Furthermore, we validated the FAPSO-GRU model with real data from Beijing, Guangdong, Hubei, Hunan, and Shanghai. The experimental results convincingly demonstrate that the proposed model provides a highly accurate solution for carbon emission prediction tasks, effectively addressing the limitations posed by limited training data. [ABSTRACT FROM AUTHOR]

To achieve the goals of "carbon peaking and carbon neutrality", this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. We defined the carbon intensity of urban industrial land as the industrial carbon emissions per unit area of land, which is a spatial mapping of urban industrial economic development and carbon spillover and a key indicator for urban and territorial spatial planning oriented towards the "dual carbon" goal. Findings: The carbon emission density of industrial land in the YREB varied greatly between cities and exhibited significant positive spatial autocorrelation. In addition, the geographical pattern and spatio-temporal evolution model of the urban industrial land carbon emission density had a very complex driving mechanism, and different factors had significant synergistic effects. Therefore, it is suggested that while striving towards the goal of "dual carbon", the government should incorporate the carbon emission density indicator of urban industrial land into the urban and territorial spatial planning system, and based on the threshold of the medium suitable density, they should design differentiated management policies according to concrete urban policies and encourage cooperation among cities to jointly promote carbon emission management of urban industrial land. In policy design, emphasis should also be placed on highlighting the interactive effects of foreign direct investment, fiscal expenditure, and the number of patent authorizations as well as constructing a combination of policies centered around them to better leverage the impacts of globalization, government intervention, and innovation. [ABSTRACT FROM AUTHOR]

In this paper, we explore the integration of building information modeling (BIM) technology to assess carbon emissions, emphasizing the unique contributions to smart and sustainable approaches in prefabricated buildings and focusing on the application of digital construction strategies facilitated by BIM to evaluate carbon emissions in green prefabricated buildings, with a detailed case study on C-House at Southeast University, Nanjing, China. The research methodology involved creating a BIM model of C-House in Rhino and collecting data from the operationalization phase. This research work delves into analyzing the structural components, on-site assembling process, and evaluation of carbon emissions by using a BIM-based assessment, as well as the energy load and consumption of prefabricated components, including sustainable PV panels, to enhance building efficiency and sustainability. The findings uncover the life cycle of C-House, which spans seven stages, compared with the five stages of conventional builds. Currently in its third cycle, C-House exhibits significant reductions of 70.57% in carbon emissions during the second cycle and 43.53% in the first one. This highlights the pattern showing that the prolonged reuse of prefabricated buildings leads to decreasing emissions over time. Such results underscore the potential carbon emission reductions and environmental advantages of reusing green prefabricated buildings. Furthermore, this study provides insights into the entire life cycle of the building, from inception to occupation and post-phase performance evaluation. By employing BIM for modeling, simulation, and analysis, we offer practical insights into the application of smart technologies for sustainable construction practices, significantly contributing to the advancement of green and digital construction technologies. [ABSTRACT FROM AUTHOR]

Based on the panel data of 100 cities in China's Yangtze River Economic Belt from 2010 to 2020 and the extended STIRPAT model, this paper uses SYS-GMM to empirically study the impact of green taxation on carbon emissions in the Yangtze River Economic Belt. Then, it explores the effect path of green taxation on regional carbon emissions using the intermediary effect model and analyzes the threshold characteristics of the influence of urban greening level on the regional carbon emissions of green taxation using the threshold effect model. The results show that, (1) from 2010 to 2020, the carbon emissions in China's Yangtze River Economic Belt showed a slow rising trend, and carbon emissions in the lower reaches were significantly higher than those in the middle and upper reaches. (2) Green taxation can significantly suppress carbon emissions in the Yangtze River Economic Belt. However, green taxation has the weakest inhibitory effect on carbon emissions in the upstream region and is slightly stronger in the middle reaches, with the strongest inhibitory effect on carbon emission in the downstream region. (3) From the perspective of the action path, the level of green technology innovation has a significant partial mediating effect. Green taxation mainly realizes carbon emission reductions by improving the level of urban green technology innovation, and its intermediary effect accounts for 17.6% of the total effect of green taxation on regional carbon emissions and 15.6% of the total effect of green taxation on per capita carbon emission intensity. (4) Further research shows that the emission reduction effect of green taxation is also influenced by the level of urban greening, showing a single threshold effect. Before reaching the threshold value, the inhibition effect of green taxation on carbon emission levels is relatively strong, and after crossing the threshold value, the inhibition effect is weakened. [ABSTRACT FROM AUTHOR]

Currently, a large amount of greenhouse gas emissions has caused a series of problems such as serious environmental degradation, and China is facing enormous pressure to reduce emissions. In terms of meeting the needs of people's lives, cold chain logistics has undergone faster development, and its carbon emissions are relatively high. In response to the government's advocacy for green and low-carbon concepts, some technical measures taken will increase the cost of carbon emissions. Identifying measures to reduce carbon emissions using management methods is an ongoing problem that this paper intends to solve. To address the shortcomings of the traditional cost method that cannot accurately account for the cost of each calculation object and ignores the carbon emission cost, this paper constructs an activity-based cost model for cold chain logistics enterprises to more comprehensively account for the operation cost and carbon emission cost. Then, a typical enterprise YS cold chain logistics company is used as a case study for an empirical calculation and analysis. The following conclusions are drawn: (1) the results identify the main activity centers that affect the operating costs and carbon emission costs of different customers; (2) a comparison among the total cost of each project helps to identify high-quality customers; (3) clarifying the carbon emission cost of wasting resources is beneficial for further optimizing the match between production capacity and business volume. This paper provides a path reference for enterprises to efficiently implement logistics cost management and carbon emission control, which can help enterprises cope with cost reduction and efficiency enhancement in a low-carbon environment and promote the long-term development of the logistics industry and environmental protection. [ABSTRACT FROM AUTHOR]

In the pursuit of China's carbon peak and carbon neutrality objectives, county-level areas assume a pivotal role in orchestrating diverse initiatives for low-carbon development. However, empirical evidence is limited. This paper aims to fill this gap by exploring the driving factors of carbon peak and carbon peak path at the county level, using Shandong Province as a case study. Employing data related to economic development, industrial structure, land utilization, energy consumption, and emission characteristics, a principal component analysis (PCA) was utilized to extract the following five driving factors of carbon peak: green transformation, urbanization, industrial construction, energy consumption, and environmental constraints. Subsequently, K-means clustering identified five cluster areas: (1) agricultural transformation pending area, (2) low-carbon lagging area, (3) industrial transformation area, (4) low-carbon potential areas, and (5) low-carbon demonstration area. Based on these areas, this study further elucidates spatial combination models of carbon peak within the urban system, spanning central cities, coastal cities, resource-based cities, and agricultural cities. The paper enhances comprehension of the integral role county-level areas play in achieving China's carbon reduction objectives. By providing nuanced insights into diverse developmental trajectories and spatial interactions, the study contributes to effective low-carbon strategy formulation. The findings underscore the importance of considering specific county attributes in urban areas to devise precise optimization strategies and trajectories, ultimately facilitating the realization of carbon peak goals. [ABSTRACT FROM AUTHOR]

Since 2000, China's energy intensity has shown a fluctuating downward trend. Most existing studies have attributed the decline to technological progress, and only a few studies have recognized the role of industrial structure change. In this paper, a multi-region and multi-sector CGE (computable general equilibrium) model and a numerical simulation method are used to study how technological progress and structural transformation affected the energy intensity of 30 provincial-level regions in China from 2000 to 2019. The results show the following points. (1) The contribution of technological progress to the decline in energy intensity was the highest in the central region, followed by the western region, and was the lowest in the eastern region. (2) The progress of energy technology in the agriculture and industry sectors promoted the transition of energy consumption to the service sector, thereby reducing the overall energy intensity. This effect was the strongest in the eastern region, followed by the central region, and was the weakest in the western region. (3) The progress of energy technology in the service industry promoted the transition of energy consumption to industry and agriculture, thereby enhancing the energy intensity, and this effect was the strongest in the eastern region, followed by the western region, and the weakest in the central region. The conclusion of this paper provides a theoretical basis for realizing regional carbon peaking in sequence in China. [ABSTRACT FROM AUTHOR]

With the development of EVs (Electric Vehicles) and the rapidly developing policies on low carbon and environmental protection, electric power systems and natural gas systems become increasingly larger. Under these circumstances, the V2G (Vehicle-to-grid) and the coordinated operation of an integrated electricity–gas distribution system (IEGDS), considering CO2 emissions, can play a part together in the process of energy conservation. Firstly, the V2G model is discussed; this paper presents the cost differences between out-of-order and order for the car. Secondly, the IEGDS model presents coupling constraints of gas turbines and power-to-gas. Lastly, carbon emission is considered in this paper; a carbon capture plant (CCP) captures the CO2 burning by fossil fuel in the power generation process and stores it in a carbon storage tank. This paper also considers trading with the carbon market via a carbon storage warehouse. With the cooperation of various components, a comprehensive model considers the use of V2G to store power in the IEGDS system, with consideration of the carbon trade. Numerical experiments validate the effectiveness of the combination between V2G and IEGDS, considering carbon emissions and carbon trading. [ABSTRACT FROM AUTHOR]

The field of carbon emissions in the construction industry has drawn extensive attention from researchers and practitioners due to the issue of global warming. In this study, an in-depth analysis of the research status, trends, and frontiers in the field of carbon emissions in the construction industry was carried out. The CiteSpace tool was used to visualize and analyze relevant papers from 1985 to 2023, to describe the overall knowledge structure in the field of carbon emissions in the construction industry using dual-map overlay analysis, journal co-citation network analysis, and keyword co-occurrence network analysis, to apply cluster analysis and burst detection to identify research trends in the field and the frontiers, and to analyze the scientific collaborations in the field. Further, the core issues in the field of carbon emissions in the construction industry were explored and relevant recommendations were proposed. The results are of great significance in identifying and analyzing knowledge systems and research patterns in the field of carbon emissions in the construction industry and help us to discover and understand the current deficiencies, trends, and frontiers in this field, thus providing useful suggestions and reflections for policymakers, practitioners, researchers, and other stakeholders. [ABSTRACT FROM AUTHOR]

Decoupling economic growth from carbon emissions is crucial for combating the climate crisis and promoting green development. However, a uniform approach to climate mitigation exacerbates regional disharmony. As a microcosm of China's regional heterogeneity, the Yangtze River Economic Belt (YREB) is helpful in exploring regional collaborative climate governance. This paper uses the Thiel index, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) decomposition approach to explore the decoupling of economic growth from carbon emissions in YREB from 2005 to 2019. Results indicate that the carbon intensity difference is mainly from the difference within middle-rising provinces (MRP) and western less-developed provinces (WLP). YREB exhibits strong decoupling overall, but it is not sustained. The economic growth effect significantly promotes carbon emissions, which is more prominent in MRP. The energy intensity effect plays a vital role in restraining carbon emissions. The emission factor effect signals an improved energy structure in WLP. Regional coordination is needed to achieve green development; thus, provinces should set differentiated carbon emission reduction targets, and more potent tools are recommended in major carbon emitters. [ABSTRACT FROM AUTHOR]

With the continuous development of global economic and trade activities, environmental problems have become an important factor restricting the sustainable development of all countries. How to realize the coordinated development of international trade and environmental protection has become a major issue facing the international community. Since China joined the WTO, its share of international trade has been increasing continuously. In order to deeply analyze the influence of international carbon emission trading policy on domestic carbon emissions, we use an input–output model and a GTAP analysis method to theoretically calculate the carbon emissions of the international trade of various departments in Shandong Province. At the same time, the implicit carbon emission index of various industries in 2022 is calculated through the direct energy consumption coefficient. The results show that there are significant differences in the impact of the carbon tariff system on different industries. In terms of the carbon emission index, the food processing industry showed a decrease of 18.99 Mt, while the implied carbon emission of the tobacco, textile and leather manufacturing industry reached 30.56 Mt due to the continuous expansion of trade scale. In contrast, the implied carbon emission level of the metal product processing industry reached 5.3 Mt, while the carbon emission of traditional trading industries such as coal mining was almost unaffected by international trade, and its carbon emission index reached the highest level of 5.89 in 2020. In terms of trade impact, high-trade industries such as the food processing industry are significantly affected by the carbon tariff policy, and their share has dropped from 5.89% to 3.95% in the past decade. The carbon emissions generated by GDP growth established by the GTAP model are more convincing. This model can directly reflect the energy efficiency of a region from the side. Based on the present situation of international trade, this paper analyzes the inequality of the current carbon tariff system, and puts forward some policies to optimize the energy structure to reduce carbon emissions and expand domestic demand to reduce the dependence on international trade. Through the GTAP model, we put forward policy suggestions to optimize the energy structure to reduce carbon emissions and the dependence on international trade by expanding domestic demand. [ABSTRACT FROM AUTHOR]

The design for the remanufacturing process (DFRP) is a key part of remanufacturing, which directly affects the cost, performance, and carbon emission of used product remanufacturing. However, used parts have various failure forms and defects, which make it hard to rapidly generate the remanufacturing process scheme for simultaneously satisfying remanufacturing requirements regarding cost, performance, and carbon emissions. This causes remanufactured products to lose their energy-saving and emission-reduction benefits. To this end, this paper proposes an integrated design method for the used product remanufacturing process based on the multi-objective optimization model. Firstly, an integrated DFRP framework is constructed, including design information acquisition, the virtual model construction of DFRP solutions, and the multi-objective optimization of the remanufacturing process scheme. Then, the design matrix, sensitivity analysis, and least squares are applied to construct the mapping models between performance, carbon emissions, cost, and remanufacturing process parameters. Meanwhile, a DFRP multi-objective optimization model with performance, carbon emission, and cost as the design objectives is established, and a teaching–learning based adaptive optimization algorithm is employed to solve the optimization model to acquire a DFRP solution satisfying the target information. Finally, the feasibility of the method is verified by the DFRP of the turbine blade as an example. The results show that the optimized remanufacturing process parameters reduce carbon emissions by 11.7% and remanufacturing cost by USD 0.052 compared with the original process parameters, and also improve the tensile strength of the turbine blades, which also indicates that the DFPR method can effectively achieve energy saving and emission reduction and ensure the performance of the remanufactured products. This can greatly reduce the carbon emission credits of the large-scale remanufacturing industry and promote the global industry's sustainable development; meanwhile, this study is useful for remanufacturing companies and provides remanufacturing process design methodology support. [ABSTRACT FROM AUTHOR]

Excessive carbon emissions will cause irreversible damage to the human living environment. Therefore, carbon neutrality has become an inevitable choice for sustainable development. Marine fishery is an essential pathway for biological carbon sequestration. However, it is also a source of carbon emissions. From this perspective, an in-depth assessment of the performance of carbon emissions and sinks from marine fisheries is required to achieve the goal of carbon neutrality. This paper measured the carbon emissions, carbon sinks, and net carbon emissions of marine fisheries in nine coastal provinces of China from 2005 to 2020 for the first time. Based on the calculation results, the log-mean decomposition index method was used to analyze the driving factors of net carbon emissions. The results suggested that, from 2005 to 2020, both the carbon emissions and carbon sinks of China's marine fisheries increased, and the net carbon emissions showed a downward trend. There were variations in the performance of carbon emissions, carbon sinks, and net carbon emissions in different provinces, and only Shandong could consistently achieve carbon neutrality. Fujian and Liaoning achieved carbon neutrality in 2020. In terms of the contribution of each factor, the industrial structure was the main positive driver, and carbon intensity was the main negative driver. Based on the empirical results, this paper suggested increasing the implementation of the carbon tax policy, establishing a farming compensation mechanism and promoting carbon emissions trading and international blue carbon trading. The results could give a reference for the energy conservation and emission reduction of marine fisheries while enhancing the ecological benefits of their carbon sinks and helping to achieve the carbon neutrality target. [ABSTRACT FROM AUTHOR]

The world is undergoing an irreversible shift towards clean energy. Microgrids are recognized as a key technology that holds significant potential to make a substantial difference in this regard. The paper provides a comprehensive overview of how microgrids work and their impact on climate. The research presented in this paper focuses on reducing carbon dioxide (CO2) in the main campus of Qassim University, Saudi Arabia, through the development and implementation of an engineering model that facilitates the installation of a microgrid system designed to meet the university's sustainability goals. The study aims to explore possible solutions that can reduce emissions in the administrative building (A7) at Qassim University and meet the university environmental plan. Therefore, a comprehensive study is conducted to investigate the potential reduction in emissions associated with the installation of a microgrid system. This microgrid system operates in a grid-connected mode and comprises three main components: the load, a photovoltaic (PV) system, and batteries. The results of the study indicate that the microgrid reveals a notable transition in the primary sources of electricity. Moreover, the microgrid system proves its capability to meet a substantial portion of the daily energy requirements, highlighting its efficiency and effectiveness in addressing energy needs. The findings of this study highlight the significant potential of the proposed model in curbing carbon emissions, as it demonstrates a reduction from 615.8 to 147.4 Mt of CO2. This reduction aligns with the university's commitment to sustainability and green initiatives. The computed decrease in carbon footprint emphasizes the possibility of the suggested model to encourage sustainable practices among the university community and mitigate the environmental consequences of energy usage. [ABSTRACT FROM AUTHOR]

This paper collects the nighttime light data and six control variables of 77 cities in the eastern China region from 2000 to 2020 and analyzes the spatio-temporal changes of urban sprawl and carbon emissions in the eastern China region. Using the baseline regression model, the correlation and influencing factors between urban sprawl and carbon emissions are explored. The results show that although the impact of urban sprawl on carbon emissions in the eastern China region is positive, it is the result of a trade-off of various factors. Different factors have different impacts on carbon emissions, and urban expansion of different city sizes also has different impacts on carbon emissions in the eastern China region. This paper uses nighttime light data to measure the urban sprawl index more finely, directly explores its impact on carbon emissions from the perspective of urban sprawl and conducts an in-depth analysis of multiple external factors and different city types, providing references for decision-makers to construct sustainable low-carbon city development models and low-carbon city planning systems from different dimensions. [ABSTRACT FROM AUTHOR]

Demand planning-oriented research on nighttime urban lighting provides a foundation for formulating strategies to eliminate dark areas and reduce light pollution. In this paper, Binjiang District of Hangzhou was investigated. Four factors, namely land-use type, road grade, parcel volume, and nighttime crowds, were evaluated. Based on the spatiotemporal geographic data and the urban lighting planning of Hangzhou, a calculation method for the supply and demand of urban lighting at night in Hangzhou was constructed. In this process, the current state of lighting brightness in different areas of the district were calculated and compared with the results of the total lighting demand to analyze reasonableness. The research results show that according to the actual lighting demand classification, the first to fifth levels of lighting control zones accounted for 1.84%, 19.69%, 49.61%, 21.74%, and 7.12% of the total statistical land area of the district, respectively. Focus should thus be placed on the second, third, and fourth levels of lighting control zones when covering lighting demand. Importantly, areas with unreasonable supply and demand for lighting construction accounted for 20.8% of the total statistical land area, indicating that the nighttime lighting demand and carbon emissions in the Riverside District should be adjusted and optimized. This paper proposes a research method to compare supply and demand for the planning and construction of nighttime urban lighting, which can improve the science on lighting demand measurement. [ABSTRACT FROM AUTHOR]

With the ever-increasing demand for transport in modern cities, emissions from urban transport are rising. The proportion of carbon emissions in exhaust gas accounts for a large share of society's total carbon emissions and is increasing. Therefore, urban transport has a sustainable responsibility to reduce carbon emissions. Investigating the factors that influence carbon emissions from transport has become an important practical issue that needs to be addressed. This paper adopts a "bottom-up" theoretical calculation method of transport carbon emissions and establishes the basic distribution model of inter-modal land use around rail transit stations. It clarifies the connection mode of rail transit stations and establishes the distribution model of carbon emission of stations under different building distribution modes, suggesting the planning of building distribution patterns around rail transit stations. This paper proposes a new method to analyze the influencing factors of carbon emissions at rail transit stations based on multi-modal spatial data in order to make full use of the dense characteristics of rail transit stations and reduce carbon emissions. [ABSTRACT FROM AUTHOR]

The rapid expansion of urban construction land (UCL) provides a guarantee to support rapid economic development and meet the social needs of urban residents. However, urban construction land is also an important source of carbon dioxide emissions. Therefore, it is of great research value to investigate the relationship between UCL and carbon emissions in depth. Based on this, using panel data of 57 cities in the North China Plain from 2007 to 2018, the study found that there is a strong positive correlation between UCL and CO2 emissions. It can be seen that the expansion of UCL is an important source of CO2 emissions. On the basis of this research conclusion, first, this paper uses the Tapio decoupling model to analyze the decoupling relationship between UCL and carbon emissions in the North China Plain. Then, the spatial autocorrelation analysis was applied to explore the spatial correlation characteristics of the carbon emission intensity of UCL in cities in the North China Plain. Finally, using the GTWR model to analyze the influencing factors of the carbon emission intensity of UCL, the following conclusions were drawn. In 2007–2015, the decoupling relationship performed well, but it deteriorated significantly from 2015 to 2018; in addition, there was a significant positive spatial correlation of carbon emission intensity of UCL. Various influencing factors have a significant impact on the carbon emission intensity of UCL, for example, the urbanization rate, industrial structure, economic development level, and population density have a positive impact, and environmental regulations, foreign investment intensity, land use efficiency and greenery coverage have a negative impact. The research results of this paper provide a scientific basis for making decisions and optimizing pathways to achieve carbon emission reduction from UCL in the North China Plain, as well as certain reference values for other regions to achieve low-carbon development of UCL. This is significant for exploring the optimal solution of land and carbon emissions and building a harmonious human–land relationship. [ABSTRACT FROM AUTHOR]

To provide a low-carbon economy maintenance strategy is the most challenging problem faced by pavement management authorities under the restricted budget and significant environmental repercussions. The development of a multi-objective optimization model for pavement maintenance decision making is essential to formulate pavements. Nevertheless, the existing automatic detection can only recognize and classify pavement distress. However, few studies are able to accurately determine the precise dimensions of specific distresses such as cracks and potholes, especially combined with the actual size of the image. This limitation hinders the ability to provide specific maintenance recommendations and make optimal maintenance decisions. Therefore, this paper develops a comprehensive and effective multi-objective decision-making framework for pavement maintenance. This framework consists of four distinct components: (1) recognizing the dimensions of pavement distresses based on the pavement image segmentation technique; (2) compiling a list of viable pavement maintenance strategies; (3) assessing the costs and carbon emissions of these strategies; and (4) optimizing decisions on pavement maintenance. We used the U-Net algorithm to accurately recognize the dimensions of pavement distresses, while an improved entropy-weighted TOPSIS model was proposed to determine the optimal pavement maintenance strategy with the lowest cost and carbon emissions. The results indicated that the pavement distress dimension recognition model achieved a high accuracy of 96.88%, and the TOPSIS model identified the optimal maintenance strategy with a score of 99.16. This maintenance strategy achieved a substantial reduction of 30.80% in carbon emissions and a cost reduction of 20.81% compared to the highest values among all maintenance strategies. This study not only provides a scientifically objective method for making pavement maintenance decisions but also offers specific, quantifiable maintenance programs, marking a stride towards more environmentally friendly and cost-effective road maintenance. It also contributes to the sustainability of pavement maintenance. [ABSTRACT FROM AUTHOR]

Life cycle assessment (LCA) plays an increasingly important role in environmental management, particularly in promoting energy and carbon-conscious practices across various disciplines. This review provides an overview of the latest innovations and potential benefits of integrating LCA into ecological slope treatment strategies. This study explores new developments in LCA methodology and its application to slope treatment, aiming to improve the integration of infrastructure development and environmental stewardship. Through an extensive review of over 120 peer-reviewed journal articles and a critical analysis of the intersection of LCA with slope treatment, this paper identifies innovative techniques that have the potential to significantly reduce the environmental impact of slope management. The review emphasizes advanced LCA practices that quantify and mitigate carbon emissions throughout the life cycle stages of slope treatments. Key findings demonstrate that LCA enhances the methodological rigor in assessing ecosystem services and impacts, and reveals new strategies that emphasize the importance of ecological considerations in infrastructure projects. Future research directions focus on refining LCA data acquisition and promoting a standardized knowledge base to support precision in ecological impact assessments. In conclusion, the adoption of LCA in slope treatment is imperative for aligning industry practices with global sustainability targets, emphasizing the importance of integrating uncertainty analysis and long-term impact assessments to bolster the credibility of LCA outcomes. [ABSTRACT FROM AUTHOR]

The rapid growth of urbanization in China has led to a substantial escalation in the demand for civil aviation services, consequently propelling China to the third-largest contributor of carbon emissions within the aviation sector. Using the 2012–2021 data on takeoffs and landings of civil aviation aircraft in China, the aircraft engine emission factor database of the Base of Aircraft Data (BADA) from EUROCONTROL, this paper investigates the spatial-temporal distribution characteristics of atmospheric pollutants, primarily carbon emissions from Chinese civil aviation aircraft in 19 megacities. The results indicate that (1) China's aviation CO2 emissions equivalent between 2012 and 2022 has been on an upward trajectory, peaking at 186.53 MT in 2019 with an average annual growth of 12.52%. The trend, albeit momentarily interrupted by the COVID-19 pandemic, appears to persist. (2) CO2 constitutes the highest proportion of aircraft emissions at 83.87%, with Cruise Climb Descent (CCD) cycle emissions accounting for 96.24%. CO2 and NOX, with the highest increase rates in the CCD and Landing and Takeoff (LTO) phases, respectively, are identified as the chief culprits in aviation-related greenhouse effects. (3) There is a marked spatial imbalance, with 19 megacities contributing 62.08% of total CO2 emissions, compared to the 207 least-emitting cities contributing just 9.29%. (4) The pattern of city carbon emissions is changing, with rapid growth rates in the western cities of Xinjiang, Tibet, Shaanxi, and Guizhou, and varied growth rates among megacities. The implications of this study emphasize the urgency for advancements in aviation fuel technology, rigorous management of CCD phase pollutants, strategic carbon emission controls in populous cities, fostering green aviation initiatives in western regions, diverse carbon mitigation tactics, and strengthening the precision and surveillance of aviation carbon accounting systems. Collectively, this study paints a grand picture of the complexities and challenges associated with China's urban sprawl and aviation carbon emissions. [ABSTRACT FROM AUTHOR]

Design for remanufacturing (DfRem) is to consider the remanufacturability of the product at the design stage, which can improve the remanufacturability of the product. Moreover, the DfRem solution has a significant impact on the carbon emissions of manufacturing processes. Unreasonable design solutions can significantly increase carbon emissions from manufacturing processes. However, there is no direct link between DfRem solutions and remanufacturability as well as manufacturing carbon emissions, which makes it difficult to quickly generate a rational DfRem solution that can enhance product remanufacturability and reduce carbon emissions simultaneously. To this end, this paper proposes an intelligent design method for remanufacturing that considers remanufacturability and manufacturing carbon emissions. First, an intelligent DfRem framework is constructed, which includes information acquisition, virtual model construction of the DfRem solution, and multi-objective optimization of the design solution. Then, the design matrix and sensitivity analysis are used to construct the mapping models between remanufacturability, carbon emissions, and DfRem parameters. Meanwhile, a multi-objective optimization model of DfRem with remanufacturability requirements and carbon emissions as design objectives is constructed, and an adaptive teaching and learning optimization algorithm is applied to solve the optimization model to obtain a DfRem solution that satisfies the objective information. Finally, the feasibility of the method is verified by DfRem of the injection mold as an example. [ABSTRACT FROM AUTHOR]

Global warming is one of the most compelling environmental threats today, as the rise in energy consumption and CO2 emission caused a dreadful impact on our environment. The data centers, computing devices, network equipment, etc., consume vast amounts of energy that the thermal power plants mainly generate. Primarily fossil fuels like coal and oils are used for energy generation in these power plants that induce various environmental problems such as global warming ozone layer depletion, which can even become the cause of premature deaths of living beings. The recent research trend has shifted towards optimizing energy consumption and green fields since the world recognized the importance of these concepts. This paper aims to conduct a complete systematic mapping analysis on the impact of high energy consumption in cloud data centers and its effect on the environment. To answer the research questions identified in this paper, one hundred nineteen primary studies published until February 2022 were considered and further categorized. Some new developments in green cloud computing and the taxonomy of various energy efficiency techniques used in data centers have also been discussed. It includes techniques like VM Virtualization and Consolidation, Power-aware, Bio-inspired methods, Thermal-management techniques, and an effort to evaluate the cloud data center's role in reducing energy consumption and CO2 footprints. Most of the researchers proposed software level techniques as with these techniques, massive infrastructures are not required as compared with hardware techniques, and it is less prone to failure and faults. Also, we disclose some dominant problems and provide suggestions for future enhancements in green computing. [ABSTRACT FROM AUTHOR]

As the economy continues to grow, greenhouse gas emissions are increasing, and people are paying more attention to issues related to carbon emissions. The construction of information infrastructure has also become an important support for development in the new era. Therefore, to explore whether information infrastructure construction can reduce carbon emissions, this paper conducts a series of tests based on panel data from 30 provinces in China from 2010 to 2019. The empirical results show that, in addition to directly reducing carbon emissions, the construction of information infrastructure can also affect carbon emissions through technological innovation. According to the heterogeneity test, we find that the construction of information infrastructure has better emission reduction effects for the eastern region, provinces with a higher technological innovation level, and provinces with a higher carbon emission intensity. The results of this paper provide strong support for the mitigation of global warming. [ABSTRACT FROM AUTHOR]

Based on the Web of Science core database, this paper used bibliometric analysis to analyze 4408 academic works related to carbon finance from 1992 to 2021. This work shows that the number of publications on carbon finance-related research has increased rapidly; the Journal of Cleaner Production is the most productive journal. China boasts the most significant number of publications, while the United States has the most intensive cooperation with other countries. The Chinese Academy of Sciences is the most productive and influential independent institution, and Chinese authors make up the highest proportion of the top 20 most prolific authors. We can summarize the main research directions in carbon finance through keyword analysis: carbon capture, economic growth, carbon sequestration, financial development, modeling, and carbon price forecasting. Research related to the impact of energy consumption, renewable energy, and urbanization on carbon emissions may become a hot spot for future research in carbon finance. Through an in-depth analysis of the development over the past 30 years and future trends of carbon finance, this paper can provide some reference for future research, which is of great significance in promoting carbon emission reduction. [ABSTRACT FROM AUTHOR]

Due to the emission of carbon dioxide and other greenhouse gases, the global climate is warming. As the world's biggest emitter of carbon emissions, China faces a more severe challenge in reducing carbon emissions than developed countries. A reasonable prediction of the carbon peak in China will help the government to formulate effective emission reduction paths. This paper analyzes the changes in carbon emissions in China from 2004 to 2020, uses the STIRPAT model and scenario analysis method to predict carbon emissions from 2021 to 2030, and then calculates the carbon efficiency during carbon peaking to select the most effective carbon peak path for China. The results show that China's carbon emissions increased year by year from 2004 to 2020. Under the baseline scenario, China is unlikely to reach its carbon peak before 2030. Under the regulatory scenarios, China can reach its carbon peak before 2030. The peak values from high to low are seen with the rapid development-weak carbon control scenario, rapid development-intensified carbon control scenario, slow development-weak carbon control scenario and slow development-intensified carbon control scenario, respectively. Correspondingly, China will peak its carbon emissions in 2029, 2028, 2028 and 2028, respectively, according to these scenarios. The carbon efficiency under the rapid development-weak carbon control scenario is the highest, which means that accelerating the growth rate of population, GDP and urbanization while moderately carrying out the transformation of industrial structure and energy structure is an effective way to achieve the goal of "carbon peak by 2030". [ABSTRACT FROM AUTHOR]

Urban agglomerations are becoming an increasingly important factor in advancing regional development and reshaping a new pattern of regional competition. However, few studies are focused on the impact of expanding urban agglomerations on reducing carbon emissions and its possible mechanism. Based on 285 city-level panel data from 2006 to 2017, this paper uses a staggered Difference-in-Differences (DID) model to explore the reduction effect and its possible mechanism of sustainable regional development policy, characterized by urban agglomeration expansion policy in the Yangtze River Delta, on carbon emissions with policy shocks in 2010 and 2013. The results are as follows: (1) The urban agglomeration expansion policy shows a significant marginal contribution to the reduction of carbon emissions, especially for the later joined (new) cities, and the reduction effect is particularly significant in the first and third years after the expansion, indicating that there are significant short-term and long-term reduction effects of the expansion policy. (2) The heterogeneities of reduction effect among three provinces are significant. Zhejiang Province enjoys the largest proportion carbon emission reduction effect, followed by Anhui and Jiangsu provinces. To be specific, urban agglomeration expansion in Zhejiang Province reduced carbon emissions and carbon emissions intensity in the overall, incumbent cities and new cities, while it only increased the total carbon emissions of the incumbent cities in Jiangsu province. (3) The heterogeneities of reduction effect brought by 2010 and 2013 are also significant. The urban agglomeration expansion policy in 2010 reduced carbon emissions on the whole cities and the incumbent cities with later joined cities excluded, while it had a significant reduction effect on the total, incumbent cities, and the new cities in 2013. (4) There are two possible mechanisms of this reduction effect. One is the strengthening of economic ties and enhanced environmental synergy between governments, called the market integration mechanism, which only has a significant effect on carbon emission reduction in the incumbent cities. Another is through the upgrade of the structure of regional industries, which has a significant effect in both the incumbent and new cities. These findings suggest that when formulating urban agglomerations polices, governments must take into account the carbon emissions effect, and advance the upgrading of industrial structure in the urban agglomeration. [ABSTRACT FROM AUTHOR]

As environmental awareness continues to grow and government policies provide incentives, electric vehicles (EVs) are becoming more widely used in logistics distribution. Considering green power trading and carbon emissions, this paper addresses the green vehicle routing problem (GVRP) and constructs an electric vehicle path model with time windows to minimize the total cost. To solve the model, a hybrid adaptive genetic algorithm (HAGA) is proposed. An improved nearest-neighbor algorithm is adopted to improve the quality of the initial population, and the adaptive crossover and mutation operators are introduced to achieve the better solution. In addition, based on the Schneider case, HAGA is used to solve the models with and without considering green power trading separately, and the results show that considering green power trading can reduce the total cost by 3.22% and carbon emissions by 23.38 kg. Finally, the experimental simulations further prove that with the increase in case size, HAGA can effectively reduce total cost. And it is beneficial for the popularization of electric vehicles in logistics distribution. [ABSTRACT FROM AUTHOR]

To meet the demand for constructing a market mechanism that adapts to the integrated energy system and promotes market-oriented reforms in the energy sector, in-depth research on integrated energy trading strategies is required. This study focused on the integrated energy trading problem and clarify the relationships among participants in the integrated energy market. A regional integrated energy system model was established that enables trading of electricity, gas, heat, and cold, and propose a integrated energy trading strategy based on the carbon emissions/green certificate equivalence interaction. Firstly, the trading process of carbon emissions and green certificates, the underlying representation of green attributes, and market transaction prices are analyzed. Combining with a tiered carbon trading system that includes rewards and penalties, a carbon emissions/green certificate equivalence interaction mechanism is constructed. Secondly, the paper utilized the flexible characteristics of loads within the industrial park to establish a integrated energy demand response model for electricity, heat, and cold. Finally, with the objective of minimizing regional operating costs, a integrated energy trading model considering the carbon emissions/green certificate equivalence interaction mechanism was developed. In the simulation, the operating cost of the system is reduced by 4%, and the carbon emission is reduced by 11.4%, which verifies the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Sewage treatment carbon emissions are one of the notable sources of total carbon emission in industrial parks. In order to explore the evolutionary characteristics of sewage treatment carbon emission in industrial parks and its coupling relationship with industrial economic development, based on the quarterly sewage quality monitoring data and regional economic development data of an energy and chemical industry park in Northern Shaanxi from 2016 to 2020, this paper analyzes the evolutionary characteristics of sewage treatment carbon emissions and the coupling relationship between economic development in the industrial parks by using the Intergovernmental Panel on Climate Change carbon emission accounting method and the coupling coordination degree model. The results show that the total carbon emission of sewage treatment in the industrial parks is increasing year by year, and the indirect carbon emissions occupy the dominant position. In 2020, the direct and indirect carbon emissions in the sewage treatment process accounted for 2.4% and 97.6% of the total carbon emission, respectively. It was found that the coupling and coordination relationship between sewage treatment carbon emissions and the economy has experienced the transformation process of serious imbalance—lagging economic development, lagging carbon emission and lagging economic development. In the past five years, the coordinated development degree of the two systems has increased year by year, and the benign mutual feedback mechanism between the two systems has gradually formed. However, regional economic development has lagged due to the impact of the COVID-19 epidemic, so speeding up regional economic development while protecting the environment is recommended. [ABSTRACT FROM AUTHOR]

Global climate change is one of the major challenges facing the world, and the spatial optimization of land use patterns has been regarded as critical in realizing carbon mitigation. In this study, the linear programming model and the Markov Chain model are integrated in different scenarios to optimize land use structure for low-carbon development. The land use pattern is then simulated through the adjusted convolutional neural network and cellular automata model, taking Guangzhou City as the case study area. The results reveal that construction land with high economic efficiency will increase its area, and the reaming types will experience slight changes, in 2035 in the natural development scenario and the economic priority scenario. Ecological land such as forest land, grassland, and water is partly occupied by construction land in the urban–rural fringe areas. The total carbon emissions decrease by 2.32% and 1.57% in these two scenarios. In the low-carbon-oriented scenario, the expansion of construction land is restricted, and the forest land and grassland undergo great expansion. The total carbon emission decreases by 18.95%—a figure much larger than that in the natural development scenario and the economic priority scenario. Our paper embeds the needs and constraints in land spatial planning into the spatial optimization of the land use pattern, which provides valuable references for low-carbon city development in the future. [ABSTRACT FROM AUTHOR]