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This paper studies the optimal vehicle fleet planning and collaboration problem for a fuel vehicle (FV) transport service provider, a commercial electric vehicle (CEV) transport service provider, and a carbon emission treatment agency under carbon neutrality. The FV transport service provider pays a fixed fee or a portion of its sales revenue to a carbon emission treatment agency in exchange for technology to reduce its carbon emissions, and it can adopt three strategies (i.e., no emission reduction, purchasing technology for emission reduction, and entrusting a carbon emission treatment agency). We derive each party's optimal fleet size, price, and profit in the three scenarios. Our results suggest that carbon emission reduction strategies may improve the market performance of the FV transport service provider. Then, we find no certain strategy is always preferable to another: the optimal cooperation strategy between the transport service provider and carbon emission treatment agency depends on the fixed technology fee, ratio of revenue sharing, government penalty, the transport service market potential, and consumer green preference, as well as the cost per CEV. This paper gives the transport service provider and carbon emission treatment agency a full picture of whether, when, and how to collaborate in green commerce. [ABSTRACT FROM AUTHOR]

China has committed to achieve net carbon neutrality by 2060 to combat global climate change, which will require unprecedented deployment of negative emissions technologies, renewable energies (RE), and complementary infrastructure. At terawatt-scale deployment, land use limitations interact with operational and economic features of power systems. To address this, we developed a spatially resolved resource assessment and power systems planning optimization that models a full year of power system operations, sub-provincial RE siting criteria, and transmission connections. Our modeling results show that wind and solar must be expanded to 2,000 to 3,900 GW each, with one plausible pathway leading to 300 GW/yr combined annual additions in 2046 to 2060, a three-fold increase from today. Over 80% of solar and 55% of wind is constructed within 100 km of major load centers when accounting for current policies regarding land use. Large-scale low-carbon systems must balance key trade-offs in land use, RE resource quality, grid integration, and costs. Under more restrictive RE siting policies, at least 740 GW of distributed solar would become economically feasible in regions with high demand, where utility-scale deployment is limited by competition with agricultural land. Effective planning and policy formulation are necessary to achieve Chinas climate goals.

This special issue of the International Journal of Production Research, focuses on the 'Carbon Neutrality' and 'SCM'. Nine articles have been selected for this special issue, and they cover various aspects to understand the manifestation of 'Carbon Neutrality' in supply chains, and to further illuminate how to achieve 'Carbon Neutrality' with supply chain innovation. This editorial provides a brief overview of the research domain, then introduces each article in the context of the state-of-the-art and highlights the contributions of selected papers to the field. Finally, the research perspectives are discussed. [ABSTRACT FROM AUTHOR]

Food supply chains hold significant embodied carbon emissions that need to be mitigated and neutralized. This study aimed to explore the historical Greenhouse Gas (GHG) emissions associated with household food consumption at a local scale i.e. across the eight English regions and the four nations that comprise the United Kingdom (UK). UK EatWell guidelines were used to explore the potential change in emissions and food costs in a scenario of transitions to healthier diets across the study areas. These emissions were calculated based on food consumption data before the advent of the Covid-pandemic i.e. between the years 2001 and 2018. Spatial data analysis was used to explore if the study areas had any significant correlations with respect to the emissions during the study period. The results displayed a potential reduction in GHG emissions for all study areas in the explored scenario. Further impacts include a reduction in household food costs across a majority of the areas during the study period. However, a consistent trend of significant correlations among the study areas was absent. This study concludes that local or regional policymaking should take precedence over national regulations to achieve healthier diets that are both carbon-neutral and affordable for the households. [ABSTRACT FROM AUTHOR]

Enhancing terrestrial carbon (C) stock through ecological restoration, one of the prominent approaches for natural climate solutions, is conventionally considered to be achieved through an ecological pathway, i.e., increased plant C uptake. By conducting a comprehensive regional survey of 4279 1 × 1 m² plots at 517 sites across China's drylands and a 13-y manipulative experiment in a semiarid grassland within the same region, we show that greater soil and ecosystem C stocks in restored than degraded lands result predominantly from decreased surface soil C loss via suppressed wind erosion. This biophysical pathway is always overlooked in model evaluation of land-based C mitigation strategies. Surprisingly, stimulated plant growth plays a minor role in regulating C stocks under ecological restoration. In addition, the overall enhancement of C stocks in the restored lands increases with both initial degradation intensity and restoration duration. At the national scale, the rate of soil C accumulation (7.87 Tg C y-1) due to reduced wind erosion and surface soil C loss under dryland restoration is equal to 38.8% of afforestation and 56.2% of forest protection in China. Incorporating this unique but largely missed biophysical C-conserving mechanism into land surface models will greatly improve global assessments of the potential of land restoration for mitigating climate change. [ABSTRACT FROM AUTHOR]

Steam generating heat pump (SGHP) is a key technology for industrial decarbonization. For comprehensive evaluation of the feasibility and reliability of SGHP in different industrial sector, the work develops a thorough evaluation model for assessing the performance of SGHP by considering waste heat recovery, CO2 trading value, and pollutant emission cost, in addition to the conventional evaluation criteria. This work presents a thorough comparison of the thermodynamic performance and sustainability of various types of SGHPs across different industrial sector. Additionally, the conflicting relationships between the coefficient of performance (COP) and exergy efficiency are balanced through the application of the technique for order preference by similarity to ideal solution (TOPSIS). The results show that all the indexes of SGHP connected to an open heat pump (SGHPO) with different application scenarios are higher than those of SGHP connected to a flash tank (SGHPF). At the most unfavorable operating condition of the system, the COP minimum value is 1.31 and the exergy efficiency minimum value is 20.42%. These results indicate that replacing the coal-fired boiler with SGHP is feasible and the work could provide theoretical guidance for optimal design and equipment manufacture. Highlights: • A more comprehensive SGHP valuation model that takes into account the waste heat recovery, CO2 trading value, and pollutant emission cost is proposed. • The SGHPs are classified, compared, and analyzed comprehensively, with design and optimization recommendations provided. • Optimal balance between COP and exergy efficiency of a SGHP using the TOPSIS method. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality and sustainable development, innovative solar‐to‐fuel systems have been designed through the integration of solar energy harvesting and electrochemical devices. Over the last decade, there have been notable advancements in enhancing the efficiency and durability of these solar‐to‐fuel systems. Despite the advancements, there remains significant potential for further improvements in the performance of systems. Enhancements can be achieved by optimizing electrochemical catalysts, advancing the manufacturing technologies of photovoltaics and electrochemical cells, and refining the overall design of these systems. In the realm of catalyst optimization, the effectiveness of materials can be significantly improved through active site engineering and strategic use of functional groups. Similarly, the performance of electrochemical devices can be enhanced by incorporating specific additives into electrolytes and optimizing gas diffusion electrodes. Improvements in solar harvesting devices are achievable through efficient passivant and self‐assembled monolayers, which enhance the overall quality and efficiency of these systems. Additionally, optimizing the energy conversion efficiency involves the strategic use of DC converters, photoelectrodes, and redox media. This review aims to provide a comprehensive overview of the advancements in solar‐powered electrochemical energy conversion systems, laying a solid foundation for future research and development in the field of energy sustainability. [ABSTRACT FROM AUTHOR]

The carbon neutral policy restrains the carbon emissions of product family manufacturers, which incurs additional costs for manufacturers. In previous studies of product family supplier selection, the dilemma of carbon neutrality faced by manufacturers was rarely researched. Therefore, this study puts forward an intelligent optimisation method for product family supplier selection under carbon neutral constraints, which assists manufacturers in satisfying carbon neutrality constraints while minimising total production costs. Firstly, the data representation models of product family are constructed by using information ontology technology, and then the candidate suppliers that meet the manufacturer's performance requirements are mined by semantic similarity. Secondly, by calculating the configuration cost and carbon footprint of the product family, the configuration cost-carbon neutral cost model (CC-CNC model) of the manufacturer is established with the goal of minimising the manufacturer's total cost, and then the genetic algorithm is employed to solve the model, thus the optimal supplier selection scheme is mined. The feasibility of the proposed method is demonstrated by supplier selection for water-cooled fan product family, which guides the manufacturer to minimise the cost by selecting the best supplier scheme and taking reasonable carbon neutral measures, contributing to the manufacturer's low-carbon production and economic benefits. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of Micro Gas Turbines (MGTs) in the global shift towards low-carbon energy systems, particularly focusing on their integration within microgrids and distributed energy generation systems. MGTs, recognized for their fuel flexibility and efficiency, have yet to achieve the commercialization success of rival technologies such as Internal Combustion Engines (ICEs), wind turbines, and solar power (PV) installations. Through a comprehensive review of recent techno-economic assessment (TEA) studies, we highlight the challenges and opportunities for MGTs, emphasizing the critical role of TEA in driving market penetration and technological advancement. Comparative analysis with ICE and RES technologies reveals significant gaps in TEA activities for MGTs, which have hindered their broader adoption. This paper also explores the learning and experience effects associated with TEA, demonstrating how increased research activities have propelled the success of ICE and RES technologies. The analysis reveals a broad range of learning and experience effects, with learning rates (α) varying from 0.1 to 0.25 and experience rates (β) from 0.05 to 0.15, highlighting the significant role these effects play in reducing the levelized cost of energy (LCOE) and improving the net present value (NPV) of MGT systems. Hybrid systems integrating MGTs with renewable energy sources (RESs) and ICE technologies demonstrate the most substantial cost reductions and efficiency improvements, with systems like the hybrid renewable energy CCHP with ICE achieving a learning rate of α = 0.25 and significant LCOE reductions from USD 0.02/kWh to USD 0.017/kWh. These findings emphasize the need for targeted TEA studies and strategic investments to unlock the full potential of MGTs in a decarbonized energy landscape. By leveraging learning and experience effects, stakeholders can predict cost trajectories more accurately and make informed investment decisions, positioning MGTs as a competitive and sustainable energy solution in the global energy transition. [ABSTRACT FROM AUTHOR]

Soil carbon sequestration is listed by the United Nations Framework Convention on Climate Change as one of the key ways to achieve long-term "carbon neutrality" in the context of global warming. Soil carbon sequestration is a complex biogeochemical process that involves plants, microbes, and rock minerals at its core. Yet, its regulation mechanisms and promotion pathways remain unclear. This paper reviews recent progress in the related domestic and international research and provides an overview of the key processes and mechanisms of soil carbon sequestration. The main pathways for enhancing soil carbon sequestration (including plant inputs, mineral protection, microbial transformation, and rock weathering) are summarized. The paper also discusses and synthesizes how advanced biogeochemical methods and technologies may be employed to explore soil carbon sequestration mechanisms and potentials. The overall aim of this review is to improve our understanding of soil carbon sequestration as a nature-based solution to combatting climate change from the biogeochemistry perspective, and to highlight the role of fundamental research in Earth Sciences in helping to achieve China's carbon neutrality goals. [ABSTRACT FROM AUTHOR]

The rapid expansion of global urbanization and industrialization has significantly increased the discharge of municipal wastewater, leading to issues of carbon emissions and energy consumption when using traditional biological treatment processes. This study proposes an innovative process that couples iron coagulation with microalgal–bacterial granular sludge (MBGS), with optimization and regulation based on operational conditions. The study found that the coagulation performance achieved optimal levels at an iron concentration of 25 mg/L and an anionic polyacrylamide concentration of 1 mg/L, which could remove approximately 61% of the organics and over 90% of phosphorus from raw wastewater. By relying on heterotrophic microorganisms, such as Proteobacteria, Bacteroidota, and Chloroflexi, along with the synergistic interaction between algae and bacteria, the subsequent MBGS process could further effectively remove organics over the day-night cycles. Moreover, the addition of inorganic carbon sources of NaHCO3 increased the abundance of denitrification-related genes, reduced the accumulation of nitrite within MBGS, and led to effective total nitrogen removal. These results indicate that the iron coagulation–MBGS coupling process can efficiently treat municipal wastewater, offering potential for environment-sustainable pollutant removal with reduced energy consumption. These findings provide valuable insights for the practical engineering application of MBGS in wastewater treatment systems aiming for carbon-neutral wastewater treatment. [ABSTRACT FROM AUTHOR]

To meet the temperature goal set by the Paris Agreement, cumulative CO2 emissions must be kept below 300 GtCO2. Road transportation accounted for approximately 18% of the CO2 emissions from fuel combustion in 2017. Electric vehicles (EVs) have been rapidly adopted by environmentally conscious consumers in many countries to reduce CO2 emissions. EVs have lower emission intensities than do internal combustion engine vehicles (ICEVs) in most parts of the world, except where the penetration of renewable energy is low in the energy production mix. In such places, the CO2 emissions of EVs are larger than those of ICEVs. Despite the obvious need to increase renewable energy sources to reduce CO2 emissions, Japan and many other countries around the world have yet to shift away from fossil fuels. This is due in part to carbon lock-in, which refers to prior decisions related to technologies and infrastructure that constrain the implementation of better paths toward low-carbon technologies. Coal-fired power plants are the most problematic in terms of carbon lock-in because of their high carbon intensities and long physical lives. In addition, because carbon lock-in by coal-fired power plants has a significant impact on the embodied CO2 intensity of grid power, it impacts society through products that use electric power. In this study, we propose a hybrid simulation model of lifecycle simulation and replacement simulation, considering carbon lock-in by coal-fired power plants. In the replacement simulation, we simulated the replacement of end-of-life coal- and oil-fired power plants with renewable energy power plants using a probability called the lock-in rate and estimated the changes in the embodied CO2 intensity of grid power in Japan. In the lifecycle simulation, we evaluated cumulative CO2 emissions from entire product lifecycles of ICEVs and EVs based on three different EV diffusion scenarios. The results showed that the lock-in rate of coal-fired power plants strongly affects the decarbonization effect due to the market diffusion of EVs. [ABSTRACT FROM AUTHOR]

Purpose: Calculating an organization's carbon footprint is crucial for assessing and implementing emission reductions. Although Finnish higher education institutions (HEIs) aim for carbon neutrality by 2030, limited research exists on plans to reach a similar target in any country. This paper aims to address the shared and individual challenges Finnish HEIs have with carbon footprint calculations, reductions, resources and offsetting. Design/methodology/approach: A survey was targeted to sustainability experts in all 38 HEIs in Finland to identify key patterns and trends in the focus fields of the study. SWOT analysis was used to classify main strengths, opportunities, weaknesses and threats, based on which a series of policy recommendations was drafted. Findings: Finnish HEIs are committed to carbon footprint tracking (97%, annually by 87%). The lack of standardization and the number of external stakeholders complicate accounting indirect emissions, impeding comparability and reliability. Only 39% had set separate emission reduction targets, suggesting a preference for carbon footprint over other environmental impact indicators. Insufficient monetary and human resources emerged in 23% of institutions, especially those smaller in size. Only 52% had clear offsetting plans, with shared concerns over trust and responsibility. Originality/value: By including both research universities and universities of applied sciences, the findings provide an unprecedented outlook into the entire Finnish HEI sector. The policy recommendations guide HEIs both locally and globally on how to improve their transparency and scientific integrity, reflect on core successes and weaknesses and how they complete their objectives of education, research and social impact while promoting stronger sustainability. [ABSTRACT FROM AUTHOR]

In recent decades, the Environmental policy and environmental innovation are becoming the central policy instruments aimed at carbon neutrality. This empirical study scrutinizes the role of environmental policy and eco‐innovation on CO2 emissions for G7 countries. The study employs second‐generation panel data econometric methods along with panel quantile regression spanning from 1990 to 2019. The empirical findings infer that environmental policy and eco‐innovation significantly mitigate CO2 emissions in the long run. While, panel quantile regression also infers that environmental policy is negatively significant in all quantiles, but eco‐innovation is negatively significant from the 40th to 70th quantiles and insignificant in all other quantiles. The estimated results may further reinforce the policymakers in G7 countries on the promotion of green policy and eco‐innovation in carbon neutrality targets. [ABSTRACT FROM AUTHOR]

The direct valorization of carbon dioxide (CO2) into value‐added chemicals offers an efficient and attractive approach to promoting carbon neutrality. Among the available methods, the electrocatalytic CO2 reduction reaction (eCO2RR) for producing multicarbon products (C2+) is gaining attention owing to its simplicity. However, achieving selective control over product formation remains a challenge. One key issue is the lack of a reliable correlation between the physicochemical properties of electrocatalytic materials and their activity and selectivity. To address this gap, we conducted a model study in which carbonized CuxZny@C materials, derived from metal‐organic frameworks (MOFs), were synthesized with varying Cu/Zn ratios. The pyrolyzed bimetallic MOFs retained key properties of the original MOFs while also developing new characteristics. These subtle changes in physicochemical properties influenced product selectivity. The findings of our study revealed that higher Zn doping favors the formation of single‐carbon (C1) products, whereas it is less favorable for multicarbon (C2+) products. Optimizing the Cu/Zn ratio was emphasized through characterization techniques, which will help guide the design of improved electrocatalytic systems for the eCO2RR process. [ABSTRACT FROM AUTHOR]

This study investigates the role of green technology implementation (GTI) based on artificial intelligence (AI) at the household level to achieve carbon neutrality by addressing gaps in the existing research. The research focuses on understanding how education on green consumption preferences, green invention and emission impacts can optimally influence AI-based GTI decisions. Through behavioural analysis at the household level, this study quantifies the effects of education and preferences on emissions and proposes subsidies as accelerators for carbon–neutral transitions. Furthermore, the study employs regression analysis and simulation-based optimisation, which are then validated against prior methodologies, with a focus on Punjab, Pakistan. Utilising a simple random sampling technique, approximately 1000 households were surveyed to represent the province's diverse demographics comprehensively. Findings reveal that higher education levels correlate with less enthusiasm for AI-based GTI. Simulations measured optimal subsidy levels by striking a balance between encouraging green behaviour and technological adoption. By integrating diverse factors and AI-based GTI optimisation, this study defines important thresholds for education and subsidies, thus highlighting their pivotal role in advancing AI-based green technologies and sustainable household practices. This research significantly enhances the understanding of the complex relationship between AI-based GTI decisions and educational influences, thereby contributing to the advancement of environmental sustainability. [ABSTRACT FROM AUTHOR]

For investigating the effect of the quality composition of CH refrigerant R1270/R600 (0.6:0.4) and (0.7:0.3) on the performance of a dual temperature chiller, the experiment measured at constant in and out temperatures of the refrigeration water. The results indicate that under the condensation and evaporation temperature remain constant, when the quality fraction of low boiling R1270 raises, the maximum total COP of the refrigeration system increases from 3.36 to 7.36, while the maximum COP at low temperatures does not change much, and the maximum COP at high temperatures increases from 2.02 to 5.95. The percentage of 1 evaporator capacity to total refrigeration capacity has decreased from the maximum value of 44.54% to 20.91%. The percentage of 2 evaporator capacity to total refrigeration capacity has increased from the maximum value of 68.52% to 83.19%. The compression ratio decreases. When the operating conditions changed, the maximum COP of the two components occurs at the temperatures of 1 chilled water are the highest and the temperatures of 2 chilled water are the lowest. The maximum consumption of the system compressor power is 0.99KW, and the maximum discharge temperature is 75.81℃. The finding can provide guideline for the application of the units as a substitute for refrigerants. [ABSTRACT FROM AUTHOR]

Reducing carbon dioxide emissions is one of the largest energy and environmental challenges currently faced globally. To achieve carbon neutrality, the development of new technologies and simultaneous improvement of conventional technologies are required. Catalysis, which determines the success or failure and efficiency of the process, is at the center of addressing these problems. Innovative advancements in catalysis have been accomplished through the extensive research on catalytic materials. Oxygen storage materials with oxygen storage capacity (OSC) have been widely applied in supports and active cocatalysts for energy and environmental catalytic applications. This review provides knowledge on the extended applications (reforming, water-gas shift reaction, and partial oxidation of methane (POM) for high-value-added chemicals, including hydrogen production, deoxygenation of fatty acids for second-generation biofuel production, selective catalytic reduction of NOx with NH3, hydrocarbon (HCs) oxidation for emission control, CO oxidation for vehicle exhaust control and purification of gaseous product fuel, and soot oxidation for the removal of motor-type pollutants) of these materials, which are mainly used as three-way catalysts (TWC) in automotive catalysis, to the carbon-neutral field. In particular, this study focuses on the physico-chemical properties that are closely synergistic with OSC, such as reducibility, dispersion, surface acid/base properties, and physical properties, such as surface structure or morphology. [ABSTRACT FROM AUTHOR]

In emerging economies like Kuwait, tourism funds national development and sustains local livelihoods. The rapid rise of tourism in several nations may have serious environmental effects due to increased energy usage that increases carbon dioxide (CO2) emissions and worsening global warming. Due to climate change’s growing effects on the environment, several efforts have been made by numerous countries worldwide to achieve carbon neutrality and environmental sustainability. Moreover, effective energy production prediction is crucial to establish an equilibrium between traditional and clean energy sources. However, there is a research gap investigating the environmental impacts of tourism within the framework of energy-economy-environment nexus in Kuwait’s context that propelled the development of this pioneering investigation. The present study’s objective is to determine how economic growth, energy consumption, and tourism affect carbon emissions in Kuwait. This study analyzes Kuwait’s time series data from 1995 to 2019 by using the autoregressive distributed lag (ARDL) method that analyzed the components’ relationships, allowing for long-term and short-term dynamics. The results show that increasing economic growth, energy consumption, and tourist arrivals increase CO2 emissions in Kuwait. This article proposes policies to achieve carbon neutrality in Kuwait by expanding renewable energy use and promoting sustainable tourism to boost the economy. [ABSTRACT FROM AUTHOR]

Governments globally have prioritized carbon neutrality and reduction as a response to the intensifying menace of climate change. These objectives align with the United Nations Sustainable Development Goals (UNSDG-13), stressing the imperative to take decisive action on climate change. Thus, this study aimed to assess the impact of oil price uncertainty, economic policy uncertainty, financial development, and renewable energy on ecological proxies (CO2 emissions, Ecological footprint, and Load capacity factor) using quarterly data spanning from 1990 to 2019. As far as the investigators are aware, this is the first empirical analysis examining the impact of oil price uncertainty on ecological quality. To achieve this, we employed advanced techniques, including quantile-on-quantile KRLS (QQKRLS) and quantile-on-quantile Granger causality (QQGC), to analyse the interconnections among these variables. The findings based on the load capacity factor exposed that renewable energy, economic policy uncertainty, financial development, and economic growth positively contribute to ecological quality, whereas oil price uncertainty has a detrimental effect. Additionally, as a measure of robustness, CO2 emissions and ecological footprint were included in the analysis, demonstrating comparable outcomes when assessed alongside the load capacity factor model. Furthermore, QQGC results demonstrated that all regressors significantly forecast ecological quality. Drawing from the findings, policy interventions ought to prioritize incentivizing the adoption of renewable energy, mitigating economic policy uncertainty, fostering financial development, and stimulating economic growth as pivotal strategies for augmenting ecological quality. Furthermore, integrating measures to alleviate oil price uncertainty stands as a crucial imperative for ensuring environmental sustainability. HIGHLIGHTS: The study examined the effect of oil price uncertainty and economic policy uncertainty on ecological quality The study also examined the role of renewable energy and financial development The study employed quantile-based methods for the period 1990 to 2019 for the United States Economic policy uncertainty, and renewable energy promote ecological quality Oil price uncertainty lessen ecological quality [ABSTRACT FROM AUTHOR]

A quite efficient tool to tackle climate change is green finance. By applying autoregressive distributed lag-error correction model to analyze 2011–2019 provincial data in China, this study investigated how green finance influences carbon neutrality targets, while taking considerations of industrial ecologicalization and environmental tax to thoroughly analyze interactions in the long term as well as the short term. Research outcomes indicated that, throughout the research period, green finance had greatly improved and that the measuring system was appropriate. The outcomes also demonstrated that the error correction coefficient matches the predicted adverse effect. While long-term reductions in carbon emissions per capita were significantly impacted by green finance and industrial ecologicalization. The short-term estimation's findings, nevertheless, confirmed that environmental taxes considerably reduced carbon emissions per capita. However, it was shown that environmental taxes had a negligible long-term impact on air pollution emissions. Meanwhile, green finance and industry ecologicalization showed a significant short-term impact. [ABSTRACT FROM AUTHOR]

Energy consumption plays a significant role in global warming. In order to achieve carbon neutrality and enhance energy efficiency through a stable energy supply, it is necessary to pursue the development of innovative architectures designed to optimize and analyze time series data. Therefore, this study presents a new architecture that highlights the critical role of preprocessing in improving predictive performance and demonstrates its scalability across various energy domains. The architecture, which discerns patterns indicative of time series characteristics, is founded on three core components: data preparation, process optimization methods, and prediction. The core of this architecture is the identification of patterns within the time series and the determination of optimal data processing techniques, with a strong emphasis on preprocessing methods. The experimental results for heat energy demonstrate the potential for data optimization to achieve performance gains, thereby confirming the critical role of preprocessing. This study also confirms that the proposed architecture consistently enhances predictive outcomes, irrespective of the model employed, through the evaluation of five distinct prediction models. Moreover, experiments extending to electric energy validate the architecture's scalability and efficacy in predicting various energy types using analogous input variables. Furthermore, this research employs explainable artificial intelligence to elucidate the determinants influencing energy prediction, thereby contributing to the management of low-carbon energy supply and demand. [ABSTRACT FROM AUTHOR]

As the world's largest carbon emitter, China has been confronting the dual challenge of climate change and air pollution. China's quest for reducing carbon emissions will promisingly benefit the air quality, yet its impact on carbon sinks remains unclear. Here, we assess the effect of China's clean air actions and carbon neutrality policy on air quality and its associated co‐benefits for terrestrial carbon sinks by integrating multiple observations and numerical modeling. We find a quadratic response of plant photosynthesis to aerosol loading due to trade‐offs between diffuse fertilization effect and light limitations. The estimations show that China's air pollution suppresses terrestrial carbon uptake through aerosol‐induced light limitations, leading to a 7.3% decrease in plant productivity in the 2010s. In the context of carbon neutrality pledge, the associated aerosol reductions tend to alleviate the suppression and produce an additional CO2 removal of 0.39 GtCO2 year−1. Our results uncover the enhanced terrestrial carbon sinks by aerosol mitigation, highlighting the synergy between carbon neutrality and clean air. Plain Language Summary: As the world's largest carbon emitter, China has pledged to peak its carbon emissions before 2030 and achieve carbon neutrality before 2060 as an active response to climate change. China's climate strategies and efforts to reduce carbon emissions will promisingly benefit the air quality through reducing particulate matter air pollution. However, the impact of particulate pollution reductions on vegetation photosynthesis at regional and national scales remains uncertain. Here, we assess the impact of China's climate actions on climate factors and the associated ecological impacts with multiple observations and computational modeling. We find that plant photosynthesis increases under moderate particulate pollution and decreases under heavily polluted conditions. Results from models indicate that the severe air pollution at 2015 level suppresses China's ecosystem productivity, while the air quality improvements under carbon neutrality pledge significantly enhance vegetation photosynthesis and carbon absorption. Our results highlight the overlooked climate mitigation potential of reducing air pollution to enhance ecosystem productivity under China's carbon neutrality pathways. Key Points: Both observation and simulation show a quadratic response of photosynthetic productivity to aerosol loading in the eastern China regionAerosol loading in China attenuates the incident shortwave radiation, which weakens plant photosynthesis and terrestrial carbon uptakeAerosol mitigation under China's carbon neutrality pursuit can enhance ecosystem productivity and promote terrestrial carbon sink [ABSTRACT FROM AUTHOR]

In its 2023 Climate Doctrine, Russia officially committed to carbon neutrality before 2060. However, on the roadmap fork to climate neutrality Russia’s Low Carbon Strategy chose the 2F (Forest First) pathway with the dominance of the natural solutions in the LULUCF sector and with a moderate decline or even growth (industry and agriculture) in other sectors. This paper focuses on a discussion of the roadmap to carbon neutrality. The roadmapping approach relies on a system of interconnected models for setting the scale of low carbon technologies and practices deployment. The paper concludes that excessive reliance on the 2F pathway is unrealistic, and only the Forest Last family of scenarios, which focuses on substantial reduction of GHG emissions across all sectors, is able to bring Russia to carbon neutrality in 2060. The paper also presents indicators to assess emission reductions by major sectors and discusses the need to reinforce the five pillars to support this pathway: technologies; regulations and programmes; incentives and financing; institutes; and human capital. These five pillars are required to effectively address three basic models of decisions-making (satisficing, optimization, and system transformation). [ABSTRACT FROM AUTHOR]

The automobile industry is a major economic driver in Republic of Korea (Korea). However, little is known about its climate change contribution. This study estimates the direct and indirect greenhouse gases (GHG) emissions of the Korean automobile industry for the first time, by using a 2017 environmentally extended input-output (EEIO) model integrated by energy balance, GHG inventory and input-output table of 2017. The results show that the final demand of Korean automobile industry led to 8.4% of national GHG emissions in 2017, mostly because of indirect emissions embodied in the supply chain. The study also found that the Scope 1, Scope 2 and Scope 3 emissions on average accounted for 3.0%, 2.9%, and 94.7%, respectively. This highlights the contribution of the upstream supply chain such as primary metals (40.9%) and electricity (32.5%) when assessing the GHG emissions. Finally, the study underscores that carbon taxes could have a significant impact on the competitiveness of automobile export. Overall, this study provides valuable insights on countermeasures by identifying the GHG emissions characteristics of the automobile industry. The results of the study could be used to develop policies and strategies to reduce the GHG emissions and promote sustainable practices in the Korean automobile industry. [ABSTRACT FROM AUTHOR]

Chinese megacities face significant challenges in reducing carbon emissions while balancing economic growth and social welfare. This study constructs an innovative multi-objective optimization model, the SD-NSGA-III model, integrated with a System Dynamics (SD) model and using the Non-dominated Sorting Genetic Algorithm III (NSGA-III) to optimize resource allocation in Beijing. The model targets environmental, economic, and social goals by establishing a water–land–energy–carbon (WLEC) nexus for analyzing resource allocation strategies and carbon reduction pathways under various constraints. Scenario simulations under the efficiency-oriented scenario indicated a potential reduction in energy carbon emissions of 81.4% by 2030. The fairness-oriented scenario revealed significant trade-offs between equity and emission reductions, emphasizing the need for balanced strategies. Introducing constraints on resources and economic growth significantly reduced median energy carbon emissions to 80 million tons by 2030. These findings demonstrate the effectiveness of the SD-NSGA-III model in providing actionable strategies for achieving carbon neutrality and sustainable development in cities. [ABSTRACT FROM AUTHOR]

China's coal-based energy structure and its large proportion of the manufacturing industry have resulted in China having the highest CO2 emissions in the world, accounting for about one-third of the world's total emissions. Achieving the carbon peak by 2030 and carbon neutrality by 2060, while maintaining economic development, presents a significant challenge. Industrial parks, as core units of industrial clusters, are major sites for energy consumption and CO2 emissions. Thus, industry parks with great carbon reduction potential are crucial for China's carbon reduction efforts. This review systematically examines the current state of the carbon emissions of industrial parks in China and analyzes the situation and challenges faced in the low-carbon transition of these parks. Then, the major pathways, technologies, and key policies for the low-carbon transition are summarized based on the current situation. This paper assists in the low-carbon development of industrial parks and promotes the proposal and implementation of carbon emission reduction strategies. [ABSTRACT FROM AUTHOR]

The persistent increase in atmospheric carbon dioxide (CO2) concentration poses a significant contemporary challenge. Contemporary chemistry is heavily focused on sustainable solutions, particularly the photo‐/electrocatalytic reduction of CO2 and its utilization for energy storage. Despite promising prospects, efficient chemical CO2 conversion faces obstacles such as ineffective CO2 uptake/activation and catalyst mass transport. Covalent organic frameworks (COFs) have emerged as potential catalysts due to their precise structural design, functionalizable chemical environments, and robust architectures. COF‐based materials, especially those incorporating diverse active sites like single metal sites, metal nanoparticles, and metal oxides, hold promise for CO2 conversion and energy storage. This review sheds light on CO2 photoreduction/electroreduction and storage in Li‐CO2 batteries catalyzed by COF‐based composites, focusing on recent advancements in integrating COFs with nanoparticles for CO2 reduction. It discusses design principles, synthesis methods, and catalytic mechanisms driving the enhanced performance of COF‐based nanocomposites across various applications, including electrochemical reduction, photocatalysis, and lithium CO2 batteries. The review also addresses challenges and prospects of COF‐based catalysts for efficient CO2 utilization, aiming to steer the development of innovative COF‐based nanocomposites, thus advancing sustainable energy technologies and environmental stewardship. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

With railway route selection as the research objective from the perspective of dual-carbon economy, this paper analyzed domestic and international research on railway carbon emissions and route design. It elaborated in depth on the mechanisms and approaches of railway carbon emissions at different stages and highlighted the important role of route selection in reducing railway carbon emis-sions. Based on policies and the current situation of railway development in China, this paper explored ways to achieve carbon neu-trality. Additionally, new requirements for railway route selection design under the dualcarbon goals were analyzed. For railway route selection design under carbon constraints, principles based on carbon reduction and low-carbon targets were proposed. The study investigated key aspects of route selection design and conducted a technical-economic comparison focused on carbon reduction and low-carbon targets, offering suggestions. The results revealed that railway route selection affects carbon emissions in both the construction and operation stages. Therefore, carbon emissions should be included in technical-economic evaluations. At the same time, in-depth research and technical-economic analyses should be conducted based on technical standards, spatial positioning of routes, and the distribution of different structures along the route. [ABSTRACT FROM AUTHOR]

The transition to renewable energy is prioritized at the G20 Conference in 2023. This transition is essential for reducing carbon emissions, and environmental experts have stressed the urgency of identifying the factors fueling this energy transition. This paper examines the effects of the transition to renewable energy and environmental technology innovations on achieving the G20 nations' carbon-neutrality goals between 1995 and 2020. In addition to analyzing the contribution of non-renewable energy sources, financial development, the labor force, and economic growth have been analyzed, all the selected variables are found to have a long-term cointegration relationship. Given the asymmetrical nature of the data distribution, the study employs an advanced moment quantile regression method. The outcome identifies non-renewable energy, financial development, and labor force as significant contributors to consumption-driven CO2 emissions throughout all quantiles. On the other hand, the development of renewable energy transition and advancements in environment-related technology innovations and economic growth led to a significant reduction in emission levels. The bootstrapped quantile regression provides additional confirmation of the reliability of these results. In addition, the panel causality analysis reveals both bidirectional and unidirectional causal connections among CO2 emissions and the other evaluated factors. These findings suggest that environmentally friendly strategies, green technological advancements and renewable energy are crucial for carbon mitigation. [ABSTRACT FROM AUTHOR]

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This review offers a comprehensive overview of synthetic fuels as promising alternatives to conventional fossil fuels. The carbon-neutral potential of synthetic fuels when produced using renewable energy and captured CO2, offering significant opportunities to mitigate CO2 emissions, is discussed. Moreover, the efficiency of synthetic fuels is presented, as they do not require dedicated agricultural land or substantial water resources, addressing concerns related to the land-use change and water scarcity associated with traditional biofuels. The economic viability of synthetic fuels is explored, highlighting the advancements in technology and decreased renewable-energy costs, coupled with their independence from food crops, mitigating concerns about potential impacts on food prices. Major investments by industry leaders such as Porsche, Highly Innovative Fuels Global, and ExxonMobil, totalling $1 billion, aimed at achieving an annual production of 550 million litres by 2026, are covered in detail. This study is further extended by emphasizing the scalability of synthetic fuel production through modular processes, enabling tailored facilities to meet regional demands and contribute to a decentralized and resilient energy infrastructure. Additionally, the 'drop-in' nature of synthetic fuels that are seamlessly compatible with existing fuel storage, pipelines, and pumps, facilitating a smooth transition without requiring extensive infrastructure changes, is highlighted. Challenges such as the current high cost of synthetic fuel production are acknowledged, necessitating supportive government policies and incentives for widespread adoption. Overall, synthetic fuels have emerged as promising contenders in the pursuit of sustainable and adaptable energy solutions, with tangible benefits for the environment, economy, and existing energy infrastructure. [ABSTRACT FROM AUTHOR]

As global energy consumption, climate change, and environmental degradation continue to escalate, the need for sustainable solutions has become more critical than ever. Passive cooling is emerging as a promising approach to improve energy efficiency in the built environment. This research investigates the potential of passive cooling in new buildings, focusing on its ability to lower indoor temperatures and utilize eco-friendly materials. By reviewing the existing literature, case studies, and technological innovations, this study explores the feasibility and effectiveness of passive cooling strategies, providing a basis for future research and practical implementation. Using quantitative methods, the research analyzes temperature variations under different ventilation scenarios to assess the impact of passive cooling. Additionally, it qualitatively examines the thermal properties of various interior finishing materials, including cement, wood, and loess bricks. Software simulations are employed to assess the temperature reduction effects of eco-friendly materials such as wood and clay bricks. The findings indicate that passive cooling effectively reduces indoor temperatures, irrespective of the interior materials used. While materials like wood, known for its thermal efficiency, or cost-effective red clay blocks may influence overall building performance, the core principles of passive cooling remain universally applicable across different material choices. [ABSTRACT FROM AUTHOR]

Predicting regional carbon dioxide (CO2) emissions is essential for advancing toward global carbon neutrality. This study introduces a novel CO2 emissions prediction model tailored to the unique environmental, economic, and energy consumption of Shanghai Chongming. Utilizing an innovative hybrid approach, the study first applies grey relational analysis to evaluate the influence of economic activity, natural conditions, and energy consumption on CO2 emissions. This is followed by the implementation of a dual-channel pooled convolutional neural network (DCNN) that captures both local and global features of the data, enhanced through feature stacking. Gated recurrent unit (GRU) network then assesses the temporal aspects of these features, culminating in precise CO2 emission predictions for the region. The results indicate: (1) The proposed hybrid model achieves accurate predictions based on accounting data, with high precision, low error, and good stability. (2) The study found an overall increase in Chongming's carbon emissions from 2000 to 2022, with the prediction results being generally consistent with existing research findings. (3) The proposed method, based on Chongming's CO2 emission predictions, addresses issues such as the scarcity of effective accounting data and inaccuracies in traditional calculation methods. The results can provide effective technical support for local government policies on carbon reduction and promote sustainable development. [ABSTRACT FROM AUTHOR]

The global warming phenomenon caused by greenhouse gas emission leads to the deterioration of the ecological environment. In urban spaces, the selection of garden tree species with high carbon sequestration rates can effectively contribute to carbon neutrality. In this study, we measured the height, diameter at breast height, and crown width of 643 ancient trees around the West Lake Scenic Spot, Hangzhou, China, and recorded their species and ages. By the biomass expansion factor method, the long-term carbon sequestration of the trees was calculated, and the corresponding statistical analysis indicated the following findings: (1) The maximum carbon sequestration of ancient trees varies with the species; the simple rational function has the best fit for the relationship between mean annual carbon sequestration and age. (2) For the five most common species in the Hangzhou area, the total individual amount of carbon sequestration per tree species can be ranked from high to low as follows: Celtis julianae, Cinnamomum camphora, Castanopsis sclerophylla, Liquidambar formosana, and Ginkgo biloba (tree age < 260 years). The ranking for trees aged above 260 years is as follows: Celtis julianae, Cinnamomum camphora, Liquidambar formosana, Castanopsis sclerophylla, and Ginkgo biloba. (3) The transient and mean annual carbon sequestration rate decreases as tree age increases; for most of the ancient trees in this research, the main growing period is 0–300 years. (4) Castanopsis sclerophylla, Liquidambar Formosana, and Osmanthus fragrans are recommended for urban landscape greening as they provide continuous long-term carbon sequestration and special landscape features. [ABSTRACT FROM AUTHOR]

Many countries have committed to carbon reductions and carbon neutrality targets in response to the Paris Agreement and Sustainable Development Goals (SDGs). With economic development, the transportation sector has become a major source of carbon emissions. In China, transport infrastructure—as an important carrier of the transportation sector—is important for controlling carbon emissions from this sector and achieving carbon neutrality and the targets of the SDGs. However, most studies have focused on transport vehicles and neglected transport infrastructure. Furthermore, the influences of collusive behavior and digital control technologies on the carbon reduction process have not yet been examined. This study aimed to analyze the influencing factors in the carbon reduction process in transport infrastructure. This study uses partial least squares structural equation modeling (PLS-SEM) to analyze the factors influencing carbon reductions in transport infrastructure and the mediating roles of collusive behavior and digital control technologies in the carbon reduction process. Low-carbon technologies, digital control technologies, and collusive behavior have positive direct and indirect effects on the carbon reduction effect. Digital control technologies have a positive effect on low-carbon regimes. Low-carbon technologies influence carbon reduction effects. Collusive behavior plays a mediating role in low-carbon regimes. Finally, the industrial structure influences carbon reduction effects. This study extends China's carbon emission research in the transportation sector by focusing on infrastructure rather than vehicles. Additionally, this is the first study to incorporate collusive behavior and digital control technologies into the framework to analyze the impact of carbon reductions. The study also employs PLS-SEM to explore effective carbon reduction paths. The findings provide decision-making support for controlling carbon reductions in transport infrastructure. [ABSTRACT FROM AUTHOR]

Natural gas is an environmentally friendly and low-carbon clean energy. Its replacement of coal and other fossil energy sources will be important in China's carbon peaking and carbon neutrality goals. The Chinese government has also introduced many policies to encourage the development of natural gas. Therefore, it is of great significance to forecast the natural gas consumption. The grey prediction model has the unique advantage that it can perform well in the case of inadequate sample size. In this paper, the fractional cumulative grey model (FGM(1,1)) is used to forecast the natural gas consumption of 30 areas (provinces, cities, and autonomous regions) in China from 2022 to 2030. According to the reasonable forecast results, except for a few special areas, the consumption in other areas of China will continue to rise in recent years. By analyzing the results, it can also be clearly concluded that the natural gas consumption has regional characteristics. The consumption in 19 regions shows a rapid growth trend, 8 regions show a steady growth trend, and 3 regions show a downward trend. The prediction results and analysis will provide some reference for different regions to formulate natural gas-related policies. [ABSTRACT FROM AUTHOR]

Biochar, produced from the thermochemical conversion of biomass waste, has various applications owing to its broad utility and advantageous properties. This study employs a scientometric approach to comprehensively assess the advancements in biochar application from 2022 to 2023. Utilizing 13,357 bibliographic records sourced from the Web of Science Core Collection with the search term "biochar", the analysis focuses on authorship, national contributions, and keyword trends. Findings demonstrate a continual rise in annual publications since 2009, albeit with a moderated growth rate in 2023. China leads in publication outputs, followed by USA and India, with Hailong Wang emerging as a prominent figure in biochar research. Keyword co-occurrence analyses identify key research themes such as biochar's role in climate change mitigation, easing salinity and drought stress, immobilizing toxic metals, degrading organic pollutants, serving as additives in anaerobic digestion, and functioning as electrodes in microbial fuel cells. Among these, biochar's application for global climate change mitigation gains significant attention, while its utilization as electrodes in microbial fuel cells emerges as a promising research frontier, indicating the growing need for sustainable energy sources. The study also outlines critical research gaps and future priorities for enhancing biochar application. Overall, it highlights the diverse applicability of biochar and offers valuable insight into research progression and forthcoming directions in biochar studies. Highlights: Utilization of bibliometric review for keyword analysis. Examination of recent developments in biochar application. The emerging focus on biochar's effectiveness as electrodes in microbial fuel cells (MFCs). Suggested future research directions and priorities for sustainable biochar application. [ABSTRACT FROM AUTHOR]

This paper investigates the role of digitalization in enhancing wastewater treatment processes, emphasizing its potential to optimize resource utilization, reduce energy consumption, and improve water quality. By examining the implementation of digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), the study demonstrates how these tools enable real-time monitoring, predictive maintenance, and intelligent decision-making in wastewater treatment operations. The paper provides a comparative analysis based on key performance indicators (MAPE, RMSE, R2) to evaluate the effectiveness of these digital solutions. Additionally, it discusses the benefits and challenges associated with integrating digital tools in wastewater treatment plants (WWTPs), including cost, complexity, and data security concerns. The study also addresses the impact of digitalization on carbon neutrality goals, highlighting how data-driven approaches can enhance resource allocation and management. By offering insights into current practices and future directions, this paper aims to contribute to the advancement of sustainable wastewater treatment and support the achievement of UN SDG#6, ensuring clean water and sanitation for all. [ABSTRACT FROM AUTHOR]

The capacity of carbon sinks varies among the different types of ecosystems, and whether national parks, as an important type of nature reserve, have a high carbon sink capacity (CSC) and whether eco-tourism in national parks affects their CSC are the main scientific issues discussed. Using MODIS Net Primary Production (NPP) product data, this study analysed the spatiotemporal variation in carbon sources and sinks (CSSs) in the ecosystem of Huangshan National Park from 2000 to 2020, as well as the impact of tourism on these carbon sources and sinks. The findings indicate that, while the ecosystems of national parks generally have a strong CSC, they may not always function as carbon sinks, and during the study period, Huangshan National Park served as a carbon source for four years. Temporally, the CSSs in the ecosystem of the national park exhibit a cyclical pattern of change with a four-year cycle and strong seasonality, with spring and autumn functioning as carbon sinks, and summer and winter as carbon sources. Spatially, the CSSs of the national park ecosystem exhibited a vertical band spectrum of spatial distribution, and the CSC showed a trend of gradual enhancement from low altitude to high altitude. Tourism is a major factor that has an impact on the CSC of national park ecosystems. [ABSTRACT FROM AUTHOR]

CO2 emission reduction of sectors such as aviation, maritime shipping, road haulage, and chemical production is challenging but necessary. Although these sectors will most likely continue to rely on carbonaceous energy carriers, they are expected to gradually shift away from fossil fuels. In order to do so, the prominent option is to utilize alternative carbon sources--like biomass and CO2 originating from carbon capture--for the production of non-fossil carbonaceous vectors (biofuels and e-fuels). However, the limited availability of biomass and the varying nature of other carbon sources necessitate a comprehensive evaluation of trade-offs between potential carbon uses and existing sources. Then, it is primordial to understand the origin of carbon used in sustainable aviation fuel (SAF) to understand the implications of defossilizing aviation for the energy system. Moreover, the production of SAF implies deep changes to the energy system that are quantified in this work. This study utilizes the linear programming cost optimization tool EnergyScope TD to analyze the holistic French energy system, encompassing transport, industry, electricity, and heat sectors while ensuring net greenhouse gas neutrality. A novel method to model and quantify carbon flows within the system is introduced, enabling a comprehensive assessment of greenhouse gas neutrality. This study highlights the significance of fulfilling clean energy requirements and implementing carbon dioxide removal measures as crucial steps toward achieving climate neutrality. Indeed, to reach climate neutrality, a production of 1,046 TWh of electricity by non-fossil sources is needed. Furthermore, the findings underscore the critical role of efficient carbon and energy valorization from biomass, providing evidence that producing fuels by combining biomass and hydrogen is optimal. The study also offers valuable insights into the future cost and impact of SAF production for air travel originating from France. That is, the European law ReFuelEU would increase the price of plane tickets by +33% and would require 126 TWh of hydrogen and 50 TWh of biomass to produce the necessary 91 TWh of jet fuel. Finally, the implications of the assumption behind the production of SAF are discussed. [ABSTRACT FROM AUTHOR]

Direct CO2 conversion to liquid hydrocarbons (HCs) in a single process was achieved using cobalt (Co) catalysts supported on lanthanum ion (La3+)‐doped cerium oxide (CeO2) under a gas stream of H2/CO2/N2=3/1/1. The yield of liquid HCs was the highest for 30 mol% of La3+‐doped CeO2, which was because extrinsic oxygen vacancy formed by doping La3+ could act as an effective reaction site for reverse water gas shift reaction. However, the excess La3+ addition afforded surface covering lanthanum carbonates, resulting in depression of the catalytic performance. On the other hand, bare CeO2 lead to an increase in the selectivity of undesirable methane, which arose from reduction of CO2 to CO proceeding by intrinsic oxygen vacancy generated by only Ce3+, and weaker CO2 capture ability of intrinsic oxygen vacancy than extrinsic one, resulting in the proceeding of Sabatier reaction on Co catalyst. The rational design of reaction sites presented in this study will contribute to sustainability. [ABSTRACT FROM AUTHOR]

Improving energy efficiency by adjusting the structure of energy consumption types is of great significance for reducing carbon emissions in the short term. The present paper constructs new data envelopment analysis models for evaluating energy utilization under different structural conditions and calculating potential emissions reductions. We conducted empirical research on 30 provinces in China from 2003 to 2019—a time frame that coincides with the instituting of China's “coal‐to‐gas” program. Our results show that technological progress is the main way for China to reduce carbon emissions and that it is possible to reduce the total amount of carbon emissions by 35%. Additionally, optimizing the energy consumption structure following the coal‐to‐gas program guidelines could reduce the country's carbon emissions by a further 25%. Finally, this paper provides specific policy recommendations based on the efficiency analysis results to guide each province in reducing carbon emissions under the conditions of energy demand growth. [ABSTRACT FROM AUTHOR]

As per the regulations of Intergovernmental Panel on Climate Change (IPCC), the country's carbon emission data hold primacy. Nevertheless, establishing and utilizing a database pose a daunting challenge. This study presents the "Carbon Seer System," a novel software prototype designed to inform and educate users about the carbon footprint during their production and in daily life. The development process involved a three-stage user interview process, ensuring system's alignment with user needs and preferences. The system employs machine learning and visual recognition technology, including convolutional neural networks (CNNs), feature pyramid networks, and self-attention mechanisms, enabling users to analyze captured images for carbon emission factors. It automatically identifies the carbon emission factors of industrial products, energy producers, household producers, waste treatment, and transportation. A unique "group detection" method allows for the simultaneous analysis of multiple objects in a single image, enhancing user convenience. Additionally, the software features a carbon footprint tracker and a carbon sink dashboard, providing users with insights into their carbon emissions and the efforts needed for offsetting. The study concludes that the "Carbon Seer System" represents a significant step towards individual enablement at understanding and actively participating in a low-carbon lifestyle. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) from road traffic is a non-negligible part of global greenhouse gas (GHG) emissions, and it is a challenge for the world today to accurately estimate road traffic CO2 emissions and formulate effective emission reduction policies. Current emission inventories for vehicles have either low-resolution, or limited coverage, and they have not adequately focused on the CO2 emission produced by new energy vehicles (NEV) considering fuel life cycle. To fill the research gap, this paper proposed a framework of a high-resolution well-to-wheel (WTW) CO2 emission estimation for a full sample of vehicles and revealed the unique CO2 emission characteristics of different categories of vehicles combined with vehicle behavior. Based on this, the spatiotemporal characteristics and influencing factors of CO2 emissions were analyzed with the geographical and temporal weighted regression (GTWR) model. Finally, the CO2 emissions of vehicles under different scenarios are simulated to support the formulation of emission reduction policies. The results show that the distribution of vehicle CO2 emissions shows obvious heterogeneity in time, space, and vehicle category. By simply adjusting the existing NEV promotion policy, the emission reduction effect can be improved by 6.5%-13.5% under the same NEV penetration. If combined with changes in power generation structure, it can further release the emission reduction potential of NEVs, which can reduce the current CO2 emissions by 78.1% in the optimal scenario. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2), as the primary greenhouse gas, has significant impacts on global climate change, leading to severe and irreversible adverse consequences for ecosystems and human environments. To address the issue of excessive CO2 emissions, efforts in recent years have yielded significant progress in the development of clean energy sources and the promotion of carbon capture, utilization, and storage (CCUS) technologies. Conventional CO2 capture techniques are limited in addressing global atmospheric CO2 excess effectively, as they target only high-concentration CO2 emissions and require implementation at specific emission points. Direct air capture (DAC) technology has emerged as a promising solution due to its flexibility in deployment, avoidance of land competition, and ability to capture legacy CO2 emissions. Additionally, DAC offers opportunities for producing synthetic clean fuels, thereby reducing reliance on traditional fossil fuels and aiding in reducing greenhouse gas emissions. This study provides a comprehensive review of DAC technology, encompassing its principles, technological advancements, real-world applications, challenges, and future research directions. By offering insights into the current state and potential of DAC technology, this study aims to guide global efforts in scaling up DAC deployment, ultimately contributing to achieving global carbon neutrality or even negative emissions. [ABSTRACT FROM AUTHOR]