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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]

Land is being degraded rapidly worldwide. United Nations Convention to Combat Desertification in 2015 has invited countries to formulate voluntary targets to achieve Land Degradation Neutrality (LDN). Under the Paris Agreement, a legally binding international treaty adopted in 2015, the world is transitioning toward Carbon Neutrality (CN) with more mitigation actions. This paper intended to review the concepts of land degradation, LDN along with CN emphasizing the degradation types, approaches, models available to analyze, synergies, economic aspects and challenges. The review explores approaches and models available for achieving LDN and CN which are both synergistic, economically efficient and could overcome the common challenges. Land degradation has to focus beyond the traditional definitions to incorporate more persistent and the difficult to restore degradation causes. Such complex land degradation requires specialized LDN approaches. The level of degradation and restoration progress could be analyzed using a variety of modeling approaches including economic models. Approaches for LDN and CN can bring significant synergies for each other. The approach proposed by the present study will provide a logical flow for decision-making while minimizing time and effort and avoiding a piecemeal approach. The approach therefore maximizes the output in relation to the inputs thus enhancing sustainability. [ABSTRACT FROM AUTHOR]

[Display omitted] • Review of advanced electrodialysis techniques for critical mineral recovery. • Investigation of lithium, nickel, cobalt, and rare earth elements sources. • Principles and performances of advanced electrodialysis techniques for metal recovery. • Necessity of feedstock-tailored advanced electrodialysis technologies is suggested. The global challenge of climate change and the pursuit of carbon neutrality drive the demand for clean energy technologies, increasing the need for critical minerals. However, diminishing ore quality and supply chain vulnerabilities highlight the necessity of exploring unconventional mineral sources. This paper assesses the potential of sources such as low-grade ores, brines, and secondary byproducts for extracting critical minerals, focusing on lithium, nickel, cobalt, and rare earth elements. Conventional refining techniques struggle with the complexity and low concentrations found in unconventional sources, prompting the exploration of innovative methods. Electrically driven membrane technologies, particularly electrodialysis (ED), show promise for selectively transporting metals through ion exchange membranes. The combination of functionalized membranes and advanced ED technologies offers high selectivity for specific elements, and renewable energy-based ED operations can minimize environmental impact. Recent advancements in ED, including selective ED and liquid membrane ED, demonstrate efficient recovery of critical minerals. This comprehensive review explores the principles and recent progress in ED technologies, with a focus on recovering critical minerals from unconventional sources. The paper is structured into three main sections: categorizing the properties of unconventional sources of critical minerals based on the latest literature, exploring the fundamental principles underpinning modern ED technologies, and investigating recent breakthroughs in the separation and recovery of critical minerals from unconventional sources using ED technologies. This framework highlights the potential of advanced ED technologies in efficiently processing diverse unconventional sources and adeptly retrieving critical minerals. [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

• A CGE model elaborately depicting six CCS technologies was developed. • Impacts of four CCS incentive scenarios on decarbonization pathways were simulated. • CCS can sequester 960 ∼ 1,604 MtCO 2 annually in China by 2060 with policy incentives. • CCS incentives can reduce China's future primary energy demand by 7.7 ∼ 17.4 %. • CCS incentives can increase GDP by 5.64 ∼ 6.59 % compared to no policy scenario. Carbon capture and storage (CCS) technology, considered as a pivotal tool in mitigating climate change within the fossil energy system, particularly in China, has experienced slower development than expected. The exploration of direct incentive policies to facilitate its growth remains relatively underdeveloped. This study developed a hybrid dynamic computable general equilibrium (CGE) model to simulate the substantial impacts of CCS incentive policies on China within the context of carbon neutrality target. Two potential incentive policies, carbon emission trading system (ETS) and 45Q tax credit, were simulated, with different sectoral coverage. The results indicate that CCS technologies can reduce carbon emissions by 960 ∼ 1,604 MtCO 2 annually by 2060 through the strategic implementation of these incentive policies. The 45Q tax credit demonstrates its effectiveness in promoting early-stage research and development (R&D) and demonstration of CCS, while the ETS policy facilitates the commercial development of CCS in the later stage of development. By 2060, the implementation of CCS incentive policies could potentially result in 7.7 ∼ 17.4 % reduction in China's primary energy consumption, 71.2 ∼ 82.7 % decrease in the carbon price of ETS and 5.64 ∼ 6.59 % increase in the GDP compared with the no-policy scenario. In addition, the sectoral output in various sectors and the welfare of urban and rural households also increase. This paper provides an important reference for the realization of China's carbon neutrality goal and the model framework can be applied to other countries. [ABSTRACT FROM AUTHOR]

Introduction: Carbon neutrality has become a key strategy to combat global climate change. However, current methods for predicting carbon emissions are limited and require the development of more effective strategies to meet this challenge. This is especially true in the field of sports and competitions, where the energy intensity of major events and activities means that time series data is crucial for predicting related carbon emissions, as it can detail the emission patterns over a period of time. Method: In this study, we introduce an artificial intelligence-based method aimed at improving the accuracy and reliability of carbon emission predictions. Specifically, our model integrates an Improved Mahjong Search Algorithm (ISSA) and GRU-Transformer technology, designed to efficiently process and analyze the complex time series data generated by sporting events. These technological components help to capture and parse carbon emission data more accurately. Results: Experimental results have demonstrated the efficiency of our model, which underwent a comprehensive evaluation involving multiple datasets and was benchmarked against competing models. Our model outperformed others across various performance metrics, including lower RMSE and MAE values and higher R2 scores. This underscores the significant potential of our model in enhancing the accuracy of carbon emission predictions. Discussion: By introducing this new AI-based method for predicting carbon emissions, this study not only provides more accurate data support for optimizing and implementing carbon neutrality measures in the sports fi eld but also improves the accuracy of time series data predictions. This enables a deeper understanding of carbon emission trends associated with sports activities. It contributes to the development of more effective mitigation strategies, making a significant contribution to global efforts to reduce carbon emissions. [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 China's climate goals. [ABSTRACT FROM AUTHOR]

Global climate change is increasingly recognized as a critical factor influencing economic performance, thereby making the Environmental, Social, and Governance (ESG) performance of businesses a vital indicator of sustainability. In the context of China's "dual-carbon" objective, this study examines the relationship between climate transition risk and the ESG performance of listed Chinese companies. Utilizing text analysis techniques, this research quantifies the Management Discussion and Analysis (MD&A) sections of annual reports from 2014 to 2019 to extract information on climate transition risks. A multiple regression analysis is then applied to assess the impact of these risks on companies' ESG performance. The findings indicate that climate transition risk has a measurable effect on the ESG performance of enterprises, suggesting its role as an incentive for achieving carbon neutrality. Specifically, the analysis shows that climate transition risk is associated with improvements in certain aspects of ESG performance, including environmental stewardship, social responsibility, and governance quality. Additionally, the study reveals that non-state-owned enterprises, those with diversified business strategies, decentralized management structures, and audits conducted by Big 4 firms, tend to exhibit better ESG performance in the face of climate transition risks. These results demonstrate the nuanced impact of climate transition risk on ESG performance, particularly within the framework of China's carbon reduction goals, and highlight the importance of firm characteristics in moderating this relationship. This evidence provides a foundation for stakeholders, including enterprises, policymakers, and investors, to consider climate transition risks in their efforts to enhance ESG performance. [ABSTRACT FROM AUTHOR]

Petrochemical producers both rely upon and generate some of the most problematic substances in the current age of socioecological crisis: fossil fuels and plastics. With mounting calls to cap fossil fuel extraction as well as plastics production, the industry appears to be caught between a rock and a hard place. Nonetheless, betting on continuously increasing global plastic demand, petrochemical production is expanding significantly. This predicament raises the question of how the industry attempts to square increasing petrochemical production with the need to address environmental issues. In recent years, leading actors in and around the industry have promoted notions of carbon circularity as a desirable mitigation strategy. In this paper, we examine this strategy, using discourse analysis to uncover what we refer to as the imaginary of circular carbon. We highlight how the circular carbon imaginary risks delaying climate mitigation by rendering alternative mitigation pathways undesirable. It does so by reconciling increased production, carbon neutrality, and circular economy in a vision of a circular carbon economy, framing the climate crisis as an issue of carbon management. In the circular carbon economy, carbon dioxide, petrochemicals, and plastics all fit as mere flows of carbon. The circular carbon imaginary thereby helps future-proof the petrochemical industry in legitimizing its carbon-intensive practises essential to the fossil world order and the plastic crisis. • We explore the circular carbon imaginary as promoted by the petrochemical industry. • It is a mitigation strategy centred around circular and diversified carbon flows. • That relies on largely unproven technologies and frames out short-term mitigation pathways. • By doing so, it risks delaying climate mitigation. [ABSTRACT FROM AUTHOR]