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Pulp and paper industry produces massive amounts of sludge from wastewater treatment, which constitute an enormous environmental challenge. A possible management option is the conversion of sludge into carbon-based adsorbents to be applied in water remediation. For such utilization it is important to investigate if sludge is a consistent raw material originating reproducible final materials (either over time or from different manufacturing processes), which is the main goal of this work. For that purpose, different primary (PS) and biological sludge (BS) batches from two factories with different operation modes were sampled and subjected to pyrolysis (P materials) and to pyrolysis followed by acid washing (PW materials). All the materials were characterized by proximate analysis, total organic carbon (TOC) and inorganic carbon (IC), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and N 2 adsorption isotherms (specific surface area (S BET )and porosity determination). Sludge from the two factories proved to have distinct physicochemical properties, mainly in what concerns IC. After pyrolysis, the washing step was essential to reduce IC and to considerably increase S BET , yet with high impact in the final production yield. Among the materials here produced, PW materials from PS were those having the highest S BET values (387-488 m 2  g -1 ). Overall, it was found that precursors from different factories might originate final materials with distinct characteristics, being essential to take into account this source of variability when considering paper mill sludge as a raw material. Nevertheless, for PS, low variability was found between batches, which points out to the reliability of such residues to be used as precursors of carbon adsorbents., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Pulp mill effluent was treated by different advanced oxidation processes (AOPs) consisting of UV, UV/H2O2, TiO2-assisted photo-catalysis (UV/TiO2) and UV/H2O2/TiO2 in lab-scale reactors for total organic carbon (TOC) and toxicity removals. Effects of some operating parameters such as the initial pH, oxidant and catalyst concentrations on TOC and toxicity removals were investigated. Almost every method resulted in some degree of TOC and toxicity removal from the pulp mill effluent. However, the TiO2-assisted photo-catalysis (UV/TiO2) resulted in the highest TOC and toxicity removals under alkaline conditions when compared with the other AOPs tested. Approximately, 79.6% TOC and 94% toxicity removals were obtained by the TiO2-assisted photo-catalysis (UV/TiO2) with a titanium dioxide concentration of 0.75gl(-1) at pH 11 within 60min.

The management of dewatered wastewater sludge is a major issue worldwide. Sludge disposal to landfills is not sustainable and thus alternative treatment techniques are being sought. The objective of this work was to determine optimal mixing ratios of dewatered sludge with other organic amendments in order to maximize the degradability of the mixtures during composting. This objective was achieved using mixture experimental design principles. An additional objective was to study the impact of the initial C/N ratio and moisture contents on the co-composting process of dewatered sludge. The composting process was monitored through measurements of O(2) uptake rates, CO(2) evolution, temperature profile and solids reduction. Eight (8) runs were performed in 100 L insulated air-tight bioreactors under a dynamic air flow regime. The initial mixtures were prepared using dewatered wastewater sludge, mixed paper wastes, food wastes, tree branches and sawdust at various initial C/N ratios and moisture contents. According to empirical modeling, mixtures of sludge and food waste mixtures at 1:1 ratio (ww, wet weight) maximize degradability. Structural amendments should be maintained below 30% to reach thermophilic temperatures. The initial C/N ratio and initial moisture content of the mixture were not found to influence the decomposition process. The bio C/bio N ratio started from around 10, for all runs, decreased during the middle of the process and increased to up to 20 at the end of the process. The solid carbon reduction of the mixtures without the branches ranged from 28% to 62%, whilst solid N reductions ranged from 30% to 63%. Respiratory quotients had a decreasing trend throughout the composting process., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Changes in material use, energy use and emissions profiles of industry are the result of complex interrelationships among a multitude of technological and economic drivers. To better understand and guide such changes requires that attention is paid to the time-varying consequences that technology and economic influences have on an industry''s choice of inputs and its associated (desired and undesired) outputs.This paper lays out an approach to improving our understanding of the dynamics of large industrial systems. The approach combines engineering and econometric analysis with a detailed representation of an industry''s capital stock structure. A transparent dynamic computer modeling approach is chosen to integrate information from these analyses in ways that foster participation of stakeholders from industry and government agencies in all stages of the modeling process—from problem definition and determination of system boundaries to generation of scenarios and interpretation of results.Three case studies of industrial energy use in the USA are presented—one each for the iron and steel, pulp and paper, and ethylene industry. Dynamic models of these industries are described and then used to investigate alternative carbon emissions and investment-led policies. A comparison of results clearly points towards two key issues: the need for industry specific policy approaches in order to effectively influence industrial energy use, fuel mix and carbon emissions, and the need for longer time horizons than have typically been chosen for the analysis of industrial responses to climate change policies. [Copyright &y& Elsevier]

This work describes the adsorptive removal of three widely consumed psychiatric pharmaceuticals (carbamazepine, paroxetine and oxazepam) from ultrapure water. Two different adsorbents were used: a commercial activated carbon and a non-activated waste-based carbon (PS800-150-HCl), produced by pyrolysis of primary paper mill sludge. These adsorbents were used in single, binary and ternary batch experiments in order to determine the adsorption kinetics and equilibrium isotherms of the considered pharmaceuticals. For the three drugs and both carbons, the equilibrium was quickly attained (with maximum equilibrium times of 15 and 120 min for the waste-based and the commercial carbons, respectively) even in binary and ternary systems. Single component equilibrium data were adequately described by the Langmuir model, with the commercial carbon registering higher maximum adsorption capacities (between 272 ± 10 and 493 ± 12 μmol g -1 ) than PS800-150-HCl (between 64 ± 2 and 74 ± 1 μmol g -1 ). Multi-component equilibrium data were also best fitted by the single component Langmuir isotherm, followed by the Langmuir competitive model. Overall, competitive effects did not largely affect the performance of both adsorbents. Binary and ternary systems maintained fast kinetics, the individual maximum adsorption capacities were not lower than half of the single component systems and both carbons presented improved total adsorption capacities for multi-component solutions., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Diverse types of saline coastal wetlands contribute significantly to global biodiversity, carbon stocks, and ecosystem functions. Opportunities to incentivise coastal wetland restoration from carbon markets is growing across the world. However, little is known of the economic feasibility of blue carbon restoration across different regions, or the quantities of ecological and social co-benefits that accompany restoration. We explored the opportunities for tidal restoration of coastal wetlands for blue carbon projects in three regions across Australia. We identified biophysically suitable potential restoration sites for mangroves, saltmarshes and supratidal forests, estimated their carbon abatement over 25 years, and undertook a cost-benefit analysis under the carbon market. Potential co-benefits of restoration sites for biodiversity, fisheries, water quality and coastal protection were measured to identify economically feasible sites that maximise the provision of co-benefits. Cultural benefits were identified as the potential for leadership and collaboration by Traditional Custodians at sites. We found that the extent of restoration opportunities varied among regions, with variation in tidal range, extent of agricultural land-use, and the type of hydrological modifications influencing carbon abatement forecasts. The presence of threatened species in hydrologically modified wetlands reduced the amount of land available for restoration, however the restoration of remaining areas could produce rich ecological and cultural benefits. A high carbon price was needed to make blue carbon restoration profitable on land used for beef production. We found sites where carbon credits can be bundled with co-benefits to possibly attain higher carbon prices. Traditional Custodians were interested in leading blue carbon projects, however the opportunity is dependent on Native Title rights. Through comparison of case studies, we developed a regional approach to identify coastal wetland restoration sites for blue carbon and co-benefits that can incorporate local knowledge and data availability, engage with Traditional Custodians, and adapt to the unique characteristics of regions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Valerie Hagger reports financial support was provided by National Environmental Science Program. Renee Rossini reports financial support was provided by National Environmental Science Program. Phoebe Stewart-Sinclair reports financial support was provided by National Environmental Science Program. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Due to the substantial emissions of global CO 2 , there has been growing interest in nitrogen-enriched porous carbonaceous materials that possess exceptional CO 2 capture capabilities. In this study, a novel N-enriched microporous carbon was synthesized by integrating waste polyamides with lignocellulosic biomass, involving carbonization and physicochemical activation. As-synthesized adsorbents demonstrated significant characteristics including a high specific surface area (1710 m 2 /g) and a large micropore volume (0.497 cm 3 /g), as well as abundant N- and O-containing functional groups, achieved through activation at 700 °C. They displayed remarkable CO 2 capture capability, achieving uptake levels of up to 6.71 mmol/g at 1 bar and 0 °C, primarily due to the filling effect of narrow micropore along with electrostatic interaction. Furthermore, the adsorbent exhibited a rapid capacity for CO 2 capture, achieving 94.9% of its saturation capacity within a mere 5 min at 30 °C. This impressive performance was accurately described by the pseudo second-order dynamic model. Additionally, as-synthesized adsorbents displayed a moderate isosteric heat of CO 2 adsorption, as well as superior selectivity over N 2 . Even after undergoing five consecutive cycles, it maintained ∼100% of its initial capacity. Undoubtedly, such findings hold immense significance in the mitigation of global plastic pollution and greenhouse effect., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Landfill is a significant source of atmospheric CH 4 and CO 2 emissions. In this study, four landfill reactor systems were constructed to investigate the effects of different ventilation methods, including continuous aeration (20 h d -1 ) and intermittent aeration (continuous aeration for 4 h d -1 and 2 h of aeration every 12 h, twice a day), on properties of landfilled waste and emissions of CH 4 and CO 2 , in comparison to a traditional landfill. Compared with continuous aeration, intermittent aeration could reduce the potential global warming effect of the CH 4 and CO 2 emissions, especially multiple intermittent aeration. The CH 4 and CO 2 emissions could be predicted by the multiple linear regression model based on the contents of carbon, sulfur and/or pH during landfill stabilization. Both intermittent and continuous aeration could enhance the methane oxidation activity of landfilled waste. The aerobic methane oxidation activity of landfilled waste reached the maximums of 50.77-73.78 μg g -1 h -1 after aeration for 5 or 15 d, which was higher than the anaerobic methane oxidation activity (0.45-1.27 μg g -1 h -1 ). CO 2 was the predominant form of organic carbon loss in the bioreactor landfills. Candidatus Methylomirabilis, Methylobacter, Methylomonas and Crenothrix were the main methane-oxidating microorganisms (MOM) in the landfills. Total, NO 2 - -N, pH and Fe 3+ were the main environmental variables influencing the MOM community, among which NO 2 - -N and pH had the significant impact on the MOM community. Partial least squares path modelling indicated that aeration modes mainly influenced the emissions of CH 4 and CO 2 by affecting the degradation of landfilled waste, environmental variables and microbial activities. The results would be helpful for designing aeration systems to reduce the emissions of CH 4 and CO 2 , and the cost during landfill stabilization., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Cultivation of sloping land is a main cause for soil erosion. Conservation practices, such as soil and stone terraces, may reduce the impacts of erosion but their impacts on soil microbial diversity and functioning related to carbon (C) and nutrient metabolisms remain unclear. This study was conducted to evaluate the effects of slope gradients (5°, 8°, 15°, 25°) and conservation practices (cultivated, uncultivated, soil terrace, and stone terrace) on bacterial and fungal diversities, metagenomic and metabolomic functioning associated with basic soil properties. Our results showed that steep slopes at 25° significantly decreased soil pH, silt percentage, and bacterial and fungal abundances, but that soil and stone terraces increased soil organic C (SOC), silt and clay contents, and fungal abundance compared to sloping cultivated lands. In addition, soil and stone terraces increased both bacterial and fungal alpha diversities, and relative abundances of Crenarchaeota, Nitrospirota, and Latescibacterota, but reduced the proportions of Actinobacteriota and Patescibacteria, thus shifting microbial beta diversities, which were significantly associated with increased SOC and silt content. For metagenomics, soil and stone terraces greatly increased the relative abundance of functional genes related to Respiration, Virulence, disease and defense, Stress response, and nitrogen and potassium metabolisms, such as Denitrification and Potassium homeostasis. For soil metabolomics, a total of 22 soil metabolites was enriched by soil and stone terraces, such as Lipids and lipid-like molecules (Arachidonic acid, Gamma-Linolenic acid, and Pentadecanoic acid), and Organoheterocyclic compounds (Adenine, Laudanosine, Methylpyrazine, and Nicotinic acid). To sum up, soil and stone terraces could reduce some of the negative impacts of steep slope cultivation on soil microbial diversity as well as their metagenomic and metabolomic functioning related to C and nutrient metabolism useful for soil health improvement, potentially bolstering the impact of sustainable practices in erosion hotspots around the world., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Regenerative agricultural practice adoption on conventionally managed fields has gained momentum as a climate mitigation strategy, given the ability of these practices to sequester carbon or reduce greenhouse gas emissions. However, the geospatial and temporal variability of the impact of specific practices, such as cover cropping or no-till, pose challenges for scalable quantification of emissions reduction and deploying incentives to drive increased adoption. To quantify impact while accounting for variability and uncertainty at scale, Indigo Ag created a monitoring, reporting, and verification (MRV) pipeline to produce agricultural soil carbon credits produced at large scales (hundreds of thousands of hectares). The pipeline ingests field data from enrolled farmers, checks data quality, uses hybrid soil sampling and biogeochemical modeling to produce estimates of emissions reduction and uncertainty, and then applies deductions based on calculated uncertainty and leakage to quantify total project-wide carbon credits and monitor for durability of carbon. The implementation of a carbon project (CAR1459) from 2018 to 2022 on 553,743 ha of U.S. cropland utilizing the pipeline is estimated to have reduced emissions by 398,408.5 tCO 2 e, amounting to 296,662 tCO2e of soil carbon credits after uncertainty deductions. This paper explores the effect sizes associated with specific regenerative practice changes across the project domain. Cover cropping consistently resulted in a net positive climate impact and reduced emissions by 1.29 tCO 2 e per hectare per year, on average. Introduction of no-till was more common in the project, but it had a lower average emissions reduction of 0.38 tCO 2 e per hectare per year. Effect sizes for no-till vary spatiotemporally and are typically low in the first several years after adoption but increase in subsequent years. Agricultural carbon programs that capture and incentivize the nuance of outcomes of practices rather than the implementation of practices, can promote adoption of the right management practice to be deployed on the right field for maximum environmental benefit., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Mark Easter reports financial support was provided by Indigo Ag, Inc. Mark A. Friedl reports financial support was provided by Indigo Ag, Inc. Ashok A. Kumar reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Mark Easter reports a relationship with Indigo Ag, Inc. that includes: consulting or advisory, employment, and equity or stocks. Mark A. Friedl reports a relationship with Indigo Ag, Inc. that includes: consulting or advisory. Charles D. Brummitt reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Cara A. Mathers reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Rebecca Arundale Keating reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Katherine O'Leary reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Eleanor E. Campbell reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Max DuBuisson reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Ryan Pape reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Samuel J.W. Peters reports a relationship with Indigo Ag, Inc. that includes: employment and equity or stocks. Ashok A. Kumar has patent issued to Indigo Ag, Inc. Eleanor E. Campbell has patent issued to Indigo Ag, Inc. Samuel J.W. Peters has patent issued to Indigo Ag, Inc. Charles D. Brummitt has patent issued to Indigo Ag, Inc. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Salt marshes cover the largest area among the three types of traditional blue carbon ecosystems in China's coastal zone, with the introduced smooth cordgrass (Spartina alterniflora Loisel.) being dominant in these marshes. The effects of eradicating S. alterniflora nationwide and the subsequent ecological restoration on blue carbon are unclear. This paper evaluates the variation in blue carbon during the national S. alterniflora eradication campaign, which involves mechanical tillage from 2022 to 2025, and proposes three scenarios for blue carbon changes after native vegetation is reestablished by 2050. The results show that, in 2025, plant carbon stock and soil carbon stock will decrease by 1.38 Tg C and 1.21 Tg C, respectively, in the areas where S. alterniflora has been removed and managed. Although blue carbon is reduced in coastal wetlands in 2025, carbon stock is expected to increase in restored native vegetated wetlands by 2050. S. alterniflora is resilient and competitive, posing a high risk in secondary invasion. Scenario Ⅰ suggests that S. alterniflora marshes could almost recover to their original state from 2022, with 7.70 Tg C stored in plant and soil carbon stocks. Scenario Ⅱ involves native vegetated wetlands coexisting with invasive S. alterniflora marshlands, with a total carbon stock estimated at 7.15 Tg C, reflecting a decrease of 0.39 Tg C in soil carbon stock and by 0.16 Tg C in plant carbon stock. In Scenario Ⅲ, mudflats dominant and native vegetated habitats are reestablished only in suitable sites, with the total carbon stock estimated at 5.63 Tg C, a 26.9% decrease compared to 2022 levels. While eradicating invasive S. alterniflora and restoring native vegetation in China's coast enhance the ecosystem services, it reduces blue carbon stocks. Therefore, developing additional strategies to increase carbon storage in coastal wetlands is necessary., Competing Interests: Declaration of competing interest We confirm that this work is original and has not been published elsewhere, no is it currently under consideration for publication elsewhere., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Active iron oxides, especially poorly crystalline forms, benefit soil organic carbon (SOC) accumulation via directly bounding and indirectly promoting aggregation. However, it remains unclear on the impacts of active iron oxides on SOC accumulation in paddy and upland soils under long-term fertilization regimes. Here, we attempted to clarify the underlying mechanisms of amorphous (Fe O ) and organically complexed (Fe P ) iron oxides mediating SOC accumulation in paddy and upland soils based on two long-term fertilization experiments (both including no fertilization [CK]; chemical nitrogen, phosphorus and potassium [NPK] and NPK plus manure [NPKM] treatments). Results showed that compared to upland soil, Fe-bound organic carbon (Fe-bound OC) content in paddy soil, occupying 21-30% of SOC, was 77% higher on average, due to larger amounts of Fe O (+31%) and Fe P (+224%). The Fe O and Fe P were positively related to mean weight diameter (MWD) of soil aggregates across paddy and upland soils. Compared to NPK treatment, NPKM treatment strongly increased Fe O (+41%), Fe P (+60%) and associated Fe-bound OC (+19%) in paddy soil, and increased Fe O (+17%) and Fe P (+25%) while decreasing Fe-bound OC (-9%) in upland soil. These combined findings indicated the importance of poorly crystalline iron oxides facilitating Fe-bound OC formation and its contribution to SOC accumulation in paddy soil rather than upland soil. Moreover, long-term manure amendment could enhance SOC accumulation by increasing Fe-bound OC and aggregation stability in paddy soil and enhancing physical protection in upland soil, largely attributed to increased poorly crystalline iron oxides. Overall, these results highlight the potential mechanisms through which active iron oxides regulate SOC accumulation and guide fertilization management in paddy and upland soils., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The complex characteristics of volatility and non-linearity of carbon price pose a serious challenge to accurately predict carbon price. Therefore, this study proposes a new hybrid model for multivariate carbon price forecasting, including feature selection, deep learning, intelligent optimization algorithms, model combination and evaluation indicators. First, this study collects and organizes the historical carbon price series of Hubei and Shanghai as well as the influencing factors in five dimensions including structured and unstructured data, totaling twenty variables. Second, data dimensionality reduction is performed and input variables are obtained using the least absolute shrinkage and selection operator, followed by the introduction of nine advanced deep learning models to predict carbon price and compare the prediction effects. Then, through the combination of models, three models with the best performance are combined with Pelican optimization algorithm to construct a hybrid forecasting model. Finally, the experimental results show that the developed forecasting model outperforms other comparation models in terms of prediction accuracy, stability and statistical hypothesis testing, and exhibits excellent prediction performance. Furthermore, this study also applies the developed model to European carbon market price prediction and uses the Hubei carbon market as an example for quantitative trading simulation, and the empirical results further verify its robust prediction performance and investment application value. In conclusion, the proposed hybrid prediction model can not only provide high-precision carbon market price prediction for the government and corporate decision makers, but also help investors optimize their trading strategies and improve their returns., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Green firebreaks (strategically placed plantings of low-flammability vegetation) are designed to reduce the rate of fire spread and thereby increase the suppressibility of fires. Successful examples have led to some fire-prone regions investing heavily in the establishment of green firebreaks as a method of reducing fire risk while improving biodiversity and carbon storage. However, beyond small-scale case studies there has been little research quantitatively exploring the interactions among biodiversity, carbon, and wildfire risk in relation to green firebreaks. Here, we combine a Bayesian Network (BN) analysis, and fire simulations in PHOENIX RapidFire (hereafter Phoenix), to identify planting designs that reduce wildfire risks while also providing positive biodiversity and carbon outcomes. Using a BN analysis, we prioritised optimal planting designs as the combination of elements (e.g., stem density, distance from houses, shrub design, age etc.) that delivered the greatest increase in biodiversity and carbon while reducing fire risk to people and property for eight sites across south-eastern Australia. We ranked combinations of planting designs, prioritising house, and life loss first, to identify optimal designs. Optimal planting designs varied among sites, although the design elements that best reduced risk to houses and lives were consistent. These elements included 'scattered' shrubs and planting densities of trees consistent with an open forest structure. Estimated fuel loads for the optimal planting design at each site were used to create a simulated revegetation area in Phoenix. We simulated fire behaviour in Phoenix across a grid of ∼1000 ignitions for each site, and for up to 54 historic weather conditions for a 'current fuel' scenario (no green firebreaks present) compared with a 'green firebreak fuel' scenario. We found that the establishment of a green firebreak did not result in significant changes to fire behaviour at most sites. In some cases, it reduced risk to people and property, and where fire behaviour did change in terms of intensity, frequency, ember attack and overall risk, the differences relative to the current fuel scenario were less than two percent. Overall, simulated green firebreaks in most cases were found to provide biodiversity and carbon benefits without increasing fire risk. These findings illustrate their potential as an effective nature-based solution for managing multiple priorities; however, further testing of real plantings is required to evaluate this potential as an at-scale solution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Reducing carbon emissions from highly polluting enterprises is crucial to meeting the world's overall carbon emission reduction targets. Green credit policy can be effective in guiding enterprises to reduce their carbon emissions and is essential to achieving the dual-carbon targets. This study uses micro-data from a 2017-2022 follow-up survey of industrial enterprises in China and a quasi-natural experiment to evaluate whether green credit policy aligned with the dual-carbon targets enable highly polluting enterprises to become "green" by reducing emissions. The results show that green credit policy can lead highly polluting enterprises to significantly reduce carbon emissions, and total factor productivity (TFP) growth plays an intermediary role in this transition. The different impact of green credit policy on TFP may impede the greening process for highly polluting enterprises, with this hindering effect exhibiting scale heterogeneity. This study offers empirical evidence for evaluating green credit policy aligned with China's dual-carbon target and provide insights into leveraging green credit policy to advance this process., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Urban agglomeration (UA) plays as the main carrier of economy and society in China, concentrating the human activities, energy consumptions, and subsequent carbon emissions in space. The policy-induced mechanism of carbon emissions in the units of UA is currently less explored, and diversities of low-carbon development path of UAs remain unknown. Thus, this study analyzes the carbon emissions of 19 UAs in China from 2006 to 2019, focuses on the low-carbon city pilot policy (LCPP), constructs an SDM-DID model to investigate the impacts of LCPP on carbon emissions regionally, and delineates the stages of low-carbon development in UAs based on the theory of Environmental Kuznets Curve. The results show that carbon emissions of China's UAs are spatially distributed as higher in the east but lower in the west, and increase faster in the central. The effect of LCPP on carbon emissions is significant but inhibitory in the central and northeastern UAs, while it becomes insignificant in the eastern ones. Finally, the low-carbon development paths of all UAs are divided into Type I, strong Type I, Type II, Type III, and Type IV stage. The eastern UAs are all at Type I stage because they are more sensitive and ahead in terms of low-carbon development strategies. The findings of this study can provide references for city groups to formulate carbon reduction policies and decouple the relations between economic development and carbon emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study evaluates the effectiveness of microalgal-based carbon-encapsulated iron nanoparticles (ME-nFe) in the removal of pharmaceutical compounds (PhACs) from water solutions and real municipal effluent at a laboratory scale. The investigated PhACs were chosen to represent different classes of synthetic drugs: antibiotics, anti-inflammatory drugs, antihypertensives, antiepileptics, neuroprotectors, and antidepressants. The adsorbent material was produced through hydrothermal carbonization (225 °C for 3 h), using microalgae grown on wastewater as the carbon source. ME-nFe showed heterogeneity in terms of porosity (with both abundance of macro and mesopores), a total pore volume of 0.65 mL g -1 , a specific surface area of 117 m 2  g -1 and a total iron content of 40%. Laboratory scale adsorption tests (1 g L -1 of nanoparticles with 2 min contact time) showed high removal for the most hydrophobic compounds. Removal efficiencies were high (over 98%) for Irbesartan, Ofloxacin and Diclofenac, promising (over 65-80%) for Clarithromycin, Fluoxetine, Lamotrigine and Metoprolol, but low for Gabapentin-Lactam and Propyphenazone (<20%). Electrostatic interactions between the drugs and the surface of the nanoparticles may account for the observed data, although additional removal mechanisms cannot be ruled out., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

With the swift expansion of global digital infrastructure, understanding its impact on carbon emissions is essential for addressing global warming. This study develops a digital infrastructure indicator system. We use panel data from 83 countries spanning 2005 to 2021 to thoroughly examine the effects and underlying mechanisms of digital infrastructure on carbon emissions. Our findings indicate that digital infrastructure contributes to an increase in carbon emissions worldwide. Mechanism tests suggest that this increase is facilitated by capital agglomeration and fossil energy consumption. However, the impact of digital infrastructure on carbon emissions shows regional variations. In the Arab region, digital infrastructure development seems to reduce carbon emissions, a trend also observed, albeit potentially, in the CIS, Africa, and the Americas. In contrast, Europe and the Asia-Pacific experience a significant surge in carbon emissions due to digital infrastructure. Population density and the proportion of renewable energy emerge as critical threshold variables. Beyond a certain population density, the impact on carbon emissions intensifies, whereas an increase in renewable energy share beyond a specific point mitigates this effect. Robustness tests confirm that digital infrastructure elevates both per capita carbon emissions and carbon intensity, with digital markets and technologies notably amplifying carbon emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Blue carbon ecosystems (BCEs), such as mangroves, saltmarshes, and seagrasses, are important nature-based solutions for climate change mitigation and adaptation but are threatened by degradation. Effective BCE restoration requires strategic planning and site selection to optimise outcomes. We developed a Geographic Information System (GIS)-based multi-criteria decision support tool to identify suitable areas for BCE restoration along the 2512 km-long coastline of Victoria, Australia. High-resolution spatial data on BCE distribution, coastal geomorphology, hydrodynamics, and land tenure were integrated into a flexible spatial model that distinguishes between passive and active restoration suitability. The tool was applied to identify high-priority locations for mangrove, saltmarsh, and seagrass restoration across different scenarios. Results indicate substantial potential for BCE restoration in Victoria, with 33,253 ha of suitable area identified, mostly (>97%) on public land, which aligned with the selection criteria used in the tool. Restoration opportunities are concentrated in bays and estuaries where historical losses have been significant. The mapped outputs provide a decision-support framework for regional restoration planning, while the tool itself can be adapted to other geographies. By integrating multiple spatial criteria and distinguishing between passive and active restoration, our approach offers a new method for targeting BCE restoration and informing resource allocation. The identified restoration potential will also require collaboration with coastal managers and communities, and consideration of socio-economic factors. With further refinements, such as incorporating multi-criteria decision analysis techniques, GIS-based tools can help catalyse strategic blue carbon investments and contribute to climate change mitigation and adaptation goals at different spatial scales. This study highlights the value of spatial identification for BCE restoration and provides a transferable framework for other regions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Peter I. Macreadie reports financial support was provided by Australian Research Council. Stacey M. Trevathan-Tackett reports financial support was provided by Australian Research Council. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Carbon emissions trading scheme (ETS) will change the internal and external operating environment of related companies, increase new carbon reduction costs, and may affect their investment behavior and decision-making. This study constructs the policy effect evaluation model to evaluate the net effect of China's ETS pilot policy on the investment efficiency of related companies in high-carbon industries. This study indicates that: first, China's ETS pilot policy has reduced the inefficient investment of related companies by 11.40% during the sample period. Second, innovation ability plays an enhanced moderating effect in the inhibitory effect of China's ETS pilot policy on the inefficient investment of related companies in the short term, but the effect is weakened in the long-term. Third, the policy effect is relatively obvious for non-state-owned companies and companies with more institutional shareholdings. This research has important reference value for the continuous improvement of China's national carbon market, and the steady transformation from simple investment-driven to investment-efficiency-driven economic development in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Pyrolyzing biomass (e.g., crop straw) to produce biochar is a sustainable strategy in agricultural farmlands. Straw-derived biochar could increase soil organic carbon (SOC) and microbial-derived carbon (C) compared to no addition, while it is imperative to understand the effects of straw-derived biochar compared to its feedstock (e.g., straw). We retrieved 321 and 387 observations to investigate the effects of straw-derived biochar on microbial-derived C (e.g., microbial biomass C (MBC) and microbial necromass C (MNC)) taking no addition and straw as control, respectively. Notably, straw-derived biochar significantly increased dissolved organic C (DOC) by 24.9% and provided available substrates for microbial utilization, thus improving MBC by 16.7% and MNC by 19.7% compared to no addition. Nevertheless, compared to its feedstock (crop straw), straw-derived biochar significantly decreased MBC by 26.1% and MNC by 18.0% attributed to lower DOC, supported by a positive correlation between MBC and DOC (R 2  = 0.53). A negative correlation between changes in MBC and SOC indicated the adverse of microbial activity for C accrual under conversion from straw to biochar. Moreover, soil layer, experiment duration, and initial C/N ratio are the crucial factors affecting MBC under the conversion from straw to biochar. Specifically, with significant variations among subgroups, when compared to straw addition, straw-derived biochar had lower reduction in MBC observed on 0-5 cm layers, mean annual precipitation ≥550 mm, mean annual temperature ≥10 °C, clay loam soil, experiment duration≥1 yr, initial SOC≥14 g kg -1 , pH≥8, and bulk density ≥1.28 g cm -3 . Straw-derived biochar even increased MBC by 32.8% in an anaerobic environment, associated with biochar produced under limited oxygen and anaerobic microorganisms dominating the microbial community. This study concludes that the conversion from crop straw to biochar increases SOC but constrains microbial-derived C, which may disturb the microbial-mediated C-cycling process., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Promoting digital governance is crucial for the Chinese government's governance reform. This study utilizes panel data covering 280 cities in China to examine the influence of government digital governance on reducing carbon emissions. The "National Pilot Policy of Information Benefiting the People," implemented in 2014, serves as the quasi-natural experiment for the analysis. The study employs the difference-in-difference (DID) methodology to indicate that improving the government's digital capacity contributes to reducing carbon emissions, which is robust to several robustness tests. Government digital governance facilitates the reduction of carbon emissions primarily via three mechanisms: developing green finance, gathering green talents, and promoting green technology innovation. Enhanced digital governance by the government exerts a more pronounced effect on reducing carbon emissions in cities in the eastern region, smaller municipalities, and resource-dependent municipalities. Additionally, current policies have notably decreased carbon emissions in the pilot cities, though a lag exists in the policy spillover effect affecting neighboring cities. This study investigates the influence of government digital governance on reducing carbon emissions through the lens of digital transformation. It offers valuable empirical insights for enhancing the governance capabilities of the Chinese government in the new era and facilitating the achievement of carbon reduction targets in urban areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Dual control policies aim to effectively reduce energy consumption and carbon emission by setting targets for total volume and intensity control. With global climate change becoming increasingly serious. China, as a large energy-consuming and carbon-emitting country, faces a huge challenge to reduce carbon emissions. The transition from the "dual control of energy consumption" to the "dual control of carbon emissions" in China is necessary to optimize energy structures, promote energy conservation, reduce carbon emissions, and reach carbon neutrality. This study utilizes multi-regional input-output models to evaluate the results toward both goals from production-based, consumption-based, and income-based perspectives. The findings indicate that "dual control of carbon emissions" is a more precise approach than "dual control of energy consumption". Some provinces have met the latter goal while still falling short of the former. Provinces having met their production-based energy intensity and carbon emission intensity targets, but having failed their consumption-based and income-based targets, are identified to develop a comprehensive and accurate assessment of these targets. A net outflow of embodied energy and carbon emissions is observed among provinces in less-developed central and southern regions to more-developed eastern and northern regions. Suggestions and policy implications based on these findings include establishing a comprehensive evaluation of energy and carbon intensity, considering both consumption-based and income-based perspectives, as well as facilitating enhanced cooperation among developed and developing provinces., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Landscapes evolution have significantly altered the Earth's energy balance and biogeochemical cycles, thereby exacerbating climate change. This, in turn, affects surface characteristics and the provision of ecosystem services, especially carbon storage. While recent centuries have witnessed unprecedented landscape changes, limited long-term studies have offered insights into the comparison between present-day features and historical conditions. This study utilized historical reconstruction data and remote sensing imagery to assess landscape evolution and its consequences for carbon stocks over 300 years. Employing multiple regression and random forest models were selected to quantify the influence of key landscape metrics on carbon stocks in the Dongting Lake basin, allowing for a thorough analysis across different sub-basins and land types. The results revealed that intensified human disturbances led to increased landscape fragmentation (+82%), regularity (+56%), and diversity (+37%) within the basin. Moreover, carbon stocks decreased from 4.13 Gt to 3.66 Gt, representing an 11.4% loss, with soil carbon stock experiencing the most considerable reduction (0.24 Gt, 51%). These changes in carbon stock metrics corresponded to shifts in landscape patterns, both undergoing significant transitions at the turn of the 21st century. Meanwhile, fragmentation and regularity played a vital role in explaining carbon stock changes, as their increase contributes to greater carbon losses. Likewise, an increase in landscape diversity correlated with decreased carbon stocks, challenging the prevailing notion that enhanced diversity promotes carbon stocks. The influence of landscape patterns on carbon stocks varies notably across distinct land types. An increase in the dominance of farmland and built-up land led to decreased carbon stocks, while the opposite holds true for forestland. Similarly, a decrease in regularity for farmland, forestland, and built-up land benefits carbon storage, while grassland demonstrates the opposite trend. These findings offer insights for countries and regions in the early stages of development or approaching development, suggesting improvements in land use practices and strategies to address climate change. This involves offsetting land-based carbon emissions through changes in landscape spatial configuration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

With the rapid expansion of human activities, there has been a significant increase in the release of volatile organic compounds (VOCs) from factories and interior decoration materials, posing a substantial risk to the surrounding ecosystem and human health. Photocatalysis technology based on semiconductors has emerged as a promising solution for mitigating atmospheric pollution and indoor air quality concerns. However, single semiconductors encounter several challenges when it comes to VOC photodegradation, including issues like the weak adsorption capacity for VOC molecules, insufficient surface-active sites, and limited light utilization. In recent decades, carbon-based materials have gained considerable interest in photodegrading VOCs owing to their strong adsorption capacity, electrical conductivity, broad light absorption range, and tunable surface characteristics. The incorporation of carbon materials can enhance the photodegradation efficiency of VOCs by facilitating the transfer of VOCs from the ambient air to the surface of the photocatalysts, increasing the number of active surface sites, expanding the light absorption region, and promoting the separation of charge carriers. This review provides a comprehensive overview of the applications of carbon materials with different dimensions in enhancing the performance of semiconductors for the photocatalytic degradation of VOCs. Based on the fundamental principles of photocatalytic VOC degradation, this review explores the factors influencing the degradation performance of catalysts and elucidates the degradation mechanisms. Moreover, it summarizes a range of synthesis approaches for carbon-based photocatalysts, discussing the multiple roles played by carbon materials in these processes. In conclusion, the review offers insights into the current state of carbon-based photocatalysts and outlines the existing challenges. It also provides a perspective on the future development of these materials, highlighting the need for continued research and innovation in this field., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

As a strategic resource, big data has become a key force affecting carbon emission reduction in agriculture. However, its impacts remain controversial, and relevant empirical evidence remains to be explored. Based on quasi-natural experimental analysis, this study explored the impact and mechanism of the construction of the National Big Data Comprehensive Pilot Zone (NBDCPZ) on agricultural carbon emissions (ACE) in China and adopted a difference-in-difference (DID) model using China's provincial panel data from 2003 to 2020. The results showed that the ACE in the NBDCPZ establishment area was significantly reduced by 11.91%, a finding that remained robust following the parallel trend test and the placebo test, among others. Mechanism analysis showed that the ACE was reduced through industrial upgrading and technological innovation. Heterogeneity analysis showed that more pronounced policy gains were achieved in China's central-eastern regions as well as in non-major grain-producing areas compared to western and major grain-producing areas. This research provided supporting evidence for the prospect of big data application in ACE and provided useful guidance regarding the promotion of green and sustainable agricultural development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Colloidal activated carbon (CAC) is an emerging remedial enhancement fluid that is injected into the subsurface to adsorb hazardous industrial compounds for subsequent removal. CAC-enhanced remediation relies on accurate subsurface characterization and monitoring to ensure CAC reaches intended treatment locations. The objective of this study was to assess the effectiveness of the spectral induced polarization (SIP) technique to track CAC migration within porous media and its adsorption of the chlorinated solvent, tetrachloroethylene (PCE). Dynamic column experiments were performed with cyclic injection and flow of groundwater, CAC, and PCE within porous media, and simultaneous measurements of SIP and effluent quality. Results showed an increase in both the real and imaginary conductivities of the SIP response during injection/flow of CAC within porous media. Real conductivity returned to pre-CAC levels during subsequent flushing of CAC with groundwater, which had left behind only carbon-coated soil grains; however, imaginary conductivity identified the change in polarizability due to the alterations on the grain surface. The subsequent adsorption of aqueous phase PCE did not generate a distinctive change in SIP response, mainly due to the low 50 mg/L concentrations used. Overall, this study suggests that SIP can be a valuable tool to effectively and non-invasively track the migration of injected CAC within porous media for contaminant adsorption, suggesting it can be used to enhance the implementation and management of environmental remediation programs., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Christopher Power reports financial support was provided by Natural Sciences and Engineering Research Council of Canada. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Grazing plays a key role in ecosystem biogeochemistry, particularly soil carbon (C) pools. The non-trophic interactions between herbivores and soil processes through herbivore trampling have recently attracted extensive attention. However, their concurrent and legacy effects on the ecosystem properties and processes are still not clear, due to their effects being hard to separate via field experiments. In this study, we conducted a 2-year simulated-sheep-trampling experiment with four trampling intensity treatments (i.e., T0, T40, T80, and T120 for 0, 40, 80, and 120 hoofprints m -2 , respectively) in a typical steppe to explore the concurrent and legacy effects of trampling on grassland ecosystem properties and processing. In 2017 (trampling treatment year), we found that trampling decreased aboveground biomass (AGB) of plant community and community-weighted mean shoot C concentration (CWM C), soil available nitrogen (N) and available phosphorus (P), but did not affect plant species diversity and belowground biomass (BGB). We show that compared with T0, trampling increased soil bulk density (BD) at T80, and decreased soil organic carbon (SOC) stocks. After the cessation of trampling for two years (i.e., in 2019), previous trampling increased plant diversity and BGB, reaching the highest values at T80, but decreased soil available N and available P. Compared with T0, previous trampling significantly increased soil BD at T120, while significantly decreased CWM C at T80 and T120, and reduced SOC stocks at T80. Compared with 2017, the trampling negative legacy effects amplified at T80 but weakened at T40 and T120. We also show that trampling-induced decreases in soil available N, AGB of Fabaceae and CWM C were the main predictors of decreasing SOC stocks in 2017, while previous trampling-induced legacy effects on soil available P, AGB of Poaceae and CWM C contributed to the variations of SOC stocks in 2019. Taken together, short-term trampling with low intensity could maintain most plant functions, while previous trampling with low intensity was beneficial to most plant and soil functions. The results of this study show that T40 caused by sheep managed at a stocking rate of 2.7 sheep ha -1 is most suitable for grassland adaptive management in the typical steppe. The ecosystem functions can be maintained under a high stocking rate through the process of providing enough time to rebuild sufficient vegetation cover and restore soil through measures such as regional rotational grazing and seasonal grazing., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Gaining a comprehensive understanding of the effect of land use/land cover (LULC) and soil depth on soil carbon storage, through the manipulation of external carbon input and turnover processes, is crucial for accurate predictions of regional soil carbon storage. Numerous research investigations have been conducted to examine the impact of LULC on the storage and cycling of carbon in the surface soils of coastal wetlands. Nevertheless, there remains a dearth of understanding concerning the implications of this phenomenon on subterranean soils, a crucial factor in discerning the capacity for carbon sequestration in coastal wetlands and implementing measures for their preservation. The study focused on the Yellow River Delta (YRD) in China, which serves as a representative model system. It aimed to assess the impact of LULC as well as soil depth on carbon storage. This was achieved by a combination of remote sensing interpretation and field samplings. The findings of the study indicate that there was an increase in soil organic carbon storage with both the area covered and the depth of the soil across the four different land use types, namely forest, grass, tidal flat, and cultivated land. Cultivated land was identified as the predominant LULC type, encompassing 41.73% of the entire YRD. Furthermore, it accounted for a substantial carbon storage of 76.08%. In comparison to soil layers at depths of 0-20 cm and 20-40 cm, 40-60 cm was discovered to have the maximum carbon storage, accounting for 42.29% of total carbon storage. Furthermore, one of the main factors influencing carbon storage is salinity, which shows a negative association with carbon storage. Moreover, the aforementioned findings underscore the significance of the conjoined physical and chemical properties induced by LULC in influencing the dynamics of soil carbon. This suggests that the inclusion of deep soil carbon in the estimation and restoration of soil carbon storage is necessary. This inclusion will support the realization of the United Nations' "Toward Zero Carbon" effort and facilitate the implementation of China's national carbon neutrality objectives., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Applying biochar to nitrogen (N)-fertilized soils is recognized as an effective technique for enhancing soil carbon (C) accumulation and improving agroecosystem sustainability. However, the impact of co-application of biochar and N fertilizer on soil C and N stocks, as well as their fractions, within the 0-60 cm soil profile remains unclear. This study examined the soil C and N fractions as well as stocks in soil profiles, and the primary influencing factors in wheat field with different rates of biochar (0, 20 and 40 t ha -1 ; B0, B1 and B2) and N application (0, 180 and 360 kg N ha -1 ; N0, N1 and N2). The results revealed that compared to B0N0 treatment, biochar plus N application increased soil organic carbon (SOC) and dissolved organic carbon (DOC), while N application alone decreased microbial biomass carbon (MBC). SOC in topsoil (0-10 cm) and DOC in subsoil (40-60 cm) were more susceptible to biochar and N application. The combined application of biochar and N enhanced soil N fractions, with NO 3 - -N having the highest sensitivity than the other N fractions, whereas biochar application alone decreased topsoil inorganic N content. Biochar and N application significantly altered soil C stocks (4.33%-42.20%) and N stocks (-1.24%-20.91%) within the 0-60 cm soil layers, and belowground biomass and SOC were the main influencing factors, respectively. The combination of moderate biochar (42.35 t ha -1 ) and N (277.78 kg ha -1 ) application was the most beneficial for soil C accumulation in the 0-60 cm depth. These findings indicate the positive impacts of co-applying of biochar and N in agroecosystems on soil C and N accumulations, and highlight the importance of C and N stabilization in both topsoil and subsoil under management practice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

With the increasing importance of environmental and economic sustainability concerns, the concept of Environmental, Social, and Governance (ESG) has gained significant attention. In the era of digitalization, a research approach called carbon sentiment analysis has emerged as an innovative method. This study aims to explore the connections between carbon sentiment, ESG, and corporate sustainable growth within the context of the green economy. By using Ordinary Least Squares (OLS) regression analysis and establishing a panel data model of ESG performance and sustainable growth for Chinese listed companies, a notable positive correlation between the two variables was observed. Endogeneity was addressed using the two-stage instrumental variable method (2SLS) and the dynamic panel Generalized Method of Moments (GMM) model, with the results remaining robust both before and after the COVID-19 pandemic. Carbon-related news and textual information were collected and analyzed using advanced deep learning methods in Natural Language Processing (NLP), specifically Bidirectional Encoder Representations from Transformers (BERT) and Long Short-Term Memory (LSTM) models. This analysis enabled sentiment analysis and identification of the sentiment orientation of carbon news. The obtained sentiment scores were then integrated with company data to establish a moderation effect model. The findings of the study reveal that carbon sentiment significantly and positively moderates ESG performance in relation to corporate sustainable growth. Furthermore, the construction of a mediation effect model showed that carbon sentiment can moderate ESG performance by reducing environmental uncertainty, enhancing social trust, and alleviating financing constraints, thereby influencing corporate sustainable growth. The results of the heterogeneity group regression analysis demonstrate that the impact of ESG performance driven by carbon sentiment on sustainable growth is more pronounced in carbon market pilot regions, non-heavily polluting industries, and labor-intensive industries. This research provides a fresh perspective for understanding the dynamics of ESG, online carbon sentiment, and their implications for corporate sustainable growth. Additionally, it contributes to the development of the green economy and the formulation of environmental management policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Driven by the "dual carbon" goal, it is essential to investigate whether companies can enhance carbon emission efficiency by improving Environmental, Social, and Governance (ESG) performance. This study investigates the relationship between ESG ratings and carbon emission efficiency among Chinese A-share listed companies. The study reveals that a higher ESG rating significantly improves carbon efficiency. Mechanism studies indicate that the effect of ESG mainly comes from easing financing constraints, promoting green innovation, and strengthening supervision. Additionally, the study finds that the impact of ESG on carbon emission efficiency is more pronounced in non-heavy polluting and non-state-owned enterprises. Economic policy uncertainty diminishes the positive effects of ESG initiatives on carbon efficiency, while enhanced governmental concerns to environmental significantly bolsters these impacts. This paper offers empirical insights that can inform adjustment of policies concerning ESG performance and carbon emission., Competing Interests: Declaration of competing interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Severe global climate change has resulted in the focus of social attention shifting to the manufacturing industry's low-carbon transformation. Digital intelligent transformation (DIT) in enterprises is identified as a crucial driver in mitigating carbon emissions. An estimation of DIT's impact on manufacturing industries' carbon emission intensity (CEI) and its underlying mechanisms was conducted using data from Chinese A-share listed companies. Research findings indicate that DIT significantly reduces corporate CEI. Robustness tests, such as the instrumental variable method and variable substitution method, confirm this conclusion. By enhancing labor productivity and accelerating capital renewal, DIT indirectly lowers CEI. Furthermore, non-state-owned enterprises with superior market competitiveness have been observed to be markedly adept at harnessing DIT for CEI. The heterogeneity test found that DIT has a considerably significant effect on reducing CEI in enterprises that are not low-carbon pilots, non-broadband pilots, smart pilots, non-provincial capitals, and eastern cities. This study provides new evidence supporting the promotion of enterprise DIT for achieving green development, offering insights for corporate policy making., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Photosynthetic carbon sequestration and microbial carbon metabolism are major processes of algae-bacteria interactions, affecting pollutant degradation as well as fundamental biogeochemical cycles in aquatic systems. Human-induced land-use changes greatly alter the molecular composition and input of terrestrial dissolved organic matter (DOM) in inland lakes. However, how the origin of DOM leads to varying effects on phycosphere microbial communities or molecular composition of DOM, e.g., via carbon metabolism, has been little studied in freshwater. Here, we incubated the cyanobacterium Microcystis aeruginosa and a bacterial community from natural lakes to establish an alga-bacteria model system. This allowed us to investigate how DOM from different sources affects phycosphere microbial diversity and DOM diversification. We showed that Suwannee River fulvic acid (SRFA), Suwannee River natural organic matter (SRNOM) and cropland lake DOM promote algal growth, whereas DOM from an urban lake inhibits algal growth. Algal metabolites and DOM together shaped the chemotaxis response of phycosphere communities. High-resolution mass spectrometry analysis demonstrated that DOM chemo-diversity tended to become uniform after interactions of diverse DOM sources with the algae-bacteria symbiosis system. Molecular thermodynamic analysis of DOM based on a substrate-explicit model further verified that microbial interactions render DOM less bioavailable and thus increase recalcitrant DOM formation. Metabolome analysis uncovered that DOM addition intensifies metabolic pathways related to labile and recalcitrant DOM utilization (mainly lignin/carboxyl-rich alicyclic molecule (CRAM)-like DOM, unsaturated hydrocarbon), whereby cofactor and vitamin metabolism represented an extremely strong activity in all metabolic pathways. Our results highlight covariation and interactions of DOM with microbial metabolism at the molecular level and expands our understanding of microbially mediated DOM shaping aquatic carbon cycling., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The continuous deepening of aging has posed new challenges for global sustainable development. Measuring the impact of population aging on carbon emissions is crucial for the next stage of climate governance. However, the structural changes in social production and consumption make it difficult to evaluate the impact effects. Therefore, this study constructed a bidirectional fixed Space Durbin Model to explore the mediating pathway of aging's impact on carbon emissions. Furthermore, we have established high-precision prediction models to simulate the evolution trajectory of carbon emissions under multi-factor driving scenarios. The main findings are as follows: (1) The process of carbon emission reduction due to population aging has significant energy hindrance effect and industrial structure effect, while the process of carbon growth is constrained by the consumption enhancement effect, technology progress effect and labor participation effect. (2) The moderating effects of energy consumption and technological innovation on carbon emissions under the aging process are 10.74% and 10.24%, respectively, while the moderating effects of industrial structure and labor force participation are relatively weak. (3) The goodness of fit of the MNGM-ARIMA and MNGM-BPNN models is over 97%. Carbon emissions in the high aging regions show a decreasing trend in all scenarios except the energy consumption-driven scenario, while in the medium and low aging regions decrease slowly only in the R&D- and labor supply-driven scenarios. This study advocates developing heterogeneous emission reduction measures based on the degree of aging, accelerating supply side upgrading, and increasing the proportion of green consumption., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Using two measures of firm carbon-risk exposure to capture convergent materiality, we examine whether the syndicated loan market considers borrowers' carbon-risk exposure in loan pricing. We find that carbon intensity does not constitute material information for banks, whereas environmental scores have a statistically significant but incidental economic effect on loan spreads. We also find inconclusive evidence that the market differentiates between firms in high and low environmentally sensitive industries. Finally, we show that green banks charge higher loan spreads to more environmentally responsible firms. Overall, we provide strong evidence that environmental scores matter in loan pricing decisions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The rapid advancement of artificial intelligence (AI) in the 21st century is driving profound societal changes and playing a crucial role in optimizing energy systems to achieve carbon neutrality. Most G20 nations have developed national AI strategies and are advancing AI applications in energy, manufacturing, and agriculture sectors to meet this goal. However, disparities exist among these nations, creating an "AI divide" that needs to be addressed for regulatory consistency and fair distribution of AI benefits. Here, we look at the linear effects of AI and the Paris Agreement (AI), as well as their potential interaction on carbon neutrality. We also investigate whether geopolitical risk (GPR) can hinder or enhance efforts to attain carbon neutrality through energy transition (ET). To measure carbon neutrality of G20 countries, we employed a robust parametric Malmquist index combined with the fixed-effect panel stochastic frontier model to account for heterogeneity. Results indicate that from 1990 to 2022, carbon neutrality has improved primarily due to technological advancements. Developed G20 countries led in technological progress, while developing countries showed modest gains in carbon efficiency. Using the Driscoll-Kraay robust standard error method, we found that AI has a positive but insignificant linear effect on carbon neutrality. However, the interaction between PA and AI was positive and statistically significant, suggesting that PA augments AI's potential in accelerating carbon neutrality. Energy transition accelerates carbon neutrality in both developed and developing G20 countries. However, the role of energy transition in achieving carbon neutrality becomes negative when the interaction term between energy transition and geopolitical risk (ET × GRP) is incorporated. Regarding control variables, green innovation positively impacts carbon neutrality, whereas financial development has an insignificant effect. Industrial structure and foreign direct investment both negatively affect carbon neutrality, thereby supporting the pollution haven hypothesis. It is recommended that strategies to bridge the "AI divide" and uphold geopolitical stability are crucial to achieve carbon neutrality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Based on the panel data of 496 firms from 2013 to 2020, this paper empirically tests the synergistic emission reduction effect and its action path of carbon emission trading mechanism and green financial tools. The study found that carbon emission trading mechanism, green credit tool, and green bond tool all significantly inhibited corporate carbon emissions. At the same time, the synergy between the carbon emission trading mechanism and the two green financial tools further effectively reduces the carbon emissions of enterprises. Green innovation plays an intermediary role between the synergistic effect on the carbon emission reduction of enterprises. That is, the carbon emission trading mechanism and green financial tools jointly promote green innovation to achieve carbon emission reduction. The impact of synergistic emission reduction mechanism on corporate carbon emissions is heterogeneous due to differences in corporate ownership, industry and region. Accordingly, we should pay attention to the synergistic emission reduction effect of carbon emission trading mechanism and green financial tools based on the mediating role of green innovation in improving the performance of corporate carbon emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study addresses the ongoing debate concerning the environmental implications of cryptocurrencies. Specifically, it investigates the impact of Bitcoin trading volume on water and sanitation (Sustainable Development Goal (SDG) 6) and climate action (SDG 13). The research employs Ordinary Least Squares (OLS) panel data analysis to examine these relationships using a sample of 32 countries with available Bitcoin trading volume data from 2013 to 2020. The findings indicate that Bitcoin trading significantly and positively impacts progress towards SDG 6, suggesting potential benefits for water and sanitation initiatives. However, the study reveals a significant negative impact of higher Bitcoin trading volume on increased carbon emissions, underscoring the environmental costs associated with cryptocurrency activities. Similar impacts are observed for gold reserves, as their mining necessitates substantial energy consumption. These results highlight the need to regulate cryptocurrency trading and promote voluntary sustainable practices, particularly given the disparities between developed and emerging markets based on their governance frameworks. Additionally, the study considers the disparities between countries based on technology exports and economic policy uncertainty as influential determinants. The study's results emphasize the importance of proactive measures to ensure the responsible and sustainable use of cryptocurrencies. While cryptocurrencies offer significant economic returns, their early adoption stage necessitates further investigation into environmentally friendly approaches. Potential strategies include directing financial returns from cryptocurrencies towards alternative energy projects and supporting other environmental SDGs, thereby fostering a positive impact on the overall ecosystem. The study's implications extend to policymakers, regulators, and stakeholders, advocating for comprehensive and collaborative efforts to integrate sustainability into the rapidly evolving cryptocurrency market. This integration is crucial to ensure that the economic benefits of cryptocurrencies do not come at the cost of our environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Soil organic carbon and nitrogen play pivotal roles as indicators of soil quality and ecological functioning in wetlands. The escalating impact of human activities and climate change has led to a severe degradation of wetland soils, particularly in semi-arid regions. However, an understanding of the factors governing the dynamics of total soil organic carbon (TSOC) and total soil nitrogen (TSN) in semi-arid areas remains elusive, impeding a comprehensive understanding of wetland ecological functions. The present study investigated variations in TSOC and TSN content as well as vegetation and soil physicochemical properties under five different land management practices (mowed wetlands, mowed and slightly grazed wetlands, moderately grazed wetlands, heavily grazed wetlands, and natural wetlands unaffected by human interference) in the semi-arid Songnen Plain region of China. The results revealed significant decreases in TSOC and TSN content within managed wetlands compared to natural wetlands. Moreover, positive correlations were observed between pairs of SOC-TN or their storage values for SOC (TSOC)-TN (TSN). Furthermore, TSOC and TSN exhibited significant positive associations with aboveground and belowground biomass levels, stem C:N, stem C:P, soil C:P, and soil N:P. Additionally, redundancy analysis indicated that species diversity accounted for 37.4% of the variations in TSOC-TSN while belowground biomass accounted for 8.5% of the variations. Furthermore, nutrient content within stems (particularly N content and C:P) contributed to a 37.2% variation in TSOC and TSN whereas root nutrient content (especially N:P, C:N, and C:P) contributed to a 15.3% variation. Soil C:P, C:N, and total phosphorous (TP) content accounted for 65.7%, 9.6%, and 7.5% of variations of TSOC and TSN, respectively. Besides, variation partitioning analysis revealed that plant community characteristics, community nutrient content, and soil physicochemical properties collectively influenced the dynamics of TSOC and TSN. Among these factors, soil physicochemical properties emerged as the primary drivers of carbon and nitrogen dynamics in degraded wetlands in semi-arid regions. The impact on TSN was more pronounced than that of TSOC. This study provides valuable insights for understanding the processes and mechanisms underlying carbon and nitrogen accumulation in degraded wetlands, facilitating the development of regionally adaptive management plans under different management practices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Tropical deforestation in the African continent plays a key role in the global carbon cycle and bears significant implications in terms of climate change and sustainable development. Especially in Sub-Saharan Africa, where more than two-thirds of the population rely on forest and woodland resources for their livelihoods, deforestation and land use changes for crop production lead to a substantial loss of ecosystem-level carbon stock. Unfortunately, the impacts of deforestation and land use change can be more critical than in any other region, but these are poorly quantified. We analyse changes in the main carbon pools (above- and below-ground, soil and litter, respectively) after deforestation and land use/land cover change, for the Jomoro District (Ghana), by assessing the initial reference level of carbon stock for primary forest and the subsequent stock changes and dynamics as a consequence of conversion to the secondary forest and to five different tree plantations (rubber, coconut, cocoa, oil palm, and mixed plantations) on a total of 72 plots. Results indicate overall a statistically significant carbon loss across all the land uses/covers and for all the carbon pools compared to the primary forest with the total carbon stock loss ranging between 35% and 85% but with no statistically significant differences observed in the comparison between primary forest and mixed plantations and secondary forest. Results also suggest that above-ground carbon and soil organic carbon are the primary pools contributing to the total carbon stocks but with opposite trends of carbon loss and accumulation. Strategies for sustainable development, policies to reduce emissions from deforestation and forest degradation, carbon stock enhancement (REDD+), and planning for sustainable land use management should carefully consider the type of conversion and carbon stock dynamics behind land use change for a win-win strategy while preserving carbon stocks potential in tropical ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Regions can meet their development demands through trade, with the attendant environmental costs being shifted to other regions, and carbon emissions emitted from different industries could be transferred over long distances through the increasingly diversified trade network. However, it remains unclear how regional trade leads to the tele-connection and transfer of embodied carbon emissions form industries, and what is the structure and characteristics of the transfer. Thus, multiregional input‒output models and complex network analysis are employed to reveal the tele-connection of carbon emissions from industries in China. The results show that embodied carbon emissions from trade increased by 869.47 million tons during in five years, with North China being the largest outflow area, while the coastal regions being the inflow areas. Moreover, the secondary industry is the highest source of embodied carbon emissions, accounting for 96.68 % of the volume, and the transfer of carbon emissions mainly occurs in North and East China. In carbon emissions networks, North China holds a controlling position, as analysed by degree and strength. The first 23.3%-30% of nodes carry about 62.6%-72.4% of the entire carbon emissions flow, and the network conforms to scale-free features. Centrality further reveals that northern and coastal areas occupy core positions, with interregional carbon flows dominating the critical pathways in the network. The number of clusters evolved from three to four communities during 2012-2017 in the network, demonstrating that the carbon flow network is developing towards multipolarity and modularity. This study underscores the urgency of mitigating carbon emissions in industrial trade by identifying key nodes and cluster structures in emission networks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

China and the USA, as preeminent contributors to global carbon emissions, demonstrate discernible differentials in both magnitude and trajectories of their respective carbon outputs. This article employed two methods, Structural Decomposition Analysis (SDA) and Quantitative Structural Modeling, to scrutinize the underpinnings of these disparities through the lens of the global value chain. Drawing upon data from the World Input-Output Database (WIOD), our analysis revealed that the compounded influences of output composition, input intensity, input composition and input origin collectively elevated China's aggregate carbon footprint from 2000 to 2014, while the scale effect made China's carbon emissions lower than of the USA. Notably, China's carbon emissions surpassed those of USA, with the gap accentuating over time. The quantitative results of the structural model showed that the difference in carbon emissions between China and USA predominantly stem from disparities in productivity, production technology, factor intensity, factor endowment and direct carbon intensity. Differences in trade costs exhibited some discernible impact, their influence remains relatively marginal, whereas distinctions in consumption behaviors and trade imbalances minimally contribute to the observed differentials. These findings have important policy implications for global carbon reduction efforts and China's trajectory towards a low-carbon economic paradigm., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Digital technology advancement provides a significant impetus to achieve China's "dual-carbon" goals, yet it also gives rise to a series of challenges. Therefore, studying the relationship between digital technology innovation and carbon emission efficiency is of paramount importance. This study theoretically analyzes and empirically tests the influence of digital technology innovation (DTI) on total factor carbon emission efficiency (TFCE) using panel data from 268 Chinese cities between 2006 and 2021. The results indicate that: (1) DTI exhibits a "U-shaped" pattern on urban TFCE, with a decrease followed by an increase. (2) Conventional technological innovation (TI) also displays a "U-shaped" relationship with TFCE, with the turning point occurring earlier than that of DTI. DTI surpasses TI in bringing about later-stage improvements in carbon emission efficiency. (3) Mechanism tests reveal that digital technology innovation indirectly affects TFCE through energy effects, technological effects, structural effects, and regulatory effects. (4) The impact of DTI on urban TFCE varies significantly due to differences in geographical location and resource endowments. (5) The development of urban polycentricity advances the turning point at which DTI enhances TFCE while amplifying both the initial "pro-carbon" effect and the subsequent "carbon reduction" effect of DTI. (6) DTI has a spatial spillover effect on urban TFCE. This study provides empirical evidence and policy recommendations for policymakers to advance the digitalization, greening, and decarbonization transformation of cities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Vietnam's government is considering introducing a carbon market as part of its decarbonization strategy. The carbon tax is an option for the government to regulate greenhouse gas emissions. We evaluate the potential macroeconomic and climate impacts of carbon tax policy in Vietnam using a unique data set and simulation analysis with a multi-sector dynamic computable general equilibrium model. The model allows for firm heterogeneity: domestic firms and foreign-invested enterprises. The results show that with plausible tax rates, emissions can be reduced to levels 1.3-2.8 percent below the target value of emissions in 2030. The cost is a loss in GDP by 1.2-2.7 percent in 2030. The results also show that foreign-invested enterprises tend to increase emissions in the medium run even with a carbon tax while a carbon tax is more effective when applied to domestic firms. In addition, a substantial reduction in emissions from the energy sector and improvement in energy efficiency are keys to success in carbon abatement., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Exploring the ecological utility of cultivated land's carbon metabolism offers policy insights for ensuring its healthy operation and promote the dual carbon goals (carbon peak and carbon neutrality). We employed ecological network analysis (ENA) and kernel density estimation to conduct an empirical study, taking Hubei Province from 2000 to 2020 as an example. The results revealed apparent negative effects of carbon metabolic flow on regional carbon balance. Specifically, cultivated land conversion into transportation and industrial land contributed significantly to the harmful carbon flow. Ecological relationships showed fierce competition for carbon storage, leading to overall adverse ecological effects. The ecological utility indicated detrimental impacts on the orderly functioning of land-use carbon metabolism. Cultivated land's carbon metabolism will be essential in achieving land-use carbon neutrality. Therefore, territorial spatial low-carbon optimization should be implemented to realize its green and sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The dune ecosystem plays a significant role in the global carbon cycle. The Horqin Sandy Land is a typical semi-arid fragile ecosystem in northern China. Understanding the magnitudes and dynamics of carbon dioxide fluxes within this region is essential for understanding the carbon balance. Used 6 years (2013-2018) measurements from an eddy-covariance system, we analyzed the dynamic patterns of net ecosystem carbon exchange (NEE), gross primary production (GPP), and ecosystem respiration (Reco) of the dune ecosystem in Horqin Sandy Land and examined their responses to climate factors with a focus on the precipitation. The results showed that the NEE of the dune ecosystem fluctuated from -166 to 100 gCO 2 ·m -2 ·year -1 across the 6 growing seasons, with an average of -56 gCO 2 ·m -2 ·year -1 . The precipitation was not a key factor influencing the carbon flux variability. During the mid-growth stage, GPP was primarily affected by the effective precipitation frequency (R 2 ranging from 0.65 to 0.85, P < 0.05), followed by fractional vegetation cover (R 2 ranging from 0.65 to 0.68, P < 0.05). However, in the early and late growth stages, temperature predominantly drove the carbon flux (R 2  = 0.75, P < 0.01). The interannual variability of carbon flux can be predominantly elucidated by phenological indicators such as CO 2 uptake (CU start ), end of CO 2 uptake (CU end ), CO 2 uptake period (CUP), and Spring lag. The results demonstrated the dune ecosystem is a weak carbon sink in semi-arid ecosystems. Furthermore, we emphasized the significance of effective precipitation frequency in regulating carbon fluxes. Our results provide a foundational understanding of the carbon balance in semi-arid ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

This study explores the comprehensive effects of green finance (GF) on the low-carbon transition of the energy system (LTES) by analyzing panel data from 281 cities in China from 2006 to 2021. It is found that GF significantly reduces overall energy consumption and exhibits a U-shaped association with energy efficiency, while its relationship with the energy consumption structure is inverted U-shaped. After accounting for endogeneity in the robustness tests, these findings remain consistent and are therefore deemed reliable. A mechanistic analysis reveals that GF promotes industrial upgrading, technological progress, and economic agglomeration, collectively facilitating the LTES. The impact of GF on LTES shows considerable variation among regions, influenced by their levels of economic growth, extents of marketization, and governmental environmental preferences. Our findings provide new evidence for the relationship between GF and LTES, offering a scientific basis for formulating GF policies to accelerate this transformation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Urban areas contribute 85% of China's CO 2 emissions. Green finance is an important means to support green energy development and achieve the low-carbon transformation of high-energy-consuming industries. The motivation of this article is to investigate the impact and mechanism of green finance on urban carbon intensity. Most existing literature uses linear models to investigate urban carbon intensity, ignoring the nonlinear relationships between economic variables. The nonparametric models can fill the inherent shortcomings of linear models and effectively simulate the nonlinear nexus between economic variables. Based on the 2011-2021 panel data of 237 cities in China, this paper applies the nonparametric additive model to survey the influence of green finance on urban carbon intensity. Empirical findings exhibit that green finance exerts an inverted U-shaped effect on urban carbon intensity, indicating that the carbon reduction effect of green finance has gradually shifted from inconspicuous in the early stages to prominent in the later stages. Then, from the perspectives of region, city size, and carbon intensity, this article conducts heterogeneity analysis. The results show that the impact of green finance on various carbon intensities all exhibits obvious nonlinear feature. Furthermore, this article employs a mediation effect model to conduct mechanism analysis. The results display that technological progress and industrial structure are two important mediating variables, both of which produce an inverted U-shaped nonlinear impact on urban carbon intensity., Competing Interests: Declaration of competing interest We hope this article will be considered for publication in “Journal of Environmental Management”. No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Heavy metals (HMs) contained terrestrial ecosystems are often significantly display the antibiotic resistome in the pristine area due to increasing pressure from anthropogenic activity, is complex and emerging research interest. This study investigated that impact of chromium (Cr), nickel (Ni), cobalt (Co) concentrations in serpentine soil on the induction of antibiotic resistance genes and antimicrobial resistance within the native bacterial community as well as demonstrated their metabolic fingerprint. The full-length 16S-rRNA amplicon sequencing observed an increased abundance of Firmicutes, Actinobacteriota, and Acidobacteriota in serpentine soil. The microbial community in serpentine soil displayed varying preferences for different carbon sources, with some, such as carbohydrates and carboxylic acids, being consistently favored. Notably, 27 potential antibiotic resistance opportunistic bacterial genera have been identified in different serpentine soils. Among these, Lapillicoccus, Rubrobacter, Lacibacter, Chloroplast, Nitrospira, Rokubacteriales, Acinetobacter, Pseudomonas were significantly enriched in high and medium HMs concentrated serpentine soil samples. Functional profiling results illustrated that vancomycin resistance pathways were prevalent across all groups. Additionally, beta-lactamase, aminoglycoside, tetracycline, and vancomycin resistance involving specific bio-maker genes (ampC, penP, OXA, aacA, strB, hyg, aph, tet(A/B), otr(C), tet(M/O/Q), van(A/B/D), and vanJ) were the most abundant and enriched in the HMs-contaminated serpentine soil. Overall, this study highlighted that heavy-metal enriched serpentine soil is potential to support the proliferation of bacterial antibiotic resistance in native microbiome, and might able to spread antibiotic resistance to surrounding environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)