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Addressing the escalating impacts of climate change, this study explores the potential of CO 2 storage in submarine sediments, presenting a promising strategy for sustainable global warming mitigation. We examine the dynamics and stability of CO 2 hydrate caps using magnetic resonance imaging to investigate their spatial-temporal distribution under varying flowrates and storage pressures. Our findings indicate that hydrate caps predominantly expand along the flow direction, influenced significantly by the state of CO 2 (liquid or gas) and operational parameters (storage pressure and CO 2 flowrate). Notably, higher flowrates and pressures expedite hydrate formation, thereby mitigating the risks of injection well blockages and enhancing cap stability. However, excessively rapid formation may compromise cap thickness and effectiveness. The study delineates optimal conditions that sustain hydrate cap integrity, advocating for a minimum safety pressure of 9000 kPa to prevent failure. These insights significantly advance the development of efficient CO 2 storage strategies in submarine environments, offering vital guidance for policy and industry practices aimed at achieving carbon neutrality. By highlighting the technological challenges and solutions associated with deep-sea CO 2 storage, this research contributes to the broader discourse on innovative approaches to climate change mitigation. [Display omitted] • Dynamic formation charactistics and stability of CO 2 hydrate storage cap is revealed. • Hydrate caps mainly expand along the flow direction and shows a spatial dependence. • Higher flowrates and pressures expedite hydrate formation and enhance cap stability. • A minimum safety pressure of 9000 kPa is delineated to sustain hydrate cap integrity. [ABSTRACT FROM AUTHOR]

Climate protection goals and the transformation of the mobility sector are pushing the shipping industry to develop new propulsion systems emitting fewer or no greenhouse gases. One promising approach to eliminate greenhouse gas emissions from ships is a hybrid propulsion system powered by fuel cells and batteries. A high-temperature solid oxide fuel cell (SOFC) can supply heat and the electrical power demand in combination with a battery. Due to the low dynamic performance of the SOFC when faced with sudden load changes, a battery is responsible for providing the power for the dynamic load components. To ensure the resource-efficient operation of the propulsion components, intelligent energy management methods are required for power distribution control. Implementing a machine-learning-based energy management method based on twin-delayed deep deterministic policy gradient (TD3) improves the overall system efficiency, lifetime, and fuel economy compared to conventional energy management methods. To verify the technical feasibility of the propulsion system including its controls, the system is tested in a hardware-in-the-loop (HIL) environment. By implementing the TD3-based algorithm within the energy management used on the test bench, hydrogen consumption was reduced by approximately 10% and the remaining battery capacity after five years was 6% higher in comparison to conventional energy management methods. [Display omitted] • Hybrid electric propulsion system for a marine application. • Development of machine-learning-based energy management algorithms. • Validation measurements with propulsion components. • Assessment of the economic performance for a large cruise ship application. [ABSTRACT FROM AUTHOR]

Sustainable socio-economic development requires a global reduction of greenhouse gas emissions. We utilize an incentivized experiment to map the preferences of 'policymakers' over climate actions of 'decision-makers'. Our design guarantees that these preferences are unaffected by selfish motives such as a concern about being re-elected or an unwillingness to pay for the greater good. Few of our impartial policymakers choose interventions that leave the autonomy of decision-makers' completely untouched. The choice patterns of those who intervene suggest that policymakers care not only about minimizing emissions, but also about how emissions are reduced. Policymakers strongly prefer pricing policies over capping emissions, and among the pricing policies, they prefer those that include voluntary carbon offsets, even if this leaves considerable scope for decision-makers to selfishly emit CO 2. The reason is that policymakers expect decision-makers to voluntarily offset some of their emissions at their own cost, and believe that this would eventually improve the outcome in terms of both emissions and the decision-makers' profit relative to a standard carbon pricing policy (without offsetting). Our decision-making data confirm this expectation. [ABSTRACT FROM AUTHOR]

Excessive application of synthetic fertilizer has resulted in serious soil degradation and significant greenhouse gases (GHGs) fluxes in farmlands. Partial organic substitution for synthetic fertilizer was considered as a possible strategy for sustainable agricultural development, but its potential effects on soil quality, GHGs emissions, and crop productivity remain unclear. A field experiment across 3-year was conducted to evaluate the responses of soil quality, nitrous oxide (N 2 O), carbon dioxide (CO 2), and methane (CH 4) emissions, and crop yields to different ratios of organic fertilizer (OF) to synthetic fertilizer (SF). Six treatments were included: non-fertilization (CK); total SF; total OF; 15 %, 30 %, and 45 % organic substitution (LO, MO, and HO). Soil cumulative N 2 O emission was decreased with increasing organic substitution ratios, mainly attributing to the reducing soil NH 4 + content. However, organic substitution increased soil CO 2 and CH 4 emissions due to the high manure-driven C input, consequently promoting global warming potential (GWP). Meanwhile, soil organic C, total N, P, available P, K, and C-acquisition enzyme activities were increased with organic substitution, resulting the higher soil quality index (SQI) under HO and OF. HO enhanced the annual yield of wheat and maize by 7.2 % and 13.0 % compared with SF and OF, respectively. The positive relationship between crop yield and SQI indicated that the yield-enhancing effect with partial organic substitution was mainly attributed to the improved synchronization in nutrient supply and soil fertility. Overall, partial organic substitution, especially 45 % organic substitution represents a viable strategy to improve soil quality and crop productivity while mitigating N 2 O emission in wheat-maize rotation systems. However, organic substitution promoted the GWP through stimulating soil CO 2 and CH 4 emissions. Further investigations of optimize fertilization managements are still needed to reduce manure-induced CO 2 and CH 4 emissions to achieve higher climate change mitigation. [Display omitted] • Organic substitution increased soil CO 2 and CH 4 emissions while reducing N 2 O emission. • HO and OF improved the SQI through increasing soil biochemical properties. • HO increased annual yield of wheat and maize compared with SF and OF. • Crop yield was positively related to the SQI. [ABSTRACT FROM AUTHOR]

Management practices in the inter-row area of olive orchards are undergoing significant transformations. Current regulations and recommendations are increasingly advocating the implementation of temporary spontaneous cover crops (TSCV) mainly to reduce erosion. Existing research has predominantly focused on evaluating the effectiveness of TSCV in mitigating soil erosion in olive orchards, with limited attention given to carbon (C) cycling, despite the potential of TSCV for contributing to the removal of atmospheric CO 2 and in the reduction of eroded carbon. Moreover, the limited number of studies on the effects of TSCV on C cycling have been confined to a few experimental sites and at the short term. This study aimed to assess the potential of TSCV to enhance carbon sequestration and nitrogen retention in rainfed commercial olive orchards under semi-arid conditions. To achieve this, we evaluated the annual aboveground organic carbon input due to TSCV, as well as the stocks of soil organic (SOC) and inorganic (SIC) carbon and total N (STN) in 24 commercial olive groves with calcareous Regosols and calcium Cambisols as the predominant soil types that have implemented TSCV for at least the last 8 years. These were compared with 24 comparable groves with bare soil (BS). Net aboveground annual carbon and CO 2 fixation of the TSCV averaged 125.7 kg C ha−1 y−1 and 460 kg CO 2 ha−1 y−1, respectively, which are figures relatively low mainly due to the low area covered by the TSCV. After eight years of implementing TSCV, the SOC stocks increased by an average of 2.03 Mg C ha−1 (in the top 30 cm of soil) compared to BS olive orchards. Moreover, SOC content of unprotected (>250 µm) and physically protected (53–250 µm) fractions were 82 and 38 % higher in the TSCV olive farms. Although there was a tendency of lower SIC content in TSCV olive orchards, differences were not significant. The STN content and the potentially mineralizable nitrogen in TSCV farms were on average 26 % and 77 % higher than in BS olive orchards. These findings underscore the potential of TSCV for organic carbon accumulation and nitrogen retention in the soil, contributing to climate change mitigation and soil fertility enhancement. Increasing vegetation coverage and productivity can enhance their effectiveness. • With TSCV on Calcareous Regosols and calcium Cambisols, SOC and STN were 25–26 % higher. • After 8 years of implementing TSCV, there were 2.0 Mg ha−1 (0–30 cm depth) more SOC compared to BS olive orchards. • Unprotected and physically protected C were the SOC fractions which most increased under TSCV. • SIC content tended to be lower under TSCV. • TSCV in olive groves demonstrated to contribute to climate change mitigation and N retention. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is a key factor in sustaining soil fertility, sequestering greenhouse gases and reducing soil erosion, in this regard, an accurate estimation and monitoring of the SOM content is crucial for sustainable land management and climate change mitigation strategies. In recent years, there has been a growing consciousness of the need to better understand the dynamics of SOM across different farm management in time and space. In this context, the main objective of the study is to improve understanding regarding the relationship between SOM and the main farming systems adopted in Italy by taking spatial correlation into account. For this purpose, a large dataset consisting of topsoil SOM values (0–20 cm) and environmental and farming information was collected in 597 locations (145 fields and 62 farms) representative of the whole agricultural area of Po Valley in Italy. This sizable dataset was analyzed by a novel geospatial analysis using a de-clustering approach in combination with polygon kriging for detecting and understanding the SOM variability over the different fields characterized by irregular shapes and different farming systems. The results provided clear evidences of the spatial correlation between SOM, farming systems and soil types. Higher SOM contents were detected in Cambisols (3.11 %) and in field managed according conservation agriculture practices (3.22 %) as compared to other farming systems. Moreover the inclusion of fodder crops in the rotation and the use of no-tillage are two of the most effective practices for increasing and preserving SOM according to our findings. Spatial information, such those provided in this study, could facilitate the delineation of tailored solutions for each European Member State for targeting future actions related to carbon farming, and offering crucial insights to support advancements in agriculture for enhancing soil fertility and health and for fostering sustainable agricultural practices. [Display omitted] • SOM estimation and monitoring is crucial for sustainable land management • Spatial information facilitates tailored solutions for enhancing soil health • A geospatial approach allowed to compare SOM content for the main farming systems • SOM content, farming systems and soil types are significant spatially correlated • Significant higher SOM content in field managed according conservation agriculture [ABSTRACT FROM AUTHOR]

Achieving China's ambitious carbon neutrality goal requires tangible action by the provinces. Significant heterogeneities between provinces make for divergent transition paths and different contributions to climate goals. To portray the dynamics of the energy transition at the provincial level, this study develops a China's provincial energy-environment-economic model (China TIMES-30PE) with special consideration of the interprovincial electricity transmission. To achieve carbon peaking, it is necessary to raise the carbon intensity reduction target on the basis of the 13th Five-Year Plan and enable rapid emission reductions through non-fossil energy expansion, end-use electrification, and the hydrogen boom to achieve carbon neutrality. Renewable energy and energy storage growth is concentrated in West, but electricity demand is growing rapidly in the East, creating a clear mismatch and making inter-provincial transmission and grid needs steeper. The central provinces shift from electricity exporters to electricity importers in future energy system landscape. By 2060, China is expected to form several major inter-regional power transmission routes from Northwest China to the Yangtze River Delta and Central China, from Inner Mongolia to Shandong, Beijing-Tianjin-Hebei and Henan, from Sichuan to the Yangtze River Delta, and from Yunnan to Guangdong. Driven by large-scale long-distance transmission, the capacity of ultra-high voltage lines is expected to increase rapidly. • Present the provincial carbon emission pathways towards carbon neutrality targets. • Provincial load curves are introduced in China TIMES-30PE model. • Large renewable power deployment increases the interprovincial power transmission. • The power transmission pattern is shifting towards long-distance and large-capacity. • Capacity of long-distance UHV lines grow rapidly under carbon neutrality targets. [ABSTRACT FROM AUTHOR]

• A between-subject design tested a dynamic social norm in a hypothetical school menu selection. • Two weekly school menus with greater and lesser environmental impacts were presented. • Intervention effectively pushed parents to select the environmentally friendly menu. • The nudge resulted in greater success among parents with lower levels of education. • Parents responsible for child-related practices were more susceptible to the nudge. Designing more sustainable school meal offerings not only contributes to environmental protection and climate change mitigation but also promotes children's health, provides food education, and raises awareness on sustainability issues. The present study, using a between-subject experimental online survey (N = 617), proved the effectiveness of a dynamic social norm nudge in encouraging parents to make more environmentally friendly choices when selecting school menus for their elementary school children. In addition, nudging was more successful in promoting sustainable food choices among parents with lower levels of education and those who are more actively involved and responsible for child-related practices. Disentangling the individual traits that leverage the effectiveness of nudges should allow public entities to fully exploit the potential of these interventions and design tailored approaches for targeted subpopulations. [ABSTRACT FROM AUTHOR]

More than 130 countries and regions have put forward various climate goals, which makes carbon-oriented energy system planning a heated topic. However, these planning studies do not consider the carbon fixation role played by forest carbon sinks (FCSs). To take advantage of the carbon fixation role of FCSs, this paper will develop a carbon-cycle integrated energy hub (CC-EH) model to quantify the economic advantages of FCSs in planning a zero-carbon energy system, where energy flow and carbon flow are both analyzed. A total planning and operating costs minimization with the constraints of CO 2 emissions is proposed as a mixed integer nonlinear programming (MINLP) optimization model and the overall problem is solved based on commercial solver. The proposed model is validated by case studies on six medium to large-size cities in different geographical locations in China. Results indicate that the typical cities in China can fulfill their carbon-neutral commitments by 2060. Throughout the entire planning period, FCSs can offset up to 55.31 % of the total carbon dioxide emissions from urban energy systems. Besides, FCSs achieved by forestation will help the energy system to reduce up to 36 % of the planning cost compared to the case without using FCSs. [Display omitted] • Forest carbon sink (FCS) is modeled considering CO 2 absorption and biomass growth. • FCS is applied to planning through a carbon-cycle integrated energy hub (CC-EH) model. • Coupling of energy system operation and FCS process on an hourly scale is realized. • A power function is introduced to characterize the transition path, and determine the optimal capacity of the CC-EH. • Typical cities in China are taken for case studies to analyze the impact of FCSs on the carbon neutral. [ABSTRACT FROM AUTHOR]

Container farm (CF) is a promising method to satisfy the urban vegetable demand and achieve global climate goals. Vegetable growth in fully artificial interior environments enables an efficient, steady, and year-round production of vegetables despite outdoor climate conditions. However, the high energy intensity associated with CF remains a bottleneck for its generalization. To minimize the energy consumption of container farms (CFs), this study conducted a detailed energy examination and proposed an energy optimization workflow. In the energy examination, an energy model was developed based on the lumped parameter method using EnergyPlus and validated by two benchmark experiments on a specific CF on Chongming Island, Shanghai. The results revealed that the predicted energy consumption was consistent with the measured energy consumption: the normalized mean bias error (NMBE) was <1%, and the coefficient of variation of the root-mean-square error (CV(RMSE)) was <25% for the hourly air-conditioning energy. With the validated energy model, energy optimization was considered in the hot period and other period, tailored to the local climate and characteristics of the equipment in the target CF. Based on parallel computing, the optimal envelope design was determined by enumeration in the hot period, whereas the optimal mechanical ventilation schedule was obtained by the selection-after-subdivision method in the other period. The maximal energy-saving potential of the two-period workflow was 773.4 kWh, which accounted for 33.8% of the original air-conditioning energy use, i.e. 25% more saving than the non-staged method. This study provides suggestions for the CF energy examination and support CF design improvements and operation decision-making. The examination process and optimization workflow can be extended to energy savings in other indoor agricultural methods. • An energy model for container farm (CF) was proposed and validated. • Two-period optimization proposed: CF envelope design in hot periods and mechanical ventilation in others. • Two-period method conserved 25% more HVAC energy than commonly-used non-staged method. • The optimized workflow can save up to 1/3 of the annual HVAC energy compared to the current CF. [ABSTRACT FROM AUTHOR]

Digital technology presents critical opportunities for controlling global warming within the 1.5 °C threshold established by the Paris Agreement. However, the nonlinear effects of data factors on climate resilience remain poorly understood. This paper, employing a Green Solow model within the framework of a Constant Elasticity of Substitution production function, uncovers a nonlinear, inverted U-shaped response. Utilizing a high-dimensional fixed-effects model and panel data from 30 Chinese provinces between 2011 and 2020, we identify a U-shaped relationship between data factors and low-carbon development in the manufacturing sector, with more pronounced effects in regions with higher levels of marketization. This impact is primarily driven by pathways such as green technological innovation and enhanced resource allocation efficiency. To further validate the global applicability of our findings, we extended the analysis to 166 countries worldwide. The results remained robust, indicating that the positive effects of improved data production factors on low-carbon development in the manufacturing sector are more significant in high-income countries, OECD member states, and nations with advanced digital infrastructure. Our study suggests that supporting and incentivizing data openness, promoting interaction and sharing of manufacturing data, and enhancing data center and network infrastructure construction are essential. [Display omitted] • A U-shaped relationship exists between data factors and low-carbon manufacturing. • Data factors impact low-carbon manufacturing via green innovation and efficiency. • The U-shaped relationship is more pronounced in regions with higher marketization. • Global analysis validates the findings, with stronger effects in advanced economies. [ABSTRACT FROM AUTHOR]

This viewpoint explores how intersectional thinking can help localise the Global Goal on Adaptation (GGA) to promote equity and justice in climate adaptation. Localising the GGA is essential for translating global objectives into actionable strategies at the local level. Adaptation goalsetting and current adaptation measurement approaches are hindered by the complexity of establishing shared metrics, the myopic focus on compliance and reporting, and the neglect of the dynamic, context-specific nature of adaptation processes. By incorporating intersectional thinking, we argue for a more nuanced approach that considers the compounded sources of vulnerability, especially in urban areas, where marginalised groups are disproportionately affected by climate impacts. We apply an Intersectional Climate Justice framework to guide the localisation of the GGA throughout the adaptation policy cycle, from impact, vulnerability, and risk assessment, to planning, implementation, and measurement. Embedding intersectional thinking throughout the GGA's adaptation policy cycle aligns global goals with local realities, enabling local actors to develop more comprehensive, context-specific strategies that address the needs and priorities of vulnerable communities. We also highlight the potential of intersectional climate justice to bridge climate action and broader development goals, ultimately fostering more equitable and just futures. • GGA lacks actionable framework, challenging practical implementation. • Localising the GGA ensures adaptation strategies reflect local needs and priorities. • Intersectional climate justice aligns local adaptation with global goals. • Intersectional thinking addresses social determinants of climate vulnerability. • Cities need intersectional approaches to tackle climate change impacts effectively. [ABSTRACT FROM AUTHOR]

Rising greenhouse gas emissions, especially CO 2 , intensify global warming. Carbon Capture and Storage (CCS) is vital for reducing emissions from industrial sources, crucial for addressing climate change urgently. This study explores reservoir characterization challenges for CCS in the Penobscot field, offshore Nova Scotia. We used to cross-plots of geophysical logs to establish relationships between petrophysical properties and subsurface litho-facies, differentiating sand and shale facies within the Mississauga Formation (Early to Middle Cretaceous). Seismic impedance inversion distinguished between reservoir and non-reservoir facies. Multi-attribute assisted transformed seismic data and a support vector machine algorithm predicted litho-facies probabilities and effective porosity volumes in 3D space. The permutation predictor importance analysis was performed to assess the relative importance of input features in facies probabilities and effective porosity prediction. The structural component delineated the CO 2 injection trap boundary. Integrated analysis of structural configuration, litho-facies probability, effective porosity, and cap-rock sealing integrity validated zones for CO 2 storage. The dry, abandoned well L-30 in the structural high zone is recommended as a pilot CO 2 injector well. This study provides critical insights into reservoir characterization for CO 2 sequestration, aiding climate change mitigation through effective CCS, and recommends geomechanical studies and time-lapse seismic monitoring. • Identified promising sites for CO 2 storage in Penobscot field, Canada Offshore. • Predicted impedance, facies probabilities, and effective porosity with high accuracy. • Enhanced discrimination between the reservoir and non-reservoir facies. • Assessed lithological and petrophysical characteristics of the reservoir and cap rocks. • Emphasised storage site identification as a strategy to mitigate climate change. [ABSTRACT FROM AUTHOR]

We develop a framework for incorporating biodiversity impacts into land use optimization models. Using the countryside species–area relationship, six approaches to incorporating biodiversity are evaluated: constraint versus objective function, and with characterization factors, piecewise linear, or non-linear implementation. We also consider the underlying ethical assumptions of different options for biodiversity evaluation considering taxa and ecoregions. To explore the six approaches, we use a case study that considers both climate change mitigation and the biodiversity impact due to habitat loss. We find that the characterization factor approach underestimates biodiversity loss, while the piecewise linear approach somewhat overestimates. Utilizing two approaches: biodiversity protection as the objective, and biodiversity as a constraint allows the construction of a Pareto frontier for cost versus loss of species. In addition to minimum cost solutions and minimum biodiversity loss solutions, the integrated model allows to identify (1) solutions with improved outcomes, those better for biodiversity and with small changes on costs, (2) mechanisms the model uses to achieve the improved solutions, (3) trade-offs and (4) challenges. [Display omitted] • We show how biodiversity can be included in land use optimization models. • A case study combines climate mitigation and biodiversity protection. • We illustrate biodiversity as a constraint or in the objective function. • Piecewise linear performs better than the characterization factor approach. • A Pareto frontier shows cost versus species trade-off and improvement possibilities. [ABSTRACT FROM AUTHOR]

With the galloping progress of the changing climates all around the world, Machine Learning (ML) approaches have been prevalently studied in many types of research in this area. ML is a robust tool for acquiring perspectives from data. In this paper, we elaborate on climate change mitigation issues and ML approaches leveraged to solve these issues and aid in the improvement and function of sustainable energy systems. ML has been employed in multiple applications and many scopes of climate subjects such as ecosystems, agriculture, buildings and cities, industry, and transportation. So, a Systematic Literature Review (SLR) is applied to explore and evaluate findings from related research. In this paper, we propose a novel taxonomy of Deep Learning (DL) method applications for climate change mitigation, a comprehensive analysis that has not been conducted before. We evaluated these methods based on critical parameters such as accuracy, scalability, and interpretability and quantitatively compared their results. This analysis provides new insights into the effectiveness and reliability of DL methods in addressing climate change challenges. We classified climate change ML methods into six key customizable groups: ecosystems, industry, buildings and cities, transportation, agriculture, and hybrid applications. Afterward, state-of-the-art research on ML mechanisms and applications for climate change mitigation issues has been highlighted. In addition, many problems and issues related to ML implementation for climate change have been mapped, which are predicted to stimulate more researchers to manage the future disastrous effects of climate change. Based on the findings, most of the papers utilized Python as the most common simulation environment 38.5 % of the time. In addition, most of the methods were analyzed and evaluated in terms of some parameters, namely accuracy, latency, adaptability, and scalability, respectively. Lastly, classification is the most frequent ML task within climate change mitigation, accounting for 40 % of the total. Furthermore, Convolutional Neural Networks (CNNs) are the most widely utilized approach for a variety of applications. • Touching on a comprehensive survey of the present challenges related to DL approaches for climate change mitigation applications. • Proposing a systematic overview of the existing methods for climate change mitigation in studied research. • Assessing each area with customized DL approaches with various aspects like benefits, limitations, datasets, security involvement, and simulation stings. • Outlining the pivotal sides that drive the referred methods to improve in future studies. • Illustrating the descriptions of particular climate change mitigation utilized in different research. [ABSTRACT FROM AUTHOR]

Energy poverty is a key dimension of multidimensional poverty and a major challenge for climate action. This study examines how climate policies affect energy poverty, especially the role of carbon tax revenue recycling in coordinating climate mitigation and energy poverty alleviation. Using an integrated Climate-Economy-Energy Poverty (RICE-EP) model that incorporates inequality aspects of energy poverty, the study analyzes the effects of climate policies on household energy consumption. The study simulates various scenarios of climate actions and carbon tax revenue recycling and finds that: i) Carbon tax revenue recycling can simultaneously advance climate change mitigation and energy poverty reduction goals, it can promote climate mitigation and enhance equity by lowering the abatement costs borne by low-income populations; ii) However, the interactions between stringent climate targets and energy affordability are complex. Modeling suggests that even optimal revenue recycling fails to prevent exacerbated energy poverty among disadvantaged groups under ambitious 2 °C climate targets; iii) Analysis indicates that an emissions reduction rate approaching 43 %, enabled by a carbon tax calibrated to incentivize an equitable transition, could maximize alleviation of energy poverty by directing subsidy support to low-income groups. The study methodology and findings offer valuable, actionable insights into coordinating equitable climate and economic policies. • An integrated Climate-Economy-Energy Poverty (RICE-EP) model has been developed. • Carbon tax revenue recycling alleviate energy poverty and reduce emission. • Achieving the 2 °C warming target will exacerbate energy poverty. • Developed countries should bear more emission reduction responsibilities. [ABSTRACT FROM AUTHOR]

Scientists have reached a consensus that limiting global warming to 1.5 °C necessitates achieving net-zero greenhouse gas emissions across all economic sectors. Numerous research institutes have prepared decarbonization strategies for the global and regional chemical industries, utilizing modeling and systems analysis to identify decarbonization pathways with different combinations of low-carbon technologies. However, technology choices and scenario designs vary widely across studies, which precludes generalizability and complicates the use of data and results by the broader decarbonization scenario modeling community. Given the varied scopes and objectives inherent in different system models, there is no standardized set of technology data for use in decarbonization pathways analysis. A systematic literature review of 27 relevant studies was performed, which found opportunities for improving technology representation, technology readiness, scenario consistency, demand factors, and policy interventions, among other quantitative elements. Only 7 out of 27 reviewed studies investigated all types of mitigation technologies, and only 3 studies included all data elements aligning with the proposed rubric in this paper. Considering these opportunities, this review proposes a comprehensive dataset structure and consistent scenario definitions that can enable more comprehensive, comparable, robust, and replicable net-zero decarbonization scenarios by modelers of the chemicals industry moving forward. [Display omitted] • Gaps in included technologies, data, and scenario elements in net-zero pathway modeling of the chemical sector are identified. • 80 % of the reviewed studies lack consideration of demand changes and policy implementations in their scenarios • 67 % of the reviewed studies overlooked technology readiness levels in deployment assumptions • Best-practice dataset structures are proposed to improve future modeling studies • Best-practice elements for more robust designs of decarbonization scenarios are proposed [ABSTRACT FROM AUTHOR]

Organic mulching offers numerous agronomical benefits, but its impact on wine quality remains unclear. This study assessed the effect of this practice on wine physicochemical, phenolic composition and sensory properties. Over four years, three organic mulches (grape pruning debris (GPD), straw (STR), and spent mushroom compost (SMC)) and two conventional practices (tillage (TILL) and herbicide (HERB)) were evaluated in two locations. Wines from mulching treatments exhibited higher pH, potassium, hue, and lower tartaric acid. Moreover, the SMC mulch treatment showed lower amounts of wine anthocyanins, flavonols and hydroxycinnamics, probably due to increased nutrient availability. However, no differences were detected in the wine sensory analysis. Therefore, organic mulches could be alternative practices to mitigate the consequences of climate change without significant impact on young wine's phenolic profile and sensory properties compared to HERB and TILL conventional soil management. However, future studies should focus on wine evolution during aging. • SMC organic mulch enhanced wine potassium, pH, hue and reduced acidity and TPI. • Phenolic content slightly differed depending on soil management practices. • In one field, SMC mulch reduced the amounts of anthocyanins and flavonols. • Soil management did not affect the sensory perception of wines in both fields. • STR and GPD: climate change mitigation with no impact on wine quality. [ABSTRACT FROM AUTHOR]

Spaceborne lidar (light detection and ranging) instruments such as the Global Ecosystem Dynamics Investigation (GEDI) provide a unique opportunity for global forest inventory by generating broad-scale measurements sensitive to the vertical arrangement of plant matter as a supplement to in situ measurements. Lidar measurables are not directly relatable to most physical attributes of interest, including biomass, and therefore must be related through statistical models. Further, GEDI observations are not spatially complete, necessitating methods to convert the incomplete samples to predictions of area averages/totals. Such methods can face challenges in equatorial and persistently cloudy areas, such as Indonesia, where the density of quality observations is diminished. We developed and implemented a hierarchical model to produce gap-free maps of aboveground biomass density (AGBD) at various resolutions within the lowlands of Jambi province, Indonesia. A biomass model was trained between local field plots and a metric from GEDI waveforms simulated with coincident airborne laser scanning (ALS) data. After selecting a locally suitable ground-finding algorithm setting, we trained an error model depicting the discrepancies between the simulated and GEDI-observed waveforms. Finally, a geostatistical model was used to model the spatial distribution of the on-orbit GEDI observations. These three models were nested into a single hierarchical model, relating the spatial distribution of GEDI observations to field-measured AGBD. The model allows spatially complete predictions at arbitrary resolutions while accounting for uncertainties at each stage of the relationship. The model uncertainties were low relative to the predicted biomass, with a median relative standard deviation of 8% at the 1 km resolution and 26% at the 100 m resolution. The spatially consistent information on AGBD provided by our model is beneficial in support of sustainable forest management, carbon sequestration initiatives and the mitigation of climate change. This is particularly relevant in a dynamic tropical landscape like Jambi, Indonesia in order to understand the impacts of land-use transformations from forests to cash crops like oil palm and rubber. More generally, we advocate for the use of hierarchical models as a framework to account for multiple stages of relationships between field and sensor data and to provide reliable uncertainty audits for final predictions. • We produced spatially complete predictions of biomass in a tropical landscape. • Hierarchical modeling depicted multiple stages of relationships and uncertainties. • GEDI provided lidar measurements to upscale field plot measurements. • A measurement error model depicted errors between GEDI and ALS. • Geostatistical modeling allowed various prediction resolutions. [ABSTRACT FROM AUTHOR]

Faced with the multiple challenges of mitigating climate change, controlling air pollution, preserving ecological environments, and promoting economic growth, developing countries need to seek a synergistic development path. The Forest Carbon Sink Project (FCSP) has the potential to support developing countries in achieving these objectives. Currently, empirical research on the synergistic benefits of FCSPs is limited, leading to ongoing debate about their economic and environmental benefits. Therefore, this study uses panel data from 1600 counties in China to provide evidence for the development of FCSPs. Firstly, the study employs a difference-in-differences model to quantitatively assess the causal relationship between FCSP and both economic development and air quality. Furthermore, this study evaluates the potential of FCSP to reduce carbon emissions by setting a scenario of bioenergy planting (BCP). The empirical results show that, compared to non-project counties, FCSP project counties experience a 6.70% increase in real GDP and a 0.90% decrease in PM 2.5 concentration. FCSP generates economic benefits by increasing residents' income, boosting fixed asset investment, and upgrading industrial structure. And it improves air quality by expanding forest area and enhancing vegetation coverage. Scenario simulations show that in the BCP scenario, one project county can yield 23.39 Kt of biomass yearly. Scaling the FCSP to 500 counties would result in an annual reduction of 24.46 Mt. of CO 2 emissions. This amount constitutes roughly 28% of China's CO 2 emission increase in [ 8 ], which was 88 Mt. • Statistical and remote sensing data are combined to build a county-level economic and air quality database in China. • A multi-period DID model is applied to identify the synergistic benefits of Forest Carbon Sink Project (FCSP). • The scenario simulation method is applied to study the possible development paths of FCSP. • Existing FCSPs can synergistically promote economic growth and improve air quality. • Developing bioenergy plantations could allow FCSP to steadily reduce carbon emission in energy sector. [ABSTRACT FROM AUTHOR]

• Intercropping with reduced N input increases deep C storage while reducing GHG emissions. • Double-legume rotation increases C content in management-sensitive SOC pools. • Alley cropping in Mediterranean regions achieved the goals of 4 ‰ initiative. • Deep burial of straw sequestered SOC primarily by increasing POC and MAOC. • No-till maintains soil quality more than it mitigates climate change. [ABSTRACT FROM AUTHOR]

We present a systematic review of the scientific production on climate adaptation in Brazil, using quantitative and qualitative methodologies. The analysis of adaptation categories indicated a good balance between social (38 %) and institutional (33 %) adaptation actions, with a lesser share of physical/infrastructure adaptation (25 %). Assessed impacts tend to focus on higher temperature or heat events (21 %), mainly with regard to human health, along with droughts or water resources issues (20 %), particularly agricultural production. The studied biomes or environments showed a predominance of the most populous areas, such as urban (27 %) and coastal (17 %), indicating the need to target climate adaptation actions at the various Brazilian natural biomes, which, together, are addressed in only 30 % of the papers analysed (all six biomes combined). Indexes development and documentary analysis were predominant methodologies. The dialogue between science and society must be improved, especially with public management, in the production, execution and dissemination of climate adaptation actions. Nature-based solutions were listed as emerging solutions for addresing climate change impacts, acting both for mitigation and adaptation. Popular participation was pointed out by several authors as fundamental in the joint construction of these actions, as well as the provision of information on access to climate finance, which may be of interest to both public and the private sectors. • A review of the scientific production in climate adaptation in Brazil was performed. • Indexes development and documentary analysis were the predominant methodologies. • Only 30 % of papers evaluated the various natural biomes in Brazil, such as the Amazon. • Engineering fields need better integration with the human aspects of climate change. • Popular participation and the dialogue between science and society must be enhanced. [ABSTRACT FROM AUTHOR]

Recent articles have demonstrated the knowledge and accuracy of oil corporations' predictions made since the 1950s on the effects of their products on the global environment. But can the early relationship between oil corporations and national governments and lack of climate actions by both actors count as ecocide? If so, should remedial strategies appeal to freer markets for oil or greater state regulation? Cast within the wide context of investigating the collusion at play between powerful political-economic actors and decision-makers as monopolists and debates about 'the modern corporation and private property' (Berle and Means, 1932/2017), 'the new industrial state' (Galbraith, 1967), and 'the economic theory of regulation' (Stigler, 1971), the paper reviews the contentious relationship between states, corporations, and markets. Specifically, the article probes strategies of oil corporations and national governments intended to delay the inclusion of environmental concerns in policies and avoid accountability. Our method of content analysis of articles, reports, and international declarations of different actors and periods relies on a qualitative methodology and ontology of critical realism. We find that not only did oil corporations hide the truth, but also that national governments, that knew (or should have known) about the threat posed by oil industrial activities and which have wider responsibilities than corporations, did not act and are (at least) as responsible and as 'ecocidal' in what could be called an oil TNC-state alliance. Accordingly, we open the avenues for redressing an evolutionary shift from markets and states to commons, and embedding power within communities (Polanyi, 1945) along with a more universal right to bring a case of ecocide against both transnational oil corporations and states that collude with them. • National governments were, as shareholders of oil companies, potentially aware of global warming before the 1970s. • There is a lack of accountability of transnational companies and national governments for the current environmental crisis. • Local communities affected by oil activities need more support to bring their cases to oil companies' home country. • The absence of constraining and applicable rules stems from a lack of political independence and will. [ABSTRACT FROM AUTHOR]

• This study uses machine learning to simulate underground climate change. • It examines ground temperatures and strains in a city district over time. • Results show that large-scale predictions are feasible with limited data. • This approach is up to 200 times more efficient than existing ones. Subsurface heat islands induce an underground climate change in urban areas, which can threaten public comfort and health, subsurface ecosystems, transportation infrastructure, and civil infrastructure. Meanwhile subsurface heat islands harbor a marked energy recovery potential. Despite increasing investigations, the understanding of subsurface heat islands remains limited and suffers from the lack of expedient and accurate simulation approaches. Here we explore the use of machine learning to accurately and expediently simulate subsurface heat islands in terms of ground temperature and deformation anomalies. Using the Chicago Loop district as a case study, we identify a series of physical features to establish a relationship between central drivers and effects of subsurface heat islands. We incorporate these features into a random forest model to simulate underground climate change with variable training datasets. The results indicate that ground temperature and deformation anomalies across an entire city district can be predicted based on data extracted solely from a handful of buildings. The proposed approach achieves comparable accuracy to current simulation methods but boasts a calculation speed that can be over a hundred times faster, promising to advance fundamental science while effectively informing engineering and decision-making in the mitigation of underground climate change. [ABSTRACT FROM AUTHOR]

• PV-GR annually cuts about 5.131×106 t CO 2 -eq. • PV-GR's power generation can meet about 22.13 % of Xiamen's annual electricity demand. • The ecological balance of PV-GR in Xiamen equals 3.872×105 Gha. • Deploying PV-GR in Xiamen can mitigate climate change. • PV-GR's carbon reduction far exceeds its emissions. The Photovoltaic-Green Roof (PV-GR) system, which integrates rooftop photovoltaics and green roofing, has significant potential for sustainable urban development and climate change mitigation. However, the specific effects of PV-GR are not yet clear. This paper employs methodologies including Geographic Information Systems (GIS), Denitrification-Decomposition(DNDC) Model, and solar simulation. Combined with ecological balance calculations, these methods assess PV-GR's carbon reduction benefits and its potential to mitigate climate change. Using Xiamen City as a case study, research shows that Xiamen has about 54 km² of rooftops suitable for PV-GR. Annually, PV-GR can produce about 5.931×103 tons of biomass and generate 7,427 GWh of electricity, meeting about 22.13 % of Xiamen's annual electricity demand. The annual carbon reduction from Xiamen's PV-GR is estimated at about 5.131×106 t CO 2 -eq , offsetting around 29.28 % of the city's annual carbon emissions. Over a 30-year lifecycle, PV-GR's carbon emissions and reduction benefits amount to 2.274×107 t CO 2 -eq and 1.539×108 t CO 2 -eq , respectively. The ecological footprint of deploying PV-GR in Xiamen is 6.709×104 Gha, while the biocapacity reaches 4.542×105 Gha. The global ecological balance stands at 3.872×105 Gha, suggesting that PV-GR can significantly contribute to mitigating climate change. [ABSTRACT FROM AUTHOR]

• Identified 95 shrinking cities in China from 2000 to 2010. • Assessed temperature at 2419 stations from 1961 to 2014. • Revealed cooling effects in shrinking cities. • This cooling exhibits significant seasonality. • Urban shrinkage contributes to mitigating regional warming. In recent years, urban areas are increasingly experiencing intense warming. Although urbanization is an important driver of warming in urban environments, it remains unclear whether depopulation trends in shrinking cities mitigate this warming effect. Here, we explored the relationship between shrinking cities and observed warming in China. Of the 356 Chinese cities, 95 were identified as shrinking between 2000 and 2010. We categorized 2419 observation stations into three groups—rural, shrinking, and non-shrinking—and generated a surface air temperature (SAT) anomaly series for each group from 1961 to 2014. Temperature differences between the shrinking and non-shrinking urban stations were investigated. Using segmented generalized least squares regression, the spatiotemporal temperature patterns across the mean (T mean), maximum (T max), and minimum temperatures (T min), diurnal temperature range (DTR) indicators, and across seasons—spring, summer, autumn, and winter—were explored. Results revealed a cooling effect in shrinking cities, with decadal decreases of 0.042 °C (–0.078 to –0.005 °C), 0.083 °C (–0.126 to –0.039 °C), and 0.029 °C (–0.062 to –0.005 °C) in regional T mean , T max , and T min anomalies, respectively. Moreover, pronounced seasonality was identified in this phenomenon—the cooling effect was most notable for T mean in spring and T max in autumn, less significant in summer, and negligible in winter. These results suggested that the population decline in shrinking cities could alleviate regional warming, having implications that could influence urban planning and climate mitigation policies. [ABSTRACT FROM AUTHOR]

Human activities like dam construction in rivers and urban development in coastal areas, combined with climate change, are degrading coastal systems. As a result, many European countries have implemented laws and strategies to protect their shorelines. This research focuses on Guardamar del Segura in Spain, where human actions in the Segura River basin and changes in wave patterns have significantly damaged the beach-dune system, with erosion rates reaching −0.71 m/year. If these rates and extreme climate events continue to rise, the shoreline will keep retreating, leading to the destruction of beachfront houses and parts of the dune surface by 2050. This will cause changes in land ownership and irreversible ecological damage to the natural ecosystem. The Spanish Public Administration's inaction on coastal protection is due to a lack of coordination between government levels, insufficient technical tools to combat erosion, and inadequate legal mechanisms to fund protective measures. In contrast, countries like Germany, the Netherlands, and the United Kingdom have effective models in place. Potential solutions for Guardamar del Segura include beach and dune restoration or adding sand through revetments. Another option is a managed retreat of the most vulnerable buildings to avoid continuous repair and maintenance costs. Coastal erosion is a growing issue, and preserving our coastal ecosystems requires proactive measures, so doing nothing is no solution. [Display omitted] • Disruption of the sediment supply and intensification of storms drive coastal erosion. • Spain does not have legislation that limits the retreat of the beach berm. • Failure to act in time will cause irreversible damage in urban and natural environments. • The solutions to be taken must be sustainable and preferably based on nature (NbS). [ABSTRACT FROM AUTHOR]

The disciplines of Coastal Management and Marine Spatial Planning (MSP) are predominantly focussed on creating a regulatory and legislative framework within which national and regional planning policies, climate mitigation measures and environmental monitoring requirements can be effectively implemented. These evidence-based processes necessitate the discoverability, accessibility and integration of appropriate 'trusted' coastal and marine data together with contiguous terrestrial datasets. This presents significant challenges at national and local levels. While authoritative open data is often available, the data for any management requirement is often dispersed across a wide range of national online portals, statistical and research hubs, 'scientific' platforms and occasionally, private companies. This is exemplified in Ireland, where MSP is in its infancy, and consequently, the breadth of MSP foundational thematic marine data requirements required to comply with this Directive has yet to be fully realised by end-users/stakeholders and data providers. This study examines the nexus between mandatory data requirements of the European Community's Infrastructure for Spatial Information in the European Community (INSPIRE) Directive 1 1 INSPIRE Directive (2007/2/EC) is a legal EU initiative to establish an INfrastructure for SPatial InfoRmation in Europe and to make geographical information more accessible and interoperable for the management of the environment and other wide range of purposes towards supporting sustainable development (EC, 2021) (2007/2/EC), (EC, 2007) and the evidence-base needs of its Maritime Spatial Planning (MSP) Directive (2014/89/EU). An extensive inventory of coastal and MSP thematic data features is identified and categorised (into sectoral/thematic clusters) and appropriate and authoritative online sources (where available) are scoped out. Through an in-depth interrogation of national and EU sectoral platforms or portals, (much of whose data was originally captured for a diverse range of applications and management processes), and in view of INSPIRE's well-established (legally-binding) data specifications, standards and guidance, a methodology is presented to accelerate coastal and marine data discovery, and to collate or 'group' these authoritative data sources under broad but succinct MSP thematic headings. The resulting coastal and marine data catalogue is the first step in the creation of an easy data reference and retrieval tool for Irish coastal and marine practitioners, and presents a model for other nations. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emission mitigation and climate change adaptation in urban communities are urgent. There is enormous potential to improve the GHG inventory at the community level. This research aims to develop a community-scale GHG emission inventory and improve its accuracy and consistency through a bottom-up approach. This study covers direct and indirect emissions categorized into three scopes and selects the Honjo Waseda community in Japan as a case study community. Energy consumption from different sectors (the residential and commercial, transport, and waste management sectors) is evaluated and calculated through Residential Energy Estimation based on the Daily Activities (REEDA) database, National Census, and first-hand field data. The outcome revealed that the residential and commercial sector emissions rank highest in the total GHG emissions of the community, with a value of 39 %. Translated into the scope concept, the emissions under scopes 2 and 3 account for 39 % and 61 %, respectively. Furthermore, a sensitivity analysis of the implementation of green technologies to reduce GHG emissions is also conducted. Mechanical biological treatment (MBT) implementation could yield the largest emission reduction (18 %–22 %), followed by implementing electric vehicles, ultralightweight vehicles, photovoltaic systems, and ground heat utilization. [Display omitted] • GHG emission mitigation and climate change adaptation of urban communities are urgent. • Evaluate GHG emission at community level from scope 1–3 through a bottom-up approach. • Develop models for evaluating emissions from residential and commercial transport, and waste management sectors. • Propose scenarios and evaluate sensitivity analysis on green technologies implementation. [ABSTRACT FROM AUTHOR]

Urban areas have key roles in climate mitigation, including increasing renewable energy penetration in smart energy systems. The potential of urban areas in limiting global warming, however, is not quantified. This research work develops a new framework to analyse urban emissions and land use efficiency scenarios with coupling to the transient climate response to cumulative carbon dioxide emissions. Two new parameters that quantify contributions to and avoidance of increments of global warming from urban areas are formulated and applied to twelve scenario combinations. The results for 465 urban areas indicate that a green-growth scenario with lower ambition in reducing urban emissions can lead up to a 0.13 °C additional increment of global warming in 2050 based on the best estimate of the transient climate response to cumulative carbon dioxide emissions. Those of the most ambitious urban emissions scenario with green-growth and renewable energy are limited to 0.06 °C. When combined with the most ambitious land use efficiency scenario for 135 urban areas, it is possible to avoid more than double or 2.09 times additional increments of global warming in comparison to other integrated urban scenarios. The mean and 5–95th percentile range of the results are compared based on 10,000 Monte Carlo simulations. Informing on the urgency to ensure ambitious mitigation action in urban areas can support a climate future that remains within critical thresholds and tipping elements of the planet. [Display omitted] • A new framework couples urban scenarios and increments of additional global warming. • Cumulative urban emissions of 465 urban areas can be 291.04 GtCO 2 eq in 30 years. • A green-growth oriented renewable energy scenario can avoid up to 0.09 °C in 2050. • Cumulative sequestration penalties of 135 urban areas are up to 2.01 GtCO 2 in 30 years. • Joint ambitious mitigation and land use efficiency in this case averts 0.039 ± 0.016 °C. [ABSTRACT FROM AUTHOR]

• A novel enhanced PV index was developed to enhance PV pixel representation. • China's total PV power station area in 2020 was estimated as 2635.64 km2. • China's PV power generation in 2020 was calculated to be 238.65 TWh. • This power amount is equivalent to reducing carbon emissions by 149.63 million tons. • Evaluation results favor Sustainable Development Goals and carbon neutrality. Global photovoltaic (PV) installed capacity and power generation are increasingly growing due to climate change mitigation efforts, suggesting the necessity of accurately determining the spatial distribution of PV power stations and scientifically evaluating their carbon reduction benefits. Considering the costs associated with data acquisition and processing, the most cost-effective choice is still high-accuracy mapping of large-scale PV power stations based on the Google Earth Engine (GEE) platform by combining effective features with machine learning algorithms. Moreover, how to analyze the carbon source effects between PV energy and traditional fossil fuels at the national scale and comprehensively evaluate the carbon reduction benefits of existing PV energy facilities is still worth exploring. To address these issues, this study proposed a novel enhanced PV index (EPVI) for mapping PV power stations across China, and the mapping results were further applied for the evaluation of carbon reduction benefits. Results show that EPVI can not only highlight the salience of PV pixels but can also effectively suppress the confusion of non-PV pixels to improve mapping accuracy. In 2020, the total area of China's PV power stations was estimated as 2635.64 km2, achieving an overall accuracy of 0.9756 and a Kappa coefficient of 0.9394. Based on the mapping results, the PV power generation was calculated to be 238.65 TWh, which is equivalent to reducing coal consumption by 72.77 million tons and carbon emissions by 149.63 million tons. The PV carbon reduction contribution rate was shown to have an obvious regional difference, with a large rate in the western area and a small rate in the eastern area. The results can contribute to clean energy utilization and management to achieve low-carbon goals, facilitating the global consensus on Sustainable Development Goals (SDGs) and carbon neutrality. [ABSTRACT FROM AUTHOR]

Decarbonizing the EU's district heating is crucial for meeting climate goals and securing a sustainable energy future. Currently, district heating suffers from inefficiency, high operating temperatures, significant distribution losses, and reliance on fossil fuels. Literature highlights strategies for reducing emissions, including integrating low-carbon heat sources, lowering supply temperatures, and employing efficient technologies like heat pumps and combined heat and power (CHP). However, the individual effectiveness of these strategies in reducing emissions within existing networks remains unassessed. This study addresses the gap by applying a comprehensive model that evaluates energy and emissions across the district heating supply chain, coupled with a derivative-based sensitivity analysis. We apply this methodology to the national-level district heating systems of Sweden, France, Germany, and Poland. Results indicate that the impact of decarbonization strategies on district heating emissions varies significantly by the system's characteristics, i.e., the energy mix in power and district heating supply and the presence of CHP plants. Primarily, incorporating more low-carbon heat sources emerges as the most effective method for emission reduction across nearly all examined countries. A 1 % increase in the share of low-carbon heat sources can potentially cut emissions by 0.8–1.3 kg CO 2 e per GJ of heat. In countries like Sweden and France, where the power generation already relies heavily on low-carbon resources, technologies which convert electricity to heat—such as heat pumps and electric boilers—rank as the second most effective approach. In contrast, for countries like Germany and Poland, with their moderate to low use of low-carbon power, reducing distribution losses and decreasing heat demand prove more effective, with emission reductions ranging between 0.8-1.3 and 0.7–1.2 kg CO 2 e per GJ in these countries, respectively. Additionally, cutting down power generation in fossil fuel-based CHP plants significantly reduces emissions in these regions. While green hydrogen and carbon capture and storage (CCS) also contribute to emission reductions, a 1 % increase in green hydrogen's share might decrease emissions by just 0.3–0.5 kg CO 2 e per GJ of heat, highlighting their lower effectiveness compared to the aforementioned strategies. These insights hold value for both district heating operators and for technology suppliers seeking decarbonization pathways. This is also true for policymakers focused on climate change mitigation, guiding the distribution of subsidies and R&D investments. • Creation of a framework to evaluate the effectiveness of strategies to reduce emissions in district heating. • Application of the method to the national-level systems of Sweden, France, Germany, and Poland. • Effectiveness of strategies varies significantly by the system's characteristics. • Identification of most effective strategies by country and policy recommendations. [ABSTRACT FROM AUTHOR]

[Display omitted] • Formation of KFeO 2 is confirmed via XRD and thermodynamic calculation. • The reactivity of the ilmenite is enhanced with WSA addition. • The reactivity of ilmenite peaks at 10 % WAS addition. • Ilmenite with 10 %WSA addition exhibits highly developed pore structure. • Ilmenite with 10 %WSA addition exhibits the highest oxygen release capability. Chemical looping combustion (CLC) offers a promising approach for biomass utilization. The utilization of biomass as the primary fuel in CLC (bio-CLC) is a way to generate negative CO 2 emissions and thus interesting for climate change mitigation. However, the presence of ash in biomass raises concerns about the performance variation of the oxygen carrier during CLC. This study investigated the impact of adding wheat straw ash (WSA) to the ilmenite oxygen carrier throughout the CLC process. The effects of WSA addition ratio (0–15 %) and cycle number on the performance of oxygen carrier were evaluated. The results showed a progressive enhancement followed by a subsequent reduction in the performance of ilmenite with the increase of WSA addition ratio, and the peak reactivity of ilmenite was attained with 10 % WSA addition. Addition of 15 % WSA resulted in severe particle sintering, causing a slight diminishment in ilmenite reactivity. Furthermore, the mechanisms of the performance variation of ilmenite with WSA addition were explored. The superior redox reactivity and oxygen release capability of the ilmenite with 10 % WSA addition were evidenced by X-ray photoelectron spectroscopy and hydrogen temperature-programmed reduction analysis, respectively. Notably, X-ray diffraction and thermodynamic calculation confirmed the formation of KFeO 2 , which significantly enhanced the reactivity of ilmenite. The specific surface area of the ilmenite was greatly enlarged with 10 % WSA addition, and a porous structure was evidenced by scanning electron microscope. The findings suggest the interaction between the WAS and ilmenite enhances the reactivity of the ilmenite with an optimal WAS addition ratio of 10 %, providing a guidance for the long-term operation of CLC. [ABSTRACT FROM AUTHOR]

Sustainable Development Goal 7 highlights the importance of affordable, reliable, and sustainable energy. Transition to clean energy is vital for achieving climate action goals. Hydrogen can serve as a clean energy carrier, with the potential to decarbonize industry, transportation, and other sectors. As of 2021, hydrogen was mainly produced using fossil fuels (grey hydrogen), and only about 1 % of global hydrogen output was produced with renewable energy (green hydrogen). The transition to green hydrogen requires new hydrogen production, storage, and distribution facilities which is challenging to implement due to a lack of associated infrastructure and high upfront costs. This study highlighted barriers and opportunities for hydrogen technologies by reviewing evidence and establishing links with the Sustainable Development Goals (SDGs). The review identified fifty-two opportunities and forty-six challenges linked to SDGs1, 2, 4.6, 7, 9, 11, 12 and 13. Out of all the hydrogen production technologies green hydrogen was the most common choice noted in the. Technical opportunities for green hydrogen production were found to have the potential to positively impact society and environment, but high costs were noted to be a barrier. To reduce economic barriers, recommendations include analysing the impact of subsidies and working further on the development of policies and regulations to support the scaling-up of green hydrogen systems. [Display omitted] • Hydrogen supports SDG 7 ambitions, but high costs and a lack of existing infrastructure noted as barriers. • Review identifies fifty-two opportunities and forty-six challenges connecting hydrogen with SDGs. • Hydrogen presents sustainability synergies (environmental and social) and trade-offs (economic). • Green hydrogen is the most common solution identified in literature with the potential to support SDGs. • Need for subsidies to support scale up of green hydrogen. [ABSTRACT FROM AUTHOR]

[Display omitted] • Active mobility (AM) contributes to the mitigation of climate change. • The study offers a methodology to measure the street use environmental impacts. • Refurbishment return environmental rates do not exceed seven months. • Sustainable transportation requires strategies: AM, carpooling, and mass transport. • Measuring the impacts of street use could generate sustainable interventions. Active mobility (AM) is a fundamental part of a sustainable mobility system that generates environmental and social advantages; however, its use and operation are understudied using quantitative tools such as life cycle assessment (LCA), especially in the Latin American context. This study aimed to analyze the use stage of a street located in Northern Mexico. Two real scenarios were compared, one conventional (CO-SC-2020) and another sustainable (SU-SC-2022), which incorporated the concept of "complete streets" through a bicycle lane and the improvement of pedestrian spaces. Available data from the "Vía Libre" project and PIMUS, as well as SIMAPRO and Ecoinvent, were used for the LCA. The results indicated that the environmental impacts derived from transportation could be reduced through strategies such as active mobility (6.55%) and carpooling (77%), favoring the conversion of cities that consider the automobile as the guiding axis to more sustainable, inclusive, and safe cities. [ABSTRACT FROM AUTHOR]

Agricultural production and climate change strongly influence each other and there are significant efforts to minimize negative impacts in both directions. In particular, breeding progress has succeeded in reducing the carbon footprint (CFP) of cereals over time. However, there is widespread certainty that climate change-related weather extremes have led to stagnation of cereal yields in many global production regions. We assume that climate change-related yield stagnation is also evident in variety trials in Germany, which has to date only been shown for on-farm yields. Furthermore, we expect that the stagnation in yields also leads to a stagnation in the downward trend of CFP, and that heat and drought stress in particular increase the CFP of cereals. In addition, we hypothesize that the site-specific soil quality largely determines stress induced increases in CFP. We conduct a partial life cycle assessment (LCA) with German variety trial data from 1993 to 2021 and determine the greenhouse gas emissions per unit of land (GHGL), as well as the CFP of winter wheat, winter rye, and winter barley. Further, we evaluate the time trends of yield, GHGL, and CFP using linear and quadratic plateau models. In addition, we calculate spatio-dynamic weather indices (WIs) for moderate, severe and extreme heat and drought stress. Using mixed models, we estimate the explanatory power and effect size of heat and drought WIs on the CFP. Finally, we present the spatial differences of heat and drought on the CFP at different soil qualities. We show yield plateaus in all crops and stagnating GHGL trends, resulting in a stagnation of the downward trend of CFP, especially for rye and barley. We highlight that heat and drought increase the CFP of all crops. However, the impact of heat and drought on the CFP varies greatly with soil quality across all crops. We conclude that climate change-induced weather extremes are major challenges not only for cereal production and food security but also for climate change mitigation in the agricultural sector, highlighting the importance of high-yield locations, alongside variety selection and resource-efficient management, for climate change mitigation. This study is the first that proves significant yield stagnation in German variety trials. Moreover, this study is the first to analyze the impact of heat and drought stress on cereal CFP, with novel results that proof that climate adaptation will become a crucial aspect of climate change mitigation in field crops. • First study that finds a yield plateau in wheat, rye, and barley variety trial data. • Heat and drought stress increases the Carbon Footprint (CFP) of cereals. • Larger variation in CFP between sites than between years in all crops. • Plateau interrupts downward trend of CFP due to negative E development. • Climate change induced abiotic stress hampers efforts in climate change mitigation. [ABSTRACT FROM AUTHOR]

The research literature on the driving mechanisms for the clean energy transition in the Next 11 (N11) economies to accomplish their carbon-free targets is scarce. We address this research gap with an empirical analysis of the effects of renewable fuels, resource allocation, corporate governance, energy trade, economic growth, carbon taxes, and digitalization on the shift to clean energy between 1990 and 2022. Using the method of Moments Quantile Regression, the results show that all regressors enhance the shift to clean energy. Based on the study outcomes, policymakers should intensify their attempts to coordinate policies to support sustainable development goal ambitions. • N11 governments strive to achieve climate change goals. • Renewable fuels can enhance the transition to clean energy. • The ecological consequence of corporate governance on the transition to clean energy is positive. • Energy trade may assist in the shift to clean energy. [ABSTRACT FROM AUTHOR]

The power industry remains a central focus of modern climate mitigation policies because of its significant contribution to global GHG emissions and increased global electricity demand. This paper examines Kazakhstan's coal-based power-generation companies' responses to a national emissions trading scheme (ETS) regulation introduced in 2013 by applying corporate climate strategy and sociotechnical systems frameworks. The in-depth case study is based on 20 interviews with managers of the six largest Kazakhstan coal-based generators and ten interviews with independent industry experts. The empirical data indicate that Kazakhstan's ETS has impacted the country's generators. The companies have responded in the form of non-compliance (i.e., application for additional free allowances), compliance (i.e., purchase of allowances from the ETS), and compliance-plus activities (i.e., exploring investment into renewable energy and fuel switching to natural gas). At the same time, Kazakhstan's generators continue the business-as-usual approach by investing in modernizing their coal-generating assets. Therefore, Kazakhstan may consider complementing its ETS regulation with additional policy reforms to support its ambitious objective to achieve carbon neutrality by 2060. • Coal-based power generators' climate strategies can be explained by contextual factors and company-specific factors. • Continued investments into coal generation indicate the limited impact of Kazakhstan's ETS on promoting the decarbonization. • In Kazakhstan, carbon regulation is a routine compliance procedure with minimal senior management involvement. • Policymakers of transitional and developing economies should consider applying complementary policies to their ETS. [ABSTRACT FROM AUTHOR]

Bauxite residue or Red Mud (RM) is a by-product from alumina refineries. It has a high pH of 11–13 and accumulates globally at 200 million tons yearly, totalling about 4.6 billion tons. Being an alkaline anthropogenic geomaterial, its adsorption properties and reactivity with acidic gases make it a potential sink for CO 2 and SO X emissions from the aluminium industry. It offers both research challenges and opportunities for its utilisation at an industrial scale. In particular, carbon capture and mineralisation (CCM) within RM has been demonstrated in situ and waste disposal areas through direct air trapping of atmospheric CO 2. The RM-CO 2 system is also operated in ex-situ conditions in various physical states, such as powder, wet cakes, and slurry, with yields of carbonates as CaCO 3 , Na 2 CO 3 , and FeCO 3. Our contribution as a review illuminates significant advancements made and challenges for enhancing the mineral carbonation potential of RM, thereby delineating areas necessitating further exploration. Although, researchers have primarily focused on accelerating the CCM process in RM through slurry carbonation techniques. Recent advancements in filter press technologies have favoured soda recycling and wet cake disposal of RM, creating artificial mountains of RM stacks. With changing disposal trends for RM, it is vital to understand the mechanisms that govern long-term atmospheric CO 2 trapping in RM disposal areas. Recent investigations of techniques, hydrothermal treatment and dual-stage calcification-carbonation methods have expanded the domain of CCM in RM. Given the global need to reduce CO 2 emissions, CCM using RM does offer promising insights on account of its unique physicochemical and mineralogical properties. We, although presume that RM alone will not fully offset the CO 2 emissions of the aluminium industry. Enhanced weathering and mineral carbonation could reduce over 50% of refinery emissions. Uncertainties persist regarding methods of CO 2 sequestration potential and techno-economic feasibility when tested at a field scale. Moreover, contrasting results are revealed, primarily regarding changing disposal trends, variabilities in mineralogy, and limited knowledge of micro-mechanisms of the CCM process in RM. This work elucidates existing knowledge on synthesising CO 2 mineralisation, pathways, and mechanisms under various states associated with leveraging RM as a significant carbon sink in current and future climate change mitigation efforts. [Display omitted] • Illustrates RM mineral carbonation process and mechanistic models for CCM methods (slurry, semi-dry, atmospheric). • CCM potential is studied along with mechanisms using hydrothermal treatment, siderite formation and calcification-carbonation method. • Guidelines for RM sample extraction methods based on its physico-geochemical changes in BRDA with atmospheric CO 2. • Current and future research directions are discussed. [ABSTRACT FROM AUTHOR]

This editorial summarizes the papers selected for publication in the Special Issue on Climate Change Mitigation and Adaptation in Power and Energy Systems (CMAP). After a rigorous review of 86 submitted manuscripts, 23 papers were accepted for publication. These accepted papers cover various aspects of climate change mitigation and adaptation and are classified as follows: boosting renewable energy efficiency (two papers), climate resilience strategies (four papers), decarbonization strategies (four papers), renewable energy integration (five papers), policies, incentives, and science communications (four papers), and the role of energy markets (four papers). The Guest Editorial Board is optimistic that this Special Issue will serve as a rich resource, offering invaluable insights to propel future research and advancements in climate change mitigation and adaptation. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is crucial for karst ecosystems, affecting cropland health, climate change mitigation, and rocky desertification control. However, there are limited research on cropland SOM prediction in karst areas with complex topography and diverse microclimates. Here, we compared the performance of four machine learning algorithms—random forest (RF), support vector regression (SVR), multilayer perceptron regression (MLP), and gradient boosting regression trees (GBRT)—for predicting cropland SOM in a typical karst landform area in 2019. Our results indicated that the GBRT model achieved the highest prediction accuracy with an R² of 0.69, MAE of 2.19 g/kg, RMSE of 3.37 g/kg, and LCCC of 0.82. Using the GBRT model and spatial data on climate, topography, and remote sensing, we predicted SOM for each 30 m × 30 m grid cell. The analysis revealed higher SOM content in the northeastern and southwestern regions and lower content in the central area, ranging from 13.95 to 47.81 g/kg, with an average of 27.16 g/kg. Lime soil had the highest SOM content, while purple soil had the lowest. Paddy fields showed significantly higher SOM than dry land. Over the past 40 years, SOM content has slightly increased, while its spatial distribution has remained stable. [Display omitted] • GBRT algorithm could effectively predict SOM content in the typical karst cropland. • Climate, topography and remote sensing vegetation indices were key variables for SOM prediction in karst cropland. • In karst cropland, lime soil exhibited the highest SOM content, while purple soil had the lowest. • Over the past 40 years, the mean SOM content has shown a slight upward trend since the national soil survey in 1980s. [ABSTRACT FROM AUTHOR]

The port governance literature has charted the trend towards devolution of port services to the private sector, also showing how the increasing influence of external private actors such as shipping lines and global terminal operators affects decisions on expansion and service provision, producing a more multifaceted and polycentric kind of port governance. In this paper we extend these notions to cover both mitigation of and adaptation to climate change. A growing body of literature on green ports discusses the various actions that can be taken to limit emissions in the port area, while another body of literature is growing on climate change adaptation measures, including the uncertain risks and rewards. Both mitigation and adaptation actions are partly linked to the commercial decisions of port actors but also partly driven by external actors (e.g. society, government, regulators). The analysis produces an updated conceptualisation of port governance under climate change, based on four stakeholder groups (public policy, commercial actors, indirect actors and international shipping governance) and produces three key conclusions. First, concession contracts and commercial relationships will need to change, with a more integrated vision and approach to sharing future (sometimes undefined or uncosted) costs and benefits between the port authority and commercial partners. Second, diversification of the port business model will see a larger focus on energy production and provision, requiring the more explicit inclusion of external stakeholders, particularly energy companies, in port governance. Third, port governance will see a return to prominence of the public dimension, both in terms of national decarbonisation plans and particularly regarding adaptation to an uncertain and turbulent future. As ports are both commercial activities and national infrastructure, these different identities will need to be united in a joint vision. [ABSTRACT FROM AUTHOR]

Straw application is an effective and common measure to improve soil quality but generally increases greenhouse gas (GHG) emissions. The combined application of biochar and straw has been proposed to mitigate these emissions. However, the effects of the combined application of biochar and maize straw, particularly at different proportions, on GHG emissions remain inadequately understood. In this study, an incubation experiment was conducted with five treatments: soil only (CK), 1 % maize straw application (TS), 0.7 % maize straw +0.3 % biochar application (S7B3), 0.5 % maize straw +0.5 % biochar application (S5B5) and 0.3 % maize straw +0.7 % biochar application (S3B7). The study also considered the effect of 1 % biochar application (TB) from our previous study with the same soil type and incubation condition. Carbon isotope technology was utilized to trace CO 2 sources and assess the priming effects on soil organic carbon (SOC) mineralization. The results showed that TB reduced CO 2 emission, while TS increased CO 2 emission due to maize straw decomposition and its positive priming effect on native SOC mineralization. S7B3, S5B5 and S3B7 also increased CO 2 emissions, but with significantly lower emissions than TS, in the order of TS > S7B3 > S5B5 ≥ S3B7. The positive priming effects of S7B3, S5B5 and S3B7 on native SOC mineralization weakened over time and eventually turned negative. TB, TS and combined applications reduced N 2 O emission due to decreased substrates (NH 4 + and NO 3 −) for nitrification and denitrification, induced by promoting microbial fixation of inorganic nitrogen. The reduction effects on N 2 O emission of combined applications were superior to those of TS and TB, with S5B5 demonstrating the best efficacy. TS increased CH 4 emission, while S7B3, S5B5 and S3B7 reduced CH 4 emission. The reduction effects of CH 4 emission with combined applications were superior to that of TB, and S5B5 exhibited the lowest CH 4 emission. Unlike soils with higher nitrogen content, where N 2 O emission dominated the global warming potential (GWP), CO 2 emission dominated the GWP in this study, resulting in increased GWP in TS, S7B3, S5B5 and S3B7, but with significantly lower values for S7B3, S5B5 and S3B7 compared to TS. In conclusion, our study suggests that the combined application of biochar and maize straw, especially S5B5, could effectively mitigate GHG emissions promoted by maize straw application, especially in soils with higher nitrogen content. [Display omitted] • Biochar and maize straw co-application reduced CO 2 emission promoted by maize straw application. • The priming effect of co-application on SOC shifted from positive to negative over time. • Co-application reduced stimulation of CH 4 emission caused by maize straw application. • Co-application exhibited superior efficacy in reducing N 2 O emissions. • The optimal co-application ratio for mitigating greenhouse gas emissions was 1:1. [ABSTRACT FROM AUTHOR]

Livestock are an important component of livelihoods in smallholder dairy systems in Africa, but are characterized by low animal productivity and large environmental impacts per unit of animal product (e.g. greenhouse gas emissions (GHG) intensities). Governments in African countries have set ambitious targets for dairy systems, but development of climate-smart strategies has been hindered by a scarcity of baseline data and local intervention trials. We use a rich dataset from smallholder mixed dairy systems in Kenya to determine whether national climate and development goals for 2030 can be met using locally appropriate interventions. Interventions considered included improved herd management and feed interventions. We conducted a yield gap analysis to determine the scope of the existing milk yield gaps, then evaluated the extent to which yield gaps could be closed using interventions in a second step. We outscaled our results to the national level to determine the potential impact of adopting our interventions on national dairy production and GHG emission goals using the FAO Global Livestock Environmental Assessment Model – interactive (GLEAM-i) tool. Our analysis showed that substantial yield gaps exist in Kenyan dairy systems (39 to 49% of attainable yields). These gaps could be closed by intervention packages but not by individual interventions alone. Our outscaled scenarios showed interventions can reduce milk GHG emission intensities (−6.5 to −27.4%), while absolute emissions would increase in most scenarios (−3.9 to +25.9%). To meet national milk production goals, we estimated that a large increase in animal numbers is needed by 2030 compared to 2010 (from ∼2.7 M to 4.5–7.1 M heads of cattle). However, most scenarios fell short of the emissions target (−4% to +48%) by 2030. It may be possible to narrowly meet Kenyan national milk production and GHG emission goals by 2030. National goals for milk production and reducing GHG emissions were only marginally compatible in Kenya. Other sectors of the economy will need to reduce emissions to ensure that food and nutrition security objectives are not jeopardized. In order to achieve national milk goals, there will be need to be a consummate increase in animal numbers even with the adoption of multiple interventions. To meet Kenya's national emissions goals, widespread adoption of several locally appropriate interventions will be required. International support will be needed to meet Kenya's conditional Nationally Determined Contributions under the 2015 Paris Agreement, as well as food and nutrition security goals. [Display omitted] • Livestock are a primary source of GHG emissions in African countries, but demand for animal products is increasing. • Assessed milk yield gaps for dairy systems in Kenya and outscaled results to national level to determine milk and climate goals can be reached by 2030 using interventions. • Large milk yield gaps exist in Kenya, but gaps can be at least partially closed using locally appropriate interventions. • At the national scale, locally appropriate interventions reduced GHG emission intensities but increased absolute emissions. • All except one scenario fell short of Kenya's national emissions target by 2030, even with adoption of interventions. [ABSTRACT FROM AUTHOR]

Sustainable dairy production is included in the policy agenda of many countries in the tropics to address, among others, their commitment to the Paris Agreement. To the best of our knowledge, however, a study to assess the impact of the proposed interventions for sustainable dairy production is still lacking for most of those countries. Using policy goals as entry points to develop scenarios can provide insight into the impact of policy interventions on dairy farming practices. This study aimed to evaluate the implication of interventions towards sustainable dairy development identified by the governments of Indonesia and Costa Rica. Information about current farming practices (i.e. the baseline) were collected on 32 smallholder dairy farms in Indonesia and 24 dairy farms in Costa Rica. Scenarios were designed based on policy goals for dairy development and climate change mitigation in each country. The scenarios for Indonesia encompassed relocation of the dairy sector to Sumatra to allow coupling of livestock to land combined with a restriction on manure production to ensure all manure to be applied to grow forage, and a restriction on the amount of purchased feeds, at two levels: maximally 100% and 50% of the baseline. The scenarios for Costa Rica included a silvopastoral system and a reduction in the amount of purchased feeds, at two levels: 50% and 80% lower than the baseline. We estimated greenhouse gas (GHG) emissions at chain level and carbon (C) stocks at farm level. The scenarios for Indonesia increased herd size and milk output by 240–360%, and GHG emissions per farm by 269–455%, while decreased GHG emissions per kg milk by 1–10%, compared to the baseline. C stocks per farm were higher in the scenarios than in the baseline, but compared to natural vegetation much more C is lost under the scenarios because more land is being used. The scenarios for Costa Rica reduced herd size and milk output by 5–25% and GHG emissions per farm by 17–35%, while GHG emissions per kg milk decreased by 10%, compared to the baseline. C stocks per farm were comparable. To achieve the multiple policy goals for sustainable dairy development, the governments need to consider the trade-off between increasing milk production and reducing GHG emissions. In Indonesia, relocation of the dairy sector needs a strict policy to avoid the expansion of dairy farms into tropical forest land. Furthermore, the Costa Rican government needs to incentivise dairy farmers to implement a silvopastoral system to reduce GHG emissions and land use. This, however, will be at the expense of milk output. [Display omitted] • Implications of policy interventions for sustainable dairy development were assessed. • Scenario analysis shows trade-offs between policy goals for Indonesia and Costa Rica. • Improving feed self-sufficiency can contribute to climate change mitigation but needs land. • Silvopasture improves carbon stocks but climate change mitigation is limited. • Trade-off between enhanced milk production and climate change mitigation is evident. [ABSTRACT FROM AUTHOR]

To achieve the goal of Green Hydrogen Mission, India needs to work on three fronts concurrently. These are Feedstock Systems, Circular Economy integration, and the Environmental Impact of Hydrogen Emissions. This study addresses a critical research gap by offering a holistic assessment of India's preparedness in these interconnected areas. Prior research has often focused on individual aspects of this challenge. This work examines all three factors simultaneously to gain a clearer picture of India's ability to achieve its ambitious emission reduction goals. It analyzes India's rich feedstock resources, exploring initiatives like methane cracking and green hydrogen blending as emission reduction and sustainable energy solutions. Examining various sectors, including manufacturing and waste management, reveals barriers to circular economy integration, such as economic constraints and lack of awareness, alongside proposed solutions. Furthermore, the environmental impact of hydrogen emissions is scrutinized, stressing the importance of understanding and mitigating hydrogen emissions for a low-carbon economy. The study concludes by advocating for collaborative efforts among policymakers, industry stakeholders, and researchers. This collaboration is crucial to drive India's Green Hydrogen Mission forward through innovative solutions, policy interventions, and technological advancements. By addressing these interconnected areas, India can achieve its Green Hydrogen Mission goals and contribute significantly to sustainable development and climate change mitigation. [Display omitted] • Assesses India's readiness on three fronts, guiding future strategies. • Emphasizes methane cracking and hydrogen blending for emissions reduction. • Examines India's circular economy integration across sectors. • Addresses hydrogen emissions' environmental impact and mitigation. [ABSTRACT FROM AUTHOR]

The afforestation of tropical forests plays an important role in mitigating climate change. Exploring the impacts of nitrogen (N) and phosphorus (P) deposition on earthworm communities is significant for understanding the contributions of tropical forests to global change. A 14-year field experiment simulating N and P deposition at a station with 50-year-old tropical plantations was conducted. We found that the pantropical widespread exotic earthworm species Pontoscolex corethrurus was dominant, and it did not respond to exogenous N input. Moreover, P addition only increased the abundance of P. corethrurus after 14 years. Similarly, neither N addition nor P addition changed the stoichiometric traits of P. corethrurus. However, over the past decade, the abundance, biomass, and carbon (C), N, and P concentrations in the tissues of P. corethrurus have increased. A strong positive correlation between P. corethrurus population size and soil gram-negative (G−) bacteria biomass was observed, suggesting that P. corethrurus may benefit from the soil bacterial channel. This study ascertained that non-natural tropical lands may be resistant to N and P deposition in terms of earthworm related belowground processes, which would be helpful for fully understanding plant-soil biota feedback and their contributions to tropical plantation development and the mitigation of global climate change. • 14-year effects of N and P deposition on the earthworm Pontoscolex corethrurus were studied. • The dominant earthworm P. corethrurus did not respond to N addition. • P addition increased the abundance of P. corethrurus until 14 years later. • Both N and P addition did not alter the stoichiometric traits of P. corethrurus. • P. corethrurus became more abundant and may be related to soil G− bacteria. [ABSTRACT FROM AUTHOR]

The application of renewable energy to drive the electroreduction of carbon dioxide (CO 2) into valuable compounds serves as a means of energy storage and simultaneously aids in the mitigation of climate change. In this study, a bimetallic catalyst consisting of Zinc and Copper is synthesized using the Zinc-doped HKUST-1 metal-organic framework. The catalyst is then fabricated on gas diffusional electrode and investigated in both H-Cell and Flow cell configurations for electrochemical CO 2 reduction reaction (ECO 2 RR). In the H-Cell, the catalysts that have been developed exhibit an ethylene faradaic efficiency (FE) up to 40 % when operated at a potential of −0.8 V relative to the reversible hydrogen electrode (RHE). The Zn-Cu bimetallic gas diffusion electrodes (GDE) exhibit an impressive ethylene FE up to 45 % when operating at a current density of −200 mA cm−2 at −1.0 V versus RHE in the flow cell. This research offers valuable insights into the strategic development of copper-based bimetallic catalysts with the aim of enhancing the efficiency of electrochemical reduction of CO 2 to yield multicarbon compounds. [Display omitted] [ABSTRACT FROM AUTHOR]