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Renewable microgrids enhance security, reliability, and power quality in power systems by integrating solar and wind sources, reducing greenhouse gas emissions. This paper proposes a machine learning approach, leveraging Gaussian Process (GP) and Krill Herd Algorithm (KHA), for energy management in renewable microgrids with a reconfigurable structure based on remote switching of tie and sectionalizing. The method utilizes Gaussian Process (GP) for modeling hybrid electric vehicle (HEV) charging demand. To counteract HEV charging effects, two scenarios are explored: coordinated and intelligent charging. A novel optimization method inspired by the Krill Herd Algorithm (KHA) is introduced for the complex problem, along with a self-adaptive modification to tailor solutions to specific situations. Simulation on an IEEE microgrid demonstrates efficiency in both scenarios. The predictive model yields a remarkably low Mean Absolute Percentage Error (MAPE) of 1.02381 for total HEV charging demand. Results also reveal a reduction in microgrid operation cost in the intelligent charging scenario compared to coordinated charging. [ABSTRACT FROM AUTHOR]

Our understanding of the environmental and occupational health implications of pollutants emitted in steel production is still lacking, despite the considerable amount of research devoted to this topic. Given the significance of steel recycling and the need to reduce greenhouse gas emissions, many steel factories are adopting electric arc furnace (EAF) technology. The use of a technological system designed for the capture of pollutants emitted through EAF steel production is highly ecological because of its utilization of iron scrap and low investment cost. Despite this, the main issue with the EAF is the environmental impact it poses, specifically the release of pollutants into the air, such as dust and organic substances, chlorinated dioxins and furans, dioxin-like polychlorinated biphenyls and brominated dioxins and furans. As a result, workers in this field have a considerable rate of morbidity. The main challenge for EAFs is to optimize the capture of powders produced during the techno-logical process, both from the EAF and the workplace. A state-of-the art solution for managing pollutants in modern steel manufacturing is highlighted in this paper, featuring a method used in Romania that employs the Best Available Techniques (BAT) reference document for iron and steel production to directly collect pollutants from the EAF. The system included a cylindrical fitting, a heat exchanger to cool the gases and a hood to collect contaminants. In comparison to other ventilation options, this equipment boasts lower investment and lower operational costs because of its effective and minimal air flow. Through the use of cutting-edge technology and progressive strategies, we can move closer toward our objective of a workplace free from injuries in the steel industry. [ABSTRACT FROM AUTHOR]

A substantial level of significance has been placed on renewable energy systems, especially photovoltaic (PV) systems, given the urgent global apprehensions regarding climate change and the need to cut carbon emissions. One of the main concerns in the field of PV is the ability to track power effectively over a range of factors. In the context of solar power extraction, this research paper performs a thorough comparative examination of ten controllers, including both conventional maximum power point tracking (MPPT) controllers and artificial intelligence (AI) controllers. Various factors, such as voltage, current, power, weather dependence, cost, complexity, response time, periodic tuning, stability, partial shading, and accuracy, are all intended to be evaluated by the study. It is aimed to provide insight into how well each controller performs in various circumstances by carefully examining these broad parameters. The main goal is to identify and recommend the best controller based on their performance. It is notified that, conventional techniques like INC, P&O, INC-PSO, P&O-PSO, achieved accuracies of 94.3, 97.6, 98.4, 99.6 respectively while AI based techniques Fuzzy-PSO, ANN, ANFIS, ANN-PSO, PSO, and FLC achieved accuracies of 98.6, 98, 98.6, 98.8, 98.2, 98 respectively. The results of this study add significantly to our knowledge of the applicability and effectiveness of both AI and traditional MPPT controllers, which will help the solar industry make well-informed choices when implementing solar energy systems. [ABSTRACT FROM AUTHOR]

Rapid placement of electric vehicle charging stations (EVCSs) is essential for the transportation industry in response to the growing electric vehicle (EV) fleet. The widespread usage of EVs is an essential strategy for reducing greenhouse gas emissions from traditional vehicles. The focus of this study is the challenge of smoothly integrating Plug-in EV Charging Stations (PEVCS) into distribution networks, especially when distributed photovoltaic (PV) systems are involved. A hybrid Genetic Algorithm and Simulated Annealing method (GA-SAA) are used in the research to strategically find the optimal locations for PEVCS in order to overcome this integration difficulty. This paper investigates PV system situations, presenting the problem as a multicriteria task with two primary objectives: reducing power losses and maintaining acceptable voltage levels. By optimizing the placement of EVCS and balancing their integration with distributed generation, this approach enhances the sustainability and reliability of distribution networks. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]

With the gradual increase of international willingness to reach the carbon peak and carbon neutrality, this paper decomposes the influencing factors of China's carbon emission changes from 2008 to 2019 using the Logarithmic Mean Divisia Index model (LMDI), and analyzes the contribution amount and rate of each influencing factor. The results found that: for the whole country, the cumulative growth of carbon emissions during the study period is about 416,484.47 (104 tons), among which the economic growth effect plays a major role in promoting, with a cumulative contribution rate of 284.16%; The increase in regulation intensity and the optimization of industrial structure, however, suppress carbon emissions well, with a cumulative contribution rate of about – 199.21% and − 64.75%, respectively, during the study period. For economic regions, the cumulative influence direction of each driver is the same as that of the whole country, while the population size effect in the northeast economic region and the regulation input effect in the eastern coastal economic region act in the opposite direction from other economic regions, and the carbon emission reduction direction of the energy intensity effect varies from one economic region to another. Accordingly, this paper proposes policy recommendations to enhance regulatory intensity, optimize industrial and energy consumption structure, implement localized emission reduction strategies, and promote synergistic emission reduction in economic zones. [ABSTRACT FROM AUTHOR]

Nowadays environmental issues have been of great concern to the world, among which the problem of global warming caused by greenhouse gas emissions is particularly prominent. All countries in the Kyoto Protocol and the Paris Agreement have committed to control greenhouse gas emissions, and China, as the largest carbon emitter, has assumed a heavier burden. China has been striving to develop low-carbon technologies such as hydrogen, nuclear, wind, and solar energy, but the most attention should be paid to CCUS, which many scholars have high expectations that CCUS can help China reduce emissions to some extent. Therefore, this paper presents a prediction that CCUS can reduce 3.8% of carbon emissions for China in 2040 when CCUS emission reductions increase at a rate of 30%. The power and chemical industries could reduce carbon emissions by 2.3% and 17.3%, respectively. [ABSTRACT FROM AUTHOR]

This paper focuses on the development trend of industrial carbon emissions in Bengbu city, Anhui Province in the next ten years, and how to help the industry reach the carbon peak as soon as possible. The research process and conclusions are as follows: (1) Through literature review and carbon emission index method, five main factors affecting industrial carbon emission are identified. (2) The resistance model is used to analyze the main resistance factors of industrial carbon emission reduction in Bengbu city. (3) Based on the existing data of Bengbu city from 2011 to 2020, the grey prediction EGM (1,1) model is used to predict the industrial carbon emissions of Bengbu city from 2021 to 2030. The results show that among the five factors, the urbanization rate has the most significant impact on industrial carbon emissions, while energy intensity has the least impact. Bengbu's industrial carbon emissions will continue to increase in the next decade, but the growth rate will be flat. Based on the findings of the analysis, specific recommendations on urbanization development, energy structure, and industrial structure of Bengbu city are put forward. [ABSTRACT FROM AUTHOR]

Nowadays environmental issues have been of great concern to the world, among which the problem of global warming caused by greenhouse gas emissions is particularly prominent. All countries in the Kyoto Protocol and the Paris Agreement have committed to control greenhouse gas emissions, and China, as the largest carbon emitter, has assumed a heavier burden. China has been striving to develop low-carbon technologies such as hydrogen, nuclear, wind, and solar energy, but the most attention should be paid to CCUS, which many scholars have high expectations that CCUS can help China reduce emissions to some extent. Therefore, this paper presents a prediction that CCUS can reduce 3.8% of carbon emissions for China in 2040 when CCUS emission reductions increase at a rate of 30%. The power and chemical industries could reduce carbon emissions by 2.3% and 17.3%, respectively. [ABSTRACT FROM AUTHOR]

This paper focuses on the development trend of industrial carbon emissions in Bengbu city, Anhui Province in the next ten years, and how to help the industry reach the carbon peak as soon as possible. The research process and conclusions are as follows: (1) Through literature review and carbon emission index method, five main factors affecting industrial carbon emission are identified. (2) The resistance model is used to analyze the main resistance factors of industrial carbon emission reduction in Bengbu city. (3) Based on the existing data of Bengbu city from 2011 to 2020, the grey prediction EGM (1,1) model is used to predict the industrial carbon emissions of Bengbu city from 2021 to 2030. The results show that among the five factors, the urbanization rate has the most significant impact on industrial carbon emissions, while energy intensity has the least impact. Bengbu's industrial carbon emissions will continue to increase in the next decade, but the growth rate will be flat. Based on the findings of the analysis, specific recommendations on urbanization development, energy structure, and industrial structure of Bengbu city are put forward. [ABSTRACT FROM AUTHOR]

In order to reveal the relationship between new urbanization and carbon emission to provide reference opinions for the construction of low-carbon urbanization, an evaluation system between new urbanization and carbon emission was constructed. Then their matching degree relationship was analyzed by coupling coordination degree model based on the data from 2012 to 2021 in Anhui Province, and their development trend from 2023 to 2032 was predicted by gray prediction model. The results show that: (1) New urbanization and carbon emission have the co-trend effect, and the consistency of core impact factors is relatively significant. Among them, the level of new urbanization increases from 0.058 in 2012 to 0.699 in 2021 and carbon emission development increases from 0.023 in 2012 to 0.165 in 2021, which both showing an upward trend. Meanwhile, social urbanization and population carbon emission are the core influencing factors. (2) The coupling coordination degree between new urbanization and carbon emission is low, but the synergy trend is optimistic and there is a large room for improvement. Among them, the coupling coordination coefficient of the coupling system rises from 0.136 in 2012 to 1.412 in 2021 (antagonistic phase), and then reaches 0.820 by 2032 (highly coordinated phase) by forecast. It shows that their current development is unbalanced, but the development trend is good, and there is a chance for improvement. This paper deepens the understanding of the logical correlation between new urbanization and carbon emission, and the following views are formed: (1) Low-carbon development is still the mainstream of new urbanization; (2) The coordination development of new urbanization and carbon emission reduction should be strengthened. [ABSTRACT FROM AUTHOR]

Based on the counted power system emission factors of North China Power Grid, a community carbon emissions sample database is constructed. The support vector regression (SVR) model is trained to forecast the power carbon emissions, which is optimized by genetic algorithm (GA). A community carbon emission warning system is designed according the results. The dynamic emission coefficient curve of the power system is obtained by fitting the annual carbon emission coefficients. The time series SVR carbon emission prediction model is constructed, while the GA is improved to optimize its parameters. Taking Beijing Caochang Community as an example, a carbon emission sample database is generated based on the electricity consumption and emission coefficient curve to train and test the SVR model. The results show that the GA–SVR model fits well with the training set and the testing set, and the prediction accuracy of the testing set reaches 86%. In view of the training model in this paper, the carbon emission trend of community electricity consumption in the next month is predicted. The carbon emission warning system of the community is designed, and the specific strategy of community carbon emission reduction is proposed. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of Emission Trading Scheme (ETS) adoption on the country-level reduction rate of carbon emission. We first used Environmental Kuznets Curve (EKC) tests to group countries into three categories: inverse U-shaped and gamma-shaped EKC for decoupled countries, and a positive linear EKC for non-decoupled countries. We then examined the effectiveness of ETS adoption. We found ETS was effective for both post-industrial and pre-industrial economies. Compared to countries that have not adopted ETS, the carbon emission reduction (increment) rate of decoupled (non-decoupled) countries that have adopted ETS is faster (slower). Furthermore, ETS adoption significantly reduces overall carbon emissions per capita compared to other global events, such as oil crises. The results imply that a market-based mechanism is an effective strategy for achieving sustainable development, thus, providing insights for policymakers and governments to design effective carbon neutrality policies to achieve sustainable development. [ABSTRACT FROM AUTHOR]

As the main means to dovetail the domestic system with international rules, institutional openness is the key to deepening participation in the global economic governance system, breaking through energy and carbon emission constraints, and achieving green and sustainable economic development. Taking 284 prefecture-level cities in China from 2006 to 2019 as the research sample, this paper uses the establishment of Pilot Free Trade Zones as a quasi-natural experiment to systematically identify and test the actual impact of institutional openness on urban carbon emissions in China through the asymptotic difference in difference method, instrumental variables method, spatial econometric model, and mediating effects model. Meanwhile, technological progress is used as the entry point to analyze the intrinsic mechanism of action by adopting digital transformation oriented to efficiency improvement and green innovation capability oriented to R&D innovation as the differentiated perspective. It is found that institutional openness significantly suppresses urban CO2 emissions, and there is a certain heterogeneity and spatial spillover effect of this effect. Further study finds that institutional openness achieves carbon emission reduction through technological progress. The study aims to find new institutional innovation and development paths for low carbon development. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal reactive power control method to maximize wind farm revenue and minimize the total electrical losses of a doubly-fed induction generator (DFIG)-based wind farm. Specifically, the split Bregman method is used to solve the optimal control problem in a distributed manner. That is, the optimization problem is decomposed into sub-problems by the optimal distributed control strategy, and each sub-problem is solved independently in each local controller through the parallel method, which reduces the calculating burden and improves the information privacy. Thus, when a fault occurs, the proposed distributed control strategy can overcome the system fault and improve the reliability and security of the system. Furthermore, an economic financial model of annual revenue is contributed to examine the income impact with or without certified emission reduction (CER) by the clean development mechanism (CDM). Compared with the dual ascent (DA) method, sequential quadratic programming (SQP) method and the proportional dispatch method (PDM), the annual revenue (AR) of the wind farm using the proposed split Bregman method is the highest. Simulation results demonstrate that this method has promising performance in both optimization quality and computational efficiency. [ABSTRACT FROM AUTHOR]

Many developing countries are facing the difficulty of choosing between economic growth and energy conservation and emission reduction (ECER). China has strengthened the implementation of ECER by setting environmental accountability as the development goal of local governments, hoping to have better governance effects. To evaluate the actual intervention effect of this approach, this paper constructs panel data covering 46 countries from 1995 to 2014 and uses the difference-in-differences (DID) method and the composite control method to quantitatively analyse the policy effect. The results show that China can effectively curb energy consumption and carbon emission intensity per unit of GDP by adding ECER targets to the government's five-year plan, which has significant effects on ECER. Furthermore, we use an intermediary mechanism to test and identify low-carbon alternatives and an ECER promotion mechanism for technological advancement. The conclusion shows that economic development is compatible with low carbon and energy consumption. Combined with China's long-term goals for ECER, it can be considered that on the road to achieving carbon peaking and carbon neutrality in the future, the economy and tertiary industry should be rationally developed, the degree of urbanization should receive more attention, and the proportion of thermal power generation should be reduced. [ABSTRACT FROM AUTHOR]

Characterizing the permeability evolution and methane release is of great significance for the safe mining of the high gas outburst seams, as well as coal and gas simultaneous extraction. It contributes to reduce methane emissions from coal mining for greenhouse effect control. Theoretical analysis, laboratory testing, and numerical simulation are widely used methods to characterize the permeability and methane release with the treatment process of pressure-relief mining. However, these methods cannot fully reflect the complexity of filed practice. In this study, we report the effectiveness of protective coal seam (PCS) mining and the pressure-relief area in the protected coal seam (PDCS) based on detailed and integrated field measurements in a Chinese coal mine. To the best of our knowledge, it is the first time to measure the permeability coefficient and gas pressure evolution in the PDCS during the process of PCS longwall mining. The evolution of the permeability coefficient in the pressure-relief area during PCS mining can be divided into four stages: slowly decreasing, sharply increasing, gradually decreasing, and basically stable. The maximum permeability coefficient is 322 times of the initial value and stabilized at 100 times after the goaf compacted. The gas pressure evolution in the PDCS indicates that the strike pressure relief angle is 52.2° at the active longwall face zone, and 59.3° at the installation roadway side. The inclined pressure relief angles at the lower and upper sides of the longwall face are 75° and 78.9°, respectively. The residual gas content and gas pressure of the PDCS in the pressure-relief area are reduced to less than 6 m3/t and within 0.4 MPa, respectively. The field measurements further prove that pressure-relief mining can prevent coal and gas outbursts in PDCSs. The field observations in this paper can serve as benchmark evidence for theoretical analysis and numerical simulations, and also provide insights into realizing safety mining in similar conditions. [ABSTRACT FROM AUTHOR]

As the world is giving climate change a higher priority, several Coalitions are working on meeting a clean and green environment (SDG 13), focusing on new streets' design in total urban development. A previous study discussed the pedestrian mobility status in Riyadh city, with attention to sustainable mobility, considering the pedestrians' traveling patterns that use their cars rather than public transportation. This paper investigates the Ecomobility that seeks to promote the integration of passenging, cycling, wheeling, and walking. This approach will provide better health (SDG 3), clean air, mobility and accessibility, noise avoidance, greenhouse gas emission reduction, individual cost savings, and energy efficiency (SDG 11). It analyzes the pedestrians' traveling modes in Riyadh city through a case study of the Prince Sultan University's (PSU) community, then evaluates the pedestrians' environment quality in the campus surroundings. Analysis used a web-based survey referred to the PSU people, including Students, Faculty, and Staff. On the other hand, the pedestrian's environment quality was evaluated on-site built on well-constructed criteria. The assessment's results addressed the factors influencing pedestrian choices and underlined the barriers to transformation to Ecomobility. They revealed that around 73% of the respondents expressed willingness to transform to ecomobility modes. About 52% of the survey sample preferred the public bus option. For the non-motorized options, students preferred cycling and wheeling modes, while faculty members and staff preferred walking. Based on conclusions, recommendations are proposed to foster pedestrian ecomobility for sustainable urban development in Riyadh city. [ABSTRACT FROM AUTHOR]

With the rapid development of distributed energy resources and natural gas power generation, multi-energy microgrid (MEMG) is considered as a critical technology to increase the penetration of renewable energy and achieve the target of carbon emission reduction. Therefore, this paper proposes a low-carbon economic dispatch model for MEMG to minimize the daily operation cost by considering integrated demand response (IDR) and multistep carbon trading. Specifically, IDR operation includes shifting of shiftable electric load, adjusting of flexible thermal load and cooling load, and it is employed to decrease operation cost. Besides, the multistep carbon trading means that different carbon trading prices correspond to different carbon trading volumes, which is applied to stringently restrict carbon emission. The simulation results show that the proposed model can effectively reduce the carbon emission while greatly decrease the operation cost. [ABSTRACT FROM AUTHOR]

The Brazilian government's decision to open the Amazon biome to sugarcane expansion reignited EU concerns regarding the sustainability of Brazil's sugar sector, hindering the ratification of the EU-Mercosur trade agreement. Meanwhile, in the EU, certain conventional biofuels face stricter controls, whilst uncertainty surrounding the commercialisation of more sustainable advanced-biofuels renders bioethanol as a short- to medium-term fix. This paper examines Brazil's land-use changes and associated greenhouse gas emissions arising from an EU driven ethanol import policy and projections for other 13 biocommodities. Results suggest that Brazil's sugarcane could satisfy growing ethanol demand and comply with EU environmental criteria, since almost all sugarcane expansion is expected to occur on long-established pasturelands in the South and Midwest. However, expansion of sugarcane is also driven by competition for viable lands with other relevant commodities, mainly soy and beef. As a result, deforestation trends in the Amazon and Cerrado biomes linked to soy and beef production could jeopardize Brazil's contribution to the Paris agreement with an additional 1 ± 0.3 billion CO2eq tonnes above its First NDC target by 2030. Trade talks with a narrow focus on a single commodity could thus risk unsustainable outcomes, calling for systemic sustainability benchmarks, should the deal be ratified. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

The risk of points-of-no-return, which, once surpassed lock the world into new dynamics, have been discussed for decades. Recently, there have been warnings that some of these tipping points are coming closer and are too dangerous to be disregarded. In this paper we report that in the ESCIMO climate model the world is already past a point-of-no-return for global warming. In ESCIMO we observe self-sustained melting of the permafrost for hundreds of years, even if global society stops all emissions of man-made GHGs immediately. We encourage other model builders to explore our discovery in their (bigger) models, and report on their findings. The melting (in ESCIMO) is the result of a continuing self-sustained rise in the global temperature. This warming is the combined effect of three physical processes: (1) declining surface albedo (driven by melting of the Arctic ice cover), (2) increasing amounts of water vapour in the atmosphere (driven by higher temperatures), and (3) changes in the concentrations of the GHG in the atmosphere (driven by the absorption of CO2 in biomass and oceans, and emission of carbon (CH4 and CO2) from melting permafrost). This self-sustained, in the sense of no further GHG emissions, melting process (in ESCIMO) is a causally determined, physical process that evolves over time. It starts with the man-made warming up to the 1950s, leading to a rise in the amount of water vapour in the atmosphere—further lifting the temperature, causing increasing release of carbon from melting permafrost, and simultaneously a decline in the surface albedo as the ice and snow covers melts. To stop the self-sustained warming in ESCIMO, enormous amounts of CO2 have to be extracted from the atmosphere. [ABSTRACT FROM AUTHOR]

Brazil is one of the world's biggest emitters of greenhouse gases (GHGs). Fire foci across the country contributes to these emissions and compromises emission reduction targets pledged by Brazil under the Paris Agreement. In this paper, we quantify fire foci, burned areas, and carbon emissions in all Brazilian biomes (i.e., Amazon, Cerrado, Caatinga, Atlantic Forest, Pantanal and Pampa). We analyzed these variables using cluster analysis and non-parametric statistics to predict carbon and CO2 emissions for the next decade. Our results showed no increase in the number of fire foci and carbon emissions for the evaluated time series, whereby the highest emissions occur and will persist in the Amazon and Cerrado biomes. The Atlantic Forest, Pantanal, Caatinga and Pampa biomes had low emissions compared to the Amazon and Cerrado. Based on 2030 projections, the sum of emissions from fire foci in the six Brazilian biomes will exceed 5.7 Gt CO2, compromising the national GHG reduction targets. To reduce GHG emissions, Brazil will need to control deforestation induced by the expansion of the agricultural frontier in the Amazon and Cerrado biomes. This can only be achieved through significant political effort involving the government, entrepreneurs and society as a collective. [ABSTRACT FROM AUTHOR]

Most studies on CO2 emissions reduction strategies that address the 'two-degree scenario' (2DS) recognize a significant role for CCS. For CCS to be effective, it must be deployed globally on both existing and emerging energy systems. For nations with large-scale emissions, offshore geologic CO2 storage provides an attractive and efficient long-term strategy. While some nations are already developing CCS projects using offshore CO2 storage resources, most geographic regions have yet to begin. This paper demonstrates the geologic significance of global continental margins for providing broadly-equitable, geographically-relevant, and high-quality CO2 storage resources. We then use principles of pore-space utilization and subsurface pressure constraints together with analogs of historic industry well deployment rates to demonstrate how the required storage capacity can be developed as a function of time and technical maturity to enable the global deployment of offshore storage for facilitating 2DS. Our analysis indicates that 10–14 thousand CO2 injection wells will be needed globally by 2050 to achieve this goal. [ABSTRACT FROM AUTHOR]