High Share Of Renewable Energy Research Articles

Global Wind-Power Generation Capacity in the Context of Climate Change

Establishing power systems with a high share of renewable energy sources is a pivotal step toward achieving a globally sustainable transition to green and low-carbon energy. This study focuses on low-output wind power that affects the generation capacity of power systems with a high share of renewable energy sources. Utilizing the Coupled Model Intercomparison Project Phase 6 datasets, a predictive model for low-output wind power was employed to investigate regional trends worldwide. The frequency and duration of low-output wind-power events exhibited increasing trends globally, particularly in East Asia and South America, but not in North America. By 2060, the annual total days with low-output wind power in East Asia and South America could rise to 13 and 5 d, and the maximum continuous duration of low-output wind power could reach 5 and 2 d, respectively. As wind power becomes a primary electricity source, such low output could lead to shortages in energy supply within the power system, triggering large-scale power outages. This issue calls for critical attention when establishing power systems with a high share of renewable energy sources. The conclusions provide a basis for analyzing power supply risks and configuring flexible power sources for scenarios with a high share of renewable energy.

Coordinated price-based control of modulating heat pumps for practical demand response and peak shaving in building clusters

With a high share of renewable energy in the power grid, it becomes increasingly difficult to ensure a continuous balance between power generation and consumption, thereby endangering grid stability. A substantial opportunity to address this challenge and align the heating demand with intermittent power production is offered by space heating and domestic hot water, which account for 80% of the energy consumption in buildings. Further research on the control of building clusters is required, where peak load management of multiple buildings can ensure grid stability during peak hours and contribute to avoiding power outages. In this paper, a rule-based controller is presented, called Extended Price Storage Control+ (EPSC+), for the practical and flexible operation of heating systems in a building cluster. Under dynamic pricing, the loads of electric heating devices for the provision of space heating and domestic hot water are shifted by EPSC+ while accounting for peak load constraints. The performance of EPSC+ is evaluated in a nine-week winter simulation study with a building cluster of ten buildings in Germany. For comparison, a hierarchical model predictive controller (MPC) and a hysteresis two-point controller are employed as benchmarks. Results close to those of MPC are achieved by EPSC+by reducing the median peak load by 38.8% and median electricity costs by 15% compared with the hysteresis controller. In contrast to MPC, EPSC+ does not require models, forecasts, or optimization and is computationally inexpensive, rendering it more attainable for real-world implementation.

Dispatch strategies for large-scale heat pump based district heating under high renewable share and risk-aversion: A multistage stochastic optimization approach

Heat pumps play an essential role in decarbonizing the heating sector, and their adoption is projected to rise significantly. The high share of large-scale heat pumps in district heating exposes heating utilities to uncertainty in electricity markets. This challenge is further exacerbated by 1) future high share of renewable energy resulting in increased uncertainty of electricity prices, and 2) introduction of voluntary energy bids for balancing energy markets (or regulation market). Despite the importance of this issue, little research has been conducted to address it. Therefore, this paper investigates the optimal dispatch of large-scale heat pump based district heating by adopting multi-stage stochastic optimization approach to minimize the total expected heat generation cost, taking sequential electricity markets prices as stochastic. We also evaluate the impact of high renewable energy penetration on this optimal dispatch strategy. Furthermore, we include the risk preference of district heating operator by using conditional value at risk in the objective function. We conclude that heat pump should be coupled with flexible technologies like electric boilers as more renewable energy and balancing market trading increases flexible units' dispatch. Also, most of the heat produced (50%) in our case study is used flexibly via thermal storage. We find more renewable could lead to negative expected costs and voluntary bids in balancing market further reduces the expected cost by 28–59%. Furthermore, trading risk increases significantly with renewable energy penetration, which can be mitigated to a limited extent by bidding in up and down balancing market. Risk aversion shifts trading from intraday to day-ahead market and promotes heat pump dispatch.

Mitigation of land-related impacts of solar deployment in the European Union through land planning policies

Solar power is space-intensive and will contribute to intensify land competition, a factor typically not captured by models. This study uses the Integrated Assessment Model WILIAM which explicitly represents the land use changes driven by solar energy expansion through a hard link of its energy and land modules including net energy restrictions. A Green Growth type transition is simulated for the European Union with a high renewable energy share target in electricity mix by 2050, testing different land use planning policies.The results show that a rapid deployment of solar power in land without land policies can intensify land use conflicts and increase associated land use change emissions. Land-use requirements for solar would be 1–1.4 % of total land (corresponding to 55–75 % of urban land), which could be problematic locally. The implementation of land-use protection and land siting policies could reduce 23 % of total land occupied bv solar photovoltaics panels (with respect to forest and cropland the area occupied could be reduced up to 88 %), and 23–47 % of the land use change associated emissions with respect to a scenario where not policies are applied. These results show the importance of integrating land use and energy planning policies to alleviate the undesired impacts.

Incorporating operational constraints into long-term energy planning: The case of the Egyptian power system under high share of renewables

This study assesses the performance of Egypt's energy system on a short-term basis to ensure that it can handle a high share of renewable energy, as predicted in the long-term planning up to 2040. PLEXOS software is used for short-term analysis to simulate operational performance on an hourly basis while considering the constraints of Unit Commitment (UC) and Economic Dispatch (ED). The long-term energy planning model, which covered the years 2020–2040 with chosen representative years (2020 as the base year and 2025, 2030, 2035, and 2040), was validated by the short-term operational model. The results from the short-term analysis indicate that by the year 2040, 69.5 % of the electricity mix from renewable energy sources (excluding hydro) can be accommodated, representing a slightly lower capacity than the 70 % predicted by the long-term plan. Due to the high share of intermittent renewable energy sources, traditional generators will experience excessive cycling in 2040. The average weighted short-run marginal cost in 2040 is projected to be 7.8 USD/MWh, compared to 18.37 USD/MWh in 2020, due to the low operating costs of renewable energy plants and their high penetration in 2040. Various operational techniques have been suggested to reduce the curtailment of renewable energy to achieve only 1.2 % of the total energy generation of the system by 2040. Additionally, other adjustments to the system operation are being considered to maintain a balance in the power system on a short-term basis.

Does energy transition reduce carbon inequality? A global analysis.

Energy transition from fossil fuels to renewables is instrumental in mitigating climate change. Low-income countries have a higher share of renewable energy in their total energy consumption than rich countries (WDI, 2023). Thus, it is imperative to examine the role of energy transition in affecting relative CO2 emissions between rich and poor sections of the societies across income groups of the countries. In this context, our study contributes by constructing the carbon inequality models with renewable and non-renewable energy consumption as prime explanatory variables separately for 114 countries over a data period 1990-2019. The models are estimated individually for high-middle-low-income countries by controlling for foreign direct investment (FDI), economic growth, and innovations. Starting with preliminary econometric operations, we employ the dynamic simulated panel autoregressive distributed lag approach and Driscoll-Kraay standard error regression for empirical investigation. We find that energy transition reduces carbon inequality globally. Innovation has a negative impact, economic growth has a positive impact on carbon inequality, and FDI has an asymmetric impact based on the income level of the countries. The crucial global policy implications are discussed.

Evaluation of a carbon tax in Costa Rica linking a demand system focused on energy goods and an input-output model

This study evaluates the impact of a carbon tax on CO2 emissions in Costa Rica. For the above, a demand system is estimated using data from a household expenditure survey, which allows for obtaining the elasticities of demand for various groups of goods focused on energy. Then, the environmental extension of the Leontief price model is implemented to determine the change in prices caused by different carbon tax rates (25, 50, 75, and 100 USD/ton CO2). Subsequently, both models are linked to obtain the variations in production and sectoral emissions. In addition, a Monte Carlo simulation is carried out since the estimated price elasticities have a standard deviation associated with them. The results suggest that carbon taxes mainly affect transportation, while the rest of the sectors have slight impacts in all simulated scenarios. For example, the drop in total CO2 emissions is explained between 89.6% and 91.3% by the decrease in emissions in the passenger transport and other transport sectors with a 95% confidence interval. The previous is explained by the composition of Costa Rica's energy matrix, which has a very high share of renewable energies. Finally, some climate policy options are suggested to contribute to this country's carbon neutrality.

Optimization model of low-carbon technology adoption timing for coal power under decarbonization and flexibility demand: Empirical study in Beijing-Tianjin-Hebei region, China

Substituting renewable energy for coal power under the carbon neutrality goal is an inevitable path for power system transformation, while the high share of renewable energy leads to a rapid rise in system flexibility demand. Currently, coal-fired power is still one of the most economical and reliable large-scale flexible resources in China. Therefore, the issue of how to mitigate the conflict between cleanliness and flexibility for coal-fired power is urgent to be solved. Accordingly, this paper established an optimization framework for the retirement and technology adoption of coal-fired power units with high spatial-temporal resolution, and the regional carbon emission budget is estimated from a top-down perspective. Secondly, a dynamic carbon quota allocation method considering technological innovation and adoption is proposed. The carbon trading cost of the units is evaluated from a bottom-up perspective, to realize the interaction between the obligatory policy constraints of the top-level target and the flexible incentives of the market mechanism. Finally, the empirical analysis was conducted in the Beijing-Tianjin-Hebei region of China. The optimal solution achieved by proposed method results in a substantial 27% reduction in total costs while keeping the increase in carbon emissions below 3%. By analyzing the dynamic evolution path of coal and the scale of diffusion of multi-type technologies, the differences in the roles coal power assuming at various stages of decarbonization are discussed. The robustness of the model and the validity of the proposed method were verified by comparing the dynamic/static carbon quota allocation. Overall, this study provides an effective optimization model for investigating the low-carbon technology adoption timing for coal power in Beijing-Tianjin-Hebei region, and offers valuable insights for other coal-dominated emerging economies seeking for power system transformation roadmap in the forthcoming net-zero carbon age.

Electrification of public buses in Jakarta, Indonesia: A life cycle study

Indonesia plans to mitigate the environmental emissions, particularly the carbon emissions, from the transport by replacing conventional buses with battery electric buses (BEBs). However, there are limited studies on the potential environmental benefits of BEBs and mostly focused on carbon emissions. In this study, the environmental impacts of adopting BEBs in Jakarta's public transportation system were examined using Life Cycle Assessment (LCA) to better understand its potential environmental impacts. Using LCA, the environmental impacts of BEBs were also compared with conventional buses across their life cycles, which included raw materials extraction until the end of life stages. The results showed diesel buses have generally lower environmental impacts than BEBs due to the high share of fossil fuels in the electricity generation in Indonesia. Scenario analysis showed that extending the life cycle, using different battery disposal methods, and using battery reuse could lead to higher environmental benefits in using BEBs. Among the scenarios considered in the study, prolonging the lifespan of the bus to 32 years, using electricity mix with a higher share of renewable energy and reusing the lithium-ion batteries, BEBs would have lesser environmental impact per kilometre. In particular, the particulate matter formation (PM2.5) dropped 21 %, while the overall life cycle of BEB using the highest renewable scenario showed an average of 25 % improvement compared to the baseline scenario regarding environmental impact.

Least‐Cost for High Renewable Energy Share in the Distributed Energy System through Integrated Supply and Demand Side Management

This study analyzes energy supply and demand‐side management strategies to increase the renewable energy share in a distributed energy system (DES), which includes demand response (DR) options and different renewable energy sources (RES) and energy storage systems (ESS). To analyze the least costs for increasing the renewable energy share by integrating the DR, RES, and ESS, four scenarios of the DES were generated. Then, a new optimization model was proposed to identify the optimal design and operation strategies, which includes maximizing the profit as an objective function subject to various constraints, such as technical capacity and electricity price. To illustrate the capability of the proposed model, this study presented a case study of the DES for the residential sector of Jeju Island, Korea. The results showed that the optimal scenario, involving the integration of the DR, RES, and ESS, shows 0.115 $/kW hr of the levelized cost of electricity and 10% of renewable energy share, which correspond to 32.7% and 31.5% improvement, respectively, compared to the baseline. Additionally, the practical strategies to meet the Korean target of the high‐share RES were discussed through a sensitivity analysis of major external factors, such as carbon tax, incentives, and the electricity trading price in electricity markets.

Validation Aspects for Grid-Forming Converters Based on System Characteristics and Inertia Impact

Grid-forming converters are considered a key technology for electrical grids with a high share of renewable energy. However, there is a lack of a general, robust and verifiable definition of what constitutes this behaviour. Therefore, this paper presents three simple scenarios that enable such a definition. They are based on simple black-box simulations that allow manufacturers to protect their development work. It can be shown that grid forming can be clearly distinguished from grid-following controls by their grid behaviour in the proposed scenarios. Extensive results illustrate this and also provide suggestions to deepen the understanding of grid-forming grid behaviour and its impact on system inertia. These findings should inspire the development of a clear definition and ultimately new requirements for converter systems.

A multi-area intra-day dispatch strategy for power systems under high share of renewable energy with power support capacity assessment

Long-distance power support through High-voltage Direct Current (HVDC) has provided feasible solutions for power dispatch and control problems in multi-area power systems under high share of renewable energy. In this paper, an advanced multi-area intra-day dispatch strategy for power systems with high penetration of renewable energy considering power support capacity is established to increase the accommodation of wind power and enhance the stability of the power system. At first, a novel assessment method of regional active power support capacity is carried out in this paper, which can sufficiently quantify the regional power margin (RPM), the DC dispatchable power (DCDP), and the regional power support distance (RPSD) of a power system. Subsequently, a multi-area intra-day dispatch strategy based on power support capacity analysis is proposed, where constraints on conventional units, wind farms, transmission lines, and RPSD are developed. Finally, to enable the development of the dispatch model, a model predictive control (MPC) scheme is used to update the power support capacity indicators dynamically and improve model reliability. The effectiveness and superiority of the proposed strategy are verified by case studies. Numerical results show a 7.02% cost reduction and overload risk reduction by using the proposed strategy compared to conventional global optimization methods.

Fault Detection and Classification to Design a Protection Scheme for Utility Grid with High Penetration of Wind and Solar Energy

This paper designed a protection scheme for utility grid with high share of renewable energy (RE) generated from wind energy and solar energy plants. This is based on extraction of features from the current using Stockwell transform (ST), Hilbert transform (HT), and alienation coefficient. A Stockwell index (SI) is designed by extracting current features using ST, a Hilbert index (HI) is designed by extracting current features using HT, and an alienation index (AI) is designed by extracting current features using an alienation coefficient. A fault index (FI) is formulated by multiplying the SI, HI, AI, and WF (weight factor). This FI is implemented for fault detection. Fault classification is achieved considering number of fault phases and ground fault index (GFI). This GFI is designed by processing zero sequence currents applying ST. GFI effectively identifies the ground involved during event of a fault. A designed protection scheme is effective to identify faults in the scenario of high RE share and during various cases of study which includes the variations of fault impedance, different fault occurrence angles (FOA), fault incident at different nodes, and noisy condition. This protection scheme effectively discriminates the fault events from the operational events such as feeder operation, load, and capacitor switching. Performance of hybrid protection method formulated in this paper is better relative to alienation coefficient-based protection scheme (ACPS) reported in literature. The ACPS has maximum error and mean error of fault detection equal to 9.54% and 5.99%, respectively, which is relatively high compared to the respective values for the proposed method which are 1.89% and 0.978%, respectively. ACPS is effective for detecting the fault events in noise level of 30 dB SNR (signal-to-noise ratio) whereas the proposed method effectively identifies the faults in the high noise scenario of 20 dB SNR.

Co-optimization of decarbonized operation of coal-fired power plants and seasonal storage based on green ammonia co-firing

Coal-fired power plants (CFPP) can provide significant inertia and flexibility support for power systems with a high share of renewable energy (RE). The ammonia–coal co-firing technology can effectively reduce carbon emissions (CE) from CFPP. We propose a low-carbon power supply and multi-timescale energy storage system in combination with this technology. The system consists of batteries, fuel cells and the CFPP equipped with the ammonia–coal co-combustion module. It can also cope with short and long term fluctuations in RE. We use the Mixed Integer Linear Programming method to construct an optimization model for this system. We then set up six sub-cases according to the power systems in Texas, USA. Based on weekly and annual simulations of these cases, we analyze the economic and environmental performances of the proposed system with different RE shares, as well as exploring the characteristics of different energy storage methods. Compared to batteries or fuel cells only scenarios, CFPP configured with green ammonia co-firing can significantly reduce the total operating cost (TOC), CE and RE curtailment. We use the rolling horizon optimization method to simulate and calculate the distribution of ammonia storage levels throughout the year. The ammonia storage levels are high in spring and autumn and low in summer. Finally, the sensitivity and efficiency analysis of the proposed system is carried out. As far as ammonia co-firing technology allows, the higher the maximum ammonia–coal mixing ratio, the lower TOC, CE and RE curtailment. This phenomenon is more significant at a higher RE share. The overall efficiency of green ammonia synthesis and combustion for power generation is around 13.92%. It can work in synergy with batteries and fuel cells to improve efficiency and reduce the marginal cost of long-term energy storage.

러시아-우크라이나 전쟁에 대한 유럽연합(EU) 회원국의 여론과 그 형성 배경에 관한 비교 연구

This study examines public opinion in European countries on the Russo-Ukrainian war and the EU’s sanctions against Russia. In particular, it investigates the different perceptions of issues related to the war in Ukraine in terms of security and economic implications and seeks to explain the differences in public opinions among European countries. Leading public opinions in Europe strongly condemn Russia’s invasion of Ukraine and agree to impose strong sanctions. However, there are different attitudes in public opinion depending on the expected economic damage and energy mix. Countries concerned about significant economic damage due to rising energy prices tend to prefer measures that take the economic impact into account rather than value-oriented hard-line responses. Additionally, countries with a high proportion of fossil fuel use also show the same tendency. On the other hand, countries that can endure economic damage and better respond to energy crises with a high share of renewable energy prefer a hard-line response. Countries with a favorable image of Russia have a relatively solid public opinion insisting on considering the economic situation, while countries with a pro-American tendency demand a hard-line response based on values. In terms of diplomacy and security, it was found that the more countries feel the security threat from the war, the more public opinion supports a value-centered policy stance and insists on military aid to Ukraine. In particular, the three Nordic countries, which have a long tradition of neutrality, judge Russia’s invasion of Ukraine as a threat to fundamental European values and are more in favor of military aid to Ukraine than other countries. This study provides significant implications for forecasting the EU’s response to Russia. For the EU to maintain a strong stance against Russia, it is essential to secure solidarity among the members. The EU will need to coordinate the different economic burdens of its Member States and fully reflect the varying security awareness of European countries on its common security and defense policy. These efforts are necessary to maintain a solid and coherent policy stance on the war in Ukraine.

Short-term energy scenario of district energy system using optimised renewable energy mix with and without energy storage

The study proposes a multi-objective, multi-node optimisation model for the district energy system to achieve high renewable energy share by 2030. A combined analysis is conducted to reduce total system cost, carbon footprint; and satisfy inertia and flexibility requirements of integrated renewable energy system of the considered district. An hourly deterministic tool, Flextool, developed by IRENA, is used for analysis. Multiple scenarios are analysed to identify an optimal capacity expansion plan. The interaction between various energy generation units while meeting hourly energy demand is studied. The flexibility issues concerned with high VRE (Variable renewable energy) integration expected in the future energy grid are identified, and the effect of battery storage on curtailment is evaluated. The maximum VRE absorption capacity of the district is examined, and the shadow value is calculated for all considered scenarios. It is concluded that the district energy system could achieve 52% renewable energy share, zero loss of load and minimum curtailment in 2030 with adequate policy interventions. If the recommended investment pattern is followed, carbon intensity will reduce from 10.729 g/kWh to 6.70 g/kWh and 6.02 g/kWh without and with battery storage systems. The application of battery storage as a flexibility solution resulted in a significant reduction in curtailments. The study demonstrated that Flextool is a competent flexibility assessment tool which provides comprehensive support to optimise capacity expansion and system operations.

Comparative sustainability assessment of lithium-ion, lithium-sulfur, and all-solid-state traction batteries

PurposeTraction batteries are a key component for the performance and cost of electric vehicles. While they enable emission-free driving, their supply chains are associated with environmental and socio-economic impacts. Hence, the advancement of batteries increasingly focuses on sustainability next to technical performance. However, due to different system definitions, comparing the results of sustainability assessments is difficult. Therefore, a sustainability assessment of different batteries on a common basis considering the three sustainability dimensions is needed.MethodsThis paper investigates the sustainability of current and prospective traction battery technologies for electric vehicles. It provides a common base for the comparison of the predominant lithium-ion batteries with new technologies such as lithium-sulfur and all-solid-state batteries regarding the environmental and socio-economic impacts in their supply chain. A life cycle sustainability assessment of ten battery types is carried out using a cradle-to-gate perspective and consistent system boundaries. Four environmental impact categories (climate change, human toxicity, mineral resource depletion, photochemical oxidant formation), one economic performance indicator (total battery cost), and three social risk categories (child labor, corruption, forced labor) are analyzed.ResultsThe assessment results indicate that the new battery technologies are not only favorable in terms of technical performance but also have the potential to reduce environmental impacts, costs, and social risks. This holds particularly for the lithium-sulfur battery with solid electrolyte. The environmental benefits are even amplified with a higher share of renewable energy for component and battery production. Nevertheless, hotspots related to the high energy demand of production and the supply chain of the active materials remain.ConclusionsThis article emphasizes the need to evaluate different battery technologies on a common basis to ensure comparability of the results and to derive reliable recommendations. The results indicate that the lithium-sulfur battery with solid electrolyte is preferable since this battery has the best indicator scores for all impact categories investigated. However, all-solid-state batteries are still under development so that no conclusive recommendation can be made, but further development of these battery technologies appears promising.

Definition of Scenarios for Modern Power Systems with a High Renewable Energy Share.

Recent environmental policies have led academic, industrial, and governmental stakeholders to plan scenarios with a high share of renewable energy sources (RES), to ensure that future energy systems, composed mostly of RES, can remain stable, match the demand during seasonal variations and are economically feasible. This article considers different energy scenarios to obtain various options in terms of size, generation technologies, and grid configuration. The scenarios are studied in the POSYTYF project and are quantified through an optimization-based algorithm, where the test grids topologies are based on specific locations in Europe, and real data related to the availability of RES, as well as the demand. Different RES technologies are considered to meet requirements of grid integration of renewables at different horizons of time, up to 100% in the most futuristic case. The optimization algorithm is applied to three scenarios. It is shown that solar photovoltaic (PV) and wind can provide the renewable backbone, but they lack flexibility to achieve a very high share in the energy mix. Solar thermal and pumped hydro become important to cover the last range of integration, as they provide high flexibility, which is crucial for high share, but they are expensive for low share.

Sizing Design for a Hybrid Renewable Power System Using HOMER and iHOGA Simulators

In this study, a comparative sizing design for renewable power systems was developed based on HOMER (Hybrid Optimization of Multiple Energy Resources) and iHOGA (improved Hybrid Optimization by Genetic Algorithms) simulators. A comparative analysis of the solutions obtained with iHOGA and HOMER simulators for the same hybrid renewable power system (HRPS) is presented in detail. The system contained a new hybrid configuration that used fuel cell (FC) as a green energy source, replacing the polluting diesel generator system, as well as other renewable energy sources, namely, photovoltaic panels, wind turbine, a battery stack, power converters, and electric load. The same case study was carried out for the design of the hybrid system using HOMER and iHOGA simulators to perform a comparative analysis of the solutions obtained for potential investment. The analysis showed a higher share of renewable energy for iHOGA (92%) compared to HOMER (81%), so the first design produced 51.61 kg/year less carbon dioxide. Moreover, the operating costs (2134 RON/year for HOMER and 70.56 RON/year for iHOGA) and the cost of electricity were higher by 96% and 2.5%, respectively, for HOMER compared to iHOGA. Taking into account the need for high reliability, safe operation, and lower operation/exploitation costs, the design implemented in iHOGA is clearly more efficient and useful in practice, and this is supported by the three iHOGA case studies.

Can enhancing financial inclusivity lower climate risks by inhibiting carbon emissions? Contextual evidence from emerging economies

Climate change is regarded as a global concern whereby lowering climate risks, especially by curbing greenhouse gas emissions, has become a critically important policy agenda worldwide. Hence, this study assesses whether financial inclusion, alongside energy efficiency improvement, renewable energy use, economic growth, international trade, and urbanization, can mitigate carbon dioxide emissions in 22 emerging economies. Considering the period of analysis from 2008 to 2018 and utilizing econometric methods robust to handling cross-sectionally-dependent, heterogeneous, and endogenous panel data, the findings reveal that financial inclusion is directly associated with higher discharges of carbon dioxide. Contrarily, energy efficiency improvement and higher share of renewable energy in the aggregate energy consumption level inhibit carbon dioxide emissions. Moreover, energy efficiency gains moderate the financial inclusion-emissions nexus by jointly reducing carbon emissions with greater financial inclusivity. Finally, the results indicate that economic growth, international trade, and urbanization trigger climate risks by boosting the emission figures. In light of these findings, several carbon dioxide-mitigating policies are recommended for neutralizing climate risks in emerging countries of concern.