Search Results (415)

The carbon dioxide spillover effects and influencing factors of the “Belt and Road Initiative” (BRI) in African countries must be assessed to evaluate the effectiveness, promote low-carbon transmissions in African countries, and provide recommendations for achieving the 2030 Sustainable Development Goals. This novel study employs carbon dioxide emission intensity (CEI) and per capita carbon dioxide emissions (PCE) as dual indicators to evaluate the spatial spillover effects of 54 BRI African countries on their neighboring countries’ carbon emissions from 2007 to 2023. It identifies the key factors and mechanisms affecting these spillover effects using the spatial differences-in-differences (SDID) model. Results indicate that since the launch of the BRI, the CEI and PCE of BRI African countries have significantly increased, largely due to trade patterns and industrialization structures. Greater trade openness has further boosted local economic development, thereby increasing carbon dioxide’s spatial spillover. Government management and corruption control levels show some heterogeneity in the spillover effects, which may be attributed to long-standing issues of weak institutional enforcement in Africa. Overall, this study reveals the complex relationship between BRI African economic development and environmental outcomes, highlighting the importance of developing sustainable development strategies and establishing strong differentiated regulatory regimes to effectively address environmental challenges. Full article

With the rapid pace of urbanization, cities are increasingly facing severe challenges related to environmental pollution, ecological degradation, and climate change. Extreme climate events—such as heatwaves, droughts, heavy rainfall, and wildfires—have intensified public concern about sustainability, environmental protection, and low-carbon development. Ensuring environmental preservation while maintaining residents’ quality of life has become a central focus of urban governance. In this context, evaluating green indicators and predicting urban greenness is both necessary and urgent. This study incorporates international frameworks such as the EU Green City Index, the European Green Capital Award, and the United Nations Sustainable Development Goals to assess urban sustainability. The Extreme Gradient Boosting (XGBoost) algorithm is employed to predict the green level of cities and to develop multiple optimized models. Comparative analysis with traditional models demonstrates that XGBoost achieves superior performance, with an accuracy of 0.84 and an F1-score of 0.81. Case study findings identify “Greenhouse Gas Emissions per Person” and “Per Capita Emissions from Transport” as the most critical indicators. These results provide practical guidance for policymakers, suggesting that targeted regulations based on these key factors can effectively support emission reduction and urban sustainability goals. Full article

Research on ecosystem carbon sequestration services and ecological compensation is crucial for advancing carbon neutrality. As a public good, ecosystem carbon sequestration services inherently lead to externalities. Therefore, it is essential to consider externalities in the flow of sequestration services. However, few studies have examined intra- and inter-regional ecosystem carbon sequestration flows, making regional ecosystem carbon sequestration flows less comprehensive. Against this background, the research objectives of this paper are as follows. The flow of carbon sequestration services between Henan Province and out-of-province regions is studied. In addition, this study clarifies the beneficiary and supply areas of carbon sink services in Henan Province and the neighboring regions at the prefecture-level city scale to obtain a more systematic, comprehensive, and actual flow of carbon sequestration services for scientific and effective eco-compensation and to promote regional synergistic emission reductions. The research methodologies used in this paper are as follows. First, this study adopts a meta-coupling framework, designating Henan Province as the focal system, the Central Urban Agglomeration as the adjacent system, and eight surrounding provinces as remote systems. Regional carbon sequestration was assessed using net primary productivity (NEP), while carbon emissions were evaluated based on per capita carbon emissions and population density. A carbon balance analysis integrated carbon sequestration and emissions. Hotspot analysis identified areas of carbon sequestration service supply and associated benefits. Ecological radiation force formulas were used to quantify service flows, and compensation values were estimated considering the government’s payment capacity and willingness. A three-dimensional evaluation system—incorporating technology, talent, and fiscal capacity—was developed to propose a diversified ecological compensation scheme by comparing supply and beneficiary areas. By modeling the ecosystem carbon sequestration service flow, the main results of this paper are as follows: (1) Within Henan Province, Luoyang and Nanyang provided 521,300 tons and 515,600 tons of carbon sinks to eight cities (e.g., Jiaozuo, Zhengzhou, and Kaifeng), warranting an ecological compensation of CNY 262.817 million and CNY 263.259 million, respectively. (2) Henan exported 3.0739 million tons of carbon sinks to external provinces, corresponding to a compensation value of CNY 1756.079 million. Conversely, regions such as Changzhi, Xiangyang, and Jinzhong contributed 657,200 tons of carbon sinks to Henan, requiring a compensation of CNY 189.921 million. (3) Henan thus achieved a net ecological compensation of CNY 1566.158 million through carbon sink flows. (4) In addition to monetary compensation, beneficiary areas may also contribute through technology transfer, financial investment, and talent support. The findings support the following conclusions: (1) it is necessary to consider the externalities of ecosystem services, and (2) the meta-coupling framework enables a comprehensive assessment of carbon sequestration service flows, providing actionable insights for improving ecosystem governance in Henan Province and comparable regions. Full article

Rural areas around the world are increasingly dealing with energy and environmental challenges. These challenges are particularly acute in developing countries, where persistent reliance on traditional energy sources—such as wood fuel—intersects with concerns about forest conservation and energy sustainability. While wood fuel use is often portrayed as unsustainable, it is important to acknowledge that much of it remains ecologically viable and socially embedded. This study explores the role of rural entrepreneurs in shaping low-carbon transitions at the intersection of household energy practices and environmental stewardship. Fieldwork was carried out in four rural Zambian communities in 2016 and complemented by 2024 follow-up reports. It examines the connections between household energy choices, greenhouse gas emissions, and forest resource dynamics. Findings reveal that over 60% of rural households rely on charcoal for cooking, with associated emissions estimated between 80 and 150 kg CO₂ per household per month. Although this is significantly lower than the average per capita carbon footprint in industrialized countries, such emissions are primarily biogenic in nature. While rural communities contribute minimally to global climate change, their practices have significant local environmental consequences. This study draws attention to the structural constraints as well as emerging opportunities within Zambia’s rural energy economy. It positions rural entrepreneurs not merely as policy recipients but as active agents of innovation, environmental monitoring, and participatory resource governance. A model is proposed to support sustainable rural energy transitions by aligning forest management with context-sensitive emissions strategies. Full article

Driven by the urgent need to mitigate climate change and achieve net-zero emissions, carbon pricing has emerged as a critical policy tool in major economies worldwide. This study compares carbon pricing in the EU, China, Canada, and Singapore, evaluating effectiveness in emission reductions, with the EU ranking first with high carbon prices, road market coverage, and strict penalties, based on carbon price per capita. Conversely, Singapore’s position as fourth in carbon price per capita among these four most mature carbon markets, Singapore has a high GDP per capita and lower carbon prices. Canada’s fragmented provincial policies and China’s limited market coverage, despite being the top global emitter. Our analysis reveals three critical success factors: (1) higher carbon prices per capita are essential for carbon reduction, (2) the necessity of penalties on carbon price per capita from EUR 20–EUR 100, and (3) expanded market coverage maximizes impact. To address global disparities, we propose a Uniform Carbon Pricing Mechanism under the Global Carbon Resilience Framework (GCRF), based on carbon price per capita tiered pricing: EUR 100/t (developed), EUR 30–50 (developing), and EUR 5–15 (least-developed countries). This balanced system supports vulnerable regions while cutting emissions, proving that fair carbon pricing is crucial for climate goals and economic stability. Full article

Carbon emission forecasting is a critical step in addressing climate change and effective environmental management. However, previous studies have concentrated mainly on socioeconomic factors, with less attention directed toward the significant impact of urban form. To address the shortcomings of previous studies, this study introduced three types of landscape indices that can characterize urban form and combined them with conventional socioeconomic factors to create a new carbon emission forecasting method. The enhanced STIRPAT and PLUS models were employed to forecast future changes in various socioeconomic factors and urban form, with the aim of forecasting carbon emissions in 21 cities of Guangdong during 2025–2060. The results confirm that urban form has an obvious influence on carbon emissions. In comparison to the baseline model, which considered only socioeconomic factors, the incorporation of urban form into the carbon emission forecast resulted in a reduction in the mean absolute percentage error from 7.16% to 6.18%. Moreover, carbon emissions were found to be positively correlated with GDP per capita, energy intensity, permanent population, share of secondary sector, LSI, and PLADJ but negatively correlated with PD. Furthermore, Guangdong will not be able to accomplish its “carbon peaking” objective around 2030, except in a low-carbon situation. Our proposed method could enhance the rationality of carbon emission forecasting, thereby providing a reasonable decision-making basis for low-carbon management. Full article

Air quality and environmental issues have gained attention from countries and organizations worldwide over the past several decades. In recent years, carbon peak and carbon neutrality have been mentioned at many international conferences and meetings aimed at reducing and controlling environmental challenges. This study focuses on trend analysis and expectations for the duration of control for environmental air quality (EAQ) indicators, assesses the current EAQ conditions across global countries, and presents reasonable suggestions for environmental control. The study begins by examining the annual, per capita, and per square meter (${\mathrm{m}}^2$) carbon dioxide (CO₂) emission peak and standardizations, where carbon standardization is a replacement for carbon neutrality. A similar quantitative methodology was employed to assess classical air quality factors such as sulfur dioxide (SO₂) and nitrogen oxides (NO_x). The findings suggest that the average control year length (ACYL) of NO_x is longer than that of SO₂, and the ACYL of SO₂ is, in turn, longer than that of CO₂. From an energy structure perspective, regressions results indicate that biofuel and wind power contribute to improvements in EAQ, while coal, oil, and gas power exert negative impacts. Moreover, a long-term EAQ model utilizing an adjusted max–min normalization method is proposed to integrate various EAQ indicators. This study also presents an EAQ ranking for global countries and recommends countries with critical EAQ challenges. The results demonstrate that it is plausible to control EAQ factors at an excellent level with advances in control technologies and effective measures by government, industries, and individuals. Full article

The United Arab Emirates has become increasingly concerned about carbon dioxide emissions due to their impact on climate change and the environment, as it is one of the top ten world oil producers. This reflects its recognition of the need for sustainable development. Therefore, this research aims to study the dynamic impact of economic growth, urbanization, energy consumption, and economic openness on CO₂ emissions, during the period 1975–2022. To capture these effects, a novel dynamic ARDL is employed to separate the impact of each variable separately. The results indicate that the effect of GDP per capita on carbon emissions is negative, as a 1% increase in economic growth leads to a decrease in carbon dioxide emissions by 0.6%. Moreover, the findings confirm that the UAE economy does not apply to the Kuznets curve in developing countries. Furthermore, the impact of energy consumption, urbanization, and trade openness is positive on CO₂ emissions, as a 1% increase in each raises CO₂ by 0.17%, 11.6%, and 1.2%, respectively. These findings are important for decision makers in the environmental field to make decisions to reduce carbon emissions by altering the impact of economic variables and spread awareness towards reducing carbon emissions. Full article

In this study, the relationship between economic growth and carbon emissions for the period 1968–2022 in Turkey was evaluated within the framework of the EKC (Environmental Kuznets Curve) hypothesis. In addition, the impacts of renewable energy consumption and agricultural value added on carbon emissions were analyzed using the ARDL bounds testing approach. The validity of the results was also tested using the FMOLS and DOLS methods. The findings confirmed the existence of a cointegration relationship between carbon emissions and per capita income, renewable energy consumption, and agricultural value added. Long-term analyses indicate that renewable energy consumption reduces carbon emissions, whereas growth in agricultural value added leads to an increase in emissions. In addition, it has been determined that the EKC hypothesis is valid in both the long and short terms and that increases in per capita income raise emissions up to a certain threshold and have a mitigating effect when this threshold is exceeded. The results of the short-term analysis showed that the effects of renewable energy consumption vary across periods, and that agricultural value added increases emissions in the short term. This study provides empirical evidence for Turkey by incorporating sectoral variables within the EKC framework and offers meaningful insights for policymakers regarding the environmental impacts of agricultural value added and renewable energy use in the context of a developing country. Accordingly, fiscal policy instruments such as green taxation, carbon credit trading mechanisms, and financial and agricultural subsidies should be more effectively utilized in Turkey to support structural transformation in agriculture and promote the use of clean energy, in line with the findings that suggest the need for targeted agricultural and energy policies aligned with Turkey’s SDG commitments. Full article

This study investigates the environmental effects of agricultural trade, renewable energy use, and economic growth in a panel of 14 selected countries for the period 2000–2021. Per capita CO₂ emissions are modeled as the dependent variable using a second-generation panel data method, the Augmented Mean Group (AMG) estimator, which accounts for cross-sectional dependence and slope heterogeneity. The analysis reveals that the share of renewable energy in total energy consumption significantly reduces carbon emissions, emphasizing the role of green energy policies in environmental improvement. In contrast, economic growth is found to increase emissions, indicating the validity of only the initial phase of the Environmental Kuznets Curve (EKC) hypothesis. Additionally, agricultural imports—and in certain cases, exports—exert upward pressure on emissions, likely due to logistics and production-related externalities embedded in the trade process. Group-specific results highlight distinct dynamics across countries: while renewable energy adoption plays a stronger role in emission mitigation in developing economies, trade composition and production technology drive environmental outcomes in developed ones. The findings underscore the need to redesign trade and energy strategies with explicit consideration of environmental externalities to align with long-term sustainability objectives. Full article

Understanding the historical peak situation and the rules for CO₂ emissions from buildings helps to formulate reasonable building mitigation strategies, accelerating the achievement of the Chinese government’s carbon peak goal. As developed regions, cities in the Guangdong–Hong Kong–Macao Great Bay Area (GBA) provide valuable reference cases. This study quantified the historical building CO₂ emissions of GBA cities and analyzed the contribution of driving factors using the Kaya identity and logarithmic mean Divisia index. Furthermore, we assessed the historical peak situation using the MK trend test method and discussed the reasons behind the inter-city difference in the peak situation shown by the environmental Kuznets curve. The results indicate that the building-related CO₂ emissions of the GBA will slowly increase to 96.90 Mt CO₂ by 2020 and that P&C buildings accounted for a larger proportion of emissions. Emission factors and population made the largest positive and negative contributions, respectively, to this total. At the city level, Guangzhou, Shenzhen, and Hong Kong ranked as the top three sources of building CO₂ emissions. Hong Kong peaked, Dongguan and Macao plateaued, and other cities maintained either slow or quick growth. CO₂ emissions unit area, per capita building CO₂ emissions, and building CO₂ emissions reached a peak in that order. This study provides a valuable reference for formulating a city-level path showing building CO₂ emissions peaks. Full article

As China steadily advances its “dual carbon” strategy, understanding the factors influencing carbon emission efficiency (CEE) is crucial for promoting high-quality urban development. This study examines Western Valley cities (WVCs), which play a key role in regional development and exhibit a distinct spatial structure. Using a super-efficiency slacks-based measure (SBM) model and economic and social panel data, we measured CEE and analyzed its spatiotemporal evolution. A geographically and temporally weighted regression (GTWR) was then applied to assess the spatiotemporal heterogeneity of influencing factors. Our findings revealed that the overall CEE of these cities remains relatively low, with a complex pattern of change. While efficiency levels in northern, southern, and central cities have gradually increased, there are notable differences in the quantity and spatial distribution of cities with high, relatively high, relatively low, and low efficiency over time. Additionally, the positive effects of technological investment, road density, population density, and per capita gross domestic product on CEE follow an increasing trend, whereas the negative impacts of energy intensity, green space ratio, secondary industry proportion, land use scale, and gas consumption gradually weaken. Additionally, the magnitude and direction of these effects vary significantly across northern, central, and southern cities. These findings provide important theoretical and practical insights for region-specific strategies aimed at reducing emissions and improving efficiency in WVCs. Full article

This study investigates the impact of income redistribution on carbon emissions across 154 countries from 1995 to 2023, with a particular focus on carbon inequality. Using a dynamic panel approach with two-step System GMM estimations, the analysis considers three dependent variables: average per capita emissions, top 1% per capita emissions, and the ratio of top 1% per capita emissions to national average per capita emissions. Results show that income redistribution (measured in both absolute and relative terms) significantly reduces average per capita emissions in the short term. However, redistribution has no mitigating effect on the carbon emissions of the top 1%; in some models, it is even associated with increases in elite emissions and a widening of carbon inequality. These findings suggest that while redistribution may contribute to national emission reductions, it is insufficient to curb the carbon-intensive lifestyles of the wealthiest. The analysis confirms the Environmental Kuznets Curve (EKC) hypothesis and underscores the need for complementary policy tools to more effectively address the emissions of high-emitting individuals. Overall, this study contributes to the literature by linking income redistribution with emission disparities across income groups and highlights the importance of considering distributional dynamics in climate policy design. Full article

Despite global efforts to address climate change, carbon dioxide (CO₂) emissions are still on the rise. While carbon dioxide is essential for life on Earth, its increasing concentration due to human activities poses severe environmental and health risks. Therefore, accurately and efficiently predicting CO₂ emissions is essential. Hence, this research delves deeply into the prediction of CO₂ emissions by examining various deep learning models utilizing time series data to identify carbon dioxide levels in Oman. First, four important production materials of Oman (oil, gas, cement, and flaring), which have a great impact on CO₂ emissions, were selected. Then, the time series related to the release of CO₂ was collected from 1964 to 2022. After data collection, preprocessing was performed, in which outliers were removed and corrected, and data that had not been measured were completed using interpolation. Then, by dividing the data into two sections, education (1946–2004) and test (2022–2005) and creating scenarios, predictions were made. By creating four scenarios and modeling with two independent GRU and LSTM models and a hybrid LSTM-GRU model, annual carbon was predicted for Oman. The results were evaluated with three criteria: root mean square error (RMSE), mean absolute percentage error (MAPE), and correlation coefficient (r). The evaluations showed that the hybrid LSTM-GRU model with an error of 2.104 tons has the best performance compared to the rest of the models. By identifying key contributors to carbon footprints, these models can guide targeted interventions to reduce emissions. They can highlight the impact of industrial activities on per capita emissions, enabling policymakers to design more effective strategies. Therefore, in order to reduce pollution and increase the productivity of factories, using an advanced hybrid model, it is possible to identify the carbon footprint and make accurate predictions for different countries. Full article

The choice of carbon inequality metrics can significantly influence demand-side mitigation policies and their equity outcomes. We propose integrated carbon inequality metrics, including juxtaposing carbon inequality with economic inequality, disparity ratios across income and age groups, and structural income–urbanization inequality patterns. We then apply these new metrics and use the household expenditure survey data from China Family Panel Studies as a case study to examine household consumption-based carbon emissions in China. We assess the extent to which household consumption patterns, household expenditure, age, and urbanization contribute to the gap in per-capita household carbon footprints (CF) across income groups. We find that in relative terms, the top 20% income group accounts for 38% of total emissions, whereas the bottom 20% emit about 8% in China. Per-capita CFs vary slightly widely in their inequality than expenditure. The CF disparity ratios of all eight consumption categories across provinces concentrate around 4.5. CF disparity ratios of households with elderly members range from 1 to 3 and decrease with increasing household size. Rural CF-Gini exhibit a slightly wider range (0.15 to 0.52) than urban CF-Gini (0.16 to 0.42). Per capita CF of urban inhabitants was substantially larger than that of the rural ones, with 8.83 tCO₂ per capita in urban regions vs. 2.68 tCO₂ in rural regions. This study provides a nuanced understanding of within-country disparities to inform equitable demand-side mitigation solutions. Full article