CO2 Emission Intensity Research Articles

Observed carbon decoupling of subnational production insufficient for net-zero goal by 2050

Historically, economic growth has been closely coupled to carbon emissions responsible for climate change, but to stabilize global mean temperature, net-zero carbon emissions are necessary. Some economies have begun to reduce emissions while continuing to grow, but this decoupling is not fast enough to achieve global climate targets. Subnational climate actions seem to be crucial for the achievement of these targets. Here, we uncover the effectiveness of subnational efforts by estimating decoupling rates and CO2 emission intensities over the last three decades for over 1,500 subnational regions, encompassing 85% of global emissions, using global data on reported economic output and gridded production-based emissions. Thirty percent of regions with available data have fully decoupled, with higher-income and historically carbon-intensive regions exhibiting higher rates of decoupling and declining emission intensity. Countries of the Organization for Economic Co-operation and Development with greater spending on subnational climate actions show higher decoupling rates, as do subnational regions in EU countries where climate policies have been implemented, highlighting the effectiveness of subnational policies. Moreover, subnational analysis reveals greater variance of decoupling rates within national boundaries than between them and that countries with weaker governance typically show higher variance of decoupling within their borders. If recent rates of production-based carbon decoupling continue, less than half of subnational regions would reach net-zero before 2050, even when accounting for observed acceleration via socioeconomic development and assuming no interregional carbon leakage.

Decarbonization pathways analysis and recommendations in the green steel supply chain of a typical steel end user-automotive industry

China's automotive industry, the world's largest producer and consumer, has reached a crucial stage in its transition from rapid expansion to high-quality and low-carbon development. Considering the decarbonization of the whole automotive industry, in addition to reducing the CO2 emissions from fuel supply and exhaust pipes, which account for 65–80 % of the total value chain CO2 emissions, the automotive industry should also accelerate the decarbonization of raw materials, which contribute to 18–22 % of these CO2 emissions. Many automotive manufacturers are collaborating with steel producers on green steel initiatives due to the high CO2 emissions from steel production, the integrated nature of the steel supply chain, and the need for early planning in low-carbon steel production routes transformation. To clarify the carbon emission characteristic of the automotive steel supply chain, this research establishes a mathematical method for calculating cradle-to-gate carbon footprint of automotive steel product based on BF (Blast furnace)-BOF (Basic oxygen furnace), Scrap-EAF (Electric arc furnace), and DRI (Direct reduced iron)-EAF steel production routes. The cradle-to-gate carbon footprints of BF-BOF, Scrap-EAF, and DRI-EAF steel production routes are 1711.84 kgCO2/t-sp (steel product), 916.39 kgCO2/t-sp, and 2738.53 kgCO2/t-sp. A projection of CO2 emissions in automotive steel supply chain from 2020 to 2060 has been investigated, taking into account production structure adjustment, scrap recycling, and low-carbon electricity adoption, as well as the demand for automotive steel products. Projections from 2020 to 2060 indicate that the CO2 emission intensity of the automotive steel supply chain will decrease by 28.25 % by 2030 and 93.99 % by 2060, with total emissions dropping by 28.47 % and 96.92 %, respectively. This research identifies effective decarbonization measures in the automotive steel supply chain, including internal and end-of-life (EOL) steel scrap recycling, which offer significant CO2 emissions reduction without increased costs, demonstrating high cost-effectiveness. In a word, this research provides a technical framework and data foundation for decarbonizing the automotive steel supply chain.

Does the application of industrial robots reduce the intensity of CO2 emissions embodied in manufacturing exports?

Industrial robot application (IRA) provides an opportunity for the low-carbon development of trade. This study focuses on the green revolution of manufacturing export trade, analyzes the mechanism by which IRA affects CO2 emissions embodied in manufacturing exports (CIE), and conducts an empirical test based on panel data from 37 countries from 2000 to 2019. This study found that first, IRA can significantly reduce CIE, but there is a U-shaped nexus between the two, which shows a rebound effect. Second, the heterogeneity test demonstrates that in comparison to both the low-tech and high-tech sectors, IRA in the medium-tech industry can significantly reduce CIE; compared with the low-IRA sectors, the high-IRA sectors exhibit a more obvious reduction. In addition, IRA has a stronger effect on high-carbon-intensity areas. Third, the mechanism test shows that IRA mainly affects CIE through low-carbon technology and productivity effects. Moreover, environmental regulations and the manufacturing intelligence process positively moderate the nexus between IRA and CIE. Finally, these conclusions provide possible empirical evidence for the smart evolution of the manufacturing industry and the green development of trade.

Thermoeconomic modeling of new energy system based on biogas upgrading to multigenerational purpose

The following article outlines an integrated approach toward the valorization of biogas for energy, chilled water, hot water, freshwater, and liquid carbon dioxide production. The suggested system includes a biogas upgrading unit with a biomethane-fueled burner, a Kalian cycle, an LNG regasification process, and a multi-effect desalination unit that can provide CO2, electricity, cooling, and heating. The new ideas in the proposed system include a cryogenic biogas upgrading process that can be used in many industrial settings, the production of liquid carbon dioxide through biogas upgrading, and the use of biomethane in the integrated combustion process. Furthermore, the grey wolf optimization technique is applied in various multi-objective optimization contexts to achieve optimal operating conditions and preferred performance outcomes. In this simulation, the generation of electricity reaches a value of 755 kW. Attached to it is a cooling load of about 5102 kW, with a heating load of 4725 kW, freshwater capacity about 1.33 kg/s, production rate of liquid CO2 at 0.58 kg/s, and natural gas at 3.1 kg/s. Thermodynamic results reveal that the proposed multigeneration performance scheme providently enhances energy and exergy efficiencies up to 59.82 % and 5.74 %, respectively, compared to the condition of a single product. The performed exergy analysis shows that the overall irreversibility of the suggested configuration is equal to 18,047 kW while about 42.6 % of this value is contributed from the heat exchanger E-104. Moreover, the CO2 emission intensity of the process can be kept as 0.35 kg/kWh. Cryogenic separation can obtain about 88 % of CO2 in biogas and turn it into its liquid phase. The performed economic assessment has resulted in the following total cost rate as well as cost per unit exergy: 321.38 $/h and 83.06 $/GJ, respectively. Under optimal conditions, an exergy efficiency of 13.40 % and a net power output of 2034.39 kW are attained.

Carbon emission scenario analysis of data centers in China under the carbon neutrality target

The low-carbon transformation of data centers is of great significance to achieve the goals of carbon peaking and carbon neutrality. This study compared and analyzed the overall situation of data centers in China. Based on China's CO2 emission and intensity targets in key years, the four variables of energy efficiency improvement rate, nonfossil energy consumption proportion, negative emission technology intensity, and waste energy utilization rate were introduced, and a net zero emission path model of data centers was established. Using scenario analysis to predict the total CO2 emissions and emission intensity from 2021 to 2060, three emission reduction path scenarios were obtained. Results showed that the energy consumption of data centers increased gradually, the carbon emissions first increased and then decreased, and the power usage effectiveness (PUE) of the data centers decreased gradually. The carbon peak time of the three scenarios is 2030, and the time for carbon neutrality is 2055, 2053, and 2051 in three scenarios. The data center industry should further improve the energy efficiency utilization rate, increase the proportion of nonfossil energy consumption, strengthen the technological innovation of carbon capture and storage, enhance the level of carbon sink, and optimize the utilization rate of waste energy.

МОНИТОРИНГ ПОТОКОВ ДИОКСИДА УГЛЕРОДА НА РАЗНОВОЗРАСТНЫХ ЗАЛЕЖАХ В РАЗЛИЧНЫХ ПРИРОДНО-КЛИМАТИЧЕСКИХ ЗОНАХ ЮГА ЗАПАДНОЙ СИБИРИ

The paper reflects the spatial and temporal variability of CO2 fluxes on fallow lands. The aim was to determine the soil CO2 emissions from fallow lands of different ages, taking into account the natural and climatic zones of the south of Western Siberia. The research was carried out in three natural and climatic zones of the Omsk region: steppe, forest-steppe, subtaiga; in each zone, three sites with different age fallow lands were identified: 5-10, 10-20 and older than 20 years. The soil CO2 emission was measured using exposure chambers with determination on a gas chromatograph. When comparing the intensity of CO2 emissions from fallow lands, depending on the natural and climatic zone, it can be noted that in the warm season the maximum level was in the subtaiga zone (on average for May-September 54.1 g of CO2 ∙ m-2 ∙ day-1), followed by the magnitude of flows in the forest-steppe zone (29.4), the minimum It was observed in the steppe zone (25.0). At the same time, the maximum value of the flows was observed in the subtaiga zone in July, in the forest–steppe and steppe zone in June. Younger deposits are characterized by a large amount of soil carbon dioxide emissions compared with older ones: in the subtaiga zone, the average seasonal emission of deposits 5-10 years old is 1.30 times higher than deposits older than 20 years, in the forest–steppe zone, respectively, 1.51, steppe – 1.63 times. The daily dynamics of soil CO2 fluxes has an increased level in the morning and afternoon hours, decreased in the evening and night hours, regardless of the zone.

2D mesh-knots metal organic frameworks functionalized with phytic acid for improving flame retardancy

Metal ions and organic compounds were adopted to form a two-dimensional mesh-knots metal organic frameworks (TMMOFs), which could functionalize with Phytic Acid (PA) for fireproof. The results of the functional group test show that two-dimensional mesh-knots metal organic frameworks (TM), TM with -NH2 (TMN) and TMN with PA (TMNP) have been successfully prepared by coordination bond. The samples appeared irregular ellipsoid with size of particles below 100 nm. The values of limiting oxygen index (LOI) test depicted the flame resistance have been enhanced from 22.7 % to 30 % due to the addition of -NH2 and PA. The peak heat release rate (pHRR) and total heat release (THR) value of TM-PA@wood declined noticeably by 55.9 % and 68.6 % compared to pure wood. CO2 emissions intensity of TMNP@wood declined from about 0.40 to 0.12 compared with samples without PA. The CO2 and CO maximum production of TMNP@wood were significantly lower 246% and 64% than TMN@wood, respectively. PA and ZrO2 after combustion could catalyze wood to form carbon residue as condense phase, delay and minimize the peak of CO2 and CO to reduce toxicity. This work provides an effective strategy for synthesis and application of two-dimensional materials in flame retardant field.

Energy efficiency and greenhouse gas emissions: A panel ARDL model of top five emitters in Africa

The Paris Agreement has mandated drastic decarbonization by developed and developing economies. Many of the top African emitters are now exploring drastic restructuring of the production processes in a way that promotes energy utilization efficiency. This is critical for ensuring an environmentally benign growth process. This study presents a unique addition to the body of existing knowledge by analysing the effect of some indicators of energy efficiency on three indicators of environmental quality among the top five emitters of GHG in Africa. The data were from the World Development Indicators (WDI), covering the 1990–2020 periods for South Africa, Egypt, Nigeria, Algeria, and Libya. The panel Autoregressive Distributed Lag (ARDL) model was used for data analysis. The results showed that all the included series were stationary at first difference. The optimum lag lengths were determined independently in STATA 17 software, and the most frequent lags across the countries were selected. The Hausman test revealed that the pooled mean group (PMG) estimation was preferred to other estimators. The results showed that in the long-run, particulate emission damages, CO2 intensity, and energy use intensity positively impacted GHG emissions, while GDP per capita and renewable energy utilization produced mixed results. In the short run, the error correction mechanism parameters were all significant (p < 0.01) in Libya for all emission indicators, while Algeria showed significance (p < 0.01) in total GHG and CO2 per capita models. The coefficient of particulate emission damages significantly reduced (p < 0.01) total GHG emissions in Libya and Nigeria and renewable energy significantly increased (p < 0.01) GHG emissions in South Africa but reduced them in Nigeria. Also, CO2 emission intensity significantly (p < 0.01) and positively impacted GHG emissions in South Africa, Egypt, Libya, and Nigeria, while electricity power transmission losses increased total emissions and CO2 emissions in Libya and Algeria. It was concluded that initiatives to reduce GHG emissions should focus on developing countries’ sensitivity to emission damages, and promotion of initiatives for using renewable energies. Also, promotion of energy efficiency across industries offers a prospect for ensuring environmental sustainability.

Low-emission hydrogen production from gasification of Australian coals – Process simulation and technoeconomic assessment

Although renewable energy-based technologies such as water electrolysis and biomass gasification for hydrogen production are cleaner than fossil energy-based routes, there are still prevailing challenges associated with the high cost and operational challenges in the scale-up of those technologies in the short term. Considering the abundance of coal as a current primary source of energy in Australia, the use of coal to produce hydrogen is not only in line with Australia's resource endowment but is also expected to become a supplement to the other hydrogen production pathways during the global energy transition period. This paper presents a comprehensive techno-economic assessment of low-emission hydrogen production from Australian coal gasification integrated with carbon capture and storage (CCS). The study explores four cases of hydrogen production, comparing Australian brown coal (Victorian brown coal) and black coal (Queensland black coal) gasification. Variations in gasifiers, gasification agents, and associated operating conditions contribute to differences in energy efficiency, costs, and CO2 emissions among the cases. The findings reveal a levelized cost of hydrogen from coal gasification ranging between A$4.12–4.90 per kg of hydrogen. Notably, entrained flow gasification of Victorian brown coal in a mixture of oxygen and steam environment demonstrates advantages under the current market conditions. However, less mature technologies like dual fluidized bed gasifiers could emerge as viable alternatives if deployed on a commercial scale. The study also addresses direct carbon emissions from the process, indicating a CO2 emission intensity range of 16.3–20.9 kg CO2/kg H2 without CCS and 0.1–1.1 kg CO2/kg H2 with CCS for the four cases. These insights contribute valuable information for decision-making in the pursuit of sustainable and economically feasible hydrogen production methods during the ongoing energy transition.

Dynamic correlation between surface carbon response and underlying emissions from spontaneous combustion goaf: field study of an abandoned coal mine

Abandoned coal mine goaf is affected by air leakages and prone to spontaneous combustion, resulting in environmental pollution and geological disasters. Haizhou Open-pit Mine adopts both underground and open-pit mining methods. During the long-term mining process, the original stable stratum structure is constantly destroyed, and the slope slides, increasing cracks and severe air leakage around the goaf and roadway. The spontaneous combustion of coal is particularly prominent after the mine shut down. At present, there is no suitable indirect monitoring method to effectively explore the spontaneous combustion area in goaf. The study developed an all-weather monitoring plan and conducted multi-point continuous long-term measurements of the spontaneous combustion state in one abandoned coal mine goaf located in the eastern part of the Haizhou Open-pit Mine. We evaluated the dynamic correlation between surface CO2 flux (SCF) and changes in the underground fire areas, determined the scope and evolution trend of the fire areas, and identified the distribution and change laws of SCF. The results show a significant positive correlation between SCF and soil temperature; moreover, the SCF value was found to reflect the CO2 emission intensity of the goaf. The high SCF in the test area showed month-wise expansion and increase, while the CO2 emission gradually increased monthly, and the calculated annual total emission was approximately 7017 t. Hence, the study can further provide guidance for the monitoring of spontaneous combustion in shallow coal seams, goaf and the assessment of CO2 emissions from underground coal fires through the on-site monitoring and analysis results.

Renewable energy and CO2 emissions in developing and developed nations: a panel estimate approach

Emerging economies and ecosystems are critically dependent on fossil fuels, and a country’s energy dependence is a significant measure of its reliance on foreign suppliers. This study evaluates the impact of energy reliance on energy intensity, CO2 emission intensity, and the utilization of renewable resources in 35 developing and 20 developed nations, as well as the connection between renewable energy (REN), GDP growth, and CO2 emissions. This study employs the generalized linear model (GLM) and the robust least squares (RLS) method to assess the inverse association between renewable energy and developed and developing economy policymakers, utilizing unique linear panel estimate approaches (1970–2022). The impact of renewable energy as a response variable on economic growth, energy consumption, and CO2 emissions across four continents is investigated in this study. The findings indicate that developing countries experience a rise in per capita CO2 emissions if their renewable energy use exceeds their capacity. This finding remains significant even when other proxies for renewable energy use are introduced using modified approaches. Furthermore, it is particularly relevant to industrialized nations that possess more developed institutions. Even more surprisingly, in terms of the energy and emission intensity required for growth, energy dependence has accelerated all components. The regional analysis revealed a spillover impact in most areas, suggesting that the consequences of energy dependence are essentially the same in neighboring countries. The growth of the renewable energy sector and the decrease in greenhouse gas emissions depend critically on the ability of regional energy exchange unions to mitigate the negative environmental and economic impacts of energy dependency. These underdeveloped countries need to spend more on research and development to catch up technologically.

Strategizing CO2 emission commitments in mainland China by integrating the experiences of primary energy consumption structures from the European assemblage and the USA in 1971–2021

To fulfill CO2 emission commitments becomes strategic to meet energy demands of sustainable economic growth via adjusting primary energy consumption structure. This study analyzed energy efficiency and CO2 emission intensity in the top three world economies in the period 1971–2021 and attempted to optimize structure of primary energy consumption for the CO2 emission commitments in mainland China, reaching peak emission by 2030 and neutrality by 2060. Results indicated that the USA and the European 16 – countries had significant higher energy efficiency and lower CO2 emission intensity than mainland China (α = 0.05). Reducing coal consumption is an efficient measure to reduce CO2 emission from fossil energy in the structure. However, renewable energies are crucial for achieving CO2 emission neutrality. As predicted, mainland China might peak CO2 emission by 2030 at 14.7 × 109 ton CO2 with 278 × 1018 J of total primary energy consumption, and would neutralize CO2 emissions by 2060 from 184 × 1018 J of primary fossil energy in the consumption structure in 2030 with renewable energies, hydropower, and nuclear as planned. Findings of this study provide a practical strategy for fulfilling CO2 emission commitments in mainland China and might be applicable to the developing world.

Renewable Adoption, Energy Reliance, and CO2 Emissions: A Comparison of Developed and Developing Economies

Emerging economies and ecosystems rely heavily on fossil fuels, and a country’s energy dependence is a strong indicator of its reliance on foreign suppliers. This study investigates the impact of energy dependence on energy intensity, CO2 emission intensity, and the exploitation of renewable resources in 35 developing and 20 developed nations. It also explores the correlation between renewable energy, GDP growth, and CO2 emissions. This study utilizes the Generalized Linear Model (GLM) and the Robust Least Squares (RLS) method to investigate the negative correlation between renewable energy and policymakers in established and emerging economies. It also employs distinctive linear panel estimation techniques spanning from 1970 to 2022. This study examines the impact of renewable energy on economic growth, energy consumption, and CO2 emissions across four continents. Developing countries see an increase in per capita CO2 emissions when their utilization of renewable energy exceeds their capacity. Even with the introduction of several proxies for renewable energy use using changed techniques, this discovery remains valid. Moreover, this is particularly crucial for industrialized nations with well-established institutions. Energy dependency has increased the energy and carbon intensity needed for expansion across all components, which is surprising. The regional study discovered a spillover impact in most regions, indicating that the consequences of energy reliance are similar in neighboring countries. Regional energy exchange unions play a vital role in reducing the adverse environmental and economic impacts of energy dependence, which is essential for the growth of the renewable energy sector and the decrease in greenhouse gas emissions. Undeveloped countries need to enhance their investment in research and development to advance technologically.

Evolution and driving factors of inequality in CO2 emissions from agricultural energy consumption in China

The inequality in CO2 emissions from agricultural energy consumption is a major challenge for coordinating low-carbon agricultural development across regions in China. However, the evolutionary characteristics and driving factors of inequality in China’s agricultural energy-related CO2 emissions are poorly understood. In response, the Kaya–Theil model was adopted to examine the three potential factors influencing CO2 emission inequality in China’s agricultural energy consumption. The results revealed that, from 1997 to 2021, agricultural energy-related CO2 emissions per capita showed a significant upward trend, with prominent polarization and right-tailing phenomena. Overall, the inequality was on a downward trend, with the Theil index falling from 0.4109 in 1997 to 0.1957 in 2021. Meanwhile, the decomposition of the national inequality revealed that the within-group inequality declined from 0.3991 to 0.1634, which was greater than between-group inequality, based on zoning the 28 provinces into three grain production functional areas. As for the three kaya factors, the energy intensity contributed the most to the overall inequality, followed by the agricultural economic development and CO2 emission intensity. Based on these results, this study provided some potential strategies to reduce agricultural-related CO2 emissions.

Green technology innovations, natural gas and resource extraction strategies in BRICS: Modeling impacts on CO2 emission intensity

The article extends beyond conventional models and indicators by initially attempting to capture the complex effects of green technological innovations and changes in natural resource extraction and natural gas production on a novel environmental quality indicator (CO, intensity, CO2ei) for the BRICS countries from 1990 to 2020. The empirical analysis for the candidate panel was conducted using robust analytical techniques, including the fully modified OLS (FMOLS), dynamic OLS (DOLS), canonical correlation regression (CCR), and seemingly unrelated regression (SUR). The results corroborated the role of green technological innovations as an effective deterrent against increasing levels of CO2ei. Still, the outcomes suggested that changes in natural gas production and natural resource extraction had escalated CO2ei in the candidate panel. The country-wise analysis reflected significant variance among the candidate panel countries. For instance. the model revealed that natural gas production abated CO2ei in China and India only, while its environmental effects remained adverse in the remaining countries. Per estimations, the unrequited extraction of natural resources facilitated the reduction of CO2ei in Brazil and Russia, but it also raised CO2ei in the rest of the BRICS countries. In addition, the causality estimation highlighted the following causal flows: i) the feedback effect from natural gas production to CO2ei; ii) one-way causality from CO2ei to green technological innovations and from natural resources extraction to CO2ei. The study offers novel and actionable policy recommendations for policymakers and theorists to steer sustainable and environmentally conscious initiatives in the BRICS countries.

Foreign demand shocks and CO2 emission intensity: firm-level evidence from China

ABSTRACT Constrained by data availability and challenges in causality identification, the relationship between trade and the environment remains theoretically ambiguous. This paper constructs a novel Chinese manufacturing firms’ CO2 emission intensity dataset by converting different types of firms’ energy consumption. Using disaggregated transaction data and the Shift-Share design, this paper exploits the effects of foreign demand shocks on firms’ CO2 emission intensity from 2007 to 2014. We document that a 10% increase in foreign demand leads to a 0.28% reduction in firms’ CO2 emission intensity. We find that multi-product exporters can benefit more from foreign demand shocks, and further prove the absence of CO2 leakage due to the EU ETS. This paper demonstrates that firms can be beneficiaries of foreign demand shocks, unmasking the trade-environment nexus by providing micro evidence from the largest developing country.

Wind energy resource assessment and wind turbine selection analysis for sustainable energy production

The objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub height set at 80 m. Wind power potential was assessed using the Weibull analysis. The values of the scale coefficient c were determined, and a large monthly variation was observed, with values ranging from 1.92 to 8.36 m/s and an annual value of 4.95 m/s. Monthly values for the shape coefficient k varied between 0.86 and 1.53, with an annual value of 1.07. Additionally, the capacity factor of the turbines was determined, ranging from 17.75 to 22.22%. The Vestas turbine, with a nominal power of 2 MW and a capacity factor of 22.22%, proved to be the most efficient wind turbine for the specific conditions of the location. The quantity of greenhouse gas emissions that will be reduced if this type of turbine is implemented was also calculated, considering the average CO2 emission intensity factor (kg CO2/kWh) of the national electricity system.

A comparison of deflation methods for carbon footprint calculations using Japanese data

An embodied CO2 emissions intensity database estimated from input–output data at current prices is now available in Japan. This study compares two non-survey methods: The double-deflation (DD) method and an elaborated approach combining the DD method with the generalized RAS method to deflate an input–output table (IOT). We used these methods to estimate new datasets of embodied CO2 emission intensity data in Japan, utilizing Japan's IOTs for 2005, 2011, and 2015 at constant prices in 2015. Furthermore, we compare the estimated data of 367 commodity sectors for a specific year (2005 or 2011). The results reveal that the intensity for certain aggregated sector groups, such as non-ferrous metals and finance and insurance, exhibits higher uncertainty owing to the extreme price homogeneity assumption associated with the DD method. Consequently, we recommend that life-cycle-assessment practitioners use an open database when analyzing changes in the carbon footprint of products over time.

Transfer payments and carbon reduction in China: The effect of the national comprehensive demonstration city of energy saving and emission reduction fiscal policy

To address climate change and achieve high-quality economic development, China began implementing the Comprehensive Demonstration City of Energy Saving and Emission Reduction Fiscal Policy (ESERFP) in 2011. This policy relies on special transfer payments to increase the integration of various energy conservation and emission reduction fiscal policies, thereby accelerating institutional and mechanism innovation, actively promoting economic structure adjustment and development mode transformation, and achieving energy conservation and emission reduction goals in various regions. This study uses a multi-period difference-in-difference (DID) model to estimate the ESERFP's CO2 emission reduction effect and paths. The findings demonstrate the following: (1) The ESERFP has lessened the CO2 emission intensity of the demonstration city and effectively played a role in reducing CO2 emissions. (2) Mechanism analysis demonstrates that the ESERFP has significantly improved the green travel level of residents in pilot cities and can also reduce cities' total energy consumption. Therefore, the ESERFP can effectively suppress CO2 emissions by improving transportation systems and optimizing energy consumption structures. (3) Further analysis shows that the ESERFP can reduce the CO2 emission scale of the demonstration cities and effectively promote the increase of actual per capita gross domestic product in pilot cities, bringing economic dividends and thus achieving a “win-win” situation of environmental protection and economic growth. (4) Heterogeneity analysis demonstrates that the CO2 emission reduction effect is more significant in non-old industrial-based cities, non-resource-based cities, and urban agglomerations. This study not only evaluates the CO2 reduction effect of the demonstration city but also provides reference significance for the improvement of subsequent environmental regulations. In addition, clarifying the implementation effect of the ESERFP can help alleviate ecological and environmental problems in the process of urban economic development in China and achieve the sustainable development goal of green transformation.

Coal consumption and carbon emission reductions in BRICS countries.

The primary energy consumption structure of BRICS countries is dominated by fossil energy, particularly coal. Coal consumption in BRICS countries is a major driver underlying increased carbon emissions. Therefore, this study developed a spatiotemporal decoupling mode and incorporated factors related to coal consumption-induced carbon emissions into a spatiotemporal decoupling analysis method to provide differentiated and targeted policies for energy restructuring and emission reduction targets in BRICS countries. Moreover, a temporal-spatial decomposition logarithmic mean Divisia index model was developed using the spatiotemporal decoupling index method. The model is based on CO2 emissions generated by coal consumption in BRICS countries, with a primary focus on data from Brazil, Russia, South Africa, India, and China. The findings reveal distinct spatiotemporal distributions and driving effects of coal consumption and carbon dioxide emissions across various countries. Factors such as CO2 emission intensity, coal consumption intensity, economic output per capita, and population structure exerted either positive or negative effects on the distributional effect of the carbon emission-economic output per capita association in BRICS countries. Additionally, country-level heterogeneity in the influence of the distributional effects of CO2 emissions was observed within each BRICS country. Thus, different policies are needed to achieve carbon emission reduction targets in different countries.