Search Results (41)

Household appliances constitute the second largest source of residential energy consumption in China, accounting for over 20% of the total and exhibiting a steady growth trend. Despite their substantial impact on energy demand and carbon emissions, a comprehensive analysis of the current status and future trends of household appliances in China is still lacking. This study employs the Long-Range Energy Alternatives Planning (LEAP) system to model energy consumption and carbon emissions for five major household appliances (air conditioners, refrigerators, washing machines, TVs, and water heaters) from 2022 to 2052. Three scenarios were analyzed: a Reference (REF) scenario (current trends), an Existing Policy Option (EPO) scenario (current energy-saving measures), and a Further Strengthening (FUR) scenario (enhanced efficiency measures). Key results show that by 2052, the EPO scenario achieves cumulative savings of 1074.8 billion kWh and reduces emissions by 580.7 million metric tons of CO₂ equivalent compared to REF. The FUR scenario yields substantially greater benefits, demonstrating the significant potential of strengthened policies. This analysis underscores the critical role of improving appliance energy efficiency and provides vital insights for policymakers and stakeholders aiming to reduce residential sector emissions. Full article

To achieve carbon neutrality targets in the power sector, regions with rich coal and renewable energy resources are facing unprecedented pressure. This paper explores the decarbonization pathway in the power sector in Inner Mongolia, China, under different energy transition scenarios based on the Long-Range Energy Alternatives Planning System (LEAP) model. This includes renewable energy expansion, carbon capture and storage (CCS) applications, demand response, and economic regulation scenarios. Subsequently, a combination of the Logarithmic Mean Divisia Index (LMDI) and Slack-Based Measure Data Envelopment Analysis (SBM-DEA) model was developed to investigate the influencing factors and power generation efficiency in low-carbon electricity. The results revealed that this region emphasizes first developing renewable energy and improving the carbon and green electricity market and then accelerating CCS technology. Its carbon emissions are among the lowest, at about 77.29 million tons, but the cost could reach CNY 229.8 billion in 2060. We also found that the influencing factors of carbon productivity, low-carbon electricity structures, and carbon emissions significantly affected low-carbon electricity generation; their cumulative contribution rate is 367–588%, 155–399%, and −189–−737%, respectively. Regarding low-carbon electricity efficiency, the demand response scenario is the lowest at about 0.71; other scenarios show similar efficiency values. This value could be improved by optimizing the energy consumption structure and the installed capacity configuration. Full article

Rapid urbanization in China is intensifying travel demand while making transport the nation’s third-largest source of carbon emissions. Anticipating continued growth in private-car fleets, this study integrates vehicle-stock forecasting with multi-scenario emission modeling to identify effective decarbonization pathways for Chinese cities. First, Kendall rank and grey relational analyses are combined to screen the key drivers of car ownership, creating a concise input set for prediction. A Lévy-flight-enhanced Sparrow Search Algorithm (LSSA) is then used to optimize the smoothing factor of the Generalized Regression Neural Network (GRNN), producing the Levy flight-improved Sparrow Search Algorithm optimized Generalized Regression Neural Network (LSSA-GRNN) model for annual fleet projections. Second, a three-tier scenario framework—Baseline, Moderate Low-Carbon, and Enhanced Low-Carbon—is constructed in the Long-range Energy Alternatives Planning System (LEAP) platform. Using Ningbo as a case study, the LSSA-GRNN outperforms both the benchmark Sparrow Search Algorithm optimized Generalized Regression Neural Network (SSA-GRNN) and the conventional GRNN across all accuracy metrics. Results indicate that Ningbo’s car fleet will keep expanding to 2030, albeit at a slowing rate. Relative to 2022 levels, the Enhanced Low-Carbon scenario delivers the largest emission reduction, driven primarily by accelerated electrification, whereas public transport optimization exhibits a slower cumulative effect. The methodological framework offers a transferable tool for cities seeking to link fleet dynamics with emission scenarios and to design robust low-carbon transport policies. Full article

Facing the intensifying global climate change pressures and China’s strategic commitment to carbon peaking and carbon neutrality, this study focuses on the multiple challenges faced by the Sichuan-Chongqing region, the economic core of southwest China, in optimizing its energy structure, controlling carbon emissions, and exploring sustainable development pathways. The study uses the LEAP (Long-range Energy Alternatives Planning) model to simulate energy demand and carbon emission trends under different policies and innovative technologies by constructing various scenarios. By conducting a comparative analysis of the LEAP model’s projection results under four scenarios (baseline scenario, alleviative scenario, low-carbon scenario, and high-efficiency low-carbon scenario), this study quantifies the energy demand and carbon emission pathways in the Sichuan-Chongqing region. The results show that optimizing the energy structure and improving energy efficiency are key to achieving carbon neutrality in the Sichuan-Chongqing region. Under the high-efficiency low-carbon scenario, the region is expected to reach peak energy consumption by 2050 and achieve a significant reduction in carbon emissions by 2060, with emissions dropping to 58.1% of the total emissions in 2050 and falling below 25% of the base year’s emissions. The industry sector is expected to account for 77.6% of total emissions. This study highlights the positive impact of widespread clean energy adoption on carbon reduction and demonstrates the importance of industrial restructuring and low-carbon technological innovation, among other green technologies, in promoting economic and environmental sustainability. Furthermore, by quantitatively analyzing carbon emission pathways under different scenarios, the study provides quantitative support and policy references for Sichuan-Chongqing and other regions to implement more scientific emission reduction measures and carbon neutrality pathway planning. The findings contribute to advancing regional collaborative governance, enhancing the scientific rigor of policy implementation, and fostering global climate governance cooperation, ultimately contributing to the coordinated and sustainable development of the ecological environment, economy, and society, embodying the “Sichuan-Chongqing efforts”. Full article

The study quantifies the benefits of expanding electric cooking in the residential sector in replacement of liquefied petroleum gas (LPG), including economic savings and the avoided emissions resulting from this transition, viewed through the perspective of a long-range optimal energy system model developed for the Ecuadorian energy system under the LEAP (Long-range Energy Alternative Planning) framework. In Ecuador, electricity generation is predominantly based on hydropower obtained from run-of-the-river schemes. The model results indicate that a sectorial-level policy to promote electric cooking reduces the use of LPG per annum, which consequently leads to reductions in greenhouse gas emissions. Additionally, the electric cooking scenario also complements the Ecuadorian vision of reducing deforestation and reaching carbon neutrality. Furthermore, the subsidies to LPG will be reduced, improving energy sovereignty. Finally, the paper discusses the effects and implications of this policy implementation over the nationally determined contributions (NDC). Full article

Short-lived climate pollutants (SLCPs) and municipal solid wastes (MSWs) have been found to be viable sources of clean energy. This study integrates the Intergovernmental Panel on Climate Change (IPCC) guidelines for methane flow rate estimation in the software Long-Range Energy Alternatives Planning-Integrated Benefit Calculator (LEAP-IBC) system to estimate and project the methane emissions coming from the waste generated by Metro Manila, disposed in sanitary landfills. It aims to analyze the environmental impacts of the emissions coming from the non-energy sector using the IBC feature of LEAP and by developing two scenarios with 2010 and 2050 as the base and end years: the baseline and methane recovery scenario, where the latter represents the solid waste management undertaken to counter the emissions. Under the baseline, 97.30 million metric tonnes of methane emissions are expected to be produced and are predicted to continuously increase. In the same scenario, the cities of Quezon, Manila, and Caloocan account for the biggest methane emissions. On the other hand, in the methane recovery scenario, the methane emissions are expected to have a decline of 36% from 127.036 to 81.303 million metric tonnes by 2025, 52% from 135.358 to 64.972 million metric tonnes by 2030, and 54% from 150.554 to 69.254 million metric tonnes by 2040. For the 40-year projection of the study under the 100-year global warming potential analysis, a total of 10,249 million metric tonnes of CO₂ equivalent is avoided in the methane recovery compared to the BAU, and a maximum of 0.019 °C temperature increase can also be avoided. Moreover, electricity costs without LFG technology increase from 2.21 trillion to 8.75 trillion, while costs with LFG technology also rise but remain consistently lower, ranging from 2.20 trillion to 8.74 trillion. This consistent reduction in electricity costs underscores the long-term value and importance of adopting LFG technology, even as its relative savings impact diminishes over time. Finally, the fixed effects and random effects panel data regression analysis reinforces and asserts that the solid waste management is really improved by means of the methane recovery technology, leading the methane emissions to decrease. Full article

The present study aims to describe the potential sources of energy in Peru with the purpose of implementing them to achieve a sustainable system, taking advantage of the natural resources in the Peruvian land. To achieve this, three alternative scenarios have been defined and analyzed using the LEAP (Long-range Energy Alternatives Planning) software [Software Version: 2020.1.112]. The scenarios are as follows: the first one, the Business-as-Usual scenario, is based on normal trends according to historical data and referencing projections made by Peruvian state entities; the second one is focused on Energy Efficiency, the highlighted characteristic is taking into consideration the efficient conditions in transmission and distribution of electric energy; and the third one, centered on Geothermal Energy, focused on the development of this type of energy source and prioritizing it. The primary purpose of this analysis is to identify the advantages and disadvantages inherent in each scenario in order to obtain the best out of each one. In this way, the intention is to propose solutions based on Peru’s national reality or possible uses of the country’s energy potential to supply its energy demand. Currently, Peru’s energy demand relies on fossil fuels, hydraulic, and thermal energy. However, there is the possibility of transforming this system into a sustainable one by strengthening existing and growing energy sources such as solar and wind energy and new technologies for hydraulic and thermal energy, in addition to considering geothermal energy as the main energy source in the third scenario. The new system mentioned satisfactorily indicates that the CO₂ equivalent emissions decrease significantly in the third scenario, with a 15.8% reduction compared to the first scenario and a 9.7% reduction in comparison to the second. On the other hand, the second scenario shows a 5.6% decrease in CO₂ emissions compared to the first, resulting from improvements in technology and energy efficiency without requiring significant modifications or considerable investments, as in the third scenario. Full article

Decomposition analysis and forecasting of carbon emissions in manufacturing are crucial for setting sustainable carbon-reduction targets. Given the varied carbon-emission efficiencies across sectors, this study applied the Logarithmic Mean Divisia Index (LMDI) decomposition method to analyze the drivers of carbon emissions in Gansu’s manufacturing sector, encompassing high, medium, and low-efficiency industries, and it identified vital factors affecting carbon emissions. A localized Long-range Energy Alternatives Planning System (LEAP) model for Gansu was also developed. This model includes six developmental scenarios to project future carbon emissions. The study results are as follows: (1) LMDI decomposition indicates that increased carbon emissions in the manufacturing industry primarily result from economic growth in less efficient sectors and the dominance of moderately efficient ones. (2) Under Optimization Scenario 6, a 50.82 × 10⁴ ton reduction in carbon emissions is projected for Gansu’s manufacturing sector by 2030 compared to 2020, marking the carbon peak. These outcomes provide valuable insights for policy reforms in Gansu’s manufacturing industry, aiming for carbon peaking by 2030. Full article

Coordinating and controlling carbon and atmospheric pollutant emissions in industrial cities poses challenges, making it difficult to formulate effective environmental governance strategies in China. This study used the Community Multiscale Air Quality (CMAQ) and Long-range Energy Alternatives Planning (LEAP) models, with a typical industrial city in the Sichuan Basin as the case study. Five emission reduction scenarios, one integration scenario, and one baseline scenario were set to quantitatively analyze the synergistic effect between carbon emissions and atmospheric pollutant emissions. The results indicate a high synergy between sulfur dioxide and greenhouse gases. For every one-point decrease in the Air Quality Composite Index (AQCI), the Industrial Restructuring Scenario (IR), Other Source Management Scenario (OSM), Transportation Energy Efficiency Improvement Scenario (TEEI), Industrial Energy Efficiency Improvement Scenario (IEEI), and Transportation Restructuring (TR) scenarios would require a reduction in carbon emissions by 56,492.79 kilotons, 39,850.45 kilotons, 34,027.5 kilotons, 22,356.58 kilotons, and 3243.33 kilotons, respectively. The results indicate that governance measures, such as improving transportation structure and upgrading industrial technologies, provide stronger support for simultaneous carbon emissions reductions and air quality improvement. Full article

Global climate change imposes significant challenges on the ecological environment and human sustainability. Industrial parks, in line with the national climate change mitigation strategy, are key targets for low-carbon revolution within the industrial sector. To predict the carbon emission of industrial parks and formulate the strategic path of emission reduction, this paper amalgamates the benefits of the “top-down” and “bottom-up” prediction methodologies, incorporating the logarithmic mean divisia index (LMDI) decomposition method and long-range energy alternatives planning (LEAP) model, and integrates the Tapio decoupling theory to predict the carbon emissions of an industrial park cluster of an economic development zone in Yancheng from 2020 to 2035 under baseline (BAS) and low-carbon scenarios (LC1, LC2, and LC3). The findings suggest that, in comparison to the BAS scenario, the carbon emissions in the LC1, LC2, and LC3 scenarios decreased by 30.4%, 38.4%, and 46.2%, respectively, with LC3 being the most suitable pathway for the park’s development. Finally, the paper explores carbon emission sources, and analyzes emission reduction potential and optimization measures of the energy structure, thus providing a reference for the formulation of emission reduction strategies for industrial parks. Full article

As important nodes in the air transport system, it is of great significance for airports to achieve the carbon-peaking goal before 2030 under the target of peaking carbon emissions in China’s civil aviation industry. However, it remains unknown whether airports will be able to realize this ambitious goal due to a variety of uncertain factors, such as the social economy, epidemic impact, and emission reduction measures. According to the possibilities of uncertain factors, 12 uncertain scenarios were constructed. Using the case of Guangzhou Baiyun International Airport (CAN), this study predicted medium- and long-term carbon emission trends under 12 uncertain scenarios based on the Long-range Energy Alternatives Planning System (LEAP) model. Furthermore, the effects of carbon abatement measures and emission reduction responsibilities were analyzed. The results show that CAN cannot guarantee that it will realize the goal under the established abatement policy. If socioeconomic development is rapid, carbon emissions will peak at about 90 kt tons in 2030, and if socioeconomic development is slow, it will plateau at about 1 million tons between 2030 and 2035. What is more, airlines bear the greatest responsibility for reducing emissions, and technological progress measures have the highest abatement potential. This study provides decision support for airport stakeholders in abatement work so as to ensure that airports can achieve the carbon-peaking goal. Full article

Sierra Leone is suffering from a persistent electricity gap that has crippled its economic growth and prevented it from attaining several health and education development goals. This persistent electricity gap has generated significant interest in tackling the country’s long-lasting energy deficiency. Providing electricity in a reliable, sustainable, and cost-effective manner in Sierra Leone requires adopting robust integrated energy planning and appropriate technologies. Despite various interventions by the government, a balance between electricity demand and supply has yet to be achieved. Using the Long-range Energy Alternatives Planning System (LEAP), this work assesses Sierra Leone’s energy supply and demand for 2019–2040. We developed three case scenarios (Base, Middle, and High) based on forecasted demand, resource potential, techno-economic parameters, and CO₂ emissions. The Base case considers the electricity sector as business as usual, the Middle case examines the electricity sector reform roadmap and the prospect of integrating renewable energy into the power system, and the High case examines the sustainable development of the power generation system considering the electricity sector roadmap. As part of this study, we analyze potential alternatives to conventional electricity generation systems aimed at providing electricity in a sustainable, reliable, and affordable manner, including the use of renewable energy sources and technologies with less CO₂ emissions. Model results estimate an increase in electricity demand of 1812.5 GWh, 1936 GWh, and 2635.8 GWh for Base, Middle, and High cases respectively. Also, there is a reduction in production, fuel cost, and CO₂ emission in the High case to the Base case by 67.15%, 35.79%, and 51.8%, respectively. This paper concludes with recommendations devised from the study results for the power system of Sierra Leone. Full article

As a designated national low-carbon pilot city, Nanjing faces the challenge of reducing energy consumption and carbon emissions while experiencing rapid economic growth. This study developed a localized Long-range Energy Alternatives Planning System (LEAP) model specifically for Nanjing and constructed four different development scenarios. By utilizing the Log Mean Divisia Index (LMDI) decomposition, the Tapio decoupling elasticity coefficient, and comparing the emission reduction effects of individual measures and their cross-elasticity of carbon reduction, this study investigated the key factors and their carbon reduction path characteristics in Nanjing toward its carbon peak target by 2030. The results indicate that: (i) Nanjing could reach its peak carbon target of about 3.48 million tons by 2025 if carbon reduction measures are strengthened; (ii) The main elements influencing Nanjing’s carbon peak include controlling industrial energy consumption, restructuring the industry, promoting the construction of a new power system, and developing green transportation; (iii) Controlling industrial energy consumption and changing industrial structure have a greater impact on reducing carbon emissions than other measures, and both have a synergistic effect. Therefore, Nanjing should prioritize these two strategies as the most effective methods to reduce carbon emissions. Additionally, to slow down the growth of urban carbon emissions, policies aimed at reducing the energy intensity and carbon intensity of energy consumption should be formulated. For instance, the integration and innovation of green industries within the city region, such as new energy vehicles, new energy materials, and big data, should be accelerated, and the proportion of clean energy consumption in urban areas should be increased. The LEAP (Nanjing) model has successfully explored Nanjing’s low-carbon pathway and provided policy guidance for the optimal transformation of industrial cities and early carbon peaking. Full article

Petroleum has become a strategic resource to the national economy, and forecasting its demand is a critical step to supporting energy planning and policy-making for carbon reduction. We first conducted a characteristic analysis of end consumption for petroleum products, and the key affecting factors are identified through an extended logarithmic mean Divisia index (LMDI) method. Afterwards, the long-range energy alternatives planning system (LEAP) was adopted to predict the petroleum products demand by considering the potential impacts of different policies on the identified key factors. Through comparative analysis of three scenarios including five sub-scenarios, the findings show that the dual carbon constraints are crucial to petroleum demand control. Under the enforcement of existing carbon peaking policies, the petroleum products demand will peak around 2043 at 731.5 million tons, and the impact of energy intensity-related policies is more significant than that of activity level. However, even if the existing policy efforts are continued, supporting the carbon-neutral target will not be easy. By further strengthening the constraints, the demand will peak around 2027 at 680 million tons, and the abatement contribution will come mainly from industry (manufacturing), construction, and transportation. Additional abatement technologies are necessary for the petroleum industry to achieve carbon neutrality. Full article

In recent years, the world’s environmental problems have become increasingly serious, and energy transition and carbon emission issues have gradually gained attention from various countries. China has promulgated several policies and adopted various reform measures to achieve a comprehensive energy transition and carbon neutrality as soon as possible. Therefore, this study makes researches and forecasts the energy transition and carbon emissions in China under the dual carbon target. A LEAP (Long range Energy Alternatives Planning) model is developed to analyze the energy parameters of Beijing under various scenarios and to provide a quantitative analysis basis for the energy transition path. The obtained experimental results indicate that the energy demand under the partial energy transition scenario and full energy transition scenarios are 68.651 million tons of standard coal and 75.759 million tons of standard coal, respectively, forming an effective control, while the carbon emissions both achieve the carbon peak in 2025 at 81.903 million tons and 80.624 million tons respectively, and achieve 46.588 million tons in 2060. The carbon-neutral pathway reaches the carbon peak in 2025, and approaches full energy transition in 2035, and finally reaches the full energy transition control effect in 2060. To date, most of the relevant studies have been conducted in a qualitative way, and the amount of quantitative analysis is insufficient. At the same time, research on the development path specifically at the city level is relatively insufficient as well. Therefore, the present study can provide a theoretical basis for specifying the promotion method of urban energy transformation and the path of carbon emission reduction. Full article