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Environmental pollution caused by energy consumption is a global problem. Optimization of the energy system will contribute to the sustainable development of city, especially of the industrial cities. Based on the Long-term Energy Alternative Planning System (LEAP) model, the LEAP-Suzhou model was established to explore the energy system optimization and emission reduction path of Suzhou to 2050. By accounting for current energy consumption and carbon emissions, the baseline scenario (BAU) was established. According to the different methods and intensities of energy transformation, an industrial structure optimization scenario (ISO), an energy structure optimization scenario (ESO), and an energy transformation optimization scenario (ETD) were created. Combined with the energy flow diagram, the energy structure and the direction of optimization were analyzed. The results showed that the baseline scenario will consume 259.954 million tons of standard coal by 2050, and the carbon emission will be 677.6 Mt. Compared with BAU, the ISO, ESO, and ETD scenarios will reduce energy consumption by 37.9%, 37.4%, and 74.8%, respectively, by 2050. ETD had the best carbon dioxide reduction, followed by ESO, and finally ISO. Among them, the carbon emission of ETD will reach its peak around 2030 and decrease to 73.8 Mt in 2050, resulting in the best emission reduction effect. This scenario is the best path for Suzhou to achieve the goal of “carbon peak and neutrality” and sustainable development. The LEAP-Suzhou model successfully explores the low carbon path of Suzhou, provides policy guidance for the optimization of energy transition and carbon neutrality of industrial cities, In the future, the energy structure should be further optimized in Suzhou, and advanced energy technologies should be introduced to improve energy efficiency, especially for the power generation sector, and the proportion of clean energy such as gas should be further expanded.

Abstract This study analyzes the local energy planning (LEP), a set of urban energy strategies and potential scope, for São Paulo from 2014 to 2030. A simulation model is used to quantify the impacts of implementing LEP strategies on the city’s energy system based on three indicators: energy demand, percentage usage of renewable sources, and greenhouse gas (GHG) emissions. The performance of LEP strategies was analyzed for two scenarios: the first reproduces the city policies in force, and the second expands the population’s access to city energy services. Considering the implementation of LEP in the first scenario, the city exhibits a 65% usage of renewable energy and a 43% reduction in GHG emissions in 2030. Furthermore, implementation of the same strategies in the second scenario, also for 2030, results in a 67% usage of renewable energy with a 24% reduction in emissions compared to 2014. Resumo Este artigo analisa o potencial do Planejamento Energético Local (PEL), conjunto de estratégias de energia no âmbito urbano, na cidade de São Paulo (período 2014 - 2030), através de modelo de simulação para quantificar os impactos da implementação destas estratégias no sistema energético da cidade segundo três indicadores: demanda de energia, % de uso de fontes renováveis e emissões de gases de efeito estufa (GEE). O desempenho das estratégias de PEL foi analisado segundo dois cenários: o primeiro reproduz as políticas vigentes na cidade e o segundo amplia o acesso da população aos serviços de energia. Considerando a implementação de PEL no primeiro cenário, a cidade alcançará, em 2030, 65% de energia renovável e redução de 43% das emissões de GEE. Se as mesmas estratégias forem implementadas no segundo cenário, 67% da participação de energia renovável será alcançada com uma redução de 24% nas emissões quando comparadas a 2014. Resumen Este artículo analiza el potencial del Planeamiento Energético Local (PEL), en las megalópolis de São Paulo (período 2014 - 2030), a través de un modelo de simulación para cuantificar los impactos de la implementación de PEL en el sistema energético de São Paulo de acuerdo con tres indicadores: demanda de energía, % de uso de fuentes renovables y emisiones de gases de efecto invernadero (GEI). Se analizó el desempeño de las estrategias del PEL según dos escenarios: el primero reproduce las políticas vigentes y el segundo aumenta el acceso de la población a los servicios energéticos. Considerando la implementación del PEL en el primer escenario, la ciudad alcanzará en 2030, 65% de energía renovable y 43% de reducción de GEI. Si se aplican las mismas estrategias en el segundo escenario, se logrará 67% renovable con una reducción del 24% de las emisiones en comparación con 2014.

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.

Systematically predicting carbon emissions in the building sector is crucial for formulating effective policies and plans. However, the timing and potential peak emissions from urban buildings remain unclear. This research integrates socio-economic, urban planning, building technology, and energy consumption factors to develop a LEAP-SD model using Shenzhen as a case study. The model considers the interrelationship between socio-economic development and energy consumption, providing more realistic scenario simulations to predict changes in carbon emissions within the urban building sector. The study investigates potential emission peaks and peak times of buildings under different population and building area development scenarios. The results indicate that achieving carbon peaking by 2030 is challenging under a business as usual (BAU) scenario. However, a 10% greater reduction in energy intensity compared to BAU could result in peaking around 2030. The simulation analysis highlights the significant impact of factors such as population growth rate, per capita residential building area, and energy consumption per unit building area and the need for a comprehensive analysis. It provides more realistic scenario simulations that not only enhance theories and models for predicting carbon emissions but also offer valuable insights for policymakers in establishing effective reduction targets and strategies.

Japan has lagged behind other developed nations in transitioning its transportation sector to sustainable energy sources. This study employs the Low Emissions Analysis Platform model to examine six scenarios, assessing energy consumption and emissions associated with four major energy sources and pollutants. Our findings reveal an overall decline in total energy consumption across all scenarios. Notably, the Combined scenario where multiple policies are integrated demonstrates the most significant reduction, with a 56% decrease compared to the Business as usual scenario by 2050. The analysis also indicates that the electricity and hydrogen demand for electric vehicles and fuel cell vehicles remains economically viable within future strategic plans. Emissions, including CO 2 , Carbon Monoxide (CO), Methane (CH 4 ), and Nitrous Oxide (N 2 O), exhibit substantial reductions, particularly under the Active Promotion Scenario, where a high EV adoption rate is achieved. Moreover, the Combined scenario resulting in a comprehensive and integrated approach, leads to a remarkable 66% decrease in emissions. These results serve as valuable reference points for the Japanese government, aiding in the formulation of future targets for widespread EV adoption and emission standards for pollutants.

Based on the emission factor method and LMDI-LEAP model, this paper systematically studies the current situation, influencing factors and changing trend of carbon emissions from rural buildings in a typical village located in southern China. The results showed that (1) the per capita carbon emissions generated by the energy consumption of rural buildings is 2.58 tCO2/a. Carbon emissions from electricity consumption in buildings account for about 96.07%; (2) the per capita building area, building area energy intensity, population size, population structure and carbon emission coefficient affect rural building carbon emissions, with contribution rates of 70.13%, 31.27%, 0.61%, −1.21% and −0.80%, respectively; (3) from 2021 to 2060, the carbon emissions of rural buildings are expected to increase first and then decrease. In 2021, the base year, carbon emissions from buildings were 2755.49 tCO2. The carbon emissions will peak at 5275.5 tCO2. Measures such as controlling the scale of buildings and improving the utilization rate of clean energy can effectively reduce carbon emissions, in which case the peak can be reduced to 4830.06 tCO2. Finally, the countermeasures and suggestions about rural building energy saving and emission reduction are proposed, including improving the construction management, raising energy efficiency standards in buildings, increasing the proportion of clean energy and raising residents’ awareness of energy conservation.

In this paper, the Long-range Energy Alternatives Planning (LEAP) model is constructed to simulate six scenarios for forecasting national electricity demand in China. The results show that in 2020 the total electricity demand will reach 6407.9~7491.0 billion KWh, and will be 6779.9~10,313.5 billion KWh in 2030. Moreover, under the assumption of power production just meeting the social demand and considering the changes in the scale and technical structure of power industry, this paper simulates two scenarios to estimate carbon emissions and carbon intensity till 2030, with 2012 as the baseline year. The results indicate that the emissions intervals are 4074.16~4692.52 million tCO2 in 2020 and 3948.43~5812.28 million tCO2 in 2030, respectively. Carbon intensity is 0.63~0.64 kg CO2/KWh in 2020 and 0.56~0.58 kg CO2/KWh in 2030. In order to accelerate carbon reduction, the future work should focus on making a more stringent criterion on the intensity of industrial power consumption and expanding the proportion of power generation using clean energy, large capacity, and high efficiency units.

In this study, the water-energy nexus is investigated throughout coupling the Water Evaluation and Planning (WEAP) and Low Emission Analysis Platform (LEAP) models under the climate change effects in the Marun basin, Iran. For this purpose, first, the climate change effects on water resources and consumption nodes are calculated under representative concentration pathway (RCP) scenarios from the fifth report of the International Panel on Climate Change (IPCC). Artificial neural network (ANN) is used to model river inflow and Cropwat model is used for agricultural water demand in future time (2015–2040). In the next step, water system is modeled in WEAP and energy system is modeled in LEAP. Then, three water-energy nexus scenarios include (1) calculating the actual hydropower generation capacity in LEAP model (W-E-N1), (2) water-energy nexus evaluation indexes in the WEAP model (W-E-N2), and (3) changes in the electricity consumption intensity in the LEAP model (W-E-N3) are modeled under RCP 2.6, RCP 4.5 and RCP 8.5 climate scenarios. The results of W-E-N1 scenario show that the actual hydropower generation capacity with water-energy nexus is reduced by 78%, 89%, and 91%, respectively, compared to no water-energy nexus under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios. The results of W-E-N2 show that the hydropower generation reliability index will be reduced by 19%, 31%, and 13%, respectively under RCP 2.6, RCP 4.5, and RCP 8.5 compared no water-energy nexus. The results of W-E-N3 scenario show that the electricity consumption intensity will increase considering the electricity required for water transferring to demand sites. The results of the present study show that the water-energy nexus will lead to more accurate results and, as a result, more realistic planning for water and energy resources.

To identify the emission reduction potential and policy synergies of Tokyo’s road passenger and urban road freight transport under the “carbon neutrality target,” this paper constructs an assessment framework for megacities. First, based on macroeconomic socioeconomic variables (population, GDP, road length, and employment), regression equations are used to predict traffic turnover for different modes of transport from 2021 to 2050. Then, the prediction results are imported into the LEAP (Long-range Energy Alternatives Planning) model. By adjusting three policy levers—vehicle technology substitution (ZEV: EV/FCEV), energy intensity improvement, and upstream electricity and hydrogen supply decarbonization—a “single-factor vs. multi-factor (policy synergy)” scenario matrix is designed for comparison. The results show that the emission reduction potential of a single measure is limited; upstream decarbonization yields the greatest independent emission reduction effect, while the emission reduction effect of deploying zero-emission vehicles and improving energy efficiency alone is small. In the most ambitious composite scenario, emissions will decrease by approximately 83% by 2050 compared to the baseline scenario, with cumulative emissions decreasing by over 35%. Emissions from rail and taxis will approach zero, while buses and freight will remain the primary residual sources. This indicates that achieving net zero emissions in the transportation sector requires not only accelerated ZEV penetration but also the simultaneous decarbonization of electricity and hydrogen, as well as policy timing design oriented towards fleet replacement cycles. The integrated modeling and scenario analysis presented in this paper provide quantifiable evidence for the formulation of a medium- to long-term emissions reduction roadmap and the optimization of policy mix in Tokyo’s transportation sector.

China has grown into the world’s largest tourist source market and its huge tourism activities and resulting greenhouse gas (GHG) emissions are particularly becoming a concern in the context of global climate warming. To depict the trajectory of carbon emissions, a long-range energy alternatives planning system (LEAP)-Tourist model, consisting of two scenarios and four sub-scenarios, was established for observing and predicting tourism greenhouse gas peaks in China from 2017 to 2040. The results indicate that GHG emissions will peak at 1048.01 million-ton CO2 equivalent (Mt CO2e) in 2033 under the integrated (INT) scenario. Compared with the business as usual (BAU) scenario, INT will save energy by 24.21% in 2040 and reduce energy intensity from 0.4979 tons of CO2 equivalent/104 yuan (TCO2e/104 yuan) to 0.3761 Tce/104 yuan. Although the INT scenario has achieved promising effects of energy saving and carbon reduction, the peak year 2033 in the tourist industry is still later than China’s expected peak year of 2030. This is due to the growth potential and moderate carbon control measures in the tourist industry. Thus, in order to keep the tourist industry in synchronization with China’s peak goals, more stringent measures are needed, e.g., the promotion of clean fuel shuttle buses, the encouragement of low carbon tours, the cancelation of disposable toiletries and the recycling of garbage resources. The results of this simulation study will help set GHG emission peak targets in the tourist industry and formulate a low carbon roadmap to guide carbon reduction actions in the field of GHG emissions with greater certainty.