LEAP Model Research Articles

Construction Path of "Zero Carbon" Power Plant Based on the LEAP Model

As the power industry is the primary carbon emission industry, the research on the construction path of "zero-carbon" power plants against the background of the "dual-carbon" goal must be strengthened. Considering a state-owned power generation enterprise as an example, based on the carbon emissions of the power plant in recent years, the LEAP model was constructed by combining its energy structure and geographical and climatic conditions and the baseline, energy structure adjustment, technological progress, and comprehensive scenarios were set up. The energy consumption demand under each scenario was analyzed and the future carbon emissions under each scenario were predicted. The results showed that in 2060, the total carbon emissions from the power generation sector under the technological progress and energy structure adjustment scenarios decrease by 54.55% and 75.97% compared with those in the baseline scenario, respectively, which demonstrated the large potential for carbon emission reduction from clean energy substitution and that the flexibility transformation of thermal power units and the upgrading and replacement of ultra-supercritical generating units could reduce coal consumption and decrease carbon emissions, whereas the development of CCUS technology was significant, and the construction of CCUS projects was a necessary condition for realizing carbon neutrality of power plants while retaining a certain scale of thermal power generation. Under a comprehensive scenario, "zero carbon" emissions from power plants could be realized around 2056. The results of the study provide ideas for the construction of "zero carbon" power plants.

Low-carbon Development Path of Ordos Based on LEAP Model

To determine the low-carbon development path of Ordos, three scenarios （baseline scenario, low carbon scenario, and enhanced low carbon scenario） were constructed based on the LEAP model to forecast the energy demand and carbon emission in Ordos from 2020 to 2050 and to analyze the contribution of various policy initiatives to reduce carbon emission. The results showed that under the enhanced low carbon scenario, the energy demand in Ordos peaked at 52 million tons of standard coal equivalent in 2025 and decreased to 40 million tons of standard coal equivalent in 2050, and carbon emissions peaked at 163 million tons in 2025 and decreased to 16 million tons in 2050, which was 88% lower than that in 2020. Regarding emission reduction contribution, comparing the baseline scenario and the enhanced low-carbon scenario, the increase in renewable energy power generation installation, the reduction in energy consumption of terminal energy use, and the increase in terminal electrification rate contributed to the emission reductions of 43%, 25%, and 24%, respectively. The Ordos should vigorously develop renewable energy and make full use of the rich endowment of wind and light resources； at the same time, it should promote economic transformation and gradually increase the proportion of high-value-added and low-energy-consuming industries in the industrial structure. For the power sector, the power generation structure should be adjusted. Traditional thermal power generation should be replaced by zero-carbon and low-carbon power generation technologies. For the industrial and transportation sectors, the terminal electrification rate should be increased, and the energy intensity should be reduced.

Simulation of hydrogen transportation development path and carbon emission reduction path based on LEAP model - A case study of Beijing-Tianjin-Hebei Region

Hydrogen-fuelled vehicles have attracted significant attention around the world recent years as the main form of hydrogen transportation. Chinese government in September 2020 has introduced corresponding supporting policies. In particular, Beijing-Tianjin-Hebei urban agglomeration is the first batch of pilot cities. To research the development of hydrogen transportation and carbon emission reduction paths in Beijing-Tianjin-Hebei urban agglomeration, we construct LEAP-Beijing-Tianjin-Hebei Urban Agglomeration Hydrogen Transportation model, and simulate it based on the scenario analysis method. The results show that the total hydrogen demand reaches 7,975,860 tonnes in the year 2060. And the freight transportation sector is the largest hydrogen consumer in transportation. For carbon emission reduction, transportation sector under different scenarios could achieve net-zero emission in year 2060, with total emission reduction 431.19 million metric tonnes. We suggest that the promotion of hydrogen transportation should be carried out in stages. Early large-scale development of hydrogen-fuelled vehicles in sectors such as passenger cars and specialized vehicles is not significant in emission reduction, and it is more appropriate to start with medium and large-sized commercial vehicles. Gradually extend to the whole transportation sector after the technology of hydrogen-fuelled vehicles is mature and the supply capacity of clean hydrogen is improved.

Prediction of hydrogen consumption scale and hydrogen price based on LEAP model and two-factor learning curve

Under the dual-carbon target, hydrogen energy, as a zero-carbon secondary energy source, has great scope for replacing fossil feedstocks in the fields of energy, transportation and industry. However, the current research on the competitiveness of hydrogen energy in various fields is not sufficiently addressed. In this paper, we use the LEAP model to predict the future scale of hydrogen use and the two-factor learning curve to predict the trend of hydrogen price change from 2025 to 2050, using Qinghai Province as the research background. At the same time, considering the carbon emission reduction benefits and raw material costs, the competitiveness of hydrogen energy in energy, transportation, industry and other fields in the future is compared. The results show that: 1) The hydrogen load scale in Qinghai Province will grow fast from 2025 to 2030. From 2030 to 2040, it slows under the steady and basic scenarios but remains high under the accelerated one. By 2040, the consumption scales are 1.057 million, 649,000 and 442,000 tons respectively. 2) The price of hydrogen energy will drop rapidly from the current 28 CNY/kg to about 20 CNY/kg in the next 5 years. By 2040, the price of hydrogen energy will be reduced to about 17 CNY/kg. 3) In terms of hydrogen energy competitiveness, when carbon emissions are not taken into account, hydrogen energy is currently competitive in the transportation field. During 2032–2038, it will be competitive in the field of methanol synthesis. By 2040, hydrogen energy will not be competitive in the fields of ammonia synthesis and power/heating. When considering carbon emissions, the competitiveness of hydrogen energy in the transportation field will become greater. The competitive year in the field of methanol synthesis will be 1–2 years ahead. By 2040, it will not be competitive in the field of synthetic ammonia and power/heating, but the gap will be significantly reduced due to the consideration of carbon emissions.

Environmental-economic analysis of regional energy system under different supply and demand side scenarios with LEAP model

Environmental-economic analysis of regional energy system under different supply and demand side scenarios with LEAP model

Decomposition Analysis of Carbon Emission Drivers and Peaking Pathways for Key Sectors under China’s Dual Carbon Goals: A Case Study of Jiangxi Province, China

Clarifying the factors influencing CO2 emissions and their peaking pathways in major sectors holds significant practical importance for achieving regional dual-carbon goals. This paper takes Jiangxi, a less developed demonstration zone in central China, as an example. It pioneeringly combines the LMDI method, Tapio decoupling model, and LEAP model to multi-dimensionally analyze the driving mechanisms, evolution patterns, and dynamic relationships with the economic development of carbon emissions in Jiangxi’s key sectors from 2007 to 2021. It also explores the future carbon emission trends and peaking potentials of various sectors under different scenarios. Our results show that (1) Carbon emissions in various sectors in Jiangxi have continued to grow over the past fifteen years, and although some sectors have seen a slowdown in emission growth, most still rely on traditional fossil fuels; (2) Economic growth and industrial structure effects are the main drivers of carbon emission increases, with a general trend towards decoupling achieved across sectors, while agriculture, forestry, animal husbandry and fishery, and ferrous metal smelting have shown a decline in their decoupling status; (3) In the carbon reduction and low-carbon scenarios, the carbon emission peaks in Jiangxi are estimated to be 227.5 Mt and 216.4 Mt, respectively, and targeted strategies for high-emission industries will facilitate a phased peak across sectors and enhance emissions reduction benefits. This has significant reference value for the central region and even globally in formulating differentiated, phased, sector-specific carbon peaking plans, and exploring pathways for high-quality economic development in tandem with ecological civilization construction.

Carbon emissions path of public buildings based on LEAP model in Changsha city (China)

China is currently the world's top carbon emitter due to the acceleration of urbanization, the rapid growth of energy consumption and the rise in carbon emissions, with the construction industry leading the three energy sectors in terms of emission reduction potential. Among the various sectors, the construction industry holds immense potential for emission reduction, with public buildings playing a crucial role. In China, the expansion of public building spaces is closely linked to the pace of urbanization and contributes to a rising share of total building area. Public buildings, characterized by high energy usage, offer a great opportunity for energy conservation and emission reduction. Changsha is experiencing rapid growth and change, and the city is becoming more industrialized and urbanized, which leads to a prominent contradiction between energy supply and demand. There is also great potential for energy conservation and emission reduction in public buildings. Additionally, Changsha is an important node city in the Yangtze River urban agglomeration and the middle reaches of the Yangtze River Economic Belt. It is a typical area that has hot summer and cold winter, thus Changsha is selected as the research case to examine the carbon emission path of public buildings. The primary influencing factors of carbon emissions of public buildings in Changsha City are determined by using the LMDI factor decomposition method addition model. The scenario analysis method is adopted to set the two energy consumption forecast scenarios, which are the baseline scenario and the green scenario. Based on LEAP model and GREAT framework structure, the LEAP prediction model is constructed to predict the carbon emissions of public buildings in Changsha City from 2021 to 2035. The Baseline scenario indicates that while carbon emissions from public buildings in Changsha continue to rise, they are expected to decline starting in 2030. The peak carbon emission of 34.279 million tons of CO2 is predicted for 2032. In contrast, the Green scenario reveals a significantly slower growth rate in carbon emissions from public buildings, with the peak carbon emission projected to reach 27.054 million tons in 2030. This aligns with China's national goal. The findings of this study support the accuracy of the long-term prediction of the model, and offer recommendations for energy conservation and emission reduction in Changsha. This study also provides an example and certain guidance for other provinces and cities that have similar development models and climate conditions. Pertinent development strategies serve as a point of reference for other typical hot summer and cold winter regions.

Pathway for China's provincial carbon emission peak: A case study of the Jiangsu Province

This study establishes the LEAP-Jiangsu model and uses the improved multilevel logarithmic mean Divisia index, Tapio decoupling, and synergistic effect models to explore the carbon reduction paths. The improved multilevel logarithmic mean Divisia index model analyzed the influencing factors of the historical and future carbon emissions. A provincial LEAP model was established to predict the time and value of carbon emission peaks. The Tapio decoupling and synergistic effect models were used to clarify the relationship between carbon emissions and economic development, the synergistic effect of carbon and pollutant reduction, and the terminal sector's carbon reduction potential. The results show that Jiangsu Province will most likely achieve carbon peaking in 2025∼2030, and the peak carbon emission is about 792∼853.9 Mt. Terminal energy intensity, power production structure, and terminal energy consumption structure are the main influencing factors of carbon reduction, with a cumulative contribution rate of about 74.4 %–83.5 %. The power production structure is critical in promoting the decoupling of economic development and carbon emissions. The contribution rates of energy intensity reduction, industrial structure optimization, improving terminal electrification level, and energy structure adjustment are 30.3 %, 26.2 %, 20.9 %, and 17 %, respectively. Coordinating carbon reduction measures will have better synergistic carbon and pollutant reduction effects.

A scenario analysis of the energy transition in Japan’s road transportation sector based on the LEAP model

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 CO2, Carbon Monoxide (CO), Methane (CH4), and Nitrous Oxide (N2O), 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.

LEAP model-based analysis to low-carbon transformation path in the power sector: a case study of Guangdong–Hong Kong–Macao Greater Bay Area

As a major carbon emitter, the power sector plays a crucial role in realizing the goal of carbon peaking and carbon neutrality. This study constructed a low-carbon power system based on the LEAP model (LEAP-GBA) with 2020 as a statistic base aiming of exploring the low-carbon transformation pathway of the power sector in the Guangdong–Hong Kong, and Macao Greater Bay Area (GBA). Five scenarios are set up to simulate the demand, power generation structure, carbon emissions, and power generation costs in the power sector under different scenarios. The results indicate that total electricity demand will peak after 2050, with 80% of it coming from industry, buildings and residential use. To achieve net-zero emissions from the power sector in the GBA, a future power generation mix dominated by nuclear and renewable energy generation and supplemented by fossil energy generation equipped with CCUS technologies. BECCS technology and nuclear power are the key to realize zero carbon emissions from the power sector in the GBA, so it should be the first to promote BECCS technology testing and commercial application, improve the deployment of nuclear power sites, and push forward the construction of nuclear power and technology improvement in the next 40 years.

Policy scenario analysis of achieving the "dual carbon" goal for the road transportation sector in China

The goal of "dual carbon" has brought the pressure of reducing carbon emissions to the road transportation sector in China. This study aims to identify and analyze possible policy measures that would help to achieve this goal from the perspective of the whole life cycle. We build a bottom-up computing framework based on the LEAP model. Six policy scenarios are designed to quantitatively assess their effects. The results show that promoting pure electric vehicles (PEV) and plug-in hybrid electric vehicles (PHEV) is appropriate for the passenger vehicles (PV), light-duty trucks (LDT), and mini trucks (MT) sub-sectors, while hydrogen fuel cell vehicles (FCV) are more suitable for the promotion of the heavy-duty trucks (HDT), heavy-duty buses (HDB), and medium-duty buses (MDB) sub-sectors. Additionally, the recycling of vehicle materials can effectively reduce the carbon emissions during the life cycle of motor vehicles. Furthermore, reducing the carbon emissions from the vehicle cycle of PV and the fuel cycle of HDT should be taken seriously. The main contribution of this study lies in establishing a comprehensive list of vehicle cycle carbon emission factors, covering various sub-sectors of China's road transportation sector. Besides, this study considers China's strategic planning and "dual carbon" goal, and proposes policy recommendations specifically tailored to the practical issues faced by China.

Transforming the transportation sector: Mitigating greenhouse gas emissions through electric vehicles (EVs) and exploring sustainable pathways

Transportation-related emissions in Pakistan have been rapidly increasing in recent years. This study aims to determine how important it is to electrify road transportation in Pakistan to reduce greenhouse gas (GHG) emissions from the transportation sector. Motivated by the need to tackle the growing environmental issues related to conventional fuel-powered automobiles, this research explores the application of electrification techniques in the context of Pakistan’s transportation system. During the 2019 fiscal year, the transportation industry in Pakistan consumed 23 × 106 tonnes of energy from the burning of fossil fuels and produced 52.9 × 106 metric tons of CO2, which made up 31% of the country’s total carbon emissions. In this research, different scenarios, such as business as usual, low carbon, strengthen low carbon, and Pakistan National Electric Vehicle Policy 2040, are evaluated for the transportation sector of the country. Using the LEAP model, this study projects the effects of electrification on Pakistan road transportation over 30 years. When estimating how electrification will affect road transportation in Pakistan over the next 30 years, several factors were taken into account, including policy frameworks, changing consumer behavior, technology advancements, and infrastructure improvements. The analysis covered the emission levels, adoption hurdles, and possible advantages of transitioning to electric vehicles (EVs). The outcomes illustrate that adopting EVs can produce substantial drops in fuel consumption and environmental emissions, providing a sustainable solution to mitigate global warming. This work is directly associated with various Sustainable Development Goals, including SDG3 (good health and well-being), SDG7 (affordable and clean energy), and SDG13 (climate action). The results of this study highlight the considerable potential for GHG reduction associated with the widespread adoption of EVs, offering crucial insights to stakeholders and policymakers.

Medium and Long-term Carbon Emission Projections and Emission Reduction Potential Analysis of the Lingang Special Area Based on the LEAP Model

Based on the existing statistical data of the Lingang Special Area in Shanghai and considering its future socio-economic development， industrial structure， and technological development， a LEAP-Lingang model was developed to analyze the evolution trends of energy demand and carbon emissions under the baseline scenario， low-carbon scenario， and enhanced low-carbon scenario. To enhance the prediction accuracy of the model， the Logistic population growth model was used to predict future population data， and the learning curve model was used to simulate the cost evolution trend of related carbon reduction technologies. In addition， an economic evaluation model for carbon reduction technologies was developed， and the economic costs and emission reduction potential of typical carbon reduction technologies were evaluated by drawing a marginal emission reduction cost curve. The results showed that under the enhanced low-carbon scenario， the renewable energy accounted for 69% of the primary energy consumption， and the electric energy accounted for 91% of the terminal energy demand in 2060. The Lingang Special Area could achieve carbon peak by 2030， and the carbon emissions in 2060 were predicted to decrease by 94% compared to that in the baseline scenario. In terms of contribution to emission reduction， clean energy substitution， industrial structure optimization， and terminal energy efficiency improvement played a key role in reducing carbon emissions near the port. In the medium term （until 2035）， they were predicted to contribute 35.1%， 27.3%， and 16.2% of carbon emissions， respectively， and in the long term （until 2060）， they should contribute 50.6%， 8.75%， and 7.7% of carbon emissions， respectively. Regarding specific carbon reduction technologies， hydrogen power generation； water electrolysis for hydrogen； and carbon capture， utilization， and storage （CCUS） technology were of great significance for achieving net-zero emissions， but the costs of emission reduction were relatively high. The research results can provide ideas and references for the low-carbon and green development of the Lingang Special Area and related areas.

Study of Peak Carbon Emission of a City in Yangtze River Delta Based on LEAP Model

Based on the LEAP model framework, a LEAP-X sub-sector calculation model suitable for X City was constructed in this study. Four scenarios including a baseline scenario, low-carbon scenario, enhanced low-carbon scenario, and peak in 2023 scenario were set up to predict and analyze the carbon emission situation. The calculation and analysis results showed that it could achieve the carbon peak before 2030 only under the enhanced low-carbon scenario and peak in 2023 scenario. The peak year of the enhanced low-carbon scenario was around 2025 with a peak carbon emission of approximately 170 million tons, but the peak time may actually be delayed. Industry was the largest sector of carbon emissions, and the petrochemical industry was the largest portion of industry, the proportion of which was always maintained at approximately 30% under different scenarios. However, the proportion of power generation and steel industry decreased annually, whereas the proportion of the net imported power gradually increased. Industrial structure optimization and energy structure adjustment were the main driving factors of carbon peak in X City. Carbon emissions per unit of GDP will fall by approximately 41% in 2030 compared with that in 2020 under the enhanced low-carbon scenario.

Medium- and Long-Term Prediction of Airport Carbon Emissions under Uncertain Conditions Based on the LEAP Model

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.

Exploring health care professionals' experiences and knowledge of woman-centred care in a university hospital.

Inspired by the six quality-of-care goals developed by the Institute of Medicine, woman-centred care (WCC) as model of care is used in maternity services as it gives an emphasis on the woman as an individual and not her status as a patient. Bringing stronger attention to women's needs and values, is proven to have clear benefits for perinatal outcomes, but fails to be known or recognised by healthcare professionals' (HCPs) and implemented. Using a mixed-methods approach, this study aimed to explore HCPs definitions of WCC and identify the degree of agreement and knowledge regarding perinatal indicators when a WCC model of care is implemented. The quantitative part was carried using a self-administered questionnaire with perinatal indicators identified from the literature. Semi-structured interviews were realized using a purposive sample of 15 HCPs and an interview grid inspired by Leap's WCC model. The study was conducted in the maternity of a university hospital in French-speaking part of Switzerland. Out of 318 HCPs working with mothers and their newborns, 51% had already heard of WCC without being familiar with Leap's model. The HCPs were aware of the positive perinatal care outcomes when WCC was implemented: women's satisfaction (99.2%), health promotion (97.6%), HCP's job satisfaction (93.2%) and positive feelings about their work (85.6%), which were strongly emphasised in the interviews. The respondents reported institutional difficulties in implementing the model such as administrative overload and lack of time. The positive outcomes of WCC on spontaneous deliveries and improved neonatal adaptation were known by most HCPs (63.4% and 59.9%, respectively). However, fewer than half of the HCPs highlighted the model's positive effects on analgesia and episiotomies or its financial benefits. Knowledge of quality-of-care outcomes (i.e women's satisfaction, positive impact on practice…) was prevalent among most of HCPs. Without adhering to a common definition and without a specific model for consensus, most providers have integrated some aspects of WCC into their practice. However, specific perinatal indicators remain largely unknown, which may hinder the implementation of WCC.

Long-term energy-environment-economic programming under carbon neutrality target: a study on China’s regional energy transition pathways and CO2 mitigation strategies

ABSTRACT Carbon neutrality is one of the key issues in mitigating global climate change. The carbon neutrality process accelerates the global energy transformation from fossil energy to renewable energy. Among the main indicators related to carbon neutrality proposed by the Chinese government, those directly related to energy include carbon emission intensity, the proportion of non-fossil energy consumption, and the total installed capacity of wind and solar power generation. It can be seen that the transformation of energy development is crucial for realizing carbon neutrality. Meanwhile, the correlation between carbon neutrality and economic development is not antagonistic. On the contrary, carbon neutrality can not only enhance the quality and efficiency of traditional industries but also improve the overall development of society. Therefore, the coordinated and sustainable developments of the energy - economy- environment (3E) system is the priority for achieving the target of carbon neutrality. However, the impact of carbon neutrality on regional development requires long-term consideration, which increases the difficulties of comprehensive planning. In this study, a long-term comprehensive programming model of regional energy and economic development under carbon peaking and carbon neutrality targets was established. A carbon neutrality assessment indicator (CNAI) framework was constructed to assess the effect of carbon neutrality actions in different regions. Meanwhile, a LEAP model was developed to simulate energy demand and carbon emissions. The multi-target weights determined by assessment results of CNAI and the parameters range set by LEAP model were the basis of the multi-objective optimization model to support regional development. Furthermore, the proposed method was applied to Shaanxi province in China, which offered quantitative targets and suggestions for energy structure transformation and industrial structure adjustment. The results show that coal and oil will account for 6.25% of the total energy consumption and the proportion of secondary industry will drop to 25.40% by 2060. The method established in this study provides a new scientific approach for resolving multi-objective trade-offs in long-term programming and determining a reasonable optimization range for regional development under climate mitigation policies.

Main Pathways of Carbon Reduction in Cities under the Target of Carbon Peaking: A Case Study of Nanjing, China

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.

Analysis on the Energy Demand, CO2 and Pollutant Emissions, and Health Benefits from Urban Road Transport Sector: A Case Study of Shenyang

As society develops and urbanization accelerates, energy requirement and environmental emissions in the road transport field have expanded in Shenyang, China. It is necessary to look at its future energy needs and environmental emission trends. In this work, we have used the LEAP model to account for the energy requirement and environmental emissions from 2017 to 2030 under five scenarios for the road transport sector in Shenyang. Additionally, the intake fraction approach was applied to estimate the health effects and financial damages of NOX, SO2, PM10, and PM2.5 emissions. The results indicate that the energy required in 2030 will reach 8.18~10.65 Mtce in various scenarios. By 2030, under the business as usual (BAU) scenario, the emissions of CO2, CO, SO2, NOX, PM10, and PM2.5 will be 31089.51, 1794.4, 20.59, 205.88, 6.6 and 6.5 kt, respectively. Regarding health benefits, financial damage caused by NOX, SO2, PM10, PM2.5 emissions will reach RMB 8.594, 0.117, 1.013, and 1.566 billion in 2030 under the BAU scenario. Moreover, the development of energy-efficient and new energy automobiles is the best means of reducing energy demand and environmental emissions; thus, this approach should be paid special attention when developing future energy efficiency and emission abatement policies for road transport.

China's oil and gas demand forecast and pipeline network layout optimization analysis

In order to accelerate the speed of pipeline network construction and expand the scale of oil and gas pipeline network, we need to forecast the total oil and gas demand and regional demand structure, so as to better serve the future construction of national oil and gas network. In this paper, the LEAP model is used to forecast the total oil and gas demand consumption and its regional distribution in 2050. The results show that in the low-carbon scenario, China's oil and gas will decrease in 2035, but still maintain a certain proportion. There are great differences in oil and gas demand among provinces. In the future, the layout of oil and gas pipeline network should consider the changes of demand structure and spatial layout, and comprehensively consider the transportation distance, transportation cost, transaction price and other factors of oil and gas pipeline network, so as to scientifically layout oil and gas transportation pipeline and optimize the flow of resources.