From intention to action: Modeling student lifestyle carbon emissions and reduction scenarios

Background and objective: Carbon neutrality must be achieved across societal sectors through carbon neutral policies. Therefore, local governments, which realize the actual greenhouse gas (GHG) reduction, must develop GHG reduction strategies. This study aims to present information on the GHG reduction of the building sector (BS) at the local government level, for the carbon neutrality by 2050 (CN).Methods: The gross floor area (GFA) of all buildings and the total floor area of household (HBs), business (BBs), and public buildings (PBs) and by 2050 were predicted using building and demographic information from Jeollanam-do. Buildings were classified as over or under 10 years old. GHG emissions projection by 2050 were combined the GFA prediction results with public information on building energy consumption (BEC). After adjusting the nationwide CN goal for the BS in Jeollanam-do, the pathways for two scenarios were to estimate GHG reduction.Results: HBs showed the steepest increase in GFA, while BBs and PBs showed a very modest increase. About 30% of HBs and BBs were under 10 years and about 70% were over 10 years. The HB's GHG emissions increased remarkably, reflecting the GFA results, while the emissions of BBs and PBs didn't raised much. GHG reduction targets by 2030 were calculated as 1.4, 0.7, and 0.35 million TOE for HBs, BBs, and PBs, respectively. Reduction Scenario 1 shows a straight-line path with a negative slope from 2023. Reduction Scenario 2 shows an increase in emissions after 2023, which begins to decrease from 2028, falling with a curved steep slope until 2035, followed by a very modest decline until 2050.Conclusion: This study calculated GHG emissions from the BS by 2050 using the latest information on BEC and GHG calculation guidelines. The method in this study helps establish regional/local GHG reduction targets, setting scenarios, and estimating GHG reduction.

Long-term CO 2 emissions reduction target and scenarios of power sector in Taiwan

Grey forecasting the impact of population and GDP on the carbon emission in a Chinese region

How to deal with carbon emissions—a rare externality that spans a large time frame and geographical scope—is a difficult task for the world. This task is particularly challenging for China, mainly in that the country must coordinate dual objectives, including existing economic growth targets and the newly added carbon neutrality goal. Over the past 40 years of reform and opening up, China has been setting economic growth targets and striving to achieve them. In recent years, although growth targets have softened along with the secular decline in potential growth rate, economic growth remains a top priority for China, the world’s largest developing country. We expect China to reach the current standard for a high-income country by the end of the 14th Five-Year Plan period, and to double its GDP or per capita income by 2035. Currently, China is adding a new constraint over the next 40 years. As the world’s largest carbon emitter, China has set out a clear timetable for carbon neutrality—to reduce its carbon emission intensity in 2030 by more than 65% from the 2005 level, and reach the peak of carbon dioxide emissions by 2030 and become carbon neutral by 2060. We note that it will take 71 and 45 years, respectively, for the EU and the US to achieve the carbon neutrality goal from peak carbon emissions (reached by the EU in 1979 and by the US in 2005) to net zero emissions. China’s aggressive timetable to achieve carbon neutrality within 40 years means that the country will face a much steeper slope of carbon emissions than the EU and the US. How will China strike a balance between the objectives of economic growth in the past 40 years and carbon neutrality in the next 40 years? We discuss this issue from an aggregate and a structural point of view. In our aggregate analysis, the most important task is to identify the peak of China’s carbon emissions in 2030. We believe that in order to take economic growth and emission reduction into consideration, it is more appropriate to set the carbon peak target in a range to avoid rigid constraints. From a structural perspective, we discuss how China can achieve its carbon peak and neutrality goals. Under the framework of a “green premium”, we come up with a preliminary idea of “technology + carbon pricing” based on the analysis of eight high-emission industries. We prove that this idea can strike a balance between the constraints of economic growth and carbon neutrality goals through general equilibrium analysis using the computable general equilibrium (CGE) model. Finally, we incorporate social governance into our analysis by discussing the meaning of a negative green premium, and arrive at this formula: the road to carbon neutrality = technology + carbon pricing + social governance.

Global climate change, marked by persistent warming trends, has emerged as one of the foremost challenges confronting human society in the 21st century. Systematically promoting carbon peak and neutrality has become a critical priority for governments in China. As the most active urbanization region in the country, metropolitan areas assume a pivotal leadership and exemplary role in executing carbon peak and neutrality initiatives. Consequently, we focus our research on the Chang-Zhu-Tan Metropolitan Area (CMA). The STIRPAT and CA-Markov models are employed to forecast carbon sinks and carbon emissions under various scenarios in 2030 and 2060, respectively, to explore pathways to carbon neutrality under various conditions. The findings indicate that the carbon surplus and deficit (CSD) values have consistently been negative from 2000 to 2020, signifying a persistent carbon deficit in the region, which has exhibited an upward trend. Notably, the CSD in Yuelu, Ningxiang, and Changsha experienced the most significant increases, particularly in Yuelu, where it reached - 11.22 × 106 t by 2020. Depending on the combinations of scenarios, the CSD values are anticipated to range from - 130.75 × 106 t to - 98.22 × 106 t in 2030, and from - 63.28 × 106 t to - 21.22 × 106 t in 2060. Furthermore, the carbon emissions under different scenarios are projected to reach peaks in 2030, with a maximum of 66.54 × 106 t in 2060. The prediction results of carbon neutrality in the CMA indicate that carbon emission is expected to reach peaks before 2030 across various scenarios. However, carbon emissions will significantly exceed the carbon sink capacity by 2060, and there is still a carbon emission gap of at least 2122.44 × 104 t from achieving carbon neutrality, highlighting the necessity of accelerating emission reduction in the industrial and energy sectors. Consequently, the critical challenge to achieve carbon neutrality lies in the substantial reduction of carbon emissions.

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

Purpose There is a close relationship between carbon emission and climate change, and the climate issue is a common concern for all countries today. Global warming affects the ecological environment and even human health. In this paper, the non-equal order spatial disturbance grey forecasting model is established to predict the temperature difference of European Union countries under different carbon emission scenarios. Design/methodology/approach The non-equal order spatial disturbance grey forecasting model is established to predict the temperature difference of European Union countries under different carbon emission scenarios. Findings The results show that the temperature difference in most European Union countries is on the rise under the carbon increase scenario. Under the scenario of carbon reduction, European Union countries show a rise, fall or flat state. But overall, the temperature difference in most countries under the carbon increase scenario is greater than that under the carbon reduction scenario. This suggests that reducing carbon dioxide emissions is beneficial to narrow the temperature difference and mitigate climate change to a certain extent. Originality/value The research conclusions are conducive to providing scientific guidance for the formulation of carbon reduction and emission reduction policies and contributing to the achievement of climate goals.

China's low-carbon industrial transformation assessment based on Logarithmic Mean Divisia Index model

In China, manufacturing is the industry that consumes the most energy and emits the most carbon, and the effect of emission reduction on the process of reaching carbon peaking and carbon neutrality is decisive. The existing research on the driving factors of manufacturing carbon emissions has not analyzed the specific structural characteristics of manufacturing carbon emissions from the perspective of industrial relevance, and little attention has been paid to the discussion of carbon emission reduction paths of different manufacturing sectors from the perspective of final demand. This study examines the direct carbon emissions and carbon emissions from final demand in China's manufacturing sector, and decomposes the carbon emissions from final demand into six distinct components using input-output analysis. In addition, this study examines the carbon emission path in manufacturing production activities, as well as the carbon emission reduction potential and scenario prediction of the factors influencing manufacturing carbon emissions. In 2018, the direct carbon emissions and carbon emissions from final demand were approximately 4.61 billion tons and 3.50 billion tons, respectively. Meanwhile, direct and indirect spillovers accounted for 62.1% and 23.1% of carbon emissions from final demand, respectively. Using the carbon emission transfer route map of the manufacturing industry, the direction and amount of carbon emission transfer from various energy sources can be accurately determined. The CR scenario predicts that the manufacturing industry will reach its carbon peak between 2025 and 2030, with a corresponding peak between 4.02 and 4.06 billion tons, and that carbon emissions in 2060 will be 40% lower than in 2018.

Synergistic assessment of environmental pollutants and carbon emissions in the Yellow River Basin, China: An integrated study based on scenario simulation and process decomposition

Will China achieve its 2060 carbon neutral commitment from the provincial perspective?

With emphasis on constructing low-carbon cities, the renovation of the riverbank highlights energy conservation and carbon reduction. However, methods and standards for quantifying carbon emissions during ecological river channel construction are currently lacking. There is a scientific gap in research into carbon footprint assessment and reduction potential in ecological revetment technologies in water networks of China. This study attempts to clarify the carbon emission factors of different ecological revetment technologies and explore the carbon reduction potential during the construction stage of ecological rivers from the river revetment design, construction process and materials. The results show that in the carbon emission factors of six ecological revetment technologies, building materials have the largest adjusting potential for carbon reduction. The concrete material is responsible for 55.37–95.86% of carbon emissions in six ecological river technologies, with an average proportion of 69.96%. Accordingly, the concrete material emerges as the primary contributor to carbon emissions in ecological river engineering, followed by gasoline truck transportation and earthwork excavation. Moreover, the carbon emissions from ecological frame structures were the largest, followed by those of block structures, gabion structures, planted concrete and interlocking blocks and the wooden stake structure has the smallest carbon footprint. The choice of ecological revetment technologies is not only related to the realisation of regional water conservancy functions, but it also affects the carbon emissions of water conservancy projects. Engineers and decision-makers should pay great attention to the optimal design of the project, selection of low-carbon materials, energy saving and emission reduction in the construction process. This research not only provides guidance for design units in selecting appropriate river revetment technologies but also offers a theoretical foundation and data support for construction units to optimise their construction process management.

Based on the double-carbon target, the agricultural sector has implemented the concept of being green and synergistically promoted pollution and carbon reduction. Positioned as a novel financial paradigm, green finance places greater emphasis on environmental stewardship compared to its traditional counterparts. This focus enhances resource allocation efficiency, thereby achieving the goal of reducing pollution and carbon emissions. To research the influence of green finance on agricultural pollution and carbon reduction, this study leverages panel data spanning 2011 to 2021 from 31 provinces, autonomous regions, and municipalities across China. It employs the fixed-effect model and mediating-effect model. The findings reveal that: (1) Green finance exerts a notable influence on reducing both pollution and carbon emissions in agriculture, with the latter showing a more pronounced effect. (2) Regional disparities exist in green finance, affecting agricultural pollution and carbon reduction. (3) By fostering technological innovation and optimizing industrial frameworks, green finance emerges as a catalyst for curbing surface pollution and carbon dioxide emissions in agriculture. On this basis, relevant suggestions are put forward to provide policy insights for improving the green financial system, which will help further promote carbon and pollution reduction.

Development of bottom-up model to estimate dynamic carbon emission for city-scale buildings

Carbon peaking and carbon neutrality will be important policies to constrain China's economic and social development in the future. Based on the theory of computable general equilibrium, CGE model of carbon emission was constructed in this paper to simulate the influence of different scenarios of carbon emission reduction on economic and social development. The major contribution is to subdivide the energy sector according to primary energy and secondary energy, and construct the macro SAM table and micro SAM table of 21 energy sectors in 2017 to quantitatively simulate the impact of carbon emission reduction policies on China's economy and society, and put forward some policy suggestions based on this.