CO₂ Emission Reduction Concepts and Zero-to-Low Carbon Technologies

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

As the global third-largest stationary source of carbon emissions, petroleum refineries have attracted much attention. Many investigations and methodologies have been used for the quantification of carbon emissions of refineries at the industry or enterprise scale. The granularity of current carbon emissions data impairs the reliability of precise mitigation, so analysis and identification of influencing factors for carbon emissions at a more micro-level, such as unit level, is essential. In this paper, four typical units, including fluid catalytic cracking, Continuous Catalytic Reforming, delayed coking, and hydrogen production, were chosen as objects. A typical 5-million-ton scale Chinese petroleum refinery was selected as an investigating object. The Redundancy analysis and multiple regression analysis were utilized to explore the relationship between the process parameters and carbon emissions. Three types of influencing factors include reaction conditions, processing scale, and materials property. The most important mitigation of carbon emission, in this case, can be summarized as measures of improving energy efficiency via optimizing equipment parameters or prompting mass efficiency by upgrading the scale for material and energy flow. 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

Lightweight design is a common approach to reduce energy demand in the use stage of vehicles. The production of lightweight materials is usually associated with an increase in energy demand, so the environmental impacts of lightweight structures need to be assessed holistically using a life cycle assessment. To estimate the life cycle environmental impacts of a product in its developmental stage, for example, by life cycle engineering, future changes in relevant influencing factors must be considered. Prospective life cycle assessment provides methods for integrating future scenarios into life cycle assessment studies. However, approaches for integrating prospective life cycle assessment into product development are limited. The objective of this work is to provide the methodological foundation for integrating future scenarios of relevant influencing factors in the development of lightweight structures. The applicability of the novel methodology is demonstrated by a case study of a structural component in a steel, aluminium, and hybrid design. The results show that appropriate decarbonisation measures can reduce the life cycle greenhouse gas emissions by up to 95 percent until 2050. We also found that shifts in the environmentally optimal design are possible in future scenarios. Therefore, the methodology and data provided contribute to improved decision-making in product development. Full article

Transforming the transport sector to zero emission is an integral part of changes to the energy sector worldwide. This effects not only the electrification of the private sector but also the commercial sector. The aim of this study is to develop methodologies, algorithms and associated requirements for the integration of electric vehicles into a logistics application with a possible reduction in operating costs. The most favorable solution for a company was evaluated using the analytic hierarchy process algorithm considering three main aspects: economic, environmental and technical. An analysis of the environmental impact of the vehicle fleet in terms of atmospheric emissions was also conducted, based on the data available for combustion and electric vehicles, considering the well-to-tank approach. The costs associated with operating an electric vehicle were identified and compared to the current costs associated with operating a standard diesel-based fleet. Incorporating the identified costs of electrifying the vehicle fleet, an algorithm was implemented to reduce the number of vehicles in the company and, thereby, significantly reducing the costs associated with fleet maintenance. Full article

University campuses represent a heterogeneous ecosystem as to social, economic, energetic, and personal travel planning with a huge impact on hosting cities and territories. Sustainable policies are thus fundamental to reduce this impact and to adopt ecological behaviors. The measures for any University Sustainability Plan should be evaluated in terms of GHG emissions, as well as the overall impact of the university itself. Carbon footprint (CF) calculation is a relevant Decision Support tool that allows university organizations to measure and communicate the environmental effects of their activities. The aim of this paper is to present a carbon footprint methodology specifically designed to calculate the carbon footprint of large universities. The methodology was applied to calculate the CF of the University of Bologna by following international standards—i.e., the GHG protocol, the ISO 14064, and the ISO/TR 14069 guide—to understand the environmental impact caused by greenhouse gas emissions from direct and indirect university activities. The study was conducted upon the data available in 2020 and then was compared to the 2018 data, with the aim to recognize if the effect of the pandemic could have altered the results. In 2020, the University of Bologna emitted 16,467 tCO₂e which became 15,753 tCO₂e considering the offset and avoided emission provided by the internal production of energy from renewable sources. Comparison between 2020 and 2018 shows how, in 2018, most of the emissions came from transportation, representing 74% of the total emissions, while in 2020 almost 50% of total emissions derived by IT procurements. The case application demonstrates the way with which the methodology may be applied to assess environmental impact for complex university campuses. Full article

This paper proposes decarbonization pathways for Thailand based on a review of the status of renewable and fossil energies, technology evaluation and scenario studies. Results show that renewable electricity generation needs to grow at a 7.1% average annual growth rate (AAGR) between now and 2050 for the power sector to achieve net-zero by 2050. This would require it to reach 400 TWh, exceeding its technical potential. We propose a more achievable scenario of between 5% and 6% AAGR wherein renewable electricity will grow from 51 TWh to 217–291 TWh between 2020 and 2050. Gas-powered electricity will grow from 127 TWh to 185–111 TWh, requiring carbon capture and storage (CCS) to mitigate 75–45 Mtpa CO₂ by 2050. For the transport sector, electric vehicles have the highest decarbonization potential, but they would add 45 TWh of electricity demand by 2050. For the industry sector, installing CCS in existing plants has the highest decarbonization potential. Overall, CCS is a key decarbonization technology and its large-scale implementation will be needed for Thailand to achieve net-zero by 2050. Full article

Climatic changes and environmental pollution caused by traditional urban development models have increased due to accelerated urbanisation and industrialisation. As a new model of urban development, smart city construction relies on digital technology reform to achieve intelligent urban governance, which is crucial for reducing carbon emission intensity and achieving regional green development. This paper constructs a multi-period DID model based on panel data from 283 cities from 2007 to 2019 to explore the impact of smart city construction on urban carbon emission intensity. This study found that smart city construction decreased urban carbon emissions intensity significantly and decreased carbon emissions per unit GDP in pilot areas by 0.1987 tonnes/10,000 CNY compared to that in non-pilot areas. According to a heterogeneity analysis, the integration of smart city developments could decrease carbon emission intensity in northern China’s cities and resource-based cities significantly but had an insignificant influence on carbon emission intensity in southern China’s cities and non-resource-based cities. The reason for this finding is that northern cities and resource-based cities have a higher carbon emission intensity and enjoy more marginal benefits from smart city construction. Based on an analysis of the influencing mechanisms, smart city construction can decrease urban carbon emission intensity by stimulating green innovation vitality, upgrading industrial structures, and decreasing energy consumption. These research conclusions can provide directions for urban transformation and low-carbon development, as well as a case study and experience for countries that have not yet established smart city construction. Full article