Study on Carbon Emission Characteristics and Emission Reduction Measures of Lime Production—A Case of Enterprise in the Yangtze River Basin

<sec><title>Objective</title> The world is still in a phase of rapid industrialization and urbanization. Excessive carbon emissions has become the primary root cause of various urban or even global environmental problems, further impacting human physiological and psychological health. Cities are the largest sources of carbon emissions and are crucial regions for achieving carbon neutrality goals. Urban blue-green infrastructure (UBGI), comprising natural, semi-natural, or artificial green and blue spaces within cities, is considered as the most important carbon sink space in urban areas and has increasingly attracted widespread attention from researchers. However, there are still many unresolved issues regarding the effectiveness of UBGI in carbon sink enhancement and emission reduction: 1) How is the energy efficiency of carbon sink enhancement and emission reduction measured, and what factors influence it? 2) What are the mechanisms and pathways through which UBGI enhances carbon sink and reduces carbon emission? 3) How can UBGI be regulated to better enhance its effectiveness in carbon sink enhancement and emission reduction? 4) What are the limitations and potential directions for future research? This research aims to address these issues and propose scientifically sound planning strategies for UBGI construction to achieve urban carbon neutrality goals. </sec><sec><title>Methods</title> Through literature synthesis and deduction, this research organizes and analyzes the multi-scale measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction, identifies corresponding influencing factors at each scale, and constructs multi-scale planning strategies for UBGI based on the logical framework of “measurement methods–influencing factors – planning strategies”. </sec><sec><title>Results</title> The research proposes UBGI planning strategies across three spatial scales (site, community and urban area), covering three key aspects: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. Based on current research gaps and planning needs, five major research topics are further identified. This research provides a detailed analysis of the measurement methods and influencing factors of UBGI’s efficiency in carbon sink enhancement and emission reduction from three perspectives: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. The research finds significant differences in the measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction efficiency across different scales. Contradictory results may occur at different scales, and large-scale research often lacks characterization of internal features, leading to unclear mechanisms of influencing factors and obstructing practical planning. Based on the interpretation of UBGI’s mechanisms for carbon sink enhancement and emission reduction at different scales, this research formulates UBGI planning strategies across three spatial scales (site, community, and urban area). These strategies include: 1) At the site scale, for carbon sequestration and sink enhancement – carbon sink at the source, land balance, and ecological design; for emission reduction – symbiosis with buildings and integration into daily life. 2) At the community scale, for carbon sequestration – overall balance of revenue and expenditure, precise positioning, and proper interconnection of the carbon chain; for emission reduction – incorporation of cool islands and co-construction. 3) At the urban area scale, for carbon sequestration – enhancement of ecological space management and establishment of a carbon-safe pattern; for emission reduction – demand-based layout and organic dispersion. Finally, the research proposes five major research topics for the planning of UBGI’s carbon sink enhancement and emission reduction: How to construct unified measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction across scales? How to measure UBGI’s efficiency in carbon reduction based on temperature reduction (or preservation) at the site scale? How to integrate the pathways of carbon sink enhancement and emission reduction for a life cycle assessment of UBGI? How to balance UBGI’s carbon sink enhancement and emission reduction with other functions to achieve the optimal layout for comprehensive benefits? How to achieve urban “carbon justice” through UBGI? </sec><sec><title>Conclusion</title> The carbon sink pathway of the strategy framework requires “carbon sink at the source – precise positioning – safe pattern”, and the emission reduction pathway requires “symbiotic integration – co-construction and sharing – organic dispersion”. The key trade-offs between these two pathways at three spatial scales may provide theoretical support and practical guidance for UBGI construction and management. The five major research topics mentioned above may offer valuable assistance for UBGI construction and future research. </sec>

Making clear the exact amount of carbon emissions from the planting industry is of great significance for developing low-carbon agriculture and helping achieve carbon neutrality. The current carbon emissions from the planting industry in Beijing, the capital of China, are still unclear, and there is a lack of quantitative research on the production, economic, and ecological benefits of carbon emissions. This paper used the carbon emissions factor method to study the inter-annual variation characteristics of carbon emissions and carbon benefits in Beijing’s planting industry since 2000. The results show that the carbon emissions from the planting industry in Beijing in 2023 were 256,400 tons, of which the carbon emissions from agricultural inputs, nitrous oxide (N2O) from farmland, and methane (CH4) from rice cultivation were 149,300, 105,200, and 2000 tons, respectively. From 2000 to 2023, the total carbon emissions from the planting industry in Beijing have shown a downward trend. Compared with 2000, the carbon emissions from agricultural inputs and N2O in 2023 decreased by 59.88% and 74.52%, respectively. The carbon emissions of CH4 from rice cultivation were only 2.38% of those in 2000, and the total carbon emissions from the planting industry in Beijing decreased by 70.43%. The average carbon emissions from agricultural inputs and N2O accounted for 50.85% and 47.95% of the total level of the planting industry, respectively, and were the main sources of carbon emissions in Beijing. Chemical fertilizer and agricultural film inputs were important sources of carbon emissions from agricultural inputs. Reducing inputs for agriculture and sources of N2O from farmland is an important way to reduce carbon emissions from agriculture in Beijing. In the end, some suggestions were proposed for reducing carbon emissions from the planting industry.

Decomposition of carbon emission and its decoupling analysis and prediction with economic development: A case study of industrial sectors in Henan Province

The emission of greenhouse gases poses enormous pressure on current carbon emissions and carbon reduction. Accurate quantification of carbon emissions from coal-fired power plants is of great significance for achieving the dual carbon goal. To enable enterprises to better understand their carbon emissions, this study constructs a carbon emission model and carbon emission data accounting model for coal-fired power plants. Case data calculations and a carbon emission reduction analysis were conducted. The experiment showcases that the carbon sensitivity of the inner side of the boiler under control conditions is higher than that of the operating parameters controlled on the inner side of the steam turbine, with a maximum total value of 16.67 g/MJ; the annual average low calorific value of coal remains between 16,000 kJ/kg; the activity level of coal remains between 30,000 TJ; and the oxidation probability of coal char during combustion fluctuates, with a maximum of 99.8%. In the calculation of coal-fired carbon emissions, the fitting difference between the emissions of generator unit 1 and generator unit 2 is maintained within 2%. Overall, the CO2 emissions of power plants involved in the study are generally high. The model built through this study has well analyzed the carbon emissions of power plants. It is of great significance for the actual carbon emission reduction of coal-fired power plants.

Currently, scientifically and reasonably specifying carbon emission reduction measures in the context of "double carbon" has become a common concern worldwide. China's administrative divisions have a notable impact on the formulation and implementation of relevant policies. Therefore the carbon emissions must be calculated accurately under China's administrative divisions at different scales. The spatiotemporal change characteristics of absorption and carbon emissions can provide scientific basis for the formulation of reasonable and differentiated carbon emission reduction policies in different administrative regions in China. To this end, this study used multi-source data such as remote sensing and statistics and integrated ecological models, statistics, and GIS space analysis and other methods to analyze the spatiotemporal dynamic change characteristics of carbon emissions and carbon absorption at different administrative scales （provinces, cities, and counties） in China. The results showed that： ① The total carbon absorption of vegetation in China continued to increase from 2000 to 2021 and the average value gradually increased. Differences were observed in spatiotemporal changes in carbon emissions at different administrative scales. The spatiotemporal changes at smaller scales were more evident. Carbon emissions showed obvious spatial differences of "high in the north and low in the south, high in the east and low in the west." ② The spatiotemporal distribution of CPI at the administrative scale was similar to that of carbon emissions and the overall trend was increasing annually. The pressure of carbon emissions on carbon absorption gradually weakened from the east to the central and western regions. ③ Spatiotemporal hotspot analysis showed that the overall spatial distribution of cold and hot spots in China's carbon absorption was as follows： In the spatial pattern of "hot in the east and cold in the west," the spatial distribution of cold and hot spots of carbon emissions showed agglomeration characteristics. The provincial scale was primarily oscillating hotspot whereas municipal and county scales were majorly continuous hot spots. Further results revealed that： ① Carbon absorption in different regions and periods in China showed significant variability, especially in the central and eastern regions. The possibility of offsetting carbon emissions by increasing carbon absorption remains. ② At the same scale, administrative regions （such as different provinces） and lower-level administrative regions at another scale （such as different cities in the same province） showed varying degrees of variability in carbon absorption and carbon emissions. Therefore, taking provincial administrative regions as an example for subsequent formulation considering carbon trading, emission reduction, and other policies, we should first consider the coordination of emissions between different cities in the province and then consider the coordination between provinces, which is expected to better promote the implementation of relevant policies.

The Hu-Bao-O-Yu urban agglomeration is an important energy exporting and high-end chemical base in China, and is an important source of carbon emissions in China. The early achievement of peak carbon emissions in this region is particularly crucial to achieving the national carbon emission reduction targets. However, there is a lack of multi-factor system dynamics analysis of resource-dependent urban agglomerations in Northwest China, as most studies have focused on single or static aspects of developed urban agglomerations. This paper analyses the relationship between carbon emissions and their influencing factors, constructs a carbon emission system dynamics model for the Hu-Bao-O-Yu urban agglomeration, and sets up different single regulation and comprehensive regulation scenarios to simulate and predict the carbon peak time, peak value, and emission reduction potential of each city and urban agglomeration under different scenarios. The results show that: (1) Hohhot and Baotou are expected to reach peak carbon by 2033 and 2031 respectively, under the baseline scenario, while other regions and the urban agglomeration will not be able to reach peak carbon by 2035. (2) Under single regulation scenarios, the effect of factors other than the energy consumption varies across cities, but the energy consumption and environmental protection input are the main factors affecting carbon emissions in the urban agglomeration. (3) A combination of the economic growth, industrial structure, energy policy, environmental protection, and technology investment is the best measure to achieve carbon peaking and enhance the carbon emission reduction in each region as soon as possible. In the future, we need to coordinate the economic development, energy structure optimisation and transformation, low-carbon transformation of industry, strengthen research on carbon sequestration technology, and further increase the investment in environmental protection to make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration with an optimal emission reduction.

Chinese universities have the characteristics of a dense population and high per capita energy consumption. Quantitative analysis of campus carbon emissions, research on the characteristics of campus carbon emissions, and exploring the potential for campus emission reduction have become effective carbon reduction paths for universities. Taking a university in Shanghai as an example, based on the set organizational boundaries, carbon emission sources are determined and classified, and the most suitable carbon emission factors are selected for them. Activity data on relevant carbon emission sources is collected through on-site research, and the emission factor method is used for carbon emission accounting and analysis. Finally, by analyzing the current carbon reduction status of existing green technologies, feasible carbon reduction potentials of green technologies are explored to optimize campus carbon reduction strategies. The results show that indirect emissions generated by electricity are the main source of its carbon emissions, accounting for 89.9% of the total carbon emissions. The utilization of renewable energy and carbon sequestration through green plants offset at least 69.75% of the total carbon emissions on campus. In addition, promoting the centralized opening of self-study rooms, improving the shading system of graphic and text centers, and implementing energy-saving renovations for elevators can achieve energy efficiency rates of 76.12%, 20%, and 37.73%. The results of this study provide valuable references for the development of carbon emission inventories for new green campuses, carbon emission accounting, and the construction of low-carbon pathways for universities.

<p id="C3">Crop production not only ensures national food security, but also is the main source of agricultural carbon emissions and an important pool of carbon sequestration. To clarify the characteristics of carbon emissions from crop production and discuss the approaches to reach the peak and neutrality in major agricultural areas can provide important scientific basis to the decision making of green and high-quality agricultural development and “dual-carbon” goal. Based on the national statistical data, this study compared and analyzed the characteristics of carbon emissions in crop planting regions in China, and presented the recommendations for carbon sequestration and greenhouse gas emission mitigation. The carbon emissions of crop production accounted for 45.5% of the national agricultural total carbon emissions in 2018, and the emissions of farmland methane (CH₄), nitrous oxide (N₂O), and carbon dioxide (CO₂) of diesel consumption accounted for 22.9%, 14.7%, and 7.9% of the total carbon emissions of agricultural production, respectively. In terms of the regional emissions, both the total carbon emission of crop production and the carbon emission per sowing area are higher in South than North China, with the highest emissions in East and central China and the greatest potential for emission mitigation. In the carbon emission from crop production, CH₄ emission from rice fields accounts for the main part (50.3%) and is the focus of emission reduction. The annual carbon emission of crop production in China peaked in 2015, and then dropped down. It was mainly attributed to the decrease trend of rice sown area, agricultural nitrogen application rate, and diesel oil consumption. If the existing agricultural imports are not significantly affected, the carbon emissions in crop production have basically reached the peak. However, it is very difficult to achieve carbon neutrality in crop production if only by soil carbon sequestration of farmland, and it is necessary to consider both farmland emission reduction and carbon sequestration. On the premise of high and stable grain yield, the carbon neutrality of modern crop production should prioritize CH₄ and N₂O reduction, and fully exploit the integrated carbon sequestration potential of farmland ecosystems, such as straw utilization, combination of the use and protection of farmland, and construction of farmland forest network.

The urban agglomerations in the middle reaches of the Yangtze River (MYR-UA) are facing a severe challenge in reducing carbon emissions while maintaining stable economic growth and prioritizing ecological protection. The energy consumption related to land urbanization makes an important contribution to the increase in carbon emissions. In this study, an IPAT/Kaya identity model is used to understand how land urbanization affected carbon emissions in Wuhan, Changsha, and Nanchang, the three major cities in the middle reaches of the Yangtze River, from 2000 to 2017. Following the core idea of the Kaya identity model, sources of carbon emissions are decomposed into eight factors: urban expansion, economic level, industrialization, population structure, land use, population density, energy intensity, and carbon emission intensity. Furthermore, using the Logarithmic Mean Divisia Index (LMDI), we analyze how the different time periods and time series driving forces, especially land urbanization, affect regional carbon emissions. The results indicate that the total area of construction land and the total carbon emissions increased from 2000 to 2017, whereas the growth in carbon emissions decreased later in the period. Energy intensity is the biggest factor in restraining carbon emissions, followed by population density. Urban expansion is more significant than economic growth in promoting carbon emissions, especially in Nanchang. In contrast, the carbon emission intensity has little influence on carbon emissions. Changes in population structure, industrial level, and land use vary regionally and temporally over the different time period.

Research on peak prediction of urban differentiated carbon emissions -- a case study of Shandong Province, China

Reducing carbon emissions from infrastructure delivery is key to achieving national carbon emission reductions and is fundamental to addressing the global challenge of climate change. There is also a compelling business case for reducing infrastructure carbon emissions. Reducing carbon emissions can reduce costs, unlock innovation and drive better solutions, drive resource efficiency and deliver better-performing infrastructure. High Speed Two (HS2) Ltd has adopted ambitious targets to reduce carbon emissions from the construction and operation of the programme. Whole-life carbon emission baselines are necessary to determine carbon reduction performance against the targets and are essential in enabling effective carbon management. Through collaborative working with – and between – supply chain partners, whole-life carbon baselines have been established for HS2 Phase One civil assets and stations; a first for an infrastructure project of the nature and scale of HS2. The baselines, produced in accordance with best practice standards, create a reference level against which whole-life carbon reduction performance can be monitored and reported and identify ‘carbon hotspots’ – sources of carbon emissions with the greatest impact and potential for carbon reduction – on which to focus efforts to reduce emissions. This paper outlines how whole-life carbon baselines have been established for Phase One civil and stations assets, presents key outputs from the process and identifies key lessons learned relating to accuracy, collaboration, tools and continual improvement, that can be applied to future HS2 carbon baseline activities and other infrastructure projects.

Towards low-carbon cities through building-stock-level carbon emission analysis: a calculating and mapping method

Excessive carbon emissions lead to global warming, which has attracted widespread attention in the global society. Carbon emissions and land use are closely related. An analysis of land use carbon emissions and carbon fairness can provide guidance for the formulation of energy conservation and emission reduction policies. This study uses data on agricultural production activities, land use and energy consumption and uses the carbon emission coefficient method to calculate carbon emissions and carbon absorption. The tendency value is used to analyze trends in land use carbon emissions and carbon absorption. The Gini coefficient, ecological support coefficient and economic contributive coefficient are used to analyze the fairness and difference of carbon emissions. The results showed that: (1) During the study period, there were fewer provinces with rapid growth in carbon emissions and carbon absorption and more provinces with slow growth. (2) Cultivated land and woodland are the main carriers of land use carbon absorption, and most provinces steadily maintain the type of carbon absorption to which they belong. (3) Carbon emissions from construction land are the main source of total carbon emissions, and the high concentration areas of carbon emissions are mainly located in the more economically developed areas. (4) There are obvious regional differences in the net carbon emissions. By 2015, Shanxi–Shandong High–High agglomeration areas and Yunnan–Guangxi Low–Low agglomeration areas were finally formed. (5) The distribution of carbon emissions in different provinces is not fair, and the spatial distribution is obviously different. Based on the analysis results, relevant suggestions are made from the perspectives of carbon emission reduction and carbon sink enhancement.

Under the background of the energy revolution, the energy structure is constantly optimized, the proportion of primary energy consumption such as fossil energy is continuing to decline, and low-carbon economy is an important trend of global economic development. However, coal power is the main power source positioning in the short term will not change. Therefore, we should constantly adjust the energy structure at the same time, strengthen the low-carbon use of primary energy, reduce carbon emissions. Reducing carbon emissions in the coal supply chain is an important measure under the "low carbon policy". Therefore, this paper mainly focuses on the coal supply chain carbon dioxide emissions research and analysis, discusses the main sources of carbon emissions and key factors, the construction of interpretation structure model for the analysis and ranking of nine major factors, and divide it into levels. Finally, according to the results of the analysis, some rationalization suggestions are put forward to the relevant enterprises in the coal supply chain to realize the low carbon development of coal supply chain network.

The farming-pastoral ecotone has an important strategic place in the energy supply and ecological layout of China. Thus, exploring the spatial and temporal variation characteristics of carbon emissions in this region will help to deeply understand the information on the historical carbon emissions in China's energy production bases and provide data references for the formulation of differentiated emission reduction policies and the promotion of regional energy-saving and carbon-reducing measures, which is of great significance for the realization of low-carbon economic development. This study constructed a spatialization model of carbon emissions based on land use, night lighting, and provincial energy consumption data； explored the spatiotemporal changes and aggregation characteristics of carbon emissions in the farming-pastoral ecotone from 1995 to 2020 using the global Moran's index and hotspot analysis； and then combined it with the slack-based measure model to calculate the carbon emission efficiency and emission reduction potential of each city from 2010 to 2020 and classify cities to propose a differentiated emission reduction path. The results showed that, firstly, the estimated results at the prefectural city level of the carbon emission spatialization model constructed in this study with multi-source data could reach an R2 of 0.92 for a linear fit. Secondly, the total carbon emissions in the farming-pastoral ecotone increased from 176.29 million tons in 1995 to 1 014.51 million tons in 2020. However, the carbon emission intensity and growth rate both decreased, which was related to adjusting the energy structure and improving energy efficiency. Regarding spatial distribution, the cities with high carbon emissions over time were Datong, Baotou, and Yulin in order. Thirdly, the carbon emissions in the study area showed a significant global spatial positive correlation at the county level, with the hot spots mainly located at the junction of Shanxi, Shaanxi, and Inner Mongolia, while the cold spots were extended from Yanan City to Qingyang and Guyuan City after 2010. Finally, based on the differences in carbon emission efficiency and reduction potential, cities could be classified into four types： "high-efficiency and high potential," "low-efficiency and high potential," "high-efficiency and low potential," and "low-efficiency and low potential" to implement targeted emission reduction strategies.