Carbon Emission Effects Driven by Evolution of Chinese Dietary Structure from 1987 to 2020

Exploring carbon emission effects based on the evolution of residents’ dietary structure to achieve the carbon neutrality goal and mitigate climate change is an important task.This study took China as the research object(data excluding Hong Kong,Macao and Taiwan) and used the carbon emission coefficient method to quantitatively measure the food carbon emissions from 1987–2020,then analyzed the carbon emission effects under the evolution of dietary structure.The results showed that during the study period,the Chinese dietary structure gradually changed to a high-carbon consumption pattern.The dietary structure of urban residents developed to a balanced one,while that of rural residents developed to a high-quality one.During the study period,the per capita food carbon emissions and total food consumption of Chinese showed an increasing trend.The per capita food carbon emissions of residents in urban and rural showed an overall upward trend.The total food carbon emissions in urban increased significantly,while that in rural increased first and then decreased.The influence of beef and mutton on carbon emissions is the highest in dietary structure.Compared with the balanced dietary pattern,the food carbon emissions of Chinese residents had not yet reached the peak,but were evolving to a high-carbon consumption pattern.

Spatial-temporal Heterogeneity of Industrial Structure Transformation and Carbon Emission Effects in Xuzhou Metropolitan Area

Employing decoupling index and industrial structure characteristic bias index methods, this study analyzed the spatial-temporal characteristics of industrial structure transformations and their resulting carbon emissions in the Xuzhou Metropolitan Area from 2000 to 2014, with a focus on their relationships and driving factors. Our research indicates that carbon emission intensity from industrial structures in the Xuzhou Metropolitan Area at first showed an increasing trend, which then decreased. Furthermore, the relationship between emissions and industrial economic growth has been trending toward absolute decoupling. From the perspective of the center-periphery, the Xuzhou Metropolitan Area formed a concentric pattern, where both progress towards low emissions and the level of technological advancement gradually diminished from the center to the periphery. In terms of variation across provinces, the ISCB index in the eastern Henan has decreased the slowest, followed by the southern Shandong and the northern Anhui, with the northern Jiangsu ranking last. During this period, resource-and labor-intensive industries were the primary growth industries in the northern Anhui and the eastern Henan, while labor-intensive industries dominated the southern Shandong and capital-intensive industries dominated the northern Jiangsu. In terms of city types, the spatial pattern for industrial structure indicates that recession resource-based cities had higher carbon emission intensities than mature resource-based cities, followed by non-resource-based cities and regenerative resource-based cities. Generally, the industrial structure in the Xuzhou Metropolitan Area has transformed from being resource-intensive to capital-intensive, and has been trending toward technology-intensive as resource availability has been exploited to exhaustion and then been regenerated. Industrial structure has been the leading factor causing heterogeneity of carbon emission intensities between metropolitan cities. Therefore, the key to optimizing the industrial structure and layout of metropolitan areas is to promote industrial structure transformation and improve the system controlling collaborative industrial development between cities.

The Measurement of Carbon Emission Effect of Construction Land Changes in Anhui Province Based on the Extended LMDI Model

In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the increase of carbon emissions in the atmosphere. In this study, the drivers of carbon emissions in Anhui Province from 1997 to 2011 were quantitatively measured using the improved Kaya identity and Logarithmic Mean Divisia Index. The results show that： economic growth, expansion of construction land and changes in population density have incremental effects on carbon emissions. The average contribution rate of economic growth as the first driver is 266.32 percent. The construction land expansion is an important driving factor with annual mean carbon effect of 6.4057 million tons and annual mean contribution rate of 187.30 percent. But the change in population density has little impact on carbon emission driving. Energy structure changes and energy intensity reduction have inhibitory effects on carbon emissions, of which the annual mean contribution rate is -212.06 percent and -158.115 percent respectively. The targeted policy approaches of carbon emission reduction were put forward based on the decomposition of carbon emission factors, laying a scientific basis to rationally use the land for the Government, which is conducive to build an ecological province for Anhui and achieve the purpose of emission reduction, providing a reference for the research on carbon emission effect of changes in provincial-scale construction land.

Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.

建设用地规划方案的碳排放核算与低碳优化方法

Built-up area(BUA)significantly contributes to global greenhouse gas emissions,making strategic spatial planning crucial for carbon emission control.Given the diverse land use patterns and carbon emission sources in BUAs,this study proposed a land-based strategy system for carbon emission assessment and optimization.A three-step method was devised to create a planner-friendly tool for implementing the system,which involves carbon emission intensity calculation based on current land use,spatial illustration of carbon emission intensities based on land use planning,and planning program optimization and emission reduction effect assessment.The method was applied to the central urban area of Changxing County(Zhejiang)in China.The results showed that the structures and emission intensities of urban land use substantially influenced the overall carbon emissions in the central urban area.Our comprehensive land use optimization strategies reduced the overall carbon emissions of the central urban area by 36.9%when compared to the original planning program.The Monte Carlo simulation indicated that land use structure optimization and emission intensity control measures could reduce carbon emission rate by 5.20%to 18.28%,and 18.44%to 31.67%,respectively.The results underlined the importance of making specific adjustments to land use structure and implementing intensity control measures for effective carbon reduction.In conclusion,this study offers methods and insights for urban planners in creating sustainable and low-carbon urban spaces.