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.

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.