| 城市尺度下长江经济带城市生活垃圾碳排放的因素分解与减碳潜力分析 |
| 摘要点击 902 全文点击 15 投稿时间：2025-06-25 修订日期：2025-09-10 |
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| 中文关键词 长江经济带 聚类分析 生活垃圾碳排放 影响因素 减碳潜力 |
| 英文关键词 Yangtze River Economic Belt cluster analysis carbon emissions of domestic waste influencing factors carbon reduction potential |
| DOI 10.13227/j.hjkx.202506299 |
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| 中文摘要 |
| 推动城市生活垃圾碳减排，是实现“双碳”目标和协同减污降碳的重要举措. 基于长江经济带111个地级及以上城市2010~2020年的面板数据，构建涵盖“源头减量+末端处置”的核算体系测算城市生活垃圾碳排放量，结合人口和经济特征将城市聚类为四大类型进行探讨，并解构了生活垃圾碳排放的影响因素. 最后，运用BP神经网络模型结合情景分析方法，预测不同类别城市的垃圾处理减碳潜力. 结果表明：①长江经济带生活垃圾碳排放量在观察期内呈现逐年递增趋势. 从碳排放结构看，填埋始终是最主要碳源，焚烧碳排放次之，生化排放占比最小，而回收碳减排增长率最高、减排效能持续增强；②处理结构、经济发展、城镇化水平和人口规模均对生活垃圾碳排放产生正效应，产废强度与产业升级则呈现负效应，且在不同城市类型中作用各异；③4类城市均存在显著的垃圾处理减碳空间，但差异明显. 第二类城市潜力远超其他类别，第一类整体最低，第三和第四类减碳潜力变化趋势相近，总体表现为先升后降. |
| 英文摘要 |
| Promoting carbon emissions reduction of urban domestic waste is an important measure to achieve the “dual carbon” goals and achieve coordinated pollution reduction and carbon emission reduction. Based on the panel data of 111 cities above prefecture level in the Yangtze River Economic Belt from 2010 to 2020， this study calculated the carbon emissions of urban domestic waste， including the “source reduction + terminal disposal” process. The cities were clustered into four types based on population and economic characteristics， and the influencing factors of carbon emissions from urban domestic waste were decomposed. Furthermore， the BP neural network model and scenario analysis method were used to predict the carbon reduction potential of domestic waste in each type of city. The results show that： ① The total carbon emissions of domestic waste in the Yangtze River Economic Belt had been increasing year by year during the observation period. From the perspective of the carbon emission structure， landfill was always the main carbon source with the largest proportion， followed by incineration， and the proportion of biodegradation emissions was the lowest， while the growth rate of carbon reduction from recycling was the highest， and the reduction efficiency was continuously enhanced. ② The impact effects of treatment structure， economic development， urbanization level， and total population size on the carbon emissions of domestic waste were all positive， while the impact effects of waste generation intensity and industrial structure optimization were negative， and they showed different effects in various cities. ③ All types of cities had great carbon reduction potential in domestic waste， but there were great differences. The carbon reduction potential of the second type of city was far higher than that of other cities， while the first type of city had the lowest carbon reduction potential overall. The change degree of carbon reduction potential of the third and fourth types of cities was similar， showing a trend of increasing first and then decreasing. All localities should formulate and implement carbon reduction measures for domestic waste disposal according to local conditions. |
