| 多场景下低碳交通模式转换对碳排放的影响 |
| 摘要点击 574 全文点击 4 投稿时间：2025-07-10 修订日期：2025-09-11 |
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| 中文关键词 城市交通 碳排放 情景分析 多模式 云模型 |
| 英文关键词 urban traffic carbon emissions scenario analysis multi-mode travel cloud model |
| DOI 10.13227/j.hjkx.202507142 |
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| 中文摘要 |
| 随着城市交通出行需求日益增加，绿色出行已成为城市减碳的主要方式之一. 利用出租车GPS数据、地铁刷卡数据和共享单车订单数据等多源交通数据，以揭示城市公共交通出行模式转换的碳减排潜力. 首先，通过提取不同交通方式的行驶里程，建立“自下而上”的城市交通碳排放计算模型，拟合不同出行模式碳排放的空间分布特征；结合减碳政策的可实施性，提出3种低碳组合出行场景，对差异化场景下城市公共交通的碳减排潜力进行评估. 以深圳为例进行验证，结果表明，城市交通中出租车出行、地铁出行及共享单车出行在空间上高度重合，出租车出行能够被组合低碳出行模式替代；“共享单车+轨道交通”组合出行最高能降低20.34%的碳排放；地铁站点衔接换乘能力会影响选择低碳模式的意愿，考虑站点换乘能力差异化的出行替代场景下，组合出行最高能降低13.57%的碳排放；增加共享电动单车投放量最高可以降低22.01%的碳排放，相比共享单车替代进一步下降11.21%. 研究结果可为优化换乘设施和降低高出行需求区域的碳排放提供参考. |
| 英文摘要 |
| With the increasing demand for urban transportation， green travel has become one of the main ways for cities to reduce carbon emissions. By utilizing multi-source transportation data such as taxi GPS data， subway card usage data， and bike-sharing order data， we aim to reveal the carbon emission reduction potential of the transformation of urban public transportation travel patterns. Firstly， by extracting the driving mileage of different transportation modes， a “bottom-up” urban transportation carbon emission calculation model is established to fit the spatial distribution characteristics of carbon emissions from different travel modes. Combined with the implementability of carbon reduction policies， three low-carbon combined travel scenarios are proposed to evaluate the carbon reduction potential of urban public transportation in differentiated scenarios. Taking Shenzhen City as an example for verification， the results showed that taxi travel， subway travel， and shared bike travel in urban transportation had a high degree of spatial overlap， and taxi travel could be replaced by combined low-carbon travel modes. The combined travel of “shared bikes + rail transit” could reduce carbon emissions by up to 20.34%. The connection and transfer capacity of subway stations will affect the willingness to choose low-carbon modes. Under the travel alternative scenarios considering the differentiation of station transfer capabilities， combined travel could reduce carbon emissions by up to 13.57%. Increasing the deployment of shared electric bikes could reduce carbon emissions by up to 22.01%， which would be a further decrease of 11.21% compared with the substitution of shared bikes. The research results can provide references for optimizing transfer facilities and reducing carbon emissions in areas with higher demand. |
