为完善城市轨道交通综合评价系统，促进城市轨道交通高质量发展，围绕“绿色低碳”理念，基于城市轨道交通流动空间特性，提出涵盖车站建筑、车轨隧道和通行列车的全生命周期绿色低碳耦合评价方法。通过专家调查法建立包含设计、施工、运营全生命周期及通勤服务便捷、人工环境舒适、资源节约利用和生态环境保护4方面的全场景、全过程、全方位的绿色评价体系，采用层次分析法计算指标权重，得出主观评价分值； 基于全生命周期理论确立碳排放核算边界，采用碳排因子法计算建材生产、施工、运营各阶段的碳排放量，并引入年度人均碳排放量作为评价指标，客观计算碳排放强度。以北京某典型车站作为案例，进行耦合评价模型验证，评估其绿色部分评价分值，并计算年度人均碳排放量。结果表明：
该车站绿色低碳耦合评价结果为绿色评价分值243分、年度人均碳排放量17.2
tCO2e/万人次。为全面提升车站的整体绿色性能并有效降低碳排放，提出针对该车站的全过程优化方案，最终可将绿色评价分值提升至271分，显著降低年度人均碳排放量至13.3 tCO2e/万人次。
Improved comprehensive evaluation system of urban rail
transit can promote high-quality development of urban rail
transit. Herein, a green and low-carbon coupling
evaluation method covering the whole life cycle of station buildings, vehicle-track tunnels, and passing trains is proposed based on the
characteristics of urban rail transit flow space, centering on the concept of
"green and low-carbon". The green evaluation
part uses the expert survey method to establish a full-scene,
full-process, and all-round
green evaluation system including the whole life cycle of design, construction,
and operation involving convenient commuting service, comfortable artificial
environment, resource conservation and utilization, and ecological environment
protection. The analytic hierarchy process is used to calculate the index
weights and yield the subjective evaluation score. The low-carbon evaluation part establishes the carbon emission accounting
boundary based on the whole life cycle theory, and uses the carbon emission
factor method to calculate the carbon emissions in each stage of building
materials production, construction, and operation. The annual per capita carbon
emissions are introduced as an evaluation indicator to objectively calculate
the carbon emission intensity. Finally, a case study is conducted on a station
in Beijing, and the coupling evaluation model is verified, thus calculating its
green evaluation score and annual per capita carbon emissions. The results show
that the green and low-carbon coupling evaluation
results of the station are 243 points for green evaluation and 17.2 tCO2e per 10 000 people for annual per capita carbon emissions. To
comprehensively improve the overall green performance of the station and
effectively reduce carbon emissions, a full-process
optimization plan for the station is proposed, which ultimately increases the
green evaluation score to 271 points and significantly reduces the annual per
capita carbon emissions to 13.3 tCOe per 10 000 people.
