铁路干预的事前经济和环境评估:以伦巴第大区为例

IF 2.4 Q3 TRANSPORTATION
Giovanni Garola , Guillaume Monchambert , Giovanni Mancardi , Chiara Siragusa , Riccardo Mangiaracina
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引用次数: 0

摘要

本案例研究旨在丰富对传统铁路(CR)干预措施的讨论,研究两种解决方案,分别在高需求和低需求的两种不同背景下,增加频率和新建车站。调查地区是伦巴第大区(意大利)。我们结合效益成本分析(BCA)和生命周期评估(LCA)来评估经济和环境可行性。我们根据不同的场景找到不同的表演。在高需求地区,两种干预措施的效益成本比(BCR)均大于1,而在低需求地区,BCR显著低于1。就排放而言,干预措施的实施表明,节省的排放与产生的额外排放之间的净平衡几乎为零。对不同的关键变量(即需求转移、投资成本和排放因子)进行敏感性分析。转移的需求对改善这两种绩效至关重要,而将环境和运输政策结合起来的互利方法对减少运输排放至关重要。下面的研究通过比较不同铁路干预措施在CR系统中的预期效果,使用综合经济和环境评估来进行评估,从而为学术界做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An ex-ante economic and environmental assessment of railway intervention: A case study in Regione Lombardia
The present case study aims to enrich the discussion on Conventional Rail (CR) interventions, investigating two types of solutions, a frequency increase and a new station construction, in two different contexts, respectively, characterised by high and low demands. The area of investigation is Regione Lombardia (Italy). We combine a Benefit-Cost Analysis (BCA) and a Life Cycle Assessment (LCA) to estimate economic and environmental viability. We find different performances according to the scenarios. In the high-demand area, a Benefit Cost Ratio (BCR) larger than 1 is observed in both interventions, while in the low-demand area, the BCR is significantly lower than 1. For the emissions, the implementation of the interventions shows almost a net balance of zero between the emissions saved and the additional emissions produced. Sensitivity analyses varying the critical variables (i.e., demand diverted, investment costs, and emission factors) are performed. The diverted demand results in being critical to improve both performances, whereas a mutually beneficial approach that combines environmental and transport policies is essential to reduce transport emissions. The following study contributes to academia by comparing the expected effects of different railway interventions in a CR system, using a combined economic and environmental assessment for their evaluation.
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来源期刊
CiteScore
5.00
自引率
12.00%
发文量
222
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