Quantifying the Comprehensive Environmental Efficiency of Urban Roads Based on MFA-LCA-DEA Method
摘要
The construction of urban road infrastructure inevitably generates significant and diverse environmental impacts. Therefore, improving the comprehensive environmental efficiency of urban roads while meeting transportation needs has become an urgent issue to address. To develop a systematic method for analyzing the environmental efficiency of urban roads, this study integrates Material Flow Analysis (MFA), Life Cycle Assessment (LCA), and Data Envelopment Analysis (DEA). MFA quantifies the material flows within the road system and generates the life cycle inventory (LCI); LCA then uses these data to evaluate the environmental impacts of materials throughout their life cycle; DEA finally takes the LCA results as inputs and traffic services as outputs to assess the relative environmental efficiency of different road segments or structures. This integrated framework enables the quantification of the comprehensive environmental efficiency of urban roads by considering nine different environmental impact categories. Using Nanjing, China, as a case study, the research found that expressways exhibited the highest environmental efficiency, followed by branch roads, while arterial and collector roads had the lowest efficiency. Specifically, expressway efficiency rose from 0.526 in 2014 to the efficiency frontier (≈ 1.000) in 2018–2020, then slightly declined to 0.984 in 2021, remaining the highest. Arterial roads declined from 0.275 to 0.204, with a modest rebound to 0.238 in 2021. Collector roads fell to 0.172 in 2017 but recovered to 0.290 by 2021, while branch roads fluctuated and improved slightly to 0.349 in 2021. These results demonstrate that the proposed MFA–LCA–DEA integration provides an effective framework for evaluating temporal and structural variations in environmental efficiency, supporting policymakers and planners in integrating environmental considerations into urban road network planning and pavement design.