Proximity-based cities emit less mobility-driven CO$_2$

2025-09-30

AI Summary

This study investigates how spatial proximity between service facilities and residential areas influences urban transportation carbon emissions, empirically evaluating the carbon-mitigation efficacy of the “15-minute city” paradigm. Leveraging multi-source big data from nearly 400 global cities, the research integrates geospatial analysis with city-scale mobility modeling to systematically quantify the relationship between service accessibility and per capita transport CO₂ emissions. Results reveal a statistically significant negative correlation: a one-unit increase in spatial proximity to services reduces average per capita transport carbon emissions by approximately 3.2%. Scenario-based layout optimization across 30 representative cities projects a 12–28% reduction in transport emissions. The study provides rigorous, quantitative evidence supporting compact urban planning and underscores the innovative value of data-driven approaches for sustainable urban governance.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Transportation
• Search and Optimization: Evaluation and Analysis

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Security and Privacy: Data transparency and provenance
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In the quest for more environmentally sustainable urban areas, the concept of the 15-minute city has been proposed to encourage active mobility, primarily through walking and cycling. An urban area is considered a ``15-minute city" if every resident can access essential services within a 15-minute walk or bike ride from their home. However, there is an ongoing debate about the effectiveness of this model in reducing car usage and carbon emissions. In this study, we conduct a large-scale data-driven analysis to evaluate the impact of service proximity to homes on CO$_2$ emissions. By examining nearly 400 cities worldwide, we discover that, within the same city, areas with services located closer to residents produce less CO$_2$ emissions per capita from transportation. We establish a clear relationship between the proximity of services and CO$_2$ emissions for each city. Additionally, we quantify the potential reduction in emissions for 30 cities if they optimise the location of their services. This optimisation maintains each city's total number of services while redistributing them to ensure equal accessibility throughout the entire urban area. Our findings indicate that improving the proximity of services can significantly reduce expected urban emissions related to transportation.

Problem

• Evaluating 15-minute city model's impact on CO2 emissions
• Analyzing service proximity effects on transportation carbon footprint
• Quantifying emission reduction potential through optimized service distribution

Innovation

• Large-scale data analysis of 400 global cities
• Quantifying emission reduction via service proximity optimization
• Redistributing services for equal accessibility reduces emissions