Summary:
Road transport is a leading source of urban nitrogen oxides (NOx) and fine particulate matter (PM2.5)—a public-health and urban-sustainability challenge—and Low-Emission Zones (LEZs) are Europe’s principal response. Yet most are governed statically, unable to track conditions changing by the hour and the street. A digital twin, treated as decision infrastructure rather than a 3D model, recasts the LEZ as an adaptive decision infrastructure: a closed loop of sensing, modelling and rule-based adjustment. We develop a scalable, five-phase lifecycle methodology with auditability and GDPR-by-design built in, and derive three falsifiable hypotheses—efficiency, data integration, responsiveness—defining a research agenda. We test only the first. A diagnostic reading of London’s ULEZ shows its unimplemented phases are precisely those that close the loop. A proof-of-concept on real hourly NO2 from five London sites (2023–2024) tests efficiency: at equal abatement effort, adaptive targeting avoids significantly more elevated-pollution hours than a uniformly stricter policy (about 37% versus 27%; 95% CI excludes parity), the advantage rising with forecast quality. This demonstrates the mechanism in reduced form, not a generalizable figure for a deployed system. By making regulation more responsive and accountable, it advances the Sustainable Development Goals on health, sustainable cities and climate (SDGs 3, 11, 13).
Spanish layman's summary:
Reformulamos las zonas de bajas emisiones como infraestructuras de decisión adaptativas gobernadas por un gemelo digital: un ciclo sensar-modelar-decidir con una metodología de cinco fases, auditable y con protección de datos. Un caso en Londres respalda la propuesta.
English layman's summary:
We reframe Low-Emission Zones as adaptive decision infrastructures run through a digital twin: a sense-model-decide loop with a five-phase, auditable, GDPR-by-design lifecycle. A London proof-of-concept shows forecast-triggered targeting beats a uniformly stricter zone at equal effort.
Keywords: low-emission zones; digital twins; urban air quality; adaptive policy; decision infrastructure; smart cities; sustainable urban mobility; environmental governance; Sustainable Development Goals; data integration
JCR-JIF Impact Factor and WoS quartile: 4,100 - Q2 (2025)
DOI reference:
https://doi.org/10.3390/su18147100
Published on paper: July 2026.
Published on-line: July 2026.
Citation:
A. Cantalapiedra-Asensio, J.C. Romero, "Reframing Low-Emission Zones as Adaptive Decision Infrastructures: A Digital-Twin Framework and Lifecycle Methodology for Sustainable Urban Air Quality", Sustainability, Vol. 18, nº. 14, pp. 7100, July 2026. [Online: July 2026] doi: 10.3390/su18147100
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