A Web-Based Digital Twin for Traffic and Air Quality Monitoring: A Prototype Study in Almaty, Kazakhstan

Urban air pollution driven by road traffic poses a significant public health challenge in cities with high vehicle density and frequent congestion, particularly in topographically constrained environments such as Almaty, Kazakhstan. This study presents a web-based digital twin prototype for the integrated monitoring and analysis of traffic flow and air quality in Almaty, Kazakhstan. The system autonomously collects data from the TomTom Traffic, OpenWeather Air Pollution, and WAQI APIs and official population statistics for five fixed monitoring stations, computing traffic density, vehicles per hour, road congestion, estimated CO2 emissions, an air pollution index, and a population exposure index, and providing real-time dashboard visualization alongside longitudinal data accumulation. Over a 50-day deployment (26 May–16 July 2026), 4961 real co-located observations across 18 active days were analyzed; records generated by the prototype’s fallback mechanism during API outages were excluded from the scientific analysis. During this summer period, PM2.5 was low (mean ≈ 6 µg/m3) and spatially uniform, and showed no statistically significant association with traffic intensity (r ≈ −0.03). Traffic indicators were instead weakly but significantly correlated with the vehicle-emitted gases NO2 (r ≈ 0.16) and CO (r ≈ 0.10), which they preceded by up to about one hour. A short-horizon PM2.5 nowcasting task, evaluated across temporal resolutions with time-series cross-validation, was dominated by temporal persistence, with traffic-derived features contributing negligibly. The absence of a summer traffic–PM2.5 association does not preclude such a relationship during the heating season, when particulate levels are higher. The results indicate that the traffic–air-quality relationship in Almaty is season- and pollutant-dependent, and demonstrate a lightweight, reproducible platform suitable for longitudinal monitoring and future heating-season assessment.

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Publication Details

Journal
Technologies
Published
2026-08-18
DOI
https://doi.org/10.3390/technologies14080512
Primary Topic
Vehicle emissions and performance
Type
article
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article

A Web-Based Digital Twin for Traffic and Air Quality Monitoring: A Prototype Study in Almaty, Kazakhstan

Saya Sapakova, Zhomart Ualiyev, Lyailya Tukenova, Aigul Skakova et al.
Technologies
Vehicle emissions and performance
article

A Web-Based Digital Twin for Traffic and Air Quality Monitoring: A Prototype Study in Almaty, Kazakhstan

Saya Sapakova, Zhomart Ualiyev, Lyailya Tukenova, Aigul Skakova, Omirlan Auyelbekov, Assem Kabdoldina, Sakhybay Tynymbayev, Askar Sapakov
article en

Abstract

Urban air pollution driven by road traffic poses a significant public health challenge in cities with high vehicle density and frequent congestion, particularly in topographically constrained environments such as Almaty, Kazakhstan. This study presents a web-based digital twin prototype for the integrated monitoring and analysis of traffic flow and air quality in Almaty, Kazakhstan. The system autonomously collects data from the TomTom Traffic, OpenWeather Air Pollution, and WAQI APIs and official population statistics for five fixed monitoring stations, computing traffic density, vehicles per hour, road congestion, estimated CO2 emissions, an air pollution index, and a population exposure index, and providing real-time dashboard visualization alongside longitudinal data accumulation. Over a 50-day deployment (26 May–16 July 2026), 4961 real co-located observations across 18 active days were analyzed; records generated by the prototype’s fallback mechanism during API outages were excluded from the scientific analysis. During this summer period, PM2.5 was low (mean ≈ 6 µg/m3) and spatially uniform, and showed no statistically significant association with traffic intensity (r ≈ −0.03). Traffic indicators were instead weakly but significantly correlated with the vehicle-emitted gases NO2 (r ≈ 0.16) and CO (r ≈ 0.10), which they preceded by up to about one hour. A short-horizon PM2.5 nowcasting task, evaluated across temporal resolutions with time-series cross-validation, was dominated by temporal persistence, with traffic-derived features contributing negligibly. The absence of a summer traffic–PM2.5 association does not preclude such a relationship during the heating season, when particulate levels are higher. The results indicate that the traffic–air-quality relationship in Almaty is season- and pollutant-dependent, and demonstrate a lightweight, reproducible platform suitable for longitudinal monitoring and future heating-season assessment.

TechnologiesVol. 14(8)
Almaty Management University (KZ), Satbayev University (KZ), Almaty University of Power Engineering and Telecommunications (KZ), University of International Business (KZ), Kazakh Scientific Research Veterinary Institute (KZ), Abai Kazakh National Pedagogical University (KZ), Kazakh National Agrarian Research University (KZ), Institute of Physics and Technology (KZ), Institute of Information and Computational Technologies (KZ), International Information Technologies University (KZ), Kazakh German University (KZ)
Sustainable cities and communities
Openalex Percentile: Top 16%
Vehicle emissions and performance
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