Towards high-resolution pollutant mapping in narrow spaces: Integrating fixed sensors, mobile robots, and enhanced reconstruction techniques

Abstract

Narrow spaces—including underground tunnels, subway platforms, corridors, overpasses, and public transportation vehicles—are prone to pollutant accumulation due to spatial constraints and limited ventilation, posing significant health and safety risks. Achieving high-resolution mapping of pollutant distribution patterns is crucial for mitigating these risks, yet traditional monitoring methods often fail to adequately address the trade-offs between temporal and spatial resolution. This study introduces an innovative monitoring and analysis framework designed for the efficient dispersion of pollutants in ventilated narrow spaces. It integrates fixed sensors for high temporal resolution data acquisition, mobile robots for enhanced spatial coverage, and advanced field reconstruction methods—specifically, Kernel DM+V/W+ and Kernel DM+V/W++ methods—to extrapolate limited sampling data into high-resolution concentration fields. The efficacy of this framework is demonstrated through meticulous ethanol and methane dispersion experiments conducted in a long corridor and a scaled-down utility tunnel model, respectively. The results underscore the framework’s capability to precisely depict pollutant distributions, effectively extrapolate concentrations to unmonitored areas, and produce comprehensive environmental distribution maps. This novel approach not only significantly enhances the precision of pollutant distribution reconstruction but also optimizes sampling strategies and improves overall monitoring efficiency.