Development of a Black Carbon Aerosol Sensor Based on Multispectral Laser Scattering

Black carbon (BC) aerosols, with their increasing emissions, have become a critical driver exacerbating global warming. However, the wide variety of atmospheric particulate matter poses substantial challenges to accurate BC detection. Traditional methods, such as offline sampling with black carbon analyzers and manual laboratory analysis, are plagued by high costs, time-consuming procedures, and operational complexity, limiting their applicability in real-time monitoring scenarios. To address these limitations, this study proposes an innovative BC detection method integrating microfluidic separation, sheath flow focusing, and multi-spectral laser scattering, aiming to achieve rapid and high-precision quantification of BC concentrations in samples. The microfluidic chip’s separation and focusing structure was rationally designed based on inertial impaction and bilateral sheath flow focusing principles, laying a foundation for effective BC isolation from complex matrices. A multi-spectral laser scattering detection platform was constructed to capture characteristic optical signals of BC, and a lightweight on-chip analysis model was further developed to realize qualitative identification and quantitative calculation of BC. Experimental results showed that the effective separation efficiency of the microfluidic chip in this system reached 95%, and the detection results were highly consistent with the calibration data from a black carbon mass spectrometer, with a Pearson correlation coefficient of 0.9823 and a detection accuracy of 0.01 mg/m³. Compared to traditional BC detection methods, the sensor designed in this paper offers advantages such as low cost, high efficiency, and rapid response. Primarily targeting high-emission areas like factories and power plants, it holds broad potential for engineering applications and market promotion.