Fine Particle Sensor Based on Multi-Angle Light Scattering and Data Fusion

Abstract

Meteorological parameters such as relative humidity have a significant impact on the precision of PM2.5 measurement instruments based on light scattering. Instead of adding meteorological sensors or dehumidification devices used widely in commercial PM2.5 measurement instruments, a novel particle sensor based on multi-angle light scattering and data fusion is proposed to eliminate the effect of meteorological factors. Three photodiodes are employed to collect the scattered light flux at three distinct angles. Weather index is defined as the ratio of scattered light fluxes collected at the 40° and 55° angles, which can be used to distinguish the mass median diameter variation caused by different meteorological parameters. Simulations based on Lorenz-Mie theory and field experiments establish the feasibility of this scheme. Experimental results indicate that mass median diameter has less effect on the photodiode at the 55° angle in comparison with photodiodes at the 40° angle and 140° angle. After correction using the weather index, the photodiode at the 40° angle yielded the best results followed by photodiodes at the 55° angle and the 140° angle.

Development of Low-Cost Air Quality Stations for Next Generation Monitoring Networks: Calibration and Validation of PM2.5 and PM10 Sensors

“…On the contrary, scores from current PM 2.5 calibration are outperformed by those obtained by Shao et al [ 24 ], who compared their low-cost PM 2.5 sensing system against a Tapered Element Oscillating Microbalance (TEOM) reference station in Wolongqiao (China) based on 1-h data collected from 7 to 14 March 2016. In doing so, they used a non-linear model as a function of PM readings and scattered light fluxes.…”

“…Furthermore, since only employing PM sensors readings as a regressor, simplicity of the currently-implemented PM calibration model—and thus its easier portability to other contexts/applications—should also be highlighted. This marks a clear distinction from multi-linear regressions or non-linear multi-variate models such as those that also consider relative humidity (e.g., [ 16 , 48 ]), air temperature (e.g., [ 48 ]), or scattered light fluxes (e.g., [ 24 ]) as regressors.…”

“…Recently, there has been an emerging trend of using the next generation air sensors to provide highly resolved air quality data as an alternative or integrative monitoring option. Miniaturization and other technological advances have brought to market a number of low-cost (<€2000) sensors designed to measure atmospheric particles and gases [ 11 , 12 , 13 ], including for example: CO [ 14 , 15 , 16 ], NO 2 [ 15 , 16 , 17 , 18 ], O 3 [ 1 , 15 , 16 , 17 , 19 , 20 ], VOC [ 21 , 22 ], PM 2.5 [ 16 , 22 , 23 , 24 , 25 , 26 , 27 ], PM 10 [ 1 , 25 ], and black carbon [ 28 ]. Due to their low cost, small size and low power consumption, the new technologies are very appealing in situations where traditional monitors are impractical [ 6 , 29 ].…”

Evaluation of the Performance of Low-Cost Air Quality Sensors at a High Mountain Station with Complex Meteorological Conditions

“…LR and MLR use covariates to improve calibrations, and are the most popular methods used to calibrate the sensors' data. However, LR reports the worst R 2 and should be avoided for gaseous sensors [35][36][37]. The remaining four calibration approaches are supervised learning techniques and can greatly improve the R 2 in most sensors and situations.…”

Evaluation of Performance of Inexpensive Laser Based PM2.5 Sensor Monitors for Typical Indoor and Outdoor Hotspots of South Korea

“…However, recently, inexpensive (<$300) particulate matter (PM) monitors (PM) have been introduced for home usage in South Korea. These devices can provide PM distribution patterns at high temporal and spatial resolution [3][4][5] which is a substantial improvement on establishing a pollution monitoring networking system as well as environmental epidemiologic study [6], as compared to traditional approaches that relied on relatively small number of ground-based fixed national air monitoring stations or mobile sampling techniques.…”