Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements

The environments in which we live, work, breathe, and play are subject to enormous variability in air pollutant concentrations. To adequately characterize air quality, measurements must be fast (real-time), scalable, and reliable (with known accuracy, precision, and stability over time). Low-cost AQ sensor technologies offer new opportunities for fast and distributed measurements, but a persistent characterization gap remains when it comes to evaluating sensor performance under realistic environmental sampling conditions. This limits our ability to inform stakeholders about pollution sources and inspire policy makers to address environmental justice air quality issues. In this paper, initial results obtained with a recently developed low-cost air quality sensor system are reported. In this project, data were acquired with the ARISense integrated sensor package over a 4-month time interval during which the sensor system was co-located with a state-operated (Massachusetts, USA) air quality monitoring station equipped with reference instrumentation measuring the same pollutant species. This paper focuses on validating electrochemical sensor measurements of CO, NO, NO 2 , and O 3 . Through the use of High Dimensional Model Representation (HDMR), we show that interference effects derived from changing environmental conditions and the ambient-gas concentration mix encountered at an urban neighborhood site can be effectively modelled for the Alphasense CO-B4, NO-B4, NO2-B43F, and Ox-B421 sensors, improving the credibility of air pollutant measurements made with these sensors.