Dataset Information

Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study.

ABSTRACT: We designed and built a network of monitors for ambient air pollution equipped with low-cost gas sensors to be used to supplement regulatory agency monitoring for exposure assessment within a large epidemiological study. This paper describes the development of a series of hourly and daily field calibration models for Alphasense sensors for carbon monoxide (CO; CO-B4), nitric oxide (NO; NO-B4), nitrogen dioxide (NO₂; NO2-B43F), and oxidizing gases (OX-B431)-which refers to ozone (O₃) and NO₂. The monitor network was deployed in the Puget Sound region of Washington, USA, from May 2017 to March 2019. Monitors were rotated throughout the region, including at two Puget Sound Clean Air Agency monitoring sites for calibration purposes, and over 100 residences, including the homes of epidemiological study participants, with the goal of improving long-term pollutant exposure predictions at participant locations. Calibration models improved when accounting for individual sensor performance, ambient temperature and humidity, and concentrations of co-pollutants as measured by other low-cost sensors in the monitors. Predictions from the final daily models for CO and NO performed the best considering agreement with regulatory monitors in cross-validated root-mean-square error (RMSE) and R² measures (CO: RMSE = 18 ppb, R² = 0.97; NO: RMSE = 2 ppb, R² = 0.97). Performance measures for NO₂ and O₃ were somewhat lower (NO₂: RMSE = 3 ppb, R² = 0.79; O₃: RMSE = 4 ppb, R² = 0.81). These high levels of calibration performance add confidence that low-cost sensor measurements collected at the homes of epidemiological study participants can be integrated into spatiotemporal models of pollutant concentrations, improving exposure assessment for epidemiological inference.

SUBMITTER: Zuidema C

PROVIDER: S-EPMC8234435 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Typical low-cost electrochemical sensors for ozone (O3) are also highly responsive to nitrogen dioxide (NO2). Consequently, a single sensor's response to O3 is indistinguishable from its response to NO2. Recently, a method for quantifying O3 concentrations became commercially available (Alphasense Ltd., Essex, UK): collocating a pair of sensors, a typical oxidative gas sensor that responds to both O3 and NO2 (model OX-B431) and a second similar sensor that filters O3 and responds only to NO2 (model NO2-B43F). By pairing the two sensors, O3 concentrations can be calculated. We calibrated samples of three NO2-B43F sensors and three OX-B431 sensors with NO2 and O3 exclusively and conducted mixture experiments over a range of 0-1.0 ppm NO2 and 0-125 ppb O3 to evaluate the ability of the paired sensors to quantify NO2 and O3 concentrations in mixture. Although the slopes of the response among our samples of three sensors of each type varied by as much as 37%, the individual response of the NO2-B43F sensors to NO2 and OX-B431 sensors to NO2 and O3 were highly linear over the concentrations studied (R2 ≥ 0.99). The NO2-B43F sensors responded minimally to O3 gas with statistically non-significant slopes of response. In mixtures of NO2 and O3, quantification of NO2 was generally accurate with overestimates up to 29%, compared to O3, which was generally underestimated by as much as 187%. We observed changes in sensor baseline over 4 days of experiments equivalent to 34 ppb O3, prompting an alternate method of calculating concentrations by baseline-correcting sensor signal. The baseline-correction method resulted in underestimates of NO2 up to 44% and decreases in the underestimation of O3 up to 107% for O3. Both methods for calculating gas concentrations progressively underestimated O3 concentrations as the ratio of NO2 signal to O3 signal increased. Our results suggest that paired NO2-B43F and OX-B431 sensors permit quantification of NO2 and O3 in mixture, but that O3 concentration estimates are less accurate and precise than those for NO2.

Dataset Information

Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study.

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