4.6 Article

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

期刊

SENSORS
卷 21, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/s21124214

关键词

low-cost sensors; sensor network; hazardous gases; air pollution; exposure assessment; environmental epidemiology

资金

  1. National Institute for Environmental Health Science (NIEHS) [R56ES026528, P30ES007033]
  2. NIEHS
  3. National Institute on Aging (NIA) [R01ES026187]
  4. University of Washington's Biostatistics, Epidemiology, and Bioinformatics Training in Environmental Health (BEBTEH) [T32ES015459]

向作者/读者索取更多资源

This study developed a network of low-cost gas sensors for ambient air pollution monitoring to supplement regulatory agency monitoring in a large epidemiological study. The sensors were calibrated for carbon monoxide, nitric oxide, nitrogen dioxide, and oxidizing gases, with models accounting for sensor performance, environmental conditions, and pollutant concentrations. The daily models for carbon monoxide and nitric oxide showed the best performance, with high levels of calibration performance adding confidence in integrating low-cost sensor measurements for improved exposure assessment.
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 (O-3) 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 R-2 measures (CO: RMSE = 18 ppb, R-2 = 0.97; NO: RMSE = 2 ppb, R-2 = 0.97). Performance measures for NO2 and O-3 were somewhat lower (NO2: RMSE = 3 ppb, R-2 = 0.79; O-3: RMSE = 4 ppb, R-2 = 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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据