Dataset Information

Evaluation and Field Calibration of a Low-Cost Ozone Monitor at a Regulatory Urban Monitoring Station.

ABSTRACT: The performance of a low cost ozone monitor (Aeroqual Series 500 portable gas monitors using a metal oxide sensor for ozone; model OZL) was assessed under field conditions. Ten ozone monitors were calibrated under clean-air laboratory conditions and controlled ozone concentrations of 5 to 100 ppb. Good linearity and response were obtained relative to a research-grade ozone monitor. One monitor was co-located at a regulatory air quality monitoring station that uses a U.S. federal equivalent method (FEM) ozone analyzer. Raw data from the Aeroqual monitor collected over 4 months (June-October) at a 10-minute time-resolution, showed good agreement (r2=0.83) with the FEM values but with an overestimation of ~12%. Data were averaged to different time resolutions; 1 h time averaged concentrations showed the best fit with the FEM results (r2=0.87). Data analyses suggested the potential of interferences due to temperature, relative humidity, nitrogen oxides, and volatile organic compounds. Correction models using temperature, humidity, and nitrogen dioxide (NO2) were tested to relate the monitor concentrations to the FEM values. Temperature and humidity were two readily available variables. The model (#3) that added NO2 did not provide a substantial improvement in the fit. Thus, the models with only temperature and humidity can be easily developed by any user. The best model explained 91% of the variance and showed statistically significant improvement of the goodness of fits as well as decreased influence of the interfering variables on the diurnal and weekly patterns. The correction models were also able to lower the effect of seasonal temperature changes, allowing the use of the monitors over long-term sampling campaigns. Thus, the Aeroqual ozone monitor can return "FEM-like" concentrations after appropriate corrections. Data provided by a network of monitors could provide intra-urban spatial variations in ozone concentrations and provide more accurate human exposure assessments by reducing exposure misclassification.

SUBMITTER: Masiol M

PROVIDER: S-EPMC7518407 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluation and Field Calibration of a Low-Cost Ozone Monitor at a Regulatory Urban Monitoring Station.

Masiol Mauro M Squizzato Stefania S Chalupa David D Rich David Q DQ Hopke Philip K PK

Aerosol and air quality research 20180727 8

The performance of a low cost ozone monitor (Aeroqual Series 500 portable gas monitors using a metal oxide sensor for ozone; model OZL) was assessed under field conditions. Ten ozone monitors were calibrated under clean-air laboratory conditions and controlled ozone concentrations of 5 to 100 ppb. Good linearity and response were obtained relative to a research-grade ozone monitor. One monitor was co-located at a regulatory air quality monitoring station that uses a U.S. federal equivalent metho ...[more]

PMID: 32983236

Similar Datasets

Project description:Low-cost air pollution monitors are increasingly being deployed to enrich knowledge about ambient air-pollution at high spatial and temporal resolutions. However, unlike regulatory-grade (FEM or FRM) instruments, universal quality standards for low-cost sensors are yet to be established and their data quality varies widely. This mandates thorough evaluation and calibration before any responsible use of such data. This study presents evaluation and field-calibration of the PM2.5 data from a network of low-cost monitors currently operating in Baltimore, MD, which has only one regulatory PM2.5 monitoring site within city limits. Co-location analysis at this regulatory site in Oldtown, Baltimore revealed high variability and significant overestimation of PM2.5 levels by the raw data from these monitors. Universal laboratory corrections reduced the bias in the data, but only partially mitigated the high variability. Eight months of field co-location data at Oldtown were used to develop a gain-offset calibration model, recast as a multiple linear regression. The statistical model offered substantial improvement in prediction quality over the raw or lab-corrected data. The results were robust to the choice of the low-cost monitor used for field-calibration, as well as to different seasonal choices of training period. The raw, lab-corrected and statistically-calibrated data were evaluated for a period of two months following the training period. The statistical model had the highest agreement with the reference data, producing a 24-hour average root-mean-square-error (RMSE) of around 2 μg m-3. To assess transferability of the calibration equations to other monitors in the network, a cross-site evaluation was conducted at a second co-location site in suburban Essex, MD. The statistically calibrated data once again produced the lowest RMSE. The calibrated PM2.5 readings from the monitors in the low-cost network provided insights into the intra-urban spatiotemporal variations of PM2.5 in Baltimore.

Project description:Soil volumetric water content ( V W C ) is a vital parameter to understand several ecohydrological and environmental processes. Its cost-effective measurement can potentially drive various technological tools to promote data-driven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available V W C sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two low-cost capacitive sensors-SMEC300 and SM100-manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very low-cost resistive sensors-the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuru-were tested for performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed in-house and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their precision performance, i.e., the precision performance largely follows sensor costs. The other aspects of sensor performance do not necessarily follow sensor costs. The low-cost capacitive sensors were more accurate than manufacturer specifications, and could match the performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate ( M A E , R M S E , and R A E of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multi-purpose sensing capabilities. The less-expensive SM100 sensor had a better accuracy ( M A E , R M S E , and R A E of 1.67%, 2.36% and 0.21 respectively) but poorer precision than the SMEC300. However, it was established as a robust, field ready, low-cost sensor due to its more consistent performance in soils (particularly the field soil) and superior performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate ( M A E , R M S E , and R A E of 3.51%, 5.21% and 0.37 respectively) than YL69 ( M A E , R M S E , and R A E of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very low-cost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low- and very low-cost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems.

Dataset Information

Evaluation and Field Calibration of a Low-Cost Ozone Monitor at a Regulatory Urban Monitoring Station.

Publications

Evaluation and Field Calibration of a Low-Cost Ozone Monitor at a Regulatory Urban Monitoring Station.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets