Field evaluations of newly available “interference-free” monitors for nitrogen dioxide and ozone at near-road and conventional National Ambient Air Quality Standards compliance sites

Leston, Alan R.; Ollison, Will

doi:10.1080/10962247.2017.1339645

Cited by 3 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The 2B Tech Model 211 also uses UV absorption, but instead of a solid-phase scrubber to remove ozone to zero-out interferences (e.g., Hg vapor, water vapor, and polar aromatic VOCs common in the T400) it removes O 3 more selectively by a gas phase titration reaction with NO. This has been shown to reduce interferences from other compounds that absorb at 254 nm by only removing O 3 from the zero air stream (Leston and Ollison 2017). For both FEM instruments, EPA standard operating procedures and data validation were followed.…”

Section: Federal Equivalence Methods (Fem) Instrumentsmentioning

confidence: 99%

Performance evaluation of ozone and particulate matter sensors

DeWitt¹,

Crow²,

Flowers³

2020

Journal of the Air & Waste Management Association

View full text Add to dashboard Cite

As public awareness and concern about air quality grows, companies and researchers have begun to develop small, low-cost sensors to measure local air quality. These sensors have been used in citizen science projects, in distributed networks within cities, and in combination with public health studies on asthma and other air-quality-associated diseases. However, sensor long-term performance under different environmental conditions and pollutant levels is not fully understood. In addition, further evaluation is needed for other long-term performance trends such as performance among sensors of the same model, comparison between sensors from different companies and comparison of sensor data to federal equivalence or reference method (FEM/FRM) measurements. A 10-month evaluation of two popular particulate matter (PM) sensors, Dylos DC1100 and AirBeam, and a popular ozone (O 3 ) sensor, Aeroqual 500, was performed as part of this study. Data from these sensors were compared to each other and to FEM/FRM data and local meteorology. The study took place at the Houston Regional Monitoring (HRM) site 3, located between the Houston Ship Channel and Houston's urban center. PM sensor performance was found to vary in time, with multivariate analysis, binning of data by meteorological parameter, and machine learning techniques able to account for some but not all performance variations. PM type (i.e., size distribution, fiber-flake-spheroid shape and black-brownwhite color) likely played a role in the changing sensor performance. Triplicate individual Aeroqual O 3 sensors tracked reasonably well with the FEM data for most of the measurement period but had irregular periods of O 3 measurement offset. While the FEM data indicated 4 days where ozone levels were above the NAAQS, the Aeroqual ozone sensors indicated a substantially higher number of days, ranging from 9 to 16 for the three sensors.Implications: This paper evaluated the long-term performance of several commercial low-cost sensors (PM 2.5 and ozone) as compared to federal equivalence method (FEM) monitors under a range of meteorological and air quality conditions. PM 2.5 sensors performed well on low humidity days with winds indicative of sea salt or dust PM sources but had poor correlation with FEM data under other conditions. Two types of PM sensors were studied (Dylos 1100 and AirBeam) and data only correlated well between sensors of the same type. Sensor networks with multiple PM sensor types would not be as useful for comparative purposes as sensor networks of the same type. Relative humidity corrections alone did not increase sensor agreement with FEM to acceptable levels, specific information about PM sources and sensor response in the area measured is needed. Low-cost ozone sensors tested (Aeroqual) performed well but were biased high and overestimated days above ozone NAAQS.

show abstract

Section: Federal Equivalence Methods (Fem) Instrumentsmentioning

confidence: 99%

Performance evaluation of ozone and particulate matter sensors

DeWitt¹,

Crow²,

Flowers³

2020

Journal of the Air & Waste Management Association

View full text Add to dashboard Cite

show abstract

“…In the study of Leston and Ollison [64], comparison was made between a thermal-converter instrument and a direct NO 2 -reading photometer at a "near-road" site (15 m from an interstate carriageway edge) in Hartford, USA. On average, hourly averages from the former instrument were 10% higher than for the latter.…”

Section: Field Studiesmentioning

confidence: 99%

Biases in the Measurement of Ambient Nitrogen Dioxide (NO2) by Palmes Passive Diffusion Tube: A Review of Current Understanding

2019

View full text Add to dashboard Cite

Palmes-type passive diffusion tubes (PDTs) are widely used to measure levels of nitrogen dioxide (NO2) in air quality studies. Molecules of NO2 diffuse down the concentration gradient established in the tube by their reactive conversion into nitrite (NO2−) with triethanolamine (TEA) absorbent at the inner end. The relatively low uptake rate for the tube geometry means that exposure-averaged NO2 concentration can be calculated from first principles using the diffusion coefficient, D, for NO2 in air. This review provides a critical assessment of the current understanding of sources and extent of potential bias in NO2 PDT measurements in each of the following methodological stages: preparation of the absorbent; quantification of the absorbed NO2−; deployment in the field; calculation of the exposure-average NO2 concentration from the absorbed NO2−; and assessment of PDT bias through comparison against a chemiluminescence NO2 analyser. The review has revealed strong evidence that PDT measurement of NO2 can be subject to bias from a number of sources. The most significant positive biases are ambient wind flow at the entrance of the tube potentially leading to bias of tens of percent, and within-tube chemical reaction between NO and O3 causing bias up to ~25% at urban background locations, but much less at roadside and rural locations. Sources of potentially significant negative bias are associated with deployment times of several weeks in warm and sunny conditions, and deployments in atmospheres with relative humidities <~75% which causes incomplete conversion of NO2 to NO2−. Evidence suggests that biases (positive or negative) can be introduced by individual laboratories in the PDT preparation and NO2− quantification steps. It is insufficiently acknowledged that the value of D is not accurately known—some controlled chamber experiments can be interpreted as indicating that the value of D currently used is too low, giving rise to a positive bias in PDT-derived NO2 concentration. More than one bias may be present in a given PDT deployment, and because the biases act independently the net effect on PDT NO2 determination is the linear sum of individual biases acting on that deployment. The effect of net bias can be reduced by application of a local “bias adjustment” factor derived from co-locations of PDTs with a chemiluminescence analyser. When this is carried out, the PDT is suitable as an indicative measure of NO2 for air quality assessments. However, it must be recognised that individual PDT deployments may be subject to unknown variation in the bias adjustment factor for that deployment.

show abstract