ArticleInternational journal of environmental research and public health2022
Evaluating the Performance of Low-Cost Air Quality Monitors in Dallas, Texas.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 46 citations in OpenAlex.
- Expert perspectives on exposure-response functions for urban health policy: Lessons from a UBDPolicy workshop.Environmental research · 2026Review
- Air Sensor Network Analysis Tool: R-Shiny Application.Atmosphere · 2025Article
- The use of public spatial databases in risk analysis: A US-oriented tutorial.Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- Efficient field correction of low-cost particulate matter sensors using machine learning, mixed multiplicative/additive scaling and extended calibration inputs.Scientific reports · 2025Article
- Air Pollution Monitoring Using Cost-Effective Devices Enhanced by Machine Learning.Sensors (Basel, Switzerland) · 2025Article
- Evaluation of Long-Term Performance of Six PMSensors (Basel, Switzerland) · 2025Article
- A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.Sensors (Basel, Switzerland) · 2025Article
- Challenges and Opportunities in Calibrating Low-Cost Environmental Sensors.Sensors (Basel, Switzerland) · 2024Review
- Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring.Sensors (Basel, Switzerland) · 2024Article
- Application of an Ultra-Low-Cost Passive Sampler for Light-Absorbing Carbon in Mongolia.Sensors (Basel, Switzerland) · 2023Article
- Optimizing Urban Air Pollution Detection Systems.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The emergence of low-cost air quality sensors may improve our ability to capture variations in urban air pollution and provide actionable information for public health. Despite the increasing popularity of low-cost sensors, there remain some gaps in the understanding of their performance under real-world conditions, as well as compared to regulatory monitors with high accuracy, but also high cost and maintenance requirements. In this paper, we report on the performance and the linear calibration of readings from 12 commercial low-cost sensors co-located at a regulatory air quality monitoring site in Dallas, Texas, for 18 continuous measurement months. Commercial AQY1 sensors were used, and their reported readings of O
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.