Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring
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Carl Malings | Naomi Zimmerman | L. Kara | Naomi Zimmerman | A. Presto | Srini Kumar | A. Hauryliuk | C. Malings | Rebecca Tanzer | Albert A. Presto | Rebecca Tanzer | Aliaksei Hauryliuk | Sriniwasa P. N. Kumar | Levent B. Kara
[1] E. Seto,et al. The Imperial County Community Air Monitoring Network: A Model for Community-based Environmental Monitoring for Public Health Action , 2017, Environmental health perspectives.
[2] Olalekan Popoola,et al. Development of a baseline-temperature correction methodology for electrochemical sensors and its implications for long-term stability , 2016 .
[3] Michael Brauer,et al. Within-urban variability in ambient air pollution: Comparison of estimation methods , 2008 .
[4] John W. Cherrie,et al. How Sensors Might Help Define the External Exposome , 2017, International journal of environmental research and public health.
[5] Gb Stewart,et al. The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks , 2013 .
[6] Michael Hannigan,et al. Quantification Method for Electrolytic Sensors in Long-Term Monitoring of Ambient Air Quality , 2015, Sensors.
[7] Allen L. Robinson,et al. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring , 2018 .
[8] David Balshaw,et al. Assessing the Exposome with External Measures: Commentary on the State of the Science and Research Recommendations , 2017, Annual review of public health.
[9] Daniel Krewski,et al. Spatial analysis of air pollution and mortality in California. , 2013, American journal of respiratory and critical care medicine.
[10] E. Snyder,et al. The changing paradigm of air pollution monitoring. , 2013, Environmental science & technology.
[11] Teuvo Kohonen,et al. An introduction to neural computing , 1988, Neural Networks.
[12] R. Burnett,et al. Spatial Analysis of Air Pollution and Mortality in Los Angeles , 2005, Epidemiology.
[13] Evan Coffey,et al. Intra-urban spatial variability of surface ozone in Riverside, CA: viability and validation of low-cost sensors , 2018 .
[14] L. Spinelle,et al. Sensors and Actuators B: Chemical Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide (cid:2) , 2022 .
[15] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[16] Kurt Hornik,et al. Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.
[17] Jonathan P. Franklin,et al. Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments , 2017 .
[18] D. Niemeier,et al. Near-roadway air quality: synthesizing the findings from real-world data. , 2010, Environmental science & technology.
[19] D. Worsnop,et al. Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements , 2017 .
[20] A. Robinson,et al. Characterizing the spatial variation of air pollutants and the contributions of high emitting vehicles in Pittsburgh, PA. , 2014, Environmental science & technology.
[21] Alena Bartonova,et al. Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates? , 2017, Environment international.
[22] Geb Thomas,et al. Evaluation of low-cost electro-chemical sensors for environmental monitoring of ozone, nitrogen dioxide, and carbon monoxide , 2018, Journal of occupational and environmental hygiene.
[23] A. Lewis,et al. Clustering approaches to improve the performance of low cost air pollution sensors. , 2017, Faraday discussions.
[24] Ian T. Nabney,et al. Netlab: Algorithms for Pattern Recognition , 2002 .