Articles | Volume 7, issue 10
https://doi.org/10.5194/amt-7-3325-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-3325-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
The next generation of low-cost personal air quality sensors for quantitative exposure monitoring
R. Piedrahita
University of Colorado Boulder, Department of Mechanical Engineering, 427 UCB, 1111 Engineering Drive, Boulder, CO 80309, USA
Y. Xiang
University of Michigan, Department of Electrical Engineering and Computer Science, 2417-E EECS, 1301 Beal Avenue, Ann Arbor, MI 48109, USA
N. Masson
University of Colorado Boulder, Department of Mechanical Engineering, 427 UCB, 1111 Engineering Drive, Boulder, CO 80309, USA
J. Ortega
University of Colorado Boulder, Department of Mechanical Engineering, 427 UCB, 1111 Engineering Drive, Boulder, CO 80309, USA
A. Collier
University of Colorado Boulder, Department of Mechanical Engineering, 427 UCB, 1111 Engineering Drive, Boulder, CO 80309, USA
Y. Jiang
University of Colorado Boulder, Department of Computer Science, 1045 Regent Drive, Boulder, CO 80309, USA
K. Li
University of Colorado Boulder, Department of Electrical Engineering, 425 UCB, 1111 Engineering Drive, Boulder, CO 80309, USA
R. P. Dick
University of Michigan, Department of Electrical Engineering and Computer Science, 2417-E EECS, 1301 Beal Avenue, Ann Arbor, MI 48109, USA
Q. Lv
University of Colorado Boulder, Department of Computer Science, 1045 Regent Drive, Boulder, CO 80309, USA
M. Hannigan
University of Colorado Boulder, Department of Mechanical Engineering, 427 UCB, 1111 Engineering Drive, Boulder, CO 80309, USA
L. Shang
University of Colorado Boulder, Department of Electrical Engineering, 425 UCB, 1111 Engineering Drive, Boulder, CO 80309, USA
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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We implemented a two-step colocation strategy to improve the transferability of sensor calibration models to field conditions, particularly for total volatile organic compound (TVOC) and benzene, toluene, ethylbenzene, and xylene (BTEX) sensors. In our comparison of various calibration models, we found that they generally performed well even as they tended to overpredict baseline concentrations and underpredict peaks. This work provides important insights on TVOC and BTEX sensor calibration.
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Chelsea E. Stockwell, Matthew M. Coggon, Georgios I. Gkatzelis, John Ortega, Brian C. McDonald, Jeff Peischl, Kenneth Aikin, Jessica B. Gilman, Michael Trainer, and Carsten Warneke
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Volatile chemical products are emerging as a large source of petrochemical organics in urban environments. We identify markers for the coatings category by linking ambient observations to laboratory measurements, investigating volatile organic compound (VOC) composition, and quantifying key VOC emissions via controlled evaporation experiments. Ingredients and sales surveys are used to confirm the prevalence and usage trends to support the assignment of water and solvent-borne coating tracers.
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