Examining spatiotemporal variability of urban particulate matter and application of high-time resolution data from a network of low-cost air pollution sensors-Reference-Cited by-同舟云学术

Examining spatiotemporal variability of urban particulate matter and application of high-time resolution data from a network of low-cost air pollution sensors

Published:2019-09 Issue: Volume:213 Page:579-584
ISSN:1352-2310
Container-title:Atmospheric Environment
language:en
Short-container-title:Atmospheric Environment

Author:

Feinberg Stephen Neil,Williams Ron,Hagler Gayle,Low Judy,Smith Larry,Brown Ryan,Garver Daniel,Davis Michael,Morton Michael,Schaefer Joe,Campbell John

Funder

Research Participation Program at the National Risk Management Research Laboratory

Environmental Protection Agency

Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and EPA

Publisher

Elsevier BV

Subject

Atmospheric Science,General Environmental Science

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4. Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado;Feinberg;Atmos. Meas. Tech.,2018

5. A distributed network of low cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi’an, China;Gao;Environ. Pollut.,2015

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