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Sensors for Environment Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 10810

Special Issue Editor


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Guest Editor
Faculty of Food Engineering, Tourism and Environmental Protection, “Aurel Vlaicu” University of Arad, Arad, Romania
Interests: environmental engineering; electrochemistry; biosensors; biotechnologies in environmental protection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

The development of the industrial activity related to the growth of the world population has contributed to the release of a number of hazardous pollutants in the environment. Therefore, as a consequence of the presence of these toxic chemicals in the environment, it is mandatory to develop fast, simple, easy-to-use, portable, and cost-effective devices for their detection. Enzyme-based sensors are good candidates for the detection of a minimal level of pollutants.

This Special Issue is addressed to all types of enzyme-based sensors designed for environmental monitoring.

Prof. Dr. Florentina-Daniela Munteanu
Guest Editor

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Keywords

  • • Enzyme-based sensors
  • • Environmental monitoring
  • • Toxic compounds
  • • Enzymes
  • • Pollutants
  • • Transducers
  • • Electrode materials
  • • Methods of detection.

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Published Papers (1 paper)

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Research

17 pages, 1415 KiB  
Article
Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke
by Amara L. Holder, Anna K. Mebust, Lauren A. Maghran, Michael R. McGown, Kathleen E. Stewart, Dena M. Vallano, Robert A. Elleman and Kirk R. Baker
Sensors 2020, 20(17), 4796; https://doi.org/10.3390/s20174796 - 25 Aug 2020
Cited by 66 | Viewed by 8999
Abstract
Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public as a source of air quality information during wildfires, although [...] Read more.
Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public as a source of air quality information during wildfires, although their performance during smoke impacted conditions has not been thoroughly evaluated. We collocated three types of low-cost fine PM (PM2.5) sensors with reference instruments near multiple fires in the western and eastern United States (maximum hourly PM2.5 = 295 µg/m3). Sensors were moderately to strongly correlated with reference instruments (hourly averaged r2 = 0.52–0.95), but overpredicted PM2.5 concentrations (normalized root mean square errors, NRMSE = 80–167%). We developed a correction equation for wildfire smoke that reduced the NRMSE to less than 27%. Correction equations were specific to each sensor package, demonstrating the impact of the physical configuration and the algorithm used to translate the size and count information into PM2.5 concentrations. These results suggest the low-cost sensors can fill in the large spatial gaps in monitoring networks near wildfires with mean absolute errors of less than 10 µg/m3 in the hourly PM2.5 concentrations when using a sensor-specific smoke correction equation. Full article
(This article belongs to the Special Issue Sensors for Environment Monitoring)
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