Monitoring VOCs in atmospheric air I. On-line gas analyzers

Król, Sylwia; Zabiegała, Bożena; Namieśnik, Jacek

doi:10.1016/j.trac.2010.05.007

Cited by 63 publications

(29 citation statements)

References 39 publications

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“…In turn, benzene, ethylbenzene, toluene, and o-, m-, and p-xylenes (BTEX) are also included in the Clean Air Act (USA) of 1990, according to the Agency for Toxic Substances and Disease Registry. Moreover, VOCs also play a significant role in the formation of tropospheric O 3 and urban aerosols precursors (Król et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Volatile organic compounds and bioaerosols in the vicinity of a municipal waste organic fraction treatment plant. Human health risks

Vilavert

Nadal

Figueras

et al. 2011

Environ Sci Pollut Res

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Section: Introductionmentioning

confidence: 99%

Volatile organic compounds and bioaerosols in the vicinity of a municipal waste organic fraction treatment plant. Human health risks

Vilavert

Nadal

Figueras

et al. 2011

Environ Sci Pollut Res

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“…Throughout Europe, about one thousand five hundred air monitoring stations have been deployed to control air pollution on a large scale, providing coarse-granularity pollution levels for most relevant cities. Despite the fact that this number may seem large, when focusing on a specific city we find that these stations are quite scarce, failing to provide detailed pollution levels on a per-neighborhood basis [1]. For instance, in Valencia, the third largest city in Spain, there are only 5 monitoring stations, as shown Figure 1.…”

Section: Introductionmentioning

confidence: 90%

An Architecture Offering Mobile Pollution Sensing with High Spatial Resolution

et al. 2016

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Mobile sensing is becoming the best option to monitor our environment due to its ease of use, high flexibility, and low price. In this paper, we present a mobile sensing architecture able to monitor different pollutants using low-end sensors. Although the proposed solution can be deployed everywhere, it becomes especially meaningful in crowded cities where pollution values are often high, being of great concern to both population and authorities. Our architecture is composed of three different modules: a mobile sensor for monitoring environment pollutants, an Android-based device for transferring the gathered data to a central server, and a central processing server for analyzing the pollution distribution. Moreover, we analyze different issues related to the monitoring process: (i) filtering captured data to reduce the variability of consecutive measurements; (ii) converting the sensor output to actual pollution levels; (iii) reducing the temporal variations produced by mobile sensing process; and (iv) applying interpolation techniques for creating detailed pollution maps. In addition, we study the best strategy to use mobile sensors by first determining the influence of sensor orientation on the captured values and then analyzing the influence of time and space sampling in the interpolation process.

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“…Detection and analysis of flammable liquids have been developed due to strong demand in many fields, especially in the field of public safety [5][6][7]. The ideal flammable liquid detectors for buses need to have the following characteristics: a recognition model to identify liquid species to prevent false positives, a quantitative model to analyze danger levels, and a temperature controller to manage temperature changes inside the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Development of Electronic Nose for Qualitative and Quantitative Monitoring of Volatile Flammable Liquids

Wang

Zheng

et al. 2020

Sensors

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A real-time electric nose (E-nose) with a metal oxide sensor (MOS) array was developed to monitor 5 highly flammable liquids (ethanol, tetrahydrofuran, turpentine, lacquer thinner, and gasoline) in this work. We found that temperature had a significant impact on the test results and temperature control could efficiently improve the performance of our E-nose. The results of our qualitative analysis showed that principal component analysis (PCA) could not efficiently distinguish these samples compared to a back-propagation artificial neural network (BP-ANN) which had a 100% accuracy rate on the test samples. Quantitative analysis was performed by regression analysis and the average errors were 9.1%–18.4%. In addition, through anti-interference training, the E-nose could filter out the potential false alarm caused by mosquito repellent, perfume and hair jelly.

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Monitoring VOCs in atmospheric air I. On-line gas analyzers

Cited by 63 publications

References 39 publications

Volatile organic compounds and bioaerosols in the vicinity of a municipal waste organic fraction treatment plant. Human health risks

Volatile organic compounds and bioaerosols in the vicinity of a municipal waste organic fraction treatment plant. Human health risks

An Architecture Offering Mobile Pollution Sensing with High Spatial Resolution

Development of Electronic Nose for Qualitative and Quantitative Monitoring of Volatile Flammable Liquids

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