Measurement and Monitoring of Particulate Matter in Construction Sites: Guidelines for Gravimetric Approach

Araújo, Ingrid Priscylla Silva; Costa, Dayana Bastos

doi:10.3390/su14010558

Cited by 8 publications

(3 citation statements)

References 45 publications

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“…In this study, mass concentrations of PM2.5 collected from the study area were measured and compared with the guideline of WHO of PM2.5 concentrations. The limiting values stated by WHO (2005) guideline for PM2.5 concentration in air are 10 µg/m 3 as annual limit and 25 µg/m3 as twenty -four hours limit [1,15]. Furthermore, our study measured the black carbon concentrations in PM2.5 samples and results were compared with some international studies.…”

Section: Introductionmentioning

confidence: 88%

Concentration of Fine Particulate Matter (PM\(_{2.5}\)) and Black Carbon (Bc) in Aerosol Samples in Al-Zubairy Area in Sana’a, Yemen

Abdul-Rahim

Al-Sowaidi

Eadan

2022

Electron. J. Univ. Aden Basic Appl. Sci.

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This research aims to study the air pollution due to fine Particulate Matter of radius less than 2.5µm (PM2.5) and Black Carbon concentration (BC) in air samples. Aerosol PM2.5 samples were collected from the rooftop of the National Oncology Center site in Al-Zubairy area in Sana’a Yemen. A Microprocessor Controlled Aerosol Sampling device ISAP1050e (Gerhard Schulze Automation Engineering, Germany company) was used to collect samples. The mass concentration of PM2.5 of collected samples ranged from 14.27 to 159.09 µg/m3 with an average of 32.66µg/m3. The PM2.5 results were compared with the World Health Organization (WHO) 2005 guideline of PM2.5 concentration in air. Statistical analysis showed a positive correlation between PM2.5 concentrations and temperature for both fall and summer samples. However, analysis showed a positive correlation between PM2.5 concentrations and relative humidity for fall samples and a negative correlation for summer samples. The black carbon (BC) concentrations in PM2.5 samples were measured using a Smoke Stain Reflectometer (SSR) device. The BC concentration ranged from 1.84 to 3.90 µg/m3 with an average of 2.90 µg/m3. The BC results were compared with some international reported results. The Air Quality Index (AQI) of 78.95% of PM2.5 concentrations was higher than the standard limit (AQI < 100) developed by the United States Environmental Protection Agency (EPA).

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Section: Introductionmentioning

confidence: 88%

Concentration of Fine Particulate Matter (PM\(_{2.5}\)) and Black Carbon (Bc) in Aerosol Samples in Al-Zubairy Area in Sana’a, Yemen

Abdul-Rahim

Al-Sowaidi

Eadan

2022

Electron. J. Univ. Aden Basic Appl. Sci.

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“…This method has been widely used because of its accuracy, but the drawbacks of this method are its inefficiency and high cost. [13][14][15] Optical particulate matter sensors are either based on light scattering or 2D matrix cameras. The sensing signal for scattering-based sensors is represented by the light intensity change, while the sensing signal for the camera-based sensors requires an image processing process.…”

Section: Introductionmentioning

confidence: 99%

Selective Detection of Functionalized Carbon Particles based on Polymer Semiconducting and Conducting Devices as Potential Particulate Matter Sensors

Song,

Chen,

Jiang

et al. 2023

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This paper reports a new mechanism for particulate matter detection and identification. Three types of carbon particles are synthesized with different functional groups to mimic the real particulates in atmospheric aerosol. After exposing polymer‐based organic devices in organic field effect transistor (OFET) architectures to the particle mist, the sensitivity and selectivity of the detection of different types of particles are shown by the current changes extracted from the transfer curves. The results indicate that the sensitivity of the devices is related to the structure and functional groups of the organic semiconducting layers, as well as the morphology. The predominant response is simulated by a model that yielded values of charge carrier density increase and charge carriers delivered per unit mass of particles. The research points out that polymer semiconductor devices have the ability to selectively detect particles with multiple functional groups, which reveals a future direction for selective detection of particulate matter.

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“…[18,21]. Some studies have evaluated the PM10-increasing effect of the transportation infrastructure related to, e.g., the construction of new motorways [22,23]. Studies on real-time air quality monitoring and the modelling of traffic-related pollutant emissions [24][25][26] also highlight the importance of the effect of road density (RD) on AQ estimations [24,[27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Connection between the Spatial Characteristics of the Road and Railway Networks and the Air Pollution (PM10) in Urban–Rural Fringe Zones

2022

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Atmospheric particulate matter (PM10) is one of the most important pollutants for human health, and road transport could be a major anthropogenic source of it. Several research studies have shown the impact of roads on the air quality in urban areas, but the relationship between road and rail networks and ambient PM10 concentrations has not been well studied, especially in suburban and rural landscapes. In this study, we examined the link between the spatial characteristics of each road type (motorway, primary road, secondary road, and railway) and the annual average PM10 concentration. We used the European 2931 air quality (AQ) station dataset, which is classified into urban, suburban, and rural landscapes. Our results show that in urban and rural landscapes, the spatial characteristics (the density of the road network and its distance from the AQ monitoring points) have a significant statistical relationship with PM10 concentrations. According to our findings from AQ monitoring sites within the urban landscape, there is a significant negative relationship between the annual average PM10 concentration and the density of the railway network. This result can be explained by the driving wind generated by railway trains (mainly electric trains). Among the road network types, all road types in the urban landscape, only motorways in the suburban landscape, and only residential roads in the rural landscape have a significant positive statistical relationship with the PM10 values at the AQ monitoring points. Our results show that in the suburban zones, which represent the rural–urban fringe, motorways have a strong influence on PM-related air pollution. In the suburban areas, the speed of vehicles changes frequently near motorways and intersections, so higher traffic-related PM10 emission levels can be expected in these areas. The findings of this study can be used to decrease transportation-related environmental conflicts related to the air quality in urban, urban–rural fringe, and rural (agricultural) landscapes.

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Measurement and Monitoring of Particulate Matter in Construction Sites: Guidelines for Gravimetric Approach

Cited by 8 publications

References 45 publications

Concentration of Fine Particulate Matter (PM\(_{2.5}\)) and Black Carbon (Bc) in Aerosol Samples in Al-Zubairy Area in Sana’a, Yemen

Concentration of Fine Particulate Matter (PM\(_{2.5}\)) and Black Carbon (Bc) in Aerosol Samples in Al-Zubairy Area in Sana’a, Yemen

Selective Detection of Functionalized Carbon Particles based on Polymer Semiconducting and Conducting Devices as Potential Particulate Matter Sensors

Connection between the Spatial Characteristics of the Road and Railway Networks and the Air Pollution (PM10) in Urban–Rural Fringe Zones

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