Assessing the distributional characteristics of PM10, PM2.5, and PM1 exposure profile produced and propagated from a construction activity

Cheriyan, Daniel; Hyun, Kim Young; Jaegoo, Han; Choi, Ji Min

doi:10.1016/j.jclepro.2020.124335

Cited by 26 publications

(15 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The R pre of PM 2.5 and SO 2 in P3 at the transport sites were 42.3% and 54.4%, respectively, which was higher than those at other site types. Notably, PM 10 had the most significant relative change at the urban sites, due to the limitations imposed on the transportation and construction industries ( Zhang et al., 2017 ; Cheriyan et al., 2020 ).…”

Section: Resultsmentioning

confidence: 99%

Changes in air pollutants during the COVID-19 lockdown in Beijing: Insights from a machine-learning technique and implications for future control policy

Hu¹,

Pan²,

He³

et al. 2021

Atmospheric and Oceanic Science Letters

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Changes in air pollutants during the COVID-19 lockdown in Beijing: Insights from a machine-learning technique and implications for future control policy

Hu¹,

Pan²,

He³

et al. 2021

Atmospheric and Oceanic Science Letters

View full text Add to dashboard Cite

“…Smaller particles have different characteristics than larger ones, i.e., different settlements and distributional characteristics, physicochemical properties, toxicity, emission, impact on human health, health risk, and others [7][8][9]35]. Similarly, this reasoning should be extended to other PM fractions, confirming, therefore, that the more details investigated of the different PM sizes, the more information is reached for more effective monitoring and controls [22,59].…”

Section: Monitoring Of Suspended Particlesmentioning

confidence: 84%

“…The sampling period was 24 Systematic experimental assessments were carried out during construction activity, concrete mixing activity in an area of 3 × 4 m, using a location-based PM monitoring approach. Three PM monitoring points were installed (Alphasenses sensors, with 2 s sampling times) and arranged between them (horizontal distances of 1 m and 1.5 m and vertical distances of 0.8 m and 1.3 m) and at an angle of 120 This study adopted a location-based real-time PM monitoring system proposed by Cheriyan et al [22] with Alphasense OPC-N3 sensors. The authors also installed the Hexoskin wearable monitor to identify (IR) inhalation rate real-time variation.…”

Section: London Englandmentioning

confidence: 99%

“…In addition to studies in construction sites under local conditions, Cheriyan et al [22,23] carried out a series of laboratory experiments to evaluate the propagation of the different PM sizes (PM 10 , PM 2.5 , and PM 1 ) away from a construction source. The authors argued that a location-based real-time PM monitoring system could provide accurate measurements, as it considers the distributional characteristics of the different PM sizes [22,23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Araújo

Costa

2022

Sustainability

View full text Add to dashboard Cite

Studies on particulate matter (PM) from construction activities are still at an early stage. Thus, there is still no consensus on standardized experimental methods for monitoring PM in construction sites, which impedes the advancement of knowledge on this subject. This work proposes guidelines for measuring and monitoring the concentration of suspended PM and the annoyance generated by sedimented particles on construction sites in urban areas. These guidelines aim to reduce the variability and uncertainties that exist during the PM sampling processes at construction sites. This study adopts a literature review strategy in order to update the available scientific literature based on empirical evidence obtained in experimental PM studies and relevant documents from government agencies. The proposed guidelines were applied in a study protocol for gravimetric monitoring PM and annoyance tracking generated by sedimented particles using sticky pads. As a result, this article details sampling techniques, procedures, and instruments, focusing on gravimetric sampling, highlighting their characteristics compared to other monitoring approaches. Additionally, it points out a series of parameters for the measurement and monitoring of PM. This paper seeks to support future researchers in this area, inform decision making for experimental sampling, and provide a benchmark for measuring and monitoring PM at construction sites.

show abstract

“…The different particle sizes have different effects on the human body; PM 2.5 is smaller than PM 10 and can therefore penetrate the human cilia and mucus, reach the bronchi and alveoli and then the walls of the bronchioles, and finally interfere with the gas exchange in the lungs. In addition, PM 2.5 is more easily suspend in air, does not settle easily, and interacts with other air pollutants [ 1 , 2 ]. Once inhaled by a human, PM 2.5 can reach the depth of the lungs and even penetrate the alveoli and enter the cardiovascular system.…”

Section: Introductionmentioning

confidence: 99%

Investigating a Potential Map of PM2.5 Air Pollution and Risk for Tourist Attractions in Hsinchu County, Taiwan

Lin

Shih

Lai

et al. 2020

IJERPH

View full text Add to dashboard Cite

In the past few years, human health risks caused by fine particulate matters (PM2.5) and other air pollutants have gradually received attention. According to the Disaster Prevention and Protection Act of Taiwan’s Government enforced in 2017, “suspended particulate matter” has officially been acknowledged as a disaster-causing hazard. The long-term exposure to high concentrations of air pollutants negatively affects the health of citizens. Therefore, the precise determination of the spatial long-term distribution of hazardous high-level air pollutants can help protect the health and safety of residents. The analysis of spatial information of disaster potentials is an important measure for assessing the risks of possible hazards. However, the spatial disaster-potential characteristics of air pollution have not been comprehensively studied. In addition, the development of air pollution potential maps of various regions would provide valuable information. In this study, Hsinchu County was chosen as an example. In the spatial data analysis, historical PM2.5 concentration data from the Taiwan Environmental Protection Administration (TWEPA) were used to analyze and estimate spatially the air pollution risk potential of PM2.5 in Hsinchu based on a geographic information system (GIS)-based radial basis function (RBF) spatial interpolation method. The probability that PM2.5 concentrations exceed a standard value was analyzed with the exceedance probability method; in addition, the air pollution risk levels of tourist attractions in Hsinchu County were determined. The results show that the air pollution risk levels of the different seasons are quite different. The most severe air pollution levels usually occur in spring and winter, whereas summer exhibits the best air quality. Xinfeng and Hukou Townships have the highest potential for air pollution episodes in Hsinchu County (approximately 18%). Hukou Old Street, which is one of the most important tourist attractions, has a relatively high air pollution risk. The analysis results of this study can be directly applied to other countries worldwide to provide references for tourists, tourism resource management, and air quality management; in addition, the results provide important information on the long-term health risks for local residents in the study area.

show abstract

Assessing the distributional characteristics of PM10, PM2.5, and PM1 exposure profile produced and propagated from a construction activity

Cited by 26 publications

References 31 publications

Changes in air pollutants during the COVID-19 lockdown in Beijing: Insights from a machine-learning technique and implications for future control policy

Changes in air pollutants during the COVID-19 lockdown in Beijing: Insights from a machine-learning technique and implications for future control policy

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

Investigating a Potential Map of PM2.5 Air Pollution and Risk for Tourist Attractions in Hsinchu County, Taiwan

Contact Info

Product

Resources

About