Exposure to polycyclic aromatic hydrocarbons in atmospheric PM1.0 of urban environments: Carcinogenic and mutagenic respiratory health risk by age groups

Agudelo-Castañeda, Dayana Milena; Teixeira, Elba Calesso; Schneider, Ismael L.; Lara, Sheila Rincón; Silva, Luis

doi:10.1016/j.envpol.2017.01.075

Cited by 169 publications

(60 citation statements)

References 78 publications

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“…This cluster is highly associated with NO x and PM 10 , confirming that incomplete combustion of biomass also may produce both gaseous and particulate air pollution ( Table 2). The highest occurrence was observed in May-July and at night, implying a low MLH so UFP accumulated (Agudelo-Castañeda et al, 2017). One of the lowest wind speeds also points to nocturnal accumulation of urban background particles.…”

Section: Cluster 2regional-urban Background Particlesbiomass Burning mentioning

confidence: 92%

Cluster analysis of urban ultrafine particles size distributions

Agudelo-Castañeda

Teixeira

Braga

et al. 2019

Atmospheric Pollution Research

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Measurements of particle size distribution was made in one location of an urban area in the period January-September/2015 in order to understand the sources and mechanisms influencing ultrafine particle (UFP) number concentrations (PNC 2.5-250) using a Scanning Mobility Particle Sizer Spectrometer (SMPS). kmeans cluster analysis was applied to interpret the sources, temporal and spatial trends of UFP. Eight clusters were obtained. Main PSD patterns of each cluster, mean concentration of other air pollutants tracing specific sources and processes, and that of meteorological variables, as well as the hourly and seasonal frequencies of occurrence were used to support the interpretation of their origin. Thus, clusters were attributed to traffic rush hours, midday summer new particle formation, diurnal new particle formation and growth, growth of nucleated and other urban particles, urban background, regional and urban background and regional and urban background on cold nights. Many PSDs of the clusters were dominated by nucleation mode particles: midday nucleated fresh particles, photochemically induced (NPF); diurnal nucleation episodes (NPF2); growth of nucleated particles in nocturnal aging (GNPF). Origins of the clusters were related to local/regional sources (mostly traffic and biomass burning), atmospheric processes (photochemical formation and growth) and urban/regional background. Results clearly shows that traffic is a major UFP source in nucleation mode and occurred in higher concentrations in winter (08:00 to 12:00 h) during traffic rush hours, and at night. Photochemical nucleation occurred with a relatively low frequency but yielding very high PNC.

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Section: Cluster 2regional-urban Background Particlesbiomass Burning mentioning

confidence: 92%

Cluster analysis of urban ultrafine particles size distributions

Agudelo-Castañeda

Teixeira

Braga

et al. 2019

Atmospheric Pollution Research

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“…PM 1 is the smallest detectable fraction of PM is possibly the most dangerous in children as it can easily by-pass air ltration systems and travel through nostrils, into lungs and blood vessels blood streams and by-pass air-ltration systems (Zajusz-Zubek et al, 2017). Exposure to PM 1 , mostly outdoors have been linked to health outcome ranging from metabolic disorders, cancers, respiratory health disorders across health groups (Agudelo-Castañeda et al, 2017;Zajusz-Zubek et al, 2017;Yang et al, 2018). The link of PM 1 to childhood pneumonia remains largely unexplored.…”

Section: Introductionmentioning

confidence: 99%

Association Between Specific Indoor Air Pollutants and Pneumonia Episodes in Children Under Five in Abuja, Nigeria: A Case-control Study

Adaji

Clifford

Gibson

et al. 2020

Preprint

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Background: Pneumonia causes most death in children under five globally. Indoor air pollution has been reported to increase the risk of children to pneumonia. ObjectiveTo investigate the association between specific indoor air pollutants and pneumonia episodes in children under five.MethodsUsing a case-control study design, we compared exposure of cases and controls to specific pollutants (PM2.5, CO, BC and PM1), using battery operated aerosol monitors. Data was analysed using Wilcoxon signed-rank test.ResultsThe mean PM2.5 was higher in controls compared to cases. PM2.5 highest mean recorded for controls was 177 µg/m3. There was a significant difference between cases and controls for 10 hours (p-value 0.0147), 15 hours (p-value 0.0111) and 20-24 hours (p-value 0.0296) for PM2.5. No significant difference in CO concentration between cases and controls, the highest CO mean concentration recorded being 2930 µg/m3. Similarly, PM1 was consistently higher in controls compared to cases. However, this difference was not significant from exposure to PM1 between cases and controls (P-value>0.05), with the highest PM1 mean concentration recorded being 91 µg/m3. There was a significant difference (p-value 0.0260) in exposure to Black Carbon between cases and controls. BC was higher in households of cases compared to controls, with the mean average of BC for cases 4350 µg/m3 and controls 4126 µg/m3. In this study, BC is positively associated with a pneumonia episode. We also report the importance of unmodifiable and behaviourally modifiable factors on pneumonia episode in children.Discussion: In conclusion, we show that children present during cooking, number of available windows and MUAC increased the likelihood of a pneumonia episode. We recommend household level behaviour changes and targeted IMCI including early effective detection and treatment of childhood pneumonia particularly in high pollution areas in Nigeria.

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“…Amongst important constituents of petroleum like alkanes and alkenes, polycyclic aromatic hydrocarbons (PAHs) have merited special global attention for posing great threat to humans' and environmental health as well as for the ubiquity of these contaminants sources. 5 PAHs comprise a group of thousands of organic compounds containing 2-7 fused aromatic rings in different configurations, originated from both natural and anthropogenic activities and which occurs in the ecosystem as colorless, white or pale yellow solids. 6,7 Usually, PAHs mainly arise from natural incomplete combustion processes in forests and brush fires or from combustion sources provoked by human action, entering the soil, water and air as a harm contaminant.…”

Section: Introductionmentioning

confidence: 99%

Application of biosensors in the petrochemical industry: a mini review on the sensing platforms for polycyclic aromatic hydrocarbons detection

Vasconcellos¹,

Lins²,

Faria³

2019

IJBSBE

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The increased awareness of the hazardous effects of polycyclic aromatic hydrocarbons (PAHs) has been the target of several studies in the current literature. PAHs are a group of organic molecules derived from petroleum that contains from two to seven aromatic rings in their structure that have been largely emitted to the environment from natural but especially anthropogenic sources. In this research, we reviewed the main aspects concerning the effects of PAHs in the environment with a special focus on the biosensing platforms recently developed to detect these pollutants. Herein, we reported the use of biosensors as an alternative to the expensive, time-consuming and laborious traditional techniques commonly employed to detect PAHs. Most of the examined literature referred to the use of antibodies and DNA as biological elements to fabricate the sensors, and the electrochemical and optical mechanisms comprised the preferred transduction techniques for this purpose. Among the 16 PAHs present in the priority list established by the United States Environmental Protection Agency (US EPA) with respect to the toxicity and abundance, B[a]P was the pollutant most studied by researchers in the field of biosensors, who found limits of detection in the order of micro molar. Overall, the reviewed biosensors presented significant promise for the reliable, selective and sensitive detection of PAHs in the ecosystem.

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Exposure to polycyclic aromatic hydrocarbons in atmospheric PM1.0 of urban environments: Carcinogenic and mutagenic respiratory health risk by age groups

Cited by 169 publications

References 78 publications

Cluster analysis of urban ultrafine particles size distributions

Cluster analysis of urban ultrafine particles size distributions

Association Between Specific Indoor Air Pollutants and Pneumonia Episodes in Children Under Five in Abuja, Nigeria: A Case-control Study

Application of biosensors in the petrochemical industry: a mini review on the sensing platforms for polycyclic aromatic hydrocarbons detection

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