PM2.5-PAHs and PM10-PAHs at roadside environment: levels, meteorological impact, source apportionment, and health risks

2022 ◽  
Author(s):  
Qijun Zhang ◽  
Lei Yang ◽  
Yanjie Zhang ◽  
Xiaozhen Fang ◽  
Lin Wu ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Health Risks ◽  
Meteorological Impact ◽  
Roadside Environment

scholarly journals Spatial Distribution, Source Apportionment, Ozone Formation Potential, and Health Risks of Volatile Organic Compounds over a Typical Central Plain City in China

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1365
Author(s):  
Kun He ◽  
Zhenxing Shen ◽  
Jian Sun ◽  
Yali Lei ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Source Apportionment ◽  
Organic Compounds ◽  
Health Risks ◽  
Urban Areas ◽  
High Time Resolution ◽  
Ozone Formation ◽  
Industrial Site ◽  
Industrial Emissions ◽  
Volatile Organic

The profiles, contributions to ozone formation, and associated health risks of 56 volatile organic compounds (VOCs) species were investigated using high time resolution observations from photochemical assessment monitoring stations (PAMs) in Luoyang, China. The daily averaged concentration of total VOCs (TVOCs) was 21.66 ± 10.34 ppbv in urban areas, 14.45 ± 7.40 ppbv in suburbs, and 37.58 ± 13.99 ppbv in an industrial zone. Overall, the VOCs levels in these nine sites followed a decreasing sequence of alkanes > aromatics > alkenes > alkyne. Diurnal variations in VOCs exhibited two peaks at 8:00–9:00 and 19:00–20:00, with one valley at 23:00–24:00. Source apportionment indicated that vehicle and industrial emissions were the dominant sources of VOCs in urban and suburban sites. The industrial site displayed extreme levels, with contributions from petrochemical-related sources of up to 38.3%. Alkenes and aromatics displayed the highest ozone formation potentials because of their high photochemical reactivity. Cancer and noncancer risks in the industrial site were higher than those in the urban and suburban areas, and USEPA possible risk thresholds were reached in the industrial site, indicating PAMs VOC–related health problems cannot be ignored. Therefore, vehicle and industrial emissions should be prioritized when considering VOCs and O3 control strategies in Luoyang.

Characterization and source apportionment of health risks from ambient PM 10 in Hong Kong over 2000–2011

2015 ◽  
Vol 122 ◽  
pp. 892-899 ◽  
Author(s):  
Zhiyuan Li ◽  
Zibing Yuan ◽  
Ying Li ◽  
Alexis K.H. Lau ◽  
Peter K.K. Louie
Keyword(s):  
Hong Kong ◽  
Source Apportionment ◽  
Health Risks ◽  
Pm 10

scholarly journals Assessment of Pollution and Health Risks of Heavy Metals in Particulate Matter and Road Dust Along the Road Network of Dhanbad, India

2021 ◽  
Vol 11 (29) ◽  
Author(s):  
Shweta Kumari ◽  
Manish Kumar Jain ◽  
Suresh Pandian Elumalai
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
Particulate Matter ◽  
Health Risk ◽  
Human Health ◽  
Source Apportionment ◽  
Health Risks ◽  
Mass Concentration ◽  
Road Dust

Background. The rise in particulate matter (PM) concentrations is a serious problem for the environment. Heavy metals associated with PM10, PM2.5, and road dust adversely affect human health. Different methods have been used to assess heavy metal contamination in PM10, PM2.5, and road dust and source apportionment of these heavy metals. These assessment tools utilize pollution indices and health risk assessment models. Objectives. The present study evaluates the total mass and average concentrations of heavy metals in PM10, PM2.5, and road dust along selected road networks in Dhanbad, India, analyzes the source apportionment of heavy metals, and assesses associated human health risks. Methods. A total of 112 PM samples and 21 road dust samples were collected from six stations and one background site in Dhanbad, India from December 2015 to February 2016, and were analyzed for heavy metals (iron (Fe), lead (Pb), cadmium (Cd), nickel (Ni), copper (Cu), chromium (Cr), and zinc (Zn)) using atomic absorption spectrophotometry. Source apportionment was determined using principal component analysis. A health risk assessment of heavy metal concentrations in PM10, PM2.5, and road dust was also performed. Results. The average mass concentration was found to be 229.54±118.40 μg m−3 for PM10 and 129.73 ±61.74 μg m−3 for PM2.5. The average concentration of heavy metals was found to be higher in PM2.5 than PM10. The pollution load index value of PM10 and PM2.5 road dust was found to be in the deteriorating category. Vehicles were the major source of pollution. The non-carcinogenic effects on children and adults were found to be within acceptable limits. The heavy metals present in PM and road dust posed a health risk in the order of road dust> PM10> and PM2.5. Particulate matter posed higher health risks than road dust due to particle size. Conclusions. The mass concentration analysis indicates serious PM10 and PM2.5 contamination in the study area. Vehicle traffic was the major source of heavy metals in PM10, PM2.5, and road dust. In terms of non-carcinogenic risks posed by heavy metals in the present study, children were more affected than adults. The carcinogenic risk posed by the heavy metals was negligible. Competing Interests. The authors declare no competing financial interests

scholarly journals Source apportionment of atmospheric PM<sub>10</sub> oxidative potential: synthesis of 15 year-round urban datasets in France

2021 ◽  
Vol 21 (14) ◽  
pp. 11353-11378
Author(s):  
Samuël Weber ◽  
Gaëlle Uzu ◽  
Olivier Favez ◽  
Lucille Joanna S. Borlaza ◽  
Aude Calas ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Health Risks ◽  
Biomass Burning ◽  
Large Scale ◽  
Road Traffic ◽  
Urban Traffic ◽  
Redox Activity ◽  
Significant Activity ◽  
Oxidative Potential

Abstract. Reactive oxygen species (ROS) carried or induced by particulate matter (PM) are suspected of inducing oxidative stress in vivo, leading to adverse health impacts such as respiratory or cardiovascular diseases. The oxidative potential (OP) of PM, displaying the ability of PM to oxidize the lung environment, is gaining strong interest in examining health risks associated with PM exposure. In this study, OP was measured by two different acellular assays (dithiothreitol, DTT, and ascorbic acid, AA) on PM10 filter samples from 15 yearly time series of filters collected at 14 different locations in France between 2013 and 2018, including urban, traffic and Alpine valley site typologies. A detailed chemical speciation was also performed on the same samples, allowing the source apportionment of PM using positive matrix factorization (PMF) for each series, for a total number of more than 1700 samples. This study then provides a large-scale synthesis of the source apportionment of OP using coupled PMF and multiple linear regression (MLR) models. The primary road traffic, biomass burning, dust, MSA-rich, and primary biogenic sources had distinct positive redox activity towards the OPDTT assay, whereas biomass burning and road traffic sources only display significant activity for the OPAA assay. The daily median source contribution to the total OPDTT highlighted the dominant influence of the primary road traffic source. Both the biomass burning and the road traffic sources contributed evenly to the observed OPAA. Therefore, it appears clear that residential wood burning and road traffic are the two main target sources to be prioritized in order to decrease significantly the OP in western Europe and, if the OP is a good proxy of human health impact, to lower the health risks from PM exposure.

Black carbon over an urban atmosphere in northern peninsular Southeast Asia: Characteristics, source apportionment, and associated health risks

2020 ◽  
Vol 259 ◽  
pp. 113871 ◽  
Author(s):  
Shantanu Kumar Pani ◽  
Sheng-Hsiang Wang ◽  
Neng-Huei Lin ◽  
Somporn Chantara ◽  
Chung-Te Lee ◽  
...  
Keyword(s):  
Southeast Asia ◽  
Black Carbon ◽  
Source Apportionment ◽  
Health Risks ◽  
Urban Atmosphere

scholarly journals Airborne particles in the Brazilian city of São Paulo: One-year investigation for the chemical composition and source apportionment

2017 ◽  
Author(s):  
Guilherme Martins Pereira ◽  
Kimmo Teinilä ◽  
Danilo Custódio ◽  
Aldenor Gomes Santos ◽  
Huang Xian ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Source Apportionment ◽  
Health Risks ◽  
Biomass Burning ◽  
Sao Paulo ◽  
Airborne Particles ◽  
São Paulo ◽  
Carbonaceous Species ◽  
Local Sources

Abstract. São Paulo in Brazil has relatively relaxed regulations for ambient air pollution standards and often experiences high air pollution levels due to emissions of airborne particles from local sources and long-range transport of biomass burning-impacted air masses. In order to evaluate the sources of particulate air pollution (PM) and related health risks, a year-round sampling was performed for PM2.5 (&amp;leq; 2.5 μm) and PM10 (&amp;leq; 10 μm) in 2014 through intensive (every day sampling in wintertime) and extensive campaigns (once a week for the whole year) with 24 h of sampling. This year was characterized to have lower average precipitation comparing to meteorological data, and high pollution episodes were observed all year round, with a significant increase of pollution level in the intensive campaign, which was performed during wintertime. Different chemical constituents, such as carbonaceous species, polycyclic aromatic hydrocarbons (PAHs) and derivatives, water-soluble ions and biomass burning tracers were identified in order to evaluate health risks and to apportion sources. The species such as PAHs, inorganic and organic ions and monosaccharides were determined by chromatographic techniques and carbonaceous species by thermal-optical analysis. The associated risks to particulate matter exposure based on PAH concentrations were also assessed, along with indexes such as the benzo[a]pyrene equivalent (BaPE) and lung cancer risk (LCR). High BaPE and LCR were observed in most of the samples, rising to critical values in the wintertime. Also, biomass burning tracers and PAHs were higher in this season, while secondarily formed ions presented low variation throughout the year. Meanwhile, vehicular tracer species were also higher in the intensive campaign suggesting the influence of lower dispersion conditions in that period. Source apportionment was done by Positive Matrix Factorization (PMF), which indicated five different factors: road dust, industrial emissions, vehicular exhaust, biomass burning and secondary processes. The results highlighted the contribution of vehicular emissions and the significant input from biomass combustion in wintertime, suggesting that most of the particulate matter is due to local sources, besides the influence of pre-harvest sugarcane burning.

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